Sample records for abnormal neural connectivity

  1. Abnormal Neural Connectivity in Schizophrenia and fMRI-Brain-Computer Interface as a Potential Therapeutic Approach

    PubMed Central

    Ruiz, Sergio; Birbaumer, Niels; Sitaram, Ranganatha

    2012-01-01

    Considering that single locations of structural and functional abnormalities are insufficient to explain the diverse psychopathology of schizophrenia, new models have postulated that the impairments associated with the disease arise from a failure to integrate the activity of local and distributed neural circuits: the “abnormal neural connectivity hypothesis.” In the last years, new evidence coming from neuroimaging have supported and expanded this theory. However, despite the increasing evidence that schizophrenia is a disorder of neural connectivity, so far there are no treatments that have shown to produce a significant change in brain connectivity, or that have been specifically designed to alleviate this problem. Brain-Computer Interfaces based on real-time functional Magnetic Resonance Imaging (fMRI-BCI) are novel techniques that have allowed subjects to achieve self-regulation of circumscribed brain regions. In recent studies, experiments with this technology have resulted in new findings suggesting that this methodology could be used to train subjects to enhance brain connectivity, and therefore could potentially be used as a therapeutic tool in mental disorders including schizophrenia. The present article summarizes the findings coming from hemodynamics-based neuroimaging that support the abnormal connectivity hypothesis in schizophrenia, and discusses a new approach that could address this problem. PMID:23525496

  2. Abnormal functional connectivity during visuospatial processing is associated with disrupted organisation of white matter in autism

    PubMed Central

    McGrath, Jane; Johnson, Katherine; O'Hanlon, Erik; Garavan, Hugh; Leemans, Alexander; Gallagher, Louise

    2013-01-01

    Disruption of structural and functional neural connectivity has been widely reported in Autism Spectrum Disorder (ASD) but there is a striking lack of research attempting to integrate analysis of functional and structural connectivity in the same study population, an approach that may provide key insights into the specific neurobiological underpinnings of altered functional connectivity in autism. The aims of this study were (1) to determine whether functional connectivity abnormalities were associated with structural abnormalities of white matter (WM) in ASD and (2) to examine the relationships between aberrant neural connectivity and behavior in ASD. Twenty-two individuals with ASD and 22 age, IQ-matched controls completed a high-angular-resolution diffusion MRI scan. Structural connectivity was analysed using constrained spherical deconvolution (CSD) based tractography. Regions for tractography were generated from the results of a previous study, in which 10 pairs of brain regions showed abnormal functional connectivity during visuospatial processing in ASD. WM tracts directly connected 5 of the 10 region pairs that showed abnormal functional connectivity; linking a region in the left occipital lobe (left BA19) and five paired regions: left caudate head, left caudate body, left uncus, left thalamus, and left cuneus. Measures of WM microstructural organization were extracted from these tracts. Fractional anisotropy (FA) reductions in the ASD group relative to controls were significant for WM connecting left BA19 to left caudate head and left BA19 to left thalamus. Using a multimodal imaging approach, this study has revealed aberrant WM microstructure in tracts that directly connect brain regions that are abnormally functionally connected in ASD. These results provide novel evidence to suggest that structural brain pathology may contribute (1) to abnormal functional connectivity and (2) to atypical visuospatial processing in ASD. PMID:24133425

  3. Abnormal network connectivity in frontotemporal dementia: evidence for prefrontal isolation.

    PubMed

    Farb, Norman A S; Grady, Cheryl L; Strother, Stephen; Tang-Wai, David F; Masellis, Mario; Black, Sandra; Freedman, Morris; Pollock, Bruce G; Campbell, Karen L; Hasher, Lynn; Chow, Tiffany W

    2013-01-01

    Degraded social function, disinhibition, and stereotypy are defining characteristics of frontotemporal dementia (FTD), manifesting in both the behavioral variant of frontotemporal dementia (bvFTD) and semantic dementia (SD) subtypes. Recent neuroimaging research also associates FTD with alterations in the brain's intrinsic connectivity networks. The present study explored the relationship between neural network connectivity and specific behavioral symptoms in FTD. Resting-state functional magnetic resonance imaging was employed to investigate neural network changes in bvFTD and SD. We used independent components analysis (ICA) to examine changes in frontolimbic network connectivity, as well as several metrics of local network strength, such as the fractional amplitude of low-frequency fluctuations, regional homogeneity, and seed-based functional connectivity. For each analysis, we compared each FTD subgroup to healthy controls, characterizing general and subtype-unique network changes. The relationship between abnormal connectivity in FTD and behavior disturbances was explored. Across multiple analytic approaches, both bvFTD and SD were associated with disrupted frontolimbic connectivity and elevated local connectivity within the prefrontal cortex. Even after controlling for structural atrophy, prefrontal hyperconnectivity was robustly associated with apathy scores. Frontolimbic disconnection was associated with lower disinhibition scores, suggesting that abnormal frontolimbic connectivity contributes to positive symptoms in dementia. Unique to bvFTD, stereotypy was associated with elevated default network connectivity in the right angular gyrus. The behavioral variant was also associated with marginally higher apathy scores and a more diffuse pattern of prefrontal hyperconnectivity than SD. The present findings support a theory of FTD as a disorder of frontolimbic disconnection leading to unconstrained prefrontal connectivity. Prefrontal hyperconnectivity may

  4. Abnormal Neural Progenitor Cells Differentiated from Induced Pluripotent Stem Cells Partially Mimicked Development of TSC2 Neurological Abnormalities.

    PubMed

    Li, Yaqin; Cao, Jiqing; Chen, Menglong; Li, Jing; Sun, Yiming; Zhang, Yu; Zhu, Yuling; Wang, Liang; Zhang, Cheng

    2017-04-11

    Tuberous sclerosis complex (TSC) is a disease featuring devastating and therapeutically challenging neurological abnormalities. However, there is a lack of specific neural progenitor cell models for TSC. Here, the pathology of TSC was studied using primitive neural stem cells (pNSCs) from a patient presenting a c.1444-2A>C mutation in TSC2. We found that TSC2 pNSCs had higher proliferative activity and increased PAX6 expression compared with those of control pNSCs. Neurons differentiated from TSC2 pNSCs showed enlargement of the soma, perturbed neurite outgrowth, and abnormal connections among cells. TSC2 astrocytes had increased saturation density and higher proliferative activity. Moreover, the activity of the mTOR pathway was enhanced in pNSCs and induced in neurons and astrocytes. Thus, our results suggested that TSC2 heterozygosity caused neurological malformations in pNSCs, indicating that its heterozygosity might be sufficient for the development of neurological abnormalities in patients. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

  5. Abnormal resting-state connectivity of motor and cognitive networks in early manifest Huntington's disease.

    PubMed

    Wolf, R C; Sambataro, F; Vasic, N; Depping, M S; Thomann, P A; Landwehrmeyer, G B; Süssmuth, S D; Orth, M

    2014-11-01

    Functional magnetic resonance imaging (fMRI) of multiple neural networks during the brain's 'resting state' could facilitate biomarker development in patients with Huntington's disease (HD) and may provide new insights into the relationship between neural dysfunction and clinical symptoms. To date, however, very few studies have examined the functional integrity of multiple resting state networks (RSNs) in manifest HD, and even less is known about whether concomitant brain atrophy affects neural activity in patients. Using MRI, we investigated brain structure and RSN function in patients with early HD (n = 20) and healthy controls (n = 20). For resting-state fMRI data a group-independent component analysis identified spatiotemporally distinct patterns of motor and prefrontal RSNs of interest. We used voxel-based morphometry to assess regional brain atrophy, and 'biological parametric mapping' analyses to investigate the impact of atrophy on neural activity. Compared with controls, patients showed connectivity changes within distinct neural systems including lateral prefrontal, supplementary motor, thalamic, cingulate, temporal and parietal regions. In patients, supplementary motor area and cingulate cortex connectivity indices were associated with measures of motor function, whereas lateral prefrontal connectivity was associated with cognition. This study provides evidence for aberrant connectivity of RSNs associated with motor function and cognition in early manifest HD when controlling for brain atrophy. This suggests clinically relevant changes of RSN activity in the presence of HD-associated cortical and subcortical structural abnormalities.

  6. Connectivity and functional profiling of abnormal brain structures in pedophilia

    PubMed Central

    Poeppl, Timm B.; Eickhoff, Simon B.; Fox, Peter T.; Laird, Angela R.; Rupprecht, Rainer; Langguth, Berthold; Bzdok, Danilo

    2015-01-01

    Despite its 0.5–1% lifetime prevalence in men and its general societal relevance, neuroimaging investigations in pedophilia are scarce. Preliminary findings indicate abnormal brain structure and function. However, no study has yet linked structural alterations in pedophiles to both connectional and functional properties of the aberrant hotspots. The relationship between morphological alterations and brain function in pedophilia as well as their contribution to its psychopathology thus remain unclear. First, we assessed bimodal connectivity of structurally altered candidate regions using meta-analytic connectivity modeling (MACM) and resting-state correlations employing openly accessible data. We compared the ensuing connectivity maps to the activation likelihood estimation (ALE) maps of a recent quantitative meta-analysis of brain activity during processing of sexual stimuli. Second, we functionally characterized the structurally altered regions employing meta-data of a large-scale neuroimaging database. Candidate regions were functionally connected to key areas for processing of sexual stimuli. Moreover, we found that the functional role of structurally altered brain regions in pedophilia relates to nonsexual emotional as well as neurocognitive and executive functions, previously reported to be impaired in pedophiles. Our results suggest that structural brain alterations affect neural networks for sexual processing by way of disrupted functional connectivity, which may entail abnormal sexual arousal patterns. The findings moreover indicate that structural alterations account for common affective and neurocognitive impairments in pedophilia. The present multi-modal integration of brain structure and function analyses links sexual and nonsexual psychopathology in pedophilia. PMID:25733379

  7. Connectivity and functional profiling of abnormal brain structures in pedophilia.

    PubMed

    Poeppl, Timm B; Eickhoff, Simon B; Fox, Peter T; Laird, Angela R; Rupprecht, Rainer; Langguth, Berthold; Bzdok, Danilo

    2015-06-01

    Despite its 0.5-1% lifetime prevalence in men and its general societal relevance, neuroimaging investigations in pedophilia are scarce. Preliminary findings indicate abnormal brain structure and function. However, no study has yet linked structural alterations in pedophiles to both connectional and functional properties of the aberrant hotspots. The relationship between morphological alterations and brain function in pedophilia as well as their contribution to its psychopathology thus remain unclear. First, we assessed bimodal connectivity of structurally altered candidate regions using meta-analytic connectivity modeling (MACM) and resting-state correlations employing openly accessible data. We compared the ensuing connectivity maps to the activation likelihood estimation (ALE) maps of a recent quantitative meta-analysis of brain activity during processing of sexual stimuli. Second, we functionally characterized the structurally altered regions employing meta-data of a large-scale neuroimaging database. Candidate regions were functionally connected to key areas for processing of sexual stimuli. Moreover, we found that the functional role of structurally altered brain regions in pedophilia relates to nonsexual emotional as well as neurocognitive and executive functions, previously reported to be impaired in pedophiles. Our results suggest that structural brain alterations affect neural networks for sexual processing by way of disrupted functional connectivity, which may entail abnormal sexual arousal patterns. The findings moreover indicate that structural alterations account for common affective and neurocognitive impairments in pedophilia. The present multimodal integration of brain structure and function analyses links sexual and nonsexual psychopathology in pedophilia. © 2015 Wiley Periodicals, Inc.

  8. Rod-Shaped Neural Units for Aligned 3D Neural Network Connection.

    PubMed

    Kato-Negishi, Midori; Onoe, Hiroaki; Ito, Akane; Takeuchi, Shoji

    2017-08-01

    This paper proposes neural tissue units with aligned nerve fibers (called rod-shaped neural units) that connect neural networks with aligned neurons. To make the proposed units, 3D fiber-shaped neural tissues covered with a calcium alginate hydrogel layer are prepared with a microfluidic system and are cut in an accurate and reproducible manner. These units have aligned nerve fibers inside the hydrogel layer and connectable points on both ends. By connecting the units with a poly(dimethylsiloxane) guide, 3D neural tissues can be constructed and maintained for more than two weeks of culture. In addition, neural networks can be formed between the different neural units via synaptic connections. Experimental results indicate that the proposed rod-shaped neural units are effective tools for the construction of spatially complex connections with aligned nerve fibers in vitro. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  9. Abnormal interhemispheric connectivity in male psychopathic offenders.

    PubMed

    Hoppenbrouwers, Sylco S; De Jesus, Danilo R; Sun, Yinming; Stirpe, Tania; Hofman, Dennis; McMaster, Jeff; Hughes, Ginny; Daskalakis, Zafiris J; Schutter, Dennis J L G

    2014-01-01

    Psychopathic offenders inevitably violate interpersonal norms and frequently resort to aggressive and criminal behaviour. The affective and cognitive deficits underlying these behaviours have been linked to abnormalities in functional interhemispheric connectivity. However, direct neurophysiological evidence for dysfunctional connectivity in psychopathic offenders is lacking. We used transcranial magnetic stimulation combined with electroencephalography to examine interhemispheric connectivity in the dorsolateral and motor cortex in a sample of psychopathic offenders and healthy controls. We also measured intracortical inhibition and facilitation over the left and right motor cortex to investigate the effects of local cortical processes on interhemispheric connectivity. We enrolled 17 psychopathic offenders and 14 controls in our study. Global abnormalities in right to left functional connectivity were observed in psychopathic offenders compared with controls. Furthermore, in contrast to controls, psychopathic offenders showed increased intracortical inhibition in the right, but not the left, hemisphere. The relatively small sample size limited the sensitivity to show that the abnormalities in interhemispheric connectivity were specifically related to the dorsolateral prefrontal cortex in psychopathic offenders. To our knowledge, this study provides the first neurophysiological evidence for abnormal interhemispheric connectivity in psychopathic offenders and may further our understanding of the disruptive antisocial behaviour of these offenders.

  10. Abnormal interhemispheric connectivity in male psychopathic offenders

    PubMed Central

    Hoppenbrouwers, Sylco S.; De Jesus, Danilo R.; Sun, Yinming; Stirpe, Tania; Hofman, Dennis; McMaster, Jeff; Hughes, Ginny; Daskalakis, Zafiris J.; Schutter, Dennis J.L.G.

    2014-01-01

    Background Psychopathic offenders inevitably violate interpersonal norms and frequently resort to aggressive and criminal behaviour. The affective and cognitive deficits underlying these behaviours have been linked to abnormalities in functional interhemispheric connectivity. However, direct neurophysiological evidence for dysfunctional connectivity in psychopathic offenders is lacking. Methods We used transcranial magnetic stimulation combined with electroencephalography to examine interhemispheric connectivity in the dorsolateral and motor cortex in a sample of psychopathic offenders and healthy controls. We also measured intracortical inhibition and facilitation over the left and right motor cortex to investigate the effects of local cortical processes on interhemispheric connectivity. Results We enrolled 17 psychopathic offenders and 14 controls in our study. Global abnormalities in right to left functional connectivity were observed in psychopathic offenders compared with controls. Furthermore, in contrast to controls, psychopathic offenders showed increased intracortical inhibition in the right, but not the left, hemisphere. Limitations The relatively small sample size limited the sensitivity to show that the abnormalities in interhemispheric connectivity were specifically related to the dorsolateral prefrontal cortex in psychopathic offenders. Conclusion To our knowledge, this study provides the first neurophysiological evidence for abnormal interhemispheric connectivity in psychopathic offenders and may further our understanding of the disruptive antisocial behaviour of these offenders. PMID:23937798

  11. Detection of Structural Abnormalities Using Neural Nets

    NASA Technical Reports Server (NTRS)

    Zak, M.; Maccalla, A.; Daggumati, V.; Gulati, S.; Toomarian, N.

    1996-01-01

    This paper describes a feed-forward neural net approach for detection of abnormal system behavior based upon sensor data analyses. A new dynamical invariant representing structural parameters of the system is introduced in such a way that any structural abnormalities in the system behavior are detected from the corresponding changes to the invariant.

  12. Weakly connected neural nets

    NASA Technical Reports Server (NTRS)

    Zak, Michail

    1990-01-01

    A new neural network architecture is proposed based upon effects of non-Lipschitzian dynamics. The network is fully connected, but these connections are active only during vanishingly short time periods. The advantages of this architecture are discussed.

  13. Altered Immune Function Associated with Disordered Neural Connectivity and Executive Dysfunctions: A Neurophysiological Study on Children with Autism Spectrum Disorders

    ERIC Educational Resources Information Center

    Han, Yvonne M. Y.; Chan, Agnes S.; Sze, Sophia L.; Cheung, Mei-Chun; Wong, Chun-kwok; Lam, Joseph M. K.; Poon, Priscilla M. K.

    2013-01-01

    Previous studies have shown that children with autism spectrum disorders (ASDs) have impaired executive function, disordered neural connectivity, and abnormal immunologic function. The present study examined whether these abnormalities were associated. Seventeen high-functioning (HFA) and 17 low-functioning (LFA) children with ASD, aged 8-17…

  14. Artificial Neural Network for the Prediction of Chromosomal Abnormalities in Azoospermic Males.

    PubMed

    Akinsal, Emre Can; Haznedar, Bulent; Baydilli, Numan; Kalinli, Adem; Ozturk, Ahmet; Ekmekçioğlu, Oğuz

    2018-02-04

    To evaluate whether an artifical neural network helps to diagnose any chromosomal abnormalities in azoospermic males. The data of azoospermic males attending to a tertiary academic referral center were evaluated retrospectively. Height, total testicular volume, follicle stimulating hormone, luteinising hormone, total testosterone and ejaculate volume of the patients were used for the analyses. In artificial neural network, the data of 310 azoospermics were used as the education and 115 as the test set. Logistic regression analyses and discriminant analyses were performed for statistical analyses. The tests were re-analysed with a neural network. Both logistic regression analyses and artificial neural network predicted the presence or absence of chromosomal abnormalities with more than 95% accuracy. The use of artificial neural network model has yielded satisfactory results in terms of distinguishing patients whether they have any chromosomal abnormality or not.

  15. Tcof1/Treacle is required for neural crest cell formation and proliferation deficiencies that cause craniofacial abnormalities

    PubMed Central

    Dixon, Jill; Jones, Natalie C.; Sandell, Lisa L.; Jayasinghe, Sachintha M.; Crane, Jennifer; Rey, Jean-Philippe; Dixon, Michael J.; Trainor, Paul A.

    2006-01-01

    Neural crest cells are a migratory cell population that give rise to the majority of the cartilage, bone, connective tissue, and sensory ganglia in the head. Abnormalities in the formation, proliferation, migration, and differentiation phases of the neural crest cell life cycle can lead to craniofacial malformations, which constitute one-third of all congenital birth defects. Treacher Collins syndrome (TCS) is characterized by hypoplasia of the facial bones, cleft palate, and middle and external ear defects. Although TCS results from autosomal dominant mutations of the gene TCOF1, the mechanistic origins of the abnormalities observed in this condition are unknown, and the function of Treacle, the protein encoded by TCOF1, remains poorly understood. To investigate the developmental basis of TCS we generated a mouse model through germ-line mutation of Tcof1. Haploinsufficiency of Tcof1 leads to a deficiency in migrating neural crest cells, which results in severe craniofacial malformations. We demonstrate that Tcof1/Treacle is required cell-autonomously for the formation and proliferation of neural crest cells. Tcof1/Treacle regulates proliferation by controlling the production of mature ribosomes. Therefore, Tcof1/Treacle is a unique spatiotemporal regulator of ribosome biogenesis, a deficiency that disrupts neural crest cell formation and proliferation, causing the hypoplasia characteristic of TCS craniofacial anomalies. PMID:16938878

  16. Tcof1/Treacle is required for neural crest cell formation and proliferation deficiencies that cause craniofacial abnormalities.

    PubMed

    Dixon, Jill; Jones, Natalie C; Sandell, Lisa L; Jayasinghe, Sachintha M; Crane, Jennifer; Rey, Jean-Philippe; Dixon, Michael J; Trainor, Paul A

    2006-09-05

    Neural crest cells are a migratory cell population that give rise to the majority of the cartilage, bone, connective tissue, and sensory ganglia in the head. Abnormalities in the formation, proliferation, migration, and differentiation phases of the neural crest cell life cycle can lead to craniofacial malformations, which constitute one-third of all congenital birth defects. Treacher Collins syndrome (TCS) is characterized by hypoplasia of the facial bones, cleft palate, and middle and external ear defects. Although TCS results from autosomal dominant mutations of the gene TCOF1, the mechanistic origins of the abnormalities observed in this condition are unknown, and the function of Treacle, the protein encoded by TCOF1, remains poorly understood. To investigate the developmental basis of TCS we generated a mouse model through germ-line mutation of Tcof1. Haploinsufficiency of Tcof1 leads to a deficiency in migrating neural crest cells, which results in severe craniofacial malformations. We demonstrate that Tcof1/Treacle is required cell-autonomously for the formation and proliferation of neural crest cells. Tcof1/Treacle regulates proliferation by controlling the production of mature ribosomes. Therefore, Tcof1/Treacle is a unique spatiotemporal regulator of ribosome biogenesis, a deficiency that disrupts neural crest cell formation and proliferation, causing the hypoplasia characteristic of TCS craniofacial anomalies.

  17. Neural mechanisms of oculomotor abnormalities in the infantile strabismus syndrome.

    PubMed

    Walton, Mark M G; Pallus, Adam; Fleuriet, Jérome; Mustari, Michael J; Tarczy-Hornoch, Kristina

    2017-07-01

    Infantile strabismus is characterized by numerous visual and oculomotor abnormalities. Recently nonhuman primate models of infantile strabismus have been established, with characteristics that closely match those observed in human patients. This has made it possible to study the neural basis for visual and oculomotor symptoms in infantile strabismus. In this review, we consider the available evidence for neural abnormalities in structures related to oculomotor pathways ranging from visual cortex to oculomotor nuclei. These studies provide compelling evidence that a disturbance of binocular vision during a sensitive period early in life, whatever the cause, results in a cascade of abnormalities through numerous brain areas involved in visual functions and eye movements. Copyright © 2017 the American Physiological Society.

  18. Connecting Teratogen-Induced Congenital Heart Defects to Neural Crest Cells and Their Effect on Cardiac Function

    PubMed Central

    Karunamuni, Ganga H.; Ma, Pei; Gu, Shi; Rollins, Andrew M.; Jenkins, Michael W.; Watanabe, Michiko

    2014-01-01

    Neural crest cells play many key roles in embryonic development, as demonstrated by the abnormalities that result from their specific absence or dysfunction. Unfortunately, these key cells are particularly sensitive to abnormalities in various intrinsic and extrinsic factors, such as genetic deletions or ethanol-exposure that lead to morbidity and mortality for organisms. This review discusses the role identified for a segment of neural crest is in regulating the morphogenesis of the heart and associated great vessels. The paradox is that their derivatives constitute a small proportion of cells to the cardiovascular system. Findings supporting that these cells impact early cardiac function raises the interesting possibility that they indirectly control cardiovascular development at least partially through regulating function. Making connections between insults to the neural crest, cardiac function, and morphogenesis is more approachable with technological advances. Expanding our understanding of early functional consequences could be useful in improving diagnosis and testing therapies. PMID:25220155

  19. Abnormal functional network connectivity among resting-state networks in children with frontal lobe epilepsy.

    PubMed

    Widjaja, E; Zamyadi, M; Raybaud, C; Snead, O C; Smith, M L

    2013-12-01

    Epilepsy is considered a disorder of neural networks. The aims of this study were to assess functional connectivity within resting-state networks and functional network connectivity across resting-state networks by use of resting-state fMRI in children with frontal lobe epilepsy and to relate changes in resting-state networks with neuropsychological function. Fifteen patients with frontal lobe epilepsy and normal MR imaging and 14 healthy control subjects were recruited. Spatial independent component analysis was used to identify the resting-state networks, including frontal, attention, default mode network, sensorimotor, visual, and auditory networks. The Z-maps of resting-state networks were compared between patients and control subjects. The relation between abnormal connectivity and neuropsychological function was assessed. Correlations from all pair-wise combinations of independent components were performed for each group and compared between groups. The frontal network was the only network that showed reduced connectivity in patients relative to control subjects. The remaining 5 networks demonstrated both reduced and increased functional connectivity within resting-state networks in patients. There was a weak association between connectivity in frontal network and executive function (P = .029) and a significant association between sensorimotor network and fine motor function (P = .004). Control subjects had 79 pair-wise independent components that showed significant temporal coherence across all resting-state networks except for default mode network-auditory network. Patients had 66 pairs of independent components that showed significant temporal coherence across all resting-state networks. Group comparison showed reduced functional network connectivity between default mode network-attention, frontal-sensorimotor, and frontal-visual networks and increased functional network connectivity between frontal-attention, default mode network-sensorimotor, and frontal

  20. Neural Connectivity Evidence for a Categorical-Dimensional Hybrid Model of Autism Spectrum Disorder.

    PubMed

    Elton, Amanda; Di Martino, Adriana; Hazlett, Heather Cody; Gao, Wei

    2016-07-15

    Autism spectrum disorder (ASD) encompasses a complex manifestation of symptoms that include deficits in social interaction and repetitive or stereotyped interests and behaviors. In keeping with the increasing recognition of the dimensional characteristics of ASD symptoms and the categorical nature of a diagnosis, we sought to delineate the neural mechanisms of ASD symptoms based on the functional connectivity of four known neural networks (i.e., default mode network, dorsal attention network, salience network, and executive control network). We leveraged an open data resource (Autism Brain Imaging Data Exchange) providing resting-state functional magnetic resonance imaging data sets from 90 boys with ASD and 95 typically developing boys. This data set also included the Social Responsiveness Scale as a dimensional measure of ASD traits. Seed-based functional connectivity was paired with linear regression to identify functional connectivity abnormalities associated with categorical effects of ASD diagnosis, dimensional effects of ASD-like behaviors, and their interaction. Our results revealed the existence of dimensional mechanisms of ASD uniquely affecting each network based on the presence of connectivity-behavioral relationships; these were independent of diagnostic category. However, we also found evidence of categorical differences (i.e., diagnostic group differences) in connectivity strength for each network as well as categorical differences in connectivity-behavioral relationships (i.e., diagnosis-by-behavior interactions), supporting the coexistence of categorical mechanisms of ASD. Our findings support a hybrid model for ASD characterization that includes a combination of categorical and dimensional brain mechanisms and provide a novel understanding of the neural underpinnings of ASD. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  1. Impulsive-antisocial dimension of psychopathy linked to enlargement and abnormal functional connectivity of the striatum.

    PubMed

    Korponay, Cole; Pujara, Maia; Deming, Philip; Philippi, Carissa; Decety, Jean; Kosson, David S; Kiehl, Kent A; Koenigs, Michael

    2017-03-01

    Psychopathy is a mental health disorder characterized by callous and impulsive antisocial behavior, and is associated with a high incidence of violent crime, substance abuse, and recidivism. Recent studies suggest that the striatum may be a key component of the neurobiological basis for the disorder, though structural findings have been mixed and functional connectivity of the striatum in psychopathy has yet to be fully examined. We performed a multimodal neuroimaging study of striatum volume and functional connectivity in psychopathy, using a large sample of adult male prison inmates ( N =124). We conducted volumetric analyses in striatal subnuclei, and subsequently assessed resting-state functional connectivity in areas where volume was related to psychopathy severity. Total PCL-R and Factor 2 scores (which index the impulsive/antisocial traits of psychopathy) were associated with larger striatal subnuclei volumes and increased volume in focal areas throughout the striatum, particularly in the nucleus accumbens and putamen bilaterally. Furthermore, at many of the striatal areas where volume was positively associated with Factor 2 scores, psychopathy severity was also associated with abnormal functional connectivity with other brain regions, including dorsolateral prefrontal cortex, ventral midbrain and other areas of the striatum. The results were not attributable to age, race, IQ, substance use history, or intracranial volume. These findings associate the impulsive/antisocial dimension of psychopathy with enlarged striatal subnuclei and aberrant functional connectivity between the striatum and other brain regions. Furthermore, the co-localization of volumetric and functional connectivity findings suggests that these neural abnormalities may be pathophysiologically linked.

  2. Impulsive-antisocial dimension of psychopathy linked to enlargement and abnormal functional connectivity of the striatum

    PubMed Central

    Korponay, Cole; Pujara, Maia; Deming, Philip; Philippi, Carissa; Decety, Jean; Kosson, David S.; Kiehl, Kent A.; Koenigs, Michael

    2016-01-01

    Background Psychopathy is a mental health disorder characterized by callous and impulsive antisocial behavior, and is associated with a high incidence of violent crime, substance abuse, and recidivism. Recent studies suggest that the striatum may be a key component of the neurobiological basis for the disorder, though structural findings have been mixed and functional connectivity of the striatum in psychopathy has yet to be fully examined. Methods We performed a multimodal neuroimaging study of striatum volume and functional connectivity in psychopathy, using a large sample of adult male prison inmates (N=124). We conducted volumetric analyses in striatal subnuclei, and subsequently assessed resting-state functional connectivity in areas where volume was related to psychopathy severity. Results Total PCL-R and Factor 2 scores (which index the impulsive/antisocial traits of psychopathy) were associated with larger striatal subnuclei volumes and increased volume in focal areas throughout the striatum, particularly in the nucleus accumbens and putamen bilaterally. Furthermore, at many of the striatal areas where volume was positively associated with Factor 2 scores, psychopathy severity was also associated with abnormal functional connectivity with other brain regions, including dorsolateral prefrontal cortex, ventral midbrain and other areas of the striatum. The results were not attributable to age, race, IQ, substance use history, or intracranial volume. Conclusion These findings associate the impulsive/antisocial dimension of psychopathy with enlarged striatal subnuclei and aberrant functional connectivity between the striatum and other brain regions. Furthermore, the co-localization of volumetric and functional connectivity findings suggests that these neural abnormalities may be pathophysiologically linked. PMID:28367514

  3. 5-Mehtyltetrahydrofolate rescues alcohol-induced neural crest cell migration abnormalities.

    PubMed

    Shi, Yu; Li, Jiejing; Chen, Chunjiang; Gong, Manzi; Chen, Yuan; Liu, Youxue; Chen, Jie; Li, Tingyu; Song, Weihong

    2014-09-16

    Alcohol is detrimental to early development. Fetal alcohol spectrum disorders (FASD) due to maternal alcohol abuse results in a series of developmental abnormalities including cranial facial dysmorphology, ocular anomalies, congenital heart defects, microcephaly and intellectual disabilities. Previous studies have been shown that ethanol exposure causes neural crest (NC) apoptosis and perturbation of neural crest migration. However, the underlying mechanism remains elusive. In this report we investigated the fetal effect of alcohol on the process of neural crest development in the Xenopus leavis. Pre-gastrulation exposure of 2-4% alcohol induces apoptosis in Xenopus embryo whereas 1% alcohol specifically impairs neural crest migration without observing discernible apoptosis. Additionally, 1% alcohol treatment considerably increased the phenotype of small head (43.4% ± 4.4%, total embryo n = 234), and 1.5% and 2.0% dramatically augment the deformation to 81.2% ± 6.5% (n = 205) and 91.6% ± 3.0% (n = 235), respectively (P < 0.05). Significant accumulation of Homocysteine was caused by alcohol treatment in embryos and 5-mehtyltetrahydrofolate restores neural crest migration and alleviates homocysteine accumulation, resulting in inhibition of the alcohol-induced neurocristopathies. Our study demonstrates that prenatal alcohol exposure causes neural crest cell migration abnormality and 5-mehtyltetrahydrofolate could be beneficial for treating FASD.

  4. Classification of breast abnormalities using artificial neural network

    NASA Astrophysics Data System (ADS)

    Zaman, Nur Atiqah Kamarul; Rahman, Wan Eny Zarina Wan Abdul; Jumaat, Abdul Kadir; Yasiran, Siti Salmah

    2015-05-01

    Classification is the process of recognition, differentiation and categorizing objects into groups. Breast abnormalities are calcifications which are tumor markers that indicate the presence of cancer in the breast. The aims of this research are to classify the types of breast abnormalities using artificial neural network (ANN) classifier and to evaluate the accuracy performance using receiver operating characteristics (ROC) curve. The methods used in this research are ANN for breast abnormalities classifications and Canny edge detector as a feature extraction method. Previously the ANN classifier provides only the number of benign and malignant cases without providing information for specific cases. However in this research, the type of abnormality for each image can be obtained. The existing MIAS MiniMammographic database classified the mammogram images into three features only namely characteristic of background tissues, class of abnormality and radius of abnormality. However, in this research three other features are added-in. These three features are number of spots, area and shape of abnormalities. Lastly the performance of the ANN classifier is evaluated using ROC curve. It is found that ANN has an accuracy of 97.9% which is considered acceptable.

  5. Abnormal Neural Network of Primary Insomnia: Evidence from Spatial Working Memory Task fMRI.

    PubMed

    Li, Yongli; Liu, Liya; Wang, Enfeng; Zhang, Hongju; Dou, Shewei; Tong, Li; Cheng, Jingliang; Chen, Chuanliang; Shi, Dapeng

    2016-01-01

    Contemporary functional MRI (fMRI) methods can provide a wealth of information about the neural mechanisms associated with primary insomnia (PI), which centrally involve neural network circuits related to spatial working memory. A total of 30 participants diagnosed with PI and without atypical brain anatomy were selected along with 30 age- and gender-matched healthy controls. Subjects were administered the Pittsburgh Sleep Quality Index (PSQI), Hamilton Rating Scale for Depression and clinical assessments of spatial working memory, followed by an MRI scan and fMRI in spatial memory task state. Statistically significant differences between PSQI and spatial working memory were observed between PI patients and controls (p < 0.01). Activation of neural networks related to spatial memory task state in the PI group was observed at the left temporal lobe, left occipital lobe and right frontal lobe. Lower levels of activation were observed in the left parahippocampal gyrus, right parahippocampal gyrus, bilateral temporal cortex, frontal cortex and superior parietal lobule. Participants with PI exhibited characteristic abnormalities in the neural network connectivity related to spatial working memory. These results may be indicative of an underlying pathological mechanism related to spatial working memory deterioration in PI, analogous to recently described mechanisms in other mental health disorders. © 2016 S. Karger AG, Basel.

  6. Neural correlates of abnormal sensory discrimination in laryngeal dystonia.

    PubMed

    Termsarasab, Pichet; Ramdhani, Ritesh A; Battistella, Giovanni; Rubien-Thomas, Estee; Choy, Melissa; Farwell, Ian M; Velickovic, Miodrag; Blitzer, Andrew; Frucht, Steven J; Reilly, Richard B; Hutchinson, Michael; Ozelius, Laurie J; Simonyan, Kristina

    2016-01-01

    Aberrant sensory processing plays a fundamental role in the pathophysiology of dystonia; however, its underpinning neural mechanisms in relation to dystonia phenotype and genotype remain unclear. We examined temporal and spatial discrimination thresholds in patients with isolated laryngeal form of dystonia (LD), who exhibited different clinical phenotypes (adductor vs. abductor forms) and potentially different genotypes (sporadic vs. familial forms). We correlated our behavioral findings with the brain gray matter volume and functional activity during resting and symptomatic speech production. We found that temporal but not spatial discrimination was significantly altered across all forms of LD, with higher frequency of abnormalities seen in familial than sporadic patients. Common neural correlates of abnormal temporal discrimination across all forms were found with structural and functional changes in the middle frontal and primary somatosensory cortices. In addition, patients with familial LD had greater cerebellar involvement in processing of altered temporal discrimination, whereas sporadic LD patients had greater recruitment of the putamen and sensorimotor cortex. Based on the clinical phenotype, adductor form-specific correlations between abnormal discrimination and brain changes were found in the frontal cortex, whereas abductor form-specific correlations were observed in the cerebellum and putamen. Our behavioral and neuroimaging findings outline the relationship of abnormal sensory discrimination with the phenotype and genotype of isolated LD, suggesting the presence of potentially divergent pathophysiological pathways underlying different manifestations of this disorder.

  7. Abnormal prefrontal cortex resting state functional connectivity and severity of internet gaming disorder.

    PubMed

    Jin, Chenwang; Zhang, Ting; Cai, Chenxi; Bi, Yanzhi; Li, Yangding; Yu, Dahua; Zhang, Ming; Yuan, Kai

    2016-09-01

    Internet Gaming Disorder (IGD) among adolescents has become an important public concern and gained more and more attention internationally. Recent studies focused on IGD and revealed brain abnormalities in the IGD group, especially the prefrontal cortex (PFC). However, the role of PFC-striatal circuits in pathology of IGD remains unknown. Twenty-five adolescents with IGD and 21 age- and gender-matched healthy controls were recruited in our study. Voxel-based morphometric (VBM) and functional connectivity analysis were employed to investigate the abnormal structural and resting-state properties of several frontal regions in individuals with online gaming addiction. Relative to healthy comparison subjects, IGD subjects showed significant decreased gray matter volume in PFC regions including the bilateral dorsolateral prefrontal cortex (DLPFC), orbitofrontal cortex (OFC), anterior cingulate cortex (ACC) and the right supplementary motor area (SMA) after controlling for age and gender effects. We chose these regions as the seeding areas for the resting-state analysis and found that IGD subjects showed decreased functional connectivity between several cortical regions and our seeds, including the insula, and temporal and occipital cortices. Moreover, significant decreased functional connectivity between some important subcortical regions, i.e., dorsal striatum, pallidum, and thalamus, and our seeds were found in the IGD group and some of those changes were associated with the severity of IGD. Our results revealed the involvement of several PFC regions and related PFC-striatal circuits in the process of IGD and suggested IGD may share similar neural mechanisms with substance dependence at the circuit level.

  8. Polygenic risk for five psychiatric disorders and cross-disorder and disorder-specific neural connectivity in two independent populations.

    PubMed

    Wang, Tianqi; Zhang, Xiaolong; Li, Ang; Zhu, Meifang; Liu, Shu; Qin, Wen; Li, Jin; Yu, Chunshui; Jiang, Tianzi; Liu, Bing

    2017-01-01

    Major psychiatric disorders, including attention deficit hyperactivity disorder (ADHD), autism (AUT), bipolar disorder (BD), major depressive disorder (MDD), and schizophrenia (SZ), are highly heritable and polygenic. Evidence suggests that these five disorders have both shared and distinct genetic risks and neural connectivity abnormalities. To measure aggregate genetic risks, the polygenic risk score (PGRS) was computed. Two independent general populations (N = 360 and N = 323) were separately examined to investigate whether the cross-disorder PGRS and PGRS for a specific disorder were associated with individual variability in functional connectivity. Consistent altered functional connectivity was found with the bilateral insula: for the left supplementary motor area and the left superior temporal gyrus with the cross-disorder PGRS, for the left insula and right middle and superior temporal lobe associated with the PGRS for autism, for the bilateral midbrain, posterior cingulate, cuneus, and precuneus associated with the PGRS for BD, and for the left angular gyrus and the left dorsolateral prefrontal cortex associated with the PGRS for schizophrenia. No significant functional connectivity was found associated with the PGRS for ADHD and MDD. Our findings indicated that genetic effects on the cross-disorder and disorder-specific neural connectivity of common genetic risk loci are detectable in the general population. Our findings also indicated that polygenic risk contributes to the main neurobiological phenotypes of psychiatric disorders and that identifying cross-disorder and specific functional connectivity related to polygenic risks may elucidate the neural pathways for these disorders.

  9. Abnormal neural activities of directional brain networks in patients with long-term bilateral hearing loss.

    PubMed

    Xu, Long-Chun; Zhang, Gang; Zou, Yue; Zhang, Min-Feng; Zhang, Dong-Sheng; Ma, Hua; Zhao, Wen-Bo; Zhang, Guang-Yu

    2017-10-13

    The objective of the study is to provide some implications for rehabilitation of hearing impairment by investigating changes of neural activities of directional brain networks in patients with long-term bilateral hearing loss. Firstly, we implemented neuropsychological tests of 21 subjects (11 patients with long-term bilateral hearing loss, and 10 subjects with normal hearing), and these tests revealed significant differences between the deaf group and the controls. Then we constructed the individual specific virtual brain based on functional magnetic resonance data of participants by utilizing effective connectivity and multivariate regression methods. We exerted the stimulating signal to the primary auditory cortices of the virtual brain and observed the brain region activations. We found that patients with long-term bilateral hearing loss presented weaker brain region activations in the auditory and language networks, but enhanced neural activities in the default mode network as compared with normally hearing subjects. Especially, the right cerebral hemisphere presented more changes than the left. Additionally, weaker neural activities in the primary auditor cortices were also strongly associated with poorer cognitive performance. Finally, causal analysis revealed several interactional circuits among activated brain regions, and these interregional causal interactions implied that abnormal neural activities of the directional brain networks in the deaf patients impacted cognitive function.

  10. Connective tissue spectrum abnormalities associated with spontaneous cerebrospinal fluid leaks: a prospective study.

    PubMed

    Reinstein, Eyal; Pariani, Mitchel; Bannykh, Serguei; Rimoin, David L; Schievink, Wouter I

    2013-04-01

    We aimed to assess the frequency of connective tissue abnormalities among patients with cerebrospinal fluid (CSF) leaks in a prospective study using a large cohort of patients. We enrolled a consecutive group of 50 patients, referred for consultation because of CSF leak. All patients have been carefully examined for the presence of connective tissue abnormalities, and based on findings, patients underwent genetic testing. Ancillary diagnostic studies included echocardiography, eye exam, and histopathological examinations of skin and dura biopsies in selected patients. We identified nine patients with heritable connective tissue disorders, including Marfan syndrome, Ehlers-Danlos syndrome and other unclassified forms. In seven patients, spontaneous CSF leak was the first noted manifestation of the genetic disorder. We conclude that spontaneous CSF leaks are associated with a spectrum of connective tissue abnormalities and may be the first noted clinical presentation of the genetic disorder. We propose that there is a clinical basis for considering spontaneous CSF leak as a clinical manifestation of heritable connective tissue disorders, and we suggest that patients with CSF leaks should be screened for connective tissue and vascular abnormalities.

  11. Attractor neural networks with resource-efficient synaptic connectivity

    NASA Astrophysics Data System (ADS)

    Pehlevan, Cengiz; Sengupta, Anirvan

    Memories are thought to be stored in the attractor states of recurrent neural networks. Here we explore how resource constraints interplay with memory storage function to shape synaptic connectivity of attractor networks. We propose that given a set of memories, in the form of population activity patterns, the neural circuit choses a synaptic connectivity configuration that minimizes a resource usage cost. We argue that the total synaptic weight (l1-norm) in the network measures the resource cost because synaptic weight is correlated with synaptic volume, which is a limited resource, and is proportional to neurotransmitter release and post-synaptic current, both of which cost energy. Using numerical simulations and replica theory, we characterize optimal connectivity profiles in resource-efficient attractor networks. Our theory explains several experimental observations on cortical connectivity profiles, 1) connectivity is sparse, because synapses are costly, 2) bidirectional connections are overrepresented and 3) are stronger, because attractor states need strong recurrence.

  12. Abnormal Amygdalar Activation and Connectivity in Adolescents With Attention-Deficit/Hyperactivity Disorder

    PubMed Central

    Posner, Jonathan; Nagel, Bonnie J.; Maia, Tiago V.; Mechling, Anna; Oh, Milim; Wang, Zhishun; Peterson, Bradley S.

    2011-01-01

    Objective Emotional reactivity is one of the most disabling symptoms associated with ADHD. We aimed to identify neural substrates associated with emotional reactivity and assess the effects of stimulants on those substrates. Method We used functional magnetic resonance imaging (fMRI) to assess neural activity in adolescents with (N=15) and without (N=15) ADHD while they performed a task involving the subliminal presentation of fearful faces. Using dynamic causal modeling, we also examined the effective connectivity of two regions associated with emotional reactivity — the amygdala and the lateral prefrontal cortex (LPFC). The participants with ADHD were scanned both on and off stimulant medication in a counterbalanced fashion. Results During the task, we found that activity in the right amygdala was greater in adolescents with ADHD than in controls. Additionally, in adolescents with ADHD, greater connectivity was detected between the amygdala and LPFC. Stimulants had a normalizing effect on both the activity in the right amygdala and the connectivity between the amygdala and LPFC. Conclusions Our findings demonstrate that in adolescents with ADHD, a neural substrate of fear processing is atypical, as is the connectivity between the amygdala and LPFC. These findings suggest possible neural substrates for the emotional reactivity that is often present in youths with ADHD and provide putative neural targets for the development of novel therapeutic interventions for this condition. PMID:21784302

  13. Computational neuroanatomy: ontology-based representation of neural components and connectivity

    PubMed Central

    Rubin, Daniel L; Talos, Ion-Florin; Halle, Michael; Musen, Mark A; Kikinis, Ron

    2009-01-01

    Background A critical challenge in neuroscience is organizing, managing, and accessing the explosion in neuroscientific knowledge, particularly anatomic knowledge. We believe that explicit knowledge-based approaches to make neuroscientific knowledge computationally accessible will be helpful in tackling this challenge and will enable a variety of applications exploiting this knowledge, such as surgical planning. Results We developed ontology-based models of neuroanatomy to enable symbolic lookup, logical inference and mathematical modeling of neural systems. We built a prototype model of the motor system that integrates descriptive anatomic and qualitative functional neuroanatomical knowledge. In addition to modeling normal neuroanatomy, our approach provides an explicit representation of abnormal neural connectivity in disease states, such as common movement disorders. The ontology-based representation encodes both structural and functional aspects of neuroanatomy. The ontology-based models can be evaluated computationally, enabling development of automated computer reasoning applications. Conclusion Neuroanatomical knowledge can be represented in machine-accessible format using ontologies. Computational neuroanatomical approaches such as described in this work could become a key tool in translational informatics, leading to decision support applications that inform and guide surgical planning and personalized care for neurological disease in the future. PMID:19208191

  14. Computational neuroanatomy: ontology-based representation of neural components and connectivity.

    PubMed

    Rubin, Daniel L; Talos, Ion-Florin; Halle, Michael; Musen, Mark A; Kikinis, Ron

    2009-02-05

    A critical challenge in neuroscience is organizing, managing, and accessing the explosion in neuroscientific knowledge, particularly anatomic knowledge. We believe that explicit knowledge-based approaches to make neuroscientific knowledge computationally accessible will be helpful in tackling this challenge and will enable a variety of applications exploiting this knowledge, such as surgical planning. We developed ontology-based models of neuroanatomy to enable symbolic lookup, logical inference and mathematical modeling of neural systems. We built a prototype model of the motor system that integrates descriptive anatomic and qualitative functional neuroanatomical knowledge. In addition to modeling normal neuroanatomy, our approach provides an explicit representation of abnormal neural connectivity in disease states, such as common movement disorders. The ontology-based representation encodes both structural and functional aspects of neuroanatomy. The ontology-based models can be evaluated computationally, enabling development of automated computer reasoning applications. Neuroanatomical knowledge can be represented in machine-accessible format using ontologies. Computational neuroanatomical approaches such as described in this work could become a key tool in translational informatics, leading to decision support applications that inform and guide surgical planning and personalized care for neurological disease in the future.

  15. Knowledge Synthesis with Maps of Neural Connectivity

    PubMed Central

    Tallis, Marcelo; Thompson, Richard; Russ, Thomas A.; Burns, Gully A. P. C.

    2011-01-01

    This paper describes software for neuroanatomical knowledge synthesis based on neural connectivity data. This software supports a mature methodology developed since the early 1990s. Over this time, the Swanson laboratory at USC has generated an account of the neural connectivity of the sub-structures of the hypothalamus, amygdala, septum, hippocampus, and bed nucleus of the stria terminalis. This is based on neuroanatomical data maps drawn into a standard brain atlas by experts. In earlier work, we presented an application for visualizing and comparing anatomical macro connections using the Swanson third edition atlas as a framework for accurate registration. Here we describe major improvements to the NeuARt application based on the incorporation of a knowledge representation of experimental design. We also present improvements in the interface and features of the data mapping components within a unified web-application. As a step toward developing an accurate sub-regional account of neural connectivity, we provide navigational access between the data maps and a semantic representation of area-to-area connections that they support. We do so based on an approach called “Knowledge Engineering from Experimental Design” (KEfED) model that is based on experimental variables. We have extended the underlying KEfED representation of tract-tracing experiments by incorporating the definition of a neuronanatomical data map as a measurement variable in the study design. This paper describes the software design of a web-application that allows anatomical data sets to be described within a standard experimental context and thus indexed by non-spatial experimental design features. PMID:22053155

  16. Knowledge synthesis with maps of neural connectivity.

    PubMed

    Tallis, Marcelo; Thompson, Richard; Russ, Thomas A; Burns, Gully A P C

    2011-01-01

    This paper describes software for neuroanatomical knowledge synthesis based on neural connectivity data. This software supports a mature methodology developed since the early 1990s. Over this time, the Swanson laboratory at USC has generated an account of the neural connectivity of the sub-structures of the hypothalamus, amygdala, septum, hippocampus, and bed nucleus of the stria terminalis. This is based on neuroanatomical data maps drawn into a standard brain atlas by experts. In earlier work, we presented an application for visualizing and comparing anatomical macro connections using the Swanson third edition atlas as a framework for accurate registration. Here we describe major improvements to the NeuARt application based on the incorporation of a knowledge representation of experimental design. We also present improvements in the interface and features of the data mapping components within a unified web-application. As a step toward developing an accurate sub-regional account of neural connectivity, we provide navigational access between the data maps and a semantic representation of area-to-area connections that they support. We do so based on an approach called "Knowledge Engineering from Experimental Design" (KEfED) model that is based on experimental variables. We have extended the underlying KEfED representation of tract-tracing experiments by incorporating the definition of a neuronanatomical data map as a measurement variable in the study design. This paper describes the software design of a web-application that allows anatomical data sets to be described within a standard experimental context and thus indexed by non-spatial experimental design features.

  17. Estimation of effective connectivity via data-driven neural modeling

    PubMed Central

    Freestone, Dean R.; Karoly, Philippa J.; Nešić, Dragan; Aram, Parham; Cook, Mark J.; Grayden, David B.

    2014-01-01

    This research introduces a new method for functional brain imaging via a process of model inversion. By estimating parameters of a computational model, we are able to track effective connectivity and mean membrane potential dynamics that cannot be directly measured using electrophysiological measurements alone. The ability to track the hidden aspects of neurophysiology will have a profound impact on the way we understand and treat epilepsy. For example, under the assumption the model captures the key features of the cortical circuits of interest, the framework will provide insights into seizure initiation and termination on a patient-specific basis. It will enable investigation into the effect a particular drug has on specific neural populations and connectivity structures using minimally invasive measurements. The method is based on approximating brain networks using an interconnected neural population model. The neural population model is based on a neural mass model that describes the functional activity of the brain, capturing the mesoscopic biophysics and anatomical structure. The model is made subject-specific by estimating the strength of intra-cortical connections within a region and inter-cortical connections between regions using a novel Kalman filtering method. We demonstrate through simulation how the framework can be used to track the mechanisms involved in seizure initiation and termination. PMID:25506315

  18. Ground states of partially connected binary neural networks

    NASA Technical Reports Server (NTRS)

    Baram, Yoram

    1990-01-01

    Neural networks defined by outer products of vectors over (-1, 0, 1) are considered. Patterns over (-1, 0, 1) define by their outer products partially connected neural networks consisting of internally strongly connected, externally weakly connected subnetworks. Subpatterns over (-1, 1) define subnetworks, and their combinations that agree in the common bits define permissible words. It is shown that the permissible words are locally stable states of the network, provided that each of the subnetworks stores mutually orthogonal subwords, or, at most, two subwords. It is also shown that when each of the subnetworks stores two mutually orthogonal binary subwords at most, the permissible words, defined as the combinations of the subwords (one corresponding to each subnetwork), that agree in their common bits are the unique ground states of the associated energy function.

  19. Neural autoantibodies and neurophysiologic abnormalities in patients exposed to molds in water-damaged buildings.

    PubMed

    Campbell, Andrew W; Thrasher, Jack D; Madison, Roberta A; Vojdani, Aristo; Gray, Michael R; Johnson, Al

    2003-08-01

    Adverse health effects of fungal bioaerosols on occupants of water-damaged homes and other buildings have been reported. Recently, it has been suggested that mold exposure causes neurological injury. The authors investigated neurological antibodies and neurophysiological abnormalities in patients exposed to molds at home who developed symptoms of peripheral neuropathy (i.e., numbness, tingling, tremors, and muscle weakness in the extremities). Serum samples were collected and analyzed with the enzyme-linked immunosorbent assay (ELISA) technique for antibodies to myelin basic protein, myelin-associated glycoprotein, ganglioside GM1, sulfatide, myelin oligodendrocyte glycoprotein, alpha-B-crystallin, chondroitin sulfate, tubulin, and neurofilament. Antibodies to molds and mycotoxins were also determined with ELISA, as reported previously. Neurophysiologic evaluations for latency, amplitude, and velocity were performed on 4 motor nerves (median, ulnar, peroneal, and tibial), and for latency and amplitude on 3 sensory nerves (median, ulnar, and sural). Patients with documented, measured exposure to molds had elevated titers of antibodies (immunoglobulin [Ig]A, IgM, and IgG) to neural-specific antigens. Nerve conduction studies revealed 4 patient groupings: (1) mixed sensory-motor polyneuropathy (n = 55, abnormal), (2) motor neuropathy (n = 17, abnormal), (3) sensory neuropathy (n = 27, abnormal), and (4) those with symptoms but no neurophysiological abnormalities (n = 20, normal controls). All groups showed significantly increased autoantibody titers for all isotypes (IgA, IgM, and IgG) of antibodies to neural antigens when compared with 500 healthy controls. Groups 1 through 3 also exhibited abnormal neurophysiologic findings. The authors concluded that exposure to molds in water-damaged buildings increased the risk for development of neural autoantibodies, peripheral neuropathy, and neurophysiologic abnormalities in exposed individuals.

  20. A small number of abnormal brain connections predicts adult autism spectrum disorder

    PubMed Central

    Yahata, Noriaki; Morimoto, Jun; Hashimoto, Ryuichiro; Lisi, Giuseppe; Shibata, Kazuhisa; Kawakubo, Yuki; Kuwabara, Hitoshi; Kuroda, Miho; Yamada, Takashi; Megumi, Fukuda; Imamizu, Hiroshi; Náñez Sr, José E.; Takahashi, Hidehiko; Okamoto, Yasumasa; Kasai, Kiyoto; Kato, Nobumasa; Sasaki, Yuka; Watanabe, Takeo; Kawato, Mitsuo

    2016-01-01

    Although autism spectrum disorder (ASD) is a serious lifelong condition, its underlying neural mechanism remains unclear. Recently, neuroimaging-based classifiers for ASD and typically developed (TD) individuals were developed to identify the abnormality of functional connections (FCs). Due to over-fitting and interferential effects of varying measurement conditions and demographic distributions, no classifiers have been strictly validated for independent cohorts. Here we overcome these difficulties by developing a novel machine-learning algorithm that identifies a small number of FCs that separates ASD versus TD. The classifier achieves high accuracy for a Japanese discovery cohort and demonstrates a remarkable degree of generalization for two independent validation cohorts in the USA and Japan. The developed ASD classifier does not distinguish individuals with major depressive disorder and attention-deficit hyperactivity disorder from their controls but moderately distinguishes patients with schizophrenia from their controls. The results leave open the viable possibility of exploring neuroimaging-based dimensions quantifying the multiple-disorder spectrum. PMID:27075704

  1. Identification of the connections in biologically inspired neural networks

    NASA Technical Reports Server (NTRS)

    Demuth, H.; Leung, K.; Beale, M.; Hicklin, J.

    1990-01-01

    We developed an identification method to find the strength of the connections between neurons from their behavior in small biologically-inspired artificial neural networks. That is, given the network external inputs and the temporal firing pattern of the neurons, we can calculate a solution for the strengths of the connections between neurons and the initial neuron activations if a solution exists. The method determines directly if there is a solution to a particular neural network problem. No training of the network is required. It should be noted that this is a first pass at the solution of a difficult problem. The neuron and network models chosen are related to biology but do not contain all of its complexities, some of which we hope to add to the model in future work. A variety of new results have been obtained. First, the method has been tailored to produce connection weight matrix solutions for networks with important features of biological neural (bioneural) networks. Second, a computationally efficient method of finding a robust central solution has been developed. This later method also enables us to find the most consistent solution in the presence of noisy data. Prospects of applying our method to identify bioneural network connections are exciting because such connections are almost impossible to measure in the laboratory. Knowledge of such connections would facilitate an understanding of bioneural networks and would allow the construction of the electronic counterparts of bioneural networks on very large scale integrated (VLSI) circuits.

  2. Abnormal regional activity and functional connectivity in resting-state brain networks associated with etiology confirmed unilateral pulsatile tinnitus in the early stage of disease.

    PubMed

    Lv, Han; Zhao, Pengfei; Liu, Zhaohui; Li, Rui; Zhang, Ling; Wang, Peng; Yan, Fei; Liu, Liheng; Wang, Guopeng; Zeng, Rong; Li, Ting; Dong, Cheng; Gong, Shusheng; Wang, Zhenchang

    2017-03-01

    Abnormal neural activities can be revealed by resting-state functional magnetic resonance imaging (rs-fMRI) using analyses of the regional activity and functional connectivity (FC) of the networks in the brain. This study was designed to demonstrate the functional network alterations in the patients with pulsatile tinnitus (PT). In this study, we recruited 45 patients with unilateral PT in the early stage of disease (less than 48 months of disease duration) and 45 normal controls. We used regional homogeneity (ReHo) and seed-based FC computational methods to reveal resting-state brain activity features associated with pulsatile tinnitus. Compared with healthy controls, PT patients showed regional abnormalities mainly in the left middle occipital gyrus (MOG), posterior cingulate gyrus (PCC), precuneus and right anterior insula (AI). When these regions were defined as seeds, we demonstrated widespread modification of interaction between the auditory and non-auditory networks. The auditory network was positively connected with the cognitive control network (CCN), which may associate with tinnitus related distress. Both altered regional activity and changed FC were found in the visual network. The modification of interactions of higher order networks were mainly found in the DMN, CCN and limbic networks. Functional connectivity between the left MOG and left parahippocampal gyrus could also be an index to reflect the disease duration. This study helped us gain a better understanding of the characteristics of neural network modifications in patients with pulsatile tinnitus. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Inferring Functional Neural Connectivity with Phase Synchronization Analysis: A Review of Methodology

    PubMed Central

    Sun, Junfeng; Li, Zhijun; Tong, Shanbao

    2012-01-01

    Functional neural connectivity is drawing increasing attention in neuroscience research. To infer functional connectivity from observed neural signals, various methods have been proposed. Among them, phase synchronization analysis is an important and effective one which examines the relationship of instantaneous phase between neural signals but neglecting the influence of their amplitudes. In this paper, we review the advances in methodologies of phase synchronization analysis. In particular, we discuss the definitions of instantaneous phase, the indexes of phase synchronization and their significance test, the issues that may affect the detection of phase synchronization and the extensions of phase synchronization analysis. In practice, phase synchronization analysis may be affected by observational noise, insufficient samples of the signals, volume conduction, and reference in recording neural signals. We make comments and suggestions on these issues so as to better apply phase synchronization analysis to inferring functional connectivity from neural signals. PMID:22577470

  4. Introduction to a system for implementing neural net connections on SIMD architectures

    NASA Technical Reports Server (NTRS)

    Tomboulian, Sherryl

    1988-01-01

    Neural networks have attracted much interest recently, and using parallel architectures to simulate neural networks is a natural and necessary application. The SIMD model of parallel computation is chosen, because systems of this type can be built with large numbers of processing elements. However, such systems are not naturally suited to generalized communication. A method is proposed that allows an implementation of neural network connections on massively parallel SIMD architectures. The key to this system is an algorithm permitting the formation of arbitrary connections between the neurons. A feature is the ability to add new connections quickly. It also has error recovery ability and is robust over a variety of network topologies. Simulations of the general connection system, and its implementation on the Connection Machine, indicate that the time and space requirements are proportional to the product of the average number of connections per neuron and the diameter of the interconnection network.

  5. Introduction to a system for implementing neural net connections on SIMD architectures

    NASA Technical Reports Server (NTRS)

    Tomboulian, Sherryl

    1988-01-01

    Neural networks have attracted much interest recently, and using parallel architectures to simulate neural networks is a natural and necessary application. The SIMD model of parallel computation is chosen, because systems of this type can be built with large numbers of processing elements. However, such systems are not naturally suited to generalized elements. A method is proposed that allows an implementation of neural network connections on massively parallel SIMD architectures. The key to this system is an algorithm permitting the formation of arbitrary connections between the neurons. A feature is the ability to add new connections quickly. It also has error recovery ability and is robust over a variety of network topologies. Simulations of the general connection system, and its implementation on the Connection Machine, indicate that the time and space requirements are proportional to the product of the average number of connections per neuron and the diameter of the interconnection network.

  6. Multidimensional analysis of the abnormal neural oscillations associated with lexical processing in schizophrenia.

    PubMed

    Xu, Tingting; Stephane, Massoud; Parhi, Keshab K

    2013-04-01

    The neural mechanisms of language abnormalities, the core symptoms in schizophrenia, remain unclear. In this study, a new experimental paradigm, combining magnetoencephalography (MEG) techniques and machine intelligence methodologies, was designed to gain knowledge about the frequency, brain location, and time of occurrence of the neural oscillations that are associated with lexical processing in schizophrenia. The 248-channel MEG recordings were obtained from 12 patients with schizophrenia and 10 healthy controls, during a lexical processing task, where the patients discriminated correct from incorrect lexical stimuli that were visually presented. Event-related desynchronization/synchronization (ERD/ERS) was computed along the frequency, time, and space dimensions combined, that resulted in a large spectral-spatial-temporal ERD/ERS feature set. Machine intelligence techniques were then applied to select a small subset of oscillation patterns that are abnormal in patients with schizophrenia, according to their discriminating power in patient and control classification. Patients with schizophrenia showed abnormal ERD/ERS patterns during both lexical encoding and post-encoding periods. The top-ranked features were located at the occipital and left frontal-temporal areas, and covered a wide frequency range, including δ (1-4 Hz), α (8-12 Hz), β (12-32 Hz), and γ (32-48 Hz) bands. These top features could discriminate the patient group from the control group with 90.91% high accuracy, which demonstrates significant brain oscillation abnormalities in patients with schizophrenia at the specific frequency, time, and brain location indicated by these top features. As neural oscillation abnormality may be due to the mechanisms of the disease, the spectral, spatial, and temporal content of the discriminating features can offer useful information for helping understand the physiological basis of the language disorder in schizophrenia, as well as the pathology of the

  7. Intranasal oxytocin modulates neural functional connectivity during human social interaction.

    PubMed

    Rilling, James K; Chen, Xiangchuan; Chen, Xu; Haroon, Ebrahim

    2018-02-10

    Oxytocin (OT) modulates social behavior in primates and many other vertebrate species. Studies in non-primate animals have demonstrated that, in addition to influencing activity within individual brain areas, OT influences functional connectivity across networks of areas involved in social behavior. Previously, we used fMRI to image brain function in human subjects during a dyadic social interaction task following administration of either intranasal oxytocin (INOT) or placebo, and analyzed the data with a standard general linear model. Here, we conduct an extensive re-analysis of these data to explore how OT modulates functional connectivity across a neural network that animal studies implicate in social behavior. OT induced widespread increases in functional connectivity in response to positive social interactions among men and widespread decreases in functional connectivity in response to negative social interactions among women. Nucleus basalis of Meynert, an important regulator of selective attention and motivation with a particularly high density of OT receptors, had the largest number of OT-modulated connections. Regions known to receive mesolimbic dopamine projections such as the nucleus accumbens and lateral septum were also hubs for OT effects on functional connectivity. Our results suggest that the neural mechanism by which OT influences primate social cognition may include changes in patterns of activity across neural networks that regulate social behavior in other animals. © 2018 Wiley Periodicals, Inc.

  8. Abnormal Connectional Fingerprint in Schizophrenia: A Novel Network Analysis of Diffusion Tensor Imaging Data

    PubMed Central

    Edwin Thanarajah, Sharmili; Han, Cheol E.; Rotarska-Jagiela, Anna; Singer, Wolf; Deichmann, Ralf; Maurer, Konrad; Kaiser, Marcus; Uhlhaas, Peter J.

    2016-01-01

    The graph theoretical analysis of structural magnetic resonance imaging (MRI) data has received a great deal of interest in recent years to characterize the organizational principles of brain networks and their alterations in psychiatric disorders, such as schizophrenia. However, the characterization of networks in clinical populations can be challenging, since the comparison of connectivity between groups is influenced by several factors, such as the overall number of connections and the structural abnormalities of the seed regions. To overcome these limitations, the current study employed the whole-brain analysis of connectional fingerprints in diffusion tensor imaging data obtained at 3 T of chronic schizophrenia patients (n = 16) and healthy, age-matched control participants (n = 17). Probabilistic tractography was performed to quantify the connectivity of 110 brain areas. The connectional fingerprint of a brain area represents the set of relative connection probabilities to all its target areas and is, hence, less affected by overall white and gray matter changes than absolute connectivity measures. After detecting brain regions with abnormal connectional fingerprints through similarity measures, we tested each of its relative connection probability between groups. We found altered connectional fingerprints in schizophrenia patients consistent with a dysconnectivity syndrome. While the medial frontal gyrus showed only reduced connectivity, the connectional fingerprints of the inferior frontal gyrus and the putamen mainly contained relatively increased connection probabilities to areas in the frontal, limbic, and subcortical areas. These findings are in line with previous studies that reported abnormalities in striatal–frontal circuits in the pathophysiology of schizophrenia, highlighting the potential utility of connectional fingerprints for the analysis of anatomical networks in the disorder. PMID:27445870

  9. Abnormal Connectional Fingerprint in Schizophrenia: A Novel Network Analysis of Diffusion Tensor Imaging Data.

    PubMed

    Edwin Thanarajah, Sharmili; Han, Cheol E; Rotarska-Jagiela, Anna; Singer, Wolf; Deichmann, Ralf; Maurer, Konrad; Kaiser, Marcus; Uhlhaas, Peter J

    2016-01-01

    The graph theoretical analysis of structural magnetic resonance imaging (MRI) data has received a great deal of interest in recent years to characterize the organizational principles of brain networks and their alterations in psychiatric disorders, such as schizophrenia. However, the characterization of networks in clinical populations can be challenging, since the comparison of connectivity between groups is influenced by several factors, such as the overall number of connections and the structural abnormalities of the seed regions. To overcome these limitations, the current study employed the whole-brain analysis of connectional fingerprints in diffusion tensor imaging data obtained at 3 T of chronic schizophrenia patients (n = 16) and healthy, age-matched control participants (n = 17). Probabilistic tractography was performed to quantify the connectivity of 110 brain areas. The connectional fingerprint of a brain area represents the set of relative connection probabilities to all its target areas and is, hence, less affected by overall white and gray matter changes than absolute connectivity measures. After detecting brain regions with abnormal connectional fingerprints through similarity measures, we tested each of its relative connection probability between groups. We found altered connectional fingerprints in schizophrenia patients consistent with a dysconnectivity syndrome. While the medial frontal gyrus showed only reduced connectivity, the connectional fingerprints of the inferior frontal gyrus and the putamen mainly contained relatively increased connection probabilities to areas in the frontal, limbic, and subcortical areas. These findings are in line with previous studies that reported abnormalities in striatal-frontal circuits in the pathophysiology of schizophrenia, highlighting the potential utility of connectional fingerprints for the analysis of anatomical networks in the disorder.

  10. Abnormal Superior Temporal Connectivity During Fear Perception in Schizophrenia

    PubMed Central

    Leitman, David I.; Loughead, James; Wolf, Daniel H.; Ruparel, Kosha; Kohler, Christian G.; Elliott, Mark A.; Bilker, Warren B.; Gur, Raquel E.; Gur, Ruben C.

    2008-01-01

    Patients with schizophrenia have difficulty in decoding facial affect. A study using event–related functional neuroimaging indicated that errors in fear detection in schizophrenia are associated with paradoxically higher activation in the amygdala and an associated network implicated in threat detection. Furthermore, this exaggerated activation to fearful faces correlated with severity of flat affect. These findings suggest that abnormal threat detection processing may reflect disruptions between nodes that comprise the affective appraisal circuit. Here we examined connectivity within this network by determining the pattern of intercorrelations among brain regions (regions of interest) significantly activated during fear identification in both healthy controls and patients using a novel procedure CORANOVA. This analysis tests differences in the interregional correlation strength between schizophrenia and healthy controls. Healthy subjects' task activation was principally characterized by robust correlations between medial structures like thalamus (THA) and amygdala (AMY) and middle frontal (MF), inferior frontal (IF), and prefrontal cortical (PFC) regions. In contrast, schizophrenia patients displayed no significant correlations between the medial regions and either MF or IF. Further, patients had significantly higher correlations between occipital lingual gyrus and superior temporal gyrus than healthy subjects. These between-group connectivity differences suggest that schizophrenia threat detection impairment may stem from abnormal stimulus integration. Such abnormal integration may disrupt the evaluation of threat within fronto-cortical regions. PMID:18550592

  11. Enhancement of Spike Synchrony in Hindmarsh-Rose Neural Networks by Randomly Rewiring Connections

    NASA Astrophysics Data System (ADS)

    Yang, Renhuan; Song, Aiguo; Yuan, Wujie

    Spike synchrony of the neural system is thought to have very dichotomous roles. On the one hand, it is ubiquitously present in the healthy brain and is thought to underlie feature binding during information processing. On the other hand, large scale synchronization is an underlying mechanism of epileptic seizures. In this paper, we investigate the spike synchrony of Hindmarsh-Rose (HR) neural networks. Our focus is the influence of the network connections on the spike synchrony of the neural networks. The simulations show that desynchronization in the nearest-neighbor coupled network evolves into accurate synchronization with connection-rewiring probability p increasing. We uncover a phenomenon of enhancement of spike synchrony by randomly rewiring connections. With connection strength c and average connection number m increasing spike synchrony is enhanced but it is not the whole story. Furthermore, the possible mechanism behind such synchronization is also addressed.

  12. Neural connectivity of the lateral geniculate body in the human brain: diffusion tensor imaging study.

    PubMed

    Kwon, Hyeok Gyu; Jang, Sung Ho

    2014-08-22

    A few studies have reported on the neural connectivity of some neural structures of the visual system in the human brain. However, little is known about the neural connectivity of the lateral geniculate body (LGB). In the current study, using diffusion tensor tractography (DTT), we attempted to investigate the neural connectivity of the LGB in normal subjects. A total of 52 healthy subjects were recruited for this study. A seed region of interest was placed on the LGB using the FMRIB Software Library which is a probabilistic tractography method based on a multi-fiber model. Connectivity was defined as the incidence of connection between the LGB and target brain areas at the threshold of 5, 25, and 50 streamlines. In addition, connectivity represented the percentage of connection in all hemispheres of 52 subjects. We found the following characteristics of connectivity of the LGB at the threshold of 5 streamline: (1) high connectivity to the corpus callosum (91.3%) and the contralateral temporal cortex (56.7%) via the corpus callosum, (2) high connectivity to the ipsilateral cerebral cortex: the temporal lobe (100%), primary visual cortex (95.2%), and visual association cortex (77.9%). The LGB appeared to have high connectivity to the corpus callosum and both temporal cortexes as well as the ipsilateral occipital cortex. We believe that the results of this study would be helpful in investigation of the neural network associated with the visual system and brain plasticity of the visual system after brain injury. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  13. Social anhedonia is associated with neural abnormalities during face emotion processing.

    PubMed

    Germine, Laura T; Garrido, Lucia; Bruce, Lori; Hooker, Christine

    2011-10-01

    Human beings are social organisms with an intrinsic desire to seek and participate in social interactions. Social anhedonia is a personality trait characterized by a reduced desire for social affiliation and reduced pleasure derived from interpersonal interactions. Abnormally high levels of social anhedonia prospectively predict the development of schizophrenia and contribute to poorer outcomes for schizophrenia patients. Despite the strong association between social anhedonia and schizophrenia, the neural mechanisms that underlie individual differences in social anhedonia have not been studied and are thus poorly understood. Deficits in face emotion recognition are related to poorer social outcomes in schizophrenia, and it has been suggested that face emotion recognition deficits may be a behavioral marker for schizophrenia liability. In the current study, we used functional magnetic resonance imaging (fMRI) to see whether there are differences in the brain networks underlying basic face emotion processing in a community sample of individuals low vs. high in social anhedonia. We isolated the neural mechanisms related to face emotion processing by comparing face emotion discrimination with four other baseline conditions (identity discrimination of emotional faces, identity discrimination of neutral faces, object discrimination, and pattern discrimination). Results showed a group (high/low social anhedonia) × condition (emotion discrimination/control condition) interaction in the anterior portion of the rostral medial prefrontal cortex, right superior temporal gyrus, and left somatosensory cortex. As predicted, high (relative to low) social anhedonia participants showed less neural activity in face emotion processing regions during emotion discrimination as compared to each control condition. The findings suggest that social anhedonia is associated with abnormalities in networks responsible for basic processes associated with social cognition, and provide a

  14. Abnormalities of Intrinsic Functional Connectivity in Autism Spectrum Disorders

    PubMed Central

    Monk, Christopher S.; Peltier, Scott J.; Wiggins, Jillian Lee; Weng, Shih-Jen; Carrasco, Melisa; Risi, Susan; Lord, Catherine

    2009-01-01

    Autism spectrum disorders (ASD) impact social functioning and communication, and individuals with these disorders often have restrictive and repetitive behaviors. Accumulating data indicate that ASD is associated with alterations of neural circuitry. Functional MRI (FMRI) studies have focused on connectivity in the context of psychological tasks. However, even in the absence of a task, the brain exhibits a high degree of functional connectivity, known as intrinsic or resting connectivity. Notably, the default network, which includes the posterior cingulate cortex, retro-splenial, lateral parietal cortex/angular gyrus, medial prefrontal cortex, superior frontal gyrus, temporal lobe, and parahippocampal gyrus, is strongly active when there is no task. Altered intrinsic connectivity within the default network may underlie offline processing that may actuate ASD impairments. Using FMRI, we sought to evaluate intrinsic connectivity within the default network in ASD. Relative to controls, the ASD group showed weaker connectivity between the posterior cingulate cortex and superior frontal gyrus and stronger connectivity between the posterior cingulate cortex and both the right temporal lobe and right parahippocampal gyrus. Moreover, poorer social functioning in the ASD group was correlated with weaker connectivity between the posterior cingulate cortex and the superior frontal gyrus. In addition, more severe restricted and repetitive behaviors in ASD were correlated with stronger connectivity between the posterior cingulate cortex and right parahippocampal gyrus. These findings indicate that ASD subjects show altered intrinsic connectivity within the default network, and connectivity between these structures is associated with specific ASD symptoms. PMID:19409498

  15. Abnormal Functional Connectivity in Autism Spectrum Disorders during Face Processing

    ERIC Educational Resources Information Center

    Kleinhans, Natalia M.; Richards, Todd; Sterling, Lindsey; Stegbauer, Keith C.; Mahurin, Roderick; Johnson, L. Clark; Greenson, Jessica; Dawson, Geraldine; Aylward, Elizabeth

    2008-01-01

    Abnormalities in the interactions between functionally linked brain regions have been suggested to be associated with the clinical impairments observed in autism spectrum disorders (ASD). We investigated functional connectivity within the limbic system during face identification; a primary component of social cognition, in 19 high-functioning…

  16. Neural systems language: a formal modeling language for the systematic description, unambiguous communication, and automated digital curation of neural connectivity.

    PubMed

    Brown, Ramsay A; Swanson, Larry W

    2013-09-01

    Systematic description and the unambiguous communication of findings and models remain among the unresolved fundamental challenges in systems neuroscience. No common descriptive frameworks exist to describe systematically the connective architecture of the nervous system, even at the grossest level of observation. Furthermore, the accelerating volume of novel data generated on neural connectivity outpaces the rate at which this data is curated into neuroinformatics databases to synthesize digitally systems-level insights from disjointed reports and observations. To help address these challenges, we propose the Neural Systems Language (NSyL). NSyL is a modeling language to be used by investigators to encode and communicate systematically reports of neural connectivity from neuroanatomy and brain imaging. NSyL engenders systematic description and communication of connectivity irrespective of the animal taxon described, experimental or observational technique implemented, or nomenclature referenced. As a language, NSyL is internally consistent, concise, and comprehensible to both humans and computers. NSyL is a promising development for systematizing the representation of neural architecture, effectively managing the increasing volume of data on neural connectivity and streamlining systems neuroscience research. Here we present similar precedent systems, how NSyL extends existing frameworks, and the reasoning behind NSyL's development. We explore NSyL's potential for balancing robustness and consistency in representation by encoding previously reported assertions of connectivity from the literature as examples. Finally, we propose and discuss the implications of a framework for how NSyL will be digitally implemented in the future to streamline curation of experimental results and bridge the gaps among anatomists, imagers, and neuroinformatics databases. Copyright © 2013 Wiley Periodicals, Inc.

  17. Abnormal neural hierarchy in processing of verbal information in patients with schizophrenia.

    PubMed

    Lerner, Yulia; Bleich-Cohen, Maya; Solnik-Knirsh, Shimrit; Yogev-Seligmann, Galit; Eisenstein, Tamir; Madah, Waheed; Shamir, Alon; Hendler, Talma; Kremer, Ilana

    2018-01-01

    Previous research indicates abnormal comprehension of verbal information in patients with schizophrenia. Yet the neural mechanism underlying the breakdown of verbal information processing in schizophrenia is poorly understood. Imaging studies in healthy populations have shown a network of brain areas involved in hierarchical processing of verbal information over time. Here, we identified critical aspects of this hierarchy, examining patients with schizophrenia. Using functional magnetic resonance imaging, we examined various levels of information comprehension elicited by naturally presented verbal stimuli; from a set of randomly shuffled words to an intact story. Specifically, patients with first episode schizophrenia ( N  = 15), their non-manifesting siblings ( N  = 14) and healthy controls ( N  = 15) listened to a narrated story and randomly scrambled versions of it. To quantify the degree of dissimilarity between the groups, we adopted an inter-subject correlation (inter-SC) approach, which estimates differences in synchronization of neural responses within and between groups. The temporal topography found in healthy and siblings groups were consistent with our previous findings - high synchronization in responses from early sensory toward high order perceptual and cognitive areas. In patients with schizophrenia, stimuli with short and intermediate temporal scales evoked a typical pattern of reliable responses, whereas story condition (long temporal scale) revealed robust and widespread disruption of the inter-SCs. In addition, the more similar the neural activity of patients with schizophrenia was to the average response in the healthy group, the less severe the positive symptoms of the patients. Our findings suggest that system-level neural indication of abnormal verbal information processing in schizophrenia reflects disease manifestations.

  18. Neural correlates of genetically abnormal social cognition in Williams syndrome.

    PubMed

    Meyer-Lindenberg, Andreas; Hariri, Ahmad R; Munoz, Karen E; Mervis, Carolyn B; Mattay, Venkata S; Morris, Colleen A; Berman, Karen Faith

    2005-08-01

    Williams-Beuren syndrome (WBS), caused by a microdeletion of approximately 21 genes on chromosome 7q11.23, is characterized by unique hypersociability combined with increased non-social anxiety. Using functional neuroimaging, we found reduced amygdala activation in individuals with WBS for threatening faces but increased activation for threatening scenes, relative to matched normal controls. Activation and interactions of prefrontal regions linked to amygdala, especially orbitofrontal cortex, were abnormal, suggesting a genetically controlled neural circuitry for regulating human social behavior.

  19. Aberrant Hyperconnectivity in the Motor System at Rest Is Linked to Motor Abnormalities in Schizophrenia Spectrum Disorders.

    PubMed

    Walther, Sebastian; Stegmayer, Katharina; Federspiel, Andrea; Bohlhalter, Stephan; Wiest, Roland; Viher, Petra V

    2017-09-01

    Motor abnormalities are frequently observed in schizophrenia and structural alterations of the motor system have been reported. The association of aberrant motor network function, however, has not been tested. We hypothesized that abnormal functional connectivity would be related to the degree of motor abnormalities in schizophrenia. In 90 subjects (46 patients) we obtained resting stated functional magnetic resonance imaging (fMRI) for 8 minutes 40 seconds at 3T. Participants further completed a motor battery on the scanning day. Regions of interest (ROI) were cortical motor areas, basal ganglia, thalamus and motor cerebellum. We computed ROI-to-ROI functional connectivity. Principal component analyses of motor behavioral data produced 4 factors (primary motor, catatonia and dyskinesia, coordination, and spontaneous motor activity). Motor factors were correlated with connectivity values. Schizophrenia was characterized by hyperconnectivity in 3 main areas: motor cortices to thalamus, motor cortices to cerebellum, and prefrontal cortex to the subthalamic nucleus. In patients, thalamocortical hyperconnectivity was linked to catatonia and dyskinesia, whereas aberrant connectivity between rostral anterior cingulate and caudate was linked to the primary motor factor. Likewise, connectivity between motor cortex and cerebellum correlated with spontaneous motor activity. Therefore, altered functional connectivity suggests a specific intrinsic and tonic neural abnormality in the motor system in schizophrenia. Furthermore, altered neural activity at rest was linked to motor abnormalities on the behavioral level. Thus, aberrant resting state connectivity may indicate a system out of balance, which produces characteristic behavioral alterations. © The Author 2017. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  20. Reorganization of the Connectivity between Elementary Functions – A Model Relating Conscious States to Neural Connections

    PubMed Central

    Mogensen, Jesper; Overgaard, Morten

    2017-01-01

    In the present paper it is argued that the “neural correlate of consciousness” (NCC) does not appear to be a separate “module” – but an aspect of information processing within the neural substrate of various cognitive processes. Consequently, NCC can only be addressed adequately within frameworks that model the general relationship between neural processes and mental states – and take into account the dynamic connectivity of the brain. We presently offer the REFGEN (general reorganization of elementary functions) model as such a framework. This model builds upon and expands the REF (reorganization of elementary functions) and REFCON (of elementary functions and consciousness) models. All three models integrate the relationship between the neural and mental layers of description via the construction of an intermediate level dealing with computational states. The importance of experience based organization of neural and cognitive processes is stressed. The models assume that the mechanisms of consciousness are in principle the same as the basic mechanisms of all aspects of cognition – when information is processed to a sufficiently “high level” it becomes available to conscious experience. The NCC is within the REFGEN model seen as aspects of the dynamic and experience driven reorganizations of the synaptic connectivity between the neurocognitive “building blocks” of the model – the elementary functions. PMID:28473797

  1. A novel method linking neural connectivity to behavioral fluctuations: Behavior-regressed connectivity.

    PubMed

    Passaro, Antony D; Vettel, Jean M; McDaniel, Jonathan; Lawhern, Vernon; Franaszczuk, Piotr J; Gordon, Stephen M

    2017-03-01

    During an experimental session, behavioral performance fluctuates, yet most neuroimaging analyses of functional connectivity derive a single connectivity pattern. These conventional connectivity approaches assume that since the underlying behavior of the task remains constant, the connectivity pattern is also constant. We introduce a novel method, behavior-regressed connectivity (BRC), to directly examine behavioral fluctuations within an experimental session and capture their relationship to changes in functional connectivity. This method employs the weighted phase lag index (WPLI) applied to a window of trials with a weighting function. Using two datasets, the BRC results are compared to conventional connectivity results during two time windows: the one second before stimulus onset to identify predictive relationships, and the one second after onset to capture task-dependent relationships. In both tasks, we replicate the expected results for the conventional connectivity analysis, and extend our understanding of the brain-behavior relationship using the BRC analysis, demonstrating subject-specific BRC maps that correspond to both positive and negative relationships with behavior. Comparison with Existing Method(s): Conventional connectivity analyses assume a consistent relationship between behaviors and functional connectivity, but the BRC method examines performance variability within an experimental session to understand dynamic connectivity and transient behavior. The BRC approach examines connectivity as it covaries with behavior to complement the knowledge of underlying neural activity derived from conventional connectivity analyses. Within this framework, BRC may be implemented for the purpose of understanding performance variability both within and between participants. Published by Elsevier B.V.

  2. Cell death in neural precursor cells and neurons before neurite formation prevents the emergence of abnormal neural structures in the Drosophila optic lobe.

    PubMed

    Hara, Yusuke; Sudo, Tatsuya; Togane, Yu; Akagawa, Hiromi; Tsujimura, Hidenobu

    2018-04-01

    Programmed cell death is a conserved strategy for neural development both in vertebrates and invertebrates and is recognized at various developmental stages in the brain from neurogenesis to adulthood. To understand the development of the central nervous system, it is essential to reveal not only molecular mechanisms but also the role of neural cell death (Pinto-Teixeira et al., 2016). To understand the role of cell death in neural development, we investigated the effect of inhibition of cell death on optic lobe development. Our data demonstrate that, in the optic lobe of Drosophila, cell death occurs in neural precursor cells and neurons before neurite formation and functions to prevent various developmental abnormalities. When neuronal cell death was inhibited by an effector caspase inhibitor, p35, multiple abnormal neuropil structures arose during optic lobe development-e.g., enlarged or fused neuropils, misrouted neurons and abnormal neurite lumps. Inhibition of cell death also induced morphogenetic defects in the lamina and medulla development-e.g., failures in the separation of the lamina and medulla cortices and the medulla rotation. These defects were reproduced in the mutant of an initiator caspase, dronc. If cell death was a mechanism for removing the abnormal neuropil structures, we would also expect to observe them in mutants defective for corpse clearance. However, they were not observed in these mutants. When dead cell-membranes were visualized with Apoliner, they were observed only in cortices and not in neuropils. These results suggest that the cell death occurs before mature neurite formation. Moreover, we found that inhibition of cell death induced ectopic neuroepithelial cells, neuroblasts and ganglion mother cells in late pupal stages, at sites where the outer and inner proliferation centers were located at earlier developmental stages. Caspase-3 activation was observed in the neuroepithelial cells and neuroblasts in the proliferation centers

  3. Neural network connectivity differences in children who stutter

    PubMed Central

    Zhu, David C.

    2013-01-01

    Affecting 1% of the general population, stuttering impairs the normally effortless process of speech production, which requires precise coordination of sequential movement occurring among the articulatory, respiratory, and resonance systems, all within millisecond time scales. Those afflicted experience frequent disfluencies during ongoing speech, often leading to negative psychosocial consequences. The aetiology of stuttering remains unclear; compared to other neurodevelopmental disorders, few studies to date have examined the neural bases of childhood stuttering. Here we report, for the first time, results from functional (resting state functional magnetic resonance imaging) and structural connectivity analyses (probabilistic tractography) of multimodal neuroimaging data examining neural networks in children who stutter. We examined how synchronized brain activity occurring among brain areas associated with speech production, and white matter tracts that interconnect them, differ in young children who stutter (aged 3–9 years) compared with age-matched peers. Results showed that children who stutter have attenuated connectivity in neural networks that support timing of self-paced movement control. The results suggest that auditory-motor and basal ganglia-thalamocortical networks develop differently in stuttering children, which may in turn affect speech planning and execution processes needed to achieve fluent speech motor control. These results provide important initial evidence of neurological differences in the early phases of symptom onset in children who stutter. PMID:24131593

  4. Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science.

    PubMed

    Mocanu, Decebal Constantin; Mocanu, Elena; Stone, Peter; Nguyen, Phuong H; Gibescu, Madeleine; Liotta, Antonio

    2018-06-19

    Through the success of deep learning in various domains, artificial neural networks are currently among the most used artificial intelligence methods. Taking inspiration from the network properties of biological neural networks (e.g. sparsity, scale-freeness), we argue that (contrary to general practice) artificial neural networks, too, should not have fully-connected layers. Here we propose sparse evolutionary training of artificial neural networks, an algorithm which evolves an initial sparse topology (Erdős-Rényi random graph) of two consecutive layers of neurons into a scale-free topology, during learning. Our method replaces artificial neural networks fully-connected layers with sparse ones before training, reducing quadratically the number of parameters, with no decrease in accuracy. We demonstrate our claims on restricted Boltzmann machines, multi-layer perceptrons, and convolutional neural networks for unsupervised and supervised learning on 15 datasets. Our approach has the potential to enable artificial neural networks to scale up beyond what is currently possible.

  5. Abnormalities of neural circuitry in Alzheimer's disease: hippocampus and cortical cholinergic innervation.

    PubMed

    Geula, C

    1998-07-01

    Severe pathology in Alzheimer's disease (AD) results in marked disruption of cortical circuitry. Formation of neurofibrillary tangles, neuronal loss, decrease in dendritic extent, and synaptic depletion combine to halt communication among various cortical areas, resulting in anatomic isolation and fragmentation of many cortical zones. The clinical manifestation of this disruption is severe and debilitating cognitive dysfunction, often accompanied by psychiatric and behavioral disturbances and a diminished ability to perform activities of daily living. However, different cortical circuits are not equally vulnerable to AD pathology. In particular, two cortical systems that appear to be involved in the neural processing of memory are selectively vulnerable to degeneration in AD. One consists of connections between the hippocampus and its neighboring cortical structures within the temporal lobe. The second is the cortical cholinergic system that originates in neurons within the basal forebrain and innervates the entire cortical mantle. The circuitry in these systems shows early and severe degenerative changes in the course of AD. The selective vulnerability of these circuits is the probable reason for the early and marked loss of memory observed in these patients. This review presents current knowledge of the general pattern of cortical circuitry, followed by a summary of abnormalities of this circuitry in AD. The cortical circuits that exhibit selective pathology in AD are described in greater detail. Therapeutic implications of the abnormal circuitry in AD are also discussed. For therapies to be effective, early diagnosis of AD is necessary. Future efforts at AD therapy must be combined with an equally intense effort to develop tools capable of early diagnosis of AD, preferably at a preclinical stage before the onset of cognitive symptoms.

  6. Neural conduction abnormality in the brain stem and prevalence of the abnormality in late preterm infants with perinatal problems.

    PubMed

    Jiang, Ze Dong

    2013-08-01

    Neurodevelopment in late preterm infants has recently attracted considerable interest. The prevalence of brain stem conduction abnormality remains unknown. We examined maximum length sequence brain stem auditory evoked response in 163 infants, born at 33-36 weeks gestation, who had various perinatal problems. Compared with 49 normal term infants without problems, the late preterm infants showed a significant increase in III-V and I-V interpeak intervals at all 91-910/s clicks, particularly at 455 and 910/s (p < 0.01-0.001). The I-III interval was slightly increased, without statistically significant difference from the controls at any click rates. These results suggest that neural conduction along the, mainly more central or rostral part of, auditory brain stem is abnormal in late preterm infants with perinatal problems. Of the 163 late preterm infant, the number (and percentage rate) of infants with abnormal I-V interval at 91, 227, 455, and 910/s clicks was, respectively, 11 (6.5%), 17 (10.2%), 37 (22.3%), and 31 (18.7%). The number (and percentage rate) of infants with abnormal III-V interval at these rates was, respectively, 10 (6.0%), 17 (10.2%), 28 (16.9), and 36 (21.2%). Apparently, the abnormal rates were much higher at 455 and 910/s clicks than at lower rates 91 and 227/s. In total, 42 (25.8%) infants showed abnormal I-V and/or III-V intervals. Conduction in, mainly in the more central part, the brain stem is abnormal in late preterm infants with perinatal problems. The abnormality is more detectable at high- than at low-rate sensory stimulation. A quarter of late preterm infants with perinatal problems have brain stem conduction abnormality.

  7. Somatosensory cortex functional connectivity abnormalities in autism show opposite trends, depending on direction and spatial scale

    PubMed Central

    Khan, Sheraz; Michmizos, Konstantinos; Tommerdahl, Mark; Ganesan, Santosh; Kitzbichler, Manfred G.; Zetino, Manuel; Garel, Keri-Lee A.; Herbert, Martha R.; Hämäläinen, Matti S.

    2015-01-01

    Functional connectivity is abnormal in autism, but the nature of these abnormalities remains elusive. Different studies, mostly using functional magnetic resonance imaging, have found increased, decreased, or even mixed pattern functional connectivity abnormalities in autism, but no unifying framework has emerged to date. We measured functional connectivity in individuals with autism and in controls using magnetoencephalography, which allowed us to resolve both the directionality (feedforward versus feedback) and spatial scale (local or long-range) of functional connectivity. Specifically, we measured the cortical response and functional connectivity during a passive 25-Hz vibrotactile stimulation in the somatosensory cortex of 20 typically developing individuals and 15 individuals with autism, all males and right-handed, aged 8–18, and the mu-rhythm during resting state in a subset of these participants (12 per group, same age range). Two major significant group differences emerged in the response to the vibrotactile stimulus. First, the 50-Hz phase locking component of the cortical response, generated locally in the primary (S1) and secondary (S2) somatosensory cortex, was reduced in the autism group (P < 0.003, corrected). Second, feedforward functional connectivity between S1 and S2 was increased in the autism group (P < 0.004, corrected). During resting state, there was no group difference in the mu-α rhythm. In contrast, the mu-β rhythm, which has been associated with feedback connectivity, was significantly reduced in the autism group (P < 0.04, corrected). Furthermore, the strength of the mu-β was correlated to the relative strength of 50 Hz component of the response to the vibrotactile stimulus (r = 0.78, P < 0.00005), indicating a shared aetiology for these seemingly unrelated abnormalities. These magnetoencephalography-derived measures were correlated with two different behavioural sensory processing scores (P < 0.01 and P < 0.02 for the autism

  8. Abnormal Neural Activation to Faces in the Parents of Children with Autism

    PubMed Central

    Yucel, G. H.; Belger, A.; Bizzell, J.; Parlier, M.; Adolphs, R.; Piven, J.

    2015-01-01

    Parents of children with an autism spectrum disorder (ASD) show subtle deficits in aspects of social behavior and face processing, which resemble those seen in ASD, referred to as the “Broad Autism Phenotype ” (BAP). While abnormal activation in ASD has been reported in several brain structures linked to social cognition, little is known regarding patterns in the BAP. We compared autism parents with control parents with no family history of ASD using 2 well-validated face-processing tasks. Results indicated increased activation in the autism parents to faces in the amygdala (AMY) and the fusiform gyrus (FG), 2 core face-processing regions. Exploratory analyses revealed hyper-activation of lateral occipital cortex (LOC) bilaterally in autism parents with aloof personality (“BAP+”). Findings suggest that abnormalities of the AMY and FG are related to underlying genetic liability for ASD, whereas abnormalities in the LOC and right FG are more specific to behavioral features of the BAP. Results extend our knowledge of neural circuitry underlying abnormal face processing beyond those previously reported in ASD to individuals with shared genetic liability for autism and a subset of genetically related individuals with the BAP. PMID:25056573

  9. Mindfulness and dynamic functional neural connectivity in children and adolescents.

    PubMed

    Marusak, Hilary A; Elrahal, Farrah; Peters, Craig A; Kundu, Prantik; Lombardo, Michael V; Calhoun, Vince D; Goldberg, Elimelech K; Cohen, Cindy; Taub, Jeffrey W; Rabinak, Christine A

    2018-01-15

    Interventions that promote mindfulness consistently show salutary effects on cognition and emotional wellbeing in adults, and more recently, in children and adolescents. However, we lack understanding of the neurobiological mechanisms underlying mindfulness in youth that should allow for more judicious application of these interventions in clinical and educational settings. Using multi-echo multi-band fMRI, we examined dynamic (i.e., time-varying) and conventional static resting-state connectivity between core neurocognitive networks (i.e., salience/emotion, default mode, central executive) in 42 children and adolescents (ages 6-17). We found that trait mindfulness in youth relates to dynamic but not static resting-state connectivity. Specifically, more mindful youth transitioned more between brain states over the course of the scan, spent overall less time in a certain connectivity state, and showed a state-specific reduction in connectivity between salience/emotion and central executive networks. The number of state transitions mediated the link between higher mindfulness and lower anxiety, providing new insights into potential neural mechanisms underlying benefits of mindfulness on psychological health in youth. Our results provide new evidence that mindfulness in youth relates to functional neural dynamics and interactions between neurocognitive networks, over time. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. Ground-state coding in partially connected neural networks

    NASA Technical Reports Server (NTRS)

    Baram, Yoram

    1989-01-01

    Patterns over (-1,0,1) define, by their outer products, partially connected neural networks, consisting of internally strongly connected, externally weakly connected subnetworks. The connectivity patterns may have highly organized structures, such as lattices and fractal trees or nests. Subpatterns over (-1,1) define the subcodes stored in the subnetwork, that agree in their common bits. It is first shown that the code words are locally stable stares of the network, provided that each of the subcodes consists of mutually orthogonal words or of, at most, two words. Then it is shown that if each of the subcodes consists of two orthogonal words, the code words are the unique ground states (absolute minima) of the Hamiltonian associated with the network. The regions of attraction associated with the code words are shown to grow with the number of subnetworks sharing each of the neurons. Depending on the particular network architecture, the code sizes of partially connected networks can be vastly greater than those of fully connected ones and their error correction capabilities can be significantly greater than those of the disconnected subnetworks. The codes associated with lattice-structured and hierarchical networks are discussed in some detail.

  11. Thalamocortical functional connectivity in Lennox-Gastaut syndrome is abnormally enhanced in executive-control and default-mode networks.

    PubMed

    Warren, Aaron E L; Abbott, David F; Jackson, Graeme D; Archer, John S

    2017-12-01

    To identify abnormal thalamocortical circuits in the severe epilepsy of Lennox-Gastaut syndrome (LGS) that may explain the shared electroclinical phenotype and provide potential treatment targets. Twenty patients with a diagnosis of LGS (mean age = 28.5 years) and 26 healthy controls (mean age = 27.6 years) were compared using task-free functional magnetic resonance imaging (MRI). The thalamus was parcellated according to functional connectivity with 10 cortical networks derived using group-level independent component analysis. For each cortical network, we assessed between-group differences in thalamic functional connectivity strength using nonparametric permutation-based tests. Anatomical locations were identified by quantifying spatial overlap with a histologically informed thalamic MRI atlas. In both groups, posterior thalamic regions showed functional connectivity with visual, auditory, and sensorimotor networks, whereas anterior, medial, and dorsal thalamic regions were connected with networks of distributed association cortex (including the default-mode, anterior-salience, and executive-control networks). Four cortical networks (left and right executive-control network; ventral and dorsal default-mode network) showed significantly enhanced thalamic functional connectivity strength in patients relative to controls. Abnormal connectivity was maximal in mediodorsal and ventrolateral thalamic nuclei. Specific thalamocortical circuits are affected in LGS. Functional connectivity is abnormally enhanced between the mediodorsal and ventrolateral thalamus and the default-mode and executive-control networks, thalamocortical circuits that normally support diverse cognitive processes. In contrast, thalamic regions connecting with primary and sensory cortical networks appear to be less affected. Our previous neuroimaging studies show that epileptic activity in LGS is expressed via the default-mode and executive-control networks. Results of the present study suggest that

  12. Effect of Explicit Evaluation on Neural Connectivity Related to Listening to Unfamiliar Music

    PubMed Central

    Liu, Chao; Brattico, Elvira; Abu-jamous, Basel; Pereira, Carlos S.; Jacobsen, Thomas; Nandi, Asoke K.

    2017-01-01

    People can experience different emotions when listening to music. A growing number of studies have investigated the brain structures and neural connectivities associated with perceived emotions. However, very little is known about the effect of an explicit act of judgment on the neural processing of emotionally-valenced music. In this study, we adopted the novel consensus clustering paradigm, called binarisation of consensus partition matrices (Bi-CoPaM), to study whether and how the conscious aesthetic evaluation of the music would modulate brain connectivity networks related to emotion and reward processing. Participants listened to music under three conditions – one involving a non-evaluative judgment, one involving an explicit evaluative aesthetic judgment, and one involving no judgment at all (passive listening only). During non-evaluative attentive listening we obtained auditory-limbic connectivity whereas when participants were asked to decide explicitly whether they liked or disliked the music excerpt, only two clusters of intercommunicating brain regions were found: one including areas related to auditory processing and action observation, and the other comprising higher-order structures involved with visual processing. Results indicate that explicit evaluative judgment has an impact on the neural auditory-limbic connectivity during affective processing of music. PMID:29311874

  13. Abnormal Neural Activation to Faces in the Parents of Children with Autism.

    PubMed

    Yucel, G H; Belger, A; Bizzell, J; Parlier, M; Adolphs, R; Piven, J

    2015-12-01

    Parents of children with an autism spectrum disorder (ASD) show subtle deficits in aspects of social behavior and face processing, which resemble those seen in ASD, referred to as the "Broad Autism Phenotype " (BAP). While abnormal activation in ASD has been reported in several brain structures linked to social cognition, little is known regarding patterns in the BAP. We compared autism parents with control parents with no family history of ASD using 2 well-validated face-processing tasks. Results indicated increased activation in the autism parents to faces in the amygdala (AMY) and the fusiform gyrus (FG), 2 core face-processing regions. Exploratory analyses revealed hyper-activation of lateral occipital cortex (LOC) bilaterally in autism parents with aloof personality ("BAP+"). Findings suggest that abnormalities of the AMY and FG are related to underlying genetic liability for ASD, whereas abnormalities in the LOC and right FG are more specific to behavioral features of the BAP. Results extend our knowledge of neural circuitry underlying abnormal face processing beyond those previously reported in ASD to individuals with shared genetic liability for autism and a subset of genetically related individuals with the BAP. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  14. Abnormal cardiovascular response to exercise in hypertension: contribution of neural factors.

    PubMed

    Mitchell, Jere H

    2017-06-01

    During both dynamic (e.g., endurance) and static (e.g., strength) exercise there are exaggerated cardiovascular responses in hypertension. This includes greater increases in blood pressure, heart rate, and efferent sympathetic nerve activity than in normal controls. Two of the known neural factors that contribute to this abnormal cardiovascular response are the exercise pressor reflex (EPR) and functional sympatholysis. The EPR originates in contracting skeletal muscle and reflexly increases sympathetic efferent nerve activity to the heart and blood vessels as well as decreases parasympathetic efferent nerve activity to the heart. These changes in autonomic nerve activity cause an increase in blood pressure, heart rate, left ventricular contractility, and vasoconstriction in the arterial tree. However, arterial vessels in the contracting skeletal muscle have a markedly diminished vasoconstrictor response. The markedly diminished vasoconstriction in contracting skeletal muscle has been termed functional sympatholysis. It has been shown in hypertension that there is an enhanced EPR, including both its mechanoreflex and metaboreflex components, and an impaired functional sympatholysis. These conditions set up a positive feedback or vicious cycle situation that causes a progressively greater decrease in the blood flow to the exercising muscle. Thus these two neural mechanisms contribute significantly to the abnormal cardiovascular response to exercise in hypertension. In addition, exercise training in hypertension decreases the enhanced EPR, including both mechanoreflex and metaboreflex function, and improves the impaired functional sympatholysis. These two changes, caused by exercise training, improve the muscle blood flow to exercising muscle and cause a more normal cardiovascular response to exercise in hypertension. Copyright © 2017 the American Physiological Society.

  15. Abnormal rich club organization and impaired correlation between structural and functional connectivity in migraine sufferers.

    PubMed

    Li, Kang; Liu, Lijun; Yin, Qin; Dun, Wanghuan; Xu, Xiaolin; Liu, Jixin; Zhang, Ming

    2017-04-01

    Because of the unique position of the topologically central role of densely interconnected brain hubs, our study aimed to investigate whether these regions and their related connections would be particularly vulnerable to migraine. In our study, we explored the rich club structure and its role in global functional dynamics in 30 patients with migraine without aura and 30 healthy controls. DTI and resting fMRI were used to construct structural connectivity (SC) and functional connectivity (FC) networks. An independent replication data set of 26 patients and 26 controls was included to replicate and validate significant findings. As compared with the controls, the structural networks of patients exhibited altered rich club organization with higher level of feeder connection density, abnormal small-world organization with increased global efficiency and decreased strength of SC-FC coupling. As these abnormal topological properties and headache attack duration exhibited a significant association with increased density of feeder connections, our results indicated that migraine may be characterized by a selective alteration of the structural connectivity of the rich club regions, tending to have higher 'bridgeness' with non-rich club regions, which may increase the integration among pain-related brain circuits with more excitability but less inhibition for the modulation of migraine.

  16. Task-Rest Modulation of Basal Ganglia Connectivity in Mild to Moderate Parkinson’s Disease

    PubMed Central

    Müller-Oehring, Eva M.; Sullivan, Edith V.; Pfefferbaum, Adolf; Huang, Neng C.; Poston, Kathleen L.; Bronte-Stewart, Helen M.; Schulte, Tilman

    2014-01-01

    Parkinson’s disease (PD) is associated with abnormal synchronization in basal ganglia-thalamo-cortical loops. We tested whether early PD patients without demonstrable cognitive impairment exhibit abnormal modulation of functional connectivity at rest, while engaged in a task, or both. PD and healthy controls underwent two functional MRI scans: a resting-state scan and a Stroop Match-to-Sample task scan. Rest-task modulation of basal ganglia (BG) connectivity was tested using seed-to-voxel connectivity analysis with task and rest time series as conditions. Despite substantial overlap of BG–cortical connectivity patterns in both groups, connectivity differences between groups had clinical and behavioral correlates. During rest, stronger putamen–medial parietal and pallidum–occipital connectivity in PD than controls was associated with worse task performance and more severe PD symptoms suggesting that abnormalities in resting-state connectivity denote neural network dedifferentiation. During the executive task, PD patients showed weaker BG-cortical connectivity than controls, i.e., between caudate–supramarginal gyrus and pallidum–inferior prefrontal regions, that was related to more severe PD symptoms and worse task performance. Yet, task processing also evoked stronger striatal–cortical connectivity, specifically between caudate–prefrontal, caudate–precuneus, and putamen–motor/premotor regions in PD relative to controls, which was related to less severe PD symptoms and better performance on the Stroop task. Thus, stronger task-evoked striatal connectivity in PD demonstrated compensatory neural network enhancement to meet task demands and improve performance levels. fMRI-based network analysis revealed that despite resting-state BG network compromise in PD, BG connectivity to prefrontal, premotor, and precuneus regions can be adequately invoked during executive control demands enabling near normal task performance. PMID:25280970

  17. Relation between cognition and neural connection from injured cingulum to brainstem cholinergic nuclei in chronic patients with traumatic brain injury.

    PubMed

    Yoo, Jin-Sun; Kim, Oh Lyong; Kim, Seong Ho; Kim, Min Su; Jang, Sung Ho

    2014-01-01

    This study investigated the relation between cognition and the neural connection from injured cingulum to brainstem cholinergic nuclei in patients with traumatic brain injury (TBI), using diffusion tensor tractography (DTT). Among 353 patients with TBI, 20 chronic patients who showed discontinuation of both anterior cingulums from the basal forebrain on DTT were recruited for this study. The Wechsler Intelligence Scale and the Memory Assessment Scale (MAS; short-term, verbal, visual and total memory) were used for assessment of cognition. Patients were divided into two groups according to the presence of a neural connection between injured cingulum and brainstem cholinergic nuclei. Eight patients who had a neural connection between injured cingulum and brainstem cholinergic nuclei showed better short-term memory on MAS than 12 patients who did not (p < 0.05). However, other results of neuropsychological testing showed no significant difference (p > 0.05). Better short-term memory in patients who had the neural connection between injured cingulum and brainstem cholinergic nuclei appears to have been attributed to the presence of cholinergic innervation to the cerebral cortex through the neural connection instead of the injured anterior cingulum. The neural connection appears to compensate for the injured anterior cingulum in obtaining cholinergic innervation.

  18. Intrinsic connectivity of neural networks in the awake rabbit.

    PubMed

    Schroeder, Matthew P; Weiss, Craig; Procissi, Daniel; Disterhoft, John F; Wang, Lei

    2016-04-01

    The way in which the brain is functionally connected into different networks has emerged as an important research topic in order to understand normal neural processing and signaling. Since some experimental manipulations are difficult or unethical to perform in humans, animal models are better suited to investigate this topic. Rabbits are a species that can undergo MRI scanning in an awake and conscious state with minimal preparation and habituation. In this study, we characterized the intrinsic functional networks of the resting New Zealand White rabbit brain using BOLD fMRI data. Group independent component analysis revealed seven networks similar to those previously found in humans, non-human primates and/or rodents including the hippocampus, default mode, cerebellum, thalamus, and visual, somatosensory, and parietal cortices. For the first time, the intrinsic functional networks of the resting rabbit brain have been elucidated demonstrating the rabbit's applicability as a translational animal model. Without the confounding effects of anesthetics or sedatives, future experiments may employ rabbits to understand changes in neural connectivity and brain functioning as a result of experimental manipulation (e.g., temporary or permanent network disruption, learning-related changes, and drug administration). Copyright © 2016 Elsevier Inc. All rights reserved.

  19. Abnormal ventral tegmental area-anterior cingulate cortex connectivity in Parkinson's disease with depression.

    PubMed

    Wei, Luqing; Hu, Xiao; Yuan, Yonggui; Liu, Weiguo; Chen, Hong

    2018-07-16

    Neuropathology suggests that Parkinson's disease (PD) with depression may involve a progressive degeneration of the nigrostriatal and mesocorticolimbic dopaminergic systems. Previous positron emission tomography (PET) and single-photon emission computed tomography (SPECT) studies have shown that dopamine changes in individual brain regions constituting the nigrostriatal and mesocorticolimbic circuits are associated with depression in PD. However, few studies have been conducted on the circuit-level alterations in this disease. The present study used resting-state fMRI and seed-based functional connectivity of putative dopaminergic midbrain regions (i.e., substantia nigra (SN) and ventral tegmental area (VTA)) to investigate the circuit-related abnormalities in PD with depression. The results showed that depressed PD (DPD) patients relative to healthy controls (HC) and non-depressed PD (NDPD) patients had increased functional connectivity between VTA and anterior cingulate cortex (ACC), demonstrating that dysfunctional mesocorticolimbic dopaminergic neurotransmission may be associated with depression in PD. Compared with HC, DPD and NDPD patients showed increased functional connectivity from SN to sensorimotor cortex, validating that alterations in the nigrostriatal circuitry could be responsible for cardinal motor features in PD. In addition, aberrant connectivity between VTA and ACC was correlated with the severity of depression in PD patients, further supporting that abnormal mesocorticolimbic system may account for depressive symptoms in PD. These results have provided potential circuit-level biomarkers of depression in PD, and suggested that resting state functional connectivity of midbrain dopaminergic nuclei may be useful for understanding the underlying pathology in PD with depression. Copyright © 2018 Elsevier B.V. All rights reserved.

  20. Multi-Connection Pattern Analysis: Decoding the representational content of neural communication.

    PubMed

    Li, Yuanning; Richardson, Robert Mark; Ghuman, Avniel Singh

    2017-11-15

    The lack of multivariate methods for decoding the representational content of interregional neural communication has left it difficult to know what information is represented in distributed brain circuit interactions. Here we present Multi-Connection Pattern Analysis (MCPA), which works by learning mappings between the activity patterns of the populations as a factor of the information being processed. These maps are used to predict the activity from one neural population based on the activity from the other population. Successful MCPA-based decoding indicates the involvement of distributed computational processing and provides a framework for probing the representational structure of the interaction. Simulations demonstrate the efficacy of MCPA in realistic circumstances. In addition, we demonstrate that MCPA can be applied to different signal modalities to evaluate a variety of hypothesis associated with information coding in neural communications. We apply MCPA to fMRI and human intracranial electrophysiological data to provide a proof-of-concept of the utility of this method for decoding individual natural images and faces in functional connectivity data. We further use a MCPA-based representational similarity analysis to illustrate how MCPA may be used to test computational models of information transfer among regions of the visual processing stream. Thus, MCPA can be used to assess the information represented in the coupled activity of interacting neural circuits and probe the underlying principles of information transformation between regions. Copyright © 2017 Elsevier Inc. All rights reserved.

  1. What Can Psychiatric Disorders Tell Us about Neural Processing of the Self?

    PubMed

    Zhao, Weihua; Luo, Lizhu; Li, Qin; Kendrick, Keith M

    2013-01-01

    Many psychiatric disorders are associated with abnormal self-processing. While these disorders also have a wide-range of complex, and often heterogeneous sets of symptoms involving different cognitive, emotional, and motor domains, an impaired sense of self can contribute to many of these. Research investigating self-processing in healthy subjects has facilitated identification of changes in specific neural circuits which may cause altered self-processing in psychiatric disorders. While there is evidence for altered self-processing in many psychiatric disorders, here we will focus on four of the most studied ones, schizophrenia, autism spectrum disorder (ASD), major depression, and borderline personality disorder (BPD). We review evidence for dysfunction in two different neural systems implicated in self-processing, namely the cortical midline system (CMS) and the mirror neuron system (MNS), as well as contributions from altered inter-hemispheric connectivity (IHC). We conclude that while abnormalities in frontal-parietal activity and/or connectivity in the CMS are common to all four disorders there is more disruption of integration between frontal and parietal regions resulting in a shift toward parietal control in schizophrenia and ASD which may contribute to the greater severity and delusional aspects of their symptoms. Abnormalities in the MNS and in IHC are also particularly evident in schizophrenia and ASD and may lead to disturbances in sense of agency and the physical self in these two disorders. A better future understanding of how changes in the neural systems sub-serving self-processing contribute to different aspects of symptom abnormality in psychiatric disorders will require that more studies carry out detailed individual assessments of altered self-processing in conjunction with measurements of neural functioning.

  2. Abnormal functional brain connectivity and personality traits in myotonic dystrophy type 1.

    PubMed

    Serra, Laura; Silvestri, Gabriella; Petrucci, Antonio; Basile, Barbara; Masciullo, Marcella; Makovac, Elena; Torso, Mario; Spanò, Barbara; Mastropasqua, Chiara; Harrison, Neil A; Bianchi, Maria L E; Giacanelli, Manlio; Caltagirone, Carlo; Cercignani, Mara; Bozzali, Marco

    2014-05-01

    Myotonic dystrophy type 1 (DM1), the most common muscular dystrophy observed in adults, is a genetic multisystem disorder affecting several other organs besides skeletal muscle, including the brain. Cognitive and personality abnormalities have been reported; however, no studies have investigated brain functional networks and their relationship with personality traits/disorders in patients with DM1. To use resting-state functional magnetic resonance imaging to assess the potential relationship between personality traits/disorders and changes to functional connectivity within the default mode network (DMN) in patients with DM1. We enrolled 27 patients with genetically confirmed DM1 and 16 matched healthy control individuals. Patients underwent personality assessment using clinical interview and Minnesota Multiphasic Personality Inventory-2 administration; all participants underwent resting-state functional magnetic resonance imaging. Investigations were conducted at the Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Catholic University of Sacred Heart, and Azienda Ospedaliera San Camillo Forlanini. Resting-state functional magnetic resonance imaging. Measures of personality traits in patients and changes in functional connectivity within the DMN in patients and controls. Changes in functional connectivity and atypical personality traits in patients were correlated. We combined results obtained from the Minnesota Multiphasic Personality Inventory-2 and clinical interview to identify a continuum of atypical personality profiles ranging from schizotypal personality traits to paranoid personality disorder within our DM1 patients. We also demonstrated an increase in functional connectivity in the bilateral posterior cingulate and left parietal DMN nodes in DM1 patients compared with controls. Moreover, patients with DM1 showed strong associations between DMN functional connectivity and schizotypal-paranoid traits. Our findings provide novel

  3. Modeling neural circuits in Parkinson's disease.

    PubMed

    Psiha, Maria; Vlamos, Panayiotis

    2015-01-01

    Parkinson's disease (PD) is caused by abnormal neural activity of the basal ganglia which are connected to the cerebral cortex in the brain surface through complex neural circuits. For a better understanding of the pathophysiological mechanisms of PD, it is important to identify the underlying PD neural circuits, and to pinpoint the precise nature of the crucial aberrations in these circuits. In this paper, the general architecture of a hybrid Multilayer Perceptron (MLP) network for modeling the neural circuits in PD is presented. The main idea of the proposed approach is to divide the parkinsonian neural circuitry system into three discrete subsystems: the external stimuli subsystem, the life-threatening events subsystem, and the basal ganglia subsystem. The proposed model, which includes the key roles of brain neural circuit in PD, is based on both feed-back and feed-forward neural networks. Specifically, a three-layer MLP neural network with feedback in the second layer was designed. The feedback in the second layer of this model simulates the dopamine modulatory effect of compacta on striatum.

  4. Abnormal neural precursor cell regulation in the early postnatal Fragile X mouse hippocampus.

    PubMed

    Sourial, Mary; Doering, Laurie C

    2017-07-01

    The regulation of neural precursor cells (NPCs) is indispensable for a properly functioning brain. Abnormalities in NPC proliferation, differentiation, survival, or integration have been linked to various neurological diseases including Fragile X syndrome. Yet, no studies have examined NPCs from the early postnatal Fragile X mouse hippocampus despite the importance of this developmental time point, which marks the highest expression level of FMRP, the protein missing in Fragile X, in the rodent hippocampus and is when hippocampal NPCs have migrated to the dentate gyrus (DG) to give rise to lifelong neurogenesis. In this study, we examined NPCs from the early postnatal hippocampus and DG of Fragile X mice (Fmr1-KO). Immunocytochemistry on neurospheres showed increased Nestin expression and decreased Ki67 expression, which collectively indicated aberrant NPC biology. Intriguingly, flow cytometric analysis of the expression of the antigens CD15, CD24, CD133, GLAST, and PSA-NCAM showed a decreased proportion of neural stem cells (GLAST + CD15 + CD133 + ) and an increased proportion of neuroblasts (PSA-NCAM + CD15 + ) in the DG of P7 Fmr1-KO mice. This was mirrored by lower expression levels of Nestin and the mitotic marker phospho-histone H3 in vivo in the P9 hippocampus, as well as a decreased proportion of cells in the G 2 /M phases of the P7 DG. Thus, the absence of FMRP leads to fewer actively cycling NPCs, coinciding with a decrease in neural stem cells and an increase in neuroblasts. Together, these results show the importance of FMRP in the developing hippocampal formation and suggest abnormalities in cell cycle regulation in Fragile X. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

  5. Estimate the effective connectivity in multi-coupled neural mass model using particle swarm optimization

    NASA Astrophysics Data System (ADS)

    Shan, Bonan; Wang, Jiang; Deng, Bin; Zhang, Zhen; Wei, Xile

    2017-03-01

    Assessment of the effective connectivity among different brain regions during seizure is a crucial problem in neuroscience today. As a consequence, a new model inversion framework of brain function imaging is introduced in this manuscript. This framework is based on approximating brain networks using a multi-coupled neural mass model (NMM). NMM describes the excitatory and inhibitory neural interactions, capturing the mechanisms involved in seizure initiation, evolution and termination. Particle swarm optimization method is used to estimate the effective connectivity variation (the parameters of NMM) and the epileptiform dynamics (the states of NMM) that cannot be directly measured using electrophysiological measurement alone. The estimated effective connectivity includes both the local connectivity parameters within a single region NMM and the remote connectivity parameters between multi-coupled NMMs. When the epileptiform activities are estimated, a proportional-integral controller outputs control signal so that the epileptiform spikes can be inhibited immediately. Numerical simulations are carried out to illustrate the effectiveness of the proposed framework. The framework and the results have a profound impact on the way we detect and treat epilepsy.

  6. Neural activity, neural connectivity, and the processing of emotionally valenced information in older adults: links with life satisfaction.

    PubMed

    Waldinger, Robert J; Kensinger, Elizabeth A; Schulz, Marc S

    2011-09-01

    This study examines whether differences in late-life well-being are linked to how older adults encode emotionally valenced information. Using fMRI with 39 older adults varying in life satisfaction, we examined how viewing positive and negative images would affect activation and connectivity of an emotion-processing network. Participants engaged most regions within this network more robustly for positive than for negative images, but within the PFC this effect was moderated by life satisfaction, with individuals higher in satisfaction showing lower levels of activity during the processing of positive images. Participants high in satisfaction showed stronger correlations among network regions-particularly between the amygdala and other emotion processing regions-when viewing positive, as compared with negative, images. Participants low in satisfaction showed no valence effect. Findings suggest that late-life satisfaction is linked with how emotion-processing regions are engaged and connected during processing of valenced information. This first demonstration of a link between neural recruitment and late-life well-being suggests that differences in neural network activation and connectivity may account for the preferential encoding of positive information seen in some older adults.

  7. Neural Activity, Neural Connectivity, and the Processing of Emotionally-Valenced Information in Older Adults: Links with Life Satisfaction

    PubMed Central

    Waldinger, Robert J.; Kensinger, Elizabeth A.; Schulz, Marc S.

    2013-01-01

    This study examines whether differences in late-life well-being are linked to how older adults encode emotionally-valenced information. Using fMRI with 39 older adults varying in life satisfaction, we examined how viewing positive and negative images affected activation and connectivity of an emotion-processing network. Participants engaged most regions within this network more robustly for positive than for negative images, but within the PFC this effect was moderated by life satisfaction, with individuals higher in satisfaction showing lower levels of activity during the processing of positive images. Participants high in satisfaction showed stronger correlations among network regions – particularly between the amygdala and other emotion processing regions – when viewing positive as compared to negative images. Participants low in satisfaction showed no valence effect. Findings suggest that late-life satisfaction is linked with how emotion-processing regions are engaged and connected during processing of valenced information. This first demonstration of a link between neural recruitment and late-life well-being suggests that differences in neural network activation and connectivity may account for the preferential encoding of positive information seen in some older adults. PMID:21590504

  8. Neural connectivity of the anterior body of the fornix in the human brain: diffusion tensor imaging study.

    PubMed

    Jang, Sung Ho; Kwon, Hyeok Gyu

    2014-01-24

    A few studies have reported on the neural connectivity of the fornix in the human brain, however, little is known about the neural connectivity of the anterior body of the fornix. In this study, we used diffusion tensor imaging in investigation of the neural connectivity of the anterior body of the fornix in normal subjects. Forty healthy subjects were recruited for this study. A seed region of interest was placed on the anterior body of the fornix using the FMRIB Software Library. Connectivity was defined as the incidence of connection between the anterior body of the fornix and any neural structure of the brain at the threshold of 5, 25, and 50 streamlines. In all subjects, the anterior body of the fornix showed 100% connectivity to the anterior commissure and hypothalamus at thresholds of 5, 25, and 50. On the other hand, regarding the thresholds of 5, 25, and 50, the anterior body of the fornix showed connectivity to the septal forebrain region (53.8, 23.8, and 15.0%), frontal lobe via anterior commissure (41.3,12.5, and 10.0%), medial temporal lobe (85.0,66.3, and 62.5%), lateral temporal lobe (75.0, 56.3, and 35.0%), occipital lobe (21.3, 5.0, and 1.3%), frontal lobe via septum pellucidum (28.8, 13.8, and 8.8%), tegmentum of midbrain (7.5, 5.0, and 0%), tectum of midbrain (2.5,0, and 0%), and tegmentum of pons (5.0,0, and 0%). The anterior body of the fornix showed high connectivity with the anterior commissure and hypothalamus, and brain areas relevant to cholinergic nuclei (the septal forebrain region and brainstem) and memory function (the medial temporal lobe). Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  9. Connectivity inference from neural recording data: Challenges, mathematical bases and research directions.

    PubMed

    Magrans de Abril, Ildefons; Yoshimoto, Junichiro; Doya, Kenji

    2018-06-01

    This article presents a review of computational methods for connectivity inference from neural activity data derived from multi-electrode recordings or fluorescence imaging. We first identify biophysical and technical challenges in connectivity inference along the data processing pipeline. We then review connectivity inference methods based on two major mathematical foundations, namely, descriptive model-free approaches and generative model-based approaches. We investigate representative studies in both categories and clarify which challenges have been addressed by which method. We further identify critical open issues and possible research directions. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  10. Anhedonia correlates with abnormal functional connectivity of the superior temporal gyrus and the caudate nucleus in patients with first-episode drug-naive major depressive disorder.

    PubMed

    Yang, Xin-Hua; Tian, Kai; Wang, Dong-Fang; Wang, Yi; Cheung, Eric F C; Xie, Guang-Rong; Chan, Raymond C K

    2017-08-15

    Recent empirical findings have suggested that imbalanced neural networks may underlie the pathophysiology of major depressive disorder (MDD). However, the contribution of the superior temporal gyrus (STG) and the caudate nucleus to its pathophysiology remains unclear. Functional magnetic resonance imaging (MRI) date were acquired from 40 patients with first-episode drug-naive MDD and 36 matched healthy controls during wakeful rest. We used whole-brain voxel-wise statistical maps to quantify within-group resting state functional connectivity (RSFC) and between-group differences of bilateral caudate and STG seeds. Compared with healthy controls, first-episode MDD patients were found to have reduced connectivity between the ventral caudate and several brain regions including the superior frontal gyrus (SFG), the superior parietal lobule (SPL) and the middle temporal gyrus (MTG), as well as increased connectivity with the cuneus. We also found increased connectivity between the left STG and the precuneus, the angular gyrus and the cuneus. Moreover, we found that increased anhedonia severity was correlated with the magnitude of ventral caudate functional connectivity with the cuneus and the MTG in MDD patients. Due to our small sample size, we did not correct the statistical threshold in the correlation analyses between clinical variables and connectivity abnormalities. The present study suggests that anhedonia is mainly associated with altered ventral caudate-cortical connectivity and highlights the importance of the ventral caudate in the neurobiology of MDD. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. Abnormalities in hemispheric specialization of caudate nucleus connectivity in schizophrenia

    PubMed Central

    Mueller, Sophia; Wang, Danhong; Pan, Ruiqi; Holt, Daphne J.; Liu, Hesheng

    2015-01-01

    Importance Hemispheric specialization of the human brain is a marker of successful neurodevelopment. Altered brain asymmetry that has been repeatedly reported in schizophrenia may represent consequences of disrupted neurodevelopment in the disorder. However, a complete picture of functional specialization in the schizophrenic brain and its connectional substrates are yet to be unveiled. Objective We aimed to quantify intrinsic hemispheric specialization at a cortical and subcortical level and to reveal potential disease effects in schizophrenia. Design/Participants Resting-state functional connectivity MRI has been previously used to quantitatively measure hemispheric specialization in healthy subjects, in a reliable manner. Here we quantified the intrinsic hemispheric specialization at the whole brain level in 31 patients with schizophrenia and 37 demographically matched healthy control subjects using resting-state functional connectivity MRI. Results The caudate nucleus, and cortical regions with connections to the caudate nucleus, showed markedly abnormal hemispheric specialization in schizophrenia. Compared to healthy controls, patients exhibited weaker specialization in the left, but the opposite pattern in the right, caudate nucleus. Schizophrenia patients also displayed a disruption of the inter-hemispheric coordination among the cortical regions with connections to the caudate nucleus. A linear classifier based on the specialization of the caudate nucleus distinguished patients from controls with a classification accuracy of 74%. Conclusions and Relevance These data suggested that hemispheric specialization could serve as a potential imaging biomarker of schizophrenia that, compared to task-based fMRI measures, is less prone to the confounding effects of variation in task compliance, cognitive ability, and command of language. PMID:25830688

  12. Anisotropic connectivity implements motion-based prediction in a spiking neural network.

    PubMed

    Kaplan, Bernhard A; Lansner, Anders; Masson, Guillaume S; Perrinet, Laurent U

    2013-01-01

    Predictive coding hypothesizes that the brain explicitly infers upcoming sensory input to establish a coherent representation of the world. Although it is becoming generally accepted, it is not clear on which level spiking neural networks may implement predictive coding and what function their connectivity may have. We present a network model of conductance-based integrate-and-fire neurons inspired by the architecture of retinotopic cortical areas that assumes predictive coding is implemented through network connectivity, namely in the connection delays and in selectiveness for the tuning properties of source and target cells. We show that the applied connection pattern leads to motion-based prediction in an experiment tracking a moving dot. In contrast to our proposed model, a network with random or isotropic connectivity fails to predict the path when the moving dot disappears. Furthermore, we show that a simple linear decoding approach is sufficient to transform neuronal spiking activity into a probabilistic estimate for reading out the target trajectory.

  13. Neural connectivity of the posterior body of the fornix in the human brain: diffusion tensor imaging study.

    PubMed

    Jang, Sung Ho; Kwon, Hyeok Gyu

    2013-08-09

    Little is known about the neural connectivity of the fornix in the human brain. In the current study, using diffusion tensor imaging, we attempted to investigate the neural connectivity of the posterior body of the fornix in the normal human brain. A total of 43 healthy subjects were recruited for this study. DTIs were acquired using a sensitivity-encoding head coil at 1.5T. For connectivity of the posterior body of the fornix, a seed region of interest was used on the posterior body of the fornix. Connectivity was defined as the incidence of connection between the posterior body of the fornix and any neural structure of the brain at the threshold of 5, 25, and 50 streamline. At the threshold of 5, 25, and 50, the posterior body of the fornix showed connectivity to the precentral gyrus (37%, 19%, and 15%), the postcentral gyrus (25%, 11.5%, and 7%), the posterior parietal cortex (16.5%, 5%, and 5%), the brainstem (12%, 4.5%, and 3.5%), the crus of the fornix (34%, 10.5%, and 7%), the contralateral splenium of the corpus callosum (12.5%, 5%, and 0%), and the ipsilateral splenium of the CC (69.8%%, 33.7%, and 23.3%), respectively. Findings of this study showed that the posterior body of the fornix had connectivity with the cerebral cortex, the brainstem, the fornical crus, and the contralateral splenium through the splenium of the corpus callosum in normal subjects. We believe that the results of this study would be helpful in investigation of the neural network related to memory and recovery mechanisms following fornical injury in the human brain. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  14. Neural connectivity during reward expectation dissociates psychopathic criminals from non-criminal individuals with high impulsive/antisocial psychopathic traits

    PubMed Central

    von Borries, Katinka; Volman, Inge; Bulten, Berend Hendrik; Cools, Roshan; Verkes, Robbert-Jan

    2016-01-01

    Criminal behaviour poses a big challenge for society. A thorough understanding of the neurobiological mechanisms underlying criminality could optimize its prevention and management. Specifically,elucidating the neural mechanisms underpinning reward expectation might be pivotal to understanding criminal behaviour. So far no study has assessed reward expectation and its mechanisms in a criminal sample. To fill this gap, we assessed reward expectation in incarcerated, psychopathic criminals. We compared this group to two groups of non-criminal individuals: one with high levels and another with low levels of impulsive/antisocial traits. Functional magnetic resonance imaging was used to quantify neural responses to reward expectancy. Psychophysiological interaction analyses were performed to examine differences in functional connectivity patterns of reward-related regions. The data suggest that overt criminality is characterized, not by abnormal reward expectation per se, but rather by enhanced communication between reward-related striatal regions and frontal brain regions. We establish that incarcerated psychopathic criminals can be dissociated from non-criminal individuals with comparable impulsive/antisocial personality tendencies based on the degree to which reward-related brain regions interact with brain regions that control behaviour. The present results help us understand why some people act according to their impulsive/antisocial personality while others are able to behave adaptively despite reward-related urges. PMID:27217111

  15. Altered Appetitive Conditioning and Neural Connectivity in Subjects With Compulsive Sexual Behavior.

    PubMed

    Klucken, Tim; Wehrum-Osinsky, Sina; Schweckendiek, Jan; Kruse, Onno; Stark, Rudolf

    2016-04-01

    There has been growing interest in a better understanding of the etiology of compulsive sexual behavior (CSB). It is assumed that facilitated appetitive conditioning might be an important mechanism for the development and maintenance of CSB, but no study thus far has investigated these processes. To explore group differences in neural activity associated with appetitive conditioning and connectivity in subjects with CSB and a healthy control group. Two groups (20 subjects with CSB and 20 controls) were exposed to an appetitive conditioning paradigm during a functional magnetic resonance imaging experiment, in which a neutral stimulus (CS+) predicted visual sexual stimuli and a second stimulus (CS-) did not. Blood oxygen level-dependent responses and psychophysiologic interaction. As a main result, we found increased amygdala activity during appetitive conditioning for the CS+ vs the CS- and decreased coupling between the ventral striatum and prefrontal cortex in the CSB vs control group. The findings show that neural correlates of appetitive conditioning and neural connectivity are altered in patients with CSB. The increased amygdala activation might reflect facilitated conditioning processes in patients with CSB. In addition, the observed decreased coupling could be interpreted as a marker for impaired emotion regulation success in this group. Copyright © 2016 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

  16. Resting State fMRI Functional Connectivity-Based Classification Using a Convolutional Neural Network Architecture

    PubMed Central

    Meszlényi, Regina J.; Buza, Krisztian; Vidnyánszky, Zoltán

    2017-01-01

    Machine learning techniques have become increasingly popular in the field of resting state fMRI (functional magnetic resonance imaging) network based classification. However, the application of convolutional networks has been proposed only very recently and has remained largely unexplored. In this paper we describe a convolutional neural network architecture for functional connectome classification called connectome-convolutional neural network (CCNN). Our results on simulated datasets and a publicly available dataset for amnestic mild cognitive impairment classification demonstrate that our CCNN model can efficiently distinguish between subject groups. We also show that the connectome-convolutional network is capable to combine information from diverse functional connectivity metrics and that models using a combination of different connectivity descriptors are able to outperform classifiers using only one metric. From this flexibility follows that our proposed CCNN model can be easily adapted to a wide range of connectome based classification or regression tasks, by varying which connectivity descriptor combinations are used to train the network. PMID:29089883

  17. Resting State fMRI Functional Connectivity-Based Classification Using a Convolutional Neural Network Architecture.

    PubMed

    Meszlényi, Regina J; Buza, Krisztian; Vidnyánszky, Zoltán

    2017-01-01

    Machine learning techniques have become increasingly popular in the field of resting state fMRI (functional magnetic resonance imaging) network based classification. However, the application of convolutional networks has been proposed only very recently and has remained largely unexplored. In this paper we describe a convolutional neural network architecture for functional connectome classification called connectome-convolutional neural network (CCNN). Our results on simulated datasets and a publicly available dataset for amnestic mild cognitive impairment classification demonstrate that our CCNN model can efficiently distinguish between subject groups. We also show that the connectome-convolutional network is capable to combine information from diverse functional connectivity metrics and that models using a combination of different connectivity descriptors are able to outperform classifiers using only one metric. From this flexibility follows that our proposed CCNN model can be easily adapted to a wide range of connectome based classification or regression tasks, by varying which connectivity descriptor combinations are used to train the network.

  18. Spatial working memory in neurofibromatosis 1: Altered neural activity and functional connectivity.

    PubMed

    Ibrahim, Amira F A; Montojo, Caroline A; Haut, Kristen M; Karlsgodt, Katherine H; Hansen, Laura; Congdon, Eliza; Rosser, Tena; Bilder, Robert M; Silva, Alcino J; Bearden, Carrie E

    2017-01-01

    Neurofibromatosis Type 1 (NF1) is a genetic disorder that disrupts central nervous system development and neuronal function. Cognitively, NF1 is characterized by difficulties with executive control and visuospatial abilities. Little is known about the neural substrates underlying these deficits. The current study utilized Blood-Oxygen-Level-Dependent (BOLD) functional MRI (fMRI) to explore the neural correlates of spatial working memory (WM) deficits in patients with NF1. BOLD images were acquired from 23 adults with NF1 (age M  = 32.69; 61% male) and 25 matched healthy controls (age M  = 33.08; 64% male) during an in-scanner visuo-spatial WM task. Whole brain functional and psycho-physiological interaction analyses were utilized to investigate neural activity and functional connectivity, respectively, during visuo-spatial WM performance. Participants also completed behavioral measures of spatial reasoning and verbal WM. Relative to healthy controls, participants with NF1 showed reduced recruitment of key components of WM circuitry, the left dorsolateral prefrontal cortex and right parietal cortex. In addition, healthy controls exhibited greater simultaneous deactivation between the posterior cingulate cortex (PCC) and temporal regions than NF1 patients. In contrast, NF1 patients showed greater PCC and bilateral parietal connectivity with visual cortices as well as between the PCC and the cerebellum. In NF1 participants, increased functional coupling of the PCC with frontal and parietal regions was associated with better spatial reasoning and WM performance, respectively; these relationships were not observed in controls. Dysfunctional engagement of WM circuitry, and aberrant functional connectivity of 'task-negative' regions in NF1 patients may underlie spatial WM difficulties characteristic of the disorder.

  19. Neural Correlates and Connectivity underlying Stress-related Impulse Control Difficulties in Alcoholism

    PubMed Central

    Seo, Dongju; Lacadie, Cheryl M.; Sinha, Rajita

    2016-01-01

    BACKGROUND Stress triggers impulsive and addictive behaviors, and alcoholism has been frequently associated with increased stress sensitivity and impulse control problems. However, neural correlates underlying the link between alcoholism and impulsivity in the context of stress in patients with alcohol use disorders (AUD) have not been well studied. METHOD The current study investigated neural correlates and connectivity patterns associated with impulse control difficulties in abstinent AUD patients. Using functional magnetic resonance imaging, brain responses of 37 AUD inpatients and 37 demographically-matched healthy controls were examined during brief individualized imagery trials of stress, alcohol-cue and neutral-relaxing conditions. Stress-related impulsivity was measured using a subscale score of impulse control problems from Difficulties in Emotion Regulation Scale (DERS). RESULTS Impulse control difficulties in AUD patients were significantly associated with hypoactive response to stress in the ventromedial prefrontal cortex (VmPFC), right caudate, and left lateral PFC (LPFC) compared to the neutral condition (p<0.01, whole-brain corrected). These regions were used as seed regions to further examine the connectivity patterns with other brain regions. With the VmPFC seed, AUD patients showed reduced connectivity with the anterior cingulate cortex (ACC) compared to controls, which are core regions of emotion regulation, suggesting AUD patients’ decreased ability to modulate emotional response under distressed state. With the right caudate seed, patients showed increased connectivity with the right motor cortex, suggesting increased tendency toward habitually driven behaviors. With the left LPFC seed, decreased connectivity with the dorsomedial PFC (DmPFC), but increased connectivity with sensory and motor cortices were found in AUD patients compared to controls (p<0.05, whole-brain corrected). Reduced connectivity between the left LPFC and DmPFC was

  20. Neural Correlates and Connectivity Underlying Stress-Related Impulse Control Difficulties in Alcoholism.

    PubMed

    Seo, Dongju; Lacadie, Cheryl M; Sinha, Rajita

    2016-09-01

    Stress triggers impulsive and addictive behaviors, and alcoholism has been frequently associated with increased stress sensitivity and impulse control problems. However, neural correlates underlying the link between alcoholism and impulsivity in the context of stress in patients with alcohol use disorders (AUD) have not been well studied. This study investigated neural correlates and connectivity patterns associated with impulse control difficulties in abstinent AUD patients. Using functional magnetic resonance imaging, brain responses of 37 AUD inpatients, and 37 demographically matched healthy controls were examined during brief individualized imagery trials of stress, alcohol cue, and neutral-relaxing conditions. Stress-related impulsivity was measured using a subscale score of impulse control problems from Difficulties in Emotion Regulation Scale. Impulse control difficulties in AUD patients were significantly associated with hypo-active response to stress in the ventromedial prefrontal cortex (VmPFC), right caudate, and left lateral PFC (LPFC) compared to the neutral condition (p < 0.01, whole-brain corrected). These regions were used as seed regions to further examine the connectivity patterns with other brain regions. With the VmPFC seed, AUD patients showed reduced connectivity with the anterior cingulate cortex compared to controls, which are core regions of emotion regulation, suggesting AUD patients' decreased ability to modulate emotional response under distressed state. With the right caudate seed, patients showed increased connectivity with the right motor cortex, suggesting increased tendency toward habitually driven behaviors. With the left LPFC seed, decreased connectivity with the dorsomedial PFC (DmPFC), but increased connectivity with sensory and motor cortices were found in AUD patients compared to controls (p < 0.05, whole-brain corrected). Reduced connectivity between the left LPFC and DmPFC was further associated with increased stress

  1. Functional connectivity abnormalities and associated cognitive deficits in fetal alcohol Spectrum disorders (FASD).

    PubMed

    Wozniak, Jeffrey R; Mueller, Bryon A; Mattson, Sarah N; Coles, Claire D; Kable, Julie A; Jones, Kenneth L; Boys, Christopher J; Lim, Kelvin O; Riley, Edward P; Sowell, Elizabeth R

    2017-10-01

    Consistent with well-documented structural and microstructural abnormalities in prenatal alcohol exposure (PAE), recent studies suggest that functional connectivity (FC) may also be disrupted. We evaluated whole-brain FC in a large multi-site sample, examined its cognitive correlates, and explored its potential to objectively identify neurodevelopmental abnormality in individuals without definitive dysmorphic features. Included were 75 children with PAE and 68 controls from four sites. All participants had documented heavy prenatal alcohol exposure. All underwent a formal evaluation of physical anomalies and dysmorphic facial features. MRI data were collected using modified matched protocols on three platforms (Siemens, GE, and Philips). Resting-state FC was examined using whole-brain graph theory metrics to characterize each individual's connectivity. Although whole-brain FC metrics did not discriminate prenatally-exposed from unexposed overall, atypical FC (> 1 standard deviation from the grand mean) was significantly more common (2.7 times) in the PAE group vs. In a subset of 55 individuals (PAE and controls) whose dysmorphology examination could not definitively characterize them as either Fetal Alcohol Syndrome (FAS) or non-FAS, atypical FC was seen in 27 % of the PAE group, but 0 % of controls. Across participants, a 1 % difference in local network efficiency was associated with a 36 point difference in global cognitive functioning. Whole-brain FC metrics have potential to identify individuals with objective neurodevelopmental abnormalities from prenatal alcohol exposure. When applied to individuals unable to be classified as FAS or non-FAS from dysmorphology alone, these measures separate prenatally-exposed from non-exposed with high specificity.

  2. Toward Rigorous Parameterization of Underconstrained Neural Network Models Through Interactive Visualization and Steering of Connectivity Generation

    PubMed Central

    Nowke, Christian; Diaz-Pier, Sandra; Weyers, Benjamin; Hentschel, Bernd; Morrison, Abigail; Kuhlen, Torsten W.; Peyser, Alexander

    2018-01-01

    Simulation models in many scientific fields can have non-unique solutions or unique solutions which can be difficult to find. Moreover, in evolving systems, unique final state solutions can be reached by multiple different trajectories. Neuroscience is no exception. Often, neural network models are subject to parameter fitting to obtain desirable output comparable to experimental data. Parameter fitting without sufficient constraints and a systematic exploration of the possible solution space can lead to conclusions valid only around local minima or around non-minima. To address this issue, we have developed an interactive tool for visualizing and steering parameters in neural network simulation models. In this work, we focus particularly on connectivity generation, since finding suitable connectivity configurations for neural network models constitutes a complex parameter search scenario. The development of the tool has been guided by several use cases—the tool allows researchers to steer the parameters of the connectivity generation during the simulation, thus quickly growing networks composed of multiple populations with a targeted mean activity. The flexibility of the software allows scientists to explore other connectivity and neuron variables apart from the ones presented as use cases. With this tool, we enable an interactive exploration of parameter spaces and a better understanding of neural network models and grapple with the crucial problem of non-unique network solutions and trajectories. In addition, we observe a reduction in turn around times for the assessment of these models, due to interactive visualization while the simulation is computed. PMID:29937723

  3. Functional Connectivity with Distinct Neural Networks Tracks Fluctuations in Gain/Loss Framing Susceptibility

    PubMed Central

    Smith, David V.; Sip, Kamila E.; Delgado, Mauricio R.

    2016-01-01

    Multiple large-scale neural networks orchestrate a wide range of cognitive processes. For example, interoceptive processes related to self-referential thinking have been linked to the default-mode network (DMN); whereas exteroceptive processes related to cognitive control have been linked to the executive-control network (ECN). Although the DMN and ECN have been postulated to exert opposing effects on cognition, it remains unclear how connectivity with these spatially overlapping networks contribute to fluctuations in behavior. While previous work has suggested the medial prefrontal cortex (MPFC) is involved in behavioral change following feedback, these observations could be linked to interoceptive processes tied to DMN or exteroceptive processes tied to ECN because MPFC is positioned in both networks. To address this problem, we employed independent component analysis combined with dual-regression functional connectivity analysis. Participants made a series of financial decisions framed as monetary gains or losses. In some sessions, participants received feedback from a peer observing their choices; in other sessions, feedback was not provided. Following feedback, framing susceptibility—indexed as the increase in gambling behavior in loss frames compared to gain frames—was heightened in some participants and diminished in others. We examined whether these individual differences were linked to differences in connectivity by contrasting sessions containing feedback against those that did not contain feedback. We found two key results. As framing susceptibility increased, the MPFC increased connectivity with DMN; in contrast, temporal-parietal junction decreased connectivity with the ECN. Our results highlight how functional connectivity patterns with distinct neural networks contribute to idiosyncratic behavioral changes. PMID:25858445

  4. Functional connectivity with distinct neural networks tracks fluctuations in gain/loss framing susceptibility.

    PubMed

    Smith, David V; Sip, Kamila E; Delgado, Mauricio R

    2015-07-01

    Multiple large-scale neural networks orchestrate a wide range of cognitive processes. For example, interoceptive processes related to self-referential thinking have been linked to the default-mode network (DMN); whereas exteroceptive processes related to cognitive control have been linked to the executive-control network (ECN). Although the DMN and ECN have been postulated to exert opposing effects on cognition, it remains unclear how connectivity with these spatially overlapping networks contribute to fluctuations in behavior. While previous work has suggested the medial-prefrontal cortex (MPFC) is involved in behavioral change following feedback, these observations could be linked to interoceptive processes tied to DMN or exteroceptive processes tied to ECN because MPFC is positioned in both networks. To address this problem, we employed independent component analysis combined with dual-regression functional connectivity analysis. Participants made a series of financial decisions framed as monetary gains or losses. In some sessions, participants received feedback from a peer observing their choices; in other sessions, feedback was not provided. Following feedback, framing susceptibility-indexed as the increase in gambling behavior in loss frames compared to gain frames-was heightened in some participants and diminished in others. We examined whether these individual differences were linked to differences in connectivity by contrasting sessions containing feedback against those that did not contain feedback. We found two key results. As framing susceptibility increased, the MPFC increased connectivity with DMN; in contrast, temporal-parietal junction decreased connectivity with the ECN. Our results highlight how functional connectivity patterns with distinct neural networks contribute to idiosyncratic behavioral changes. © 2015 Wiley Periodicals, Inc.

  5. The implication of salience network abnormalities in young male adult smokers.

    PubMed

    Li, Yangding; Yuan, Kai; Guan, Yanyan; Cheng, Jiadong; Bi, Yanzhi; Shi, Sha; Xue, Ting; Lu, Xiaoqi; Qin, Wei; Yu, Dahua; Tian, Jie

    2017-08-01

    Studying the neural correlates of smoking behaviors in young adulthood is of great importance to improve treatment outcomes. In previous addiction studies, the important roles of the salience network (SN) in drug cue processing and cognitive control have been revealed. Unfortunately, few studies focused on the resting-state functional connectivity and structural integrity abnormalities of SN in young adult smokers, and less is known about its association with smoking behaviors and cognitive control deficits. Thirty-one young male adult smokers and 30 age-, education- and gender-matched nonsmokers participated in this study. The structural and functional connectivity differences of SN were investigated between young adult smokers and nonsmokers by using diffusion tensor imaging (DTI) and resting-state functional connectivity (RSFC), which were then correlated with the smoking behavioral assessments (pack-years and Fagerström Test for Nicotine Dependence (FTND)) as well as impaired cognitive control measured by the Stroop task. Within SN, reduced RSFC and increased fractional anisotropy (FA) were found between the anterior cingulate cortex (ACC) and the right insula in young adult smokers relative to nonsmokers. The RSFC between the ACC and right insula was negatively correlated with the number of errors during the incongruent condition of the Stroop task in young adult smokers. Additionally, the right insula-ACC RSFC was negatively correlated with pack-years in young adult smokers. Our results revealed abnormal RSFC and structural integrity within the SN in young adult smokers, which shed new insights into the neural mechanism of nicotine dependence.

  6. The process of learning in neural net models with Poisson and Gauss connectivities.

    PubMed

    Sivridis, L; Kotini, A; Anninos, P

    2008-01-01

    In this study we examined the dynamic behavior of isolated and non-isolated neural networks with chemical markers that follow a Poisson or Gauss distribution of connectivity. The Poisson distribution shows higher activity in comparison to the Gauss distribution although the latter has more connections that obliterated due to randomness. We examined 57 hematoxylin and eosin stained sections from an equal number of autopsy specimens with a diagnosis of "cerebral matter within normal limits". Neural counting was carried out in 5 continuous optic fields, with the use of a simple optical microscope connected to a computer (software programmer Nikon Act-1 vers-2). The number of neurons that corresponded to a surface was equal to 0.15 mm(2). There was a gradual reduction in the number of neurons as age increased. A mean value of 45.8 neurons /0.15 mm(2) was observed within the age range 21-25, 33 neurons /0.15 mm(2) within the age range 41-45, 19.3 neurons /0.15 mm(2) within the age range 56-60 years. After the age of 60 it was observed that the number of neurons per unit area stopped decreasing. A correlation was observed between these experimental findings and the theoretical neural model developed by professor Anninos and his colleagues. Equivalence between the mean numbers of neurons of the above mentioned age groups and the highest possible number of synaptic connections per neuron (highest number of synaptic connections corresponded to the age group 21-25) was created. We then used both inhibitory and excitatory post-synaptic potentials and applied these values to the Poisson and Gauss distributions, whereas the neuron threshold was varied between 3 and 5. According to the obtained phase diagrams, the hysteresis loops decrease as age increases. These findings were significant as the hysteresis loops can be regarded as the basis for short-term memory.

  7. Resting state functional MRI reveals abnormal network connectivity in neurofibromatosis 1.

    PubMed

    Tomson, Steffie N; Schreiner, Matthew J; Narayan, Manjari; Rosser, Tena; Enrique, Nicole; Silva, Alcino J; Allen, Genevera I; Bookheimer, Susan Y; Bearden, Carrie E

    2015-11-01

    Neurofibromatosis type I (NF1) is a genetic disorder caused by mutations in the neurofibromin 1 gene at locus 17q11.2. Individuals with NF1 have an increased incidence of learning disabilities, attention deficits, and autism spectrum disorders. As a single-gene disorder, NF1 represents a valuable model for understanding gene-brain-behavior relationships. While mouse models have elucidated molecular and cellular mechanisms underlying learning deficits associated with this mutation, little is known about functional brain architecture in human subjects with NF1. To address this question, we used resting state functional connectivity magnetic resonance imaging (rs-fcMRI) to elucidate the intrinsic network structure of 30 NF1 participants compared with 30 healthy demographically matched controls during an eyes-open rs-fcMRI scan. Novel statistical methods were employed to quantify differences in local connectivity (edge strength) and modularity structure, in combination with traditional global graph theory applications. Our findings suggest that individuals with NF1 have reduced anterior-posterior connectivity, weaker bilateral edges, and altered modularity clustering relative to healthy controls. Further, edge strength and modular clustering indices were correlated with IQ and internalizing symptoms. These findings suggest that Ras signaling disruption may lead to abnormal functional brain connectivity; further investigation into the functional consequences of these alterations in both humans and in animal models is warranted. © 2015 Wiley Periodicals, Inc.

  8. Resting state functional MRI reveals abnormal network connectivity in Neurofibromatosis 1

    PubMed Central

    Tomson, S.N.; Schreiner, M.; Narayan, M.; Rosser, Tena; Enrique, Nicole; Silva, Alcino J.; Allen, G.I.; Bookheimer, S.Y.; Bearden, C.E.

    2015-01-01

    Neurofibromatosis type I (NF1) is a genetic disorder caused by mutations in the neurofibromin 1 gene at locus 17q11.2. Individuals with NF1 have an increased incidence of learning disabilities, attention deficits and autism spectrum disorders. As a single gene disorder, NF1 represents a valuable model for understanding gene-brain-behavior relationships. While mouse models have elucidated molecular and cellular mechanisms underlying learning deficits associated with this mutation, little is known about functional brain architecture in human subjects with NF1. To address this question, we used resting state functional connectivity MRI (rs-fcMRI) to elucidate the intrinsic network structure of 30 NF1 participants compared with 30 healthy demographically matched controls during an eyes-open rs-fcMRI scan. Novel statistical methods were employed to quantify differences in local connectivity (edge strength) and modularity structure, in combination with traditional global graph theory applications. Our findings suggest that individuals with NF1 have reduced anterior-posterior connectivity, weaker bilateral edges, and altered modularity clustering relative to healthy controls. Further, edge strength and modular clustering indices were correlated with IQ and internalizing symptoms. These findings suggest that Ras signaling disruption may lead to abnormal functional brain connectivity; further investigation into the functional consequences of these alterations in both humans and in animal models is warranted. PMID:26304096

  9. Artificial neural networks for control of a grid-connected rectifier/inverter under disturbance, dynamic and power converter switching conditions.

    PubMed

    Li, Shuhui; Fairbank, Michael; Johnson, Cameron; Wunsch, Donald C; Alonso, Eduardo; Proaño, Julio L

    2014-04-01

    Three-phase grid-connected converters are widely used in renewable and electric power system applications. Traditionally, grid-connected converters are controlled with standard decoupled d-q vector control mechanisms. However, recent studies indicate that such mechanisms show limitations in their applicability to dynamic systems. This paper investigates how to mitigate such restrictions using a neural network to control a grid-connected rectifier/inverter. The neural network implements a dynamic programming algorithm and is trained by using back-propagation through time. To enhance performance and stability under disturbance, additional strategies are adopted, including the use of integrals of error signals to the network inputs and the introduction of grid disturbance voltage to the outputs of a well-trained network. The performance of the neural-network controller is studied under typical vector control conditions and compared against conventional vector control methods, which demonstrates that the neural vector control strategy proposed in this paper is effective. Even in dynamic and power converter switching environments, the neural vector controller shows strong ability to trace rapidly changing reference commands, tolerate system disturbances, and satisfy control requirements for a faulted power system.

  10. Aberrant Neural Connectivity during Emotional Processing Associated with Posttraumatic Stress

    PubMed Central

    Sadeh, Naomi; Spielberg, Jeffrey M.; Warren, Stacie L.; Miller, Gregory A.; Heller, Wendy

    2014-01-01

    Given the complexity of the brain, characterizing relations among distributed brain regions is likely essential to describing the neural instantiation of posttraumatic stress symptoms. This study examined patterns of functional connectivity among key brain regions implicated in the pathophysiology of posttraumatic stress disorder (PTSD) in 35 trauma-exposed adults using an emotion-word Stroop task. PTSD symptom severity (particularly hyperarousal symptoms) moderated amygdala-mPFC coupling during the processing of unpleasant words, and this moderation correlated positively with reported real-world impairment and amygdala reactivity. Reexperiencing severity moderated hippocampus-insula coupling during pleasant and unpleasant words. Results provide evidence that PTSD symptoms differentially moderate functional coupling during emotional interference and underscore the importance of examining network connectivity in research on PTSD. They suggest that hyperarousal is associated with negative mPFC-amygdala coupling and that reexperiencing is associated with altered insula-hippocampus function, patterns of connectivity that may represent separable indicators of dysfunctional inhibitory control during affective processing. PMID:25419500

  11. Aberrant Neural Connectivity during Emotional Processing Associated with Posttraumatic Stress.

    PubMed

    Sadeh, Naomi; Spielberg, Jeffrey M; Warren, Stacie L; Miller, Gregory A; Heller, Wendy

    2014-11-01

    Given the complexity of the brain, characterizing relations among distributed brain regions is likely essential to describing the neural instantiation of posttraumatic stress symptoms. This study examined patterns of functional connectivity among key brain regions implicated in the pathophysiology of posttraumatic stress disorder (PTSD) in 35 trauma-exposed adults using an emotion-word Stroop task. PTSD symptom severity (particularly hyperarousal symptoms) moderated amygdala-mPFC coupling during the processing of unpleasant words, and this moderation correlated positively with reported real-world impairment and amygdala reactivity. Reexperiencing severity moderated hippocampus-insula coupling during pleasant and unpleasant words. Results provide evidence that PTSD symptoms differentially moderate functional coupling during emotional interference and underscore the importance of examining network connectivity in research on PTSD. They suggest that hyperarousal is associated with negative mPFC-amygdala coupling and that reexperiencing is associated with altered insula-hippocampus function, patterns of connectivity that may represent separable indicators of dysfunctional inhibitory control during affective processing.

  12. Connectivity strategies for higher-order neural networks applied to pattern recognition

    NASA Technical Reports Server (NTRS)

    Spirkovska, Lilly; Reid, Max B.

    1990-01-01

    Different strategies for non-fully connected HONNs (higher-order neural networks) are discussed, showing that by using such strategies an input field of 128 x 128 pixels can be attained while still achieving in-plane rotation and translation-invariant recognition. These techniques allow HONNs to be used with the larger input scenes required for practical pattern-recognition applications. The number of interconnections that must be stored has been reduced by a factor of approximately 200,000 in a T/C case and about 2000 in a Space Shuttle/F-18 case by using regional connectivity. Third-order networks have been simulated using several connection strategies. The method found to work best is regional connectivity. The main advantages of this strategy are the following: (1) it considers features of various scales within the image and thus gets a better sample of what the image looks like; (2) it is invariant to shape-preserving geometric transformations, such as translation and rotation; (3) the connections are predetermined so that no extra computations are necessary during run time; and (4) it does not require any extra storage for recording which connections were formed.

  13. Estimation of effective connectivity using multi-layer perceptron artificial neural network.

    PubMed

    Talebi, Nasibeh; Nasrabadi, Ali Motie; Mohammad-Rezazadeh, Iman

    2018-02-01

    Studies on interactions between brain regions estimate effective connectivity, (usually) based on the causality inferences made on the basis of temporal precedence. In this study, the causal relationship is modeled by a multi-layer perceptron feed-forward artificial neural network, because of the ANN's ability to generate appropriate input-output mapping and to learn from training examples without the need of detailed knowledge of the underlying system. At any time instant, the past samples of data are placed in the network input, and the subsequent values are predicted at its output. To estimate the strength of interactions, the measure of " Causality coefficient " is defined based on the network structure, the connecting weights and the parameters of hidden layer activation function. Simulation analysis demonstrates that the method, called "CREANN" (Causal Relationship Estimation by Artificial Neural Network), can estimate time-invariant and time-varying effective connectivity in terms of MVAR coefficients. The method shows robustness with respect to noise level of data. Furthermore, the estimations are not significantly influenced by the model order (considered time-lag), and the different initial conditions (initial random weights and parameters of the network). CREANN is also applied to EEG data collected during a memory recognition task. The results implicate that it can show changes in the information flow between brain regions, involving in the episodic memory retrieval process. These convincing results emphasize that CREANN can be used as an appropriate method to estimate the causal relationship among brain signals.

  14. Differential Covariance: A New Class of Methods to Estimate Sparse Connectivity from Neural Recordings

    PubMed Central

    Lin, Tiger W.; Das, Anup; Krishnan, Giri P.; Bazhenov, Maxim; Sejnowski, Terrence J.

    2017-01-01

    With our ability to record more neurons simultaneously, making sense of these data is a challenge. Functional connectivity is one popular way to study the relationship of multiple neural signals. Correlation-based methods are a set of currently well-used techniques for functional connectivity estimation. However, due to explaining away and unobserved common inputs (Stevenson, Rebesco, Miller, & Körding, 2008), they produce spurious connections. The general linear model (GLM), which models spike trains as Poisson processes (Okatan, Wilson, & Brown, 2005; Truccolo, Eden, Fellows, Donoghue, & Brown, 2005; Pillow et al., 2008), avoids these confounds. We develop here a new class of methods by using differential signals based on simulated intracellular voltage recordings. It is equivalent to a regularized AR(2) model. We also expand the method to simulated local field potential recordings and calcium imaging. In all of our simulated data, the differential covariance-based methods achieved performance better than or similar to the GLM method and required fewer data samples. This new class of methods provides alternative ways to analyze neural signals. PMID:28777719

  15. Differential Covariance: A New Class of Methods to Estimate Sparse Connectivity from Neural Recordings.

    PubMed

    Lin, Tiger W; Das, Anup; Krishnan, Giri P; Bazhenov, Maxim; Sejnowski, Terrence J

    2017-10-01

    With our ability to record more neurons simultaneously, making sense of these data is a challenge. Functional connectivity is one popular way to study the relationship of multiple neural signals. Correlation-based methods are a set of currently well-used techniques for functional connectivity estimation. However, due to explaining away and unobserved common inputs (Stevenson, Rebesco, Miller, & Körding, 2008 ), they produce spurious connections. The general linear model (GLM), which models spike trains as Poisson processes (Okatan, Wilson, & Brown, 2005 ; Truccolo, Eden, Fellows, Donoghue, & Brown, 2005 ; Pillow et al., 2008 ), avoids these confounds. We develop here a new class of methods by using differential signals based on simulated intracellular voltage recordings. It is equivalent to a regularized AR(2) model. We also expand the method to simulated local field potential recordings and calcium imaging. In all of our simulated data, the differential covariance-based methods achieved performance better than or similar to the GLM method and required fewer data samples. This new class of methods provides alternative ways to analyze neural signals.

  16. Cocaine, Appetitive Memory and Neural Connectivity

    PubMed Central

    Ray, Suchismita

    2013-01-01

    This review examines existing cognitive experimental and brain imaging research related to cocaine addiction. In section 1, previous studies that have examined cognitive processes, such as implicit and explicit memory processes in cocaine users are reported. Next, in section 2, brain imaging studies are reported that have used chronic users of cocaine as study participants. In section 3, several conclusions are drawn. They are: (a) in cognitive experimental literature, no study has examined both implicit and explicit memory processes involving cocaine related visual information in the same cocaine user, (b) neural mechanisms underlying implicit and explicit memory processes for cocaine-related visual cues have not been directly investigated in cocaine users in the imaging literature, and (c) none of the previous imaging studies has examined connectivity between the memory system and craving system in the brain of chronic users of cocaine. Finally, future directions in the field of cocaine addiction are suggested. PMID:25009766

  17. Prevention of congenital abnormalities by periconceptional multivitamin supplementation.

    PubMed Central

    Czeizel, A E

    1993-01-01

    OBJECTIVE--To study the effect of periconceptional multivitamin supplementation on neural tube defects and other congenital abnormality entities. DESIGN--Randomised controlled trial of supplementation with multivitamins and trace elements. SETTING--Hungarian family planning programme. SUBJECTS--4156 pregnancies with known outcome and 3713 infants evaluated in the eighth month of life. INTERVENTIONS--A single tablet of a multivitamin including 0.8 mg of folic acid or trace elements supplement daily for at least one month before conception and at least two months after conception. MAIN OUTCOME MEASURES--Number of major and mild congenital abnormalities. RESULTS--The rate of all major congenital abnormalities was significantly lower in the group given vitamins than in the group given trace elements and this difference cannot be explained totally by the significant reduction of neural tube defects. The rate of major congenital abnormalities other than neural tube defects and genetic syndromes was 9.0/1000 in pregnancies with known outcome in the vitamin group and 16.6/1000 in the trace element group; relative risk 1.85 (95% confidence interval 1.02 to 3.38); difference, 7.6/1000. The rate of all major congenital abnormalities other than neural tube defects and genetic syndromes diagnosed up to the eighth month of life was 14.7/1000 informative pregnancies in the vitamin group and 28.3/1000 in the trace element group; relative risk 1.95 (1.23 to 3.09); difference, 13.6/1000. The rate of some congenital abnormalities was lower in the vitamin group than in the trace element group but the differences for each group of abnormalities were not significant. CONCLUSIONS--Periconceptional multivitamin supplementation can reduce not only the rate of neural tube defects but also the rate of other major non-genetic syndromatic congenital abnormalities. Further studies are needed to differentiate the chance effect and vitamin dependent effect. PMID:8324432

  18. Hydronephrosis in the Wnt5a-ablated kidney is caused by an abnormal ureter-bladder connection.

    PubMed

    Yun, Kangsun; Perantoni, Alan O

    The Wnt5a null mouse is a complex developmental model which, among its several posterior-localized axis defects, exhibits multiple kidney phenotypes, including duplex kidney and loss of the medullary zone. We previously reported that ablation of Wnt5a in nascent mesoderm causes duplex kidney formation as a result of aberrant development of the nephric duct and abnormal extension of intermediate mesoderm. However, these mice also display a loss of the medullary region late in gestation. We have now genetically isolated duplex kidney formation from the medullary defect by specifically targeting the progenitors for both the ureteric bud and metanephric mesenchyme. The conditional mutants fail to form a normal renal medulla but no longer exhibit duplex kidney formation. Approximately 1/3 of the mutants develop hydronephrosis in the kidneys either uni- or bilaterally when using Dll1Cre. The abnormal kidney phenotype becomes prominent at E16.5, which approximates the time when urine production begins in the mouse embryonic kidney, and is associated with a dramatic increase in apoptosis only in mutant kidneys with hydronephrosis. Methylene blue dye injection and histologic examination reveal that aberrant cell death likely results from urine toxicity due to an abnormal ureter-bladder connection. This study shows that Wnt5a is not required for development of the renal medulla and that loss of the renal medullary region in the Wnt5a-deleted kidney is caused by an abnormal ureter-bladder connection. Published by Elsevier B.V.

  19. Abnormal brain connectivity in first-episode psychosis: A diffusion MRI tractography study of the corpus callosum

    PubMed Central

    Price, Gary; Cercignani, Mara; Parker, Geoffrey J.M.; Altmann, Daniel R.; Barnes, Thomas R.E.; Barker, Gareth J.; Joyce, Eileen M.; Ron, Maria A.

    2007-01-01

    A model of disconnectivity involving abnormalities in the cortex and connecting white matter pathways may explain the clinical manifestations of schizophrenia. Recently, diffusion imaging tractography has made it possible to study white matter pathways in detail and we present here a study of patients with first-episode psychosis using this technique. We selected the corpus callosum for this study because there is evidence that it is abnormal in schizophrenia. In addition, the topographical organization of its fibers makes it possible to relate focal abnormalities to specific cortical regions. Eighteen patients with first-episode psychosis and 21 healthy subjects took part in the study. A probabilistic tractography algorithm (PICo) was used to study fractional anisotropy (FA). Seed regions were placed in the genu and splenium to track fiber tracts traversing these regions, and a multi-threshold approach to study the probability of connection was used. Multiple linear regressions were used to explore group differences. FA, a measure of tract coherence, was reduced in tracts crossing the genu, and to a lesser degree the splenium, in patients compared with controls. FA was also lower in the genu in females across both groups, but there was no gender-by-group interaction. The FA reduction in patients may be due to aberrant myelination or axonal abnormalities, but the similar tract volumes in the two groups suggest that severe axonal loss is unlikely at this stage of the illness. PMID:17275337

  20. Abnormalities in hemispheric specialization of caudate nucleus connectivity in schizophrenia.

    PubMed

    Mueller, Sophia; Wang, Danhong; Pan, Ruiqi; Holt, Daphne J; Liu, Hesheng

    2015-06-01

    Hemispheric specialization of the human brain is a marker of successful neurodevelopment. Altered brain asymmetry that has been repeatedly reported in schizophrenia may represent consequences of disrupted neurodevelopment in the disorder. However, a complete picture of functional specialization in the schizophrenic brain and its connectional substrates is yet to be unveiled. To quantify intrinsic hemispheric specialization at cortical and subcortical levels and to reveal potential disease effects in schizophrenia. Resting-state functional connectivity magnetic resonance imaging has been previously used to quantitatively measure hemispheric specialization in healthy individuals in a reliable manner. We quantified the intrinsic hemispheric specialization at the whole brain level in 31 patients with schizophrenia and 37 demographically matched healthy controls from November 28, 2007, through June 29, 2010, using resting-state functional magnetic resonance imaging. The caudate nucleus and cortical regions with connections to the caudate nucleus had markedly abnormal hemispheric specialization in schizophrenia. Compared with healthy controls, patients exhibited weaker specialization in the left, but the opposite pattern in the right, caudate nucleus (P < .001). Patients with schizophrenia also had a disruption of the interhemispheric coordination among the cortical regions with connections to the caudate nucleus. A linear classifier based on the specialization of the caudate nucleus distinguished patients from controls with a classification accuracy of 74% (with a sensitivity of 68% and a specificity of 78%). These data suggest that hemispheric specialization could serve as a potential imaging biomarker of schizophrenia that, compared with task-based functional magnetic resonance imaging measures, is less prone to the confounding effects of variation in task compliance, cognitive ability, and command of language.

  1. Abnormal synchrony and effective connectivity in patients with schizophrenia and auditory hallucinations

    PubMed Central

    de la Iglesia-Vaya, Maria; Escartí, Maria José; Molina-Mateo, Jose; Martí-Bonmatí, Luis; Gadea, Marien; Castellanos, Francisco Xavier; Aguilar García-Iturrospe, Eduardo J.; Robles, Montserrat; Biswal, Bharat B.; Sanjuan, Julio

    2014-01-01

    Auditory hallucinations (AH) are the most frequent positive symptoms in patients with schizophrenia. Hallucinations have been related to emotional processing disturbances, altered functional connectivity and effective connectivity deficits. Previously, we observed that, compared to healthy controls, the limbic network responses of patients with auditory hallucinations differed when the subjects were listening to emotionally charged words. We aimed to compare the synchrony patterns and effective connectivity of task-related networks between schizophrenia patients with and without AH and healthy controls. Schizophrenia patients with AH (n = 27) and without AH (n = 14) were compared with healthy participants (n = 31). We examined functional connectivity by analyzing correlations and cross-correlations among previously detected independent component analysis time courses. Granger causality was used to infer the information flow direction in the brain regions. The results demonstrate that the patterns of cortico-cortical functional synchrony differentiated the patients with AH from the patients without AH and from the healthy participants. Additionally, Granger-causal relationships between the networks clearly differentiated the groups. In the patients with AH, the principal causal source was an occipital–cerebellar component, versus a temporal component in the patients without AH and the healthy controls. These data indicate that an anomalous process of neural connectivity exists when patients with AH process emotional auditory stimuli. Additionally, a central role is suggested for the cerebellum in processing emotional stimuli in patients with persistent AH. PMID:25379429

  2. Effects of Methylphenidate on Resting-State Functional Connectivity of the Mesocorticolimbic Dopamine Pathways in Cocaine Addiction

    PubMed Central

    Konova, Anna B.; Moeller, Scott J.; Tomasi, Dardo; Volkow, Nora D.; Goldstein, Rita Z.

    2015-01-01

    Importance Cocaine addiction is associated with altered resting-state functional connectivity among regions of the mesocorticolimbic dopamine pathways. Methylphenidate hydrochloride, an indirect dopamine agonist, normalizes task-related regional brain activity and associated behavior in cocaine users; however, the neural systems–level effects of methylphenidate in this population have not yet been described. Objective To use resting-state functional magnetic resonance imaging to examine changes in mesocorticolimbic connectivity with methylphenidate and how connectivity of affected pathways relates to severity of cocaine addiction. Design Randomized, placebo-controlled, before-after, crossover study. Setting Clinical research center. Participants Eighteen nonabstaining individuals with cocaine use disorders. Interventions Single doses of oral methylphenidate (20 mg) or placebo were administered at each of 2 study sessions. At each session, resting scans were acquired twice: immediately after drug administration (before the onset of effects [baseline]) and 120 minutes later (within the window of peak effects). Main outcomes and Measures Functional connectivity strength was evaluated using a seed voxel correlation approach. Changes in this measure were examined to characterize the neural systems–level effects of methylphenidate; severity of cocaine addiction was assessed by interview and questionnaire. Results Short-term methylphenidate administration reduced an abnormally strong connectivity of the ventral striatum with the dorsal striatum (putamen/globus pallidus), and lower connectivity between these regions during placebo administration uniquely correlated with less severe addiction. In contrast, methylphenidate strengthened several corticolimbic and corticocortical connections. Conclusions and Relevance These findings help elucidate the neural systems–level effects of methylphenidate and suggest that short-term methylphenidate can, at least transiently

  3. [Tilt test and orthostatic intolerance: abnormalities in the neural sympathetic response to gravitational stimulus].

    PubMed

    Furlan, R

    2001-05-01

    In the present manuscript the different methodologies aimed at assessing the autonomic profile in humans during a gravitational stimulus have been described. In addition, strengths and drawbacks of the tilt test in relation to occasional orthostatic intolerance were addressed. Finally, different autonomic abnormalities underlying occasional and chronic orthostatic intolerance syndromes have been schematically highlighted. The direct recording of the neural sympathetic discharge from the peroneal nerve (MSNA), in spite of its invasive nature, still represents the recognized reference to quantify the changes in the sympathetic activity to the vessels attending postural modifications. The increase of plasma norepinephrine during a tilt test is achieved by both an increase in plasma spillover and a concomitant decrease in systemic clearance. Changes in the indices of cardiac sympathetic and vagal modulation may also be quantified during a tilt test by power spectrum analysis of RR interval variability. The spectral markers of cardiac autonomic control, if evaluated concomitantly with MSNA, may contribute to assess abnormalities in the regional distribution of the sympathetic activity to the heart and the vessels. The capability of the tilt test of reproducing a vasovagal event or of inducing "false positive responses" seems to be markedly affected by the age, thus suggesting that additional or different etiopathogenetic mechanisms might be involved in the loss of consciousness in older as compared to younger subjects. In subjects suffering from occasional or habitual neurally mediated syncope an increase or, respectively, a decrease in cardiac and vascular sympathetic modulation has been documented before the loss of consciousness. In patients with pure autonomic failure, a global dysautonomia affecting both the sympathetic and the vagal modulation to the heart, seems to be present. In chronic orthostatic intolerance, the most common form of dysautonomia of young women

  4. Knowledge engineering tools for reasoning with scientific observations and interpretations: a neural connectivity use case.

    PubMed

    Russ, Thomas A; Ramakrishnan, Cartic; Hovy, Eduard H; Bota, Mihail; Burns, Gully A P C

    2011-08-22

    We address the goal of curating observations from published experiments in a generalizable form; reasoning over these observations to generate interpretations and then querying this interpreted knowledge to supply the supporting evidence. We present web-application software as part of the 'BioScholar' project (R01-GM083871) that fully instantiates this process for a well-defined domain: using tract-tracing experiments to study the neural connectivity of the rat brain. The main contribution of this work is to provide the first instantiation of a knowledge representation for experimental observations called 'Knowledge Engineering from Experimental Design' (KEfED) based on experimental variables and their interdependencies. The software has three parts: (a) the KEfED model editor - a design editor for creating KEfED models by drawing a flow diagram of an experimental protocol; (b) the KEfED data interface - a spreadsheet-like tool that permits users to enter experimental data pertaining to a specific model; (c) a 'neural connection matrix' interface that presents neural connectivity as a table of ordinal connection strengths representing the interpretations of tract-tracing data. This tool also allows the user to view experimental evidence pertaining to a specific connection. BioScholar is built in Flex 3.5. It uses Persevere (a noSQL database) as a flexible data store and PowerLoom® (a mature First Order Logic reasoning system) to execute queries using spatial reasoning over the BAMS neuroanatomical ontology. We first introduce the KEfED approach as a general approach and describe its possible role as a way of introducing structured reasoning into models of argumentation within new models of scientific publication. We then describe the design and implementation of our example application: the BioScholar software. This is presented as a possible biocuration interface and supplementary reasoning toolkit for a larger, more specialized bioinformatics system: the Brain

  5. Management of abnormal serum markers in the absence of aneuploidy or neural tube defects

    PubMed Central

    Schnettler, William T.; Hacker, Michele R.; Barber, Rachel E.; Rana, Sarosh

    2013-01-01

    Objective Few guidelines address the management of pregnancies complicated by abnormal maternal serum analytes (MSAs) in the absence of aneuploidy or neural tube defects (NTDs). Our objective was to gather preliminary data regarding current opinions and management strategies among perinatologists in the US. Methods This survey of Maternal Fetal Medicine (MFM) physicians and fellows used a secure electronic web-based data capture tool. Results A total of 545 potential participants were contacted, and 136 (25%) responded. The majority were experienced academic physicians with robust practices. Nearly all (97.7%) respondents reported a belief in an association between abnormal MSAs and adverse pregnancy outcomes other than aneuploidy or NTDs. Plasma protein A (PAPP-A) and α-fetoprotein (AFP) were most often chosen as markers demonstrating a strong association with adverse outcomes. Most (86.9%) respondents acknowledged that abnormal MSAs influenced their counseling approach, and the majority (80.1%) offered additional ultrasound examinations. Nearly half started at 28 weeks and almost one-third at 32 weeks. Respondents acknowledging a relevant protocol in their hospital or practice were more likely to offer additional antenatal testing (p = 0.01). Conclusions Although most perinatologists were in agreement regarding the association of MSAs with adverse pregnancy outcomes, a lack of consensus exists regarding management strategies. PMID:22372385

  6. Neural abnormalities in early-onset and adolescence-onset conduct disorder.

    PubMed

    Passamonti, Luca; Fairchild, Graeme; Goodyer, Ian M; Hurford, Georgina; Hagan, Cindy C; Rowe, James B; Calder, Andrew J

    2010-07-01

    Conduct disorder (CD) is characterized by severe antisocial behavior that emerges in childhood (early-onset CD [EO-CD]) or adolescence (adolescence-onset CD [AO-CD]). Early-onset CD is proposed to have a neurodevelopmental basis, whereas AO-CD is thought to emerge owing to social mimicry of deviant peers. However, this developmental taxonomic theory is debated after reports of neuropsychological impairments in both CD subtypes. A critical, although unaddressed, issue is whether these subtypes present similar or distinct neurophysiological profiles. Hence, we investigated neurophysiological responses to emotional and neutral faces in regions associated with antisocial behavior (ie, the amygdala, ventromedial prefrontal cortex, insula, and orbitofrontal cortex) in individuals with EO-CD and AO-CD and in healthy control subjects. To investigate whether EO-CD and AO-CD subjects show neurophysiological abnormalities. Case-control study. Government research institute, university department. Seventy-five male adolescents and young adults aged 16 to 21 years, including 27 with EO-CD, 25 with AO-CD, and 23 healthy controls. Main Outcome Measure Neural activations measured by functional magnetic resonance imaging while participants viewed angry, sad, and neutral faces. Comparing angry vs neutral faces, participants with both CD subtypes displayed reduced responses in regions associated with antisocial behavior compared with controls; differences between the CD subtypes were not significant. Comparing each expression with fixation baseline revealed an abnormal (increased) amygdala response to neutral but not angry faces in both groups of CD relative to controls. For sad vs neutral faces, reduced amygdala activation was observed in EO-CD relative to AO-CD and control participants. Comparing each expression with fixation revealed hypoactive amygdala responses to sadness in individuals with EO-CD relative to AO-CD participants and controls. These findings were not accounted for

  7. Abnormal amygdala connectivity in patients with primary insomnia: evidence from resting state fMRI.

    PubMed

    Huang, Zhaoyang; Liang, Peipeng; Jia, Xiuqin; Zhan, Shuqin; Li, Ning; Ding, Yan; Lu, Jie; Wang, Yuping; Li, Kuncheng

    2012-06-01

    Neurobiological mechanisms underlying insomnia are poorly understood. Previous findings indicated that dysfunction of the emotional circuit might contribute to the neurobiological mechanisms underlying insomnia. The present study will test this hypothesis by examining alterations in functional connectivity of the amygdala in patients with primary insomnia (PI). Resting-state functional connectivity analysis was used to examine the temporal correlation between the amygdala and whole-brain regions in 10 medication-naive PI patients and 10 age- and sex-matched healthy controls. Additionally, the relationship between the abnormal functional connectivity and insomnia severity was investigated. We found decreased functional connectivity mainly between the amygdala and insula, striatum and thalamus, and increased functional connectivity mainly between the amygdala and premotor cortex, sensorimotor cortex in PI patients as compared to healthy controls. The connectivity of the amygdala with the premotor cortex in PI patients showed significant positive correlation with the total score of the Pittsburgh Sleep Quality Index (PSQI). The decreased functional connectivity between the amygdala and insula, striatum, and thalamus suggests that dysfunction in the emotional circuit might contribute to the neurobiological mechanisms underlying PI. The increased functional connectivity of the amygdala with the premotor and sensorimotor cortex demonstrates a compensatory mechanism to overcome the negative effects of sleep deficits and maintain the psychomotor performances in PI patients. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  8. Differential Hemispheric Predilection of Microstructural White Matter and Functional Connectivity Abnormalities between Respectively Semantic and Behavioral Variant Frontotemporal Dementia.

    PubMed

    Meijboom, Rozanna; Steketee, Rebecca M E; Ham, Leontine S; van der Lugt, Aad; van Swieten, John C; Smits, Marion

    2017-01-01

    Semantic dementia (SD) and behavioral variant frontotemporal dementia (bvFTD), subtypes of frontotemporal dementia, are characterized by distinct clinical symptoms and neuroimaging features, with predominant left temporal grey matter (GM) atrophy in SD and bilateral or right frontal GM atrophy in bvFTD. Such differential hemispheric predilection may also be reflected by other neuroimaging features, such as brain connectivity. This study investigated white matter (WM) microstructure and functional connectivity differences between SD and bvFTD, focusing on the hemispheric predilection of these differences. Eight SD and 12 bvFTD patients, and 17 controls underwent diffusion tensor imaging and resting state functional MRI at 3T. Whole-brain WM microstructure was assessed to determine distinct WM tracts affected in SD and bvFTD. For these tracts, diffusivity measures and lateralization indices were calculated. Functional connectivity was established for GM regions affected in early stage SD or bvFTD. Results of a direct comparison between SD and bvFTD are reported. Whole-brain WM microstructure abnormalities were more pronounced in the left hemisphere in SD and bilaterally- with a slight predilection for the right- in bvFTD. Lateralization of tract-specific abnormalities was seen in SD only, toward the left hemisphere. Functional connectivity of disease-specific regions was mainly decreased bilaterally in SD and in the right hemisphere in bvFTD. SD and bvFTD show WM microstructure and functional connectivity abnormalities in different regions, that are respectively more pronounced in the left hemisphere in SD and in the right hemisphere in bvFTD. This indicates differential hemispheric predilection of brain connectivity abnormalities between SD and bvFTD.

  9. Disruption of thalamic functional connectivity is a neural correlate of dexmedetomidine-induced unconsciousness

    PubMed Central

    Akeju, Oluwaseun; Loggia, Marco L; Catana, Ciprian; Pavone, Kara J; Vazquez, Rafael; Rhee, James; Contreras Ramirez, Violeta; Chonde, Daniel B; Izquierdo-Garcia, David; Arabasz, Grae; Hsu, Shirley; Habeeb, Kathleen; Hooker, Jacob M; Napadow, Vitaly; Brown, Emery N; Purdon, Patrick L

    2014-01-01

    Understanding the neural basis of consciousness is fundamental to neuroscience research. Disruptions in cortico-cortical connectivity have been suggested as a primary mechanism of unconsciousness. By using a novel combination of positron emission tomography and functional magnetic resonance imaging, we studied anesthesia-induced unconsciousness and recovery using the α2-agonist dexmedetomidine. During unconsciousness, cerebral metabolic rate of glucose and cerebral blood flow were preferentially decreased in the thalamus, the Default Mode Network (DMN), and the bilateral Frontoparietal Networks (FPNs). Cortico-cortical functional connectivity within the DMN and FPNs was preserved. However, DMN thalamo-cortical functional connectivity was disrupted. Recovery from this state was associated with sustained reduction in cerebral blood flow and restored DMN thalamo-cortical functional connectivity. We report that loss of thalamo-cortical functional connectivity is sufficient to produce unconsciousness. DOI: http://dx.doi.org/10.7554/eLife.04499.001 PMID:25432022

  10. Neural connections foster social connections: a diffusion-weighted imaging study of social networks

    PubMed Central

    Hampton, William H.; Unger, Ashley; Von Der Heide, Rebecca J.

    2016-01-01

    Although we know the transition from childhood to adulthood is marked by important social and neural development, little is known about how social network size might affect neurocognitive development or vice versa. Neuroimaging research has identified several brain regions, such as the amygdala, as key to this affiliative behavior. However, white matter connectivity among these regions, and its behavioral correlates, remain unclear. Here we tested two hypotheses: that an amygdalocentric structural white matter network governs social affiliative behavior and that this network changes during adolescence and young adulthood. We measured social network size behaviorally, and white matter microstructure using probabilistic diffusion tensor imaging in a sample of neurologically normal adolescents and young adults. Our results suggest amygdala white matter microstructure is key to understanding individual differences in social network size, with connectivity to other social brain regions such as the orbitofrontal cortex and anterior temporal lobe predicting much variation. In addition, participant age correlated with both network size and white matter variation in this network. These findings suggest the transition to adulthood may constitute a critical period for the optimization of structural brain networks underlying affiliative behavior. PMID:26755769

  11. Rapid Postnatal Expansion of Neural Networks Occurs in an Environment of Altered Neurovascular and Neurometabolic Coupling.

    PubMed

    Kozberg, Mariel G; Ma, Ying; Shaik, Mohammed A; Kim, Sharon H; Hillman, Elizabeth M C

    2016-06-22

    In the adult brain, increases in neural activity lead to increases in local blood flow. However, many prior measurements of functional hemodynamics in the neonatal brain, including functional magnetic resonance imaging (fMRI) in human infants, have noted altered and even inverted hemodynamic responses to stimuli. Here, we demonstrate that localized neural activity in early postnatal mice does not evoke blood flow increases as in the adult brain, and elucidate the neural and metabolic correlates of these altered functional hemodynamics as a function of developmental age. Using wide-field GCaMP imaging, the development of neural responses to somatosensory stimulus is visualized over the entire bilaterally exposed cortex. Neural responses are observed to progress from tightly localized, unilateral maps to bilateral responses as interhemispheric connectivity becomes established. Simultaneous hemodynamic imaging confirms that spatiotemporally coupled functional hyperemia is not present during these early stages of postnatal brain development, and develops gradually as cortical connectivity is established. Exploring the consequences of this lack of functional hyperemia, measurements of oxidative metabolism via flavoprotein fluorescence suggest that neural activity depletes local oxygen to below baseline levels at early developmental stages. Analysis of hemoglobin oxygenation dynamics at the same age confirms oxygen depletion for both stimulus-evoked and resting-state neural activity. This state of unmet metabolic demand during neural network development poses new questions about the mechanisms of neurovascular development and its role in both normal and abnormal brain development. These results also provide important insights for the interpretation of fMRI studies of the developing brain. This work demonstrates that the postnatal development of neuronal connectivity is accompanied by development of the mechanisms that regulate local blood flow in response to neural

  12. In Search of Neural Endophenotypes of Postpartum Psychopathology and Disrupted Maternal Caregiving

    PubMed Central

    Moses-Kolko, E. L.; Horner, M. S.; Phillips, M. L.; Hipwell, A. E.; Swain, J. E.

    2015-01-01

    This is a selective review that provides the context for the study of perinatal affective disorder mechanisms and outlines directions for future research. We integrate existing literature along neural networks of interest for affective disorders and maternal caregiving: (i) the salience/fear network; (ii) the executive network; (iii) the reward/social attachment network; and (iv) the default mode network. Extant salience/fear network research reveals disparate responses and corticolimbic coupling to various stimuli based upon a predominantly depressive versus anxious (post-traumatic stress disorder) clinical phenotype. Executive network and default mode connectivity abnormalities have been described in postpartum depression (PPD), although studies are very limited in these domains. Reward/social attachment studies confirm a robust ventral striatal response to infant stimuli, including cry and happy infant faces, which is diminished in depressed, insecurely attached and substance-using mothers. The adverse parenting experiences received and the attachment insecurity of current mothers are factors that are associated with a diminution in infant stimulus-related neural activity similar to that in PPD, and raise the need for additional studies that integrate mood and attachment concepts in larger study samples. Several studies examining functional connectivity in resting state and emotional activation functional magnetic resonance imaging paradigms have revealed attenuated corticolimbic connectivity, which remains an important outcome that requires dissection with increasing precision to better define neural treatment targets. Methodological progress is expected in the coming years in terms of refining clinical phenotypes of interest and experimental paradigms, as well as enlarging samples to facilitate the examination of multiple constructs. Functional imaging promises to determine neural mechanisms underlying maternal psychopathology and impaired caregiving, such

  13. Altered Connectivity and Action Model Formation in Autism Is Autism

    PubMed Central

    Mostofsky, Stewart H.; Ewen, Joshua B.

    2014-01-01

    Internal action models refer to sensory-motor programs that form the brain basis for a wide range of skilled behavior and for understanding others’ actions. Development of these action models, particularly those reliant on visual cues from the external world, depends on connectivity between distant brain regions. Studies of children with autism reveal anomalous patterns of motor learning and impaired execution of skilled motor gestures. These findings robustly correlate with measures of social and communicative function, suggesting that anomalous action model formation may contribute to impaired development of social and communicative (as well as motor) capacity in autism. Examination of the pattern of behavioral findings, as well as convergent data from neuroimaging techniques, further suggests that autism-associated action model formation may be related to abnormalities in neural connectivity, particularly decreased function of long-range connections. This line of study can lead to important advances in understanding the neural basis of autism and, more critically, can be used to guide effective therapies targeted at improving social, communicative, and motor function. PMID:21467306

  14. Abnormal functional connectivity density in children with anisometropic amblyopia at resting-state.

    PubMed

    Wang, Tianyue; Li, Qian; Guo, Mingxia; Peng, Yanmin; Li, Qingji; Qin, Wen; Yu, Chunshui

    2014-05-14

    Amblyopia is a developmental disorder resulting from anomalous binocular visual input in early life. Task-based neuroimaging studies have widely investigated cortical functional impairments in amblyopia, but changes in spontaneous neuronal functional activities in amblyopia remain largely unknown. In the present study, functional connectivity density (FCD) mapping, an ultrafast data-driven method based on fMRI, was applied for the first time to investigate changes in cortical functional connectivities in amblyopia during the resting-state. We quantified and compared both short- and long-range FCD in both the brains of children with anisometropic amblyopia (AAC) and normal sighted children (NSC). In contrast to the NSC, the AAC showed significantly decreased short-range FCD in the inferior temporal/fusiform gyri, parieto-occipital and rostrolateral prefrontal cortices, as well as decreased long-range FCD in the premotor cortex, dorsal inferior parietal lobule, frontal-insular and dorsal prefrontal cortices. Furthermore, most regions with reduced long-range FCD in the AAC showed decreased functional connectivity with occipital and posterior parietal cortices in the AAC. The results suggest that chronically poor visual input in amblyopia not only impairs the brain's short-range functional connections in visual pathways and in the frontal cortex, which is important for cognitive control, but also affects long-range functional connections among the visual areas, posterior parietal and frontal cortices that subserve visuomotor and visual-guided actions, visuospatial attention modulation and the integration of salient information. This study provides evidence for abnormal spontaneous brain activities in amblyopia. Copyright © 2014 Elsevier B.V. All rights reserved.

  15. Learning neural connectivity from firing activity: efficient algorithms with provable guarantees on topology.

    PubMed

    Karbasi, Amin; Salavati, Amir Hesam; Vetterli, Martin

    2018-04-01

    The connectivity of a neuronal network has a major effect on its functionality and role. It is generally believed that the complex network structure of the brain provides a physiological basis for information processing. Therefore, identifying the network's topology has received a lot of attentions in neuroscience and has been the center of many research initiatives such as Human Connectome Project. Nevertheless, direct and invasive approaches that slice and observe the neural tissue have proven to be time consuming, complex and costly. As a result, the inverse methods that utilize firing activity of neurons in order to identify the (functional) connections have gained momentum recently, especially in light of rapid advances in recording technologies; It will soon be possible to simultaneously monitor the activities of tens of thousands of neurons in real time. While there are a number of excellent approaches that aim to identify the functional connections from firing activities, the scalability of the proposed techniques plays a major challenge in applying them on large-scale datasets of recorded firing activities. In exceptional cases where scalability has not been an issue, the theoretical performance guarantees are usually limited to a specific family of neurons or the type of firing activities. In this paper, we formulate the neural network reconstruction as an instance of a graph learning problem, where we observe the behavior of nodes/neurons (i.e., firing activities) and aim to find the links/connections. We develop a scalable learning mechanism and derive the conditions under which the estimated graph for a network of Leaky Integrate and Fire (LIf) neurons matches the true underlying synaptic connections. We then validate the performance of the algorithm using artificially generated data (for benchmarking) and real data recorded from multiple hippocampal areas in rats.

  16. Knowledge engineering tools for reasoning with scientific observations and interpretations: a neural connectivity use case

    PubMed Central

    2011-01-01

    Background We address the goal of curating observations from published experiments in a generalizable form; reasoning over these observations to generate interpretations and then querying this interpreted knowledge to supply the supporting evidence. We present web-application software as part of the 'BioScholar' project (R01-GM083871) that fully instantiates this process for a well-defined domain: using tract-tracing experiments to study the neural connectivity of the rat brain. Results The main contribution of this work is to provide the first instantiation of a knowledge representation for experimental observations called 'Knowledge Engineering from Experimental Design' (KEfED) based on experimental variables and their interdependencies. The software has three parts: (a) the KEfED model editor - a design editor for creating KEfED models by drawing a flow diagram of an experimental protocol; (b) the KEfED data interface - a spreadsheet-like tool that permits users to enter experimental data pertaining to a specific model; (c) a 'neural connection matrix' interface that presents neural connectivity as a table of ordinal connection strengths representing the interpretations of tract-tracing data. This tool also allows the user to view experimental evidence pertaining to a specific connection. BioScholar is built in Flex 3.5. It uses Persevere (a noSQL database) as a flexible data store and PowerLoom® (a mature First Order Logic reasoning system) to execute queries using spatial reasoning over the BAMS neuroanatomical ontology. Conclusions We first introduce the KEfED approach as a general approach and describe its possible role as a way of introducing structured reasoning into models of argumentation within new models of scientific publication. We then describe the design and implementation of our example application: the BioScholar software. This is presented as a possible biocuration interface and supplementary reasoning toolkit for a larger, more specialized

  17. Action and semantic tool knowledge - Effective connectivity in the underlying neural networks.

    PubMed

    Kleineberg, Nina N; Dovern, Anna; Binder, Ellen; Grefkes, Christian; Eickhoff, Simon B; Fink, Gereon R; Weiss, Peter H

    2018-04-26

    Evidence from neuropsychological and imaging studies indicate that action and semantic knowledge about tools draw upon distinct neural substrates, but little is known about the underlying interregional effective connectivity. With fMRI and dynamic causal modeling (DCM) we investigated effective connectivity in the left-hemisphere (LH) while subjects performed (i) a function knowledge and (ii) a value knowledge task, both addressing semantic tool knowledge, and (iii) a manipulation (action) knowledge task. Overall, the results indicate crosstalk between action nodes and semantic nodes. Interestingly, effective connectivity was weakened between semantic nodes and action nodes during the manipulation task. Furthermore, pronounced modulations of effective connectivity within the fronto-parietal action system of the LH (comprising lateral occipito-temporal cortex, intraparietal sulcus, supramarginal gyrus, inferior frontal gyrus) were observed in a bidirectional manner during the processing of action knowledge. In contrast, the function and value knowledge tasks resulted in a significant strengthening of the effective connectivity between visual cortex and fusiform gyrus. Importantly, this modulation was present in both semantic tasks, indicating that processing different aspects of semantic knowledge about tools evokes similar effective connectivity patterns. Data revealed that interregional effective connectivity during the processing of tool knowledge occurred in a bidirectional manner with a weakening of connectivity between areas engaged in action and semantic knowledge about tools during the processing of action knowledge. Moreover, different semantic tool knowledge tasks elicited similar effective connectivity patterns. © 2018 Wiley Periodicals, Inc.

  18. Volumetric abnormalities in connectivity-based subregions of the thalamus in patients with chronic schizophrenia.

    PubMed

    Kim, Jae-Jin; Kim, Dae-Jin; Kim, Tae-Gyun; Seok, Jeong-Ho; Chun, Ji Won; Oh, Maeng-Keun; Park, Hae-Jeong

    2007-12-01

    The thalamus, which consists of multiple subnuclei, has been of particular interest in the study of schizophrenia. This study aimed to identify abnormalities in the connectivity-based subregions of the thalamus in patients with schizophrenia. Thalamic volume was measured by a manual tracing on superimposed images of T1-weighted and diffusion tensor images in 30 patients with schizophrenia and 22 normal volunteers. Cortical regional volumes automatically measured by a surface-based approach and thalamic subregional volumes measured by a connectivity-based technique were compared between the two groups and their correlations between the connected regions were calculated in each group. Volume reduction was observed in the bilateral orbitofrontal cortices and the left cingulate gyrus on the cortical side, whereas in subregions connected to the right orbitofrontal cortex and bilateral parietal cortices on the thalamic side. Significant volumetric correlations were identified between the right dorsal prefrontal cortex and its related thalamic subregion and between the left parietal cortex and its related thalamic subregion only in the normal group. Our results suggest that patients with schizophrenia have a structural deficit in the corticothalamic systems, especially in the orbitofrontal-thalamic system. Our findings may present evidence of corticothalamic connection problems in schizophrenia.

  19. Resting state electrical brain activity and connectivity in fibromyalgia

    PubMed Central

    Vanneste, Sven; Ost, Jan; Van Havenbergh, Tony; De Ridder, Dirk

    2017-01-01

    The exact mechanism underlying fibromyalgia is unknown, but increased facilitatory modulation and/or dysfunctional descending inhibitory pathway activity are posited as possible mechanisms contributing to sensitization of the central nervous system. The primary goal of this study is to identify a fibromyalgia neural circuit that can account for these abnormalities in central pain. The second goal is to gain a better understanding of the functional connectivity between the default and the executive attention network (salience network plus dorsal lateral prefrontal cortex) in fibromyalgia. We examine neural activity associated with fibromyalgia (N = 44) and compare these with healthy controls (N = 44) using resting state source localized EEG. Our data support an important role of the pregenual anterior cingulate cortex but also suggest that the degree of activation and the degree of integration between different brain areas is important. The inhibition of the connectivity between the dorsal lateral prefrontal cortex and the posterior cingulate cortex on the pain inhibitory pathway seems to be limited by decreased functional connectivity with the pregenual anterior cingulate cortex. Our data highlight the functional dynamics of brain regions integrated in brain networks in fibromyalgia patients. PMID:28650974

  20. Motor Sequence Learning-Induced Neural Efficiency in Functional Brain Connectivity

    PubMed Central

    Karim, Helmet T; Huppert, Theodore J; Erickson, Kirk I; Wollam, Mariegold E; Sparto, Patrick J; Sejdić, Ervin; VanSwearingen, Jessie M

    2016-01-01

    Previous studies have shown the functional neural circuitry differences before and after an explicitly learned motor sequence task, but have not assessed these changes during the process of motor skill learning. Functional magnetic resonance imaging activity was measured while participants (n=13) were asked to tap their fingers to visually presented sequences in blocks that were either the same sequence repeated (learning block) or random sequences (control block). Motor learning was associated with a decrease in brain activity during learning compared to control. Lower brain activation was noted in the posterior parietal association area and bilateral thalamus during the later periods of learning (not during the control). Compared to the control condition, we found the task-related motor learning was associated with decreased connectivity between the putamen and left inferior frontal gyrus and left middle cingulate brain regions. Motor learning was associated with changes in network activity, spatial extent, and connectivity. PMID:27845228

  1. Motor sequence learning-induced neural efficiency in functional brain connectivity.

    PubMed

    Karim, Helmet T; Huppert, Theodore J; Erickson, Kirk I; Wollam, Mariegold E; Sparto, Patrick J; Sejdić, Ervin; VanSwearingen, Jessie M

    2017-02-15

    Previous studies have shown the functional neural circuitry differences before and after an explicitly learned motor sequence task, but have not assessed these changes during the process of motor skill learning. Functional magnetic resonance imaging activity was measured while participants (n=13) were asked to tap their fingers to visually presented sequences in blocks that were either the same sequence repeated (learning block) or random sequences (control block). Motor learning was associated with a decrease in brain activity during learning compared to control. Lower brain activation was noted in the posterior parietal association area and bilateral thalamus during the later periods of learning (not during the control). Compared to the control condition, we found the task-related motor learning was associated with decreased connectivity between the putamen and left inferior frontal gyrus and left middle cingulate brain regions. Motor learning was associated with changes in network activity, spatial extent, and connectivity. Copyright © 2016 Elsevier B.V. All rights reserved.

  2. Abnormalities of hippocampal-cortical connectivity in temporal lobe epilepsy patients with hippocampal sclerosis

    NASA Astrophysics Data System (ADS)

    Li, Wenjing; He, Huiguang; Lu, Jingjing; Wang, Chunheng; Li, Meng; Lv, Bin; Jin, Zhengyu

    2011-03-01

    Hippocampal sclerosis (HS) is the most common damage seen in the patients with temporal lobe epilepsy (TLE). In the present study, the hippocampal-cortical connectivity was defined as the correlation between the hippocampal volume and cortical thickness at each vertex throughout the whole brain. We aimed to investigate the differences of ipsilateral hippocampal-cortical connectivity between the unilateral TLE-HS patients and the normal controls. In our study, the bilateral hippocampal volumes were first measured in each subject, and we found that the ipsilateral hippocampal volume significantly decreased in the left TLE-HS patients. Then, group analysis showed significant thinner average cortical thickness of the whole brain in the left TLE-HS patients compared with the normal controls. We found significantly increased ipsilateral hippocampal-cortical connectivity in the bilateral superior temporal gyrus, the right cingulate gyrus and the left parahippocampal gyrus of the left TLE-HS patients, which indicated structural vulnerability related to the hippocampus atrophy in the patient group. However, for the right TLE-HS patients, no significant differences were found between the patients and the normal controls, regardless of the ipsilateral hippocampal volume, the average cortical thickness or the patterns of hippocampal-cortical connectivity, which might be related to less atrophies observed in the MRI scans. Our study provided more evidence for the structural abnormalities in the unilateral TLE-HS patients.

  3. Neural correlate of resting-state functional connectivity under α2 adrenergic receptor agonist, medetomidine.

    PubMed

    Nasrallah, Fatima A; Lew, Si Kang; Low, Amanda Si-Min; Chuang, Kai-Hsiang

    2014-01-01

    Correlative fluctuations in functional MRI (fMRI) signals across the brain at rest have been taken as a measure of functional connectivity, but the neural basis of this resting-state MRI (rsMRI) signal is not clear. Previously, we found that the α2 adrenergic agonist, medetomidine, suppressed the rsMRI correlation dose-dependently but not the stimulus evoked activation. To understand the underlying electrophysiology and neurovascular coupling, which might be altered due to the vasoconstrictive nature of medetomidine, somatosensory evoked potential (SEP) and resting electroencephalography (EEG) were measured and correlated with corresponding BOLD signals in rat brains under three dosages of medetomidine. The SEP elicited by electrical stimulation to both forepaws was unchanged regardless of medetomidine dosage, which was consistent with the BOLD activation. Identical relationship between the SEP and BOLD signal under different medetomidine dosages indicates that the neurovascular coupling was not affected. Under resting state, EEG power was the same but a depression of inter-hemispheric EEG coherence in the gamma band was observed at higher medetomidine dosage. Different from medetomidine, both resting EEG power and BOLD power and coherence were significantly suppressed with increased isoflurane level. Such reduction was likely due to suppressed neural activity as shown by diminished SEP and BOLD activation under isoflurane, suggesting different mechanisms of losing synchrony at resting-state. Even though, similarity between electrophysiology and BOLD under stimulation and resting-state implicates a tight neurovascular coupling in both medetomidine and isoflurane. Our results confirm that medetomidine does not suppress neural activity but dissociates connectivity in the somatosensory cortex. The differential effect of medetomidine and its receptor specific action supports the neuronal origin of functional connectivity and implicates the mechanism of its sedative

  4. Joint multiple fully connected convolutional neural network with extreme learning machine for hepatocellular carcinoma nuclei grading.

    PubMed

    Li, Siqi; Jiang, Huiyan; Pang, Wenbo

    2017-05-01

    Accurate cell grading of cancerous tissue pathological image is of great importance in medical diagnosis and treatment. This paper proposes a joint multiple fully connected convolutional neural network with extreme learning machine (MFC-CNN-ELM) architecture for hepatocellular carcinoma (HCC) nuclei grading. First, in preprocessing stage, each grayscale image patch with the fixed size is obtained using center-proliferation segmentation (CPS) method and the corresponding labels are marked under the guidance of three pathologists. Next, a multiple fully connected convolutional neural network (MFC-CNN) is designed to extract the multi-form feature vectors of each input image automatically, which considers multi-scale contextual information of deep layer maps sufficiently. After that, a convolutional neural network extreme learning machine (CNN-ELM) model is proposed to grade HCC nuclei. Finally, a back propagation (BP) algorithm, which contains a new up-sample method, is utilized to train MFC-CNN-ELM architecture. The experiment comparison results demonstrate that our proposed MFC-CNN-ELM has superior performance compared with related works for HCC nuclei grading. Meanwhile, external validation using ICPR 2014 HEp-2 cell dataset shows the good generalization of our MFC-CNN-ELM architecture. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. Abnormal neural activity of brain regions in treatment-resistant and treatment-sensitive major depressive disorder: a resting-state fMRI study.

    PubMed

    Guo, Wen-bin; Liu, Feng; Chen, Jin-dong; Gao, Keming; Xue, Zhi-min; Xu, Xi-jia; Wu, Ren-rong; Tan, Chang-lian; Sun, Xue-li; Liu, Zhe-ning; Chen, Hua-fu; Zhao, Jing-ping

    2012-10-01

    Patients with treatment-resistant depression (TRD) and those with treatment-sensitive depression (TSD) responded to antidepressants differently. Previous studies have commonly shown that patients with TRD or TSD had abnormal neural activity in different brain regions. In the present study, we used a coherence-based ReHo (Cohe-ReHo) approach to test the hypothesis that patients with TRD or TSD had abnormal neural activity in different brain regions. Twenty-three patients with TRD, 22 with TSD, and 19 healthy subjects (HS) matched with gender, age, and education level participated in the study. ANOVA analysis revealed widespread differences in Cohe-ReHo values among the three groups in different brain regions which included bilateral superior frontal gyrus, bilateral cerebellum, left inferior temporal gyrus, left occipital cortex, and both sides of fusiform gyrus. Compared to HS, lower Cohe-ReHo values were observed in TRD group in bilateral superior frontal gyrus and left cerebellum; in contrast, in TSD group, lower Cohe-ReHo values were mainly found in bilateral superior frontal gyrus. Compared to TSD group, TRD group had lower Cohe-ReHo in bilateral cerebellum and higher Cohe-ReHo in left fusiform gyrus. There was a negative correlation between Cohe-ReHo values of the left fusiform gyrus and illness duration in the pooled patients (r = 0.480, p = 0.001). The sensitivity and specificity of cerebellar Cohe-ReHo values differentiating TRD from TSD were 83% and 86%, respectively. Compared to healthy controls, both TRD and TSD patients shared the majority of brain regions with abnormal neural activity. However, the lower Cohe-ReHo values in the cerebellum might be as a marker to differentiate TRD from TSD with high sensitivity and specificity. Copyright © 2012 Elsevier Ltd. All rights reserved.

  6. Nested Neural Networks

    NASA Technical Reports Server (NTRS)

    Baram, Yoram

    1992-01-01

    Report presents analysis of nested neural networks, consisting of interconnected subnetworks. Analysis based on simplified mathematical models more appropriate for artificial electronic neural networks, partly applicable to biological neural networks. Nested structure allows for retrieval of individual subpatterns. Requires fewer wires and connection devices than fully connected networks, and allows for local reconstruction of damaged subnetworks without rewiring entire network.

  7. Identification of neural connectivity signatures of autism using machine learning

    PubMed Central

    Deshpande, Gopikrishna; Libero, Lauren E.; Sreenivasan, Karthik R.; Deshpande, Hrishikesh D.; Kana, Rajesh K.

    2013-01-01

    Alterations in interregional neural connectivity have been suggested as a signature of the pathobiology of autism. There have been many reports of functional and anatomical connectivity being altered while individuals with autism are engaged in complex cognitive and social tasks. Although disrupted instantaneous correlation between cortical regions observed from functional MRI is considered to be an explanatory model for autism, the causal influence of a brain area on another (effective connectivity) is a vital link missing in these studies. The current study focuses on addressing this in an fMRI study of Theory-of-Mind (ToM) in 15 high-functioning adolescents and adults with autism and 15 typically developing control participants. Participants viewed a series of comic strip vignettes in the MRI scanner and were asked to choose the most logical end to the story from three alternatives, separately for trials involving physical and intentional causality. The mean time series, extracted from 18 activated regions of interest, were processed using a multivariate autoregressive model (MVAR) to obtain the causality matrices for each of the 30 participants. These causal connectivity weights, along with assessment scores, functional connectivity values, and fractional anisotropy obtained from DTI data for each participant, were submitted to a recursive cluster elimination based support vector machine classifier to determine the accuracy with which the classifier can predict a novel participant's group membership (autism or control). We found a maximum classification accuracy of 95.9% with 19 features which had the highest discriminative ability between the groups. All of the 19 features were effective connectivity paths, indicating that causal information may be critical in discriminating between autism and control groups. These effective connectivity paths were also found to be significantly greater in controls as compared to ASD participants and consisted predominantly of

  8. Chimera states in brain networks: Empirical neural vs. modular fractal connectivity

    NASA Astrophysics Data System (ADS)

    Chouzouris, Teresa; Omelchenko, Iryna; Zakharova, Anna; Hlinka, Jaroslav; Jiruska, Premysl; Schöll, Eckehard

    2018-04-01

    Complex spatiotemporal patterns, called chimera states, consist of coexisting coherent and incoherent domains and can be observed in networks of coupled oscillators. The interplay of synchrony and asynchrony in complex brain networks is an important aspect in studies of both the brain function and disease. We analyse the collective dynamics of FitzHugh-Nagumo neurons in complex networks motivated by its potential application to epileptology and epilepsy surgery. We compare two topologies: an empirical structural neural connectivity derived from diffusion-weighted magnetic resonance imaging and a mathematically constructed network with modular fractal connectivity. We analyse the properties of chimeras and partially synchronized states and obtain regions of their stability in the parameter planes. Furthermore, we qualitatively simulate the dynamics of epileptic seizures and study the influence of the removal of nodes on the network synchronizability, which can be useful for applications to epileptic surgery.

  9. The alcoholic brain: neural bases of impaired reward-based decision-making in alcohol use disorders.

    PubMed

    Galandra, Caterina; Basso, Gianpaolo; Cappa, Stefano; Canessa, Nicola

    2018-03-01

    Neuroeconomics is providing insights into the neural bases of decision-making in normal and pathological conditions. In the neuropsychiatric domain, this discipline investigates how abnormal functioning of neural systems associated with reward processing and cognitive control promotes different disorders, and whether such evidence may inform treatments. This endeavor is crucial when studying different types of addiction, which share a core promoting mechanism in the imbalance between impulsive subcortical neural signals associated with immediate pleasurable outcomes and inhibitory signals mediated by a prefrontal reflective system. The resulting impairment in behavioral control represents a hallmark of alcohol use disorders (AUDs), a chronic relapsing disorder characterized by excessive alcohol consumption despite devastating consequences. This review aims to summarize available magnetic resonance imaging (MRI) evidence on reward-related decision-making alterations in AUDs, and to envision possible future research directions. We review functional MRI (fMRI) studies using tasks involving monetary rewards, as well as MRI studies relating decision-making parameters to neurostructural gray- or white-matter metrics. The available data suggest that excessive alcohol exposure affects neural signaling within brain networks underlying adaptive behavioral learning via the implementation of prediction errors. Namely, weaker ventromedial prefrontal cortex activity and altered connectivity between ventral striatum and dorsolateral prefrontal cortex likely underpin a shift from goal-directed to habitual actions which, in turn, might underpin compulsive alcohol consumption and relapsing episodes despite adverse consequences. Overall, these data highlight abnormal fronto-striatal connectivity as a candidate neurobiological marker of impaired choice in AUDs. Further studies are needed, however, to unveil its implications in the multiple facets of decision-making.

  10. Neurologic Correlates of Gait Abnormalities in Cerebral Palsy: Implications for Treatment

    PubMed Central

    Zhou, Joanne; Butler, Erin E.; Rose, Jessica

    2017-01-01

    Cerebral palsy (CP) is the most common movement disorder in children. A diagnosis of CP is often made based on abnormal muscle tone or posture, a delay in reaching motor milestones, or the presence of gait abnormalities in young children. Neuroimaging of high-risk neonates and of children diagnosed with CP have identified patterns of neurologic injury associated with CP, however, the neural underpinnings of common gait abnormalities remain largely uncharacterized. Here, we review the nature of the brain injury in CP, as well as the neuromuscular deficits and subsequent gait abnormalities common among children with CP. We first discuss brain injury in terms of mechanism, pattern, and time of injury during the prenatal, perinatal, or postnatal period in preterm and term-born children. Second, we outline neuromuscular deficits of CP with a focus on spastic CP, characterized by muscle weakness, shortened muscle-tendon unit, spasticity, and impaired selective motor control, on both a microscopic and functional level. Third, we examine the influence of neuromuscular deficits on gait abnormalities in CP, while considering emerging information on neural correlates of gait abnormalities and the implications for strategic treatment. This review of the neural basis of gait abnormalities in CP discusses what is known about links between the location and extent of brain injury and the type and severity of CP, in relation to the associated neuromuscular deficits, and subsequent gait abnormalities. Targeted treatment opportunities are identified that may improve functional outcomes for children with CP. By providing this context on the neural basis of gait abnormalities in CP, we hope to highlight areas of further research that can reduce the long-term, debilitating effects of CP. PMID:28367118

  11. Neural electrical activity and neural network growth.

    PubMed

    Gafarov, F M

    2018-05-01

    The development of central and peripheral neural system depends in part on the emergence of the correct functional connectivity in its input and output pathways. Now it is generally accepted that molecular factors guide neurons to establish a primary scaffold that undergoes activity-dependent refinement for building a fully functional circuit. However, a number of experimental results obtained recently shows that the neuronal electrical activity plays an important role in the establishing of initial interneuronal connections. Nevertheless, these processes are rather difficult to study experimentally, due to the absence of theoretical description and quantitative parameters for estimation of the neuronal activity influence on growth in neural networks. In this work we propose a general framework for a theoretical description of the activity-dependent neural network growth. The theoretical description incorporates a closed-loop growth model in which the neural activity can affect neurite outgrowth, which in turn can affect neural activity. We carried out the detailed quantitative analysis of spatiotemporal activity patterns and studied the relationship between individual cells and the network as a whole to explore the relationship between developing connectivity and activity patterns. The model, developed in this work will allow us to develop new experimental techniques for studying and quantifying the influence of the neuronal activity on growth processes in neural networks and may lead to a novel techniques for constructing large-scale neural networks by self-organization. Copyright © 2018 Elsevier Ltd. All rights reserved.

  12. Neural network regulation driven by autonomous neural firings

    NASA Astrophysics Data System (ADS)

    Cho, Myoung Won

    2016-07-01

    Biological neurons naturally fire spontaneously due to the existence of a noisy current. Such autonomous firings may provide a driving force for network formation because synaptic connections can be modified due to neural firings. Here, we study the effect of autonomous firings on network formation. For the temporally asymmetric Hebbian learning, bidirectional connections lose their balance easily and become unidirectional ones. Defining the difference between reciprocal connections as new variables, we could express the learning dynamics as if Ising model spins interact with each other in magnetism. We present a theoretical method to estimate the interaction between the new variables in a neural system. We apply the method to some network systems and find some tendencies of autonomous neural network regulation.

  13. Genetically induced abnormal cranial development in human trisomy 18 with holoprosencephaly: comparisons with the normal tempo of osteogenic-neural development.

    PubMed

    Reid, Shaina N; Ziermann, Janine M; Gondré-Lewis, Marjorie C

    2015-07-01

    Craniofacial malformations are common congenital defects caused by failed midline inductive signals. These midline defects are associated with exposure of the fetus to exogenous teratogens and with inborn genetic errors such as those found in Down, Patau, Edwards' and Smith-Lemli-Opitz syndromes. Yet, there are no studies that analyze contributions of synchronous neurocranial and neural development in these disorders. Here we present the first in-depth analysis of malformations of the basicranium of a holoprosencephalic (HPE) trisomy 18 (T18; Edwards' syndrome) fetus with synophthalmic cyclopia and alobar HPE. With a combination of traditional gross dissection and state-of-the-art computed tomography, we demonstrate the deleterious effects of T18 caused by a translocation at 18p11.31. Bony features included a single developmentally unseparated frontal bone, and complete dual absence of the anterior cranial fossa and ethmoid bone. From a superior view with the calvarium plates removed, there was direct visual access to the orbital foramen and hard palate. Both the eyes and the pituitary gland, normally protected by bony structures, were exposed in the cranial cavity and in direct contact with the brain. The middle cranial fossa was shifted anteriorly, and foramina were either missing or displaced to an abnormal location due to the absence or misplacement of its respective cranial nerve (CN). When CN development was conserved in its induction and placement, the respective foramen developed in its normal location albeit with abnormal gross anatomical features, as seen in the facial nerve (CNVII) and the internal acoustic meatus. More anteriorly localized CNs and their foramina were absent or heavily disrupted compared with posterior ones. The severe malformations exhibited in the cranial fossae, orbital region, pituitary gland and sella turcica highlight the crucial involvement of transcription factors such as TGIF, which is located on chromosome 18 and contributes

  14. Abnormalities of the executive control network in multiple sclerosis phenotypes: An fMRI effective connectivity study.

    PubMed

    Dobryakova, Ekaterina; Rocca, Maria Assunta; Valsasina, Paola; Ghezzi, Angelo; Colombo, Bruno; Martinelli, Vittorio; Comi, Giancarlo; DeLuca, John; Filippi, Massimo

    2016-06-01

    The Stroop interference task is a cognitively demanding task of executive control, a cognitive ability that is often impaired in patients with multiple sclerosis (MS). The aim of this study was to compare effective connectivity patterns within a network of brain regions involved in the Stroop task performance between MS patients with three disease clinical phenotypes [relapsing-remitting (RRMS), benign (BMS), and secondary progressive (SPMS)] and healthy subjects. Effective connectivity analysis was performed on Stroop task data using a novel method based on causal Bayes networks. Compared with controls, MS phenotypes were slower at performing the task and had reduced performance accuracy during incongruent trials that required increased cognitive control. MS phenotypes also exhibited connectivity abnormalities reflected as weaker shared connections, presence of extra connections (i.e., connections absent in the HC connectivity pattern), connection reversal, and loss. In SPMS and the BMS groups but not in the RRMS group, extra connections were associated with deficits in the Stroop task performance. In the BMS group, the response time associated with correct responses during the congruent condition showed a positive correlation with the left posterior parietal → dorsal anterior cingulate connection. In the SPMS group, performance accuracy during the congruent condition showed a negative correlation with the right insula → left insula connection. No associations between extra connections and behavioral performance measures were observed in the RRMS group. These results suggest that, depending on the phenotype, patients with MS use different strategies when cognitive control demands are high and rely on different network connections. Hum Brain Mapp, 37:2293-2304, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  15. Abnormalities in fronto-striatal connectivity within language networks relate to differences in grey-matter heterogeneity in Asperger syndrome☆

    PubMed Central

    Radulescu, Eugenia; Minati, Ludovico; Ganeshan, Balaji; Harrison, Neil A.; Gray, Marcus A.; Beacher, Felix D.C.C.; Chatwin, Chris; Young, Rupert C.D.; Critchley, Hugo D.

    2013-01-01

    Asperger syndrome (AS) is an Autism Spectrum Disorder (ASD) characterised by qualitative impairment in the development of emotional and social skills with relative preservation of general intellectual abilities, including verbal language. People with AS may nevertheless show atypical language, including rate and frequency of speech production. We previously observed that abnormalities in grey matter homogeneity (measured with texture analysis of structural MR images) in AS individuals when compared with controls are also correlated with the volume of caudate nucleus. Here, we tested a prediction that these distributed abnormalities in grey matter compromise the functional integrity of brain networks supporting verbal communication skills. We therefore measured the functional connectivity between caudate nucleus and cortex during a functional neuroimaging study of language generation (verbal fluency), applying psycho-physiological interaction (PPI) methods to test specifically for differences attributable to grey matter heterogeneity in AS participants. Furthermore, we used dynamic causal modelling (DCM) to characterise the causal directionality of these differences in interregional connectivity during word production. Our results revealed a diagnosis-dependent influence of grey matter heterogeneity on the functional connectivity of the caudate nuclei with right insula/inferior frontal gyrus and anterior cingulate, respectively with the left superior frontal gyrus and right precuneus. Moreover, causal modelling of interactions between inferior frontal gyri, caudate and precuneus, revealed a reliance on bottom-up (stimulus-driven) connections in AS participants that contrasted with a dominance of top-down (cognitive control) connections from prefrontal cortex observed in control participants. These results provide detailed support for previously hypothesised central disconnectivity in ASD and specify discrete brain network targets for diagnosis and therapy in ASD

  16. Marshall-Smith syndrome: natural history and evidence of an osteochondrodysplasia with connective tissue abnormalities.

    PubMed

    Adam, Margaret P; Hennekam, Raoul C M; Keppen, Laura Davis; Bull, Marilyn J; Clericuzio, Carol L; Burke, Leah W; Ormond, Kelly E; Hoyme, Eugene H

    2005-08-30

    The Marshall-Smith syndrome (MSS) is a distinct malformation syndrome characterized by accelerated skeletal maturation, relative failure to thrive, respiratory difficulties, mental retardation, and unusual facies, including prominent forehead, shallow orbits, blue sclerae, depressed nasal bridge, and micrognathia. At least 33 cases have been reported in the literature, mostly as single case reports or small series. The purpose of the present study is to report on the clinical findings and natural history of MSS in five children and to review the features of three others previously reported, with particular attention to the skeletal and connective tissue findings. Our study demonstrates an increased rate of nontraumatic fractures and other bony and connective tissue abnormalities that support the hypothesis that MSS should be considered an osteochondrodysplasia. In addition, long-term survival beyond infancy is possible if respiratory problems are expectantly and aggressively managed. (c) 2005 Wiley-Liss, Inc.

  17. Ectopic Expression of Nolz-1 in Neural Progenitors Promotes Cell Cycle Exit/Premature Neuronal Differentiation Accompanying with Abnormal Apoptosis in the Developing Mouse Telencephalon

    PubMed Central

    Chang, Sunny Li-Yun; Chen, Shih-Yun; Huang, Huai-Huei; Ko, Hsin-An; Liu, Pei-Tsen; Liu, Ya-Chi; Chen, Ping-Hau; Liu, Fu-Chin

    2013-01-01

    Nolz-1, as a murine member of the NET zinc-finger protein family, is expressed in post-mitotic differentiating neurons of striatum during development. To explore the function of Nolz-1 in regulating the neurogenesis of forebrain, we studied the effects of ectopic expression of Nolz-1 in neural progenitors. We generated the Cre-loxP dependent conditional transgenic mice in which Nolz-1 was ectopically expressed in proliferative neural progenitors. Ectopic expression of Nolz-1 in neural progenitors by intercrossing the Nolz-1 conditional transgenic mice with the nestin-Cre mice resulted in hypoplasia of telencephalon in double transgenic mice. Decreased proliferation of neural progenitor cells were found in the telencephalon, as evidenced by the reduction of BrdU−, Ki67− and phospho-histone 3-positive cells in E11.5–12.5 germinal zone of telencephalon. Transgenic Nolz-1 also promoted cell cycle exit and as a consequence might facilitate premature differentiation of progenitors, because TuJ1-positive neurons were ectopically found in the ventricular zone and there was a general increase of TuJ1 immunoreactivity in the telencephalon. Moreover, clusters of strong TuJ1-expressing neurons were present in E12.5 germinal zone. Some of these strong TuJ1-positive clusters, however, contained apoptotic condensed DNA, suggesting that inappropriate premature differentiation may lead to abnormal apoptosis in some progenitor cells. Consistent with the transgenic mouse analysis in vivo, similar effects of Nozl-1 over-expression in induction of apoptosis, inhibition of cell proliferation and promotion of neuronal differentiation were also observed in three different N18, ST14A and N2A neural cell lines in vitro. Taken together, our study indicates that ectopic expression of Nolz-1 in neural progenitors promotes cell cycle exit/premature neuronal differentiation and induces abnormal apoptosis in the developing telencephalon. PMID:24073229

  18. Ectopic expression of nolz-1 in neural progenitors promotes cell cycle exit/premature neuronal differentiation accompanying with abnormal apoptosis in the developing mouse telencephalon.

    PubMed

    Chang, Sunny Li-Yun; Chen, Shih-Yun; Huang, Huai-Huei; Ko, Hsin-An; Liu, Pei-Tsen; Liu, Ya-Chi; Chen, Ping-Hau; Liu, Fu-Chin

    2013-01-01

    Nolz-1, as a murine member of the NET zinc-finger protein family, is expressed in post-mitotic differentiating neurons of striatum during development. To explore the function of Nolz-1 in regulating the neurogenesis of forebrain, we studied the effects of ectopic expression of Nolz-1 in neural progenitors. We generated the Cre-loxP dependent conditional transgenic mice in which Nolz-1 was ectopically expressed in proliferative neural progenitors. Ectopic expression of Nolz-1 in neural progenitors by intercrossing the Nolz-1 conditional transgenic mice with the nestin-Cre mice resulted in hypoplasia of telencephalon in double transgenic mice. Decreased proliferation of neural progenitor cells were found in the telencephalon, as evidenced by the reduction of BrdU-, Ki67- and phospho-histone 3-positive cells in E11.5-12.5 germinal zone of telencephalon. Transgenic Nolz-1 also promoted cell cycle exit and as a consequence might facilitate premature differentiation of progenitors, because TuJ1-positive neurons were ectopically found in the ventricular zone and there was a general increase of TuJ1 immunoreactivity in the telencephalon. Moreover, clusters of strong TuJ1-expressing neurons were present in E12.5 germinal zone. Some of these strong TuJ1-positive clusters, however, contained apoptotic condensed DNA, suggesting that inappropriate premature differentiation may lead to abnormal apoptosis in some progenitor cells. Consistent with the transgenic mouse analysis in vivo, similar effects of Nozl-1 over-expression in induction of apoptosis, inhibition of cell proliferation and promotion of neuronal differentiation were also observed in three different N18, ST14A and N2A neural cell lines in vitro. Taken together, our study indicates that ectopic expression of Nolz-1 in neural progenitors promotes cell cycle exit/premature neuronal differentiation and induces abnormal apoptosis in the developing telencephalon.

  19. Backward renormalization-group inference of cortical dipole sources and neural connectivity efficacy

    NASA Astrophysics Data System (ADS)

    Amaral, Selene da Rocha; Baccalá, Luiz A.; Barbosa, Leonardo S.; Caticha, Nestor

    2017-06-01

    Proper neural connectivity inference has become essential for understanding cognitive processes associated with human brain function. Its efficacy is often hampered by the curse of dimensionality. In the electroencephalogram case, which is a noninvasive electrophysiological monitoring technique to record electrical activity of the brain, a possible way around this is to replace multichannel electrode information with dipole reconstructed data. We use a method based on maximum entropy and the renormalization group to infer the position of the sources, whose success hinges on transmitting information from low- to high-resolution representations of the cortex. The performance of this method compares favorably to other available source inference algorithms, which are ranked here in terms of their performance with respect to directed connectivity inference by using artificially generated dynamic data. We examine some representative scenarios comprising different numbers of dynamically connected dipoles over distinct cortical surface positions and under different sensor noise impairment levels. The overall conclusion is that inverse problem solutions do not affect the correct inference of the direction of the flow of information as long as the equivalent dipole sources are correctly found.

  20. Cocaine addiction is associated with abnormal prefrontal function, increased striatal connectivity and sensitivity to monetary incentives, and decreased connectivity outside the human reward circuit.

    PubMed

    Vaquero, Lucía; Cámara, Estela; Sampedro, Frederic; Pérez de Los Cobos, José; Batlle, Francesca; Fabregas, Josep Maria; Sales, Joan Artur; Cervantes, Mercè; Ferrer, Xavier; Lazcano, Gerardo; Rodríguez-Fornells, Antoni; Riba, Jordi

    2017-05-01

    Cocaine addiction has been associated with increased sensitivity of the human reward circuit to drug-related stimuli. However, the capacity of non-drug incentives to engage this network is poorly understood. Here, we characterized the functional sensitivity to monetary incentives and the structural integrity of the human reward circuit in abstinent cocaine-dependent (CD) patients and their matched controls. We assessed the BOLD response to monetary gains and losses in 30 CD patients and 30 healthy controls performing a lottery task in a magnetic resonance imaging scanner. We measured brain gray matter volume (GMV) using voxel-based morphometry and white matter microstructure using voxel-based fractional anisotropy (FA). Functional data showed that, after monetary incentives, CD patients exhibited higher activation in the ventral striatum than controls. Furthermore, we observed an inverted BOLD response pattern in the prefrontal cortex, with activity being highest after unexpected high gains and lowest after losses. Patients showed increased GMV in the caudate and the orbitofrontal cortex, increased white matter FA in the orbito-striatal pathway but decreased FA in antero-posterior association bundles. Abnormal activation in the prefrontal cortex correlated with GMV and FA increases in the orbitofrontal cortex. While functional abnormalities in the ventral striatum were inversely correlated with abstinence duration, structural alterations were not. In conclusion, results suggest abnormal incentive processing in CD patients with high salience for rewards and punishments in subcortical structures but diminished prefrontal control after adverse outcomes. They further suggest that hypertrophy and hyper-connectivity within the reward circuit, to the expense of connectivity outside this network, characterize cocaine addiction. © 2016 Society for the Study of Addiction.

  1. Reciprocal Inhibitory Connections Within a Neural Network for Rotational Optic-Flow Processing

    PubMed Central

    Haag, Juergen; Borst, Alexander

    2007-01-01

    Neurons in the visual system of the blowfly have large receptive fields that are selective for specific optic flow fields. Here, we studied the neural mechanisms underlying flow–field selectivity in proximal Vertical System (VS)-cells, a particular subset of tangential cells in the fly. These cells have local preferred directions that are distributed such as to match the flow field occurring during a rotation of the fly. However, the neural circuitry leading to this selectivity is not fully understood. Through dual intracellular recordings from proximal VS cells and other tangential cells, we characterized the specific wiring between VS cells themselves and between proximal VS cells and horizontal sensitive tangential cells. We discovered a spiking neuron (Vi) involved in this circuitry that has not been described before. This neuron turned out to be connected to proximal VS cells via gap junctions and, in addition, it was found to be inhibitory onto VS1. PMID:18982122

  2. Altered functional connectivity in default mode network in Internet gaming disorder: Influence of childhood ADHD.

    PubMed

    Lee, Deokjong; Lee, Junghan; Lee, Jung Eun; Jung, Young-Chul

    2017-04-03

    Internet gaming disorder (IGD) is a type of behavioral addiction characterized by abnormal executive control, leading to loss of control over excessive gaming. Attention deficit and hyperactivity disorder (ADHD) is one of the most common comorbid disorders in IGD, involving delayed development of the executive control system, which could predispose individuals to gaming addiction. We investigated the influence of childhood ADHD on neural network features of IGD. Resting-state functional magnetic resonance imaging analysis was performed on 44 young, male IGD subjects with and without childhood ADHD and 19 age-matched, healthy male controls. Posterior cingulate cortex (PCC)-seeded connectivity was evaluated to assess abnormalities in default mode network (DMN) connectivity, which is associated with deficits in executive control. IGD subjects without childhood ADHD showed expanded functional connectivity (FC) between DMN-related regions (PCC, medial prefrontal cortex, thalamus) compared with controls. These subjects also exhibited expanded FC between the PCC and brain regions implicated in salience processing (anterior insula, orbitofrontal cortex) compared with IGD subjects with childhood ADHD. IGD subjects with childhood ADHD showed expanded FC between the PCC and cerebellum (crus II), a region involved in executive control. The strength of connectivity between the PCC and cerebellum (crus II) was positively correlated with self-reporting scales reflecting impulsiveness. Individuals with IGD showed altered PCC-based FC, the characteristics of which might be dependent upon history of childhood ADHD. Our findings suggest that altered neural networks for executive control in ADHD would be a predisposition for developing IGD. Copyright © 2017 Elsevier Inc. All rights reserved.

  3. Abnormalities in lung volumes and airflow in children with newly diagnosed connective tissue disease.

    PubMed

    Peradzyńska, Joanna; Krenke, Katarzyna; Szylling, Anna; Kołodziejczyk, Beata; Gazda, Agnieszka; Rutkowska-Sak, Lidia; Kulus, Marek

    2016-01-01

    Connective tissue diseases (CTDs) of childhood are rare inflammatory disorders, involving various organs and tissues including respiratory system. Pulmonary involvement in patients with CTDs is uncommon but may cause functional impairment. Data on prevalence and type of lung function abnormalities in children with CTDs are scarce. Thus, the aim of this study was to asses pulmonary functional status in children with newly diagnosed CTD and follow the results after two years of the disease course. There were 98 children (mean age: 13 ± 3; 76 girls), treated in Department of Pediatric Rheumatology, Institute of Rheumatology, Warsaw and 80 aged-matched, healthy controls (mean age 12.7 ± 2.4; 50 girls) included into the study. Study procedures included medical history, physical examination, chest radiograph and PFT (spirometry and whole body-plethysmography). Then, the assessment of PFT was performed after 24 months. FEV₁, FEV₁/FVC and MEF50 were significantly lower in CTD as compared to control group, there was no difference in FVC and TLC. The proportion of patients with abnormal lung function was significantly higher in the study group, 41 (42%) vs 9 (11%). 24-months observation didn't reveal progression in lung function impairment. Lung function impairment is relatively common in children with CTDs. Although restrictive ventilatory pattern is considered typical feature of lung involvement in CTDs, airflow limitation could also be an initial abnormality.

  4. Genetic dyslexia risk variant is related to neural connectivity patterns underlying phonological awareness in children.

    PubMed

    Skeide, Michael A; Kirsten, Holger; Kraft, Indra; Schaadt, Gesa; Müller, Bent; Neef, Nicole; Brauer, Jens; Wilcke, Arndt; Emmrich, Frank; Boltze, Johannes; Friederici, Angela D

    2015-09-01

    Phonological awareness is the best-validated predictor of reading and spelling skill and therefore highly relevant for developmental dyslexia. Prior imaging genetics studies link several dyslexia risk genes to either brain-functional or brain-structural factors of phonological deficits. However, coherent evidence for genetic associations with both functional and structural neural phenotypes underlying variation in phonological awareness has not yet been provided. Here we demonstrate that rs11100040, a reported modifier of SLC2A3, is related to the functional connectivity of left fronto-temporal phonological processing areas at resting state in a sample of 9- to 12-year-old children. Furthermore, we provide evidence that rs11100040 is related to the fractional anisotropy of the arcuate fasciculus, which forms the structural connection between these areas. This structural connectivity phenotype is associated with phonological awareness, which is in turn associated with the individual retrospective risk scores in an early dyslexia screening as well as to spelling. These results suggest a link between a dyslexia risk genotype and a functional as well as a structural neural phenotype, which is associated with a phonological awareness phenotype. The present study goes beyond previous work by integrating genetic, brain-functional and brain-structural aspects of phonological awareness within a single approach. These combined findings might be another step towards a multimodal biomarker for developmental dyslexia. Copyright © 2015 Elsevier Inc. All rights reserved.

  5. Abnormal brain functional connectivity leads to impaired mood and cognition in hyperthyroidism: a resting-state functional MRI study

    PubMed Central

    Li, Ling; Zhi, Mengmeng; Hou, Zhenghua; Zhang, Yuqun; Yue, Yingying; Yuan, Yonggui

    2017-01-01

    Patients with hyperthyroidism frequently have neuropsychiatric complaints such as lack of concentration, poor memory, depression, anxiety, nervousness, and irritability, suggesting brain dysfunction. However, the underlying process of these symptoms remains unclear. Using resting-state functional magnetic resonance imaging (rs-fMRI), we depicted the altered graph theoretical metric degree centrality (DC) and seed-based resting-state functional connectivity (FC) in 33 hyperthyroid patients relative to 33 healthy controls. The peak points of significantly altered DC between the two groups were defined as the seed regions to calculate FC to the whole brain. Then, partial correlation analyses were performed between abnormal DC, FC and neuropsychological performances, as well as some clinical indexes. The decreased intrinsic functional connectivity in the posterior lobe of cerebellum (PLC) and medial frontal gyrus (MeFG), as well as the abnormal seed-based FC anchored in default mode network (DMN), attention network, visual network and cognitive network in this study, possibly constitutes the latent mechanism for emotional and cognitive changes in hyperthyroidism, including anxiety and impaired processing speed. PMID:28009983

  6. Abnormal brain functional connectivity leads to impaired mood and cognition in hyperthyroidism: a resting-state functional MRI study.

    PubMed

    Li, Ling; Zhi, Mengmeng; Hou, Zhenghua; Zhang, Yuqun; Yue, Yingying; Yuan, Yonggui

    2017-01-24

    Patients with hyperthyroidism frequently have neuropsychiatric complaints such as lack of concentration, poor memory, depression, anxiety, nervousness, and irritability, suggesting brain dysfunction. However, the underlying process of these symptoms remains unclear. Using resting-state functional magnetic resonance imaging (rs-fMRI), we depicted the altered graph theoretical metric degree centrality (DC) and seed-based resting-state functional connectivity (FC) in 33 hyperthyroid patients relative to 33 healthy controls. The peak points of significantly altered DC between the two groups were defined as the seed regions to calculate FC to the whole brain. Then, partial correlation analyses were performed between abnormal DC, FC and neuropsychological performances, as well as some clinical indexes. The decreased intrinsic functional connectivity in the posterior lobe of cerebellum (PLC) and medial frontal gyrus (MeFG), as well as the abnormal seed-based FC anchored in default mode network (DMN), attention network, visual network and cognitive network in this study, possibly constitutes the latent mechanism for emotional and cognitive changes in hyperthyroidism, including anxiety and impaired processing speed.

  7. Intrinsic gray-matter connectivity of the brain in adults with autism spectrum disorder.

    PubMed

    Ecker, Christine; Ronan, Lisa; Feng, Yue; Daly, Eileen; Murphy, Clodagh; Ginestet, Cedric E; Brammer, Michael; Fletcher, Paul C; Bullmore, Edward T; Suckling, John; Baron-Cohen, Simon; Williams, Steve; Loth, Eva; Murphy, Declan G M

    2013-08-06

    Autism spectrum disorders (ASD) are a group of neurodevelopmental conditions that are accompanied by atypical brain connectivity. So far, in vivo evidence for atypical structural brain connectivity in ASD has mainly been based on neuroimaging studies of cortical white matter. However, genetic studies suggest that abnormal connectivity in ASD may also affect neural connections within the cortical gray matter. Such intrinsic gray-matter connections are inherently more difficult to describe in vivo but may be inferred from a variety of surface-based geometric features that can be measured using magnetic resonance imaging. Here, we present a neuroimaging study that examines the intrinsic cortico-cortical connectivity of the brain in ASD using measures of "cortical separation distances" to assess the global and local intrinsic "wiring costs" of the cortex (i.e., estimated length of horizontal connections required to wire the cortex within the cortical sheet). In a sample of 68 adults with ASD and matched controls, we observed significantly reduced intrinsic wiring costs of cortex in ASD, both globally and locally. Differences in global and local wiring cost were predominantly observed in fronto-temporal regions and also significantly predicted the severity of social and repetitive symptoms (respectively). Our study confirms that atypical cortico-cortical "connectivity" in ASD is not restricted to the development of white-matter connections but may also affect the intrinsic gray-matter architecture (and connectivity) within the cortical sheet. Thus, the atypical connectivity of the brain in ASD is complex, affecting both gray and white matter, and forms part of the core neural substrates underlying autistic symptoms.

  8. Self-regulation of brain oscillations as a treatment for aberrant brain connections in children with autism.

    PubMed

    Pineda, J A; Juavinett, A; Datko, M

    2012-12-01

    Autism is a highly varied developmental disorder typically characterized by deficits in reciprocal social interaction, difficulties with verbal and nonverbal communication, and restricted interests and repetitive behaviors. Although a wide range of behavioral, pharmacological, and alternative medicine strategies have been reported to ameliorate specific symptoms for some individuals, there is at present no cure for the condition. Nonetheless, among the many incompatible observations about aspects of the development, anatomy, and functionality of the autistic brain, it is widely agreed that it is characterized by widespread aberrant connectivity. Such disordered connectivity, be it increased, decreased, or otherwise compromised, may complicate healthy synchronization and communication among and within different neural circuits, thereby producing abnormal processing of sensory inputs necessary for normal social life. It is widely accepted that the innate properties of brain electrical activity produce pacemaker elements and linked networks that oscillate synchronously or asynchronously, likely reflecting a type of functional connectivity. Using phase coherence in multiple frequency EEG bands as a measure of functional connectivity, studies have shown evidence for both global hypoconnectivity and local hyperconnectivity in individuals with ASD. However, the nature of the brain's experience-dependent structural plasticity suggests that these abnormal patterns may be reversed with the proper type of treatment. Indeed, neurofeedback (NF) training, an intervention based on operant conditioning that results in self-regulation of brain electrical oscillations, has shown promise in addressing marked abnormalities in functional and structural connectivity. It is hypothesized that neurofeedback produces positive behavioral changes in ASD children by normalizing the aberrant connections within and between neural circuits. NF exploits the brain's plasticity to normalize aberrant

  9. Resting state EEG abnormalities in autism spectrum disorders

    PubMed Central

    2013-01-01

    Autism spectrum disorders (ASD) are a group of complex and heterogeneous developmental disorders involving multiple neural system dysfunctions. In an effort to understand neurophysiological substrates, identify etiopathophysiologically distinct subgroups of patients, and track outcomes of novel treatments with translational biomarkers, EEG (electroencephalography) studies offer a promising research strategy in ASD. Resting-state EEG studies of ASD suggest a U-shaped profile of electrophysiological power alterations, with excessive power in low-frequency and high-frequency bands, abnormal functional connectivity, and enhanced power in the left hemisphere of the brain. In this review, we provide a summary of recent findings, discuss limitations in available research that may contribute to inconsistencies in the literature, and offer suggestions for future research in this area for advancing the understanding of ASD. PMID:24040879

  10. Differential Patterns of Abnormal Activity and Connectivity in the Amygdala-Prefrontal Circuitry in Bipolar-I and Bipolar-NOS Youth

    ERIC Educational Resources Information Center

    Ladouceur, Cecile D.; Farchione, Tiffany; Diwadkar, Vaibhav; Pruitt, Patrick; Radwan, Jacqueline; Axelson, David A.; Birmaher, Boris; Phillips, Mary L.

    2011-01-01

    Objective: The functioning of neural systems supporting emotion processing and regulation in youth with bipolar disorder not otherwise specified (BP-NOS) remains poorly understood. We sought to examine patterns of activity and connectivity in youth with BP-NOS relative to youth with bipolar disorder type I (BP-I) and healthy controls (HC). Method:…

  11. A critical appraisal of neuroimaging studies of bipolar disorder: toward a new conceptualization of underlying neural circuitry and roadmap for future research

    PubMed Central

    Phillips, Mary L; Swartz, Holly A.

    2014-01-01

    Objective This critical review appraises neuroimaging findings in bipolar disorder in emotion processing, emotion regulation, and reward processing neural circuitry, to synthesize current knowledge of the neural underpinnings of bipolar disorder, and provide a neuroimaging research “roadmap” for future studies. Method We examined findings from all major studies in bipolar disorder that used fMRI, volumetric analyses, diffusion imaging, and resting state techniques, to inform current conceptual models of larger-scale neural circuitry abnormalities in bipolar disorder Results Bipolar disorder can be conceptualized in neural circuitry terms as parallel dysfunction in bilateral prefrontal cortical (especially ventrolateral prefrontal cortical)-hippocampal-amygdala emotion processing and emotion regulation neural circuitries, together with an “overactive” left-sided ventral striatal-ventrolateral and orbitofrontal cortical reward processing circuitry, that result in characteristic behavioral abnormalities associated with bipolar disorder: emotional lability, emotional dysregulation and heightened reward sensitivity. A potential structural basis for these functional abnormalities are gray matter decreases in prefrontal and temporal cortices, amygdala and hippocampus, and fractional anisotropy decreases in white matter tracts connecting prefrontal and subcortical regions. Conclusion Neuroimaging studies of bipolar disorder clearly demonstrate abnormalities in neural circuitries supporting emotion processing, emotion regulation and reward processing, although there are several limitations to these studies. Future neuroimaging research in bipolar disorder should include studies adopting dimensional approaches; larger studies examining neurodevelopmental trajectories in bipolar disorder and at-risk youth; multimodal neuroimaging studies using integrated systems approaches; and studies using pattern recognition approaches to provide clinically useful, individual

  12. The effect of the neural activity on topological properties of growing neural networks.

    PubMed

    Gafarov, F M; Gafarova, V R

    2016-09-01

    The connectivity structure in cortical networks defines how information is transmitted and processed, and it is a source of the complex spatiotemporal patterns of network's development, and the process of creation and deletion of connections is continuous in the whole life of the organism. In this paper, we study how neural activity influences the growth process in neural networks. By using a two-dimensional activity-dependent growth model we demonstrated the neural network growth process from disconnected neurons to fully connected networks. For making quantitative investigation of the network's activity influence on its topological properties we compared it with the random growth network not depending on network's activity. By using the random graphs theory methods for the analysis of the network's connections structure it is shown that the growth in neural networks results in the formation of a well-known "small-world" network.

  13. Identification of Abnormal System Noise Temperature Patterns in Deep Space Network Antennas Using Neural Network Trained Fuzzy Logic

    NASA Technical Reports Server (NTRS)

    Lu, Thomas; Pham, Timothy; Liao, Jason

    2011-01-01

    This paper presents the development of a fuzzy logic function trained by an artificial neural network to classify the system noise temperature (SNT) of antennas in the NASA Deep Space Network (DSN). The SNT data were classified into normal, marginal, and abnormal classes. The irregular SNT pattern was further correlated with link margin and weather data. A reasonably good correlation is detected among high SNT, low link margin and the effect of bad weather; however we also saw some unexpected non-correlations which merit further study in the future.

  14. Conservatism and the neural circuitry of threat: economic conservatism predicts greater amygdala–BNST connectivity during periods of threat vs safety

    PubMed Central

    Muftuler, L Tugan; Larson, Christine L

    2018-01-01

    Abstract Political conservatism is associated with an increased negativity bias, including increased attention and reactivity toward negative and threatening stimuli. Although the human amygdala has been implicated in the response to threatening stimuli, no studies to date have investigated whether conservatism is associated with altered amygdala function toward threat. Furthermore, although an influential theory posits that connectivity between the amygdala and bed nucleus of the stria terminalis (BNST) is important in initiating the response to sustained or uncertain threat, whether individual differences in conservatism modulate this connectivity is unknown. To test whether conservatism is associated with increased reactivity in neural threat circuitry, we measured participants’ self-reported social and economic conservatism and asked them to complete high-resolution fMRI scans while under threat of an unpredictable shock and while safe. We found that economic conservatism predicted greater connectivity between the BNST and a cluster of voxels in the left amygdala during threat vs safety. These results suggest that increased amygdala–BNST connectivity during threat may be a key neural correlate of the enhanced negativity bias found in conservatism. PMID:29126127

  15. Impaired functional but preserved structural connectivity in limbic white matter tracts in youth with conduct disorder or oppositional defiant disorder plus psychopathic traits.

    PubMed

    Finger, Elizabeth Carrie; Marsh, Abigail; Blair, Karina Simone; Majestic, Catherine; Evangelou, Iordanis; Gupta, Karan; Schneider, Marguerite Reid; Sims, Courtney; Pope, Kayla; Fowler, Katherine; Sinclair, Stephen; Tovar-Moll, Fernanda; Pine, Daniel; Blair, Robert James

    2012-06-30

    Youths with conduct disorder or oppositional defiant disorder and psychopathic traits (CD/ODD+PT) are at high risk of adult antisocial behavior and psychopathy. Neuroimaging studies demonstrate functional abnormalities in orbitofrontal cortex and the amygdala in both youths and adults with psychopathic traits. Diffusion tensor imaging in psychopathic adults demonstrates disrupted structural connectivity between these regions (uncinate fasiculus). The current study examined whether functional neural abnormalities present in youths with CD/ODD+PT are associated with similar white matter abnormalities. Youths with CD/ODD+PT and comparison participants completed 3.0 T diffusion tensor scans and functional magnetic resonance imaging scans. Diffusion tensor imaging did not reveal disruption in structural connections within the uncinate fasiculus or other white matter tracts in youths with CD/ODD+PT, despite the demonstration of disrupted amygdala-prefrontal functional connectivity in these youths. These results suggest that disrupted amygdala-frontal white matter connectivity as measured by fractional anisotropy is less sensitive than imaging measurements of functional perturbations in youths with psychopathic traits. If white matter tracts are intact in youths with this disorder, childhood may provide a critical window for intervention and treatment, before significant structural brain abnormalities solidify. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  16. Binary synaptic connections based on memory switching in a-Si:H for artificial neural networks

    NASA Technical Reports Server (NTRS)

    Thakoor, A. P.; Lamb, J. L.; Moopenn, A.; Khanna, S. K.

    1987-01-01

    A scheme for nonvolatile associative electronic memory storage with high information storage density is proposed which is based on neural network models and which uses a matrix of two-terminal passive interconnections (synapses). It is noted that the massive parallelism in the architecture would require the ON state of a synaptic connection to be unusually weak (highly resistive). Memory switching using a-Si:H along with ballast resistors patterned from amorphous Ge-metal alloys is investigated for a binary programmable read only memory matrix. The fabrication of a 1600 synapse test array of uniform connection strengths and a-Si:H switching elements is discussed.

  17. Connectivity constraints on cortical reorganization of neural circuits involved in object naming.

    PubMed

    Papagno, Costanza; Gallucci, Marcello; Casarotti, Alessandra; Castellano, Antonella; Falini, Andrea; Fava, Enrica; Giussani, Carlo; Carrabba, Giorgio; Bello, Lorenzo; Caramazza, Alfonso

    2011-04-01

    The brain's plasticity in response to sensory deprivation and other perturbations is well established. While the functional properties of the reorganized areas are under vigorous investigation, the factors that constrain cortical reorganization remain poorly understood. One factor constraining such reorganization may be long-distance subcortical connectivity between relevant cortical regions-reorganization attempts to preserve the functionality of subcortical connections. Here we provide human neurophysiological evidence for the role of the subcortical connections in shaping cortical reorganization of the networks involved in object naming following perturbation of normal function. We used direct electrical stimulation (DES) during surgical removal of gliomas to identify the sites that are involved in naming different categories of objects. The sites that were selectively inhibited in naming either living or non-living objects were displaced relative to those observed with other subject populations, possibly reflecting cortical reorganization due to slowly evolving brain damage. Subcortical DES applied to the white matter underlying these regions also led to category-specific naming deficits. The existence of these subcortical fiber pathways was confirmed using diffusion tensor tractography. These results constitute the first neurophysiological evidence for the critical role of subcortical pathways as part of the neural circuits that are involved in object naming; they also highlight the importance of subcortical connectivity in shaping cortical reorganization following perturbations of normal function. Copyright © 2011 Elsevier Inc. All rights reserved.

  18. Abnormal Resting-State Functional Connectivity in Patients with Chronic Fatigue Syndrome: Results of Seed and Data-Driven Analyses.

    PubMed

    Gay, Charles W; Robinson, Michael E; Lai, Song; O'Shea, Andrew; Craggs, Jason G; Price, Donald D; Staud, Roland

    2016-02-01

    Although altered resting-state functional connectivity (FC) is a characteristic of many chronic pain conditions, it has not yet been evaluated in patients with chronic fatigue. Our objective was to investigate the association between fatigue and altered resting-state FC in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Thirty-six female subjects, 19 ME/CFS and 17 healthy controls, completed a fatigue inventory before undergoing functional magnetic resonance imaging. Two methods, (1) data driven and (2) model based, were used to estimate and compare the intraregional FC between both groups during the resting state (RS). The first approach using independent component analysis was applied to investigate five RS networks: the default mode network, salience network (SN), left frontoparietal networks (LFPN) and right frontoparietal networks, and the sensory motor network (SMN). The second approach used a priori selected seed regions demonstrating abnormal regional cerebral blood flow (rCBF) in ME/CFS patients at rest. In ME/CFS patients, Method-1 identified decreased intrinsic connectivity among regions within the LFPN. Furthermore, the FC of the left anterior midcingulate with the SMN and the connectivity of the left posterior cingulate cortex with the SN were significantly decreased. For Method-2, five distinct clusters within the right parahippocampus and occipital lobes, demonstrating significant rCBF reductions in ME/CFS patients, were used as seeds. The parahippocampal seed and three occipital lobe seeds showed altered FC with other brain regions. The degree of abnormal connectivity correlated with the level of self-reported fatigue. Our results confirm altered RS FC in patients with ME/CFS, which was significantly correlated with the severity of their chronic fatigue.

  19. Abnormal Resting-State Functional Connectivity in Patients with Chronic Fatigue Syndrome: Results of Seed and Data-Driven Analyses

    PubMed Central

    Gay, Charles W.; Robinson, Michael E.; Lai, Song; O'Shea, Andrew; Craggs, Jason G.; Price, Donald D.

    2016-01-01

    Abstract Although altered resting-state functional connectivity (FC) is a characteristic of many chronic pain conditions, it has not yet been evaluated in patients with chronic fatigue. Our objective was to investigate the association between fatigue and altered resting-state FC in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Thirty-six female subjects, 19 ME/CFS and 17 healthy controls, completed a fatigue inventory before undergoing functional magnetic resonance imaging. Two methods, (1) data driven and (2) model based, were used to estimate and compare the intraregional FC between both groups during the resting state (RS). The first approach using independent component analysis was applied to investigate five RS networks: the default mode network, salience network (SN), left frontoparietal networks (LFPN) and right frontoparietal networks, and the sensory motor network (SMN). The second approach used a priori selected seed regions demonstrating abnormal regional cerebral blood flow (rCBF) in ME/CFS patients at rest. In ME/CFS patients, Method-1 identified decreased intrinsic connectivity among regions within the LFPN. Furthermore, the FC of the left anterior midcingulate with the SMN and the connectivity of the left posterior cingulate cortex with the SN were significantly decreased. For Method-2, five distinct clusters within the right parahippocampus and occipital lobes, demonstrating significant rCBF reductions in ME/CFS patients, were used as seeds. The parahippocampal seed and three occipital lobe seeds showed altered FC with other brain regions. The degree of abnormal connectivity correlated with the level of self-reported fatigue. Our results confirm altered RS FC in patients with ME/CFS, which was significantly correlated with the severity of their chronic fatigue. PMID:26449441

  20. Neural connectivity in Internet gaming disorder and alcohol use disorder: A resting-state EEG coherence study.

    PubMed

    Park, Su Mi; Lee, Ji Yoon; Kim, Yeon Jin; Lee, Jun-Young; Jung, Hee Yeon; Sohn, Bo Kyung; Kim, Dai Jin; Choi, Jung-Seok

    2017-05-02

    The present study compared neural connectivity and the level of phasic synchronization between neural populations in patients with Internet gaming disorder (IGD), patients with alcohol use disorder (AUD), and healthy controls (HCs) using resting-state electroencephalography (EEG) coherence analyses. For this study, 92 adult males were categorized into three groups: IGD (n = 30), AUD (n = 30), and HC (n = 32). The IGD group exhibited increased intrahemispheric gamma (30-40 Hz) coherence compared to the AUD and HC groups regardless of psychological features (e.g., depression, anxiety, and impulsivity) and right fronto-central gamma coherence positively predicted the scores of the Internet addiction test in all groups. In contrast, the AUD group showed marginal tendency of increased intrahemispheric theta (4-8 Hz) coherence relative to the HC group and this was dependent on the psychological features. The present findings indicate that patients with IGD and AUD exhibit different neurophysiological patterns of brain connectivity and that an increase in the fast phasic synchrony of gamma coherence might be a core neurophysiological feature of IGD.

  1. Neural Cross-Frequency Coupling: Connecting Architectures, Mechanisms, and Functions.

    PubMed

    Hyafil, Alexandre; Giraud, Anne-Lise; Fontolan, Lorenzo; Gutkin, Boris

    2015-11-01

    Neural oscillations are ubiquitously observed in the mammalian brain, but it has proven difficult to tie oscillatory patterns to specific cognitive operations. Notably, the coupling between neural oscillations at different timescales has recently received much attention, both from experimentalists and theoreticians. We review the mechanisms underlying various forms of this cross-frequency coupling. We show that different types of neural oscillators and cross-frequency interactions yield distinct signatures in neural dynamics. Finally, we associate these mechanisms with several putative functions of cross-frequency coupling, including neural representations of multiple environmental items, communication over distant areas, internal clocking of neural processes, and modulation of neural processing based on temporal predictions. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. Altered mGluR5-Homer scaffolds and corticostriatal connectivity in a Shank3 complete knockout model of autism.

    PubMed

    Wang, Xiaoming; Bey, Alexandra L; Katz, Brittany M; Badea, Alexandra; Kim, Namsoo; David, Lisa K; Duffney, Lara J; Kumar, Sunil; Mague, Stephen D; Hulbert, Samuel W; Dutta, Nisha; Hayrapetyan, Volodya; Yu, Chunxiu; Gaidis, Erin; Zhao, Shengli; Ding, Jin-Dong; Xu, Qiong; Chung, Leeyup; Rodriguiz, Ramona M; Wang, Fan; Weinberg, Richard J; Wetsel, William C; Dzirasa, Kafui; Yin, Henry; Jiang, Yong-Hui

    2016-05-10

    Human neuroimaging studies suggest that aberrant neural connectivity underlies behavioural deficits in autism spectrum disorders (ASDs), but the molecular and neural circuit mechanisms underlying ASDs remain elusive. Here, we describe a complete knockout mouse model of the autism-associated Shank3 gene, with a deletion of exons 4-22 (Δe4-22). Both mGluR5-Homer scaffolds and mGluR5-mediated signalling are selectively altered in striatal neurons. These changes are associated with perturbed function at striatal synapses, abnormal brain morphology, aberrant structural connectivity and ASD-like behaviour. In vivo recording reveals that the cortico-striatal-thalamic circuit is tonically hyperactive in mutants, but becomes hypoactive during social behaviour. Manipulation of mGluR5 activity attenuates excessive grooming and instrumental learning differentially, and rescues impaired striatal synaptic plasticity in Δe4-22(-/-) mice. These findings show that deficiency of Shank3 can impair mGluR5-Homer scaffolding, resulting in cortico-striatal circuit abnormalities that underlie deficits in learning and ASD-like behaviours. These data suggest causal links between genetic, molecular, and circuit mechanisms underlying the pathophysiology of ASDs.

  3. Altered mGluR5-Homer scaffolds and corticostriatal connectivity in a Shank3 complete knockout model of autism

    PubMed Central

    Wang, Xiaoming; Bey, Alexandra L.; Katz, Brittany M.; Badea, Alexandra; Kim, Namsoo; David, Lisa K.; Duffney, Lara J.; Kumar, Sunil; Mague, Stephen D.; Hulbert, Samuel W.; Dutta, Nisha; Hayrapetyan, Volodya; Yu, Chunxiu; Gaidis, Erin; Zhao, Shengli; Ding, Jin-Dong; Xu, Qiong; Chung, Leeyup; Rodriguiz, Ramona M.; Wang, Fan; Weinberg, Richard J.; Wetsel, William C.; Dzirasa, Kafui; Yin, Henry; Jiang, Yong-hui

    2016-01-01

    Human neuroimaging studies suggest that aberrant neural connectivity underlies behavioural deficits in autism spectrum disorders (ASDs), but the molecular and neural circuit mechanisms underlying ASDs remain elusive. Here, we describe a complete knockout mouse model of the autism-associated Shank3 gene, with a deletion of exons 4–22 (Δe4–22). Both mGluR5-Homer scaffolds and mGluR5-mediated signalling are selectively altered in striatal neurons. These changes are associated with perturbed function at striatal synapses, abnormal brain morphology, aberrant structural connectivity and ASD-like behaviour. In vivo recording reveals that the cortico-striatal-thalamic circuit is tonically hyperactive in mutants, but becomes hypoactive during social behaviour. Manipulation of mGluR5 activity attenuates excessive grooming and instrumental learning differentially, and rescues impaired striatal synaptic plasticity in Δe4–22−/− mice. These findings show that deficiency of Shank3 can impair mGluR5-Homer scaffolding, resulting in cortico-striatal circuit abnormalities that underlie deficits in learning and ASD-like behaviours. These data suggest causal links between genetic, molecular, and circuit mechanisms underlying the pathophysiology of ASDs. PMID:27161151

  4. A new class of methods for functional connectivity estimation

    NASA Astrophysics Data System (ADS)

    Lin, Wutu

    Measuring functional connectivity from neural recordings is important in understanding processing in cortical networks. The covariance-based methods are the current golden standard for functional connectivity estimation. However, the link between the pair-wise correlations and the physiological connections inside the neural network is unclear. Therefore, the power of inferring physiological basis from functional connectivity estimation is limited. To build a stronger tie and better understand the relationship between functional connectivity and physiological neural network, we need (1) a realistic model to simulate different types of neural recordings with known ground truth for benchmarking; (2) a new functional connectivity method that produce estimations closely reflecting the physiological basis. In this thesis, (1) I tune a spiking neural network model to match with human sleep EEG data, (2) introduce a new class of methods for estimating connectivity from different kinds of neural signals and provide theory proof for its superiority, (3) apply it to simulated fMRI data as an application.

  5. Alterations in Brain Structure and Functional Connectivity in Alcohol Dependent Patients and Possible Association with Impulsivity.

    PubMed

    Wang, Junkai; Fan, Yunli; Dong, Yue; Ma, Mengying; Ma, Yi; Dong, Yuru; Niu, Yajuan; Jiang, Yin; Wang, Hong; Wang, Zhiyan; Wu, Liuzhen; Sun, Hongqiang; Cui, Cailian

    2016-01-01

    Previous studies have documented that heightened impulsivity likely contributes to the development and maintenance of alcohol use disorders. However, there is still a lack of studies that comprehensively detected the brain changes associated with abnormal impulsivity in alcohol addicts. This study was designed to investigate the alterations in brain structure and functional connectivity associated with abnormal impulsivity in alcohol dependent patients. Brain structural and functional magnetic resonance imaging data as well as impulsive behavior data were collected from 20 alcohol dependent patients and 20 age- and sex-matched healthy controls respectively. Voxel-based morphometry was used to investigate the differences of grey matter volume, and tract-based spatial statistics was used to detect abnormal white matter regions between alcohol dependent patients and healthy controls. The alterations in resting-state functional connectivity in alcohol dependent patients were examined using selected brain areas with gray matter deficits as seed regions. Compared with healthy controls, alcohol dependent patients had significantly reduced gray matter volume in the mesocorticolimbic system including the dorsal posterior cingulate cortex, the dorsal anterior cingulate cortex, the medial prefrontal cortex, the orbitofrontal cortex and the putamen, decreased fractional anisotropy in the regions connecting the damaged grey matter areas driven by higher radial diffusivity value in the same areas and decreased resting-state functional connectivity within the reward network. Moreover, the gray matter volume of the left medial prefrontal cortex exhibited negative correlations with various impulse indices. These findings suggest that chronic alcohol dependence could cause a complex neural changes linked to abnormal impulsivity.

  6. Neural correlates and network connectivity underlying narrative production and comprehension: a combined fMRI and PET study.

    PubMed

    AbdulSabur, Nuria Y; Xu, Yisheng; Liu, Siyuan; Chow, Ho Ming; Baxter, Miranda; Carson, Jessica; Braun, Allen R

    2014-08-01

    The neural correlates of narrative production and comprehension remain poorly understood. Here, using positron emission tomography (PET), functional magnetic resonance imaging (fMRI), contrast and functional network connectivity analyses we comprehensively characterize the neural mechanisms underlying these complex behaviors. Eighteen healthy subjects told and listened to fictional stories during scanning. In addition to traditional language areas (e.g., left inferior frontal and posterior middle temporal gyri), both narrative production and comprehension engaged regions associated with mentalizing and situation model construction (e.g., dorsomedial prefrontal cortex, precuneus and inferior parietal lobules) as well as neocortical premotor areas, such as the pre-supplementary motor area and left dorsal premotor cortex. Narrative comprehension alone showed marked bilaterality, activating right hemisphere homologs of perisylvian language areas. Narrative production remained predominantly left lateralized, uniquely activating executive and motor-related regions essential to language formulation and articulation. Connectivity analyses revealed strong associations between language areas and the superior and middle temporal gyri during both tasks. However, only during storytelling were these same language-related regions connected to cortical and subcortical motor regions. In contrast, during story comprehension alone, they were strongly linked to regions supporting mentalizing. Thus, when employed in a more complex, ecologically-valid context, language production and comprehension show both overlapping and idiosyncratic patterns of activation and functional connectivity. Importantly, in each case the language system is integrated with regions that support other cognitive and sensorimotor domains. Copyright © 2014. Published by Elsevier Ltd.

  7. Abnormal connection of the inferior vena cava to the left atrium with double outlet right ventricle and heterotaxia: a case report.

    PubMed

    Günal, N; Bilgiç, A; Lenk, M K; Yurdakul, Y; Sarigül, A; Ispir, S

    1996-03-01

    A 4-year-old boy with abnormal connection of the inferior vena cava to the left atrium and double outlet right ventricle and right atrial isomerism is presented. The anomalies were detected by echocardiography and angiography, and later verified through surgical intervention.

  8. Abnormal brain white matter network in young smokers: a graph theory analysis study.

    PubMed

    Zhang, Yajuan; Li, Min; Wang, Ruonan; Bi, Yanzhi; Li, Yangding; Yi, Zhang; Liu, Jixin; Yu, Dahua; Yuan, Kai

    2018-04-01

    Previous diffusion tensor imaging (DTI) studies had investigated the white matter (WM) integrity abnormalities in some specific fiber bundles in smokers. However, little is known about the changes in topological organization of WM structural network in young smokers. In current study, we acquired DTI datasets from 58 male young smokers and 51 matched nonsmokers and constructed the WM networks by the deterministic fiber tracking approach. Graph theoretical analysis was used to compare the topological parameters of WM network (global and nodal) and the inter-regional fractional anisotropy (FA) weighted WM connections between groups. The results demonstrated that both young smokers and nonsmokers had small-world topology in WM network. Further analysis revealed that the young smokers exhibited the abnormal topological organization, i.e., increased network strength, global efficiency, and decreased shortest path length. In addition, the increased nodal efficiency predominately was located in frontal cortex, striatum and anterior cingulate gyrus (ACG) in smokers. Moreover, based on network-based statistic (NBS) approach, the significant increased FA-weighted WM connections were mainly found in the PFC, ACG and supplementary motor area (SMA) regions. Meanwhile, the network parameters were correlated with the nicotine dependence severity (FTND) scores, and the nodal efficiency of orbitofrontal cortex was positive correlation with the cigarette per day (CPD) in young smokers. We revealed the abnormal topological organization of WM network in young smokers, which may improve our understanding of the neural mechanism of young smokers form WM topological organization level.

  9. Disrupted Cerebro-cerebellar Intrinsic Functional Connectivity in Young Adults with High-functioning Autism Spectrum Disorder: A Data-driven, Whole-brain, High Temporal Resolution fMRI Study.

    PubMed

    Arnold Anteraper, Sheeba; Guell, Xavier; D'Mello, Anila; Joshi, Neha; Whitfield-Gabrieli, Susan; Joshi, Gagan

    2018-06-13

    To examine the resting-state functional-connectivity (RsFc) in young adults with high-functioning autism spectrum disorder (HF-ASD) using state-of-the-art fMRI data acquisition and analysis techniques. Simultaneous multi-slice, high temporal resolution fMRI acquisition; unbiased whole-brain connectome-wide multivariate pattern analysis (MVPA) techniques for assessing RsFc; and post-hoc whole-brain seed-to-voxel analyses using MVPA results as seeds. MVPA revealed two clusters of abnormal connectivity in the cerebellum. Whole-brain seed-based functional connectivity analyses informed by MVPA-derived clusters showed significant under connectivity between the cerebellum and social, emotional, and language brain regions in the HF-ASD group compared to healthy controls. The results we report are coherent with existing structural, functional, and RsFc literature in autism, extend previous literature reporting cerebellar abnormalities in the neuropathology of autism, and highlight the cerebellum as a potential target for therapeutic, diagnostic, predictive, and prognostic developments in ASD. The description of functional connectivity abnormalities using whole-brain, data-driven analyses as reported in the present study may crucially advance the development of ASD biomarkers, targets for therapeutic interventions, and neural predictors for measuring treatment response.

  10. Conservatism and the neural circuitry of threat: economic conservatism predicts greater amygdala-BNST connectivity during periods of threat vs safety.

    PubMed

    Pedersen, Walker S; Muftuler, L Tugan; Larson, Christine L

    2018-01-01

    Political conservatism is associated with an increased negativity bias, including increased attention and reactivity toward negative and threatening stimuli. Although the human amygdala has been implicated in the response to threatening stimuli, no studies to date have investigated whether conservatism is associated with altered amygdala function toward threat. Furthermore, although an influential theory posits that connectivity between the amygdala and bed nucleus of the stria terminalis (BNST) is important in initiating the response to sustained or uncertain threat, whether individual differences in conservatism modulate this connectivity is unknown. To test whether conservatism is associated with increased reactivity in neural threat circuitry, we measured participants' self-reported social and economic conservatism and asked them to complete high-resolution fMRI scans while under threat of an unpredictable shock and while safe. We found that economic conservatism predicted greater connectivity between the BNST and a cluster of voxels in the left amygdala during threat vs safety. These results suggest that increased amygdala-BNST connectivity during threat may be a key neural correlate of the enhanced negativity bias found in conservatism. © The Author (2017). Published by Oxford University Press.

  11. Intrinsic gray-matter connectivity of the brain in adults with autism spectrum disorder

    PubMed Central

    Ecker, Christine; Ronan, Lisa; Feng, Yue; Daly, Eileen; Murphy, Clodagh; Ginestet, Cedric E.; Brammer, Michael; Fletcher, Paul C.; Bullmore, Edward T.; Suckling, John; Baron-Cohen, Simon; Williams, Steve; Loth, Eva; Murphy, Declan G. M.; Bailey, A. J.; Baron-Cohen, S.; Bolton, P. F.; Bullmore, E. T.; Carrington, S.; Chakrabarti, B.; Daly, E. M.; Deoni, S. C.; Ecker, C.; Happe, F.; Henty, J.; Jezzard, P.; Johnston, P.; Jones, D. K.; Lai, M. C.; Lombardo, M. V.; Madden, A.; Mullins, D.; Murphy, C. M.; Murphy, D. G.; Pasco, G.; Sadek, S.; Spain, D.; Steward, R.; Suckling, J.; Wheelwright, S.; Williams, S. C.

    2013-01-01

    Autism spectrum disorders (ASD) are a group of neurodevelopmental conditions that are accompanied by atypical brain connectivity. So far, in vivo evidence for atypical structural brain connectivity in ASD has mainly been based on neuroimaging studies of cortical white matter. However, genetic studies suggest that abnormal connectivity in ASD may also affect neural connections within the cortical gray matter. Such intrinsic gray-matter connections are inherently more difficult to describe in vivo but may be inferred from a variety of surface-based geometric features that can be measured using magnetic resonance imaging. Here, we present a neuroimaging study that examines the intrinsic cortico-cortical connectivity of the brain in ASD using measures of “cortical separation distances” to assess the global and local intrinsic “wiring costs” of the cortex (i.e., estimated length of horizontal connections required to wire the cortex within the cortical sheet). In a sample of 68 adults with ASD and matched controls, we observed significantly reduced intrinsic wiring costs of cortex in ASD, both globally and locally. Differences in global and local wiring cost were predominantly observed in fronto-temporal regions and also significantly predicted the severity of social and repetitive symptoms (respectively). Our study confirms that atypical cortico-cortical “connectivity” in ASD is not restricted to the development of white-matter connections but may also affect the intrinsic gray-matter architecture (and connectivity) within the cortical sheet. Thus, the atypical connectivity of the brain in ASD is complex, affecting both gray and white matter, and forms part of the core neural substrates underlying autistic symptoms. PMID:23878213

  12. An optimally evolved connective ratio of neural networks that maximizes the occurrence of synchronized bursting behavior

    PubMed Central

    2012-01-01

    Background Synchronized bursting activity (SBA) is a remarkable dynamical behavior in both ex vivo and in vivo neural networks. Investigations of the underlying structural characteristics associated with SBA are crucial to understanding the system-level regulatory mechanism of neural network behaviors. Results In this study, artificial pulsed neural networks were established using spike response models to capture fundamental dynamics of large scale ex vivo cortical networks. Network simulations with synaptic parameter perturbations showed the following two findings. (i) In a network with an excitatory ratio (ER) of 80-90%, its connective ratio (CR) was within a range of 10-30% when the occurrence of SBA reached the highest expectation. This result was consistent with the experimental observation in ex vivo neuronal networks, which were reported to possess a matured inhibitory synaptic ratio of 10-20% and a CR of 10-30%. (ii) No SBA occurred when a network does not contain any all-positive-interaction feedback loop (APFL) motif. In a neural network containing APFLs, the number of APFLs presented an optimal range corresponding to the maximal occurrence of SBA, which was very similar to the optimal CR. Conclusions In a neural network, the evolutionarily selected CR (10-30%) optimizes the occurrence of SBA, and APFL serves a pivotal network motif required to maximize the occurrence of SBA. PMID:22462685

  13. Early Environmental Enrichment Enhances Abnormal Brain Connectivity in a Rabbit Model of Intrauterine Growth Restriction.

    PubMed

    Illa, Miriam; Brito, Verónica; Pla, Laura; Eixarch, Elisenda; Arbat-Plana, Ariadna; Batallé, Dafnis; Muñoz-Moreno, Emma; Crispi, Fatima; Udina, Esther; Figueras, Francesc; Ginés, Silvia; Gratacós, Eduard

    2017-10-12

    The structural correspondence of neurodevelopmental impairments related to intrauterine growth restriction (IUGR) that persists later in life remains elusive. Moreover, early postnatal stimulation strategies have been proposed to mitigate these effects. Long-term brain connectivity abnormalities in an IUGR rabbit model and the effects of early postnatal environmental enrichment (EE) were explored. IUGR was surgically induced in one horn, whereas the contralateral one produced the controls. Postnatally, a subgroup of IUGR animals was housed in an enriched environment. Functional assessment was performed at the neonatal and long-term periods. At the long-term period, structural brain connectivity was evaluated by means of diffusion-weighted brain magnetic resonance imaging and by histological assessment focused on the hippocampus. IUGR animals displayed poorer functional results and presented altered whole-brain networks and decreased median fractional anisotropy in the hippocampus. Reduced density of dendritic spines and perineuronal nets from hippocampal neurons were also observed. Of note, IUGR animals exposed to enriched environment presented an improvement in terms of both function and structure. IUGR is associated with altered brain connectivity at the global and cellular level. A strategy based on early EE has the potential to restore the neurodevelopmental consequences of IUGR. © 2017 S. Karger AG, Basel.

  14. Insular subdivisions functional connectivity dysfunction within major depressive disorder.

    PubMed

    Peng, Xiaolong; Lin, Pan; Wu, Xiaoping; Gong, Ruxue; Yang, Rui; Wang, Jue

    2018-02-01

    Major depressive disorder (MDD) is a mental disorder characterized by cognitive and affective deficits. Previous studies suggested that insula is a crucial node of the salience network for initiating network switching, and dysfunctional connection to this region may be related to the mechanism of MDD. In this study, we systematically investigated and quantified the altered functional connectivity (FC) of the specific insular subdivisions and its relationship to psychopathology of MDD. Resting-state FC of insular subdivisions, including bilateral ventral/dorsal anterior insula and posterior insula, were estimated in 19 MDD patients and 19 healthy controls. Abnormal FC was quantified between groups. Additionally, we investigated the relationships between insular connectivity and depressive symptom severity. MDD patients demonstrated aberrant FC for insular subdivisions to superior temporal sulcus, inferior prefrontal gyrus, amygdala and posterior parietal cortex. Moreover, depression symptoms (Hamilton Depression Rating Scale and Hamilton Anxiety Rating Scale scorers) were associated with the FC values of insular subdivisions. First, the sample size of our current study is relatively small, which may affect the statistic power. Second, using standardized insular subdivision seeds for FC analyses may neglect subtle natural differences in size and location of functional area across individuals and may thus affect connectivity maps. Abnormal FC of insular subdivisions to default network and central executive network may represent impaired intrinsic networks switching which may affect the underlying emotional and sensory disturbances in MDD. And our findings can help to understand the pathophysiology and underlying neural mechanisms of MDD. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. Progressive Changes in a Distributed Neural Circuit Underlie Breathing Abnormalities in Mice Lacking MeCP2.

    PubMed

    Huang, Teng-Wei; Kochukov, Mikhail Y; Ward, Christopher S; Merritt, Jonathan; Thomas, Kaitlin; Nguyen, Tiffani; Arenkiel, Benjamin R; Neul, Jeffrey L

    2016-05-18

    CP2, the protein encoded by the gene mutated in Rett syndrome, within the hindbrain are critical for control of normal breathing. Here we show that MeCP2 function plays distinct roles in specific brainstem regions in the genesis of various aspects of abnormal breathing. This provides insight into the pathogenesis of these breathing abnormalities in Rett syndrome, which could be used to target treatments to improve these symptoms. Furthermore, it provides further knowledge about the fundamental neural circuits that control breathing. Copyright © 2016 the authors 0270-6474/16/365572-15$15.00/0.

  16. Modular, Hierarchical Learning By Artificial Neural Networks

    NASA Technical Reports Server (NTRS)

    Baldi, Pierre F.; Toomarian, Nikzad

    1996-01-01

    Modular and hierarchical approach to supervised learning by artificial neural networks leads to neural networks more structured than neural networks in which all neurons fully interconnected. These networks utilize general feedforward flow of information and sparse recurrent connections to achieve dynamical effects. The modular organization, sparsity of modular units and connections, and fact that learning is much more circumscribed are all attractive features for designing neural-network hardware. Learning streamlined by imitating some aspects of biological neural networks.

  17. Eye Movement Abnormalities in Joubert Syndrome

    PubMed Central

    Weiss, Avery H.; Doherty, Dan; Parisi, Melissa; Shaw, Dennis; Glass, Ian; Phillips, James O.

    2011-01-01

    Purpose Joubert syndrome is a genetic disorder characterized by hypoplasia of the midline cerebellum and deficiency of crossed connections between neural structures in the brain stem that control eye movements. The goal of the study was to quantify the eye movement abnormalities that occur in Joubert syndrome. Methods Eye movements were recorded in response to stationary stimuli and stimuli designed to elicit smooth pursuit, saccades, optokinetic nystagmus (OKN), vestibulo-ocular reflex (VOR), and vergence using video-oculography or Skalar search coils in 8 patients with Joubert syndrome. All patients underwent high-resolution magnetic resonance imaging (MRI). Results All patients had the highly characteristic molar tooth sign on brain MRI. Six patients had conjugate pendular (n = 4) or see-saw nystagmus (n = 2); gaze holding was stable in four patients. Smooth-pursuit gains were 0.28 to 1.19, 0.11 to 0.68, and 0.33 to 0.73 at peak stimulus velocities of 10, 20, and 30 deg/s in six patients; smooth pursuit could not be elicited in four patients. Saccade gains in five patients ranged from 0.35 to 0.91 and velocities ranged from 60.9 to 259.5 deg/s. Targeted saccades could not be elicited in five patients. Horizontal OKN gain was uniformly reduced across gratings drifted at velocities of 15, 30, and 45 deg/s. VOR gain was 0.8 or higher and phase appropriate in three of seven subjects; VOR gain was 0.3 or less and phase was indeterminate in four subjects. Conclusions The abnormalities in gaze-holding and eye movements are consistent with the distributed abnormalities of midline cerebellum and brain stem regions associated with Joubert syndrome. PMID:19443711

  18. Abnormalities of hybrid grouper (Epinephelus fuscoguttatus x Epinephelus lanceolatus) in Situbondo

    NASA Astrophysics Data System (ADS)

    Triastuti, J.; Pursetyo, K. T.; Monica, A.; Lutfiyah, L.; Budi, D. S.

    2018-04-01

    Grouper is one of consumption fish which is demanded excessively by local consumers and foreign consumers. Hybridization of grouper has been performed considerably that produce the good genetic quality of hybrid variants. One of grouper fish which has good genetic in its growth is kertang grouper fish. Nowadays many hatcheries performing hybridization between kertang grouper fish and tiger grouper fish, however observation of the hybrid abnormality has not been performed yet. Abnormality is able to increase since genetic causes, so that observation of abnormality occurrence in cantang hybrid grouper fish in Situbondo, JawaTimur, Indonesia in May – July in 3 times grading of juvenile stadia was performed. Results showed abnormalities were observed on mouth and operculum, branched of neural arch, fusion of neural arch, fusion of posterior truncus vertebrae, fusion of caudal vertebrae, fusion of anterior truncus vertebrae.

  19. Association of neural tube defects in children of mothers with MTHFR 677TT genotype and abnormal carbohydrate metabolism risk: a case-control study.

    PubMed

    Cadenas-Benitez, N M; Yanes-Sosa, F; Gonzalez-Meneses, A; Cerrillos, L; Acosta, D; Praena-Fernandez, J M; Neth, O; Gomez de Terreros, I; Ybot-González, P

    2014-03-26

    Abnormalities in maternal folate and carbohydrate metabolism have both been shown to induce neural tube defects (NTD) in humans and animal models. However, the relationship between these two factors in the development of NTDs remains unclear. Data from mothers of children with spina bifida seen at the Unidad de Espina Bífida del Hospital Infantil Virgen del Rocío (case group) were compared to mothers of healthy children with no NTD (control group) who were randomly selected from patients seen at the outpatient ward in the same hospital. There were 25 individuals in the case group and 41 in the control group. Analysis of genotypes for the methylenetetrahydrofolate reductase (MTHFR) 677CT polymorphism in women with or without risk factors for abnormal carbohydrate metabolism revealed that mothers who were homozygous for the MTHFR 677TT polymorphism and at risk of abnormal carbohydrate metabolism were more likely to have offspring with spina bifida and high levels of homocysteine, compared to the control group. The increased incidence of NTDs in mothers homozygous for the MTHFR 677TT polymorphism and at risk of abnormal carbohydrate metabolism stresses the need for careful metabolic screening in pregnant women, and, if necessary, determination of the MTHFR 677CT genotype in those mothers at risk of developing abnormal carbohydrate metabolism.

  20. Frequency-specific alterations in functional connectivity in treatment-resistant and -sensitive major depressive disorder.

    PubMed

    He, Zongling; Cui, Qian; Zheng, Junjie; Duan, Xujun; Pang, Yajing; Gao, Qing; Han, Shaoqiang; Long, Zhiliang; Wang, Yifeng; Li, Jiao; Wang, Xiao; Zhao, Jingping; Chen, Huafu

    2016-11-01

    Major depressive disorder (MDD) may involve alterations in brain functional connectivity in multiple neural circuits and present large-scale network dysfunction. Patients with treatment-resistant depression (TRD) and treatment-sensitive depression (TSD) show different responses to antidepressants and aberrant brain functions. This study aims to investigate functional connectivity patterns of TRD and TSD at the whole brain resting state. Seventeen patients with TRD, 17 patients with TSD, and 17 healthy controls matched with age, gender, and years of education were recruited in this study. The brain was divided using an automated anatomical labeling atlas into 90 regions of interest, which were used to construct the entire brain functional networks. An analysis method called network-based statistic was used to explore the dysconnected subnetworks of TRD and TSD at different frequency bands. At resting state, TSD and TRD present characteristic patterns of network dysfunction at special frequency bands. The dysconnected subnetwork of TSD mainly lies in the fronto-parietal top-down control network. Moreover, the abnormal neural circuits of TRD are extensive and complex. These circuits not only depend on the abnormal affective network but also involve other networks, including salience network, auditory network, visual network, and language processing cortex. Our findings reflect that the pathological mechanism of TSD may refer to impairment in cognitive control, whereas TRD mainly triggers the dysfunction of emotion processing and affective cognition. This study reveals that differences in brain functional connectivity at resting state reflect distinct pathophysiological mechanisms in TSD and TRD. These findings may be helpful in differentiating two types of MDD and predicting treatment responses. Copyright © 2016 Elsevier Ltd. All rights reserved.

  1. Abnormal functional global and local brain connectivity in female patients with anorexia nervosa

    PubMed Central

    Geisler, Daniel; Borchardt, Viola; Lord, Anton R.; Boehm, Ilka; Ritschel, Franziska; Zwipp, Johannes; Clas, Sabine; King, Joseph A.; Wolff-Stephan, Silvia; Roessner, Veit; Walter, Martin; Ehrlich, Stefan

    2016-01-01

    Background Previous resting-state functional connectivity studies in patients with anorexia nervosa used independent component analysis or seed-based connectivity analysis to probe specific brain networks. Instead, modelling the entire brain as a complex network allows determination of graph-theoretical metrics, which describe global and local properties of how brain networks are organized and how they interact. Methods To determine differences in network properties between female patients with acute anorexia nervosa and pairwise matched healthy controls, we used resting-state fMRI and computed well-established global and local graph metrics across a range of network densities. Results Our analyses included 35 patients and 35 controls. We found that the global functional network structure in patients with anorexia nervosa is characterized by increases in both characteristic path length (longer average routes between nodes) and assortativity (more nodes with a similar connectedness link together). Accordingly, we found locally decreased connectivity strength and increased path length in the posterior insula and thalamus. Limitations The present results may be limited to the methods applied during preprocessing and network construction. Conclusion We demonstrated anorexia nervosa–related changes in the network configuration for, to our knowledge, the first time using resting-state fMRI and graph-theoretical measures. Our findings revealed an altered global brain network architecture accompanied by local degradations indicating wide-scale disturbance in information flow across brain networks in patients with acute anorexia nervosa. Reduced local network efficiency in the thalamus and posterior insula may reflect a mechanism that helps explain the impaired integration of visuospatial and homeostatic signals in patients with this disorder, which is thought to be linked to abnormal representations of body size and hunger. PMID:26252451

  2. Abnormal functional global and local brain connectivity in female patients with anorexia nervosa.

    PubMed

    Geisler, Daniel; Borchardt, Viola; Lord, Anton R; Boehm, Ilka; Ritschel, Franziska; Zwipp, Johannes; Clas, Sabine; King, Joseph A; Wolff-Stephan, Silvia; Roessner, Veit; Walter, Martin; Ehrlich, Stefan

    2016-01-01

    Previous resting-state functional connectivity studies in patients with anorexia nervosa used independent component analysis or seed-based connectivity analysis to probe specific brain networks. Instead, modelling the entire brain as a complex network allows determination of graph-theoretical metrics, which describe global and local properties of how brain networks are organized and how they interact. To determine differences in network properties between female patients with acute anorexia nervosa and pairwise matched healthy controls, we used resting-state fMRI and computed well-established global and local graph metrics across a range of network densities. Our analyses included 35 patients and 35 controls. We found that the global functional network structure in patients with anorexia nervosa is characterized by increases in both characteristic path length (longer average routes between nodes) and assortativity (more nodes with a similar connectedness link together). Accordingly, we found locally decreased connectivity strength and increased path length in the posterior insula and thalamus. The present results may be limited to the methods applied during preprocessing and network construction. We demonstrated anorexia nervosa-related changes in the network configuration for, to our knowledge, the first time using resting-state fMRI and graph-theoretical measures. Our findings revealed an altered global brain network architecture accompanied by local degradations indicating wide-scale disturbance in information flow across brain networks in patients with acute anorexia nervosa. Reduced local network efficiency in the thalamus and posterior insula may reflect a mechanism that helps explain the impaired integration of visuospatial and homeostatic signals in patients with this disorder, which is thought to be linked to abnormal representations of body size and hunger.

  3. Cortical connectivity and memory performance in cognitive decline: A study via graph theory from EEG data.

    PubMed

    Vecchio, F; Miraglia, F; Quaranta, D; Granata, G; Romanello, R; Marra, C; Bramanti, P; Rossini, P M

    2016-03-01

    Functional brain abnormalities including memory loss are found to be associated with pathological changes in connectivity and network neural structures. Alzheimer's disease (AD) interferes with memory formation from the molecular level, to synaptic functions and neural networks organization. Here, we determined whether brain connectivity of resting-state networks correlate with memory in patients affected by AD and in subjects with mild cognitive impairment (MCI). One hundred and forty-four subjects were recruited: 70 AD (MMSE Mini Mental State Evaluation 21.4), 50 MCI (MMSE 25.2) and 24 healthy subjects (MMSE 29.8). Undirected and weighted cortical brain network was built to evaluate graph core measures to obtain Small World parameters. eLORETA lagged linear connectivity as extracted by electroencephalogram (EEG) signals was used to weight the network. A high statistical correlation between Small World and memory performance was found. Namely, higher Small World characteristic in EEG gamma frequency band during the resting state, better performance in short-term memory as evaluated by the digit span tests. Such Small World pattern might represent a biomarker of working memory impairment in older people both in physiological and pathological conditions. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.

  4. Dynamic Changes in Amygdala Psychophysiological Connectivity Reveal Distinct Neural Networks for Facial Expressions of Basic Emotions.

    PubMed

    Diano, Matteo; Tamietto, Marco; Celeghin, Alessia; Weiskrantz, Lawrence; Tatu, Mona-Karina; Bagnis, Arianna; Duca, Sergio; Geminiani, Giuliano; Cauda, Franco; Costa, Tommaso

    2017-03-27

    The quest to characterize the neural signature distinctive of different basic emotions has recently come under renewed scrutiny. Here we investigated whether facial expressions of different basic emotions modulate the functional connectivity of the amygdala with the rest of the brain. To this end, we presented seventeen healthy participants (8 females) with facial expressions of anger, disgust, fear, happiness, sadness and emotional neutrality and analyzed amygdala's psychophysiological interaction (PPI). In fact, PPI can reveal how inter-regional amygdala communications change dynamically depending on perception of various emotional expressions to recruit different brain networks, compared to the functional interactions it entertains during perception of neutral expressions. We found that for each emotion the amygdala recruited a distinctive and spatially distributed set of structures to interact with. These changes in amygdala connectional patters characterize the dynamic signature prototypical of individual emotion processing, and seemingly represent a neural mechanism that serves to implement the distinctive influence that each emotion exerts on perceptual, cognitive, and motor responses. Besides these differences, all emotions enhanced amygdala functional integration with premotor cortices compared to neutral faces. The present findings thus concur to reconceptualise the structure-function relation between brain-emotion from the traditional one-to-one mapping toward a network-based and dynamic perspective.

  5. Nonequilibrium landscape theory of neural networks

    PubMed Central

    Yan, Han; Zhao, Lei; Hu, Liang; Wang, Xidi; Wang, Erkang; Wang, Jin

    2013-01-01

    The brain map project aims to map out the neuron connections of the human brain. Even with all of the wirings mapped out, the global and physical understandings of the function and behavior are still challenging. Hopfield quantified the learning and memory process of symmetrically connected neural networks globally through equilibrium energy. The energy basins of attractions represent memories, and the memory retrieval dynamics is determined by the energy gradient. However, the realistic neural networks are asymmetrically connected, and oscillations cannot emerge from symmetric neural networks. Here, we developed a nonequilibrium landscape–flux theory for realistic asymmetrically connected neural networks. We uncovered the underlying potential landscape and the associated Lyapunov function for quantifying the global stability and function. We found the dynamics and oscillations in human brains responsible for cognitive processes and physiological rhythm regulations are determined not only by the landscape gradient but also by the flux. We found that the flux is closely related to the degrees of the asymmetric connections in neural networks and is the origin of the neural oscillations. The neural oscillation landscape shows a closed-ring attractor topology. The landscape gradient attracts the network down to the ring. The flux is responsible for coherent oscillations on the ring. We suggest the flux may provide the driving force for associations among memories. We applied our theory to rapid-eye movement sleep cycle. We identified the key regulation factors for function through global sensitivity analysis of landscape topography against wirings, which are in good agreements with experiments. PMID:24145451

  6. Nonequilibrium landscape theory of neural networks.

    PubMed

    Yan, Han; Zhao, Lei; Hu, Liang; Wang, Xidi; Wang, Erkang; Wang, Jin

    2013-11-05

    The brain map project aims to map out the neuron connections of the human brain. Even with all of the wirings mapped out, the global and physical understandings of the function and behavior are still challenging. Hopfield quantified the learning and memory process of symmetrically connected neural networks globally through equilibrium energy. The energy basins of attractions represent memories, and the memory retrieval dynamics is determined by the energy gradient. However, the realistic neural networks are asymmetrically connected, and oscillations cannot emerge from symmetric neural networks. Here, we developed a nonequilibrium landscape-flux theory for realistic asymmetrically connected neural networks. We uncovered the underlying potential landscape and the associated Lyapunov function for quantifying the global stability and function. We found the dynamics and oscillations in human brains responsible for cognitive processes and physiological rhythm regulations are determined not only by the landscape gradient but also by the flux. We found that the flux is closely related to the degrees of the asymmetric connections in neural networks and is the origin of the neural oscillations. The neural oscillation landscape shows a closed-ring attractor topology. The landscape gradient attracts the network down to the ring. The flux is responsible for coherent oscillations on the ring. We suggest the flux may provide the driving force for associations among memories. We applied our theory to rapid-eye movement sleep cycle. We identified the key regulation factors for function through global sensitivity analysis of landscape topography against wirings, which are in good agreements with experiments.

  7. Amygdala activity and prefrontal cortex-amygdala effective connectivity to emerging emotional faces distinguish remitted and depressed mood states in bipolar disorder.

    PubMed

    Perlman, Susan B; Almeida, Jorge R C; Kronhaus, Dina M; Versace, Amelia; Labarbara, Edmund J; Klein, Crystal R; Phillips, Mary L

    2012-03-01

    Few studies have employed effective connectivity (EC) to examine the functional integrity of neural circuitry supporting abnormal emotion processing in bipolar disorder (BD), a key feature of the illness. We used Granger Causality Mapping (GCM) to map EC between the prefrontal cortex (PFC) and bilateral amygdala and a novel paradigm to assess emotion processing in adults with BD. Thirty-one remitted adults with BD [(remitted BD), mean age = 32 years], 21 adults with BD in a depressed episode [(depressed BD), mean age = 33 years], and 25 healthy control participants [(HC), mean age = 31 years] performed a block-design emotion processing task requiring color-labeling of a color flash superimposed on a task-irrelevant face morphing from neutral to emotional (happy, sad, angry, or fearful). GCM measured EC preceding (top-down) and following (bottom-up) activity between the PFC and the left and right amygdalae. Our findings indicated patterns of abnormally elevated bilateral amygdala activity in response to emerging fearful, sad, and angry facial expressions in remitted-BD subjects versus HC, and abnormally elevated right amygdala activity to emerging fearful faces in depressed-BD subjects versus HC. We also showed distinguishable patterns of abnormal EC between the amygdala and dorsomedial and ventrolateral PFC, especially to emerging happy and sad facial expressions in remitted-BD and depressed-BD subjects. EC measures of neural system level functioning can further understanding of neural mechanisms associated with abnormal emotion processing and regulation in BD. Our findings suggest major differences in recruitment of amygdala-PFC circuitry, supporting implicit emotion processing between remitted-BD and depressed-BD subjects, which may underlie changes from remission to depression in BD. © 2012 John Wiley and Sons A/S.

  8. Left hemisphere structural connectivity abnormality in pediatric hydrocephalus patients following surgery.

    PubMed

    Yuan, Weihong; Meller, Artur; Shimony, Joshua S; Nash, Tiffany; Jones, Blaise V; Holland, Scott K; Altaye, Mekibib; Barnard, Holly; Phillips, Jannel; Powell, Stephanie; McKinstry, Robert C; Limbrick, David D; Rajagopal, Akila; Mangano, Francesco T

    2016-01-01

    -II)]. However, one global network measure (global efficiency) and two regional network measures in the insula (local efficiency and between centrality) tested at 3-month post-surgery were found to correlate with GAC score tested at 12-month post-surgery with statistical significance (all p  < 0.05, corrected). Our data showed that the structural connectivity analysis based on DTI and graph theory was sensitive in detecting both global and regional network abnormality when the analysis was conducted in the left hemisphere only. This approach provides a new avenue enabling the application of advanced neuroimaging analysis methods in quantifying brain damage in children with hydrocephalus surgically treated with programmable shunts.

  9. Primary prevention of neural-tube defects and some other congenital abnormalities by folic acid and multivitamins: history, missed opportunity and tasks

    PubMed Central

    Bártfai, Zoltán; Bánhidy, Ferenc

    2011-01-01

    The history of intervention trials of periconception folic acid with multivitamin and folic acid supplementation in women has shown a recent breakthrough in the primary prevention of structural birth defects, namely neural-tube defects and some other congenital abnormalities. Recently, some studies have demonstrated the efficacy of this new method in reducing congenital abnormalities with specific origin; for example, in the offspring of diabetic and epileptic mothers, and in pregnancy with high fever. The benefits and drawbacks of four possible uses of periconception folate/folic acid and multivitamin supplementation are discussed: we believe there has been a missed opportunity to implement this preventive approach in medical practice. The four methods are as follows: (i) dietary intake of folate and other vitamins, (ii) periconception folic acid/multivitamin supplementation, (iii) food fortification with folic acid, and (iv) the combination of oral contraceptives with 6S-5-methytetrahydrofolate (‘folate’). PMID:25083211

  10. Abnormal cerebral functional connectivity in esophageal cancer patients with theory of mind deficits in resting state.

    PubMed

    Cao, Yin; Xiang, JianBo; Qian, Nong; Sun, SuPing; Hu, LiJun; Yuan, YongGui

    2015-01-01

    To explore the function of the default mode network (DMN) in the psychopathological mechanisms of theory of mind deficits in patients with an esophageal cancer concomitant with depression in resting the state. Twenty-five cases of esophageal cancer with theory of mind deficits (test group) that meet the diagnostic criteria of esophageal cancer and neuropsychological tests, including Beck depression inventory, reading the mind in the eyes, and Faux pas, were included, Another 25 cases of esophageal cancer patients but without theory of mind deficits (control group) were enrolled. Each patient completed a resting-state functional magnetic resonance imaging. The functional connectivity intensities within the cerebral regions in the DMN of all the enrolled patients were analyzed. The results of each group were compared. The functional connectivity of the bilateral prefrontal central region with the precuneus, bilateral posterior cingulate gyrus and bilateral ventral anterior cingulate gyrus in the patients of the test group were all reduced significantly (P < 0.05). In the resting state, the functional connectivity is abnormal in the cerebral regions in the DMN of esophageal cancer patients with theory of mind deficits. The theory of mind deficits might have an important function in the pathogenesis of esophageal cancer.

  11. Aberrant Spontaneous and Task-Dependent Functional Connections in the Anxious Brain

    PubMed Central

    MacNamara, Annmarie; DiGangi, Julia; Phan, K. Luan

    2016-01-01

    A number of brain regions have been implicated in the anxiety disorders, yet none of these regions in isolation has been distinguished as the sole or discrete site responsible for anxiety disorder pathology. Therefore, the identification of dysfunctional neural networks as represented by alterations in the temporal correlation of blood-oxygen level dependent (BOLD) signal across several brain regions in anxiety disorders has been increasingly pursued in the past decade. Here, we review task-independent (e.g., resting state) and task-induced functional connectivity magnetic resonance imaging (fcMRI) studies in the adult anxiety disorders (including trauma- and stressor-related and obsessive compulsive disorders). The results of this review suggest that anxiety disorder pathophysiology involves aberrant connectivity between amygdala-frontal and frontal-striatal regions, as well as within and between canonical “intrinsic” brain networks - the default mode and salience networks, and that evidence of these aberrations may help inform findings of regional activation abnormalities observed in the anxiety disorders. Nonetheless, significant challenges remain, including the need to better understand mixed findings observed using different methods (e.g., resting state and task-based approaches); the need for more developmental work; the need to delineate disorder-specific and transdiagnostic fcMRI aberrations in the anxiety disorders; and the need to better understand the clinical significance of fcMRI abnormalities. In meeting these challenges, future work has the potential to elucidate aberrant neural networks as intermediate, brain-based phenotypes to predict disease onset and progression, refine diagnostic nosology, and ascertain treatment mechanisms and predictors of treatment response across anxiety, trauma-related and obsessive compulsive disorders. PMID:27141532

  12. Mutual connectivity analysis (MCA) using generalized radial basis function neural networks for nonlinear functional connectivity network recovery in resting-state functional MRI

    NASA Astrophysics Data System (ADS)

    D'Souza, Adora M.; Abidin, Anas Zainul; Nagarajan, Mahesh B.; Wismüller, Axel

    2016-03-01

    We investigate the applicability of a computational framework, called mutual connectivity analysis (MCA), for directed functional connectivity analysis in both synthetic and resting-state functional MRI data. This framework comprises of first evaluating non-linear cross-predictability between every pair of time series prior to recovering the underlying network structure using community detection algorithms. We obtain the non-linear cross-prediction score between time series using Generalized Radial Basis Functions (GRBF) neural networks. These cross-prediction scores characterize the underlying functionally connected networks within the resting brain, which can be extracted using non-metric clustering approaches, such as the Louvain method. We first test our approach on synthetic models with known directional influence and network structure. Our method is able to capture the directional relationships between time series (with an area under the ROC curve = 0.92 +/- 0.037) as well as the underlying network structure (Rand index = 0.87 +/- 0.063) with high accuracy. Furthermore, we test this method for network recovery on resting-state fMRI data, where results are compared to the motor cortex network recovered from a motor stimulation sequence, resulting in a strong agreement between the two (Dice coefficient = 0.45). We conclude that our MCA approach is effective in analyzing non-linear directed functional connectivity and in revealing underlying functional network structure in complex systems.

  13. Mutual Connectivity Analysis (MCA) Using Generalized Radial Basis Function Neural Networks for Nonlinear Functional Connectivity Network Recovery in Resting-State Functional MRI.

    PubMed

    DSouza, Adora M; Abidin, Anas Zainul; Nagarajan, Mahesh B; Wismüller, Axel

    2016-03-29

    We investigate the applicability of a computational framework, called mutual connectivity analysis (MCA), for directed functional connectivity analysis in both synthetic and resting-state functional MRI data. This framework comprises of first evaluating non-linear cross-predictability between every pair of time series prior to recovering the underlying network structure using community detection algorithms. We obtain the non-linear cross-prediction score between time series using Generalized Radial Basis Functions (GRBF) neural networks. These cross-prediction scores characterize the underlying functionally connected networks within the resting brain, which can be extracted using non-metric clustering approaches, such as the Louvain method. We first test our approach on synthetic models with known directional influence and network structure. Our method is able to capture the directional relationships between time series (with an area under the ROC curve = 0.92 ± 0.037) as well as the underlying network structure (Rand index = 0.87 ± 0.063) with high accuracy. Furthermore, we test this method for network recovery on resting-state fMRI data, where results are compared to the motor cortex network recovered from a motor stimulation sequence, resulting in a strong agreement between the two (Dice coefficient = 0.45). We conclude that our MCA approach is effective in analyzing non-linear directed functional connectivity and in revealing underlying functional network structure in complex systems.

  14. Brain regions with abnormal network properties in severe epilepsy of Lennox-Gastaut phenotype: Multivariate analysis of task-free fMRI.

    PubMed

    Pedersen, Mangor; Curwood, Evan K; Archer, John S; Abbott, David F; Jackson, Graeme D

    2015-11-01

    Lennox-Gastaut syndrome, and the similar but less tightly defined Lennox-Gastaut phenotype, describe patients with severe epilepsy, generalized epileptic discharges, and variable intellectual disability. Our previous functional neuroimaging studies suggest that abnormal diffuse association network activity underlies the epileptic discharges of this clinical phenotype. Herein we use a data-driven multivariate approach to determine the spatial changes in local and global networks of patients with severe epilepsy of the Lennox-Gastaut phenotype. We studied 9 adult patients and 14 controls. In 20 min of task-free blood oxygen level-dependent functional magnetic resonance imaging data, two metrics of functional connectivity were studied: Regional homogeneity or local connectivity, a measure of concordance between each voxel to a focal cluster of adjacent voxels; and eigenvector centrality, a global connectivity estimate designed to detect important neural hubs. Multivariate pattern analysis of these data in a machine-learning framework was used to identify spatial features that classified disease subjects. Multivariate pattern analysis was 95.7% accurate in classifying subjects for both local and global connectivity measures (22/23 subjects correctly classified). Maximal discriminating features were the following: increased local connectivity in frontoinsular and intraparietal areas; increased global connectivity in posterior association areas; decreased local connectivity in sensory (visual and auditory) and medial frontal cortices; and decreased global connectivity in the cingulate cortex, striatum, hippocampus, and pons. Using a data-driven analysis method in task-free functional magnetic resonance imaging, we show increased connectivity in critical areas of association cortex and decreased connectivity in primary cortex. This supports previous findings of a critical role for these association cortical regions as a final common pathway in generating the Lennox

  15. Limitations of opto-electronic neural networks

    NASA Technical Reports Server (NTRS)

    Yu, Jeffrey; Johnston, Alan; Psaltis, Demetri; Brady, David

    1989-01-01

    Consideration is given to the limitations of implementing neurons, weights, and connections in neural networks for electronics and optics. It is shown that the advantages of each technology are utilized when electronically fabricated neurons are included and a combination of optics and electronics are employed for the weights and connections. The relationship between the types of neural networks being constructed and the choice of technologies to implement the weights and connections is examined.

  16. Increasing cyanosis early after cavopulmonary connection caused by abnormal systemic venous channels.

    PubMed

    Gatzoulis, M A; Shinebourne, E A; Redington, A N; Rigby, M L; Ho, S Y; Shore, D F

    1995-02-01

    To show that abnormal systemic venous channels in patients who undergo cavopulmonary anastomoses can become manifest and haemodynamically important only after surgery despite detailed preoperative investigation. Descriptive study of patients fulfilling the above criteria selected from hospital records over the past three years. A tertiary referral centre. Of the three cases identified, two were isomeric, one with left atrial isomerism and hemiazygos continuation of the inferior vena cava who underwent bilateral bidirectional Glenn anastomoses and one with right isomerism who underwent total cavopulmonary anastomosis. Case 3 had absent left atrioventricular connection with a hypoplastic left lung and underwent a classic right Glenn procedure. All three cases presented with progressive cyanosis in the early postoperative period. Postoperative angiography in case 1 showed a remnant of a left inferior vena cava draining to the atrium to have become grossly dilated causing cyanosis, which resolved after redirection of this vessel and of the hepatic veins into the right pulmonary artery with an intra-atrial baffle. Cyanosis in case 2 was caused by intra-hepatic shunting to a hepatic vein draining to the left of the intra-atrial baffle. The diagnosis was made at necropsy, being overlooked on postoperative angiography. Repeat angiography in case 3 showed progressive dilatation of a small left superior vena cava to coronary sinus. Test occlusion with a view to embolisation revealed hitherto an undemonstrated hemiazygos continuation of inferior caval to brachiocephalic vein. The patient underwent surgical ligation of these two venous channels. Despite appropriate investigation some "abnormal" venous pathways manifest themselves, dilate, and become haemodynamically important only after surgical cavopulmonary anastomoses. In the presence of early postoperative cyanosis "new" systemic venous collateral channels should be considered as a possible cause, which may require

  17. Targeting Neural Synchrony Deficits is Sufficient to Improve Cognition in a Schizophrenia-Related Neurodevelopmental Model

    PubMed Central

    Lee, Heekyung; Dvorak, Dino; Fenton, André A.

    2014-01-01

    Cognitive symptoms are core features of mental disorders but procognitive treatments are limited. We have proposed a “discoordination” hypothesis that cognitive impairment results from aberrant coordination of neural activity. We reported that neonatal ventral hippocampus lesion (NVHL) rats, an established neurodevelopmental model of schizophrenia, have abnormal neural synchrony and cognitive deficits in the active place avoidance task. During stillness, we observed that cortical local field potentials sometimes resembled epileptiform spike-wave discharges with higher prevalence in NVHL rats, indicating abnormal neural synchrony due perhaps to imbalanced excitation–inhibition coupling. Here, within the context of the hypothesis, we investigated whether attenuating abnormal neural synchrony will improve cognition in NVHL rats. We report that: (1) inter-hippocampal synchrony in the theta and beta bands is correlated with active place avoidance performance; (2) the anticonvulsant ethosuximide attenuated the abnormal spike-wave activity, improved cognitive control, and reduced hyperlocomotion; (3) ethosuximide not only normalized the task-associated theta and beta synchrony between the two hippocampi but also increased synchrony between the medial prefrontal cortex and hippocampus above control levels; (4) the antipsychotic olanzapine was less effective at improving cognitive control and normalizing place avoidance-related inter-hippocampal neural synchrony, although it reduced hyperactivity; and (5) olanzapine caused an abnormal pattern of frequency-independent increases in neural synchrony, in both NVHL and control rats. These data suggest that normalizing aberrant neural synchrony can be beneficial and that drugs targeting the pathophysiology of abnormally coordinated neural activities may be a promising theoretical framework and strategy for developing treatments that improve cognition in neurodevelopmental disorders such as schizophrenia. PMID:24592242

  18. Mode of effective connectivity within a putative neural network differentiates moral cognitions related to care and justice ethics.

    PubMed

    Cáceda, Ricardo; James, G Andrew; Ely, Timothy D; Snarey, John; Kilts, Clinton D

    2011-02-25

    Moral sensitivity refers to the interpretive awareness of moral conflict and can be justice or care oriented. Justice ethics is associated primarily with human rights and the application of moral rules, whereas care ethics is related to human needs and a situational approach involving social emotions. Among the core brain regions involved in moral issue processing are: medial prefrontal cortex, anterior (ACC) and posterior (PCC) cingulate cortex, posterior superior temporal sulcus (pSTS), insula and amygdala. This study sought to inform the long standing debate of whether care and justice moral ethics represent one or two different forms of cognition. Model-free and model-based connectivity analysis were used to identify functional neural networks underlying care and justice ethics for a moral sensitivity task. In addition to modest differences in patterns of associated neural activity, distinct modes of functional and effective connectivity were observed for moral sensitivity for care and justice issues that were modulated by individual variation in moral ability. These results support a neurobiological differentiation between care and justice ethics and suggest that human moral behavior reflects the outcome of integrating opposing rule-based, self-other perspectives, and emotional responses.

  19. Enhancement of oscillatory activity in the endopiriform nucleus of rats raised under abnormal oral conditions.

    PubMed

    Yoshimura, Hiroshi; Hasumoto-Honjo, Miho; Sugai, Tokio; Segami, Natsuki; Kato, Nobuo

    2014-02-21

    Endopiriform nucleus (EPN) is located deep to the piriform cortex, and has neural connections with not only neighboring sensory areas but also subcortical areas where emotional and nociceptive information is processed. Well-balanced oral condition might play an important role in stability of brain activities. When the oral condition is impaired, several areas in the brain might be affected. In the present study, we investigated whether abnormal conditions of oral region influence neural activities in the EPN. Orthodontic appliance that generates continuous force and chronic pain-related stress was fixed to maxillary incisors of rats, and raised. Field potential recordings were made from the EPN of brain slices. We previously reported that the EPN has an ability to generate membrane potential oscillation. In the present study, we have applied the same methods to assess activities of neuron clusters in the EPN. In the case of normal rats, stable field potential oscillations were induced in the EPN by application of low-frequency electrical stimulation under the medium with caffeine. In the case of rats with the orthodontic appliance, stable field potential oscillations were also induced, but both duration of oscillatory activities and wavelet number were increased. The enhanced oscillations were depressed by blockade of NMDA receptors. Thus, impairment of oral health under application of continuous orthodontic force and chronic pain-related stress enhanced neural activities in the EPN, in which up-regulation of NMDA receptors may be concerned. These findings suggest that the EPN might be involved in information processing with regard to abnormal conditions of oral region. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  20. Innervation of Extrahepatic Biliary Tract, With Special Reference to the Direct Bidirectional Neural Connections of the Gall Bladder, Sphincter of Oddi and Duodenum in Suncus murinus, in Whole-Mount Immunohistochemical Study.

    PubMed

    Yi, S-Q; Ren, K; Kinoshita, M; Takano, N; Itoh, M; Ozaki, N

    2016-06-01

    Sphincter of Oddi dysfunction is one of the most important symptoms in post-cholecystectomy syndrome. Using either electrical or mechanical stimulation and retrogradely transported neuronal dyes, it has been demonstrated that there are direct neural pathways connecting gall bladder and the sphincter of Oddi in the Australian opossum and the golden hamster. In the present study, we employed whole-mount immunohistochemistry staining to observe and verify that there are two different plexuses of the extrahepatic biliary tract in Suncus murinus. One, named Pathway One, showed a fine, irregular but dense network plexus that ran adhesively and resided on/in the extrahepatic biliary tract wall, and the plexus extended into the intrahepatic area. On the other hand, named Pathway Two, exhibiting simple, thicker and straight neural bundles, ran parallel to the surface of the extrahepatic biliary tract and passed between the gall bladder and duodenum, but did not give off any branches to the liver. Pathway Two was considered to involve direct bidirectional neural connections between the duodenum and the biliary tract system. For the first time, morphologically, we demonstrated direct neural connections between gall bladder and duodenum in S. murinus. Malfunction of the sphincter of Oddi may be caused by injury of the direct neural pathways between gall bladder and duodenum by cholecystectomy. From the viewpoint of preserving the function of the major duodenal papilla and common bile duct, we emphasize the importance of avoiding kocherization of the common bile duct so as to preserve the direct neural connections between gall bladder and sphincter of Oddi. © 2015 Blackwell Verlag GmbH.

  1. Neural-like growing networks

    NASA Astrophysics Data System (ADS)

    Yashchenko, Vitaliy A.

    2000-03-01

    On the basis of the analysis of scientific ideas reflecting the law in the structure and functioning the biological structures of a brain, and analysis and synthesis of knowledge, developed by various directions in Computer Science, also there were developed the bases of the theory of a new class neural-like growing networks, not having the analogue in world practice. In a base of neural-like growing networks the synthesis of knowledge developed by classical theories - semantic and neural of networks is. The first of them enable to form sense, as objects and connections between them in accordance with construction of the network. With thus each sense gets a separate a component of a network as top, connected to other tops. In common it quite corresponds to structure reflected in a brain, where each obvious concept is presented by certain structure and has designating symbol. Secondly, this network gets increased semantic clearness at the expense owing to formation not only connections between neural by elements, but also themselves of elements as such, i.e. here has a place not simply construction of a network by accommodation sense structures in environment neural of elements, and purely creation of most this environment, as of an equivalent of environment of memory. Thus neural-like growing networks are represented by the convenient apparatus for modeling of mechanisms of teleological thinking, as a fulfillment of certain psychophysiological of functions.

  2. Large-scale network dysfunction in Major Depressive Disorder: Meta-analysis of resting-state functional connectivity

    PubMed Central

    Kaiser, Roselinde H.; Andrews-Hanna, Jessica R.; Wager, Tor D.; Pizzagalli, Diego A.

    2015-01-01

    IMPORTANCE Major depressive disorder (MDD) has been linked to imbalanced communication among large-scale brain networks, as reflected by abnormal resting-state functional connectivity (rsFC). However, given variable methods and results across studies, identifying consistent patterns of network dysfunction in MDD has been elusive. OBJECTIVE To investigate network dysfunction in MDD through the first meta-analysis of rsFC studies. DATA SOURCES Seed-based voxel-wise rsFC studies comparing MDD with healthy individuals (published before June 30, 2014) were retrieved from electronic databases (PubMed, Web-of-Science, EMBASE), and authors contacted for additional data. STUDY SELECTION Twenty-seven datasets from 25 publications (556 MDD adults/teens; 518 controls) were included in the meta-analysis. DATA EXTRACTION AND SYNTHESIS Coordinates of seed regions-of-interest and between-group effects were extracted. Seeds were categorized into “seed-networks” by their location within a priori functional networks. Multilevel kernel density analysis of between-group effects identified brain systems in which MDD was associated with hyperconnectivity (increased positive, or reduced negative, connectivity) or hypoconnectivity (increased negative, or reduced positive, connectivity) with each seed-network. RESULTS MDD was characterized by hypoconnectivity within the frontoparietal network (FN), a set of regions involved in cognitive control of attention and emotion regulation, and hypoconnectivity between frontoparietal systems and parietal regions of the dorsal attention network (DAN) involved in attending to the external environment. MDD was also associated with hyperconnectivity within the default network (DN), a network believed to support internally-oriented and self-referential thought, and hyperconnectivity between FN control systems and regions of DN. Finally, MDD groups exhibited hypoconnectivity between neural systems involved in processing emotion or salience and midline

  3. Measuring functional connectivity using MEG: Methodology and comparison with fcMRI

    PubMed Central

    Brookes, Matthew J.; Hale, Joanne R.; Zumer, Johanna M.; Stevenson, Claire M.; Francis, Susan T.; Barnes, Gareth R.; Owen, Julia P.; Morris, Peter G.; Nagarajan, Srikantan S.

    2011-01-01

    Functional connectivity (FC) between brain regions is thought to be central to the way in which the brain processes information. Abnormal connectivity is thought to be implicated in a number of diseases. The ability to study FC is therefore a key goal for neuroimaging. Functional connectivity (fc) MRI has become a popular tool to make connectivity measurements but the technique is limited by its indirect nature. A multimodal approach is therefore an attractive means to investigate the electrodynamic mechanisms underlying hemodynamic connectivity. In this paper, we investigate resting state FC using fcMRI and magnetoencephalography (MEG). In fcMRI, we exploit the advantages afforded by ultra high magnetic field. In MEG we apply envelope correlation and coherence techniques to source space projected MEG signals. We show that beamforming provides an excellent means to measure FC in source space using MEG data. However, care must be taken when interpreting these measurements since cross talk between voxels in source space can potentially lead to spurious connectivity and this must be taken into account in all studies of this type. We show good spatial agreement between FC measured independently using MEG and fcMRI; FC between sensorimotor cortices was observed using both modalities, with the best spatial agreement when MEG data are filtered into the β band. This finding helps to reduce the potential confounds associated with each modality alone: while it helps reduce the uncertainties in spatial patterns generated by MEG (brought about by the ill posed inverse problem), addition of electrodynamic metric confirms the neural basis of fcMRI measurements. Finally, we show that multiple MEG based FC metrics allow the potential to move beyond what is possible using fcMRI, and investigate the nature of electrodynamic connectivity. Our results extend those from previous studies and add weight to the argument that neural oscillations are intimately related to functional

  4. Space-Time Neural Networks

    NASA Technical Reports Server (NTRS)

    Villarreal, James A.; Shelton, Robert O.

    1992-01-01

    Concept of space-time neural network affords distributed temporal memory enabling such network to model complicated dynamical systems mathematically and to recognize temporally varying spatial patterns. Digital filters replace synaptic-connection weights of conventional back-error-propagation neural network.

  5. Aberrant striatal functional connectivity in children with autism.

    PubMed

    Di Martino, Adriana; Kelly, Clare; Grzadzinski, Rebecca; Zuo, Xi-Nian; Mennes, Maarten; Mairena, Maria Angeles; Lord, Catherine; Castellanos, F Xavier; Milham, Michael P

    2011-05-01

    Models of autism spectrum disorders (ASD) as neural disconnection syndromes have been predominantly supported by examinations of abnormalities in corticocortical networks in adults with autism. A broader body of research implicates subcortical structures, particularly the striatum, in the physiopathology of autism. Resting state functional magnetic resonance imaging has revealed detailed maps of striatal circuitry in healthy and psychiatric populations and vividly captured maturational changes in striatal circuitry during typical development. Using resting state functional magnetic resonance imaging, we examined striatal functional connectivity (FC) in 20 children with ASD and 20 typically developing children between the ages of 7.6 and 13.5 years. Whole-brain voxelwise statistical maps quantified within-group striatal FC and between-group differences for three caudate and three putamen seeds for each hemisphere. Children with ASD mostly exhibited prominent patterns of ectopic striatal FC (i.e., functional connectivity present in ASD but not in typically developing children), with increased functional connectivity between nearly all striatal subregions and heteromodal associative and limbic cortex previously implicated in the physiopathology of ASD (e.g., insular and right superior temporal gyrus). Additionally, we found striatal functional hyperconnectivity with the pons, thus expanding the scope of functional alterations implicated in ASD. Secondary analyses revealed ASD-related hyperconnectivity between the pons and insula cortex. Examination of FC of striatal networks in children with ASD revealed abnormalities in circuits involving early developing areas, such as the brainstem and insula, with a pattern of increased FC in ectopic circuits that likely reflects developmental derangement rather than immaturity of functional circuits. Copyright © 2011 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  6. Altered neural connectivity during response inhibition in adolescents with attention-deficit/hyperactivity disorder and their unaffected siblings

    PubMed Central

    van Rooij, Daan; Hartman, Catharina A.; Mennes, Maarten; Oosterlaan, Jaap; Franke, Barbara; Rommelse, Nanda; Heslenfeld, Dirk; Faraone, Stephen V.; Buitelaar, Jan K.; Hoekstra, Pieter J.

    2015-01-01

    Introduction Response inhibition is one of the executive functions impaired in attention-deficit/hyperactivity disorder (ADHD). Increasing evidence indicates that altered functional and structural neural connectivity are part of the neurobiological basis of ADHD. Here, we investigated if adolescents with ADHD show altered functional connectivity during response inhibition compared to their unaffected siblings and healthy controls. Methods Response inhibition was assessed using the stop signal paradigm. Functional connectivity was assessed using psycho-physiological interaction analyses applied to BOLD time courses from seed regions within inferior- and superior frontal nodes of the response inhibition network. Resulting networks were compared between adolescents with ADHD (N = 185), their unaffected siblings (N = 111), and controls (N = 125). Results Control subjects showed stronger functional connectivity than the other two groups within the response inhibition network, while subjects with ADHD showed relatively stronger connectivity between default mode network (DMN) nodes. Stronger connectivity within the response inhibition network was correlated with lower ADHD severity, while stronger connectivity with the DMN was correlated with increased ADHD severity. Siblings showed connectivity patterns similar to controls during successful inhibition and to ADHD subjects during failed inhibition. Additionally, siblings showed decreased connectivity with the primary motor areas as compared to both participants with ADHD and controls. Discussion Subjects with ADHD fail to integrate activation within the response inhibition network and to inhibit connectivity with task-irrelevant regions. Unaffected siblings show similar alterations only during failed stop trials, as well as unique suppression of motor areas, suggesting compensatory strategies. These findings support the role of altered functional connectivity in understanding the neurobiology and familial

  7. Altered neural connectivity during response inhibition in adolescents with attention-deficit/hyperactivity disorder and their unaffected siblings.

    PubMed

    van Rooij, Daan; Hartman, Catharina A; Mennes, Maarten; Oosterlaan, Jaap; Franke, Barbara; Rommelse, Nanda; Heslenfeld, Dirk; Faraone, Stephen V; Buitelaar, Jan K; Hoekstra, Pieter J

    2015-01-01

    Response inhibition is one of the executive functions impaired in attention-deficit/hyperactivity disorder (ADHD). Increasing evidence indicates that altered functional and structural neural connectivity are part of the neurobiological basis of ADHD. Here, we investigated if adolescents with ADHD show altered functional connectivity during response inhibition compared to their unaffected siblings and healthy controls. Response inhibition was assessed using the stop signal paradigm. Functional connectivity was assessed using psycho-physiological interaction analyses applied to BOLD time courses from seed regions within inferior- and superior frontal nodes of the response inhibition network. Resulting networks were compared between adolescents with ADHD (N = 185), their unaffected siblings (N = 111), and controls (N = 125). Control subjects showed stronger functional connectivity than the other two groups within the response inhibition network, while subjects with ADHD showed relatively stronger connectivity between default mode network (DMN) nodes. Stronger connectivity within the response inhibition network was correlated with lower ADHD severity, while stronger connectivity with the DMN was correlated with increased ADHD severity. Siblings showed connectivity patterns similar to controls during successful inhibition and to ADHD subjects during failed inhibition. Additionally, siblings showed decreased connectivity with the primary motor areas as compared to both participants with ADHD and controls. Subjects with ADHD fail to integrate activation within the response inhibition network and to inhibit connectivity with task-irrelevant regions. Unaffected siblings show similar alterations only during failed stop trials, as well as unique suppression of motor areas, suggesting compensatory strategies. These findings support the role of altered functional connectivity in understanding the neurobiology and familial transmission of ADHD.

  8. Disrupted cortical connectivity theory as an explanatory model for autism spectrum disorders

    NASA Astrophysics Data System (ADS)

    Kana, Rajesh K.; Libero, Lauren E.; Moore, Marie S.

    2011-12-01

    such as Theory-of-Mind, cognitive flexibility, and information processing; and 2) how connection abnormalities relate to, and may determine, behavioral symptoms hallmarked by the triad of Impairments in ASD. Furthermore, we will relate the disrupted cortical connectivity model to existing cognitive and neural models of ASD.

  9. Exploring non-stationarity patterns in schizophrenia: neural reorganization abnormalities in the alpha band

    NASA Astrophysics Data System (ADS)

    Núñez, Pablo; Poza, Jesús; Bachiller, Alejandro; Gomez-Pilar, Javier; Lubeiro, Alba; Molina, Vicente; Hornero, Roberto

    2017-08-01

    Objective. The aim of this paper was to characterize brain non-stationarity during an auditory oddball task in schizophrenia (SCH). The level of non-stationarity was measured in the baseline and response windows of relevant tones in SCH patients and healthy controls. Approach. Event-related potentials were recorded from 28 SCH patients and 51 controls. Non-stationarity was estimated in the conventional electroencephalography frequency bands by means of Kullback-Leibler divergence (KLD). Relative power (RP) was also computed to assess a possible complementarity with KLD. Main results. Results showed a widespread statistically significant increase in the level of non-stationarity from baseline to response in all frequency bands for both groups. Statistically significant differences in non-stationarity were found between SCH patients and controls in beta-2 and in the alpha band. SCH patients showed more non-stationarity in the left parieto-occipital region during the baseline window in the beta-2 band. A leave-one-out cross validation classification study with feature selection based on binary stepwise logistic regression to discriminate between SCH patients and controls provided a positive predictive value of 72.73% and negative predictive value of 78.95%. Significance. KLD can characterize transient neural reorganization during an attentional task in response to novelty and relevance. Our findings suggest anomalous reorganization of neural dynamics in SCH during an oddball task. The abnormal frequency-dependent modulation found in SCH patients during relevant tones is in agreement with the hypothesis of aberrant salience detection in SCH. The increase in non-stationarity in the alpha band during the active task supports the notion that this band is involved in top-down processing. The baseline differences in the beta-2 band suggest that hyperactivation of the default mode network during attention tasks may be related to SCH symptoms. Furthermore, the classification

  10. Neural code alterations and abnormal time patterns in Parkinson’s disease

    NASA Astrophysics Data System (ADS)

    Andres, Daniela Sabrina; Cerquetti, Daniel; Merello, Marcelo

    2015-04-01

    Objective. The neural code used by the basal ganglia is a current question in neuroscience, relevant for the understanding of the pathophysiology of Parkinson’s disease. While a rate code is known to participate in the communication between the basal ganglia and the motor thalamus/cortex, different lines of evidence have also favored the presence of complex time patterns in the discharge of the basal ganglia. To gain insight into the way the basal ganglia code information, we studied the activity of the globus pallidus pars interna (GPi), an output node of the circuit. Approach. We implemented the 6-hydroxydopamine model of Parkinsonism in Sprague-Dawley rats, and recorded the spontaneous discharge of single GPi neurons, in head-restrained conditions at full alertness. Analyzing the temporal structure function, we looked for characteristic scales in the neuronal discharge of the GPi. Main results. At a low-scale, we observed the presence of dynamic processes, which allow the transmission of time patterns. Conversely, at a middle-scale, stochastic processes force the use of a rate code. Regarding the time patterns transmitted, we measured the word length and found that it is increased in Parkinson’s disease. Furthermore, it showed a positive correlation with the frequency of discharge, indicating that an exacerbation of this abnormal time pattern length can be expected, as the dopamine depletion progresses. Significance. We conclude that a rate code and a time pattern code can co-exist in the basal ganglia at different temporal scales. However, their normal balance is progressively altered and replaced by pathological time patterns in Parkinson’s disease.

  11. Connecting Neural Coding to Number Cognition: A Computational Account

    ERIC Educational Resources Information Center

    Prather, Richard W.

    2012-01-01

    The current study presents a series of computational simulations that demonstrate how the neural coding of numerical magnitude may influence number cognition and development. This includes behavioral phenomena cataloged in cognitive literature such as the development of numerical estimation and operational momentum. Though neural research has…

  12. Large-Scale Network Dysfunction in Major Depressive Disorder: A Meta-analysis of Resting-State Functional Connectivity.

    PubMed

    Kaiser, Roselinde H; Andrews-Hanna, Jessica R; Wager, Tor D; Pizzagalli, Diego A

    2015-06-01

    Major depressive disorder (MDD) has been linked to imbalanced communication among large-scale brain networks, as reflected by abnormal resting-state functional connectivity (rsFC). However, given variable methods and results across studies, identifying consistent patterns of network dysfunction in MDD has been elusive. To investigate network dysfunction in MDD through a meta-analysis of rsFC studies. Seed-based voxelwise rsFC studies comparing individuals with MDD with healthy controls (published before June 30, 2014) were retrieved from electronic databases (PubMed, Web of Science, and EMBASE) and authors contacted for additional data. Twenty-seven seed-based voxel-wise rsFC data sets from 25 publications (556 individuals with MDD and 518 healthy controls) were included in the meta-analysis. Coordinates of seed regions of interest and between-group effects were extracted. Seeds were categorized into seed-networks by their location within a priori functional networks. Multilevel kernel density analysis of between-group effects identified brain systems in which MDD was associated with hyperconnectivity (increased positive or reduced negative connectivity) or hypoconnectivity (increased negative or reduced positive connectivity) with each seed-network. Major depressive disorder was characterized by hypoconnectivity within the frontoparietal network, a set of regions involved in cognitive control of attention and emotion regulation, and hypoconnectivity between frontoparietal systems and parietal regions of the dorsal attention network involved in attending to the external environment. Major depressive disorder was also associated with hyperconnectivity within the default network, a network believed to support internally oriented and self-referential thought, and hyperconnectivity between frontoparietal control systems and regions of the default network. Finally, the MDD groups exhibited hypoconnectivity between neural systems involved in processing emotion or

  13. Coherent periodic activity in excitatory Erdös-Renyi neural networks: the role of network connectivity.

    PubMed

    Tattini, Lorenzo; Olmi, Simona; Torcini, Alessandro

    2012-06-01

    In this article, we investigate the role of connectivity in promoting coherent activity in excitatory neural networks. In particular, we would like to understand if the onset of collective oscillations can be related to a minimal average connectivity and how this critical connectivity depends on the number of neurons in the networks. For these purposes, we consider an excitatory random network of leaky integrate-and-fire pulse coupled neurons. The neurons are connected as in a directed Erdös-Renyi graph with average connectivity scaling as a power law with the number of neurons in the network. The scaling is controlled by a parameter γ, which allows to pass from massively connected to sparse networks and therefore to modify the topology of the system. At a macroscopic level, we observe two distinct dynamical phases: an asynchronous state corresponding to a desynchronized dynamics of the neurons and a regime of partial synchronization (PS) associated with a coherent periodic activity of the network. At low connectivity, the system is in an asynchronous state, while PS emerges above a certain critical average connectivity (c). For sufficiently large networks, (c) saturates to a constant value suggesting that a minimal average connectivity is sufficient to observe coherent activity in systems of any size irrespectively of the kind of considered network: sparse or massively connected. However, this value depends on the nature of the synapses: reliable or unreliable. For unreliable synapses, the critical value required to observe the onset of macroscopic behaviors is noticeably smaller than for reliable synaptic transmission. Due to the disorder present in the system, for finite number of neurons we have inhomogeneities in the neuronal behaviors, inducing a weak form of chaos, which vanishes in the thermodynamic limit. In such a limit, the disordered systems exhibit regular (non chaotic) dynamics and their properties correspond to that of a homogeneous fully

  14. Speed hysteresis and noise shaping of traveling fronts in neural fields: role of local circuitry and nonlocal connectivity

    NASA Astrophysics Data System (ADS)

    Capone, Cristiano; Mattia, Maurizio

    2017-01-01

    Neural field models are powerful tools to investigate the richness of spatiotemporal activity patterns like waves and bumps, emerging from the cerebral cortex. Understanding how spontaneous and evoked activity is related to the structure of underlying networks is of central interest to unfold how information is processed by these systems. Here we focus on the interplay between local properties like input-output gain function and recurrent synaptic self-excitation of cortical modules, and nonlocal intermodular synaptic couplings yielding to define a multiscale neural field. In this framework, we work out analytic expressions for the wave speed and the stochastic diffusion of propagating fronts uncovering the existence of an optimal balance between local and nonlocal connectivity which minimizes the fluctuations of the activation front propagation. Incorporating an activity-dependent adaptation of local excitability further highlights the independent role that local and nonlocal connectivity play in modulating the speed of propagation of the activation and silencing wavefronts, respectively. Inhomogeneities in space of local excitability give raise to a novel hysteresis phenomenon such that the speed of waves traveling in opposite directions display different velocities in the same location. Taken together these results provide insights on the multiscale organization of brain slow-waves measured during deep sleep and anesthesia.

  15. Mode of Effective Connectivity within a Putative Neural Network Differentiates Moral Cognitions Related to Care and Justice Ethics

    PubMed Central

    Cáceda, Ricardo; James, G. Andrew; Ely, Timothy D.; Snarey, John; Kilts, Clinton D.

    2011-01-01

    Background Moral sensitivity refers to the interpretive awareness of moral conflict and can be justice or care oriented. Justice ethics is associated primarily with human rights and the application of moral rules, whereas care ethics is related to human needs and a situational approach involving social emotions. Among the core brain regions involved in moral issue processing are: medial prefrontal cortex, anterior (ACC) and posterior (PCC) cingulate cortex, posterior superior temporal sulcus (pSTS), insula and amygdala. This study sought to inform the long standing debate of whether care and justice moral ethics represent one or two different forms of cognition. Methodology/Principal Findings Model-free and model-based connectivity analysis were used to identify functional neural networks underlying care and justice ethics for a moral sensitivity task. In addition to modest differences in patterns of associated neural activity, distinct modes of functional and effective connectivity were observed for moral sensitivity for care and justice issues that were modulated by individual variation in moral ability. Conclusions/Significance These results support a neurobiological differentiation between care and justice ethics and suggest that human moral behavior reflects the outcome of integrating opposing rule-based, self-other perspectives, and emotional responses. PMID:21364916

  16. Brain resting-state networks in adolescents with high-functioning autism: Analysis of spatial connectivity and temporal neurodynamics.

    PubMed

    Bernas, Antoine; Barendse, Evelien M; Aldenkamp, Albert P; Backes, Walter H; Hofman, Paul A M; Hendriks, Marc P H; Kessels, Roy P C; Willems, Frans M J; de With, Peter H N; Zinger, Svitlana; Jansen, Jacobus F A

    2018-02-01

    Autism spectrum disorder (ASD) is mainly characterized by functional and communication impairments as well as restrictive and repetitive behavior. The leading hypothesis for the neural basis of autism postulates globally abnormal brain connectivity, which can be assessed using functional magnetic resonance imaging (fMRI). Even in the absence of a task, the brain exhibits a high degree of functional connectivity, known as intrinsic, or resting-state, connectivity. Global default connectivity in individuals with autism versus controls is not well characterized, especially for a high-functioning young population. The aim of this study is to test whether high-functioning adolescents with ASD (HFA) have an abnormal resting-state functional connectivity. We performed spatial and temporal analyses on resting-state networks (RSNs) in 13 HFA adolescents and 13 IQ- and age-matched controls. For the spatial analysis, we used probabilistic independent component analysis (ICA) and a permutation statistical method to reveal the RSN differences between the groups. For the temporal analysis, we applied Granger causality to find differences in temporal neurodynamics. Controls and HFA display very similar patterns and strengths of resting-state connectivity. We do not find any significant differences between HFA adolescents and controls in the spatial resting-state connectivity. However, in the temporal dynamics of this connectivity, we did find differences in the causal effect properties of RSNs originating in temporal and prefrontal cortices. The results show a difference between HFA and controls in the temporal neurodynamics from the ventral attention network to the salience-executive network: a pathway involving cognitive, executive, and emotion-related cortices. We hypothesized that this weaker dynamic pathway is due to a subtle trigger challenging the cognitive state prior to the resting state.

  17. Evolvable Neural Software System

    NASA Technical Reports Server (NTRS)

    Curtis, Steven A.

    2009-01-01

    The Evolvable Neural Software System (ENSS) is composed of sets of Neural Basis Functions (NBFs), which can be totally autonomously created and removed according to the changing needs and requirements of the software system. The resulting structure is both hierarchical and self-similar in that a given set of NBFs may have a ruler NBF, which in turn communicates with other sets of NBFs. These sets of NBFs may function as nodes to a ruler node, which are also NBF constructs. In this manner, the synthetic neural system can exhibit the complexity, three-dimensional connectivity, and adaptability of biological neural systems. An added advantage of ENSS over a natural neural system is its ability to modify its core genetic code in response to environmental changes as reflected in needs and requirements. The neural system is fully adaptive and evolvable and is trainable before release. It continues to rewire itself while on the job. The NBF is a unique, bilevel intelligence neural system composed of a higher-level heuristic neural system (HNS) and a lower-level, autonomic neural system (ANS). Taken together, the HNS and the ANS give each NBF the complete capabilities of a biological neural system to match sensory inputs to actions. Another feature of the NBF is the Evolvable Neural Interface (ENI), which links the HNS and ANS. The ENI solves the interface problem between these two systems by actively adapting and evolving from a primitive initial state (a Neural Thread) to a complicated, operational ENI and successfully adapting to a training sequence of sensory input. This simulates the adaptation of a biological neural system in a developmental phase. Within the greater multi-NBF and multi-node ENSS, self-similar ENI s provide the basis for inter-NBF and inter-node connectivity.

  18. Generalized Adaptive Artificial Neural Networks

    NASA Technical Reports Server (NTRS)

    Tawel, Raoul

    1993-01-01

    Mathematical model of supervised learning by artificial neural network provides for simultaneous adjustments of both temperatures of neurons and synaptic weights, and includes feedback as well as feedforward synaptic connections. Extension of mathematical model described in "Adaptive Neurons For Artificial Neural Networks" (NPO-17803). Dynamics of neural network represented in new model by less-restrictive continuous formalism.

  19. Dynamic Changes in Amygdala Activation and Functional Connectivity in Children and Adolescents with Anxiety Disorders

    PubMed Central

    Swartz, Johnna R.; Phan, K. Luan; Angstadt, Mike; Fitzgerald, Kate D.; Monk, Christopher S.

    2015-01-01

    Anxiety disorders are associated with abnormalities in amygdala function and prefrontal cortex-amygdala connectivity. The majority of fMRI studies have examined mean group differences in amygdala activation or connectivity in children and adolescents with anxiety disorders relative to controls, but emerging evidence suggests that abnormalities in amygdala function are dependent on the timing of the task and may vary across the course of a scanning session. The goal of the present study was to extend our knowledge of the dynamics of amygdala dysfunction by examining whether changes in amygdala activation and connectivity over scanning differ in pediatric anxiety disorder patients relative to typically developing controls during an emotion processing task. Examining changes in activation over time allows for a comparison of how brain function differs during initial exposure to novel stimuli versus more prolonged exposure. Participants included 34 anxiety disorder patients and 19 controls 7 to 19 years old. Participants performed an emotional face matching task during fMRI scanning and the task was divided into thirds in order to examine change in activation over time. Results demonstrated that patients exhibited an abnormal pattern of amygdala activation characterized by an initially heightened amygdala response relative to controls at the beginning of scanning, followed by significant decreases in activation over time. In addition, controls evidenced greater prefrontal cortex-amygdala connectivity during the beginning of scanning relative to patients. These results indicate that differences in emotion processing between the groups vary from initial exposure to novel stimuli relative to more prolonged exposure. Implications are discussed regarding how this pattern of neural activation may relate to altered early-occurring or anticipatory emotion-regulation strategies and maladaptive later-occurring strategies in children and adolescents with anxiety disorders. PMID

  20. Visual Working Memory Load-Related Changes in Neural Activity and Functional Connectivity

    PubMed Central

    Li, Ling; Zhang, Jin-Xiang; Jiang, Tao

    2011-01-01

    Background Visual working memory (VWM) helps us store visual information to prepare for subsequent behavior. The neuronal mechanisms for sustaining coherent visual information and the mechanisms for limited VWM capacity have remained uncharacterized. Although numerous studies have utilized behavioral accuracy, neural activity, and connectivity to explore the mechanism of VWM retention, little is known about the load-related changes in functional connectivity for hemi-field VWM retention. Methodology/Principal Findings In this study, we recorded electroencephalography (EEG) from 14 normal young adults while they performed a bilateral visual field memory task. Subjects had more rapid and accurate responses to the left visual field (LVF) memory condition. The difference in mean amplitude between the ipsilateral and contralateral event-related potential (ERP) at parietal-occipital electrodes in retention interval period was obtained with six different memory loads. Functional connectivity between 128 scalp regions was measured by EEG phase synchronization in the theta- (4–8 Hz), alpha- (8–12 Hz), beta- (12–32 Hz), and gamma- (32–40 Hz) frequency bands. The resulting matrices were converted to graphs, and mean degree, clustering coefficient and shortest path length was computed as a function of memory load. The results showed that brain networks of theta-, alpha-, beta-, and gamma- frequency bands were load-dependent and visual-field dependent. The networks of theta- and alpha- bands phase synchrony were most predominant in retention period for right visual field (RVF) WM than for LVF WM. Furthermore, only for RVF memory condition, brain network density of theta-band during the retention interval were linked to the delay of behavior reaction time, and the topological property of alpha-band network was negative correlation with behavior accuracy. Conclusions/Significance We suggest that the differences in theta- and alpha- bands between LVF and RVF conditions in

  1. Neural Tube Defects

    PubMed Central

    Greene, Nicholas D.E.; Copp, Andrew J.

    2015-01-01

    Neural tube defects (NTDs), including spina bifida and anencephaly, are severe birth defects of the central nervous system that originate during embryonic development when the neural tube fails to close completely. Human NTDs are multifactorial, with contributions from both genetic and environmental factors. The genetic basis is not yet well understood, but several nongenetic risk factors have been identified as have possibilities for prevention by maternal folic acid supplementation. Mechanisms underlying neural tube closure and NTDs may be informed by experimental models, which have revealed numerous genes whose abnormal function causes NTDs and have provided details of critical cellular and morphological events whose regulation is essential for closure. Such models also provide an opportunity to investigate potential risk factors and to develop novel preventive therapies. PMID:25032496

  2. Fault detection and diagnosis using neural network approaches

    NASA Technical Reports Server (NTRS)

    Kramer, Mark A.

    1992-01-01

    Neural networks can be used to detect and identify abnormalities in real-time process data. Two basic approaches can be used, the first based on training networks using data representing both normal and abnormal modes of process behavior, and the second based on statistical characterization of the normal mode only. Given data representative of process faults, radial basis function networks can effectively identify failures. This approach is often limited by the lack of fault data, but can be facilitated by process simulation. The second approach employs elliptical and radial basis function neural networks and other models to learn the statistical distributions of process observables under normal conditions. Analytical models of failure modes can then be applied in combination with the neural network models to identify faults. Special methods can be applied to compensate for sensor failures, to produce real-time estimation of missing or failed sensors based on the correlations codified in the neural network.

  3. Disruptions in Functional Network Connectivity during Alcohol Intoxicated Driving

    PubMed Central

    Rzepecki-Smith, Catherine I.; Meda, Shashwath A.; Calhoun, Vince D.; Stevens, Michael C.; Jafri, Madiha J.; Astur, Robert S.; Pearlson, Godfrey D.

    2009-01-01

    Background: Driving while under the influence of alcohol is a major public health problem whose neural basis is not well understood. In a recently published fMRI study (Meda et al, 2009), our group identified five, independent critical driving-associated brain circuits whose inter-regional connectivity was disrupted by alcohol intoxication. However, the functional connectivity between these circuits has not yet been explored in order to determine how these networks communicate with each other during sober and alcohol-intoxicated states. Methods: In the current study, we explored such differences in connections between the above brain circuits and driving behavior, under the influence of alcohol versus placebo. Forty social drinkers who drove regularly underwent fMRI scans during virtual reality driving simulations following two alcohol doses, placebo and an individualized dose producing blood alcohol concentrations (BACs) of 0.10%. Results: At the active dose, we found specific disruptions of functional network connectivity between the frontal-temporal-basal ganglia and the cerebellar circuits. The temporal connectivity between these two circuits was found to be less correlated (p <0.05) when driving under the influence of alcohol. This disconnection was also associated with an abnormal driving behavior (unstable motor vehicle steering). Conclusions: Connections between frontal-temporal-basal ganglia and cerebellum have recently been explored; these may be responsible in part for maintaining normal motor behavior by integrating their overlapping motor control functions. These connections appear to be disrupted by alcohol intoxication, in turn associated with an explicit type of impaired driving behavior. PMID:20028354

  4. Convergent evidence for abnormal striatal synaptic plasticity in dystonia

    PubMed Central

    Peterson, David A.; Sejnowski, Terrence J.; Poizner, Howard

    2010-01-01

    Dystonia is a functionally disabling movement disorder characterized by abnormal movements and postures. Although substantial recent progress has been made in identifying genetic factors, the pathophysiology of the disease remains a mystery. A provocative suggestion gaining broader acceptance is that some aspect of neural plasticity may be abnormal. There is also evidence that, at least in some forms of dystonia, sensorimotor “use” may be a contributing factor. Most empirical evidence of abnormal plasticity in dystonia comes from measures of sensorimotor cortical organization and physiology. However, the basal ganglia also play a critical role in sensorimotor function. Furthermore, the basal ganglia are prominently implicated in traditional models of dystonia, are the primary targets of stereotactic neurosurgical interventions, and provide a neural substrate for sensorimotor learning influenced by neuromodulators. Our working hypothesis is that abnormal plasticity in the basal ganglia is a critical link between the etiology and pathophysiology of dystonia. In this review we set up the background for this hypothesis by integrating a large body of disparate indirect evidence that dystonia may involve abnormalities in synaptic plasticity in the striatum. After reviewing evidence implicating the striatum in dystonia, we focus on the influence of two neuromodulatory systems: dopamine and acetylcholine. For both of these neuromodulators, we first describe the evidence for abnormalities in dystonia and then the means by which it may influence striatal synaptic plasticity. Collectively, the evidence suggests that many different forms of dystonia may involve abnormal plasticity in the striatum. An improved understanding of these altered plastic processes would help inform our understanding of the pathophysiology of dystonia, and, given the role of the striatum in sensorimotor learning, provide a principled basis for designing therapies aimed at the dynamic processes

  5. Increased resting state functional connectivity in the fronto-parietal and default mode network in anorexia nervosa

    PubMed Central

    Boehm, Ilka; Geisler, Daniel; King, Joseph A.; Ritschel, Franziska; Seidel, Maria; Deza Araujo, Yacila; Petermann, Juliane; Lohmeier, Heidi; Weiss, Jessika; Walter, Martin; Roessner, Veit; Ehrlich, Stefan

    2014-01-01

    The etiology of anorexia nervosa (AN) is poorly understood. Results from functional brain imaging studies investigating the neural profile of AN using cognitive and emotional task paradigms are difficult to reconcile. Task-related imaging studies often require a high level of compliance and can only partially explore the distributed nature and complexity of brain function. In this study, resting state functional connectivity imaging was used to investigate well-characterized brain networks potentially relevant to understand the neural mechanisms underlying the symptomatology and etiology of AN. Resting state functional magnetic resonance imaging data was obtained from 35 unmedicated female acute AN patients and 35 closely matched healthy controls female participants (HC) and decomposed using spatial group independent component analyses (ICA). Using validated templates, we identified components covering the fronto-parietal “control” network, the default mode network (DMN), the salience network, the visual and the sensory-motor network. Group comparison revealed an increased functional connectivity between the angular gyrus and the other parts of the fronto-parietal network in patients with AN in comparison to HC. Connectivity of the angular gyrus was positively associated with self-reported persistence in HC. In the DMN, AN patients also showed an increased functional connectivity strength in the anterior insula in comparison to HC. Anterior insula connectivity was associated with self-reported problems with interoceptive awareness. This study, with one of the largest sample to date, shows that acute AN is associated with abnormal brain connectivity in two major resting state networks (RSN). The finding of an increased functional connectivity in the fronto-parietal network adds novel support for the notion of AN as a disorder of excessive cognitive control, whereas the elevated functional connectivity of the anterior insula with the DMN may reflect the high

  6. Functional connectivity and information flow of the respiratory neural network in chronic obstructive pulmonary disease.

    PubMed

    Yu, Lianchun; De Mazancourt, Marine; Hess, Agathe; Ashadi, Fakhrul R; Klein, Isabelle; Mal, Hervé; Courbage, Maurice; Mangin, Laurence

    2016-08-01

    Breathing involves a complex interplay between the brainstem automatic network and cortical voluntary command. How these brain regions communicate at rest or during inspiratory loading is unknown. This issue is crucial for several reasons: (i) increased respiratory loading is a major feature of several respiratory diseases, (ii) failure of the voluntary motor and cortical sensory processing drives is among the mechanisms that precede acute respiratory failure, (iii) several cerebral structures involved in responding to inspiratory loading participate in the perception of dyspnea, a distressing symptom in many disease. We studied functional connectivity and Granger causality of the respiratory network in controls and patients with chronic obstructive pulmonary disease (COPD), at rest and during inspiratory loading. Compared with those of controls, the motor cortex area of patients exhibited decreased connectivity with their contralateral counterparts and no connectivity with the brainstem. In the patients, the information flow was reversed at rest with the source of the network shifted from the medulla towards the motor cortex. During inspiratory loading, the system was overwhelmed and the motor cortex became the sink of the network. This major finding may help to understand why some patients with COPD are prone to acute respiratory failure. Network connectivity and causality were related to lung function and illness severity. We validated our connectivity and causality results with a mathematical model of neural network. Our findings suggest a new therapeutic strategy involving the modulation of brain activity to increase motor cortex functional connectivity and improve respiratory muscles performance in patients. Hum Brain Mapp 37:2736-2754, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

  7. A neural network with modular hierarchical learning

    NASA Technical Reports Server (NTRS)

    Baldi, Pierre F. (Inventor); Toomarian, Nikzad (Inventor)

    1994-01-01

    This invention provides a new hierarchical approach for supervised neural learning of time dependent trajectories. The modular hierarchical methodology leads to architectures which are more structured than fully interconnected networks. The networks utilize a general feedforward flow of information and sparse recurrent connections to achieve dynamic effects. The advantages include the sparsity of units and connections, the modular organization. A further advantage is that the learning is much more circumscribed learning than in fully interconnected systems. The present invention is embodied by a neural network including a plurality of neural modules each having a pre-established performance capability wherein each neural module has an output outputting present results of the performance capability and an input for changing the present results of the performance capabilitiy. For pattern recognition applications, the performance capability may be an oscillation capability producing a repeating wave pattern as the present results. In the preferred embodiment, each of the plurality of neural modules includes a pre-established capability portion and a performance adjustment portion connected to control the pre-established capability portion.

  8. Distinct neural signatures detected for ADHD subtypes after controlling for micro-movements in resting state functional connectivity MRI data

    PubMed Central

    Fair, Damien A.; Nigg, Joel T.; Iyer, Swathi; Bathula, Deepti; Mills, Kathryn L.; Dosenbach, Nico U. F.; Schlaggar, Bradley L.; Mennes, Maarten; Gutman, David; Bangaru, Saroja; Buitelaar, Jan K.; Dickstein, Daniel P.; Di Martino, Adriana; Kennedy, David N.; Kelly, Clare; Luna, Beatriz; Schweitzer, Julie B.; Velanova, Katerina; Wang, Yu-Feng; Mostofsky, Stewart; Castellanos, F. Xavier; Milham, Michael P.

    2012-01-01

    In recent years, there has been growing enthusiasm that functional magnetic resonance imaging (MRI) could achieve clinical utility for a broad range of neuropsychiatric disorders. However, several barriers remain. For example, the acquisition of large-scale datasets capable of clarifying the marked heterogeneity that exists in psychiatric illnesses will need to be realized. In addition, there continues to be a need for the development of image processing and analysis methods capable of separating signal from artifact. As a prototypical hyperkinetic disorder, and movement-related artifact being a significant confound in functional imaging studies, ADHD offers a unique challenge. As part of the ADHD-200 Global Competition and this special edition of Frontiers, the ADHD-200 Consortium demonstrates the utility of an aggregate dataset pooled across five institutions in addressing these challenges. The work aimed to (1) examine the impact of emerging techniques for controlling for “micro-movements,” and (2) provide novel insights into the neural correlates of ADHD subtypes. Using support vector machine (SVM)-based multivariate pattern analysis (MVPA) we show that functional connectivity patterns in individuals are capable of differentiating the two most prominent ADHD subtypes. The application of graph-theory revealed that the Combined (ADHD-C) and Inattentive (ADHD-I) subtypes demonstrated some overlapping (particularly sensorimotor systems), but unique patterns of atypical connectivity. For ADHD-C, atypical connectivity was prominent in midline default network components, as well as insular cortex; in contrast, the ADHD-I group exhibited atypical patterns within the dlPFC regions and cerebellum. Systematic motion-related artifact was noted, and highlighted the need for stringent motion correction. Findings reported were robust to the specific motion correction strategy employed. These data suggest that resting-state functional connectivity MRI (rs-fcMRI) data can

  9. Effective connectivity in the neural network underlying coarse-to-fine categorization of visual scenes. A dynamic causal modeling study.

    PubMed

    Kauffmann, Louise; Chauvin, Alan; Pichat, Cédric; Peyrin, Carole

    2015-10-01

    According to current models of visual perception scenes are processed in terms of spatial frequencies following a predominantly coarse-to-fine processing sequence. Low spatial frequencies (LSF) reach high-order areas rapidly in order to activate plausible interpretations of the visual input. This triggers top-down facilitation that guides subsequent processing of high spatial frequencies (HSF) in lower-level areas such as the inferotemporal and occipital cortices. However, dynamic interactions underlying top-down influences on the occipital cortex have never been systematically investigated. The present fMRI study aimed to further explore the neural bases and effective connectivity underlying coarse-to-fine processing of scenes, particularly the role of the occipital cortex. We used sequences of six filtered scenes as stimuli depicting coarse-to-fine or fine-to-coarse processing of scenes. Participants performed a categorization task on these stimuli (indoor vs. outdoor). Firstly, we showed that coarse-to-fine (compared to fine-to-coarse) sequences elicited stronger activation in the inferior frontal gyrus (in the orbitofrontal cortex), the inferotemporal cortex (in the fusiform and parahippocampal gyri), and the occipital cortex (in the cuneus). Dynamic causal modeling (DCM) was then used to infer effective connectivity between these regions. DCM results revealed that coarse-to-fine processing resulted in increased connectivity from the occipital cortex to the inferior frontal gyrus and from the inferior frontal gyrus to the inferotemporal cortex. Critically, we also observed an increase in connectivity strength from the inferior frontal gyrus to the occipital cortex, suggesting that top-down influences from frontal areas may guide processing of incoming signals. The present results support current models of visual perception and refine them by emphasizing the role of the occipital cortex as a cortical site for feedback projections in the neural network underlying

  10. Neural-Network Simulator

    NASA Technical Reports Server (NTRS)

    Mitchell, Paul H.

    1991-01-01

    F77NNS (FORTRAN 77 Neural Network Simulator) computer program simulates popular back-error-propagation neural network. Designed to take advantage of vectorization when used on computers having this capability, also used on any computer equipped with ANSI-77 FORTRAN Compiler. Problems involving matching of patterns or mathematical modeling of systems fit class of problems F77NNS designed to solve. Program has restart capability so neural network solved in stages suitable to user's resources and desires. Enables user to customize patterns of connections between layers of network. Size of neural network F77NNS applied to limited only by amount of random-access memory available to user.

  11. Automatic diagnosis of abnormal macula in retinal optical coherence tomography images using wavelet-based convolutional neural network features and random forests classifier

    NASA Astrophysics Data System (ADS)

    Rasti, Reza; Mehridehnavi, Alireza; Rabbani, Hossein; Hajizadeh, Fedra

    2018-03-01

    The present research intends to propose a fully automatic algorithm for the classification of three-dimensional (3-D) optical coherence tomography (OCT) scans of patients suffering from abnormal macula from normal candidates. The method proposed does not require any denoising, segmentation, retinal alignment processes to assess the intraretinal layers, as well as abnormalities or lesion structures. To classify abnormal cases from the control group, a two-stage scheme was utilized, which consists of automatic subsystems for adaptive feature learning and diagnostic scoring. In the first stage, a wavelet-based convolutional neural network (CNN) model was introduced and exploited to generate B-scan representative CNN codes in the spatial-frequency domain, and the cumulative features of 3-D volumes were extracted. In the second stage, the presence of abnormalities in 3-D OCTs was scored over the extracted features. Two different retinal SD-OCT datasets are used for evaluation of the algorithm based on the unbiased fivefold cross-validation (CV) approach. The first set constitutes 3-D OCT images of 30 normal subjects and 30 diabetic macular edema (DME) patients captured from the Topcon device. The second publicly available set consists of 45 subjects with a distribution of 15 patients in age-related macular degeneration, DME, and normal classes from the Heidelberg device. With the application of the algorithm on overall OCT volumes and 10 repetitions of the fivefold CV, the proposed scheme obtained an average precision of 99.33% on dataset1 as a two-class classification problem and 98.67% on dataset2 as a three-class classification task.

  12. A Realistic Neural Mass Model of the Cortex with Laminar-Specific Connections and Synaptic Plasticity – Evaluation with Auditory Habituation

    PubMed Central

    Wang, Peng; Knösche, Thomas R.

    2013-01-01

    In this work we propose a biologically realistic local cortical circuit model (LCCM), based on neural masses, that incorporates important aspects of the functional organization of the brain that have not been covered by previous models: (1) activity dependent plasticity of excitatory synaptic couplings via depleting and recycling of neurotransmitters and (2) realistic inter-laminar dynamics via laminar-specific distribution of and connections between neural populations. The potential of the LCCM was demonstrated by accounting for the process of auditory habituation. The model parameters were specified using Bayesian inference. It was found that: (1) besides the major serial excitatory information pathway (layer 4 to layer 2/3 to layer 5/6), there exists a parallel “short-cut” pathway (layer 4 to layer 5/6), (2) the excitatory signal flow from the pyramidal cells to the inhibitory interneurons seems to be more intra-laminar while, in contrast, the inhibitory signal flow from inhibitory interneurons to the pyramidal cells seems to be both intra- and inter-laminar, and (3) the habituation rates of the connections are unsymmetrical: forward connections (from layer 4 to layer 2/3) are more strongly habituated than backward connections (from Layer 5/6 to layer 4). Our evaluation demonstrates that the novel features of the LCCM are of crucial importance for mechanistic explanations of brain function. The incorporation of these features into a mass model makes them applicable to modeling based on macroscopic data (like EEG or MEG), which are usually available in human experiments. Our LCCM is therefore a valuable building block for future realistic models of human cognitive function. PMID:24205009

  13. Caged Neuron MEA: A system for long-term investigation of cultured neural network connectivity

    PubMed Central

    Erickson, Jonathan; Tooker, Angela; Tai, Y-C.; Pine, Jerome

    2008-01-01

    Traditional techniques for investigating cultured neural networks, such as the patch clamp and multi-electrode array, are limited by: 1) the number of identified cells which can be simultaneously electrically contacted, 2) the length of time for which cells can be studied, and 3) the lack of one-to-one neuron-to-electrode specificity. Here, we present a new device—the caged neuron multi-electrode array—which overcomes these limitations. This micro-machined device consists of an array of neurocages which mechanically trap a neuron near an extracellular electrode. While the cell body is trapped, the axon and dendrites can freely grow into the surrounding area to form a network. The electrode is bi-directional, capable of both stimulating and recording action potentials. This system is non-invasive, so that all constituent neurons of a network can be studied over its lifetime with stable one-to-one neuron-to-electrode correspondence. Proof-of-concept experiments are described to illustrate that functional networks form in a neurochip system of 16 cages in a 4×4 array, and that suprathreshold connectivity can be fully mapped over several weeks. The neurochip opens a new domain in neurobiology for studying small cultured neural networks. PMID:18775453

  14. Disrupted cortical connectivity theory as an explanatory model for autism spectrum disorders.

    PubMed

    Kana, Rajesh K; Libero, Lauren E; Moore, Marie S

    2011-12-01

    as Theory-of-Mind, cognitive flexibility, and information processing; and 2) how connection abnormalities relate to, and may determine, behavioral symptoms hallmarked by the triad of Impairments in ASD. Furthermore, we will relate the disrupted cortical connectivity model to existing cognitive and neural models of ASD. Published by Elsevier B.V.

  15. Incorrect electrode cable connection during electrocardiographic recording.

    PubMed

    Batchvarov, Velislav N; Malik, Marek; Camm, A John

    2007-11-01

    Incorrect electrode cable connections during electrocardiographic (ECG) recording can simulate rhythm or conduction disturbance, myocardial ischaemia and infarction, as well as other clinically important abnormalities. When only precordial or only limb cables, excluding the neutral cable, have been interchanged the waveforms in the different leads are re-arranged, inverted, or unchanged, whereas the duration of intervals is not changed. The mistake can be recognized by the presence of unusual P-QRS patterns (e.g. negative P-QRS in lead I or II, positive in lead AVR, P-QRS complexes of opposite direction in leads I and V6, etc.), change in the P-QRS axis, or abnormal precordial QRS-T wave progression. Interchange of limb cables with the neutral cable distorts Wilson's terminal and the morphology of all precordial and unipolar limb leads. The telltale sign of the mistake is the presence of (almost) a flat line in lead I, II or III. Interchange of even one of the limb cables, except for the neutral cable, with a precordial cable distorts the morphology of most leads and leaves not more than one lead (I, II, or III) unchanged. Computerized algorithms for detection of lead misplacement, such as those based on artificial neural networks, or on correlation between original and reconstructed leads, have been developed.

  16. Impaired thalamocortical connectivity in autism spectrum disorder: a study of functional and anatomical connectivity.

    PubMed

    Nair, Aarti; Treiber, Jeffrey M; Shukla, Dinesh K; Shih, Patricia; Müller, Ralph-Axel

    2013-06-01

    The thalamus plays crucial roles in the development and mature functioning of numerous sensorimotor, cognitive and attentional circuits. Currently limited evidence suggests that autism spectrum disorder may be associated with thalamic abnormalities, potentially related to sociocommunicative and other impairments in this disorder. We used functional connectivity magnetic resonance imaging and diffusion tensor imaging probabilistic tractography to study the functional and anatomical integrity of thalamo-cortical connectivity in children and adolescents with autism spectrum disorder and matched typically developing children. For connectivity with five cortical seeds (prefontal, parieto-occipital, motor, somatosensory and temporal), we found evidence of both anatomical and functional underconnectivity. The only exception was functional connectivity with the temporal lobe, which was increased in the autism spectrum disorders group, especially in the right hemisphere. However, this effect was robust only in partial correlation analyses (partialling out time series from other cortical seeds), whereas findings from total correlation analyses suggest that temporo-thalamic overconnectivity in the autism group was only relative to the underconnectivity found for other cortical seeds. We also found evidence of microstructural compromise within the thalamic motor parcel, associated with compromise in tracts between thalamus and motor cortex, suggesting that the thalamus may play a role in motor abnormalities reported in previous autism studies. More generally, a number of correlations of diffusion tensor imaging and functional connectivity magnetic resonance imaging measures with diagnostic and neuropsychological scores indicate involvement of abnormal thalamocortical connectivity in sociocommunicative and cognitive impairments in autism spectrum disorder.

  17. Emotional detachment in psychopathy: Involvement of dorsal default-mode connections.

    PubMed

    Sethi, Arjun; Gregory, Sarah; Dell'Acqua, Flavio; Periche Thomas, Eva; Simmons, Andy; Murphy, Declan G M; Hodgins, Sheilagh; Blackwood, Nigel J; Craig, Michael C

    2015-01-01

    Criminal psychopathy is defined by emotional detachment [Psychopathy Checklist - Revised (PCL-R) factor 1], and antisocial behaviour (PCL-R factor 2). Previous work has associated antisocial behaviour in psychopathy with abnormalities in a ventral temporo-amygdala-orbitofrontal network. However, little is known of the neural correlates of emotional detachment. Imaging studies have indicated that the 'default-mode network' (DMN), and in particular its dorsomedial (medial prefrontal - posterior cingulate) component, contributes to affective and social processing in healthy individuals. Furthermore, recent work suggests that this network may be implicated in psychopathy. However, no research has examined the relationship between psychopathy, emotional detachment, and the white matter underpinning the DMN. We therefore used diffusion tensor imaging (DTI) tractography in 13 offenders with psychopathy and 13 non-offenders to investigate the relationship between emotional detachment and the microstructure of white matter connections within the DMN. These included the dorsal cingulum (containing the medial prefrontal - posterior cingulate connections of the DMN), and the ventral cingulum (containing the posterior cingulate - medial temporal connections of the DMN). We found that fractional anisotropy (FA) was reduced in the left dorsal cingulum in the psychopathy group (p = .024). Moreover, within this group, emotional detachment was negatively correlated with FA in this tract portion bilaterally (left: r = -.61, p = .026; right: r = -.62, p = .023). These results suggest the importance of the dorsal DMN in the emotional detachment observed in individuals with psychopathy. We propose a 'dual-network' model of white matter abnormalities in the disorder, which incorporates these with previous findings. Copyright © 2014 Elsevier Ltd. All rights reserved.

  18. Differential Resting-State Functional Connectivity of Striatal Subregions in Bipolar Depression and Hypomania

    PubMed Central

    Altinay, Murat I.; Hulvershorn, Leslie A.; Karne, Harish; Beall, Erik B.

    2016-01-01

    Abstract Bipolar disorder (BP) is characterized by periods of depression (BPD) and (hypo)mania (BPM), but the underlying state-related brain circuit abnormalities are not fully understood. Striatal functional activation and connectivity abnormalities have been noted in BP, but consistent findings have not been reported. To further elucidate striatal abnormalities in different BP states, this study investigated differences in resting-state functional connectivity of six striatal subregions in BPD, BPM, and healthy control (HC) subjects. Ninety medication-free subjects (30 BPD, 30 BPM, and 30 HC), closely matched for age and gender, were scanned using 3T functional magnetic resonance imaging (fMRI) acquired at resting state. Correlations of low-frequency blood oxygen level dependent signal fluctuations for six previously described striatal subregions were used to obtain connectivity maps of each subregion. Using a factorial design, main effects for differences between groups were obtained and post hoc pairwise group comparisons performed. BPD showed increased connectivity of the dorsal caudal putamen with somatosensory areas such as the insula and temporal gyrus. BPM group showed unique increased connectivity between left dorsal caudate and midbrain regions, as well as increased connectivity between ventral striatum inferior and thalamus. In addition, both BPD and BPM exhibited widespread functional connectivity abnormalities between striatal subregions and frontal cortices, limbic regions, and midbrain structures. In summary, BPD exhibited connectivity abnormalities of associative and somatosensory subregions of the putamen, while BPM exhibited connectivity abnormalities of associative and limbic caudate. Most other striatal subregion connectivity abnormalities were common to both groups and may be trait related. PMID:26824737

  19. Tone-deafness – a new disconnection syndrome?

    PubMed Central

    Loui, Psyche; Alsop, David; Schlaug, Gottfried

    2009-01-01

    Communicating with one’s environment requires efficient neural interaction between action and perception. Neural substrates ofsound perception and production are connected by the arcuate fasciculus (AF). While AF is known to be involved in language, its roles in non-linguistic functions are unexplored. Here we show that tone-deaf people, with impaired sound perception and production, have reduced AF connectivity. Diffusion tensor tractography and psychophysics were assessed in tone-deaf individuals and matched controls. Abnormally-reduced AF connectivity was observed in the tone-deaf. Furthermore, we observed relationships between AF and auditory-motor behavior: superior and inferior AF branches predict psychophysically-assessed pitch-discrimination and sound production-perception abilities respectively. This neural abnormality suggests that tone-deafness leads to a reduction in connectivity resulting in pitch-related impairments. Results support a dual-stream anatomy of sound production and perception implicated in vocal communications. By identifying white-matter differences and their psychophysical correlates, results contribute to our understanding of how neural connectivity subserves behavior. PMID:19692596

  20. Neural field theory of perceptual echo and implications for estimating brain connectivity

    NASA Astrophysics Data System (ADS)

    Robinson, P. A.; Pagès, J. C.; Gabay, N. C.; Babaie, T.; Mukta, K. N.

    2018-04-01

    Neural field theory is used to predict and analyze the phenomenon of perceptual echo in which random input stimuli at one location are correlated with electroencephalographic responses at other locations. It is shown that this echo correlation (EC) yields an estimate of the transfer function from the stimulated point to other locations. Modal analysis then explains the observed spatiotemporal structure of visually driven EC and the dominance of the alpha frequency; two eigenmodes of similar amplitude dominate the response, leading to temporal beating and a line of low correlation that runs from the crown of the head toward the ears. These effects result from mode splitting and symmetry breaking caused by interhemispheric coupling and cortical folding. It is shown how eigenmodes obtained from functional magnetic resonance imaging experiments can be combined with temporal dynamics from EC or other evoked responses to estimate the spatiotemporal transfer function between any two points and hence their effective connectivity.

  1. Disrupted intrinsic and remote functional connectivity in heterotopia-related epilepsy.

    PubMed

    Liu, W; Hu, X; An, D; Gong, Q; Zhou, D

    2018-01-01

    Several neuroimaging studies have examined neural interactions in patients with periventricular nodular heterotopia (PNH). However, features of the underlying functional network remain poorly understood. In this study, we examined alterations in the local (regional) and remote (interregional) cerebral networks in this disorder. Twenty-eight subjects all having suffered from PNH with epilepsy, as well as 28 age- and sex- matched healthy controls, were enrolled in this study. Amplitude of low-frequency fluctuation (ALFF) and seed-based functional connectivity (FC) were calculated to detect regional neural function and functional network integration, respectively. Compared with healthy controls, patients with PNH-related epilepsy showed decreased ALFF in the ventromedial prefrontal cortex (vmPFC) and precuneus areas. ALFF values in both areas were negative correlated with epilepsy duration (P < .05, Bonferroni-corrected). Furthermore, patients with PNH-related epilepsy had increased remote interregional FC mainly in bilateral prefrontal and parietal cortices, supramarginal gyrus, dorsal cingulate gyrus, and right insula; lower FC was found in posterior brain regions including bilateral parahippocampal gyrus and inferior temporal gyrus. Focal spontaneous hypofunction, as assessed by ALFF, correlates with epilepsy duration in patients with PNH-related epilepsy. Abnormalities existed both within the default-mode network and then across the whole brain, demonstrating that intrinsic brain dysfunction may be related to specific network interactions. Our findings provide novel understanding of the connectivity-based pathophysiological mechanisms of PNH. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  2. Dynamic labelling of neural connections in multiple colours by trans-synaptic fluorescence complementation

    PubMed Central

    Macpherson, Lindsey J.; Zaharieva, Emanuela E.; Kearney, Patrick J.; Alpert, Michael H.; Lin, Tzu-Yang; Turan, Zeynep; Lee, Chi-Hon; Gallio, Marco

    2015-01-01

    Determining the pattern of activity of individual connections within a neural circuit could provide insights into the computational processes that underlie brain function. Here, we develop new strategies to label active synapses by trans-synaptic fluorescence complementation in Drosophila. First, we demonstrate that a synaptobrevin-GRASP chimera functions as a powerful activity-dependent marker for synapses in vivo. Next, we create cyan and yellow variants, achieving activity-dependent, multi-colour fluorescence reconstitution across synapses (X-RASP). Our system allows for the first time retrospective labelling of synapses (rather than whole neurons) based on their activity, in multiple colours, in the same animal. As individual synapses often act as computational units in the brain, our method will promote the design of experiments that are not possible using existing techniques. Moreover, our strategies are easily adaptable to circuit mapping in any genetic system. PMID:26635273

  3. Altered cerebro-cerebellum resting-state functional connectivity in HIV-infected male patients.

    PubMed

    Wang, Huijuan; Li, Ruili; Zhou, Yawen; Wang, Yanming; Cui, Jin; Nguchu, Benedictor Alexander; Qiu, Bensheng; Wang, Xiaoxiao; Li, Hongjun

    2018-05-21

    In addition to the role of planning and executing movement, the cerebellum greatly contributes to cognitive process. Numerous studies have reported structural and functional abnormalities in the cerebellum for HIV-infected patients, but little is known about the altered functional connectivity of particular cerebellar subregions and the cerebrum. Therefore, this study aimed to explore the resting-state functional connectivity (rsFC) changes of the cerebellum and further analyze the relationship between the rsFC changes and the neuropsychological evaluation. The experiment involved 26 HIV-infected men with asymptomatic neurocognitive impairment (ANI) and 28 healthy controls (HC). We selected bilateral hemispheric lobule VI and lobule IX as seed regions and mapped the whole-brain rsFC for each subregion. Results revealed that right lobule VI showed significant increased rsFC with the anterior cingulate cortex (ACC) in HIV-infected subjects. In addition, the correlation analysis on HIV-infected subjects illustrated the increased rsFC was negatively correlated with the attention/working memory score. Moreover, significantly increased cerebellar rsFCs were also observed in HIV-infected patients related to right inferior frontal gyrus (IFG) and right superior medial gyrus (SMG) while decreased rsFC was just found between right lobule VI and the left hippocampus (HIP). These findings suggested that, abnormalities of cerebro-cerebellar functional connectivity might be associated with cognitive dysfunction in HIV-infected men, particularly working memory impairment. It could also be the underlying mechanism of ANI, providing further evidence for early injury in the neural substrate of HIV-infected patients.

  4. Design of a MIMD neural network processor

    NASA Astrophysics Data System (ADS)

    Saeks, Richard E.; Priddy, Kevin L.; Pap, Robert M.; Stowell, S.

    1994-03-01

    The Accurate Automation Corporation (AAC) neural network processor (NNP) module is a fully programmable multiple instruction multiple data (MIMD) parallel processor optimized for the implementation of neural networks. The AAC NNP design fully exploits the intrinsic sparseness of neural network topologies. Moreover, by using a MIMD parallel processing architecture one can update multiple neurons in parallel with efficiency approaching 100 percent as the size of the network increases. Each AAC NNP module has 8 K neurons and 32 K interconnections and is capable of 140,000,000 connections per second with an eight processor array capable of over one billion connections per second.

  5. Maladaptive Neural Synchrony in Tinnitus: Origin and Restoration

    PubMed Central

    Eggermont, Jos J.; Tass, Peter A.

    2015-01-01

    Tinnitus is the conscious perception of sound heard in the absence of physical sound sources external or internal to the body, reflected in aberrant neural synchrony of spontaneous or resting-state brain activity. Neural synchrony is generated by the nearly simultaneous firing of individual neurons, of the synchronization of membrane-potential changes in local neural groups as reflected in the local field potentials, resulting in the presence of oscillatory brain waves in the EEG. Noise-induced hearing loss, often resulting in tinnitus, causes a reorganization of the tonotopic map in auditory cortex and increased spontaneous firing rates and neural synchrony. Spontaneous brain rhythms rely on neural synchrony. Abnormal neural synchrony in tinnitus appears to be confined to specific frequency bands of brain rhythms. Increases in delta-band activity are generated by deafferented/deprived neuronal networks resulting from hearing loss. Coordinated reset (CR) stimulation was developed in order to specifically counteract such abnormal neuronal synchrony by desynchronization. The goal of acoustic CR neuromodulation is to desynchronize tinnitus-related abnormal delta-band oscillations. CR neuromodulation does not require permanent stimulus delivery in order to achieve long-lasting desynchronization or even a full-blown anti-kindling but may have cumulative effects, i.e., the effect of different CR epochs separated by pauses may accumulate. Unlike other approaches, acoustic CR neuromodulation does not intend to reduce tinnitus-related neuronal activity by employing lateral inhibition. The potential efficacy of acoustic CR modulation was shown in a clinical proof of concept trial, where effects achieved in 12 weeks of treatment delivered 4–6 h/day persisted through a preplanned 4-week therapy pause and showed sustained long-term effects after 10 months of therapy, leading to 75% responders. PMID:25741316

  6. Dynamic Neural Networks Supporting Memory Retrieval

    PubMed Central

    St. Jacques, Peggy L.; Kragel, Philip A.; Rubin, David C.

    2011-01-01

    How do separate neural networks interact to support complex cognitive processes such as remembrance of the personal past? Autobiographical memory (AM) retrieval recruits a consistent pattern of activation that potentially comprises multiple neural networks. However, it is unclear how such large-scale neural networks interact and are modulated by properties of the memory retrieval process. In the present functional MRI (fMRI) study, we combined independent component analysis (ICA) and dynamic causal modeling (DCM) to understand the neural networks supporting AM retrieval. ICA revealed four task-related components consistent with the previous literature: 1) Medial Prefrontal Cortex (PFC) Network, associated with self-referential processes, 2) Medial Temporal Lobe (MTL) Network, associated with memory, 3) Frontoparietal Network, associated with strategic search, and 4) Cingulooperculum Network, associated with goal maintenance. DCM analysis revealed that the medial PFC network drove activation within the system, consistent with the importance of this network to AM retrieval. Additionally, memory accessibility and recollection uniquely altered connectivity between these neural networks. Recollection modulated the influence of the medial PFC on the MTL network during elaboration, suggesting that greater connectivity among subsystems of the default network supports greater re-experience. In contrast, memory accessibility modulated the influence of frontoparietal and MTL networks on the medial PFC network, suggesting that ease of retrieval involves greater fluency among the multiple networks contributing to AM. These results show the integration between neural networks supporting AM retrieval and the modulation of network connectivity by behavior. PMID:21550407

  7. Temporal abnormalities in children with developmental dyscalculia.

    PubMed

    Vicario, Carmelo Mario; Rappo, Gaetano; Pepi, Annamaria; Pavan, Andrea; Martino, Davide

    2012-01-01

    Recent imaging studies have associated Developmental dyscalculia (DD) to structural and functional alterations corresponding Parietal and the Prefrontal cortex (PFC). Since these areas were shown also to be involved in timing abilities, we hypothesized that time processing is abnormal in DD. We compared time processing abilities between 10 children with pure DD (8 years old) and 11 age-matched healthy children. Results show that the DD group underestimated duration of a sub-second scale when asked to perform a time comparison task. The timing abnormality observed in our DD participants is consistent with evidence of a shared fronto-parietal neural network for representing time and quantity.

  8. Electrophysiological signatures of atypical intrinsic brain connectivity networks in autism

    NASA Astrophysics Data System (ADS)

    Shou, Guofa; Mosconi, Matthew W.; Wang, Jun; Ethridge, Lauren E.; Sweeney, John A.; Ding, Lei

    2017-08-01

    Objective. Abnormal local and long-range brain connectivity have been widely reported in autism spectrum disorder (ASD), yet the nature of these abnormalities and their functional relevance at distinct cortical rhythms remains unknown. Investigations of intrinsic connectivity networks (ICNs) and their coherence across whole brain networks hold promise for determining whether patterns of functional connectivity abnormalities vary across frequencies and networks in ASD. In the present study, we aimed to probe atypical intrinsic brain connectivity networks in ASD from resting-state electroencephalography (EEG) data via characterizing the whole brain network. Approach. Connectivity within individual ICNs (measured by spectral power) and between ICNs (measured by coherence) were examined at four canonical frequency bands via a time-frequency independent component analysis on high-density EEG, which were recorded from 20 ASD and 20 typical developing (TD) subjects during an eyes-closed resting state. Main results. Among twelve identified electrophysiological ICNs, individuals with ASD showed hyper-connectivity in individual ICNs and hypo-connectivity between ICNs. Functional connectivity alterations in ASD were more severe in the frontal lobe and the default mode network (DMN) and at low frequency bands. These functional connectivity measures also showed abnormal age-related associations in ICNs related to frontal, temporal and motor regions in ASD. Significance. Our findings suggest that ASD is characterized by the opposite directions of abnormalities (i.e. hypo- and hyper-connectivity) in the hierarchical structure of the whole brain network, with more impairments in the frontal lobe and the DMN at low frequency bands, which are critical for top-down control of sensory systems, as well as for both cognition and social skills.

  9. Altered functional connectivity of the language network in ASD: Role of classical language areas and cerebellum☆

    PubMed Central

    Verly, Marjolein; Verhoeven, Judith; Zink, Inge; Mantini, Dante; Peeters, Ronald; Deprez, Sabine; Emsell, Louise; Boets, Bart; Noens, Ilse; Steyaert, Jean; Lagae, Lieven; De Cock, Paul; Rommel, Nathalie; Sunaert, Stefan

    2014-01-01

    The development of language, social interaction and communicative skills is remarkably different in the child with autism spectrum disorder (ASD). Atypical brain connectivity has frequently been reported in this patient population. However, the neural correlates underlying their disrupted language development and functioning are still poorly understood. Using resting state fMRI, we investigated the functional connectivity properties of the language network in a group of ASD patients with clear comorbid language impairment (ASD-LI; N = 19) and compared them to the language related connectivity properties of 23 age-matched typically developing children. A verb generation task was used to determine language components commonly active in both groups. Eight joint language components were identified and subsequently used as seeds in a resting state analysis. Interestingly, both the interregional and the seed-based whole brain connectivity analysis showed preserved connectivity between the classical intrahemispheric language centers, Wernicke's and Broca's areas. In contrast however, a marked loss of functional connectivity was found between the right cerebellar region and the supratentorial regulatory language areas. Also, the connectivity between the interhemispheric Broca regions and modulatory control dorsolateral prefrontal region was found to be decreased. This disruption of normal modulatory control and automation function by the cerebellum may underlie the abnormal language function in children with ASD-LI. PMID:24567909

  10. Serotonin mediated immunoregulation and neural functions: Complicity in the aetiology of autism spectrum disorders.

    PubMed

    Jaiswal, Preeti; Mohanakumar, Kochupurackal P; Rajamma, Usha

    2015-08-01

    Serotonergic system has long been implicated in the aetiology of autism spectrum disorders (ASD), since platelet hyperserotonemia is consistently observed in a subset of autistic patients, who respond well to selective serotonin reuptake inhibitors. Apart from being a neurotransmitter, serotonin functions as a neurotrophic factor directing brain development and as an immunoregulator modulating immune responses. Serotonin transporter (SERT) regulates serotonin level in lymphoid tissues to ensure its proper functioning in innate and adaptive responses. Immunological molecules such as cytokines in turn regulate the transcription and activity of SERT. Dysregulation of serotonergic system could trigger signalling cascades that affect normal neural-immune interactions culminating in neurodevelopmental and neural connectivity defects precipitating behavioural abnormalities, or the disease phenotypes. Therefore, we suggest that a better understanding of the cross talk between serotonergic genes, immune systems and serotonergic neurotransmission will open wider avenues to develop pharmacological leads for addressing the core ASD behavioural deficits. Copyright © 2015 Elsevier Ltd. All rights reserved.

  11. Automatic diagnosis of abnormal macula in retinal optical coherence tomography images using wavelet-based convolutional neural network features and random forests classifier.

    PubMed

    Rasti, Reza; Mehridehnavi, Alireza; Rabbani, Hossein; Hajizadeh, Fedra

    2018-03-01

    The present research intends to propose a fully automatic algorithm for the classification of three-dimensional (3-D) optical coherence tomography (OCT) scans of patients suffering from abnormal macula from normal candidates. The method proposed does not require any denoising, segmentation, retinal alignment processes to assess the intraretinal layers, as well as abnormalities or lesion structures. To classify abnormal cases from the control group, a two-stage scheme was utilized, which consists of automatic subsystems for adaptive feature learning and diagnostic scoring. In the first stage, a wavelet-based convolutional neural network (CNN) model was introduced and exploited to generate B-scan representative CNN codes in the spatial-frequency domain, and the cumulative features of 3-D volumes were extracted. In the second stage, the presence of abnormalities in 3-D OCTs was scored over the extracted features. Two different retinal SD-OCT datasets are used for evaluation of the algorithm based on the unbiased fivefold cross-validation (CV) approach. The first set constitutes 3-D OCT images of 30 normal subjects and 30 diabetic macular edema (DME) patients captured from the Topcon device. The second publicly available set consists of 45 subjects with a distribution of 15 patients in age-related macular degeneration, DME, and normal classes from the Heidelberg device. With the application of the algorithm on overall OCT volumes and 10 repetitions of the fivefold CV, the proposed scheme obtained an average precision of 99.33% on dataset1 as a two-class classification problem and 98.67% on dataset2 as a three-class classification task. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

  12. Connectomics and graph theory analyses: Novel insights into network abnormalities in epilepsy.

    PubMed

    Gleichgerrcht, Ezequiel; Kocher, Madison; Bonilha, Leonardo

    2015-11-01

    The assessment of neural networks in epilepsy has become increasingly relevant in the context of translational research, given that localized forms of epilepsy are more likely to be related to abnormal function within specific brain networks, as opposed to isolated focal brain pathology. It is notable that variability in clinical outcomes from epilepsy treatment may be a reflection of individual patterns of network abnormalities. As such, network endophenotypes may be important biomarkers for the diagnosis and treatment of epilepsy. Despite its exceptional potential, measuring abnormal networks in translational research has been thus far constrained by methodologic limitations. Fortunately, recent advancements in neuroscience, particularly in the field of connectomics, permit a detailed assessment of network organization, dynamics, and function at an individual level. Data from the personal connectome can be assessed using principled forms of network analyses based on graph theory, which may disclose patterns of organization that are prone to abnormal dynamics and epileptogenesis. Although the field of connectomics is relatively new, there is already a rapidly growing body of evidence to suggest that it can elucidate several important and fundamental aspects of abnormal networks to epilepsy. In this article, we provide a review of the emerging evidence from connectomics research regarding neural network architecture, dynamics, and function related to epilepsy. We discuss how connectomics may bring together pathophysiologic hypotheses from conceptual and basic models of epilepsy and in vivo biomarkers for clinical translational research. By providing neural network information unique to each individual, the field of connectomics may help to elucidate variability in clinical outcomes and open opportunities for personalized medicine approaches to epilepsy. Connectomics involves complex and rich data from each subject, thus collaborative efforts to enable the

  13. A hypercube compact neural network

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Rostykus, P.L.; Somani, A.K.

    1988-09-01

    A major problem facing implementation of neural networks is the connection problem. One popular tradeoff is to remove connections. Random disconnection severely degrades the capabilities. The hypercube based Compact Neural Network (CNN) has structured architecture combined with a rearrangement of the memory vectors gives a larger input space and better degradation than a cost equivalent network with more connections. The CNNs are based on a Hopfield network. The changes from the Hopfield net include states of -1 and +1 and when a node was evaluated to 0, it was not biased either positive or negative, instead it resumed its previousmore » state. L = PEs, N = memories and t/sub ij/s is the weights between i and j.« less

  14. Multiprocessor Neural Network in Healthcare.

    PubMed

    Godó, Zoltán Attila; Kiss, Gábor; Kocsis, Dénes

    2015-01-01

    A possible way of creating a multiprocessor artificial neural network is by the use of microcontrollers. The RISC processors' high performance and the large number of I/O ports mean they are greatly suitable for creating such a system. During our research, we wanted to see if it is possible to efficiently create interaction between the artifical neural network and the natural nervous system. To achieve as much analogy to the living nervous system as possible, we created a frequency-modulated analog connection between the units. Our system is connected to the living nervous system through 128 microelectrodes. Two-way communication is provided through A/D transformation, which is even capable of testing psychopharmacons. The microcontroller-based analog artificial neural network can play a great role in medical singal processing, such as ECG, EEG etc.

  15. Structural and behavioral correlates of abnormal encoding of money value in the sensorimotor striatum in cocaine addiction

    PubMed Central

    Konova, Anna B.; Moeller, Scott J.; Tomasi, Dardo; Parvaz, Muhammad A.; Alia-Klein, Nelly; Volkow, Nora D.; Goldstein, Rita Z.

    2012-01-01

    Abnormalities in frontostriatal systems are thought to be central to the pathophysiology of addiction, and may underlie maladaptive processing of the highly generalizable reinforcer, money. Although abnormal frontostriatal structure and function have been observed in individuals addicted to cocaine, it is less clear how individual variability in brain structure is associated with brain function to influence behavior. Our objective was to examine frontostriatal structure and neural processing of money value in chronic cocaine users and closely matched healthy controls. A reward task that manipulated different levels of money was used to isolate neural activity associated with money value. Gray matter volume measures were used to assess frontostriatal structure. Our results indicated that cocaine users had an abnormal money value signal in the sensorimotor striatum (right putamen/globus pallidus) which was negatively associated with accuracy adjustments to money and was more pronounced in individuals with more severe use. In parallel, group differences were also observed in both function and gray matter volume of the ventromedial prefrontal cortex; in the cocaine users, the former was directly associated with response to money in the striatum. These results provide strong evidence for abnormalities in the neural mechanisms of valuation in addiction and link these functional abnormalities with deficits in brain structure. In addition, as value signals represent acquired associations, their abnormal processing in the sensorimotor striatum, a region centrally implicated in habit formation, could signal disadvantageous associative learning in cocaine addiction. PMID:22775285

  16. The Neural Signature of Subliminal Visuomotor Priming: Brain Activity and Functional Connectivity Profiles.

    PubMed

    Ulrich, Martin; Kiefer, Markus

    2016-06-01

    Unconscious visuomotor priming defined as the advantage in reaction time (RT) or accuracy for target shapes mapped to the same (congruent condition) when compared with a different (incongruent condition) motor response as a preceding subliminally presented prime shape has been shown to modulate activity within a visuomotor network comprised of parietal and frontal motor areas in previous functional magnetic resonance imaging (fMRI) studies. The present fMRI study investigated whether, in addition to changes in brain activity, unconscious visuomotor priming results in a modulation of functional connectivity profiles. Activity associated with congruent compared with incongruent trials was lower in the bilateral inferior and medial superior frontal gyri, in the inferior parietal lobules, and in the right caudate nucleus and adjacent portions of the thalamus. Functional connectivity increased under congruent relative to incongruent conditions between ventral visual stream areas (e.g., calcarine, fusiform, and lingual gyri), the precentral gyrus, the supplementary motor area, posterior parietal areas, the inferior frontal gyrus, and the caudate nucleus. Our findings suggest that an increase in coupling between visuomotor regions, reflecting higher efficiency of processing, is an important neural mechanism underlying unconscious visuomotor priming, in addition to changes in the magnitude of activation. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  17. Elimination of spiral waves in a locally connected chaotic neural network by a dynamic phase space constraint.

    PubMed

    Li, Yang; Oku, Makito; He, Guoguang; Aihara, Kazuyuki

    2017-04-01

    In this study, a method is proposed that eliminates spiral waves in a locally connected chaotic neural network (CNN) under some simplified conditions, using a dynamic phase space constraint (DPSC) as a control method. In this method, a control signal is constructed from the feedback internal states of the neurons to detect phase singularities based on their amplitude reduction, before modulating a threshold value to truncate the refractory internal states of the neurons and terminate the spirals. Simulations showed that with appropriate parameter settings, the network was directed from a spiral wave state into either a plane wave (PW) state or a synchronized oscillation (SO) state, where the control vanished automatically and left the original CNN model unaltered. Each type of state had a characteristic oscillation frequency, where spiral wave states had the highest, and the intra-control dynamics was dominated by low-frequency components, thereby indicating slow adjustments to the state variables. In addition, the PW-inducing and SO-inducing control processes were distinct, where the former generally had longer durations but smaller average proportions of affected neurons in the network. Furthermore, variations in the control parameter allowed partial selectivity of the control results, which were accompanied by modulation of the control processes. The results of this study broaden the applicability of DPSC to chaos control and they may also facilitate the utilization of locally connected CNNs in memory retrieval and the exploration of traveling wave dynamics in biological neural networks. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. Abnormal dopaminergic modulation of striato-cortical networks underlies levodopa-induced dyskinesias in humans

    PubMed Central

    Haagensen, Brian N.; Christensen, Mark S.; Madsen, Kristoffer H.; Rowe, James B.; Løkkegaard, Annemette; Siebner, Hartwig R.

    2015-01-01

    Dopaminergic signalling in the striatum contributes to reinforcement of actions and motivational enhancement of motor vigour. Parkinson's disease leads to progressive dopaminergic denervation of the striatum, impairing the function of cortico-basal ganglia networks. While levodopa therapy alleviates basal ganglia dysfunction in Parkinson's disease, it often elicits involuntary movements, referred to as levodopa-induced peak-of-dose dyskinesias. Here, we used a novel pharmacodynamic neuroimaging approach to identify the changes in cortico-basal ganglia connectivity that herald the emergence of levodopa-induced dyskinesias. Twenty-six patients with Parkinson's disease (age range: 51–84 years; 11 females) received a single dose of levodopa and then performed a task in which they had to produce or suppress a movement in response to visual cues. Task-related activity was continuously mapped with functional magnetic resonance imaging. Dynamic causal modelling was applied to assess levodopa-induced modulation of effective connectivity between the pre-supplementary motor area, primary motor cortex and putamen when patients suppressed a motor response. Bayesian model selection revealed that patients who later developed levodopa-induced dyskinesias, but not patients without dyskinesias, showed a linear increase in connectivity between the putamen and primary motor cortex after levodopa intake during movement suppression. Individual dyskinesia severity was predicted by levodopa-induced modulation of striato-cortical feedback connections from putamen to the pre-supplementary motor area (Pcorrected = 0.020) and primary motor cortex (Pcorrected = 0.044), but not feed-forward connections from the cortex to the putamen. Our results identify for the first time, aberrant dopaminergic modulation of striatal-cortical connectivity as a neural signature of levodopa-induced dyskinesias in humans. We argue that excessive striato-cortical connectivity in response to levodopa produces an

  19. Dynamic Reorganization of Functional Connectivity Reveals Abnormal Temporal Efficiency in Schizophrenia.

    PubMed

    Sun, Yu; Collinson, Simon L; Suckling, John; Sim, Kang

    2018-06-07

    Emerging evidence suggests that schizophrenia is associated with brain dysconnectivity. Nonetheless, the implicit assumption of stationary functional connectivity (FC) adopted in most previous resting-state functional magnetic resonance imaging (fMRI) studies raises an open question of schizophrenia-related aberrations in dynamic properties of resting-state FC. This study introduces an empirical method to examine the dynamic functional dysconnectivity in patients with schizophrenia. Temporal brain networks were estimated from resting-state fMRI of 2 independent datasets (patients/controls = 18/19 and 53/57 for self-recorded dataset and a publicly available replication dataset, respectively) by the correlation of sliding time-windowed time courses among regions of a predefined atlas. Through the newly introduced temporal efficiency approach and temporal random network models, we examined, for the first time, the 3D spatiotemporal architecture of the temporal brain network. We found that although prominent temporal small-world properties were revealed in both groups, temporal brain networks of patients with schizophrenia in both datasets showed a significantly higher temporal global efficiency, which cannot be simply attributable to head motion and sampling error. Specifically, we found localized changes of temporal nodal properties in the left frontal, right medial parietal, and subcortical areas that were associated with clinical features of schizophrenia. Our findings demonstrate that altered dynamic FC may underlie abnormal brain function and clinical symptoms observed in schizophrenia. Moreover, we provide new evidence to extend the dysconnectivity hypothesis in schizophrenia from static to dynamic brain network and highlight the potential of aberrant brain dynamic FC in unraveling the pathophysiologic mechanisms of the disease.

  20. Modeling, control, and simulation of grid connected intelligent hybrid battery/photovoltaic system using new hybrid fuzzy-neural method.

    PubMed

    Rezvani, Alireza; Khalili, Abbas; Mazareie, Alireza; Gandomkar, Majid

    2016-07-01

    Nowadays, photovoltaic (PV) generation is growing increasingly fast as a renewable energy source. Nevertheless, the drawback of the PV system is its dependence on weather conditions. Therefore, battery energy storage (BES) can be considered to assist for a stable and reliable output from PV generation system for loads and improve the dynamic performance of the whole generation system in grid connected mode. In this paper, a novel topology of intelligent hybrid generation systems with PV and BES in a DC-coupled structure is presented. Each photovoltaic cell has a specific point named maximum power point on its operational curve (i.e. current-voltage or power-voltage curve) in which it can generate maximum power. Irradiance and temperature changes affect these operational curves. Therefore, the nonlinear characteristic of maximum power point to environment has caused to development of different maximum power point tracking techniques. In order to capture the maximum power point (MPP), a hybrid fuzzy-neural maximum power point tracking (MPPT) method is applied in the PV system. Obtained results represent the effectiveness and superiority of the proposed method, and the average tracking efficiency of the hybrid fuzzy-neural is incremented by approximately two percentage points in comparison to the conventional methods. It has the advantages of robustness, fast response and good performance. A detailed mathematical model and a control approach of a three-phase grid-connected intelligent hybrid system have been proposed using Matlab/Simulink. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  1. Fully Connected Cascade Artificial Neural Network Architecture for Attention Deficit Hyperactivity Disorder Classification From Functional Magnetic Resonance Imaging Data.

    PubMed

    Deshpande, Gopikrishna; Wang, Peng; Rangaprakash, D; Wilamowski, Bogdan

    2015-12-01

    Automated recognition and classification of brain diseases are of tremendous value to society. Attention deficit hyperactivity disorder (ADHD) is a diverse spectrum disorder whose diagnosis is based on behavior and hence will benefit from classification utilizing objective neuroimaging measures. Toward this end, an international competition was conducted for classifying ADHD using functional magnetic resonance imaging data acquired from multiple sites worldwide. Here, we consider the data from this competition as an example to illustrate the utility of fully connected cascade (FCC) artificial neural network (ANN) architecture for performing classification. We employed various directional and nondirectional brain connectivity-based methods to extract discriminative features which gave better classification accuracy compared to raw data. Our accuracy for distinguishing ADHD from healthy subjects was close to 90% and between the ADHD subtypes was close to 95%. Further, we show that, if properly used, FCC ANN performs very well compared to other classifiers such as support vector machines in terms of accuracy, irrespective of the feature used. Finally, the most discriminative connectivity features provided insights about the pathophysiology of ADHD and showed reduced and altered connectivity involving the left orbitofrontal cortex and various cerebellar regions in ADHD.

  2. Microstructural and functional connectivity in the developing preterm brain

    PubMed Central

    Lubsen, Julia; Vohr, Betty; Myers, Eliza; Hampson, Michelle; Lacadie, Cheryl; Schneider, Karen C.; Katz, Karol H.; Constable, R. Todd; Ment, Laura R.

    2011-01-01

    Prematurely born children are at increased risk for cognitive deficits, but the neurobiological basis of these findings remains poorly understood. Since variations in neural circuitry may influence performance on cognitive tasks, recent investigations have explored the impact of preterm birth on connectivity in the developing brain. Diffusion tensor imaging studies demonstrate widespread alterations in fractional anisotropy, a measure of axonal integrity and microstructural connectivity, throughout the developing preterm brain. Functional connectivity studies report that preterm neonates, children and adolescents exhibit alterations in both resting state and task-based connectivity when compared to term control subjects. Taken together, these data suggest that neurodevelopmental impairment following preterm birth may represent a disease of neural connectivity. PMID:21255705

  3. Mice with Tak1 deficiency in neural crest lineage exhibit cleft palate associated with abnormal tongue development.

    PubMed

    Song, Zhongchen; Liu, Chao; Iwata, Junichi; Gu, Shuping; Suzuki, Akiko; Sun, Cheng; He, Wei; Shu, Rong; Li, Lu; Chai, Yang; Chen, YiPing

    2013-04-12

    Cleft palate represents one of the most common congenital birth defects in humans. TGFβ signaling, which is mediated by Smad-dependent and Smad-independent pathways, plays a crucial role in regulating craniofacial development and patterning, particularly in palate development. However, it remains largely unknown whether the Smad-independent pathway contributes to TGFβ signaling function during palatogenesis. In this study, we investigated the function of TGFβ activated kinase 1 (Tak1), a key regulator of Smad-independent TGFβ signaling in palate development. We show that Tak1 protein is expressed in both the epithelium and mesenchyme of the developing palatal shelves. Whereas deletion of Tak1 in the palatal epithelium or mesenchyme did not give rise to a cleft palate defect, inactivation of Tak1 in the neural crest lineage using the Wnt1-Cre transgenic allele resulted in failed palate elevation and subsequently the cleft palate formation. The failure in palate elevation in Wnt1-Cre;Tak1(F/F) mice results from a malformed tongue and micrognathia, resembling human Pierre Robin sequence cleft of the secondary palate. We found that the abnormal tongue development is associated with Fgf10 overexpression in the neural crest-derived tongue tissue. The failed palate elevation and cleft palate were recapitulated in an Fgf10-overexpressing mouse model. The repressive effect of the Tak1-mediated noncanonical TGFβ signaling on Fgf10 expression was further confirmed by inhibition of p38, a downstream kinase of Tak1, in the primary cell culture of developing tongue. Tak1 thus functions to regulate tongue development by controlling Fgf10 expression and could represent a candidate gene for mutation in human PRS clefting.

  4. Neural alterations of fronto-striatal circuitry during reward anticipation in euthymic bipolar disorder.

    PubMed

    Schreiter, S; Spengler, S; Willert, A; Mohnke, S; Herold, D; Erk, S; Romanczuk-Seiferth, N; Quinlivan, E; Hindi-Attar, C; Banzhaf, C; Wackerhagen, C; Romund, L; Garbusow, M; Stamm, T; Heinz, A; Walter, H; Bermpohl, F

    2016-11-01

    Bipolar disorder (BD), with the hallmark symptoms of elevated and depressed mood, is thought to be characterized by underlying alterations in reward-processing networks. However, to date the neural circuitry underlying abnormal responses during reward processing in BD remains largely unexplored. The aim of this study was to investigate whether euthymic BD is characterized by aberrant ventral striatal (VS) activation patterns and altered connectivity with the prefrontal cortex in response to monetary gains and losses. During functional magnetic resonance imaging 20 euthymic BD patients and 20 age-, gender- and intelligence quotient-matched healthy controls completed a monetary incentive delay paradigm, to examine neural processing of reward and loss anticipation. A priori defined regions of interest (ROIs) included the VS and the anterior prefrontal cortex (aPFC). Psychophysiological interactions (PPIs) between these ROIs were estimated and tested for group differences for reward and loss anticipation separately. BD participants, relative to healthy controls, displayed decreased activation selectively in the left and right VS during anticipation of reward, but not during loss anticipation. PPI analyses showed decreased functional connectivity between the left VS and aPFC in BD patients compared with healthy controls during reward anticipation. This is the first study showing decreased VS activity and aberrant connectivity in the reward-processing circuitry in euthymic, medicated BD patients during reward anticipation. Our findings contrast with research supporting a reward hypersensitivity model of BD, and add to the body of literature suggesting that blunted activation of reward processing circuits may be a vulnerability factor for mood disorders.

  5. Dysfunctional Autism Risk Genes Cause Circuit-Specific Connectivity Deficits With Distinct Developmental Trajectories.

    PubMed

    Zerbi, Valerio; Ielacqua, Giovanna D; Markicevic, Marija; Haberl, Matthias Georg; Ellisman, Mark H; A-Bhaskaran, Arjun; Frick, Andreas; Rudin, Markus; Wenderoth, Nicole

    2018-07-01

    Autism spectrum disorders (ASD) are a set of complex neurodevelopmental disorders for which there is currently no targeted therapeutic approach. It is thought that alterations of genes regulating migration and synapse formation during development affect neural circuit formation and result in aberrant connectivity within distinct circuits that underlie abnormal behaviors. However, it is unknown whether deviant developmental trajectories are circuit-specific for a given autism risk-gene. We used MRI to probe changes in functional and structural connectivity from childhood to adulthood in Fragile-X (Fmr1-/y) and contactin-associated (CNTNAP2-/-) knockout mice. Young Fmr1-/y mice (30 days postnatal) presented with a robust hypoconnectivity phenotype in corticocortico and corticostriatal circuits in areas associated with sensory information processing, which was maintained until adulthood. Conversely, only small differences in hippocampal and striatal areas were present during early postnatal development in CNTNAP2-/- mice, while major connectivity deficits in prefrontal and limbic pathways developed between adolescence and adulthood. These findings are supported by viral tracing and electron micrograph approaches and define 2 clearly distinct connectivity endophenotypes within the autism spectrum. We conclude that the genetic background of ASD strongly influences which circuits are most affected, the nature of the phenotype, and the developmental time course of the associated changes.

  6. Reduced prefrontal connectivity in psychopathy.

    PubMed

    Motzkin, Julian C; Newman, Joseph P; Kiehl, Kent A; Koenigs, Michael

    2011-11-30

    Linking psychopathy to a specific brain abnormality could have significant clinical, legal, and scientific implications. Theories on the neurobiological basis of the disorder typically propose dysfunction in a circuit involving ventromedial prefrontal cortex (vmPFC). However, to date there is limited brain imaging data to directly test whether psychopathy may indeed be associated with any structural or functional abnormality within this brain area. In this study, we employ two complementary imaging techniques to assess the structural and functional connectivity of vmPFC in psychopathic and non-psychopathic criminals. Using diffusion tensor imaging, we show that psychopathy is associated with reduced structural integrity in the right uncinate fasciculus, the primary white matter connection between vmPFC and anterior temporal lobe. Using functional magnetic resonance imaging, we show that psychopathy is associated with reduced functional connectivity between vmPFC and amygdala as well as between vmPFC and medial parietal cortex. Together, these data converge to implicate diminished vmPFC connectivity as a characteristic neurobiological feature of psychopathy.

  7. Structural and behavioral correlates of abnormal encoding of money value in the sensorimotor striatum in cocaine addiction.

    PubMed

    Konova, Anna B; Moeller, Scott J; Tomasi, Dardo; Parvaz, Muhammad A; Alia-Klein, Nelly; Volkow, Nora D; Goldstein, Rita Z

    2012-10-01

    Abnormalities in frontostriatal systems are thought to be central to the pathophysiology of addiction, and may underlie the maladaptive processing of the highly generalizable reinforcer, money. Although abnormal frontostriatal structure and function have been observed in individuals addicted to cocaine, it is less clear how individual variability in brain structure is associated with brain function to influence behavior. Our objective was to examine frontostriatal structure and neural processing of money value in chronic cocaine users and closely matched healthy controls. A reward task that manipulated different levels of money was used to isolate neural activity associated with money value. Gray matter volume measures were used to assess frontostriatal structure. Our results indicated that cocaine users had an abnormal money value signal in the sensorimotor striatum (right putamen/globus pallidus) that was negatively associated with accuracy adjustments to money and was more pronounced in individuals with more severe use. In parallel, group differences were also observed in both the function and gray matter volume of the ventromedial prefrontal cortex; in the cocaine users, the former was directly associated with response to money in the striatum. These results provide strong evidence for abnormalities in the neural mechanisms of valuation in addiction and link these functional abnormalities with deficits in brain structure. In addition, as value signals represent acquired associations, their abnormal processing in the sensorimotor striatum, a region centrally implicated in habit formation, could signal disadvantageous associative learning in cocaine addiction. © 2012 Published 2012. This article is a US Government work and is in the public domain in the USA.

  8. Neural system prediction and identification challenge.

    PubMed

    Vlachos, Ioannis; Zaytsev, Yury V; Spreizer, Sebastian; Aertsen, Ad; Kumar, Arvind

    2013-01-01

    Can we infer the function of a biological neural network (BNN) if we know the connectivity and activity of all its constituent neurons?This question is at the core of neuroscience and, accordingly, various methods have been developed to record the activity and connectivity of as many neurons as possible. Surprisingly, there is no theoretical or computational demonstration that neuronal activity and connectivity are indeed sufficient to infer the function of a BNN. Therefore, we pose the Neural Systems Identification and Prediction Challenge (nuSPIC). We provide the connectivity and activity of all neurons and invite participants (1) to infer the functions implemented (hard-wired) in spiking neural networks (SNNs) by stimulating and recording the activity of neurons and, (2) to implement predefined mathematical/biological functions using SNNs. The nuSPICs can be accessed via a web-interface to the NEST simulator and the user is not required to know any specific programming language. Furthermore, the nuSPICs can be used as a teaching tool. Finally, nuSPICs use the crowd-sourcing model to address scientific issues. With this computational approach we aim to identify which functions can be inferred by systematic recordings of neuronal activity and connectivity. In addition, nuSPICs will help the design and application of new experimental paradigms based on the structure of the SNN and the presumed function which is to be discovered.

  9. Neural system prediction and identification challenge

    PubMed Central

    Vlachos, Ioannis; Zaytsev, Yury V.; Spreizer, Sebastian; Aertsen, Ad; Kumar, Arvind

    2013-01-01

    Can we infer the function of a biological neural network (BNN) if we know the connectivity and activity of all its constituent neurons?This question is at the core of neuroscience and, accordingly, various methods have been developed to record the activity and connectivity of as many neurons as possible. Surprisingly, there is no theoretical or computational demonstration that neuronal activity and connectivity are indeed sufficient to infer the function of a BNN. Therefore, we pose the Neural Systems Identification and Prediction Challenge (nuSPIC). We provide the connectivity and activity of all neurons and invite participants (1) to infer the functions implemented (hard-wired) in spiking neural networks (SNNs) by stimulating and recording the activity of neurons and, (2) to implement predefined mathematical/biological functions using SNNs. The nuSPICs can be accessed via a web-interface to the NEST simulator and the user is not required to know any specific programming language. Furthermore, the nuSPICs can be used as a teaching tool. Finally, nuSPICs use the crowd-sourcing model to address scientific issues. With this computational approach we aim to identify which functions can be inferred by systematic recordings of neuronal activity and connectivity. In addition, nuSPICs will help the design and application of new experimental paradigms based on the structure of the SNN and the presumed function which is to be discovered. PMID:24399966

  10. Decreased Connectivity and Cerebellar Activity in Autism during Motor Task Performance

    ERIC Educational Resources Information Center

    Mostofsky, Stewart H.; Powell, Stephanie K.; Simmonds, Daniel J.; Goldberg, Melissa C.; Caffo, Brian; Pekar, James J.

    2009-01-01

    Although motor deficits are common in autism, the neural correlates underlying the disruption of even basic motor execution are unknown. Motor deficits may be some of the earliest identifiable signs of abnormal development and increased understanding of their neural underpinnings may provide insight into autism-associated differences in parallel…

  11. Functional Connectivity Bias in the Prefrontal Cortex of Psychopaths.

    PubMed

    Contreras-Rodríguez, Oren; Pujol, Jesus; Batalla, Iolanda; Harrison, Ben J; Soriano-Mas, Carles; Deus, Joan; López-Solà, Marina; Macià, Dídac; Pera, Vanessa; Hernández-Ribas, Rosa; Pifarré, Josep; Menchón, José M; Cardoner, Narcís

    2015-11-01

    Psychopathy is characterized by a distinctive interpersonal style that combines callous-unemotional traits with inflexible and antisocial behavior. Traditional emotion-based perspectives link emotional impairment mostly to alterations in amygdala-ventromedial frontal circuits. However, these models alone cannot explain why individuals with psychopathy can regularly benefit from emotional information when placed on their focus of attention and why they are more resistant to interference from nonaffective contextual cues. The present study aimed to identify abnormal or distinctive functional links between and within emotional and cognitive brain systems in the psychopathic brain to characterize further the neural bases of psychopathy. High-resolution anatomic magnetic resonance imaging with a functional sequence acquired in the resting state was used to assess 22 subjects with psychopathy and 22 control subjects. Anatomic and functional connectivity alterations were investigated first using a whole-brain analysis. Brain regions showing overlapping anatomic and functional changes were examined further using seed-based functional connectivity mapping. Subjects with psychopathy showed gray matter reduction involving prefrontal cortex, paralimbic, and limbic structures. Anatomic changes overlapped with areas showing increased degree of functional connectivity at the medial-dorsal frontal cortex. Subsequent functional seed-based connectivity mapping revealed a pattern of reduced functional connectivity of prefrontal areas with limbic-paralimbic structures and enhanced connectivity within the dorsal frontal lobe in subjects with psychopathy. Our results suggest that a weakened link between emotional and cognitive domains in the psychopathic brain may combine with enhanced functional connections within frontal executive areas. The identified functional alterations are discussed in the context of potential contributors to the inflexible behavior displayed by individuals with

  12. Meis2 is essential for cranial and cardiac neural crest development.

    PubMed

    Machon, Ondrej; Masek, Jan; Machonova, Olga; Krauss, Stefan; Kozmik, Zbynek

    2015-11-06

    TALE-class homeodomain transcription factors Meis and Pbx play important roles in formation of the embryonic brain, eye, heart, cartilage or hematopoiesis. Loss-of-function studies of Pbx1, 2 and 3 and Meis1 documented specific functions in embryogenesis, however, functional studies of Meis2 in mouse are still missing. We have generated a conditional allele of Meis2 in mice and shown that systemic inactivation of the Meis2 gene results in lethality by the embryonic day 14 that is accompanied with hemorrhaging. We show that neural crest cells express Meis2 and Meis2-defficient embryos display defects in tissues that are derived from the neural crest, such as an abnormal heart outflow tract with the persistent truncus arteriosus and abnormal cranial nerves. The importance of Meis2 for neural crest cells is further confirmed by means of conditional inactivation of Meis2 using crest-specific AP2α-IRES-Cre mouse. Conditional mutants display perturbed development of the craniofacial skeleton with severe anomalies in cranial bones and cartilages, heart and cranial nerve abnormalities. Meis2-null mice are embryonic lethal. Our results reveal a critical role of Meis2 during cranial and cardiac neural crest cells development in mouse.

  13. Models of Innate Neural Attractors and Their Applications for Neural Information Processing

    PubMed Central

    Solovyeva, Ksenia P.; Karandashev, Iakov M.; Zhavoronkov, Alex; Dunin-Barkowski, Witali L.

    2016-01-01

    In this work we reveal and explore a new class of attractor neural networks, based on inborn connections provided by model molecular markers, the molecular marker based attractor neural networks (MMBANN). Each set of markers has a metric, which is used to make connections between neurons containing the markers. We have explored conditions for the existence of attractor states, critical relations between their parameters and the spectrum of single neuron models, which can implement the MMBANN. Besides, we describe functional models (perceptron and SOM), which obtain significant advantages over the traditional implementation of these models, while using MMBANN. In particular, a perceptron, based on MMBANN, gets specificity gain in orders of error probabilities values, MMBANN SOM obtains real neurophysiological meaning, the number of possible grandma cells increases 1000-fold with MMBANN. MMBANN have sets of attractor states, which can serve as finite grids for representation of variables in computations. These grids may show dimensions of d = 0, 1, 2,…. We work with static and dynamic attractor neural networks of the dimensions d = 0 and 1. We also argue that the number of dimensions which can be represented by attractors of activities of neural networks with the number of elements N = 104 does not exceed 8. PMID:26778977

  14. Abnormal frontoparietal synaptic gain mediating the P300 in patients with psychotic disorder and their unaffected relatives.

    PubMed

    Díez, Álvaro; Ranlund, Siri; Pinotsis, Dimitris; Calafato, Stella; Shaikh, Madiha; Hall, Mei-Hua; Walshe, Muriel; Nevado, Ángel; Friston, Karl J; Adams, Rick A; Bramon, Elvira

    2017-06-01

    The "dysconnection hypothesis" of psychosis suggests that a disruption of functional integration underlies cognitive deficits and clinical symptoms. Impairments in the P300 potential are well documented in psychosis. Intrinsic (self-)connectivity in a frontoparietal cortical hierarchy during a P300 experiment was investigated. Dynamic Causal Modeling was used to estimate how evoked activity results from the dynamics of coupled neural populations and how neural coupling changes with the experimental factors. Twenty-four patients with psychotic disorder, twenty-four unaffected relatives, and twenty-five controls underwent EEG recordings during an auditory oddball paradigm. Sixteen frontoparietal network models (including primary auditory, superior parietal, and superior frontal sources) were analyzed and an optimal model of neural coupling, explaining diagnosis and genetic risk effects, as well as their interactions with task condition were identified. The winning model included changes in connectivity at all three hierarchical levels. Patients showed decreased self-inhibition-that is, increased cortical excitability-in left superior frontal gyrus across task conditions, compared with unaffected participants. Relatives had similar increases in excitability in left superior frontal and right superior parietal sources, and a reversal of the normal synaptic gain changes in response to targets relative to standard tones. It was confirmed that both subjects with psychotic disorder and their relatives show a context-independent loss of synaptic gain control at the highest hierarchy levels. The relatives also showed abnormal gain modulation responses to task-relevant stimuli. These may be caused by NMDA-receptor and/or GABAergic pathologies that change the excitability of superficial pyramidal cells and may be a potential biological marker for psychosis. Hum Brain Mapp 38:3262-3276, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  15. Abnormal fronto-limbic engagement in incarcerated stimulant users during moral processing.

    PubMed

    Fede, Samantha J; Harenski, Carla L; Schaich Borg, Jana; Sinnott-Armstrong, Walter; Rao, Vikram; Caldwell, Brendan M; Nyalakanti, Prashanth K; Koenigs, Michael R; Decety, Jean; Calhoun, Vince D; Kiehl, Kent A

    2016-09-01

    Stimulant use is a significant and prevalent problem, particularly in criminal populations. Previous studies found that cocaine and methamphetamine use is related to impairment in identifying emotions and empathy. Stimulant users also have abnormal neural structure and function of the ventromedial prefrontal cortex (vmPFC), amygdala, and anterior (ACC) and posterior cingulate (PCC), regions implicated in moral decision-making. However, no research has studied the neural correlates of stimulant use and explicit moral processing in an incarcerated population. Here, we examine how stimulant use affects sociomoral processing that might contribute to antisocial behavior. We predicted that vmPFC, amygdala, PCC, and ACC would show abnormal neural response during a moral processing task in incarcerated methamphetamine and cocaine users. Incarcerated adult males (N = 211) were scanned with a mobile MRI system while completing a moral decision-making task. Lifetime drug use was assessed. Neural responses during moral processing were compared between users and non-users. The relationship between duration of use and neural function was also examined. Incarcerated stimulant users showed less amygdala engagement than non-users during moral processing. Duration of stimulant use was negatively associated with activity in ACC and positively associated with vmPFC response during moral processing. These results suggest a dynamic pattern of fronto-limbic moral processing related to stimulant use with deficits in both central motive and cognitive integration elements of biological moral processes theory. This increases our understanding of how drug use relates to moral processing in the brain in an ultra-high-risk population.

  16. Resting-State Functional Connectivity in the Human Connectome Project: Current Status and Relevance to Understanding Psychopathology.

    PubMed

    Barch, Deanna M

    A key tenet of modern psychiatry is that psychiatric disorders arise from abnormalities in brain circuits that support human behavior. Our ability to examine hypotheses around circuit-level abnormalities in psychiatric disorders has been made possible by advances in human neuroimaging technologies. These advances have provided the basis for recent efforts to develop a more complex understanding of the function of brain circuits in health and of their relationship to behavior-providing, in turn, a foundation for our understanding of how disruptions in such circuits contribute to the development of psychiatric disorders. This review focuses on the use of resting-state functional connectivity MRI to assess brain circuits, on the advances generated by the Human Connectome Project, and on how these advances potentially contribute to understanding neural circuit dysfunction in psychopathology. The review gives particular attention to the methods developed by the Human Connectome Project that may be especially relevant to studies of psychopathology; it outlines some of the key findings about what constitutes a brain region; and it highlights new information about the nature and stability of brain circuits. Some of the Human Connectome Project's new findings particularly relevant to psychopathology-about neural circuits and their relationships to behavior-are also presented. The review ends by discussing the extension of Human Connectome Project methods across the lifespan and into manifest illness. Potential treatment implications are also considered.

  17. Gamma band oscillations: a key to understanding schizophrenia symptoms and neural circuit abnormalities.

    PubMed

    McNally, James M; McCarley, Robert W

    2016-05-01

    We review our current understanding of abnormal γ band oscillations in schizophrenia, their association with symptoms and the underlying cortical circuit abnormality, with a particular focus on the role of fast-spiking parvalbumin gamma-aminobutyric acid (GABA) neurons in the disease state. Clinical electrophysiological studies of schizophrenia patients and pharmacological models of the disorder show an increase in spontaneous γ band activity (not stimulus-evoked) measures. These findings provide a crucial link between preclinical and clinical work examining the role of γ band activity in schizophrenia. MRI-based experiments measuring cortical GABA provides evidence supporting impaired GABAergic neurotransmission in schizophrenia patients, which is correlated with γ band activity level. Several studies suggest that stimulation of the cortical circuitry, directly or via subcortical structures, has the potential to modulate cortical γ activity, and improve cognitive function. Abnormal γ band activity is observed in patients with schizophrenia and disease models in animals, and is suggested to underlie the psychosis and cognitive/perceptual deficits. Convergent evidence from both clinical and preclinical studies suggest the central factor in γ band abnormalities is impaired GABAergic neurotransmission, particularly in a subclass of neurons which express parvalbumin. Rescue of γ band abnormalities presents an intriguing option for therapeutic intervention.

  18. Gamma band oscillations: a key to understanding schizophrenia symptoms and neural circuit abnormalities

    PubMed Central

    McNally, James M.; McCarley, Robert W.

    2016-01-01

    Purpose of review We review our current understanding of abnormal γ band oscillations in schizophrenia, their association with symptoms and the underlying cortical circuit abnormality, with a particular focus on the role of fast-spiking parvalbumin gamma-aminobutyric acid (GABA) neurons in the disease state. Recent findings Clinical electrophysiological studies of schizophrenia patients and pharmacological models of the disorder show an increase in spontaneous γ band activity (not stimulus-evoked) measures. These findings provide a crucial link between preclinical and clinical work examining the role of γ band activity in schizophrenia. MRI-based experiments measuring cortical GABA provides evidence supporting impaired GABAergic neurotransmission in schizophrenia patients, which is correlated with γ band activity level. Several studies suggest that stimulation of the cortical circuitry, directly or via subcortical structures, has the potential to modulate cortical γ activity, and improve cognitive function. Summary Abnormal γ band activity is observed in patients with schizophrenia and disease models in animals, and is suggested to underlie the psychosis and cognitive/perceptual deficits. Convergent evidence from both clinical and preclinical studies suggest the central factor in γ band abnormalities is impaired GABAergic neurotransmission, particularly in a subclass of neurons which express parvalbumin. Rescue of γ band abnormalities presents an intriguing option for therapeutic intervention. PMID:26900672

  19. Computer-assisted cervical cancer screening using neural networks.

    PubMed

    Mango, L J

    1994-03-15

    A practical and effective system for the computer-assisted screening of conventionally prepared cervical smears is presented and described. Recent developments in neural network technology have made computerized analysis of the complex cellular scenes found on Pap smears possible. The PAPNET Cytological Screening System uses neural networks to automatically analyze conventional smears by locating and recognizing potentially abnormal cells. It then displays images of these objects for review and final diagnosis by qualified cytologists. The results of the studies presented indicate that the PAPNET system could be a useful tool for both the screening and rescreening of cervical smears. In addition, the system has been shown to be sensitive to some types of abnormalities which have gone undetected during manual screening.

  20. Analog hardware for learning neural networks

    NASA Technical Reports Server (NTRS)

    Eberhardt, Silvio P. (Inventor)

    1991-01-01

    This is a recurrent or feedforward analog neural network processor having a multi-level neuron array and a synaptic matrix for storing weighted analog values of synaptic connection strengths which is characterized by temporarily changing one connection strength at a time to determine its effect on system output relative to the desired target. That connection strength is then adjusted based on the effect, whereby the processor is taught the correct response to training examples connection by connection.

  1. Adaptive Neurons For Artificial Neural Networks

    NASA Technical Reports Server (NTRS)

    Tawel, Raoul

    1990-01-01

    Training time decreases dramatically. In improved mathematical model of neural-network processor, temperature of neurons (in addition to connection strengths, also called weights, of synapses) varied during supervised-learning phase of operation according to mathematical formalism and not heuristic rule. Evidence that biological neural networks also process information at neuronal level.

  2. Computational modeling of neural plasticity for self-organization of neural networks.

    PubMed

    Chrol-Cannon, Joseph; Jin, Yaochu

    2014-11-01

    Self-organization in biological nervous systems during the lifetime is known to largely occur through a process of plasticity that is dependent upon the spike-timing activity in connected neurons. In the field of computational neuroscience, much effort has been dedicated to building up computational models of neural plasticity to replicate experimental data. Most recently, increasing attention has been paid to understanding the role of neural plasticity in functional and structural neural self-organization, as well as its influence on the learning performance of neural networks for accomplishing machine learning tasks such as classification and regression. Although many ideas and hypothesis have been suggested, the relationship between the structure, dynamics and learning performance of neural networks remains elusive. The purpose of this article is to review the most important computational models for neural plasticity and discuss various ideas about neural plasticity's role. Finally, we suggest a few promising research directions, in particular those along the line that combines findings in computational neuroscience and systems biology, and their synergetic roles in understanding learning, memory and cognition, thereby bridging the gap between computational neuroscience, systems biology and computational intelligence. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  3. Growth-related neural reorganization and the autism phenotype: a test of the hypothesis that altered brain growth leads to altered connectivity

    PubMed Central

    Lewis, John D.; Elman, Jeffrey L.

    2009-01-01

    Theoretical considerations, and findings from computational modeling, comparative neuroanatomy and developmental neuroscience, motivate the hypothesis that a deviant brain growth trajectory will lead to deviant patterns of change in cortico-cortical connectivity. Differences in brain size during development will alter the relative cost and effectiveness of short- and long-distance connections, and should thus impact the growth and retention of connections. Reduced brain size should favor long-distance connectivity; brain overgrowth should favor short-distance connectivity; and inconsistent deviations from the normal growth trajectory – as occurs in autism – should result in potentially disruptive changes to established patterns of functional and physical connectivity during development. To explore this hypothesis, neural networks which modeled inter-hemispheric interaction were grown at the rate of either typically developing children or children with autism. The influence of the length of the inter-hemispheric connections was analyzed at multiple developmental time-points. The networks that modeled autistic growth were less affected by removal of the inter-hemispheric connections than those that modeled normal growth – indicating a reduced reliance on long-distance connections – for short response times, and this difference increased substantially at approximately 24 simulated months of age. The performance of the networks showed a corresponding decline during development. And direct analysis of the connection weights showed a parallel reduction in connectivity. These modeling results support the hypothesis that the deviant growth trajectory in autism spectrum disorders may lead to a disruption of established patterns of functional connectivity during development, with potentially negative behavioral consequences, and a subsequent reduction in physical connectivity. The results are discussed in relation to the growing body of evidence of reduced functional

  4. Motor Control Abnormalities in Parkinson’s Disease

    PubMed Central

    Mazzoni, Pietro; Shabbott, Britne; Cortés, Juan Camilo

    2012-01-01

    The primary manifestations of Parkinson’s disease are abnormalities of movement, including movement slowness, difficulties with gait and balance, and tremor. We know a considerable amount about the abnormalities of neuronal and muscle activity that correlate with these symptoms. Motor symptoms can also be described in terms of motor control, a level of description that explains how movement variables, such as a limb’s position and speed, are controlled and coordinated. Understanding motor symptoms as motor control abnormalities means to identify how the disease disrupts normal control processes. In the case of Parkinson’s disease, movement slowness, for example, would be explained by a disruption of the control processes that determine normal movement speed. Two long-term benefits of understanding the motor control basis of motor symptoms include the future design of neural prostheses to replace the function of damaged basal ganglia circuits, and the rational design of rehabilitation strategies. This type of understanding, however, remains limited, partly because of limitations in our knowledge of normal motor control. In this article, we review the concept of motor control and describe a few motor symptoms that illustrate the challenges in understanding such symptoms as motor control abnormalities. PMID:22675667

  5. Hyperactive error responses and altered connectivity in ventromedial and frontoinsular cortices in obsessive-compulsive disorder.

    PubMed

    Stern, Emily R; Welsh, Robert C; Fitzgerald, Kate D; Gehring, William J; Lister, Jamey J; Himle, Joseph A; Abelson, James L; Taylor, Stephan F

    2011-03-15

    Patients with obsessive-compulsive disorder (OCD) show abnormal functioning in ventral frontal brain regions involved in emotional/motivational processes, including anterior insula/frontal operculum (aI/fO) and ventromedial frontal cortex (VMPFC). While OCD has been associated with an increased neural response to errors, the influence of motivational factors on this effect remains poorly understood. To investigate the contribution of motivational factors to error processing in OCD and to examine functional connectivity between regions involved in the error response, functional magnetic resonance imaging data were measured in 39 OCD patients (20 unmedicated, 19 medicated) and 38 control subjects (20 unmedicated, 18 medicated) during an error-eliciting interference task where motivational context was varied using monetary incentives (null, loss, and gain). Across all errors, OCD patients showed reduced deactivation of VMPFC and greater activation in left aI/FO compared with control subjects. For errors specifically resulting in a loss, patients further hyperactivated VMPFC, as well as right aI/FO. Independent of activity associated with task events, OCD patients showed greater functional connectivity between VMPFC and regions of bilateral aI/FO and right thalamus. Obsessive-compulsive disorder patients show greater activation in neural regions associated with emotion and valuation when making errors, which could be related to altered intrinsic functional connectivity between brain networks. These results highlight the importance of emotional/motivational responses to mistakes in OCD and point to the need for further study of network interactions in the disorder. Copyright © 2011 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  6. Artificial neural networks as quantum associative memory

    NASA Astrophysics Data System (ADS)

    Hamilton, Kathleen; Schrock, Jonathan; Imam, Neena; Humble, Travis

    We present results related to the recall accuracy and capacity of Hopfield networks implemented on commercially available quantum annealers. The use of Hopfield networks and artificial neural networks as content-addressable memories offer robust storage and retrieval of classical information, however, implementation of these models using currently available quantum annealers faces several challenges: the limits of precision when setting synaptic weights, the effects of spurious spin-glass states and minor embedding of densely connected graphs into fixed-connectivity hardware. We consider neural networks which are less than fully-connected, and also consider neural networks which contain multiple sparsely connected clusters. We discuss the effect of weak edge dilution on the accuracy of memory recall, and discuss how the multiple clique structure affects the storage capacity. Our work focuses on storage of patterns which can be embedded into physical hardware containing n < 1000 qubits. This work was supported by the United States Department of Defense and used resources of the Computational Research and Development Programs as Oak Ridge National Laboratory under Contract No. DE-AC0500OR22725 with the U. S. Department of Energy.

  7. Addiction Related Alteration in Resting-state Brain Connectivity

    PubMed Central

    Ma, Ning; Liu, Ying; Li, Nan; Wang, Chang-Xin; Zhang, Hao; Jiang, Xiao-Feng; Xu, Hu-Sheng; Fu, Xian-Ming; Hu, Xiaoping; Zhang, Da-Ren

    2009-01-01

    It is widely accepted that addictive drug use is related to abnormal functional organization in the user’s brain. The present study aimed to identify this type of abnormality within the brain networks implicated in addiction by resting-state functional connectivity measured with functional magnetic resonance imaging (fMRI). With fMRI data acquired during resting state from 14 chronic heroin users (12 of whom were being treated with methadone) and 13 non-addicted controls, we investigated the addiction related alteration in functional connectivity between the regions in the circuits implicated in addiction with seed-based correlation analysis. Compared with controls, chronic heroin users showed increased functional connectivity between nucleus accumbens and ventral/rostral anterior cingulate cortex (ACC), and orbital frontal cortex (OFC), between amygdala and OFC; and reduced functional connectivity between prefrontal cortex and OFC, and ACC. These observations of altered resting-state functional connectivity suggested abnormal functional organization in the addicted brain and may provide additional evidence supporting the theory of addiction that emphasizes enhanced salience value of a drug and its related cues but weakened cognitive control in the addictive state. PMID:19703568

  8. Synchronization in a noise-driven developing neural network

    NASA Astrophysics Data System (ADS)

    Lin, I.-H.; Wu, R.-K.; Chen, C.-M.

    2011-11-01

    We use computer simulations to investigate the structural and dynamical properties of a developing neural network whose activity is driven by noise. Structurally, the constructed neural networks in our simulations exhibit the small-world properties that have been observed in several neural networks. The dynamical change of neuronal membrane potential is described by the Hodgkin-Huxley model, and two types of learning rules, including spike-timing-dependent plasticity (STDP) and inverse STDP, are considered to restructure the synaptic strength between neurons. Clustered synchronized firing (SF) of the network is observed when the network connectivity (number of connections/maximal connections) is about 0.75, in which the firing rate of neurons is only half of the network frequency. At the connectivity of 0.86, all neurons fire synchronously at the network frequency. The network SF frequency increases logarithmically with the culturing time of a growing network and decreases exponentially with the delay time in signal transmission. These conclusions are consistent with experimental observations. The phase diagrams of SF in a developing network are investigated for both learning rules.

  9. An efficient optical architecture for sparsely connected neural networks

    NASA Technical Reports Server (NTRS)

    Hine, Butler P., III; Downie, John D.; Reid, Max B.

    1990-01-01

    An architecture for general-purpose optical neural network processor is presented in which the interconnections and weights are formed by directing coherent beams holographically, thereby making use of the space-bandwidth products of the recording medium for sparsely interconnected networks more efficiently that the commonly used vector-matrix multiplier, since all of the hologram area is in use. An investigation is made of the use of computer-generated holograms recorded on such updatable media as thermoplastic materials, in order to define the interconnections and weights of a neural network processor; attention is given to limits on interconnection densities, diffraction efficiencies, and weighing accuracies possible with such an updatable thin film holographic device.

  10. Multitask neurovision processor with extensive feedback and feedforward connections

    NASA Astrophysics Data System (ADS)

    Gupta, Madan M.; Knopf, George K.

    1991-11-01

    A multi-task neuro-vision parameter which performs a variety of information processing operations associated with the early stages of biological vision is presented. The network architecture of this neuro-vision processor, called the positive-negative (PN) neural processor, is loosely based on the neural activity fields exhibited by thalamic and cortical nervous tissue layers. The computational operation performed by the processor arises from the strength of the recurrent feedback among the numerous positive and negative neural computing units. By adjusting the feedback connections it is possible to generate diverse dynamic behavior that may be used for short-term visual memory (STVM), spatio-temporal filtering (STF), and pulse frequency modulation (PFM). The information attributes that are to be processes may be regulated by modifying the feedforward connections from the signal space to the neural processor.

  11. Functional connectivity and microstructural white matter changes in phenocopy frontotemporal dementia.

    PubMed

    Meijboom, R; Steketee, R M E; de Koning, I; Osse, R J; Jiskoot, L C; de Jong, F J; van der Lugt, A; van Swieten, J C; Smits, M

    2017-04-01

    Phenocopy frontotemporal dementia (phFTD) is a rare and poorly understood clinical syndrome. PhFTD shows core behavioural variant FTD (bvFTD) symptoms without associated cognitive deficits and brain abnormalities on conventional MRI and without progression. In contrast to phFTD, functional connectivity and white matter (WM) microstructural abnormalities have been observed in bvFTD. We hypothesise that phFTD belongs to the same disease spectrum as bvFTD and investigated whether functional connectivity and microstructural WM changes similar to bvFTD are present in phFTD. Seven phFTD patients without progression or alternative psychiatric diagnosis, 12 bvFTD patients and 17 controls underwent resting state functional MRI (rs-fMRI) and diffusion tensor imaging (DTI). Default mode network (DMN) connectivity and WM measures were compared between groups. PhFTD showed subtly increased DMN connectivity and subtle microstructural changes in frontal WM tracts. BvFTD showed abnormalities in similar regions as phFTD, but had lower increased DMN connectivity and more extensive microstructural WM changes. Our findings can be interpreted as neuropathological changes in phFTD and are in support of the hypothesis that phFTD and bvFTD may belong to the same disease spectrum. Advanced MRI techniques, objectively identifying brain abnormalities, would therefore be potentially suited to improve the diagnosis of phFTD. • PhFTD shows brain abnormalities that are similar to bvFTD. • PhFTD shows increased functional connectivity in the parietal default mode network. • PhFTD shows microstructural white matter abnormalities in the frontal lobe. • We hypothesise phFTD and bvFTD may belong to the same disease spectrum.

  12. Recovery of directed intracortical connectivity from fMRI data

    NASA Astrophysics Data System (ADS)

    Gilson, Matthieu; Ritter, Petra; Deco, Gustavo

    2016-06-01

    The brain exhibits complex spatio-temporal patterns of activity. In particular, its baseline activity at rest has a specific structure: imaging techniques (e.g., fMRI, EEG and MEG) show that cortical areas experience correlated fluctuations, which is referred to as functional connectivity (FC). The present study relies on our recently developed model in which intracortical white-matter connections shape noise-driven fluctuations to reproduce FC observed in experimental data (here fMRI BOLD signal). Here noise has a functional role and represents the variability of neural activity. The model also incorporates anatomical information obtained using diffusion tensor imaging (DTI), which estimates the density of white-matter fibers (structural connectivity, SC). After optimization to match empirical FC, the model provides an estimation of the efficacies of these fibers, which we call effective connectivity (EC). EC differs from SC, as EC not only accounts for the density of neural fibers, but also the concentration of synapses formed at their end, the type of neurotransmitters associated and the excitability of target neural populations. In summary, the model combines anatomical SC and activity FC to evaluate what drives the neural dynamics, embodied in EC. EC can then be analyzed using graph theory to understand how it generates FC and to seek for functional communities among cortical areas (parcellation of 68 areas). We find that intracortical connections are not symmetric, which affects the dynamic range of cortical activity (i.e., variety of states it can exhibit).

  13. Movement and Learning: A Valuable Connection

    ERIC Educational Resources Information Center

    Stevens-Smith, Deborah

    2004-01-01

    In this article, the author discusses the relatedness between movement and learning for students. The process of learning involves basic nerve cells that transmit information and create numerous neural connections essential to learning. One way to increase learning is to encourage creation of more synaptic connections in the brain through…

  14. Neural substrates underlying balanced time perspective: A combined voxel-based morphometry and resting-state functional connectivity study.

    PubMed

    Guo, Yiqun; Chen, Zhiyi; Feng, Tingyong

    2017-08-14

    Balanced time perspective (BTP), which is defined as a mental ability to switch flexibly among different time perspectives Zimbardo and Boyd (1999), has been suggested to be a central component of positive psychology Boniwell and Zimbardo (2004). BTP reflects individual's cognitive flexibility towards different time frames, which leads to many positive outcomes, including positive mood, subjective wellbeing, emotional intelligence, fluid intelligence, and executive control. However, the neural basis of BTP is still unclear. To address this question, we quantified individual's deviation from the BTP (DBTP), and investigated the neural substrates of DBTP using both voxel-based morphometry (VBM) and resting-state functional connectivity (RSFC) methods VBM analysis found that DBTP scores were positively correlated with gray matter volume (GMV) in the ventral precuneus. We further found that DBTP scores were negatively associated with RSFCs between the ventral precuneus seed region and medial prefrontal cortex (mPFC), bilateral temporoparietal junction (TPJ), parahippocampa gyrus (PHG), and middle frontal gyrus (MFG). These brain regions found in both VBM and RSFC analyses are commonly considered as core nodes of the default mode network (DMN) that is known to be involved in many functions, including episodic and autobiographical memory, self-related processing, theory of mind, and imagining the future. These functions of the DMN are also essential to individuals with BTP. Taken together, we provide the first evidence for the structural and functional neural basis of BTP, and highlight the crucial role of the DMN in cultivating an individual's BTP. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. Maturational trajectories of local and long-range functional connectivity in autism during face processing.

    PubMed

    Mamashli, Fahimeh; Khan, Sheraz; Bharadwaj, Hari; Losh, Ainsley; Pawlyszyn, Stephanie M; Hämäläinen, Matti S; Kenet, Tal

    2018-06-26

    Autism spectrum disorder (ASD) is characterized neurophysiologically by, among other things, functional connectivity abnormalities in the brain. Recent evidence suggests that the nature of these functional connectivity abnormalities might not be uniform throughout maturation. Comparing between adolescents and young adults (ages 14-21) with ASD and age- and IQ-matched typically developing (TD) individuals, we previously documented, using magnetoencephalography (MEG) data, that local functional connectivity in the fusiform face areas (FFA) and long-range functional connectivity between FFA and three higher order cortical areas were all reduced in ASD. Given the findings on abnormal maturation trajectories in ASD, we tested whether these results extend to preadolescent children (ages 7-13). We found that both local and long-range functional connectivity were in fact normal in this younger age group in ASD. Combining the two age groups, we found that local and long-range functional connectivity measures were positively correlated with age in TD, but negatively correlated with age in ASD. Last, we showed that local functional connectivity was the primary feature in predicting age in ASD group, but not in the TD group. Furthermore, local functional connectivity was only correlated with ASD severity in the older group. These results suggest that the direction of maturation of functional connectivity for processing of faces from childhood to young adulthood is itself abnormal in ASD, and that during the processing of faces, these trajectory abnormalities are more pronounced for local functional connectivity measures than they are for long-range functional connectivity measures. © 2018 Wiley Periodicals, Inc.

  16. A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy

    PubMed Central

    Shafi, Mouhsin M.; Whitfield-Gabrieli, Susan; Chu, Catherine J.; Pascual-Leone, Alvaro; Chang, Bernard S.

    2017-01-01

    Resting-state functional connectivity MRI (rs-fcMRI) is a technique that identifies connectivity between different brain regions based on correlations over time in the blood-oxygenation level dependent signal. rs-fcMRI has been applied extensively to identify abnormalities in brain connectivity in different neurologic and psychiatric diseases. However, the relationship among rs-fcMRI connectivity abnormalities, brain electrophysiology and disease state is unknown, in part because the causal significance of alterations in functional connectivity in disease pathophysiology has not been established. Transcranial Magnetic Stimulation (TMS) is a technique that uses electromagnetic induction to noninvasively produce focal changes in cortical activity. When combined with electroencephalography (EEG), TMS can be used to assess the brain's response to external perturbations. Here we provide a protocol for combining rs-fcMRI, TMS and EEG to assess the physiologic significance of alterations in functional connectivity in patients with neuropsychiatric disease. We provide representative results from a previously published study in which rs-fcMRI was used to identify regions with abnormal connectivity in patients with epilepsy due to a malformation of cortical development, periventricular nodular heterotopia (PNH). Stimulation in patients with epilepsy resulted in abnormal TMS-evoked EEG activity relative to stimulation of the same sites in matched healthy control patients, with an abnormal increase in the late component of the TMS-evoked potential, consistent with cortical hyperexcitability. This abnormality was specific to regions with abnormal resting-state functional connectivity. Electrical source analysis in a subject with previously recorded seizures demonstrated that the origin of the abnormal TMS-evoked activity co-localized with the seizure-onset zone, suggesting the presence of an epileptogenic circuit. These results demonstrate how rs-fcMRI, TMS and EEG can be

  17. Topsoil pollution forecasting using artificial neural networks on the example of the abnormally distributed heavy metal at Russian subarctic

    NASA Astrophysics Data System (ADS)

    Tarasov, D. A.; Buevich, A. G.; Sergeev, A. P.; Shichkin, A. V.; Baglaeva, E. M.

    2017-06-01

    Forecasting the soil pollution is a considerable field of study in the light of the general concern of environmental protection issues. Due to the variation of content and spatial heterogeneity of pollutants distribution at urban areas, the conventional spatial interpolation models implemented in many GIS packages mostly cannot provide appreciate interpolation accuracy. Moreover, the problem of prediction the distribution of the element with high variability in the concentration at the study site is particularly difficult. The work presents two neural networks models forecasting a spatial content of the abnormally distributed soil pollutant (Cr) at a particular location of the subarctic Novy Urengoy, Russia. A method of generalized regression neural network (GRNN) was compared to a common multilayer perceptron (MLP) model. The proposed techniques have been built, implemented and tested using ArcGIS and MATLAB. To verify the models performances, 150 scattered input data points (pollutant concentrations) have been selected from 8.5 km2 area and then split into independent training data set (105 points) and validation data set (45 points). The training data set was generated for the interpolation using ordinary kriging while the validation data set was used to test their accuracies. The networks structures have been chosen during a computer simulation based on the minimization of the RMSE. The predictive accuracy of both models was confirmed to be significantly higher than those achieved by the geostatistical approach (kriging). It is shown that MLP could achieve better accuracy than both kriging and even GRNN for interpolating surfaces.

  18. Rodent Zic Genes in Neural Network Wiring.

    PubMed

    Herrera, Eloísa

    2018-01-01

    The formation of the nervous system is a multistep process that yields a mature brain. Failure in any of the steps of this process may cause brain malfunction. In the early stages of embryonic development, neural progenitors quickly proliferate and then, at a specific moment, differentiate into neurons or glia. Once they become postmitotic neurons, they migrate to their final destinations and begin to extend their axons to connect with other neurons, sometimes located in quite distant regions, to establish different neural circuits. During the last decade, it has become evident that Zic genes, in addition to playing important roles in early development (e.g., gastrulation and neural tube closure), are involved in different processes of late brain development, such as neuronal migration, axon guidance, and refinement of axon terminals. ZIC proteins are therefore essential for the proper wiring and connectivity of the brain. In this chapter, we review our current knowledge of the role of Zic genes in the late stages of neural circuit formation.

  19. Reduced Prefrontal Connectivity in Psychopathy

    PubMed Central

    Motzkin, Julian C.; Newman, Joseph P.; Kiehl, Kent A.; Koenigs, Michael

    2012-01-01

    Linking psychopathy to a specific brain abnormality could have significant clinical, legal, and scientific implications. Theories on the neurobiological basis of the disorder typically propose dysfunction in a circuit involving ventromedial prefrontal cortex (vmPFC). However, to date there is limited brain imaging data to directly test whether psychopathy may indeed be associated with any structural or functional abnormality within this brain area. In this study, we employ two complementary imaging techniques to assess the structural and functional connectivity of vmPFC in psychopathic and non-psychopathic criminals. Using diffusion tensor imaging, we show that psychopathy is associated with reduced structural integrity in the right uncinate fasciculus, the primary white matter connection between vmPFC and anterior temporal lobe. Using functional magnetic resonance imaging, we show that psychopathy is associated with reduced functional connectivity between vmPFC and amygdala as well as between vmPFC and medial parietal cortex. Together, these data converge to implicate diminished vmPFC connectivity as a characteristic neurobiological feature of psychopathy. PMID:22131397

  20. Neural network alterations across eating disorders: a narrative review of fMRI studies.

    PubMed

    Steward, Trevor; Menchón, José M; Jiménez-Murcia, Susana; Soriano-Mas, Carles; Fernández-Aranda, Fernando

    2017-10-17

    Functional magnetic resonance imaging (fMRI) has provided insight on how neural abnormalities are related to the symptomatology of the eating disorders (EDs): anorexia nervosa (AN), bulimia nervosa (BN), and binge eating disorder (BED). More specifically, an increasingly growing number of brain imaging studies has shed light on how functionally connected brain networks contribute not only to disturbed eating behavior, but also to transdiagnostic alterations in body/interoceptive perception, reward processing and executive functions. This narrative review aims to summarize recent advances in fMRI studies of patients with EDs by highlighting studies investigating network alterations that are shared across EDs. Findings on reward processing in both AN and BN patients point to the presence of altered sensitivity to salient food stimuli in striatal regions and to the possibility of hypothalamic inputs being overridden by top-down cognitive control regions. Additionally, innovative new lines of research suggest that increased activations in fronto-striatal circuits are strongly associated with the maintenance of restrictive eating habits in AN patients. Although significantly fewer studies have been carried out in patients with BN and BED, aberrant neural responses to both food cues and anticipated food receipt appear to occur in these populations. These altered responses, coupled with diminished recruitment of prefrontal cognitive control circuitry, are believed to contribute to the binge eating of palatable foods. Results from functional network connectivity studies are diverse, but findings tend to converge on indicating disrupted resting-state connectivity in executive networks, the default-mode network and the salience network across EDs. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  1. Nested neural networks

    NASA Technical Reports Server (NTRS)

    Baram, Yoram

    1988-01-01

    Nested neural networks, consisting of small interconnected subnetworks, allow for the storage and retrieval of neural state patterns of different sizes. The subnetworks are naturally categorized by layers of corresponding to spatial frequencies in the pattern field. The storage capacity and the error correction capability of the subnetworks generally increase with the degree of connectivity between layers (the nesting degree). Storage of only few subpatterns in each subnetworks results in a vast storage capacity of patterns and subpatterns in the nested network, maintaining high stability and error correction capability.

  2. Sex differences in autism: a resting-state fMRI investigation of functional brain connectivity in males and females

    PubMed Central

    Swinnen, Stephan P.; Wenderoth, Nicole

    2016-01-01

    Autism spectrum disorders (ASD) are far more prevalent in males than in females. Little is known however about the differential neural expression of ASD in males and females. We used a resting-state fMRI-dataset comprising 42 males/42 females with ASD and 75 male/75 female typical-controls to examine whether autism-related alterations in intrinsic functional connectivity are similar or different in males and females, and particularly whether alterations reflect ‘neural masculinization’, as predicted by the Extreme Male Brain theory. Males and females showed a differential neural expression of ASD, characterized by highly consistent patterns of hypo-connectivity in males with ASD (compared to typical males), and hyper-connectivity in females with ASD (compared to typical females). Interestingly, patterns of hyper-connectivity in females with ASD reflected a shift towards the (high) connectivity levels seen in typical males (neural masculinization), whereas patterns of hypo-connectivity observed in males with ASD reflected a shift towards the (low) typical feminine connectivity patterns (neural feminization). Our data support the notion that ASD is a disorder of sexual differentiation rather than a disorder characterized by masculinization in both genders. Future work is needed to identify underlying factors such as sex hormonal alterations that drive these sex-specific neural expressions of ASD. PMID:26989195

  3. Dysfunctional Autism Risk Genes Cause Circuit-Specific Connectivity Deficits With Distinct Developmental Trajectories

    PubMed Central

    Ielacqua, Giovanna D; Markicevic, Marija; Haberl, Matthias Georg; Ellisman, Mark H; A-Bhaskaran, Arjun; Frick, Andreas; Rudin, Markus; Wenderoth, Nicole

    2018-01-01

    Abstract Autism spectrum disorders (ASD) are a set of complex neurodevelopmental disorders for which there is currently no targeted therapeutic approach. It is thought that alterations of genes regulating migration and synapse formation during development affect neural circuit formation and result in aberrant connectivity within distinct circuits that underlie abnormal behaviors. However, it is unknown whether deviant developmental trajectories are circuit-specific for a given autism risk-gene. We used MRI to probe changes in functional and structural connectivity from childhood to adulthood in Fragile-X (Fmr1−/y) and contactin-associated (CNTNAP2−/−) knockout mice. Young Fmr1−/y mice (30 days postnatal) presented with a robust hypoconnectivity phenotype in corticocortico and corticostriatal circuits in areas associated with sensory information processing, which was maintained until adulthood. Conversely, only small differences in hippocampal and striatal areas were present during early postnatal development in CNTNAP2−/− mice, while major connectivity deficits in prefrontal and limbic pathways developed between adolescence and adulthood. These findings are supported by viral tracing and electron micrograph approaches and define 2 clearly distinct connectivity endophenotypes within the autism spectrum. We conclude that the genetic background of ASD strongly influences which circuits are most affected, the nature of the phenotype, and the developmental time course of the associated changes. PMID:29901787

  4. Electronic implementation of associative memory based on neural network models

    NASA Technical Reports Server (NTRS)

    Moopenn, A.; Lambe, John; Thakoor, A. P.

    1987-01-01

    An electronic embodiment of a neural network based associative memory in the form of a binary connection matrix is described. The nature of false memory errors, their effect on the information storage capacity of binary connection matrix memories, and a novel technique to eliminate such errors with the help of asymmetrical extra connections are discussed. The stability of the matrix memory system incorporating a unique local inhibition scheme is analyzed in terms of local minimization of an energy function. The memory's stability, dynamic behavior, and recall capability are investigated using a 32-'neuron' electronic neural network memory with a 1024-programmable binary connection matrix.

  5. Control of Abnormal Synchronization in Neurological Disorders

    PubMed Central

    Popovych, Oleksandr V.; Tass, Peter A.

    2014-01-01

    In the nervous system, synchronization processes play an important role, e.g., in the context of information processing and motor control. However, pathological, excessive synchronization may strongly impair brain function and is a hallmark of several neurological disorders. This focused review addresses the question of how an abnormal neuronal synchronization can specifically be counteracted by invasive and non-invasive brain stimulation as, for instance, by deep brain stimulation for the treatment of Parkinson’s disease, or by acoustic stimulation for the treatment of tinnitus. On the example of coordinated reset (CR) neuromodulation, we illustrate how insights into the dynamics of complex systems contribute to successful model-based approaches, which use methods from synergetics, non-linear dynamics, and statistical physics, for the development of novel therapies for normalization of brain function and synaptic connectivity. Based on the intrinsic multistability of the neuronal populations induced by spike timing-dependent plasticity (STDP), CR neuromodulation utilizes the mutual interdependence between synaptic connectivity and dynamics of the neuronal networks in order to restore more physiological patterns of connectivity via desynchronization of neuronal activity. The very goal is to shift the neuronal population by stimulation from an abnormally coupled and synchronized state to a desynchronized regime with normalized synaptic connectivity, which significantly outlasts the stimulation cessation, so that long-lasting therapeutic effects can be achieved. PMID:25566174

  6. Failure to Recover from Proactive Semantic Interference and Abnormal Limbic Connectivity in Asymptomatic, Middle-Aged Offspring of Patients with Late-Onset Alzheimer's Disease.

    PubMed

    Sánchez, Stella M; Abulafia, Carolina; Duarte-Abritta, Barbara; de Guevara, M Soledad Ladrón; Castro, Mariana N; Drucaroff, Lucas; Sevlever, Gustavo; Nemeroff, Charles B; Vigo, Daniel E; Loewenstein, David A; Villarreal, Mirta F; Guinjoan, Salvador M

    2017-01-01

    We have obtained previous evidence of limbic dysfunction in middle-aged, asymptomatic offspring of late-onset Alzheimer's disease (LOAD) patients, and failure to recover from proactive semantic interference has been shown to be a sensitive cognitive test in other groups at risk for LOAD. To assess the effects of specific proactive semantic interference deficits as they relate to functional magnetic resonance imaging (fMRI) neocortical and limbic functional connectivity in middle aged offspring of individuals with LOAD (O-LOAD) and age-equivalent controls. We examined 21 O-LOAD and 20 controls without family history of neurodegenerative disorders (CS) on traditional measures of cognitive functioning and the LASSI-L, a novel semantic interference test uniquely sensitive to the failure to recover from proactive interference (frPSI). Cognitive tests then were correlated to fMRI connectivity of seeds located in entorhinal cortex and anterodorsal thalamic nuclei among O-LOAD and CS participants. Relative to CS, O-LOAD participants evidenced lower connectivity between entorhinal cortex and orbitofrontal, anterior cingulate, and anterior temporal cortex. In the offspring of LOAD patients, LASSI-L measures of frPSI were inversely associated with connectivity between anterodorsal thalamus and contralateral posterior cingulate. Intrusions on the task related to frPSI were inversely correlated with a widespread connectivity network involving hippocampal, insular, posterior cingulate, and dorsolateral prefrontal cortices, along with precunei and anterior thalamus in this group. Different patterns of connectivity associated with frPSI were observed among controls. The present results suggest that both semantic interference deficits and connectivity abnormalities might reflect limbic circuit dysfunction as a very early clinical signature of LOAD pathology, as previously demonstrated for other limbic phenotypes, such as sleep and circadian alterations.

  7. Probabilistic diffusion tractography and graph theory analysis reveal abnormal white matter structural connectivity networks in drug-naive boys with attention deficit/hyperactivity disorder.

    PubMed

    Cao, Qingjiu; Shu, Ni; An, Li; Wang, Peng; Sun, Li; Xia, Ming-Rui; Wang, Jin-Hui; Gong, Gao-Lang; Zang, Yu-Feng; Wang, Yu-Feng; He, Yong

    2013-06-26

    Attention-deficit/hyperactivity disorder (ADHD), which is characterized by core symptoms of inattention and hyperactivity/impulsivity, is one of the most common neurodevelopmental disorders of childhood. Neuroimaging studies have suggested that these behavioral disturbances are associated with abnormal functional connectivity among brain regions. However, the alterations in the structural connections that underlie these behavioral and functional deficits remain poorly understood. Here, we used diffusion magnetic resonance imaging and probabilistic tractography method to examine whole-brain white matter (WM) structural connectivity in 30 drug-naive boys with ADHD and 30 healthy controls. The WM networks of the human brain were constructed by estimating inter-regional connectivity probability. The topological properties of the resultant networks (e.g., small-world and network efficiency) were then analyzed using graph theoretical approaches. Nonparametric permutation tests were applied for between-group comparisons of these graphic metrics. We found that both the ADHD and control groups showed an efficient small-world organization in the whole-brain WM networks, suggesting a balance between structurally segregated and integrated connectivity patterns. However, relative to controls, patients with ADHD exhibited decreased global efficiency and increased shortest path length, with the most pronounced efficiency decreases in the left parietal, frontal, and occipital cortices. Intriguingly, the ADHD group showed decreased structural connectivity in the prefrontal-dominant circuitry and increased connectivity in the orbitofrontal-striatal circuitry, and these changes significantly correlated with the inattention and hyperactivity/impulsivity symptoms, respectively. The present study shows disrupted topological organization of large-scale WM networks in ADHD, extending our understanding of how structural disruptions of neuronal circuits underlie behavioral disturbances in

  8. Feature Extraction Using an Unsupervised Neural Network

    DTIC Science & Technology

    1991-05-03

    with this neural netowrk is given and its connection to exploratory projection pursuit methods is established. DD I 2 P JA d 73 EDITIONj Of I NOV 6s...IS OBSOLETE $IN 0102- LF- 014- 6601 SECURITY CLASSIFICATION OF THIS PAGE (When Daoes Enlered) Feature Extraction using an Unsupervised Neural Network

  9. Characterizing dynamic amplitude of low-frequency fluctuation and its relationship with dynamic functional connectivity: An application to schizophrenia.

    PubMed

    Fu, Zening; Tu, Yiheng; Di, Xin; Du, Yuhui; Pearlson, G D; Turner, J A; Biswal, Bharat B; Zhang, Zhiguo; Calhoun, V D

    2017-09-20

    The human brain is a highly dynamic system with non-stationary neural activity and rapidly-changing neural interaction. Resting-state dynamic functional connectivity (dFC) has been widely studied during recent years, and the emerging aberrant dFC patterns have been identified as important features of many mental disorders such as schizophrenia (SZ). However, only focusing on the time-varying patterns in FC is not enough, since the local neural activity itself (in contrast to the inter-connectivity) is also found to be highly fluctuating from research using high-temporal-resolution imaging techniques. Exploring the time-varying patterns in brain activity and their relationships with time-varying brain connectivity is important for advancing our understanding of the co-evolutionary property of brain network and the underlying mechanism of brain dynamics. In this study, we introduced a framework for characterizing time-varying brain activity and exploring its associations with time-varying brain connectivity, and applied this framework to a resting-state fMRI dataset including 151 SZ patients and 163 age- and gender matched healthy controls (HCs). In this framework, 48 brain regions were first identified as intrinsic connectivity networks (ICNs) using group independent component analysis (GICA). A sliding window approach was then adopted for the estimation of dynamic amplitude of low-frequency fluctuation (dALFF) and dFC, which were used to measure time-varying brain activity and time-varying brain connectivity respectively. The dALFF was further clustered into six reoccurring states by the k-means clustering method and the group difference in occurrences of dALFF states was explored. Lastly, correlation coefficients between dALFF and dFC were calculated and the group difference in these dALFF-dFC correlations was explored. Our results suggested that 1) ALFF of brain regions was highly fluctuating during the resting-state and such dynamic patterns are altered in SZ, 2

  10. Efficiently modeling neural networks on massively parallel computers

    NASA Technical Reports Server (NTRS)

    Farber, Robert M.

    1993-01-01

    Neural networks are a very useful tool for analyzing and modeling complex real world systems. Applying neural network simulations to real world problems generally involves large amounts of data and massive amounts of computation. To efficiently handle the computational requirements of large problems, we have implemented at Los Alamos a highly efficient neural network compiler for serial computers, vector computers, vector parallel computers, and fine grain SIMD computers such as the CM-2 connection machine. This paper describes the mapping used by the compiler to implement feed-forward backpropagation neural networks for a SIMD (Single Instruction Multiple Data) architecture parallel computer. Thinking Machines Corporation has benchmarked our code at 1.3 billion interconnects per second (approximately 3 gigaflops) on a 64,000 processor CM-2 connection machine (Singer 1990). This mapping is applicable to other SIMD computers and can be implemented on MIMD computers such as the CM-5 connection machine. Our mapping has virtually no communications overhead with the exception of the communications required for a global summation across the processors (which has a sub-linear runtime growth on the order of O(log(number of processors)). We can efficiently model very large neural networks which have many neurons and interconnects and our mapping can extend to arbitrarily large networks (within memory limitations) by merging the memory space of separate processors with fast adjacent processor interprocessor communications. This paper will consider the simulation of only feed forward neural network although this method is extendable to recurrent networks.

  11. Neural Progenitor Cells Rptor Ablation Impairs Development but Benefits to Seizure-Induced Behavioral Abnormalities.

    PubMed

    Chen, Ling-Lin; Wu, Mei-Ling; Zhu, Feng; Kai, Jie-Jing; Dong, Jing-Yin; Wu, Xi-Mei; Zeng, Ling-Hui

    2016-12-01

    Previous study suggests that mTOR signaling pathway may play an important role in epileptogenesis. The present work was designed to explore the contribution of raptor protein to the development of epilepsy and comorbidities. Mice with conditional knockout of raptor protein were generated by cross-bred Rptor flox/flox mice with nestin-CRE mice. The expression of raptor protein was analyzed by Western blotting in brain tissue samples. Neuronal death and mossy fiber sprouting were detected by FJB staining and Timm staining, respectively. Spontaneous seizures were recorded by EEG-video system. Morris water maze, open field test, and excitability test were used to study the behaviors of Rptor CKO mice. As the consequence of deleting Rptor, downstream proteins of raptor in mTORC1 signaling were partly blocked. Rptor CKO mice exhibited decrease in body and brain weight under 7 weeks old and accordingly, cortical layer thickness. After kainic acid (KA)-induced status epilepticus, overactivation of mTORC1 signaling was markedly reversed in Rptor CKO mice. Although low frequency of spontaneous seizure and seldom neuronal cell death were observed in both Rptor CKO and control littermates, KA seizure-induced mossy fiber spouting were attenuated in Rptor CKO mice. Additionally, cognitive-deficit and anxiety-like behavior after KA-induced seizures were partly reversed in Rptor CKO mice. Loss of the Rptor gene in mice neural progenitor cells affects normal development in young age and may contribute to alleviate KA seizure-induced behavioral abnormalities, suggesting that raptor protein plays an important role in seizure comorbidities. © 2016 John Wiley & Sons Ltd.

  12. Altered resting-state functional connectivity in post-traumatic stress disorder: a perfusion MRI study

    NASA Astrophysics Data System (ADS)

    Li, Baojuan; Liu, Jian; Liu, Yang; Lu, Hong-Bing; Yin, Hong

    2013-03-01

    The majority of studies on posttraumatic stress disorder (PTSD) so far have focused on delineating patterns of activations during cognitive processes. Recently, more and more researches have started to investigate functional connectivity in PTSD subjects using BOLD-fMRI. Functional connectivity analysis has been demonstrated as a powerful approach to identify biomarkers of different brain diseases. This study aimed to detect resting-state functional connectivity abnormities in patients with PTSD using arterial spin labeling (ASL) fMRI. As a completely non-invasive technique, ASL allows quantitative estimates of cerebral blood flow (CBF). Compared with BOLD-fMRI, ASL fMRI has many advantages, including less low-frequency signal drifts, superior functional localization, etc. In the current study, ASL images were collected from 10 survivors in mining disaster with recent onset PTSD and 10 survivors without PTSD. Decreased regional CBF in the right middle temporal gyrus, lingual gyrus, and postcentral gyrus was detected in the PTSD patients. Seed-based resting-state functional connectivity analysis was performed using an area in the right middle temporal gyrus as region of interest. Compared with the non-PTSD group, the PTSD subjects demonstrated increased functional connectivity between the right middle temporal gyrus and the right superior temporal gyrus, the left middle temporal gyrus. Meanwhile, decreased functional connectivity between the right middle temporal gyrus and the right postcentral gyrus, the right superior parietal lobule was also found in the PTSD patients. This is the first study which investigated resting-state functional connectivity in PTSD using ASL images. The results may provide new insight into the neural substrates of PTSD.

  13. Amygdala abnormalities in first-degree relatives of individuals with schizophrenia unmasked by benzodiazepine challenge

    PubMed Central

    Wolf, Daniel H.; Satterthwaite, Theodore D.; Loughead, James; Pinkham, Amy; Overton, Eve; Elliott, Mark A.; Dent, Gersham W.; Smith, Mark A.; Gur, Ruben C.; Gur, Raquel E.

    2014-01-01

    Rationale Impaired emotion processing in schizophrenia predicts broader social dysfunction and has been related to negative symptom severity and amygdala dysfunction. Pharmacological modulation of emotion-processing deficits and related neural abnormalities may provide useful phenotypes for pathophysiological investigation. Objectives We used an acute benzodiazepine challenge to identify and modulate potential emotion-processing abnormalities in 20 unaffected first-degree relatives of individuals with schizophrenia, compared to 25 control subjects without a family history of psychosis. Methods An oral 1mg dose of the short-acting anxiolytic benzodiazepine alprazolam was administered in a balanced crossover placebo-controlled double-blind design, preceding identical 3T fMRI sessions approximately 1 week apart. Primary outcomes included fMRI activity in amygdala and related regions during two facial emotion-processing tasks: emotion identification and emotion memory. Results Family members exhibited abnormally strong alprazolam-induced reduction in amygdala and hippocampus activation during emotion identification, compared to equal reduction in both groups for the emotion memory task. Conclusions GABAergic modulation with alprazolam produced differential responses in family members vs. controls, perhaps by unmasking underlying amygdalar and/or GABAergic abnormalities. Such pharmacological fMRI paradigms could prove useful for developing drugs targeting specific neural circuits to treat or prevent schizophrenia. PMID:21603892

  14. Pruning artificial neural networks using neural complexity measures.

    PubMed

    Jorgensen, Thomas D; Haynes, Barry P; Norlund, Charlotte C F

    2008-10-01

    This paper describes a new method for pruning artificial neural networks, using a measure of the neural complexity of the neural network. This measure is used to determine the connections that should be pruned. The measure computes the information-theoretic complexity of a neural network, which is similar to, yet different from previous research on pruning. The method proposed here shows how overly large and complex networks can be reduced in size, whilst retaining learnt behaviour and fitness. The technique proposed here helps to discover a network topology that matches the complexity of the problem it is meant to solve. This novel pruning technique is tested in a robot control domain, simulating a racecar. It is shown, that the proposed pruning method is a significant improvement over the most commonly used pruning method Magnitude Based Pruning. Furthermore, some of the pruned networks prove to be faster learners than the benchmark network that they originate from. This means that this pruning method can also help to unleash hidden potential in a network, because the learning time decreases substantially for a pruned a network, due to the reduction of dimensionality of the network.

  15. Abnormal autonomic and associated brain activities during rest in autism spectrum disorder

    PubMed Central

    Eilam-Stock, Tehila; Xu, Pengfei; Cao, Miao; Gu, Xiaosi; Van Dam, Nicholas T.; Anagnostou, Evdokia; Kolevzon, Alexander; Soorya, Latha; Park, Yunsoo; Siller, Michael; He, Yong; Hof, Patrick R.

    2014-01-01

    Autism spectrum disorders are associated with social and emotional deficits, the aetiology of which are not well understood. A growing consensus is that the autonomic nervous system serves a key role in emotional processes, by providing physiological signals essential to subjective states. We hypothesized that altered autonomic processing is related to the socio-emotional deficits in autism spectrum disorders. Here, we investigated the relationship between non-specific skin conductance response, an objective index of sympathetic neural activity, and brain fluctuations during rest in high-functioning adults with autism spectrum disorder relative to neurotypical controls. Compared with control participants, individuals with autism spectrum disorder showed less skin conductance responses overall. They also showed weaker correlations between skin conductance responses and frontal brain regions, including the anterior cingulate and anterior insular cortices. Additionally, skin conductance responses were found to have less contribution to default mode network connectivity in individuals with autism spectrum disorders relative to controls. These results suggest that autonomic processing is altered in autism spectrum disorders, which may be related to the abnormal socio-emotional behaviours that characterize this condition. PMID:24424916

  16. Detector for flow abnormalities in gaseous diffusion plant compressors

    DOEpatents

    Smith, Stephen F.; Castleberry, Kim N.

    1998-01-01

    A detector detects a flow abnormality in a plant compressor which outputs a motor current signal. The detector includes a demodulator/lowpass filter demodulating and filtering the motor current signal producing a demodulated signal, and first, second, third and fourth bandpass filters connected to the demodulator/lowpass filter, and filtering the demodulated signal in accordance with first, second, third and fourth bandpass frequencies generating first, second, third and fourth filtered signals having first, second, third and fourth amplitudes. The detector also includes first, second, third and fourth amplitude detectors connected to the first, second, third and fourth bandpass filters respectively, and detecting the first, second, third and fourth amplitudes, and first and second adders connected to the first and fourth amplitude detectors and the second and third amplitude detectors respectively, and adding the first and fourth amplitudes and the second and third amplitudes respectively generating first and second added signals. Finally, the detector includes a comparator, connected to the first and second adders, and comparing the first and second added signals and detecting the abnormal condition in the plant compressor when the second added signal exceeds the first added signal by a predetermined value.

  17. Detector for flow abnormalities in gaseous diffusion plant compressors

    DOEpatents

    Smith, S.F.; Castleberry, K.N.

    1998-06-16

    A detector detects a flow abnormality in a plant compressor which outputs a motor current signal. The detector includes a demodulator/lowpass filter demodulating and filtering the motor current signal producing a demodulated signal, and first, second, third and fourth bandpass filters connected to the demodulator/lowpass filter, and filtering the demodulated signal in accordance with first, second, third and fourth bandpass frequencies generating first, second, third and fourth filtered signals having first, second, third and fourth amplitudes. The detector also includes first, second, third and fourth amplitude detectors connected to the first, second, third and fourth bandpass filters respectively, and detecting the first, second, third and fourth amplitudes, and first and second adders connected to the first and fourth amplitude detectors and the second and third amplitude detectors respectively, and adding the first and fourth amplitudes and the second and third amplitudes respectively generating first and second added signals. Finally, the detector includes a comparator, connected to the first and second adders, and comparing the first and second added signals and detecting the abnormal condition in the plant compressor when the second added signal exceeds the first added signal by a predetermined value. 6 figs.

  18. Impaired regulation of emotion: neural correlates of reappraisal and distraction in bipolar disorder and unaffected relatives

    PubMed Central

    Kanske, P; Schönfelder, S; Forneck, J; Wessa, M

    2015-01-01

    Deficient emotion regulation has been proposed as a crucial pathological mechanism in bipolar disorder (BD). We therefore investigated emotion regulation impairments in BD, the related neural underpinnings and their etiological relevance for the disorder. Twenty-two euthymic patients with bipolar-I disorder and 17 unaffected first-degree relatives of BD-I patients, as well as two groups of healthy gender-, age- and education-matched controls (N=22/17, respectively) were included. Participants underwent functional magnetic resonance imaging while applying two different emotion regulation techniques, reappraisal and distraction, when presented with emotional images. BD patients and relatives showed impaired downregulation of amygdala activity during reappraisal, but not during distraction, when compared with controls. This deficit was correlated with the habitual use of reappraisal. The negative connectivity of amygdala and orbitofrontal cortex (OFC) observed during reappraisal in controls was reversed in BD patients and relatives. There were no significant differences between BD patients and relatives. As being observed in BD patients and unaffected relatives, deficits in emotion regulation through reappraisal may represent heritable neurobiological abnormalities underlying BD. The neural mechanisms include impaired control of amygdala reactivity to emotional stimuli and dysfunctional connectivity of the amygdala to regulatory control regions in the OFC. These are, thus, important aspects of the neurobiological basis of increased vulnerability for BD. PMID:25603413

  19. Genetic disruption of CYP26B1 severely affects development of neural crest derived head structures, but does not compromise hindbrain patterning.

    PubMed

    Maclean, Glenn; Dollé, Pascal; Petkovich, Martin

    2009-03-01

    Cyp26b1 encodes a cytochrome-P450 enzyme that catabolizes retinoic acid (RA), a vitamin A derived signaling molecule. We have examined Cyp26b1(-/-) mice and report that mutants exhibit numerous abnormalities in cranial neural crest cell derived tissues. At embryonic day (E) 18.5 Cyp26b1(-/-) animals exhibit a truncated mandible, abnormal tooth buds, reduced ossification of calvaria, and are missing structures of the maxilla and nasal process. Some of these abnormalities may be due to defects in formation of Meckel's cartilage, which is truncated with an unfused distal region at E14.5 in mutant animals. Despite the severe malformations, we did not detect any abnormalities in rhombomere segmentation, or in patterning and migration of anterior hindbrain derived neural crest cells. Abnormal migration of neural crest cells toward the posterior branchial arches was observed, which may underlie defects in larynx and hyoid development. These data suggest different periods of sensitivity of anterior and posterior hindbrain neural crest derivatives to elevated levels of RA in the absence of CYP26B1. (c) 2009 Wiley-Liss, Inc.

  20. The implications of brain connectivity in the neuropsychology of autism

    PubMed Central

    Maximo, Jose O.; Cadena, Elyse J.; Kana, Rajesh K.

    2014-01-01

    Autism is a neurodevelopmental disorder that has been associated with atypical brain functioning. Functional connectivity MRI (fcMRI) studies examining neural networks in autism have seen an exponential rise over the last decade. Such investigations have led to characterization of autism as a distributed neural systems disorder. Studies have found widespread cortical underconnectivity, local overconnectivity, and mixed results suggesting disrupted brain connectivity as a potential neural signature of autism. In this review, we summarize the findings of previous fcMRI studies in autism with a detailed examination of their methodology, in order to better understand its potential and to delineate the pitfalls. We also address how a multimodal neuroimaging approach (incorporating different measures of brain connectivity) may help characterize the complex neurobiology of autism at a global level. Finally, we also address the potential of neuroimaging-based markers in assisting neuropsychological assessment of autism. The quest for a biomarker for autism is still ongoing, yet new findings suggest that aberrant brain connectivity may be a promising candidate. PMID:24496901

  1. Sex differences in autism: a resting-state fMRI investigation of functional brain connectivity in males and females.

    PubMed

    Alaerts, Kaat; Swinnen, Stephan P; Wenderoth, Nicole

    2016-06-01

    Autism spectrum disorders (ASD) are far more prevalent in males than in females. Little is known however about the differential neural expression of ASD in males and females. We used a resting-state fMRI-dataset comprising 42 males/42 females with ASD and 75 male/75 female typical-controls to examine whether autism-related alterations in intrinsic functional connectivity are similar or different in males and females, and particularly whether alterations reflect 'neural masculinization', as predicted by the Extreme Male Brain theory. Males and females showed a differential neural expression of ASD, characterized by highly consistent patterns of hypo-connectivity in males with ASD (compared to typical males), and hyper-connectivity in females with ASD (compared to typical females). Interestingly, patterns of hyper-connectivity in females with ASD reflected a shift towards the (high) connectivity levels seen in typical males (neural masculinization), whereas patterns of hypo-connectivity observed in males with ASD reflected a shift towards the (low) typical feminine connectivity patterns (neural feminization). Our data support the notion that ASD is a disorder of sexual differentiation rather than a disorder characterized by masculinization in both genders. Future work is needed to identify underlying factors such as sex hormonal alterations that drive these sex-specific neural expressions of ASD. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  2. Neural Mechanisms of Decision Making in Hoarding Disorder

    PubMed Central

    Tolin, David F.; Stevens, Michael C.; Villavicencio, Anna L.; Norberg, Melissa M.; Calhoun, Vince D.; Frost, Randy O.; Steketee, Gail; Rauch, Scott L.; Pearlson, Godfrey D.

    2012-01-01

    Context Hoarding disorder (HD), previously considered a subtype of obsessive-compulsive disorder (OCD), has been proposed as a unique diagnostic entity in DSM-5. Current models of HD emphasize problems of decision-making, attachment to possessions, and poor insight, whereas previous neuroimaging studies have suggested abnormalities in frontal brain regions. Objective To examine the neural mechanisms of impaired decision making in HD in patients with well-defined primary HD compared with patients with OCD and healthy control subjects (HCs). Design We compared neural activity among patients with HD, patients with OCD, and HCs during decisions to keep or discard personal possessions and control possessions from November 9, 2006, to August 13, 2010. Setting Private, not-for-profit hospital. Participants A total of 107 adults (43 with HD, 31 with OCD, and 33 HCs). Main Outcome Measures Neural activity as measured by functional magnetic resonance imaging in which actual real-time and binding decisions had to be made about whether to keep or discard possessions. Results Compared with participants with OCD and HC, participants with HD exhibited abnormal activity in the anterior cingulate cortex and insula that was stimulus dependent. Specifically, when deciding about items that did not belong to them, patients with HD showed relatively lower activity in these brain regions. However, when deciding about items that belonged to them, these regions showed excessive functional magnetic resonance imaging signals compared with the other 2 groups. These differences in neural function correlated significantly with hoarding severity and self-ratings of indecisiveness and “not just right” feelings among patients with HD and were unattributable to OCD or depressive symptoms. Conclusions Findings suggest a biphasic abnormality in anterior cingulate cortex and insula function in patients with HD related to problems in identifying the emotional significance of a stimulus, generating

  3. Neural mechanisms of decision making in hoarding disorder.

    PubMed

    Tolin, David F; Stevens, Michael C; Villavicencio, Anna L; Norberg, Melissa M; Calhoun, Vince D; Frost, Randy O; Steketee, Gail; Rauch, Scott L; Pearlson, Godfrey D

    2012-08-01

    Hoarding disorder (HD), previously considered a subtype of obsessive-compulsive disorder (OCD), has been proposed as a unique diagnostic entity in DSM-5. Current models of HD emphasize problems of decision-making, attachment to possessions, and poor insight, whereas previous neuroimaging studies have suggested abnormalities in frontal brain regions. To examine the neural mechanisms of impaired decision making in HD in patients with well-defined primary HD compared with patients with OCD and healthy control subjects (HCs). We compared neural activity among patients with HD, patients with OCD, and HCs during decisions to keep or discard personal possessions and control possessions from November 9, 2006, to August 13, 2010. Private, not-for-profit hospital. A total of 107 adults (43 with HD, 31 with OCD, and 33 HCs). Neural activity as measured by functional magnetic resonance imaging in which actual real-time and binding decisions had to be made about whether to keep or discard possessions. Compared with participants with OCD and HC, participants with HD exhibited abnormal activity in the anterior cingulate cortex and insula that was stimulus dependent. Specifically, when deciding about items that did not belong to them, patients with HD showed relatively lower activity in these brain regions. However, when deciding about items that belonged to them, these regions showed excessive functional magnetic resonance imaging signals compared with the other 2 groups. These differences in neural function correlated significantly with hoarding severity and self-ratings of indecisiveness and "not just right" feelings among patients with HD and were unattributable to OCD or depressive symptoms. Findings suggest a biphasic abnormality in anterior cingulate cortex and insula function in patients with HD related to problems in identifying the emotional significance of a stimulus, generating appropriate emotional response, or regulating affective state during decision making.

  4. Selective Manipulation of Neural Circuits.

    PubMed

    Park, Hong Geun; Carmel, Jason B

    2016-04-01

    Unraveling the complex network of neural circuits that form the nervous system demands tools that can manipulate specific circuits. The recent evolution of genetic tools to target neural circuits allows an unprecedented precision in elucidating their function. Here we describe two general approaches for achieving circuit specificity. The first uses the genetic identity of a cell, such as a transcription factor unique to a circuit, to drive expression of a molecule that can manipulate cell function. The second uses the spatial connectivity of a circuit to achieve specificity: one genetic element is introduced at the origin of a circuit and the other at its termination. When the two genetic elements combine within a neuron, they can alter its function. These two general approaches can be combined to allow manipulation of neurons with a specific genetic identity by introducing a regulatory gene into the origin or termination of the circuit. We consider the advantages and disadvantages of both these general approaches with regard to specificity and efficacy of the manipulations. We also review the genetic techniques that allow gain- and loss-of-function within specific neural circuits. These approaches introduce light-sensitive channels (optogenetic) or drug sensitive channels (chemogenetic) into neurons that form specific circuits. We compare these tools with others developed for circuit-specific manipulation and describe the advantages of each. Finally, we discuss how these tools might be applied for identification of the neural circuits that mediate behavior and for repair of neural connections.

  5. Neuromorphic device architectures with global connectivity through electrolyte gating

    NASA Astrophysics Data System (ADS)

    Gkoupidenis, Paschalis; Koutsouras, Dimitrios A.; Malliaras, George G.

    2017-05-01

    Information processing in the brain takes place in a network of neurons that are connected with each other by an immense number of synapses. At the same time, neurons are immersed in a common electrochemical environment, and global parameters such as concentrations of various hormones regulate the overall network function. This computational paradigm of global regulation, also known as homeoplasticity, has important implications in the overall behaviour of large neural ensembles and is barely addressed in neuromorphic device architectures. Here, we demonstrate the global control of an array of organic devices based on poly(3,4ethylenedioxythiophene):poly(styrene sulf) that are immersed in an electrolyte, a behaviour that resembles homeoplasticity phenomena of the neural environment. We use this effect to produce behaviour that is reminiscent of the coupling between local activity and global oscillations in the biological neural networks. We further show that the electrolyte establishes complex connections between individual devices, and leverage these connections to implement coincidence detection. These results demonstrate that electrolyte gating offers significant advantages for the realization of networks of neuromorphic devices of higher complexity and with minimal hardwired connectivity.

  6. Abnormal regional homogeneity and its correlations with personality in first-episode, treatment-naive somatization disorder.

    PubMed

    Song, Yan; Su, Qinji; Jiang, Muliang; Liu, Feng; Yao, Dapeng; Dai, Yi; Long, Liling; Yu, Miaoyu; Liu, Jianrong; Zhang, Zhikun; Zhang, Jian; Xiao, Changqing; Guo, Wenbin

    2015-08-01

    Structural and functional abnormalities of the default mode network (DMN) and their correlations with personality have been found in somatization disorder (SD). However, no study is conducted to identify regional neural activity and its correlations with personality in SD. In this study, regional homogeneity (ReHo) was applied to explore whether abnormal regional neural activity is present in patients with SD and its correlations with personality measured by Eysenck Personality Questionnaire (EPQ). Twenty-five first-episode, treatment-naive patients with SD and 28 sex-, age-, and education-matched healthy controls participated in the whole study. During the scanning, all subjects were instructed to lie still with their eyes closed and remain awake. A ReHo approach was employed to analyze the data. The SD group had a significantly increased ReHo in the left angular gyrus (AG) compared to healthy controls. The increased ReHo positively correlated to the neuroticism scores of EPQ (EPQ-N). No other correlations were detected between the ReHo values and other related factors, such as symptom severity and education level. Our results suggest that abnormal regional neural activity of the DMN may play a key role in SD with clinical implications and emphasize the importance of the DMN in the pathophysiological process of SD. Copyright © 2015 Elsevier B.V. All rights reserved.

  7. Augmented Indian hedgehog signaling in cranial neural crest cells leads to craniofacial abnormalities and dysplastic temporomandibular joint in mice

    PubMed Central

    Yang, Ling; Gu, Shuping; Ye, Wenduo; Song, Yingnan; Chen, YiPing

    2016-01-01

    Extensive studies have pinpointed the crucial role of Indian hedgehog (Ihh) signaling in the development of the appendicular skeleton and the essential function of Ihh in the formation of the temporomandibular joint (TMJ). In this study, we have investigated the effect of augmented Ihh signaling in TMJ development. We took a transgenic gain-of-function approach by overexpressing Ihh in the cranial neural crest (CNC) cells using a conditional Ihh transgenic allele and the Wnt1-Cre allele. We found that Wnt1-Cre-mediated tissue-specific overexpression of Ihh in the CNC lineage caused severe craniofacial abnormalities, including cleft lip/palate, encephalocele, anophthalmos, micrognathia, and defective TMJ development. In the mutant TMJ, the glenoid fossa was completely absent, whereas the condyle and the articular disc appeared relatively normal with slightly delayed chondrocyte differentiation. Our findings thus demonstrate that augmented Ihh signaling is detrimental to craniofacial development, and that finely tuned Ihh signaling is critical for TMJ formation. Our results also provide additional evidence that the development of the condyle and articular disc is independent of the glenoid fossa. PMID:26553654

  8. Neural-Network-Development Program

    NASA Technical Reports Server (NTRS)

    Phillips, Todd A.

    1993-01-01

    NETS, software tool for development and evaluation of neural networks, provides simulation of neural-network algorithms plus computing environment for development of such algorithms. Uses back-propagation learning method for all of networks it creates. Enables user to customize patterns of connections between layers of network. Also provides features for saving, during learning process, values of weights, providing more-precise control over learning process. Written in ANSI standard C language. Machine-independent version (MSC-21588) includes only code for command-line-interface version of NETS 3.0.

  9. Is the ADHD brain wired differently? A review on structural and functional connectivity in attention deficit hyperactivity disorder.

    PubMed

    Konrad, Kerstin; Eickhoff, Simon B

    2010-06-01

    In recent years, a change in perspective in etiological models of attention deficit hyperactivity disorder (ADHD) has occurred in concordance with emerging concepts in other neuropsychiatric disorders such as schizophrenia and autism. These models shift the focus of the assumed pathology from regional brain abnormalities to dysfunction in distributed network organization. In the current contribution, we report findings from functional connectivity studies during resting and task states, as well as from studies on structural connectivity using diffusion tensor imaging, in subjects with ADHD. Although major methodological limitations in analyzing connectivity measures derived from noninvasive in vivo neuroimaging still exist, there is convergent evidence for white matter pathology and disrupted anatomical connectivity in ADHD. In addition, dysfunctional connectivity during rest and during cognitive tasks has been demonstrated. However, the causality between disturbed white matter architecture and cortical dysfunction remains to be evaluated. Both genetic and environmental factors might contribute to disruptions in interactions between different brain regions. Stimulant medication not only modulates regionally specific activation strength but also normalizes dysfunctional connectivity, pointing to a predominant network dysfunction in ADHD. By combining a longitudinal approach with a systems perspective in ADHD in the future, it might be possible to identify at which stage during development disruptions in neural networks emerge and to delineate possible new endophenotypes of ADHD. (c) 2010 Wiley-Liss, Inc.

  10. Neural processing of reward and punishment in young people at increased familial risk of depression.

    PubMed

    McCabe, Ciara; Woffindale, Caroline; Harmer, Catherine J; Cowen, Philip J

    2012-10-01

    Abnormalities in the neural representation of rewarding and aversive stimuli have been well-described in patients with acute depression, and we previously found abnormal neural responses to rewarding and aversive sight and taste stimuli in recovered depressed patients. The aim of the present study was to determine whether similar abnormalities might be present in young people at increased familial risk of depression but with no personal history of mood disorder. We therefore used functional magnetic resonance imaging to examine the neural responses to pleasant and aversive sights and tastes in 25 young people (16-21 years of age) with a biological parent with depression and 25 age- and gender-matched control subjects. We found that, relative to the control subjects, participants with a parental history of depression showed diminished responses in the orbitofrontal cortex to rewarding stimuli, whereas activations to aversive stimuli were increased in the lateral orbitofrontal cortex and insula. In anterior cingulate cortex the at-risk group showed blunted neural responses to both rewarding and aversive stimuli. Our findings suggest that young people at increased familial risk of depression have altered neural representation of reward and punishment, particularly in cortical regions linked to the use of positive and negative feedback to guide adaptive behavior. Copyright © 2012 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  11. The Role of Corpus Callosum Development in Functional Connectivity and Cognitive Processing

    PubMed Central

    Findlay, Anne M.; Honma, Susanne; Jeremy, Rita J.; Strominger, Zoe; Bukshpun, Polina; Wakahiro, Mari; Brown, Warren S.; Paul, Lynn K.; Barkovich, A. James; Mukherjee, Pratik; Nagarajan, Srikantan S.; Sherr, Elliott H.

    2012-01-01

    The corpus callosum is hypothesized to play a fundamental role in integrating information and mediating complex behaviors. Here, we demonstrate that lack of normal callosal development can lead to deficits in functional connectivity that are related to impairments in specific cognitive domains. We examined resting-state functional connectivity in individuals with agenesis of the corpus callosum (AgCC) and matched controls using magnetoencephalographic imaging (MEG-I) of coherence in the alpha (8–12 Hz), beta (12–30 Hz) and gamma (30–55 Hz) bands. Global connectivity (GC) was defined as synchronization between a region and the rest of the brain. In AgCC individuals, alpha band GC was significantly reduced in the dorsolateral pre-frontal (DLPFC), posterior parietal (PPC) and parieto-occipital cortices (PO). No significant differences in GC were seen in either the beta or gamma bands. We also explored the hypothesis that, in AgCC, this regional reduction in functional connectivity is explained primarily by a specific reduction in interhemispheric connectivity. However, our data suggest that reduced connectivity in these regions is driven by faulty coupling in both inter- and intrahemispheric connectivity. We also assessed whether the degree of connectivity correlated with behavioral performance, focusing on cognitive measures known to be impaired in AgCC individuals. Neuropsychological measures of verbal processing speed were significantly correlated with resting-state functional connectivity of the left medial and superior temporal lobe in AgCC participants. Connectivity of DLPFC correlated strongly with performance on the Tower of London in the AgCC cohort. These findings indicate that the abnormal callosal development produces salient but selective (alpha band only) resting-state functional connectivity disruptions that correlate with cognitive impairment. Understanding the relationship between impoverished functional connectivity and cognition is a key step

  12. Dissociated functional connectivity profiles for motor and attention deficits in acute right-hemisphere stroke

    PubMed Central

    Ramsey, Lenny; Rengachary, Jennifer; Zinn, Kristi; Siegel, Joshua S.; Metcalf, Nicholas V.; Strube, Michael J.; Snyder, Abraham Z.; Corbetta, Maurizio; Shulman, Gordon L.

    2016-01-01

    Strokes often cause multiple behavioural deficits that are correlated at the population level. Here, we show that motor and attention deficits are selectively associated with abnormal patterns of resting state functional connectivity in the dorsal attention and motor networks. We measured attention and motor deficits in 44 right hemisphere-damaged patients with a first-time stroke at 1–2 weeks post-onset. The motor battery included tests that evaluated deficits in both upper and lower extremities. The attention battery assessed both spatial and non-spatial attention deficits. Summary measures for motor and attention deficits were identified through principal component analyses on the raw behavioural scores. Functional connectivity in structurally normal cortex was estimated based on the temporal correlation of blood oxygenation level-dependent signals measured at rest with functional magnetic resonance imaging. Any correlation between motor and attention deficits and between functional connectivity in the dorsal attention network and motor networks that might spuriously affect the relationship between each deficit and functional connectivity was statistically removed. We report a double dissociation between abnormal functional connectivity patterns and attention and motor deficits, respectively. Attention deficits were significantly more correlated with abnormal interhemispheric functional connectivity within the dorsal attention network than motor networks, while motor deficits were significantly more correlated with abnormal interhemispheric functional connectivity patterns within the motor networks than dorsal attention network. These findings indicate that functional connectivity patterns in structurally normal cortex following a stroke link abnormal physiology in brain networks to the corresponding behavioural deficits. PMID:27225794

  13. Face off against ROS: Tcof1/Treacle safeguards neuroepithelial cells and progenitor neural crest cells from oxidative stress during craniofacial development

    PubMed Central

    Sakai, Daisuke; Trainor, Paul A.

    2016-01-01

    One-third of all congenital birth defects affect the head and face, and most craniofacial anomalies are considered to arise through defects in the development of cranial neural crest cells. Cranial neural crest cells give rise to the majority of craniofacial bones, cartilages and connective tissues. Therefore understanding the events that control normal cranial neural crest and subsequent craniofacial development is important for elucidating the pathogenetic mechanisms of craniofacial anomalies and for the exploring potential therapeutic avenues for their prevention. Treacher Collins syndrome (TCS) is a congenital disorder characterized by severe craniofacial anomalies. An animal model of TCS, generated through mutation of Tcof1, the mouse (Mus musculus) homologue of the gene primarily mutated in association with TCS in humans, has recently revealed significant insights into the pathogenesis of TCS. Apoptotic elimination of neuroepithelial cells including neural crest cells is the primary cause of craniofacial defects in Tcof1 mutant embryos. However our understanding of the mechanisms that induce tissue-specific apoptosis remains incomplete. In this review, we describe recent advances in our understanding of the pathogenesis TCS. Furthermore, we discuss the role of Tcof1 in normal embryonic development, the correlation between genetic and environmental factors on the severity of craniofacial abnormalities, and the prospect for prenatal prevention of craniofacial anomalies. PMID:27481486

  14. The role of anxiety in stuttering: Evidence from functional connectivity.

    PubMed

    Yang, Yang; Jia, Fanlu; Siok, Wai Ting; Tan, Li Hai

    2017-03-27

    Persistent developmental stuttering is a neurologically based speech disorder associated with cognitive-linguistic, motor and emotional abnormalities. Previous studies investigating the relationship between anxiety and stuttering have yielded mixed results, but it has not yet been examined whether anxiety influences brain activity underlying stuttering. Here, using functional magnetic resonance imaging (fMRI), we investigated the functional connectivity associated with state anxiety in a syllable repetition task, and trait anxiety during rest in adults who stutter (N=19) and fluent controls (N=19). During the speech task, people who stutter (PWS) showed increased functional connectivity of the right amygdala with the prefrontal gyrus (the left ventromedial frontal gyrus and right middle frontal gyrus) and the left insula compared to controls. During rest, PWS showed stronger functional connectivity between the right hippocampus and the left orbital frontal gyrus, and between the left hippocampus and left motor areas than controls. Taken together, our results suggest aberrant bottom-up and/or top-down interactions for anxiety regulation, which might be responsible for the higher level of state anxiety during speech and for the anxiety-prone trait in PWS. To our knowledge, this is the first study to examine the neural underpinnings of anxiety in PWS, thus yielding new insight into the causes of stuttering which might aid strategies for the diagnosis and treatment of stuttering. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

  15. Reduced Synchronization Persistence in Neural Networks Derived from Atm-Deficient Mice

    PubMed Central

    Levine-Small, Noah; Yekutieli, Ziv; Aljadeff, Jonathan; Boccaletti, Stefano; Ben-Jacob, Eshel; Barzilai, Ari

    2011-01-01

    Many neurodegenerative diseases are characterized by malfunction of the DNA damage response. Therefore, it is important to understand the connection between system level neural network behavior and DNA. Neural networks drawn from genetically engineered animals, interfaced with micro-electrode arrays allowed us to unveil connections between networks’ system level activity properties and such genome instability. We discovered that Atm protein deficiency, which in humans leads to progressive motor impairment, leads to a reduced synchronization persistence compared to wild type synchronization, after chemically imposed DNA damage. Not only do these results suggest a role for DNA stability in neural network activity, they also establish an experimental paradigm for empirically determining the role a gene plays on the behavior of a neural network. PMID:21519382

  16. The neural basis of trait self-esteem revealed by the amplitude of low-frequency fluctuations and resting state functional connectivity

    PubMed Central

    Pan, Weigang; Liu, Congcong; Yang, Qian; Gu, Yan; Yin, Shouhang

    2016-01-01

    Self-esteem is an affective, self-evaluation of oneself and has a significant effect on mental and behavioral health. Although research has focused on the neural substrates of self-esteem, little is known about the spontaneous brain activity that is associated with trait self-esteem (TSE) during the resting state. In this study, we used the resting-state functional magnetic resonance imaging (fMRI) signal of the amplitude of low-frequency fluctuations (ALFFs) and resting state functional connectivity (RSFC) to identify TSE-related regions and networks. We found that a higher level of TSE was associated with higher ALFFs in the left ventral medial prefrontal cortex (vmPFC) and lower ALFFs in the left cuneus/lingual gyrus and right lingual gyrus. RSFC analyses revealed that the strengths of functional connectivity between the left vmPFC and bilateral hippocampus were positively correlated with TSE; however, the connections between the left vmPFC and right inferior frontal gyrus and posterior superior temporal sulcus were negatively associated with TSE. Furthermore, the strengths of functional connectivity between the left cuneus/lingual gyrus and right dorsolateral prefrontal cortex and anterior cingulate cortex were positively related to TSE. These findings indicate that TSE is linked to core regions in the default mode network and social cognition network, which is involved in self-referential processing, autobiographical memory and social cognition. PMID:26400859

  17. Functional brain connectivity when cooperation fails.

    PubMed

    Balconi, Michela; Vanutelli, Maria Elide; Gatti, Laura

    2018-06-01

    Functional connectivity during cooperative actions is an important topic in social neuroscience that has yet to be answered. Here, we examined the effects of administration of (fictitious) negative social feedback in relation to cooperative capabilities. Cognitive performance and neural activation underlying the execution of joint actions was recorded with functional near-infrared spectroscopy (fNIRS) on prefrontal regions during a task where pairs of participants received negative feedback after their joint action. Performance (error rates (ERs) and response times (RTs)) and intra- and inter-brain connectivity indices were computed, along with the ConIndex (inter-brain/intra-brain connectivity). Finally, correlational measures were considered to assess the relation between these different measures. Results showed that the negative feedback was able to modulate participants' responses for both behavioral and neural components. Cognitive performance was decreased after the feedback. Moreover, decreased inter-brain connectivity and increased intra-brain connectivity was induced by the feedback, whereas the cooperative task pre-feedback condition was able to increase the brain-to-brain coupling, mainly localized within the dorsolateral prefrontal cortex (DLPFC). Finally, the presence of significant correlations between RTs and inter-brain connectivity revealed that ineffective joint action produces the worst cognitive performance and a more 'individual strategy' for brain activity, limiting the inter-brain connectivity. The present study provides a significant contribution to the identification of patterns of intra- and inter-brain functional connectivity when negative social reinforcement is provided in relation to cooperative actions. Copyright © 2018 Elsevier Inc. All rights reserved.

  18. Patterns of neural response to emotive stimuli distinguish the different symptom dimensions of obsessive-compulsive disorder.

    PubMed

    Phillips, Mary L; Mataix-Cols, David

    2004-04-01

    Despite its heterogeneous symptomatology, obsessive-compulsive disorder (OCD) is currently conceptualized as a unitary diagnostic entity. Recent factor-analytic studies have identified several OCD symptom dimensions that are associated with different demographic variables, comorbidity, patterns of genetic transmission, and treatment response. Functional abnormalities in neural systems important for emotion perception, including the orbitofrontal cortex, lateral prefrontal cortex, anterior cingulate gyrus, and limbic regions, have been reported in OCD. In this review, we discuss the extent to which neurobiological markers may distinguish these different symptom dimensions and whether specific symptom dimensions, such as contamination/washing, are associated with abnormalities in emotion and, in particular, disgust, perception in OCD. Also discussed are findings that indicate that anxiety can be induced in healthy volunteers in response to OCD symptom-related material, and that associated increases in activity within neural systems important for emotion perception occur to washing- and hoarding-related material in particular in these subjects. Further examination of neural responses during provocation of different symptom dimensions in OCD patients will help determine the extent to which specific abnormalities in neural systems underlying emotion perception are associated with different symptom dimensions and predict treatment response in OCD.

  19. [Neural mechanism underlying autistic savant and acquired savant syndrome].

    PubMed

    Takahata, Keisuke; Kato, Motoichiro

    2008-07-01

    , especially that of the prefrontal cortex and the posterior regions of the brain. (3) Autistic models, including those based on weak central coherence theory (Frith, 1989), that focus on how savant skills emerge from an autistic brain. Based on recent neuroimaging studies of ASD, Just et al. (2004) suggested the underconnectivity theory, which emphasizes the disruption of long-range connectivity and the relative intact or even more enhanced local connectivity in the autistic brain. All the models listed above have certain advantages and shortcomings. At the end of this review, we propose another integrative model of savant syndrome. In this model, we predict an altered balance of local/global connectivity patterns that contribute to an altered functional segregation/integration ratio. In particular, we emphasize the crucial role played by the disruption of global connectivity in a parallel distributed cortical network, which might result in impairment in integrated cognitive processing, such as impairment in executive function and social cognition. On the other hand, the reduced inter-regional collaboration could lead to a disinhibitory enhancement of neural activity and connectivity in local cortical regions. In addition, enhanced connectivity in the local brain regions is partly due to the abnormal organization of the cortical network as a result of developmental and pathological states. This enhanced local connectivity results in the specialization and facilitation of low-level cognitive processing. The disruption of connectivity between the prefrontal cortex and other regions is considered to be a particularly important factor because the prefrontal region shows the most influential inhibitory control on other cortical areas. We propose that these neural mechanisms as the underlying causes for the emergence of savant ability in ASD and FTD patients.

  20. Neural Modularity Helps Organisms Evolve to Learn New Skills without Forgetting Old Skills

    PubMed Central

    Ellefsen, Kai Olav; Mouret, Jean-Baptiste; Clune, Jeff

    2015-01-01

    A long-standing goal in artificial intelligence is creating agents that can learn a variety of different skills for different problems. In the artificial intelligence subfield of neural networks, a barrier to that goal is that when agents learn a new skill they typically do so by losing previously acquired skills, a problem called catastrophic forgetting. That occurs because, to learn the new task, neural learning algorithms change connections that encode previously acquired skills. How networks are organized critically affects their learning dynamics. In this paper, we test whether catastrophic forgetting can be reduced by evolving modular neural networks. Modularity intuitively should reduce learning interference between tasks by separating functionality into physically distinct modules in which learning can be selectively turned on or off. Modularity can further improve learning by having a reinforcement learning module separate from sensory processing modules, allowing learning to happen only in response to a positive or negative reward. In this paper, learning takes place via neuromodulation, which allows agents to selectively change the rate of learning for each neural connection based on environmental stimuli (e.g. to alter learning in specific locations based on the task at hand). To produce modularity, we evolve neural networks with a cost for neural connections. We show that this connection cost technique causes modularity, confirming a previous result, and that such sparsely connected, modular networks have higher overall performance because they learn new skills faster while retaining old skills more and because they have a separate reinforcement learning module. Our results suggest (1) that encouraging modularity in neural networks may help us overcome the long-standing barrier of networks that cannot learn new skills without forgetting old ones, and (2) that one benefit of the modularity ubiquitous in the brains of natural animals might be to

  1. Neural modularity helps organisms evolve to learn new skills without forgetting old skills.

    PubMed

    Ellefsen, Kai Olav; Mouret, Jean-Baptiste; Clune, Jeff

    2015-04-01

    A long-standing goal in artificial intelligence is creating agents that can learn a variety of different skills for different problems. In the artificial intelligence subfield of neural networks, a barrier to that goal is that when agents learn a new skill they typically do so by losing previously acquired skills, a problem called catastrophic forgetting. That occurs because, to learn the new task, neural learning algorithms change connections that encode previously acquired skills. How networks are organized critically affects their learning dynamics. In this paper, we test whether catastrophic forgetting can be reduced by evolving modular neural networks. Modularity intuitively should reduce learning interference between tasks by separating functionality into physically distinct modules in which learning can be selectively turned on or off. Modularity can further improve learning by having a reinforcement learning module separate from sensory processing modules, allowing learning to happen only in response to a positive or negative reward. In this paper, learning takes place via neuromodulation, which allows agents to selectively change the rate of learning for each neural connection based on environmental stimuli (e.g. to alter learning in specific locations based on the task at hand). To produce modularity, we evolve neural networks with a cost for neural connections. We show that this connection cost technique causes modularity, confirming a previous result, and that such sparsely connected, modular networks have higher overall performance because they learn new skills faster while retaining old skills more and because they have a separate reinforcement learning module. Our results suggest (1) that encouraging modularity in neural networks may help us overcome the long-standing barrier of networks that cannot learn new skills without forgetting old ones, and (2) that one benefit of the modularity ubiquitous in the brains of natural animals might be to

  2. Prediction of forced expiratory volume in pulmonary function test using radial basis neural networks and k-means clustering.

    PubMed

    Manoharan, Sujatha C; Ramakrishnan, Swaminathan

    2009-10-01

    In this work, prediction of forced expiratory volume in pulmonary function test, carried out using spirometry and neural networks is presented. The pulmonary function data were recorded from volunteers using commercial available flow volume spirometer in standard acquisition protocol. The Radial Basis Function neural networks were used to predict forced expiratory volume in 1 s (FEV1) from the recorded flow volume curves. The optimal centres of the hidden layer of radial basis function were determined by k-means clustering algorithm. The performance of the neural network model was evaluated by computing their prediction error statistics of average value, standard deviation, root mean square and their correlation with the true data for normal, restrictive and obstructive cases. Results show that the adopted neural networks are capable of predicting FEV1 in both normal and abnormal cases. Prediction accuracy was more in obstructive abnormality when compared to restrictive cases. It appears that this method of assessment is useful in diagnosing the pulmonary abnormalities with incomplete data and data with poor recording.

  3. Neural Differentiation of Incorrectly Predicted Memories.

    PubMed

    Kim, Ghootae; Norman, Kenneth A; Turk-Browne, Nicholas B

    2017-02-22

    When an item is predicted in a particular context but the prediction is violated, memory for that item is weakened (Kim et al., 2014). Here, we explore what happens when such previously mispredicted items are later reencountered. According to prior neural network simulations, this sequence of events-misprediction and subsequent restudy-should lead to differentiation of the item's neural representation from the previous context (on which the misprediction was based). Specifically, misprediction weakens connections in the representation to features shared with the previous context and restudy allows new features to be incorporated into the representation that are not shared with the previous context. This cycle of misprediction and restudy should have the net effect of moving the item's neural representation away from the neural representation of the previous context. We tested this hypothesis using human fMRI by tracking changes in item-specific BOLD activity patterns in the hippocampus, a key structure for representing memories and generating predictions. In left CA2/3/DG, we found greater neural differentiation for items that were repeatedly mispredicted and restudied compared with items from a control condition that was identical except without misprediction. We also measured prediction strength in a trial-by-trial fashion and found that greater misprediction for an item led to more differentiation, further supporting our hypothesis. Therefore, the consequences of prediction error go beyond memory weakening. If the mispredicted item is restudied, the brain adaptively differentiates its memory representation to improve the accuracy of subsequent predictions and to shield it from further weakening. SIGNIFICANCE STATEMENT Competition between overlapping memories leads to weakening of nontarget memories over time, making it easier to access target memories. However, a nontarget memory in one context might become a target memory in another context. How do such

  4. Neural Mechanisms of Emotion.

    ERIC Educational Resources Information Center

    Derryberry, Douglas; Tucker, Don M.

    1992-01-01

    Views neural mechanisms of emotion from an evolutionary perspective, seeing them distributed across the brainstem, limbic, paralimbic, and neocortical regions. Discusses descending and ascending connections among these levels in relation to three types of emotional processes: peripheral effects on patterned bodily responses, central effects on…

  5. Patterns of Neural Connectivity during an Attention Bias Task Moderate Associations between Early Childhood Temperament and Internalizing Symptoms in Young Adulthood

    PubMed Central

    Hardee, Jillian E.; Benson, Brenda E.; Bar-Haim, Yair; Mogg, Karin; Bradley, Brendan P; Chen, Gang; Britton, Jennifer C.; Ernst, Monique; Fox, Nathan A.; Pine, Daniel S.; Pérez-Edgar, Koraly

    2013-01-01

    Background Biased attention to threat is found in both individuals with anxiety symptoms and children with the childhood temperament of behavioral inhibition (BI). Although perturbed fronto-amygdala function is implicated in biased attention among anxious individuals, no work has examined the neural correlates of attention biases in BI. Work in this area may clarify underlying mechanisms for anxiety in a sample at risk for internalizing disorders. We examined the relations among early childhood BI, fronto-amygdala connectivity during an attention bias task in young adulthood, and internalizing symptoms, assessed in young adulthood. Methods Children were assessed for BI at multiple age points from infancy through age seven. Based on a composite of observational and maternal report data, we selected 21 young adults classified as having a history of BI and 23 classified as non-BI for this study (N=44). Participants completed an event-related fMRI attention-bias task involving threat (angry faces) and neutral trials. Internalizing symptoms were assessed by self-report and diagnostic interviews. Results The young adults characterized in childhood with BI exhibited greater strength in threat-related connectivity than non-behaviorally inhibited young adults. Between-group differences manifested in connections between the amygdala and two frontal regions: dorsolateral prefrontal cortex and anterior insula. Amygdala-insula connectivity also interacted with childhood BI to predict young adult internalizing symptoms. Conclusions BI during early childhood predicts differences as young adults in threat and attention-related fronto-amygdala connectivity. Connectivity strength, in turn, moderated the relations between early BI and later psychopathology. PMID:23489415

  6. Neural substrates of context- and person-dependent altruistic punishment.

    PubMed

    Wang, Lili; Lu, Xiaping; Gu, Ruolei; Zhu, Ruida; Xu, Rui; Broster, Lucas S; Feng, Chunliang

    2017-11-01

    Human altruistic behaviors are heterogeneous across both contexts and people, whereas the neural signatures underlying the heterogeneity remain to be elucidated. To address this issue, we examined the neural signatures underlying the context- and person-dependent altruistic punishment, conjoining event-related fMRI with both task-based and resting-state functional connectivity (RSFC). Acting as an impartial third party, participants decided how to punish norm violators either alone or in the presence of putative others. We found that the presence of others decreased altruistic punishment due to diffusion of responsibility. Those behavioral effects paralleled altered neural responses in the dorsal anterior cingulate cortex (dACC) and putamen. Further, we identified modulation of responsibility diffusion on task-based functional connectivity of dACC with the brain regions implicated in reward processing (i.e., posterior cingulate cortex and amygdala/orbital frontal cortex). Finally, the RSFC results revealed that (i) increased intrinsic connectivity strengths of the putamen with temporoparietal junction and dorsolateral PFC were associated with attenuated responsibility diffusion in altruistic punishment and (ii) increased putamen-dorsomedial PFC connectivity strengths were associated with reduced responsibility diffusion in self-reported responsibility. Taken together, our findings elucidate the context- and person-dependent altruistic behaviors as well as associated neural substrates and thus provide a potential neurocognitive mechanism of heterogeneous human altruistic behaviors. Hum Brain Mapp 38:5535-5550, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  7. The Evolution and Development of Neural Superposition

    PubMed Central

    Agi, Egemen; Langen, Marion; Altschuler, Steven J.; Wu, Lani F.; Zimmermann, Timo

    2014-01-01

    Visual systems have a rich history as model systems for the discovery and understanding of basic principles underlying neuronal connectivity. The compound eyes of insects consist of up to thousands of small unit eyes that are connected by photoreceptor axons to set up a visual map in the brain. The photoreceptor axon terminals thereby represent neighboring points seen in the environment in neighboring synaptic units in the brain. Neural superposition is a special case of such a wiring principle, where photoreceptors from different unit eyes that receive the same input converge upon the same synaptic units in the brain. This wiring principle is remarkable, because each photoreceptor in a single unit eye receives different input and each individual axon, among thousands others in the brain, must be sorted together with those few axons that have the same input. Key aspects of neural superposition have been described as early as 1907. Since then neuroscientists, evolutionary and developmental biologists have been fascinated by how such a complicated wiring principle could evolve, how it is genetically encoded, and how it is developmentally realized. In this review article, we will discuss current ideas about the evolutionary origin and developmental program of neural superposition. Our goal is to identify in what way the special case of neural superposition can help us answer more general questions about the evolution and development of genetically “hard-wired” synaptic connectivity in the brain. PMID:24912630

  8. The evolution and development of neural superposition.

    PubMed

    Agi, Egemen; Langen, Marion; Altschuler, Steven J; Wu, Lani F; Zimmermann, Timo; Hiesinger, Peter Robin

    2014-01-01

    Visual systems have a rich history as model systems for the discovery and understanding of basic principles underlying neuronal connectivity. The compound eyes of insects consist of up to thousands of small unit eyes that are connected by photoreceptor axons to set up a visual map in the brain. The photoreceptor axon terminals thereby represent neighboring points seen in the environment in neighboring synaptic units in the brain. Neural superposition is a special case of such a wiring principle, where photoreceptors from different unit eyes that receive the same input converge upon the same synaptic units in the brain. This wiring principle is remarkable, because each photoreceptor in a single unit eye receives different input and each individual axon, among thousands others in the brain, must be sorted together with those few axons that have the same input. Key aspects of neural superposition have been described as early as 1907. Since then neuroscientists, evolutionary and developmental biologists have been fascinated by how such a complicated wiring principle could evolve, how it is genetically encoded, and how it is developmentally realized. In this review article, we will discuss current ideas about the evolutionary origin and developmental program of neural superposition. Our goal is to identify in what way the special case of neural superposition can help us answer more general questions about the evolution and development of genetically "hard-wired" synaptic connectivity in the brain.

  9. The neural circuits for arithmetic principles.

    PubMed

    Liu, Jie; Zhang, Han; Chen, Chuansheng; Chen, Hui; Cui, Jiaxin; Zhou, Xinlin

    2017-02-15

    Arithmetic principles are the regularities underlying arithmetic computation. Little is known about how the brain supports the processing of arithmetic principles. The current fMRI study examined neural activation and functional connectivity during the processing of verbalized arithmetic principles, as compared to numerical computation and general language processing. As expected, arithmetic principles elicited stronger activation in bilateral horizontal intraparietal sulcus and right supramarginal gyrus than did language processing, and stronger activation in left middle temporal lobe and left orbital part of inferior frontal gyrus than did computation. In contrast, computation elicited greater activation in bilateral horizontal intraparietal sulcus (extending to posterior superior parietal lobule) than did either arithmetic principles or language processing. Functional connectivity analysis with the psychophysiological interaction approach (PPI) showed that left temporal-parietal (MTG-HIPS) connectivity was stronger during the processing of arithmetic principle and language than during computation, whereas parietal-occipital connectivities were stronger during computation than during the processing of arithmetic principles and language. Additionally, the left fronto-parietal (orbital IFG-HIPS) connectivity was stronger during the processing of arithmetic principles than during computation. The results suggest that verbalized arithmetic principles engage a neural network that overlaps but is distinct from the networks for computation and language processing. Copyright © 2016 Elsevier Inc. All rights reserved.

  10. Effects of behavioral activation on default mode network connectivity in subthreshold depression: A preliminary resting-state fMRI study.

    PubMed

    Yokoyama, Satoshi; Okamoto, Yasumasa; Takagaki, Koki; Okada, Go; Takamura, Masahiro; Mori, Asako; Shiota, Syouichi; Ichikawa, Naho; Jinnin, Ran; Yamawaki, Shigeto

    2018-02-01

    Subthreshold depression is a risk factor for major depressive disorder, and it is known to have a negative impact on quality of life (QOL). Although behavioral activation, which is one type of cognitive behavioral therapy, is an effective psychological intervention for subthreshold depression, neural mechanisms of behavioral activation are unclear. Enhanced functional connectivity between default mode network (DMN) and the other regions has been demonstrated in participants with subthreshold depression. The purpose of this study was to examine the effects of behavioral activation on DMN abnormalities by using resting-state functional MRI (rs-fMRI). Participants with subthreshold depression (N =40) were randomly assigned to either an intervention group or a non-intervention group. They were scanned using rs-fMRI before and after the intervention. Independent component analysis indicated three subnetworks of the DMN. Analyzing intervention effects on functional connectivity of each subnetwork indicated that connectivity of the anterior DMN subnetwork with the dorsal anterior cingulate was reduced after the intervention. Moreover, this reduction was correlated with an increase in health-related QOL. We did not compare the findings with healthy participants. Further research should be conducted by including healthy controls to verify the results of this study. Mechanisms of behavioral activation might be related to enhanced ability to independently use the dACC and the DMN, which increases an attention control to positive external stimuli. This is the first study to investigate neural mechanisms of behavioral activation using rs-fMRI. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. Functional neural networks underlying response inhibition in adolescents and adults.

    PubMed

    Stevens, Michael C; Kiehl, Kent A; Pearlson, Godfrey D; Calhoun, Vince D

    2007-07-19

    This study provides the first description of neural network dynamics associated with response inhibition in healthy adolescents and adults. Functional and effective connectivity analyses of whole brain hemodynamic activity elicited during performance of a Go/No-Go task were used to identify functionally integrated neural networks and characterize their causal interactions. Three response inhibition circuits formed a hierarchical, inter-dependent system wherein thalamic modulation of input to premotor cortex by fronto-striatal regions led to response suppression. Adolescents differed from adults in the degree of network engagement, regional fronto-striatal-thalamic connectivity, and network dynamics. We identify and characterize several age-related differences in the function of neural circuits that are associated with behavioral performance changes across adolescent development.

  12. Structure-function relationships during segregated and integrated network states of human brain functional connectivity.

    PubMed

    Fukushima, Makoto; Betzel, Richard F; He, Ye; van den Heuvel, Martijn P; Zuo, Xi-Nian; Sporns, Olaf

    2018-04-01

    Structural white matter connections are thought to facilitate integration of neural information across functionally segregated systems. Recent studies have demonstrated that changes in the balance between segregation and integration in brain networks can be tracked by time-resolved functional connectivity derived from resting-state functional magnetic resonance imaging (rs-fMRI) data and that fluctuations between segregated and integrated network states are related to human behavior. However, how these network states relate to structural connectivity is largely unknown. To obtain a better understanding of structural substrates for these network states, we investigated how the relationship between structural connectivity, derived from diffusion tractography, and functional connectivity, as measured by rs-fMRI, changes with fluctuations between segregated and integrated states in the human brain. We found that the similarity of edge weights between structural and functional connectivity was greater in the integrated state, especially at edges connecting the default mode and the dorsal attention networks. We also demonstrated that the similarity of network partitions, evaluated between structural and functional connectivity, increased and the density of direct structural connections within modules in functional networks was elevated during the integrated state. These results suggest that, when functional connectivity exhibited an integrated network topology, structural connectivity and functional connectivity were more closely linked to each other and direct structural connections mediated a larger proportion of neural communication within functional modules. Our findings point out the possibility of significant contributions of structural connections to integrative neural processes underlying human behavior.

  13. Neural autonomic control in orthostatic intolerance.

    PubMed

    Furlan, Raffaello; Barbic, Franca; Casella, Francesco; Severgnini, Giorgio; Zenoni, Luca; Mercieri, Angelo; Mangili, Ruggero; Costantino, Giorgio; Porta, Alberto

    2009-10-01

    Inability to maintain the upright position is manifested by a number of symptoms shared by either human pathophysiology and conditions following weightlessness or bed rest. Alterations of the neural sympathetic cardiovascular control have been suggested to be one of the potential underlying etiopathogenetic mechanisms in these conditions. We hypothesize that the study of the autonomic profile of human orthostatic intolerance syndromes may furnish a valuable insight into the complexity of the sympathetic alterations leading to a reduced gravitational tolerance. In the present paper we describe abnormalities both in the magnitude and in the pattern of the sympathetic neural firing observed in patients affected by orthostatic intolerance, attending the upright position. Also, we discuss similarity and differences in the neural sympathetic mechanisms regulating the cardiovascular system during the gravitational stimulus both in clinical syndromes and in subjects returning from space.

  14. Aberrant cerebellar connectivity in motor and association networks in schizophrenia

    PubMed Central

    Shinn, Ann K.; Baker, Justin T.; Lewandowski, Kathryn E.; Öngür, Dost; Cohen, Bruce M.

    2015-01-01

    Schizophrenia is a devastating illness characterized by disturbances in multiple domains. The cerebellum is involved in both motor and non-motor functions, and the “cognitive dysmetria” and “dysmetria of thought” models propose that abnormalities of the cerebellum may contribute to schizophrenia signs and symptoms. The cerebellum and cerebral cortex are reciprocally connected via a modular, closed-loop network architecture, but few schizophrenia neuroimaging studies have taken into account the topographical and functional heterogeneity of the cerebellum. In this study, using a previously defined 17-network cerebral cortical parcellation system as the basis for our functional connectivity seeds, we systematically investigated connectivity abnormalities within the cerebellum of 44 schizophrenia patients and 28 healthy control participants. We found selective alterations in cerebro-cerebellar functional connectivity. Specifically, schizophrenia patients showed decreased cerebro-cerebellar functional connectivity in higher level association networks (ventral attention, salience, control, and default mode networks) relative to healthy control participants. Schizophrenia patients also showed increased cerebro-cerebellar connectivity in somatomotor and default mode networks, with the latter showing no overlap with the regions found to be hypoconnected within the same default mode network. Finally, we found evidence to suggest that somatomotor and default mode networks may be inappropriately linked in schizophrenia. The relationship of these dysconnectivities to schizophrenia symptoms, such as neurological soft signs and altered sense of agency, is discussed. We conclude that the cerebellum ought to be considered for analysis in all future studies of network abnormalities in SZ, and further suggest the cerebellum as a potential target for further elucidation, and possibly treatment, of the underlying mechanisms and network abnormalities producing symptoms of

  15. Hybrid discrete-time neural networks.

    PubMed

    Cao, Hongjun; Ibarz, Borja

    2010-11-13

    Hybrid dynamical systems combine evolution equations with state transitions. When the evolution equations are discrete-time (also called map-based), the result is a hybrid discrete-time system. A class of biological neural network models that has recently received some attention falls within this category: map-based neuron models connected by means of fast threshold modulation (FTM). FTM is a connection scheme that aims to mimic the switching dynamics of a neuron subject to synaptic inputs. The dynamic equations of the neuron adopt different forms according to the state (either firing or not firing) and type (excitatory or inhibitory) of their presynaptic neighbours. Therefore, the mathematical model of one such network is a combination of discrete-time evolution equations with transitions between states, constituting a hybrid discrete-time (map-based) neural network. In this paper, we review previous work within the context of these models, exemplifying useful techniques to analyse them. Typical map-based neuron models are low-dimensional and amenable to phase-plane analysis. In bursting models, fast-slow decomposition can be used to reduce dimensionality further, so that the dynamics of a pair of connected neurons can be easily understood. We also discuss a model that includes electrical synapses in addition to chemical synapses with FTM. Furthermore, we describe how master stability functions can predict the stability of synchronized states in these networks. The main results are extended to larger map-based neural networks.

  16. Abnormal Amygdalar Activation and Connectivity in Adolescents with Attention-Deficit/Hyperactivity Disorder

    ERIC Educational Resources Information Center

    Posner, Jonathan; Nagel, Bonnie J.; Maia, Tiago V.; Mechling, Anna; Oh, Milim; Wang, Zhishun; Peterson, Bradley S.

    2011-01-01

    Objective: Emotional reactivity is one of the most disabling symptoms associated with attention-deficit/hyperactivity disorder (ADHD). We aimed to identify neural substrates associated with emotional reactivity and to assess the effects of stimulants on those substrates. Method: We used functional magnetic resonance imaging (fMRI) to assess neural…

  17. Neural crest stem cell multipotency requires Foxd3 to maintain neural potential and repress mesenchymal fates.

    PubMed

    Mundell, Nathan A; Labosky, Patricia A

    2011-02-01

    Neural crest (NC) progenitors generate a wide array of cell types, yet molecules controlling NC multipotency and self-renewal and factors mediating cell-intrinsic distinctions between multipotent versus fate-restricted progenitors are poorly understood. Our earlier work demonstrated that Foxd3 is required for maintenance of NC progenitors in the embryo. Here, we show that Foxd3 mediates a fate restriction choice for multipotent NC progenitors with loss of Foxd3 biasing NC toward a mesenchymal fate. Neural derivatives of NC were lost in Foxd3 mutant mouse embryos, whereas abnormally fated NC-derived vascular smooth muscle cells were ectopically located in the aorta. Cranial NC defects were associated with precocious differentiation towards osteoblast and chondrocyte cell fates, and individual mutant NC from different anteroposterior regions underwent fate changes, losing neural and increasing myofibroblast potential. Our results demonstrate that neural potential can be separated from NC multipotency by the action of a single gene, and establish novel parallels between NC and other progenitor populations that depend on this functionally conserved stem cell protein to regulate self-renewal and multipotency.

  18. The morphological classification of normal and abnormal red blood cell using Self Organizing Map

    NASA Astrophysics Data System (ADS)

    Rahmat, R. F.; Wulandari, F. S.; Faza, S.; Muchtar, M. A.; Siregar, I.

    2018-02-01

    Blood is an essential component of living creatures in the vascular space. For possible disease identification, it can be tested through a blood test, one of which can be seen from the form of red blood cells. The normal and abnormal morphology of the red blood cells of a patient is very helpful to doctors in detecting a disease. With the advancement of digital image processing technology can be used to identify normal and abnormal blood cells of a patient. This research used self-organizing map method to classify the normal and abnormal form of red blood cells in the digital image. The use of self-organizing map neural network method can be implemented to classify the normal and abnormal form of red blood cells in the input image with 93,78% accuracy testing.

  19. Shared neural circuits for mentalizing about the self and others.

    PubMed

    Lombardo, Michael V; Chakrabarti, Bhismadev; Bullmore, Edward T; Wheelwright, Sally J; Sadek, Susan A; Suckling, John; Baron-Cohen, Simon

    2010-07-01

    Although many examples exist for shared neural representations of self and other, it is unknown how such shared representations interact with the rest of the brain. Furthermore, do high-level inference-based shared mentalizing representations interact with lower level embodied/simulation-based shared representations? We used functional neuroimaging (fMRI) and a functional connectivity approach to assess these questions during high-level inference-based mentalizing. Shared mentalizing representations in ventromedial prefrontal cortex, posterior cingulate/precuneus, and temporo-parietal junction (TPJ) all exhibited identical functional connectivity patterns during mentalizing of both self and other. Connectivity patterns were distributed across low-level embodied neural systems such as the frontal operculum/ventral premotor cortex, the anterior insula, the primary sensorimotor cortex, and the presupplementary motor area. These results demonstrate that identical neural circuits are implementing processes involved in mentalizing of both self and other and that the nature of such processes may be the integration of low-level embodied processes within higher level inference-based mentalizing.

  20. Neonatal brain resting-state functional connectivity imaging modalities.

    PubMed

    Mohammadi-Nejad, Ali-Reza; Mahmoudzadeh, Mahdi; Hassanpour, Mahlegha S; Wallois, Fabrice; Muzik, Otto; Papadelis, Christos; Hansen, Anne; Soltanian-Zadeh, Hamid; Gelovani, Juri; Nasiriavanaki, Mohammadreza

    2018-06-01

    Infancy is the most critical period in human brain development. Studies demonstrate that subtle brain abnormalities during this state of life may greatly affect the developmental processes of the newborn infants. One of the rapidly developing methods for early characterization of abnormal brain development is functional connectivity of the brain at rest. While the majority of resting-state studies have been conducted using magnetic resonance imaging (MRI), there is clear evidence that resting-state functional connectivity (rs-FC) can also be evaluated using other imaging modalities. The aim of this review is to compare the advantages and limitations of different modalities used for the mapping of infants' brain functional connectivity at rest. In addition, we introduce photoacoustic tomography, a novel functional neuroimaging modality, as a complementary modality for functional mapping of infants' brain.

  1. Abnormal functional connectivity and cortical integrity influence dominant hand motor disability in multiple sclerosis: a multimodal analysis.

    PubMed

    Zhong, Jidan; Nantes, Julia C; Holmes, Scott A; Gallant, Serge; Narayanan, Sridar; Koski, Lisa

    2016-12-01

    Functional reorganization and structural damage occur in the brains of people with multiple sclerosis (MS) throughout the disease course. However, the relationship between resting-state functional connectivity (FC) reorganization in the sensorimotor network and motor disability in MS is not well understood. This study used resting-state fMRI, T1-weighted and T2-weighted, and magnetization transfer (MT) imaging to investigate the relationship between abnormal FC in the sensorimotor network and upper limb motor disability in people with MS, as well as the impact of disease-related structural abnormalities within this network. Specifically, the differences in FC of the left hemisphere hand motor region between MS participants with preserved (n = 17) and impaired (n = 26) right hand function, compared with healthy controls (n = 20) was investigated. Differences in brain atrophy and MT ratio measured at the global and regional levels were also investigated between the three groups. Motor preserved MS participants had stronger FC in structurally intact visual information processing regions relative to motor impaired MS participants. Motor impaired MS participants showed weaker FC in the sensorimotor and somatosensory association cortices and more severe structural damage throughout the brain compared with the other groups. Logistic regression analysis showed that regional MTR predicted motor disability beyond the impact of global atrophy whereas regional grey matter volume did not. More importantly, as the first multimodal analysis combining resting-state fMRI, T1-weighted, T2-weighted and MTR images in MS, we demonstrate how a combination of structural and functional changes may contribute to motor impairment or preservation in MS. Hum Brain Mapp 37:4262-4275, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  2. Dissociated emergent-response system and fine-processing system in human neural network and a heuristic neural architecture for autonomous humanoid robots.

    PubMed

    Yan, Xiaodan

    2010-01-01

    The current study investigated the functional connectivity of the primary sensory system with resting state fMRI and applied such knowledge into the design of the neural architecture of autonomous humanoid robots. Correlation and Granger causality analyses were utilized to reveal the functional connectivity patterns. Dissociation was within the primary sensory system, in that the olfactory cortex and the somatosensory cortex were strongly connected to the amygdala whereas the visual cortex and the auditory cortex were strongly connected with the frontal cortex. The posterior cingulate cortex (PCC) and the anterior cingulate cortex (ACC) were found to maintain constant communication with the primary sensory system, the frontal cortex, and the amygdala. Such neural architecture inspired the design of dissociated emergent-response system and fine-processing system in autonomous humanoid robots, with separate processing units and another consolidation center to coordinate the two systems. Such design can help autonomous robots to detect and respond quickly to danger, so as to maintain their sustainability and independence.

  3. Neural Connectivity in Epilepsy as Measured by Granger Causality.

    PubMed

    Coben, Robert; Mohammad-Rezazadeh, Iman

    2015-01-01

    Epilepsy is a chronic neurological disorder characterized by repeated seizures or excessive electrical discharges in a group of brain cells. Prevalence rates include about 50 million people worldwide and 10% of all people have at least one seizure at one time in their lives. Connectivity models of epilepsy serve to provide a deeper understanding of the processes that control and regulate seizure activity. These models have received initial support and have included measures of EEG, MEG, and MRI connectivity. Preliminary findings have shown regions of increased connectivity in the immediate regions surrounding the seizure foci and associated low connectivity in nearby regions and pathways. There is also early evidence to suggest that these patterns change during ictal events and that these changes may even by related to the occurrence or triggering of seizure events. We present data showing how Granger causality can be used with EEG data to measure connectivity across brain regions involved in ictal events and their resolution. We have provided two case examples as a demonstration of how to obtain and interpret such data. EEG data of ictal events are processed, converted to independent components and their dipole localizations, and these are used to measure causality and connectivity between these locations. Both examples have shown hypercoupling near the seizure foci and low causality across nearby and associated neuronal pathways. This technique also allows us to track how these measures change over time and during the ictal and post-ictal periods. Areas for further research into this technique, its application to epilepsy, and the formation of more effective therapeutic interventions are recommended.

  4. Neural network application to comprehensive engine diagnostics

    NASA Technical Reports Server (NTRS)

    Marko, Kenneth A.

    1994-01-01

    We have previously reported on the use of neural networks for detection and identification of faults in complex microprocessor controlled powertrain systems. The data analyzed in those studies consisted of the full spectrum of signals passing between the engine and the real-time microprocessor controller. The specific task of the classification system was to classify system operation as nominal or abnormal and to identify the fault present. The primary concern in earlier work was the identification of faults, in sensors or actuators in the powertrain system as it was exercised over its full operating range. The use of data from a variety of sources, each contributing some potentially useful information to the classification task, is commonly referred to as sensor fusion and typifies the type of problems successfully addressed using neural networks. In this work we explore the application of neural networks to a different diagnostic problem, the diagnosis of faults in newly manufactured engines and the utility of neural networks for process control.

  5. The neural basis of trait self-esteem revealed by the amplitude of low-frequency fluctuations and resting state functional connectivity.

    PubMed

    Pan, Weigang; Liu, Congcong; Yang, Qian; Gu, Yan; Yin, Shouhang; Chen, Antao

    2016-03-01

    Self-esteem is an affective, self-evaluation of oneself and has a significant effect on mental and behavioral health. Although research has focused on the neural substrates of self-esteem, little is known about the spontaneous brain activity that is associated with trait self-esteem (TSE) during the resting state. In this study, we used the resting-state functional magnetic resonance imaging (fMRI) signal of the amplitude of low-frequency fluctuations (ALFFs) and resting state functional connectivity (RSFC) to identify TSE-related regions and networks. We found that a higher level of TSE was associated with higher ALFFs in the left ventral medial prefrontal cortex (vmPFC) and lower ALFFs in the left cuneus/lingual gyrus and right lingual gyrus. RSFC analyses revealed that the strengths of functional connectivity between the left vmPFC and bilateral hippocampus were positively correlated with TSE; however, the connections between the left vmPFC and right inferior frontal gyrus and posterior superior temporal sulcus were negatively associated with TSE. Furthermore, the strengths of functional connectivity between the left cuneus/lingual gyrus and right dorsolateral prefrontal cortex and anterior cingulate cortex were positively related to TSE. These findings indicate that TSE is linked to core regions in the default mode network and social cognition network, which is involved in self-referential processing, autobiographical memory and social cognition. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  6. Connectivity Neurofeedback Training Can Differentially Change Functional Connectivity and Cognitive Performance.

    PubMed

    Yamashita, Ayumu; Hayasaka, Shunsuke; Kawato, Mitsuo; Imamizu, Hiroshi

    2017-10-01

    Advances in functional magnetic resonance imaging have made it possible to provide real-time feedback on brain activity. Neurofeedback has been applied to therapeutic interventions for psychiatric disorders. Since many studies have shown that most psychiatric disorders exhibit abnormal brain networks, a novel experimental paradigm named connectivity neurofeedback, which can directly modulate a brain network, has emerged as a promising approach to treat psychiatric disorders. Here, we investigated the hypothesis that connectivity neurofeedback can induce the aimed direction of change in functional connectivity, and the differential change in cognitive performance according to the direction of change in connectivity. We selected the connectivity between the left primary motor cortex and the left lateral parietal cortex as the target. Subjects were divided into 2 groups, in which only the direction of change (an increase or a decrease in correlation) in the experimentally manipulated connectivity differed between the groups. As a result, subjects successfully induced the expected connectivity changes in either of the 2 directions. Furthermore, cognitive performance significantly and differentially changed from preneurofeedback to postneurofeedback training between the 2 groups. These findings indicate that connectivity neurofeedback can induce the aimed direction of change in connectivity and also a differential change in cognitive performance. © The Author 2017. Published by Oxford University Press.

  7. Cognition and Resting-State Functional Connectivity in Schizophrenia

    PubMed Central

    Sheffield, Julia M; Barch, Deanna M

    2015-01-01

    Individuals with schizophrenia consistently display deficits in a multitude of cognitive domains, but the neurobiological source of these cognitive impairments remains unclear. By analyzing the functional connectivity of resting-state functional magnetic resonance imaging (rs-fcMRI) data in clinical populations like schizophrenia, research groups have begun elucidating abnormalities in the intrinsic communication between specific brain regions, and assessing relationships between these abnormalities and cognitive performance in schizophrenia. Here we review studies that have reported analysis of these brain-behavior relationships. Through this systematic review we found that patients with schizophrenia display abnormalities within and between regions comprising 1) the cortico-cerebellar-striatal-thalamic loop and 2) task-positive and task-negative cortical networks. Importantly, we did not observe unique relationships between specific functional connectivity abnormalities and distinct cognitive domains, suggesting that the observed functional systems may underlie mechanisms that are shared across cognitive abilities, the disturbance of which could contribute to the “generalized” cognitive deficit found in schizophrenia. We also note several areas of methodological change that we believe will strengthen this literature. PMID:26698018

  8. Serotonin, neural markers, and memory

    PubMed Central

    Meneses, Alfredo

    2015-01-01

    Diverse neuropsychiatric disorders present dysfunctional memory and no effective treatment exits for them; likely as result of the absence of neural markers associated to memory. Neurotransmitter systems and signaling pathways have been implicated in memory and dysfunctional memory; however, their role is poorly understood. Hence, neural markers and cerebral functions and dysfunctions are revised. To our knowledge no previous systematic works have been published addressing these issues. The interactions among behavioral tasks, control groups and molecular changes and/or pharmacological effects are mentioned. Neurotransmitter receptors and signaling pathways, during normal and abnormally functioning memory with an emphasis on the behavioral aspects of memory are revised. With focus on serotonin, since as it is a well characterized neurotransmitter, with multiple pharmacological tools, and well characterized downstream signaling in mammals' species. 5-HT1A, 5-HT4, 5-HT5, 5-HT6, and 5-HT7 receptors as well as SERT (serotonin transporter) seem to be useful neural markers and/or therapeutic targets. Certainly, if the mentioned evidence is replicated, then the translatability from preclinical and clinical studies to neural changes might be confirmed. Hypothesis and theories might provide appropriate limits and perspectives of evidence. PMID:26257650

  9. Contextual and Developmental Differences in the Neural Architecture of Cognitive Control.

    PubMed

    Petrican, Raluca; Grady, Cheryl L

    2017-08-09

    Because both development and context impact functional brain architecture, the neural connectivity signature of a cognitive or affective predisposition may similarly vary across different ages and circumstances. To test this hypothesis, we investigated the effects of age and cognitive versus social-affective context on the stable and time-varying neural architecture of inhibition, the putative core cognitive control component, in a subsample ( N = 359, 22-36 years, 174 men) of the Human Connectome Project. Among younger individuals, a neural signature of superior inhibition emerged in both stable and dynamic connectivity analyses. Dynamically, a context-free signature emerged as stronger segregation of internal cognition (default mode) and environmentally driven control (salience, cingulo-opercular) systems. A dynamic social-affective context-specific signature was observed most clearly in the visual system. Stable connectivity analyses revealed both context-free (greater default mode segregation) and context-specific (greater frontoparietal segregation for higher cognitive load; greater attentional and environmentally driven control system segregation for greater reward value) signatures of inhibition. Superior inhibition in more mature adulthood was typified by reduced segregation in the default network with increasing reward value and increased ventral attention but reduced cingulo-opercular and subcortical system segregation with increasing cognitive load. Failure to evidence this neural profile after the age of 30 predicted poorer life functioning. Our results suggest that distinguishable neural mechanisms underlie individual differences in cognitive control during different young adult stages and across tasks, thereby underscoring the importance of better understanding the interplay among dispositional, developmental, and contextual factors in shaping adaptive versus maladaptive patterns of thought and behavior. SIGNIFICANCE STATEMENT The brain's functional

  10. Patterns of neural connectivity during an attention bias task moderate associations between early childhood temperament and internalizing symptoms in young adulthood.

    PubMed

    Hardee, Jillian E; Benson, Brenda E; Bar-Haim, Yair; Mogg, Karin; Bradley, Brendan P; Chen, Gang; Britton, Jennifer C; Ernst, Monique; Fox, Nathan A; Pine, Daniel S; Pérez-Edgar, Koraly

    2013-08-15

    Biased attention to threat is found in both individuals with anxiety symptoms and children with the childhood temperament of behavioral inhibition (BI). Although perturbed fronto-amygdala function is implicated in biased attention among anxious individuals, no work has examined the neural correlates of attention biases in BI. Work in this area might clarify underlying mechanisms for anxiety in a sample at risk for internalizing disorders. We examined the relations among early childhood BI, fronto-amygdala connectivity during an attention bias task in young adulthood, and internalizing symptoms, assessed in young adulthood. Children were assessed for BI at multiple age points from infancy through age seven. On the basis of a composite of observational and maternal report data, we selected 21 young adults classified as having a history of BI and 23 classified as non-BI for this study (n = 44). Participants completed an event-related functional magnetic resonance imaging attention-bias task involving threat (angry faces) and neutral trials. Internalizing symptoms were assessed by self-report and diagnostic interviews. The young adults characterized in childhood with BI exhibited greater strength in threat-related connectivity than non-behaviorally inhibited young adults. Between-group differences manifested in connections between the amygdala and two frontal regions: dorsolateral prefrontal cortex and anterior insula. Amygdala-insula connectivity also interacted with childhood BI to predict young adult internalizing symptoms. Behavioral inhibition during early childhood predicts differences as young adults in threat and attention-related fronto-amygdala connectivity. Connectivity strength, in turn, moderated the relations between early BI and later psychopathology. Copyright © 2013 Society of Biological Psychiatry. All rights reserved.

  11. Functional Connectivity Magnetic Resonance Imaging Classification of Autism

    ERIC Educational Resources Information Center

    Anderson, Jeffrey S.; Nielsen, Jared A.; Froehlich, Alyson L.; DuBray, Molly B.; Druzgal, T. Jason; Cariello, Annahir N.; Cooperrider, Jason R.; Zielinski, Brandon A.; Ravichandran, Caitlin; Fletcher, P. Thomas; Alexander, Andrew L.; Bigler, Erin D.; Lange, Nicholas; Lainhart, Janet E.

    2011-01-01

    Group differences in resting state functional magnetic resonance imaging connectivity between individuals with autism and typically developing controls have been widely replicated for a small number of discrete brain regions, yet the whole-brain distribution of connectivity abnormalities in autism is not well characterized. It is also unclear…

  12. Abnormal Barrier Function in Gastrointestinal Disorders.

    PubMed

    Farré, Ricard; Vicario, María

    2017-01-01

    There is increasing concern in identifying the mechanisms underlying the intimate control of the intestinal barrier, as deregulation of its function is strongly associated with digestive (organic and functional) and a number of non-digestive (schizophrenia, diabetes, sepsis, among others) disorders. The intestinal barrier is a complex and effective defensive functional system that operates to limit luminal antigen access to the internal milieu while maintaining nutrient and electrolyte absorption. Intestinal permeability to substances is mainly determined by the physicochemical properties of the barrier, with the epithelium, mucosal immunity, and neural activity playing a major role. In functional gastrointestinal disorders (FGIDs), the absence of structural or biochemical abnormalities that explain chronic symptoms is probably close to its end, as recent research is providing evidence of structural gut alterations, at least in certain subsets, mainly in functional dyspepsia (FD) and irritable bowel syndrome (IBS). These alterations are associated with increased permeability, which seems to reflect mucosal inflammation and neural activation. The participation of each anatomical and functional component of barrier function in homeostasis and intestinal dysfunction is described, with a special focus on FGIDs.

  13. Measuring Symmetry, Asymmetry and Randomness in Neural Network Connectivity

    PubMed Central

    Esposito, Umberto; Giugliano, Michele; van Rossum, Mark; Vasilaki, Eleni

    2014-01-01

    Cognitive functions are stored in the connectome, the wiring diagram of the brain, which exhibits non-random features, so-called motifs. In this work, we focus on bidirectional, symmetric motifs, i.e. two neurons that project to each other via connections of equal strength, and unidirectional, non-symmetric motifs, i.e. within a pair of neurons only one neuron projects to the other. We hypothesise that such motifs have been shaped via activity dependent synaptic plasticity processes. As a consequence, learning moves the distribution of the synaptic connections away from randomness. Our aim is to provide a global, macroscopic, single parameter characterisation of the statistical occurrence of bidirectional and unidirectional motifs. To this end we define a symmetry measure that does not require any a priori thresholding of the weights or knowledge of their maximal value. We calculate its mean and variance for random uniform or Gaussian distributions, which allows us to introduce a confidence measure of how significantly symmetric or asymmetric a specific configuration is, i.e. how likely it is that the configuration is the result of chance. We demonstrate the discriminatory power of our symmetry measure by inspecting the eigenvalues of different types of connectivity matrices. We show that a Gaussian weight distribution biases the connectivity motifs to more symmetric configurations than a uniform distribution and that introducing a random synaptic pruning, mimicking developmental regulation in synaptogenesis, biases the connectivity motifs to more asymmetric configurations, regardless of the distribution. We expect that our work will benefit the computational modelling community, by providing a systematic way to characterise symmetry and asymmetry in network structures. Further, our symmetry measure will be of use to electrophysiologists that investigate symmetry of network connectivity. PMID:25006663

  14. Measuring symmetry, asymmetry and randomness in neural network connectivity.

    PubMed

    Esposito, Umberto; Giugliano, Michele; van Rossum, Mark; Vasilaki, Eleni

    2014-01-01

    Cognitive functions are stored in the connectome, the wiring diagram of the brain, which exhibits non-random features, so-called motifs. In this work, we focus on bidirectional, symmetric motifs, i.e. two neurons that project to each other via connections of equal strength, and unidirectional, non-symmetric motifs, i.e. within a pair of neurons only one neuron projects to the other. We hypothesise that such motifs have been shaped via activity dependent synaptic plasticity processes. As a consequence, learning moves the distribution of the synaptic connections away from randomness. Our aim is to provide a global, macroscopic, single parameter characterisation of the statistical occurrence of bidirectional and unidirectional motifs. To this end we define a symmetry measure that does not require any a priori thresholding of the weights or knowledge of their maximal value. We calculate its mean and variance for random uniform or Gaussian distributions, which allows us to introduce a confidence measure of how significantly symmetric or asymmetric a specific configuration is, i.e. how likely it is that the configuration is the result of chance. We demonstrate the discriminatory power of our symmetry measure by inspecting the eigenvalues of different types of connectivity matrices. We show that a Gaussian weight distribution biases the connectivity motifs to more symmetric configurations than a uniform distribution and that introducing a random synaptic pruning, mimicking developmental regulation in synaptogenesis, biases the connectivity motifs to more asymmetric configurations, regardless of the distribution. We expect that our work will benefit the computational modelling community, by providing a systematic way to characterise symmetry and asymmetry in network structures. Further, our symmetry measure will be of use to electrophysiologists that investigate symmetry of network connectivity.

  15. IR wireless cluster synapses of HYDRA very large neural networks

    NASA Astrophysics Data System (ADS)

    Jannson, Tomasz; Forrester, Thomas

    2008-04-01

    RF/IR wireless (virtual) synapses are critical components of HYDRA (Hyper-Distributed Robotic Autonomy) neural networks, already discussed in two earlier papers. The HYDRA network has the potential to be very large, up to 10 11-neurons and 10 18-synapses, based on already established technologies (cellular RF telephony and IR-wireless LANs). It is organized into almost fully connected IR-wireless clusters. The HYDRA neurons and synapses are very flexible, simple, and low-cost. They can be modified into a broad variety of biologically-inspired brain-like computing capabilities. In this third paper, we focus on neural hardware in general, and on IR-wireless synapses in particular. Such synapses, based on LED/LD-connections, dominate the HYDRA neural cluster.

  16. Functional neural networks underlying response inhibition in adolescents and adults

    PubMed Central

    Stevens, Michael C.; Kiehl, Kent A.; Pearlson, Godfrey D.; Calhoun, Vince D.

    2008-01-01

    This study provides the first description of neural network dynamics associated with response inhibition in healthy adolescents and adults. Functional and effective connectivity analyses of whole brain hemodynamic activity elicited during performance of a Go/No-Go task were used to identify functionally-integrated neural networks and characterize their causal interactions. Three response inhibition circuits formed a hierarchical, inter-dependent system wherein thalamic modulation of input to premotor cortex by frontostriatal regions led to response suppression. Adolescents differed from adults in the degree of network engagement, regional fronto-striatal-thalamic connectivity, and network dynamics. We identify and characterize several age-related differences in the function of neural circuits that are associated with behavioral performance changes across adolescent development. PMID:17467816

  17. Neural mechanism of optimal limb coordination in crustacean swimming

    PubMed Central

    Zhang, Calvin; Guy, Robert D.; Mulloney, Brian; Zhang, Qinghai; Lewis, Timothy J.

    2014-01-01

    A fundamental challenge in neuroscience is to understand how biologically salient motor behaviors emerge from properties of the underlying neural circuits. Crayfish, krill, prawns, lobsters, and other long-tailed crustaceans swim by rhythmically moving limbs called swimmerets. Over the entire biological range of animal size and paddling frequency, movements of adjacent swimmerets maintain an approximate quarter-period phase difference with the more posterior limbs leading the cycle. We use a computational fluid dynamics model to show that this frequency-invariant stroke pattern is the most effective and mechanically efficient paddling rhythm across the full range of biologically relevant Reynolds numbers in crustacean swimming. We then show that the organization of the neural circuit underlying swimmeret coordination provides a robust mechanism for generating this stroke pattern. Specifically, the wave-like limb coordination emerges robustly from a combination of the half-center structure of the local central pattern generating circuits (CPGs) that drive the movements of each limb, the asymmetric network topology of the connections between local CPGs, and the phase response properties of the local CPGs, which we measure experimentally. Thus, the crustacean swimmeret system serves as a concrete example in which the architecture of a neural circuit leads to optimal behavior in a robust manner. Furthermore, we consider all possible connection topologies between local CPGs and show that the natural connectivity pattern generates the biomechanically optimal stroke pattern most robustly. Given the high metabolic cost of crustacean swimming, our results suggest that natural selection has pushed the swimmeret neural circuit toward a connection topology that produces optimal behavior. PMID:25201976

  18. The Neural Crest in Cardiac Congenital Anomalies

    PubMed Central

    Keyte, Anna; Hutson, Mary Redmond

    2012-01-01

    This review discusses the function of neural crest as they relate to cardiovascular defects. The cardiac neural crest cells are a subpopulation of cranial neural crest discovered nearly 30 years ago by ablation of premigratory neural crest. The cardiac neural crest cells are necessary for normal cardiovascular development. We begin with a description of the crest cells in normal development, including their function in remodeling the pharyngeal arch arteries, outflow tract septation, valvulogenesis, and development of the cardiac conduction system. The cells are also responsible for modulating signaling in the caudal pharynx, including the second heart field. Many of the molecular pathways that are known to influence specification, migration, patterning and final targeting of the cardiac neural crest cells are reviewed. The cardiac neural crest cells play a critical role in the pathogenesis of various human cardiocraniofacial syndromes such as DiGeorge, Velocardiofacial, CHARGE, Fetal Alcohol, Alagille, LEOPARD, and Noonan syndromes, as well as Retinoic Acid Embryopathy. The loss of neural crest cells or their dysfunction may not always directly cause abnormal cardiovascular development, but are involved secondarily because crest cells represent a major component in the complex tissue interactions in the head, pharynx and outflow tract. Thus many of the human syndromes linking defects in the heart, face and brain can be better understood when considered within the context of a single cardiocraniofacial developmental module with the neural crest being a key cell type that interconnects the regions. PMID:22595346

  19. Cognitive Flexibility through Metastable Neural Dynamics Is Disrupted by Damage to the Structural Connectome.

    PubMed

    Hellyer, Peter J; Scott, Gregory; Shanahan, Murray; Sharp, David J; Leech, Robert

    2015-06-17

    Current theory proposes that healthy neural dynamics operate in a metastable regime, where brain regions interact to simultaneously maximize integration and segregation. Metastability may confer important behavioral properties, such as cognitive flexibility. It is increasingly recognized that neural dynamics are constrained by the underlying structural connections between brain regions. An important challenge is, therefore, to relate structural connectivity, neural dynamics, and behavior. Traumatic brain injury (TBI) is a pre-eminent structural disconnection disorder whereby traumatic axonal injury damages large-scale connectivity, producing characteristic cognitive impairments, including slowed information processing speed and reduced cognitive flexibility, that may be a result of disrupted metastable dynamics. Therefore, TBI provides an experimental and theoretical model to examine how metastable dynamics relate to structural connectivity and cognition. Here, we use complementary empirical and computational approaches to investigate how metastability arises from the healthy structural connectome and relates to cognitive performance. We found reduced metastability in large-scale neural dynamics after TBI, measured with resting-state functional MRI. This reduction in metastability was associated with damage to the connectome, measured using diffusion MRI. Furthermore, decreased metastability was associated with reduced cognitive flexibility and information processing. A computational model, defined by empirically derived connectivity data, demonstrates how behaviorally relevant changes in neural dynamics result from structural disconnection. Our findings suggest how metastable dynamics are important for normal brain function and contingent on the structure of the human connectome. Copyright © 2015 the authors 0270-6474/15/359050-14$15.00/0.

  20. Abnormal functional connectivity of EEG gamma band in patients with depression during emotional face processing.

    PubMed

    Li, Yingjie; Cao, Dan; Wei, Ling; Tang, Yingying; Wang, Jijun

    2015-11-01

    This paper evaluates the large-scale structure of functional brain networks using graph theoretical concepts and investigates the difference in brain functional networks between patients with depression and healthy controls while they were processing emotional stimuli. Electroencephalography (EEG) activities were recorded from 16 patients with depression and 14 healthy controls when they performed a spatial search task for facial expressions. Correlations between all possible pairs of 59 electrodes were determined by coherence, and the coherence matrices were calculated in delta, theta, alpha, beta, and gamma bands (low gamma: 30-50Hz and high gamma: 50-80Hz, respectively). Graph theoretical analysis was applied to these matrices by using two indexes: the clustering coefficient and the characteristic path length. The global EEG coherence of patients with depression was significantly higher than that of healthy controls in both gamma bands, especially in the high gamma band. The global coherence in both gamma bands from healthy controls appeared higher in negative conditions than in positive conditions. All the brain networks were found to hold a regular and ordered topology during emotion processing. However, the brain network of patients with depression appeared randomized compared with the normal one. The abnormal network topology of patients with depression was detected in both the prefrontal and occipital regions. The negative bias from healthy controls occurred in both gamma bands during emotion processing, while it disappeared in patients with depression. The proposed work studied abnormally increased connectivity of brain functional networks in patients with depression. By combing the clustering coefficient and the characteristic path length, we found that the brain networks of patients with depression and healthy controls had regular networks during emotion processing. Yet the brain networks of the depressed group presented randomization trends. Moreover

  1. Enteric nervous system abnormalities are present in human necrotizing enterocolitis: potential neurotransplantation therapy

    PubMed Central

    2013-01-01

    Introduction Intestinal dysmotility following human necrotizing enterocolitis suggests that the enteric nervous system is injured during the disease. We examined human intestinal specimens to characterize the enteric nervous system injury that occurs in necrotizing enterocolitis, and then used an animal model of experimental necrotizing enterocolitis to determine whether transplantation of neural stem cells can protect the enteric nervous system from injury. Methods Human intestinal specimens resected from patients with necrotizing enterocolitis (n = 18), from control patients with bowel atresia (n = 8), and from necrotizing enterocolitis and control patients undergoing stoma closure several months later (n = 14 and n = 6 respectively) were subjected to histologic examination, immunohistochemistry, and real-time reverse-transcription polymerase chain reaction to examine the myenteric plexus structure and neurotransmitter expression. In addition, experimental necrotizing enterocolitis was induced in newborn rat pups and neurotransplantation was performed by administration of fluorescently labeled neural stem cells, with subsequent visualization of transplanted cells and determination of intestinal integrity and intestinal motility. Results There was significant enteric nervous system damage with increased enteric nervous system apoptosis, and decreased neuronal nitric oxide synthase expression in myenteric ganglia from human intestine resected for necrotizing enterocolitis compared with control intestine. Structural and functional abnormalities persisted months later at the time of stoma closure. Similar abnormalities were identified in rat pups exposed to experimental necrotizing enterocolitis. Pups receiving neural stem cell transplantation had improved enteric nervous system and intestinal integrity, differentiation of transplanted neural stem cells into functional neurons, significantly improved intestinal transit, and significantly decreased

  2. Neural-activity mapping of memory-based dominance in the crow: neural networks integrating individual discrimination and social behaviour control.

    PubMed

    Nishizawa, K; Izawa, E-I; Watanabe, S

    2011-12-01

    Large-billed crows (Corvus macrorhynchos), highly social birds, form stable dominance relationships based on the memory of win/loss outcomes of first encounters and on individual discrimination. This socio-cognitive behaviour predicts the existence of neural mechanisms for integration of social behaviour control and individual discrimination. This study aimed to elucidate the neural substrates of memory-based dominance in crows. First, the formation of dominance relationships was confirmed between males in a dyadic encounter paradigm. Next, we examined whether neural activities in 22 focal nuclei of pallium and subpallium were correlated with social behaviour and stimulus familiarity after exposure to dominant/subordinate familiar individuals and unfamiliar conspecifics. Neural activity was determined by measuring expression level of the immediate-early-gene (IEG) protein Zenk. Crows displayed aggressive and/or submissive behaviour to opponents less frequently but more discriminatively in subsequent encounters, suggesting stable dominance based on memory, including win/loss outcomes of the first encounters and individual discrimination. Neural correlates of aggressive and submissive behaviour were found in limbic subpallium including septum, bed nucleus of the striae terminalis (BST), and nucleus taeniae of amygdala (TnA), but also those to familiarity factor in BST and TnA. Contrastingly, correlates of social behaviour were little in pallium and those of familiarity with exposed individuals were identified in hippocampus, medial meso-/nidopallium, and ventro-caudal nidopallium. Given the anatomical connection and neural response patterns of the focal nuclei, neural networks connecting pallium and limbic subpallium via hippocampus could be involved in the integration of individual discrimination and social behaviour control in memory-based dominance in the crow. Copyright © 2011 IBRO. Published by Elsevier Ltd. All rights reserved.

  3. Gamma-band abnormalities as markers of autism spectrum disorders

    PubMed Central

    Rojas, Donald C.; Wilson, Lisa B.

    2014-01-01

    Summary Autism is a behaviorally diagnosed neurodevelopmental disorder with no current biomarkers with high specificity and sensitivity. Gamma-band abnormalities have been reported in many studies of autism spectrum disorders. Gamma-band activity is associated with perceptual and cognitive functions that are compromised in autism. Some gamma-band deficits have also been seen in unaffected first-degree relatives, suggesting heritability of these findings. This review covers the published literature on gamma abnormalities in autism, the proposed mechanisms underlying the deficits, and the potential for translation into new treatments. Although the utility of gamma-band metrics as diagnostic biomarkers is currently limited, such changes in autism are also useful as endophenotypes, for evaluating potential neural mechanisms, and for use as surrogate markers of treatment response to interventions. PMID:24712425

  4. Differential reward network functional connectivity in cannabis dependent and non-dependent users☆

    PubMed Central

    Filbey, Francesca M.; Dunlop, Joseph

    2015-01-01

    Background Emergent studies show that similar to other substances of abuse, cue-reactivity to cannabis is also associated with neural response in the brain’s reward pathway (Filbey et al., 2009). However, the inter-relatedness of brain regions during cue-reactivity in cannabis users remains unknown. Methods In this study, we conducted a series of investigations to determine functional connectivity during cue-reactivity in 71 cannabis users. First, we used psychophysiological interaction (PPI) analysis to examine coherent neural response to cannabis cues. Second, we evaluated whether these patterns of network functional connectivity differentiated dependent and non-dependent users. Finally, as an exploratory analysis, we determined the directionality of these connections via Granger connectivity analyses. Results PPI analyses showed reward network functional connectivity with the nucleus accumbens (NAc) seed region during cue exposure. Between-group contrasts found differential effects of dependence status. Dependent users (N = 31) had greater functional connectivity with amygdala and anterior cingulate gyrus (ACG) seeds while the non-dependent users (N = 24) had greater functional connectivity with the NAc, orbitofrontal cortex (OFC) and hippocampus seeds. Granger analyses showed that hippocampal and ACG activation preceded neural response in reward areas. Conclusions Both PPI and Granger analyses demonstrated strong functional coherence in reward regions during exposure to cannabis cues in current cannabis users. Functional connectivity (but not regional activation) in the reward network differentiated dependent from non-dependent cannabis users. Our findings suggest that repeated cannabis exposure causes observable changes in functional connectivity in the reward network and should be considered in intervention strategies. PMID:24838032

  5. An algorithm to predict the connectome of neural microcircuits

    PubMed Central

    Reimann, Michael W.; King, James G.; Muller, Eilif B.; Ramaswamy, Srikanth; Markram, Henry

    2015-01-01

    Experimentally mapping synaptic connections, in terms of the numbers and locations of their synapses and estimating connection probabilities, is still not a tractable task, even for small volumes of tissue. In fact, the six layers of the neocortex contain thousands of unique types of synaptic connections between the many different types of neurons, of which only a handful have been characterized experimentally. Here we present a theoretical framework and a data-driven algorithmic strategy to digitally reconstruct the complete synaptic connectivity between the different types of neurons in a small well-defined volume of tissue—the micro-scale connectome of a neural microcircuit. By enforcing a set of established principles of synaptic connectivity, and leveraging interdependencies between fundamental properties of neural microcircuits to constrain the reconstructed connectivity, the algorithm yields three parameters per connection type that predict the anatomy of all types of biologically viable synaptic connections. The predictions reproduce a spectrum of experimental data on synaptic connectivity not used by the algorithm. We conclude that an algorithmic approach to the connectome can serve as a tool to accelerate experimental mapping, indicating the minimal dataset required to make useful predictions, identifying the datasets required to improve their accuracy, testing the feasibility of experimental measurements, and making it possible to test hypotheses of synaptic connectivity. PMID:26500529

  6. Predicting individual brain functional connectivity using a Bayesian hierarchical model.

    PubMed

    Dai, Tian; Guo, Ying

    2017-02-15

    Network-oriented analysis of functional magnetic resonance imaging (fMRI), especially resting-state fMRI, has revealed important association between abnormal connectivity and brain disorders such as schizophrenia, major depression and Alzheimer's disease. Imaging-based brain connectivity measures have become a useful tool for investigating the pathophysiology, progression and treatment response of psychiatric disorders and neurodegenerative diseases. Recent studies have started to explore the possibility of using functional neuroimaging to help predict disease progression and guide treatment selection for individual patients. These studies provide the impetus to develop statistical methodology that would help provide predictive information on disease progression-related or treatment-related changes in neural connectivity. To this end, we propose a prediction method based on Bayesian hierarchical model that uses individual's baseline fMRI scans, coupled with relevant subject characteristics, to predict the individual's future functional connectivity. A key advantage of the proposed method is that it can improve the accuracy of individualized prediction of connectivity by combining information from both group-level connectivity patterns that are common to subjects with similar characteristics as well as individual-level connectivity features that are particular to the specific subject. Furthermore, our method also offers statistical inference tools such as predictive intervals that help quantify the uncertainty or variability of the predicted outcomes. The proposed prediction method could be a useful approach to predict the changes in individual patient's brain connectivity with the progression of a disease. It can also be used to predict a patient's post-treatment brain connectivity after a specified treatment regimen. Another utility of the proposed method is that it can be applied to test-retest imaging data to develop a more reliable estimator for individual

  7. Demultiplexer circuit for neural stimulation

    DOEpatents

    Wessendorf, Kurt O; Okandan, Murat; Pearson, Sean

    2012-10-09

    A demultiplexer circuit is disclosed which can be used with a conventional neural stimulator to extend the number of electrodes which can be activated. The demultiplexer circuit, which is formed on a semiconductor substrate containing a power supply that provides all the dc electrical power for operation of the circuit, includes digital latches that receive and store addressing information from the neural stimulator one bit at a time. This addressing information is used to program one or more 1:2.sup.N demultiplexers in the demultiplexer circuit which then route neural stimulation signals from the neural stimulator to an electrode array which is connected to the outputs of the 1:2.sup.N demultiplexer. The demultiplexer circuit allows the number of individual electrodes in the electrode array to be increased by a factor of 2.sup.N with N generally being in a range of 2-4.

  8. How Useful Is Electroencephalography in the Diagnosis of Autism Spectrum Disorders and the Delineation of Subtypes: A Systematic Review

    PubMed Central

    Gurau, Oana; Bosl, William J.; Newton, Charles R.

    2017-01-01

    Autism spectrum disorders (ASD) are thought to be associated with abnormal neural connectivity. Presently, neural connectivity is a theoretical construct that cannot be easily measured. Research in network science and time series analysis suggests that neural network structure, a marker of neural activity, can be measured with electroencephalography (EEG). EEG can be quantified by different methods of analysis to potentially detect brain abnormalities. The aim of this review is to examine evidence for the utility of three methods of EEG signal analysis in the ASD diagnosis and subtype delineation. We conducted a review of literature in which 40 studies were identified and classified according to the principal method of EEG analysis in three categories: functional connectivity analysis, spectral power analysis, and information dynamics. All studies identified significant differences between ASD patients and non-ASD subjects. However, due to high heterogeneity in the results, generalizations could not be inferred and none of the methods alone are currently useful as a new diagnostic tool. The lack of studies prevented the analysis of these methods as tools for ASD subtypes delineation. These results confirm EEG abnormalities in ASD, but as yet not sufficient to help in the diagnosis. Future research with larger samples and more robust study designs could allow for higher sensitivity and consistency in characterizing ASD, paving the way for developing new means of diagnosis. PMID:28747892

  9. Distortions and Disconnections: Disrupted Brain Connectivity in Autism

    ERIC Educational Resources Information Center

    Wass, Sam

    2011-01-01

    The past few years have seen considerable interest in findings of abnormal brain connectivity in the autism spectrum disorders (ASD). We review recent work from neuroimaging and other sources, and argue that there is considerable convergent evidence suggesting that connectivity is disrupted in ASD. We point to evidence both of local…

  10. Socioeconomic disadvantage and neural development from infancy through early childhood

    PubMed Central

    Chin-Lun Hung, Galen; Hahn, Jill; Alamiri, Bibi; Buka, Stephen L; Goldstein, Jill M; Laird, Nan; Nelson, Charles A; Smoller, Jordan W; Gilman, Stephen E

    2015-01-01

    Background: Early social experiences are believed to shape neurodevelopment, with potentially lifelong consequences. Yet minimal evidence exists regarding the role of the social environment on children’s neural functioning, a core domain of neurodevelopment. Methods: We analysed data from 36 443 participants in the United States Collaborative Perinatal Project, a socioeconomically diverse pregnancy cohort conducted between 1959 and 1974. Study outcomes included: physician (neurologist or paediatrician)-rated neurological abnormality neonatally and thereafter at 4 months and 1 and 7 years; indicators of neurological hard signs and soft signs; and indicators of autonomic nervous system function. Results: Children born to socioeconomically disadvantaged parents were more likely to exhibit neurological abnormalities at 4 months [odds ratio (OR) = 1.20; 95% confidence interval (CI) = 1.06, 1.37], 1 year (OR = 1.35; CI = 1.17, 1.56), and 7 years (OR = 1.67; CI = 1.48, 1.89), and more likely to exhibit neurological hard signs (OR = 1.39; CI = 1.10, 1.76), soft signs (OR = 1.26; CI = 1.09, 1.45) and autonomic nervous system dysfunctions at 7 years. Pregnancy and delivery complications, themselves associated with socioeconomic disadvantage, did not account for the higher risks of neurological abnormalities among disadvantaged children. Conclusions: Parental socioeconomic disadvantage was, independently from pregnancy and delivery complications, associated with abnormal child neural development during the first 7 years of life. These findings reinforce the importance of the early environment for neurodevelopment generally, and expand knowledge regarding the domains of neurodevelopment affected by environmental conditions. Further work is needed to determine the mechanisms linking socioeconomic disadvantage with children’s neural functioning, the timing of such mechanisms and their potential reversibility. PMID:26675752

  11. Chromatin Switches during Neural Cell Differentiation and Their Dysregulation by Prenatal Alcohol Exposure.

    PubMed

    Gavin, David P; Grayson, Dennis R; Varghese, Sajoy P; Guizzetti, Marina

    2017-05-11

    Prenatal alcohol exposure causes persistent neuropsychiatric deficits included under the term fetal alcohol spectrum disorders (FASD). Cellular identity emerges from a cascade of intrinsic and extrinsic (involving cell-cell interactions and signaling) processes that are partially initiated and maintained through changes in chromatin structure. Prenatal alcohol exposure influences neuronal and astrocyte development, permanently altering brain connectivity. Prenatal alcohol exposure also alters chromatin structure through histone and DNA modifications. However, the data linking alcohol-induced differentiation changes with developmental alterations in chromatin structure remain to be elucidated. In the first part of this review, we discuss the sequence of chromatin structural changes involved in neural cell differentiation during normal development. We then discuss the effects of prenatal alcohol on developmental histone modifications and DNA methylation in the context of neurogenesis and astrogliogenesis. We attempt to synthesize the developmental literature with the FASD literature, proposing that alcohol-induced changes to chromatin structure account for altered neurogenesis and astrogliogenesis as well as altered neuron and astrocyte differentiation. Together these changes may contribute to the cognitive and behavioral abnormalities in FASD. Future studies using standardized alcohol exposure paradigms at specific developmental stages will advance the understanding of how chromatin structural changes impact neural cell fate and maturation in FASD.

  12. Chromatin Switches during Neural Cell Differentiation and Their Dysregulation by Prenatal Alcohol Exposure

    PubMed Central

    Gavin, David P.; Grayson, Dennis R.; Varghese, Sajoy P.; Guizzetti, Marina

    2017-01-01

    Prenatal alcohol exposure causes persistent neuropsychiatric deficits included under the term fetal alcohol spectrum disorders (FASD). Cellular identity emerges from a cascade of intrinsic and extrinsic (involving cell-cell interactions and signaling) processes that are partially initiated and maintained through changes in chromatin structure. Prenatal alcohol exposure influences neuronal and astrocyte development, permanently altering brain connectivity. Prenatal alcohol exposure also alters chromatin structure through histone and DNA modifications. However, the data linking alcohol-induced differentiation changes with developmental alterations in chromatin structure remain to be elucidated. In the first part of this review, we discuss the sequence of chromatin structural changes involved in neural cell differentiation during normal development. We then discuss the effects of prenatal alcohol on developmental histone modifications and DNA methylation in the context of neurogenesis and astrogliogenesis. We attempt to synthesize the developmental literature with the FASD literature, proposing that alcohol-induced changes to chromatin structure account for altered neurogenesis and astrogliogenesis as well as altered neuron and astrocyte differentiation. Together these changes may contribute to the cognitive and behavioral abnormalities in FASD. Future studies using standardized alcohol exposure paradigms at specific developmental stages will advance the understanding of how chromatin structural changes impact neural cell fate and maturation in FASD. PMID:28492482

  13. Face off against ROS: Tcof1/Treacle safeguards neuroepithelial cells and progenitor neural crest cells from oxidative stress during craniofacial development.

    PubMed

    Sakai, Daisuke; Trainor, Paul A

    2016-09-01

    One-third of all congenital birth defects affect the head and face, and most craniofacial anomalies are considered to arise through defects in the development of cranial neural crest cells. Cranial neural crest cells give rise to the majority of craniofacial bones, cartilages and connective tissues. Therefore, understanding the events that control normal cranial neural crest and subsequent craniofacial development is important for elucidating the pathogenetic mechanisms of craniofacial anomalies and for the exploring potential therapeutic avenues for their prevention. Treacher Collins syndrome (TCS) is a congenital disorder characterized by severe craniofacial anomalies. An animal model of TCS, generated through mutation of Tcof1, the mouse (Mus musculus) homologue of the gene primarily mutated in association with TCS in humans, has recently revealed significant insights into the pathogenesis of TCS. Apoptotic elimination of neuroepithelial cells including neural crest cells is the primary cause of craniofacial defects in Tcof1 mutant embryos. However, our understanding of the mechanisms that induce tissue-specific apoptosis remains incomplete. In this review, we describe recent advances in our understanding of the pathogenesis TCS. Furthermore, we discuss the role of Tcof1 in normal embryonic development, the correlation between genetic and environmental factors on the severity of craniofacial abnormalities, and the prospect for prenatal prevention of craniofacial anomalies. © 2016 Japanese Society of Developmental Biologists.

  14. Amygdala-prefrontal connectivity during appraisal of symptom-related stimuli in obsessive-compulsive disorder.

    PubMed

    Paul, Sandra; Beucke, Jan C; Kaufmann, Christian; Mersov, Anna; Heinzel, Stephan; Kathmann, Norbert; Simon, Daniela

    2018-04-06

    Cognitive models of obsessive-compulsive disorder (OCD) posit dysfunctional appraisal of disorder-relevant stimuli in patients, suggesting disturbances in the processes relying on amygdala-prefrontal connectivity. Recent neuroanatomical models add to the traditional view of dysfunction in corticostriatal circuits by proposing alterations in an affective circuit including amygdala-prefrontal connections. However, abnormalities in amygdala-prefrontal coupling during symptom provocation, and particularly during conditions that require stimulus appraisal, remain to be demonstrated directly. Amygdala-prefrontal connectivity was examined in unmedicated OCD patients during appraisal (v. distraction) of symptom-provoking stimuli compared with an emotional control condition. Subsequent analyses tested whether hypothesized connectivity alterations could be also identified during passive viewing and the resting state in two independent samples. During symptom provocation, reductions in positive coupling between amygdala and orbitofrontal cortex were observed in OCD patients relative to healthy control participants during appraisal and passive viewing of OCD-relevant stimuli, whereas abnormally high amygdala-ventromedial prefrontal cortex coupling was found when appraisal was distracted by a secondary task. In contrast, there were no group differences in amygdala connectivity at rest. Our finding of abnormal amygdala-prefrontal connectivity during appraisal of symptom-related (relative to generally aversive) stimuli is consistent with the involvement of affective circuits in the functional neuroanatomy of OCD. Aberrant connectivity can be assumed to impact stimulus appraisal and emotion regulation, but might also relate to fear extinction deficits, which have recently been described in OCD. Taken together, we propose to integrate abnormalities in amygdala-prefrontal coupling in affective models of OCD.

  15. Multimodal Imaging in Rat Model Recapitulates Alzheimer's Disease Biomarkers Abnormalities.

    PubMed

    Parent, Maxime J; Zimmer, Eduardo R; Shin, Monica; Kang, Min Su; Fonov, Vladimir S; Mathieu, Axel; Aliaga, Antonio; Kostikov, Alexey; Do Carmo, Sonia; Dea, Doris; Poirier, Judes; Soucy, Jean-Paul; Gauthier, Serge; Cuello, A Claudio; Rosa-Neto, Pedro

    2017-12-13

    Imaging biomarkers are frequently proposed as endpoints for clinical trials targeting brain amyloidosis in Alzheimer's disease (AD); however, the specific impact of amyloid-β (Aβ) aggregation on biomarker abnormalities remains elusive in AD. Using the McGill-R-Thy1-APP transgenic rat as a model of selective Aβ pathology, we characterized the longitudinal progression of abnormalities in biomarkers commonly used in AD research. Middle-aged (9-11 months) transgenic animals (both male and female) displayed mild spatial memory impairments and disrupted cingulate network connectivity measured by resting-state fMRI, even in the absence of hypometabolism (measured with PET [ 18 F]FDG) or detectable fibrillary amyloidosis (measured with PET [ 18 F]NAV4694). At more advanced ages (16-19 months), cognitive deficits progressed in conjunction with resting connectivity abnormalities; furthermore, hypometabolism, Aβ plaque accumulation, reduction of CSF Aβ 1-42 concentrations, and hippocampal atrophy (structural MRI) were detectable at this stage. The present results emphasize the early impact of Aβ on brain connectivity and support a framework in which persistent Aβ aggregation itself is sufficient to impose memory circuits dysfunction, which propagates to adjacent brain networks at later stages. SIGNIFICANCE STATEMENT The present study proposes a "back translation" of the Alzheimer pathological cascade concept from human to animals. We used the same set of Alzheimer imaging biomarkers typically used in large human cohorts and assessed their progression over time in a transgenic rat model, which allows for a finer spatial resolution not attainable with mice. Using this translational platform, we demonstrated that amyloid-β pathology recapitulates an Alzheimer-like profile of biomarker abnormalities even in the absence of other hallmarks of the disease such as neurofibrillary tangles and widespread neuronal losses. Copyright © 2017 Parent et al.

  16. Multimodal Imaging in Rat Model Recapitulates Alzheimer's Disease Biomarkers Abnormalities

    PubMed Central

    Parent, Maxime J.; Kang, Min Su; Mathieu, Axel; Aliaga, Antonio; Do Carmo, Sonia; Dea, Doris; Gauthier, Serge; Cuello, A. Claudio

    2017-01-01

    Imaging biomarkers are frequently proposed as endpoints for clinical trials targeting brain amyloidosis in Alzheimer's disease (AD); however, the specific impact of amyloid-β (Aβ) aggregation on biomarker abnormalities remains elusive in AD. Using the McGill-R-Thy1-APP transgenic rat as a model of selective Aβ pathology, we characterized the longitudinal progression of abnormalities in biomarkers commonly used in AD research. Middle-aged (9–11 months) transgenic animals (both male and female) displayed mild spatial memory impairments and disrupted cingulate network connectivity measured by resting-state fMRI, even in the absence of hypometabolism (measured with PET [18F]FDG) or detectable fibrillary amyloidosis (measured with PET [18F]NAV4694). At more advanced ages (16–19 months), cognitive deficits progressed in conjunction with resting connectivity abnormalities; furthermore, hypometabolism, Aβ plaque accumulation, reduction of CSF Aβ1-42 concentrations, and hippocampal atrophy (structural MRI) were detectable at this stage. The present results emphasize the early impact of Aβ on brain connectivity and support a framework in which persistent Aβ aggregation itself is sufficient to impose memory circuits dysfunction, which propagates to adjacent brain networks at later stages. SIGNIFICANCE STATEMENT The present study proposes a “back translation” of the Alzheimer pathological cascade concept from human to animals. We used the same set of Alzheimer imaging biomarkers typically used in large human cohorts and assessed their progression over time in a transgenic rat model, which allows for a finer spatial resolution not attainable with mice. Using this translational platform, we demonstrated that amyloid-β pathology recapitulates an Alzheimer-like profile of biomarker abnormalities even in the absence of other hallmarks of the disease such as neurofibrillary tangles and widespread neuronal losses. PMID:29097597

  17. Neural crest does not contribute to the neck and shoulder in the axolotl (Ambystoma mexicanum).

    PubMed

    Epperlein, Hans-Henning; Khattak, Shahryar; Knapp, Dunja; Tanaka, Elly M; Malashichev, Yegor B

    2012-01-01

    A major step during the evolution of tetrapods was their transition from water to land. This process involved the reduction or complete loss of the dermal bones that made up connections to the skull and a concomitant enlargement of the endochondral shoulder girdle. In the mouse the latter is derived from three separate embryonic sources: lateral plate mesoderm, somites, and neural crest. The neural crest was suggested to sustain the muscle attachments. How this complex composition of the endochondral shoulder girdle arose during evolution and whether it is shared by all tetrapods is unknown. Salamanders that lack dermal bone within their shoulder girdle were of special interest for a possible contribution of the neural crest to the endochondral elements and muscle attachment sites, and we therefore studied them in this context. We grafted neural crest from GFP+ fluorescent transgenic axolotl (Ambystoma mexicanum) donor embryos into white (d/d) axolotl hosts and followed the presence of neural crest cells within the cartilage of the shoulder girdle and the connective tissue of muscle attachment sites of the neck-shoulder region. Strikingly, neural crest cells did not contribute to any part of the endochondral shoulder girdle or to the connective tissue at muscle attachment sites in axolotl. Our results in axolotl suggest that neural crest does not serve a general function in vertebrate shoulder muscle attachment sites as predicted by the "muscle scaffold theory," and that it is not necessary to maintain connectivity of the endochondral shoulder girdle to the skull. Our data support the possibility that the contribution of the neural crest to the endochondral shoulder girdle, which is observed in the mouse, arose de novo in mammals as a developmental basis for their skeletal synapomorphies. This further supports the hypothesis of an increased neural crest diversification during vertebrate evolution.

  18. Neural Crest Does Not Contribute to the Neck and Shoulder in the Axolotl (Ambystoma mexicanum)

    PubMed Central

    Epperlein, Hans-Henning; Khattak, Shahryar; Knapp, Dunja; Tanaka, Elly M.; Malashichev, Yegor B.

    2012-01-01

    Background A major step during the evolution of tetrapods was their transition from water to land. This process involved the reduction or complete loss of the dermal bones that made up connections to the skull and a concomitant enlargement of the endochondral shoulder girdle. In the mouse the latter is derived from three separate embryonic sources: lateral plate mesoderm, somites, and neural crest. The neural crest was suggested to sustain the muscle attachments. How this complex composition of the endochondral shoulder girdle arose during evolution and whether it is shared by all tetrapods is unknown. Salamanders that lack dermal bone within their shoulder girdle were of special interest for a possible contribution of the neural crest to the endochondral elements and muscle attachment sites, and we therefore studied them in this context. Results We grafted neural crest from GFP+ fluorescent transgenic axolotl (Ambystoma mexicanum) donor embryos into white (d/d) axolotl hosts and followed the presence of neural crest cells within the cartilage of the shoulder girdle and the connective tissue of muscle attachment sites of the neck-shoulder region. Strikingly, neural crest cells did not contribute to any part of the endochondral shoulder girdle or to the connective tissue at muscle attachment sites in axolotl. Conclusions Our results in axolotl suggest that neural crest does not serve a general function in vertebrate shoulder muscle attachment sites as predicted by the “muscle scaffold theory,” and that it is not necessary to maintain connectivity of the endochondral shoulder girdle to the skull. Our data support the possibility that the contribution of the neural crest to the endochondral shoulder girdle, which is observed in the mouse, arose de novo in mammals as a developmental basis for their skeletal synapomorphies. This further supports the hypothesis of an increased neural crest diversification during vertebrate evolution. PMID:23300623

  19. Application of the ANNA neural network chip to high-speed character recognition.

    PubMed

    Sackinger, E; Boser, B E; Bromley, J; Lecun, Y; Jackel, L D

    1992-01-01

    A neural network with 136000 connections for recognition of handwritten digits has been implemented using a mixed analog/digital neural network chip. The neural network chip is capable of processing 1000 characters/s. The recognition system has essentially the same rate (5%) as a simulation of the network with 32-b floating-point precision.

  20. Developmental abnormalities of the posterior pituitary gland.

    PubMed

    di Iorgi, Natascia; Secco, Andrea; Napoli, Flavia; Calandra, Erika; Rossi, Andrea; Maghnie, Mohamad

    2009-01-01

    While the molecular mechanisms of anterior pituitary development are now better understood than in the past, both in animals and in humans, little is known about the mechanisms regulating posterior pituitary development. The posterior pituitary gland is formed by the evagination of neural tissue from the floor of the third ventricle. It consists of the distal axons of the hypothalamic magnocellular neurones that shape the neurohypophysis. After its downward migration, it is encapsulated together with the ascending ectodermal cells of Rathke's pouch which form the anterior pituitary. By the end of the first trimester, this development is completed and vasopressin and oxytocin can be detected in neurohypophyseal tissue. Abnormal posterior pituitary migration such as the ectopic posterior pituitary lobe appearing at the level of median eminence or along the pituitary stalk have been reported in idiopathic GH deficiency or in subjects with HESX1, LHX4 and SOX3 gene mutations. Another intriguing feature of abnormal posterior pituitary development involves genetic forms of posterior pituitary neurodegeneration that have been reported in autosomal-dominant central diabetes insipidus and Wolfram disease. Defining the phenotype of the posterior pituitary gland can have significant clinical implications for management and counseling, as well as providing considerable insight into normal and abnormal mechanisms of posterior pituitary development in humans.

  1. Decreased functional connectivity and structural deficit in alertness network with right-sided temporal lobe epilepsy.

    PubMed

    Gao, Yujun; Zheng, Jinou; Li, Yaping; Guo, Danni; Wang, Mingli; Cui, Xiangxiang; Ye, Wei

    2018-04-01

    Patients with temporal lobe epilepsy (TLE) often suffer from alertness alterations. However, specific regions connected with alertness remain controversial, and whether these regions have structural impairment is also elusive. This study aimed to investigate the characteristics and neural mechanisms underlying the functions and structures of alertness network in patients with right-sided temporal lobe epilepsy (rTLE) by performing the attentional network test (ANT), resting-state functional magnetic resonance imaging (R-SfMRI), and diffusion tensor imaging (DTI).A total of 47 patients with rTLE and 34 healthy controls underwent ANT, R-SfMRI, and DTI scan. The seed-based functional connectivity (FC) method and deterministic tractography were used to analyze the data.Patients with rTLE had longer reaction times in the no-cue and double-cue conditions. However, no differences were noted in the alertness effect between the 2 groups. The patient group had lower FC compared with the control group in the right inferior parietal lobe (IPL), amygdala, and insula. Structural deficits were found in the right parahippocampal gyrus, superior temporal pole, insula, and amygdala in the patient group compared with the control group. Also significantly negative correlations were observed between abnormal fractional anisotropy (between the right insula and the superior temporal pole) and illness duration in the patients with rTLE.The findings of this study suggested abnormal intrinsic and phasic alertness, decreased FC, and structural deficits within the alerting network in the rTLE. This study provided new insights into the mechanisms of alertness alterations in rTLE.

  2. Llgl1 Connects Cell Polarity with Cell-Cell Adhesion in Embryonic Neural Stem Cells.

    PubMed

    Jossin, Yves; Lee, Minhui; Klezovitch, Olga; Kon, Elif; Cossard, Alexia; Lien, Wen-Hui; Fernandez, Tania E; Cooper, Jonathan A; Vasioukhin, Valera

    2017-06-05

    Malformations of the cerebral cortex (MCCs) are devastating developmental disorders. We report here that mice with embryonic neural stem-cell-specific deletion of Llgl1 (Nestin-Cre/Llgl1 fl/fl ), a mammalian ortholog of the Drosophila cell polarity gene lgl, exhibit MCCs resembling severe periventricular heterotopia (PH). Immunohistochemical analyses and live cortical imaging of PH formation revealed that disruption of apical junctional complexes (AJCs) was responsible for PH in Nestin-Cre/Llgl1 fl/fl brains. While it is well known that cell polarity proteins govern the formation of AJCs, the exact mechanisms remain unclear. We show that LLGL1 directly binds to and promotes internalization of N-cadherin, and N-cadherin/LLGL1 interaction is inhibited by atypical protein kinase C-mediated phosphorylation of LLGL1, restricting the accumulation of AJCs to the basolateral-apical boundary. Disruption of the N-cadherin-LLGL1 interaction during cortical development in vivo is sufficient for PH. These findings reveal a mechanism responsible for the physical and functional connection between cell polarity and cell-cell adhesion machineries in mammalian cells. Copyright © 2017 Elsevier Inc. All rights reserved.

  3. The Effects of Music Intervention on Functional Connectivity Strength of the Brain in Schizophrenia.

    PubMed

    Yang, Mi; He, Hui; Duan, Mingjun; Chen, Xi; Chang, Xin; Lai, Yongxiu; Li, Jianfu; Liu, Tiejun; Luo, Cheng; Yao, Dezhong

    2018-01-01

    Schizophrenia is often associated with behavior abnormality in the cognitive and affective domain. Music intervention is used as a complementary treatment for improving symptoms in patients with schizophrenia. However, the neurophysiological correlates of these remissions remain poorly understood. Here, we investigated the effects of music intervention in neural circuits through functional magnetic resonance imaging (fMRI) study in schizophrenic subjects. Under the standard care, patients were randomly assigned to music and non-music interventions (MTSZ, UMTSZ) for 1 month. Resting-state fMRI were acquired over three time points (baseline, 1 month, and 6 months later) in patients and analyzed using functional connectivity strength (FCS) and seed-based functional connection (FC) approaches. At baseline, compared with healthy controls, decreased FCS in the right middle temporal gyrus (MTG) was observed in patients. However, after music intervention, the functional circuitry of the right MTG, which was related with the function of emotion and sensorimotor, was improved in MTSZ. Furthermore, the FC increments were significantly correlated with the improvement of symptoms, while vanishing 6 months later. Together, these findings provided evidence that music intervention might positively modulate the functional connectivity of MTG in patients with schizophrenia; such changes might be associated with the observed therapeutic effects of music intervention on neurocognitive function. This trial is registered with ChiCTR-OPC-14005339.

  4. DTI-measured white matter abnormalities in adolescents with Conduct Disorder

    PubMed Central

    Haney-Caron, Emily; Caprihan, Arvind; Stevens, Michael C.

    2013-01-01

    Emerging research suggests that antisocial behavior in youth is linked to abnormal brain white matter microstructure, but the extent of such anatomical connectivity abnormalities remain largely untested because previous Conduct Disorder (CD) studies typically have selectively focused on specific frontotemporal tracts. This study aimed to replicate and extend previous frontotemporal diffusion tensor imaging (DTI) findings to determine whether noncomorbid CD adolescents have white matter microstructural abnormalities in major white matter tracts across the whole brain. Seventeen CD-diagnosed adolescents recruited from the community were compared to a group of 24 non-CD youth which did not differ in average age (12–18) or gender proportion. Tract-based spatial statistics (TBSS) fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD) measurements were compared between groups using FSL nonparametric two-sample t test, clusterwise whole-brain corrected, p<.05. CD FA and AD deficits were widespread, but unrelated to gender, verbal ability, or CD age of onset. CD adolescents had significantly lower FA and AD values in frontal lobe and temporal lobe regions, including frontal lobe anterior/superior corona radiata, and inferior longitudinal and fronto-occpital fasciculi passing through the temporal lobe. The magnitude of several CD FA deficits was associated with number of CD symptoms. Because AD, but not RD, differed between study groups, abnormalities of axonal microstructure in CD rather than myelination are suggested. This study provides evidence that adolescent antisocial disorder is linked to abnormal white matter microstructure in more than just the uncinate fasciulcus as identified in previous DTI studies, or frontotemporal brain structures as suggested by functional neuroimaging studies. Instead, neurobiological risk specific to antisociality in adolescence is linked to microstructural abnormality in numerous long-range white matter

  5. Training and Validating a Deep Convolutional Neural Network for Computer-Aided Detection and Classification of Abnormalities on Frontal Chest Radiographs.

    PubMed

    Cicero, Mark; Bilbily, Alexander; Colak, Errol; Dowdell, Tim; Gray, Bruce; Perampaladas, Kuhan; Barfett, Joseph

    2017-05-01

    Convolutional neural networks (CNNs) are a subtype of artificial neural network that have shown strong performance in computer vision tasks including image classification. To date, there has been limited application of CNNs to chest radiographs, the most frequently performed medical imaging study. We hypothesize CNNs can learn to classify frontal chest radiographs according to common findings from a sufficiently large data set. Our institution's research ethics board approved a single-center retrospective review of 35,038 adult posterior-anterior chest radiographs and final reports performed between 2005 and 2015 (56% men, average age of 56, patient type: 24% inpatient, 39% outpatient, 37% emergency department) with a waiver for informed consent. The GoogLeNet CNN was trained using 3 graphics processing units to automatically classify radiographs as normal (n = 11,702) or into 1 or more of cardiomegaly (n = 9240), consolidation (n = 6788), pleural effusion (n = 7786), pulmonary edema (n = 1286), or pneumothorax (n = 1299). The network's performance was evaluated using receiver operating curve analysis on a test set of 2443 radiographs with the criterion standard being board-certified radiologist interpretation. Using 256 × 256-pixel images as input, the network achieved an overall sensitivity and specificity of 91% with an area under the curve of 0.964 for classifying a study as normal (n = 1203). For the abnormal categories, the sensitivity, specificity, and area under the curve, respectively, were 91%, 91%, and 0.962 for pleural effusion (n = 782), 82%, 82%, and 0.868 for pulmonary edema (n = 356), 74%, 75%, and 0.850 for consolidation (n = 214), 81%, 80%, and 0.875 for cardiomegaly (n = 482), and 78%, 78%, and 0.861 for pneumothorax (n = 167). Current deep CNN architectures can be trained with modest-sized medical data sets to achieve clinically useful performance at detecting and excluding common pathology on chest radiographs.

  6. Neural circuits via which single prolonged stress exposure leads to fear extinction retention deficits

    PubMed Central

    Stanfield, Briana R.; Staib, Jennifer M.; David, Nina P.; Keller, Samantha M.; DePietro, Thomas

    2016-01-01

    Single prolonged stress (SPS) has been used to examine mechanisms via which stress exposure leads to post-traumatic stress disorder symptoms. SPS induces fear extinction retention deficits, but neural circuits critical for mediating these deficits are unknown. To address this gap, we examined the effect of SPS on neural activity in brain regions critical for extinction retention (i.e., fear extinction circuit). These were the ventral hippocampus (vHipp), dorsal hippocampus (dHipp), basolateral amygdala (BLA), prelimbic cortex (PL), and infralimbic cortex (IL). SPS or control rats were fear conditioned then subjected to extinction training and testing. Subsets of rats were euthanized after extinction training, extinction testing, or immediate removal from the housing colony (baseline condition) to assay c-Fos levels (measure of neural activity) in respective brain region. SPS induced extinction retention deficits. During extinction training SPS disrupted enhanced IL neural activity and inhibited BLA neural activity. SPS also disrupted inhibited BLA and vHipp neural activity during extinction testing. Statistical analyses suggested that SPS disrupted functional connectivity within the dHipp during extinction training and increased functional connectivity between the BLA and vHipp during extinction testing. Our findings suggest that SPS induces extinction retention deficits by disrupting both excitatory and inhibitory changes in neural activity within the fear extinction circuit and inducing changes in functional connectivity within the Hipp and BLA. PMID:27918273

  7. XYY chromosome abnormality in sexual homicide perpetrators.

    PubMed

    Briken, Peer; Habermann, Niels; Berner, Wolfgang; Hill, Andreas

    2006-03-05

    In a retrospective investigation of the court reports about sexual homicide perpetrators chromosome analysis had been carried out in 13 of 166 (7.8%) men. Three men (1.8%) with XYY chromosome abnormality were found. This rate is much higher than that found in unselected samples of prisoners (0.7-0.9%) or in the general population (0.01%). The three men had shown prepubescent abnormalities, school problems, and had suffered from physical abuse. The chromosome analysis in all cases had been carried out in connection with the forensic psychiatric court report due to the sexual homicide. However, two men had earlier psychiatric referrals. All were diagnosed as sexual sadistic, showed a psychopathic syndrome or psychopathy according to the Psychopathy Checklist-Revised [Hare RD, 1991, The Hare Psychopathy Checklist-Revised, Toronto, Ontario, Canada: Multi-Health Systems]. Two were multiple murderers. Especially forensic psychiatrists should be vigilant of the possibility of XYY chromosome abnormalities in sexual offenders. (c) 2006 Wiley-Liss, Inc.

  8. Neural networks for vertical microcode compaction

    NASA Astrophysics Data System (ADS)

    Chu, Pong P.

    1992-09-01

    Neural networks provide an alternative way to solve complex optimization problems. Instead of performing a program of instructions sequentially as in a traditional computer, neural network model explores many competing hypotheses simultaneously using its massively parallel net. The paper shows how to use the neural network approach to perform vertical micro-code compaction for a micro-programmed control unit. The compaction procedure includes two basic steps. The first step determines the compatibility classes and the second step selects a minimal subset to cover the control signals. Since the selection process is an NP- complete problem, to find an optimal solution is impractical. In this study, we employ a customized neural network to obtain the minimal subset. We first formalize this problem, and then define an `energy function' and map it to a two-layer fully connected neural network. The modified network has two types of neurons and can always obtain a valid solution.

  9. Interleukin-6 Regulates Adult Neural Stem Cell Numbers during Normal and Abnormal Post-natal Development.

    PubMed

    Storer, Mekayla A; Gallagher, Denis; Fatt, Michael P; Simonetta, Jaclin V; Kaplan, David R; Miller, Freda D

    2018-05-08

    Circulating systemic factors can regulate adult neural stem cell (NSC) biology, but the identity of these circulating cues is still being defined. Here, we have focused on the cytokine interleukin-6 (IL-6), since increased circulating levels of IL-6 are associated with neural pathologies such as autism and bipolar disorder. We show that IL-6 promotes proliferation of post-natal murine forebrain NSCs and that, when the IL-6 receptor is inducibly knocked out in post-natal or adult neural precursors, this causes a long-term decrease in forebrain NSCs. Moreover, a transient circulating surge of IL-6 in perinatal or adult mice causes an acute increase in neural precursor proliferation followed by long-term depletion of adult NSC pools. Thus, IL-6 signaling is both necessary and sufficient for adult NSC self-renewal, and acute perturbations in circulating IL-6, as observed in many pathological situations, have long-lasting effects on the size of adult NSC pools. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

  10. Modulation of frontal effective connectivity during speech.

    PubMed

    Holland, Rachel; Leff, Alex P; Penny, William D; Rothwell, John C; Crinion, Jenny

    2016-10-15

    Noninvasive neurostimulation methods such as transcranial direct current stimulation (tDCS) can elicit long-lasting, polarity-dependent changes in neocortical excitability. In a previous concurrent tDCS-fMRI study of overt picture naming, we reported significant behavioural and regionally specific neural facilitation effects in left inferior frontal cortex (IFC) with anodal tDCS applied to left frontal cortex (Holland et al., 2011). Although distributed connectivity effects of anodal tDCS have been modelled at rest, the mechanism by which 'on-line' tDCS may modulate neuronal connectivity during a task-state remains unclear. Here, we used Dynamic Causal Modelling (DCM) to determine: (i) how neural connectivity within the frontal speech network is modulated during anodal tDCS; and, (ii) how individual variability in behavioural response to anodal tDCS relates to changes in effective connectivity strength. Results showed that compared to sham, anodal tDCS elicited stronger feedback from inferior frontal sulcus (IFS) to ventral premotor (VPM) accompanied by weaker self-connections within VPM, consistent with processes of neuronal adaptation. During anodal tDCS individual variability in the feedforward connection strength from IFS to VPM positively correlated with the degree of facilitation in naming behaviour. These results provide an essential step towards understanding the mechanism of 'online' tDCS paired with a cognitive task. They also identify left IFS as a 'top-down' hub and driver for speech change. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  11. Neural tube closure depends on expression of Grainyhead-like 3 in multiple tissues.

    PubMed

    De Castro, Sandra C P; Hirst, Caroline S; Savery, Dawn; Rolo, Ana; Lickert, Heiko; Andersen, Bogi; Copp, Andrew J; Greene, Nicholas D E

    2018-03-15

    Failure of neural tube closure leads to neural tube defects (NTDs), common congenital abnormalities in humans. Among the genes whose loss of function causes NTDs in mice, Grainyhead-like3 (Grhl3) is essential for spinal neural tube closure, with null mutants exhibiting fully penetrant spina bifida. During spinal neurulation Grhl3 is initially expressed in the surface (non-neural) ectoderm, subsequently in the neuroepithelial component of the neural folds and at the node-streak border, and finally in the hindgut endoderm. Here, we show that endoderm-specific knockout of Grhl3 causes late-arising spinal NTDs, preceded by increased ventral curvature of the caudal region which was shown previously to suppress closure of the spinal neural folds. This finding supports the hypothesis that diminished Grhl3 expression in the hindgut is the cause of spinal NTDs in the curly tail, carrying a hypomorphic Grhl3 allele. Complete loss of Grhl3 function produces a more severe phenotype in which closure fails earlier in neurulation, before the stage of onset of expression in the hindgut of wild-type embryos. This implicates additional tissues and NTD mechanisms in Grhl3 null embryos. Conditional knockout of Grhl3 in the neural plate and node-streak border has minimal effect on closure, suggesting that abnormal function of surface ectoderm, where Grhl3 transcripts are first detected, is primarily responsible for early failure of spinal neurulation in Grhl3 null embryos. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

  12. Enhanced storage capacity with errors in scale-free Hopfield neural networks: An analytical study.

    PubMed

    Kim, Do-Hyun; Park, Jinha; Kahng, Byungnam

    2017-01-01

    The Hopfield model is a pioneering neural network model with associative memory retrieval. The analytical solution of the model in mean field limit revealed that memories can be retrieved without any error up to a finite storage capacity of O(N), where N is the system size. Beyond the threshold, they are completely lost. Since the introduction of the Hopfield model, the theory of neural networks has been further developed toward realistic neural networks using analog neurons, spiking neurons, etc. Nevertheless, those advances are based on fully connected networks, which are inconsistent with recent experimental discovery that the number of connections of each neuron seems to be heterogeneous, following a heavy-tailed distribution. Motivated by this observation, we consider the Hopfield model on scale-free networks and obtain a different pattern of associative memory retrieval from that obtained on the fully connected network: the storage capacity becomes tremendously enhanced but with some error in the memory retrieval, which appears as the heterogeneity of the connections is increased. Moreover, the error rates are also obtained on several real neural networks and are indeed similar to that on scale-free model networks.

  13. Schaffer Collateral Inputs to CA1 Excitatory and Inhibitory Neurons Follow Different Connectivity Rules.

    PubMed

    Kwon, Osung; Feng, Linqing; Druckmann, Shaul; Kim, Jinhyun

    2018-05-30

    Neural circuits, governed by a complex interplay between excitatory and inhibitory neurons, are the substrate for information processing, and the organization of synaptic connectivity in neural network is an important determinant of circuit function. Here, we analyzed the fine structure of connectivity in hippocampal CA1 excitatory and inhibitory neurons innervated by Schaffer collaterals (SCs) using mGRASP in male mice. Our previous study revealed spatially structured synaptic connectivity between CA3 and CA1 pyramidal cells (PCs). Surprisingly, parvalbumin-positive interneurons (PVs) showed a significantly more random pattern spatial structure. Notably, application of Peters' rule for synapse prediction by random overlap between axons and dendrites enhanced structured connectivity in PCs, but, by contrast, made the connectivity pattern in PVs more random. In addition, PCs in a deep sublayer of striatum pyramidale appeared more highly structured than PCs in superficial layers, and little or no sublayer specificity was found in PVs. Our results show that CA1 excitatory PCs and inhibitory PVs innervated by the same SC inputs follow different connectivity rules. The different organizations of fine scale structured connectivity in hippocampal excitatory and inhibitory neurons provide important insights into the development and functions of neural networks. SIGNIFICANCE STATEMENT Understanding how neural circuits generate behavior is one of the central goals of neuroscience. An important component of this endeavor is the mapping of fine-scale connection patterns that underlie, and help us infer, signal processing in the brain. Here, using our recently developed synapse detection technology (mGRASP and neuTube), we provide detailed profiles of synaptic connectivity in excitatory (CA1 pyramidal) and inhibitory (CA1 parvalbumin-positive) neurons innervated by the same presynaptic inputs (CA3 Schaffer collaterals). Our results reveal that these two types of CA1 neurons

  14. Inter-hemispheric functional connectivity disruption in children with prenatal alcohol exposure

    PubMed Central

    Wozniak, Jeffrey R.; Mueller, Bryon A.; Muetzel, Ryan L.; Bell, Christopher J.; Hoecker, Heather L.; Nelson, Miranda L.; Chang, Pi-Nian; Lim, Kelvin O.

    2010-01-01

    Background MRI studies, including recent diffusion tensor imaging (DTI) studies, have shown corpus callosum abnormalities in children prenatally exposed to alcohol, especially in the posterior regions. These abnormalities appear across the range of Fetal Alcohol Spectrum Disorders (FASD). Several studies have demonstrated cognitive correlates of callosal abnormalities in FASD including deficits in visual-motor skill, verbal learning, and executive functioning. The goal of this study was to determine if inter-hemispheric structural connectivity abnormalities in FASD are associated with disrupted inter-hemispheric functional connectivity and disrupted cognition. Methods Twenty-one children with FASD and 23 matched controls underwent a six minute resting-state functional MRI scan as well as anatomical imaging and DTI. Using a semiautomated method, we parsed the corpus callosum and delineated seven inter-hemispheric white matter tracts with DTI tractography. Cortical regions of interest (ROIs) at the distal ends of these tracts were identified. Right-left correlations in resting fMRI signal were computed for these sets of ROIs and group comparisons were done. Correlations with facial dysmorphology, cognition, and DTI measures were computed. Results A significant group difference in inter-hemispheric functional connectivity was seen in a posterior set of ROIs, the para-central region. Children with FASD had functional connectivity that was 12% lower than controls in this region. Sub-group analyses were not possible due to small sample size, but the data suggest that there were effects across the FASD spectrum. No significant association with facial dysmorphology was found. Para-central functional connectivity was significantly correlated with DTI mean diffusivity, a measure of microstructural integrity, in posterior callosal tracts in controls but not in FASD. Significant correlations were seen between these structural and functional measures and Wechsler perceptual

  15. Cortical connective field estimates from resting state fMRI activity.

    PubMed

    Gravel, Nicolás; Harvey, Ben; Nordhjem, Barbara; Haak, Koen V; Dumoulin, Serge O; Renken, Remco; Curčić-Blake, Branislava; Cornelissen, Frans W

    2014-01-01

    One way to study connectivity in visual cortical areas is by examining spontaneous neural activity. In the absence of visual input, such activity remains shaped by the underlying neural architecture and, presumably, may still reflect visuotopic organization. Here, we applied population connective field (CF) modeling to estimate the spatial profile of functional connectivity in the early visual cortex during resting state functional magnetic resonance imaging (RS-fMRI). This model-based analysis estimates the spatial integration between blood-oxygen level dependent (BOLD) signals in distinct cortical visual field maps using fMRI. Just as population receptive field (pRF) mapping predicts the collective neural activity in a voxel as a function of response selectivity to stimulus position in visual space, CF modeling predicts the activity of voxels in one visual area as a function of the aggregate activity in voxels in another visual area. In combination with pRF mapping, CF locations on the cortical surface can be interpreted in visual space, thus enabling reconstruction of visuotopic maps from resting state data. We demonstrate that V1 ➤ V2 and V1 ➤ V3 CF maps estimated from resting state fMRI data show visuotopic organization. Therefore, we conclude that-despite some variability in CF estimates between RS scans-neural properties such as CF maps and CF size can be derived from resting state data.

  16. Aberrant Intrinsic Activity and Connectivity in Cognitively Normal Parkinson's Disease.

    PubMed

    Harrington, Deborah L; Shen, Qian; Castillo, Gabriel N; Filoteo, J Vincent; Litvan, Irene; Takahashi, Colleen; French, Chelsea

    2017-01-01

    Disturbances in intrinsic activity during resting-state functional MRI (rsfMRI) are common in Parkinson's disease (PD), but have largely been studied in a priori defined subnetworks. The cognitive significance of abnormal intrinsic activity is also poorly understood, as are abnormalities that precede the onset of mild cognitive impairment. To address these limitations, we leveraged three different analytic approaches to identify disturbances in rsfMRI metrics in 31 cognitively normal PD patients (PD-CN) and 30 healthy adults. Subjects were screened for mild cognitive impairment using the Movement Disorders Society Task Force Level II criteria. Whole-brain data-driven analytic approaches first analyzed the amplitude of low-frequency intrinsic fluctuations (ALFF) and regional homogeneity (ReHo), a measure of local connectivity amongst functionally similar regions. We then examined if regional disturbances in these metrics altered functional connectivity with other brain regions. We also investigated if abnormal rsfMRI metrics in PD-CN were related to brain atrophy and executive, visual organization, and episodic memory functioning. The results revealed abnormally increased and decreased ALFF and ReHo in PD-CN patients within the default mode network (posterior cingulate, inferior parietal cortex, parahippocampus, entorhinal cortex), sensorimotor cortex (primary motor, pre/post-central gyrus), basal ganglia (putamen, caudate), and posterior cerebellar lobule VII, which mediates cognition. For default mode network regions, we also observed a compound profile of altered ALFF and ReHo. Most regional disturbances in ALFF and ReHo were associated with strengthened long-range interactions in PD-CN, notably with regions in different networks. Stronger long-range functional connectivity in PD-CN was also partly expanded to connections that were outside the networks of the control group. Abnormally increased activity and functional connectivity appeared to have a pathological

  17. Salience Network Connectivity Modulates Skin Conductance Responses in Predicting Arousal Experience

    PubMed Central

    Xia, Chenjie; Touroutoglou, Alexandra; Quigley, Karen S.; Barrett, Lisa Feldman; Dickerson, Bradford C.

    2017-01-01

    Individual differences in arousal experience have been linked to differences in resting-state salience network connectivity strength. In this study, we investigated how adding task-related skin conductance responses (SCR), a measure of sympathetic autonomic nervous system activity, can predict additional variance in arousal experience. Thirty-nine young adults rated their subjective experience of arousal to emotionally evocative images while SCRs were measured. They also underwent a separate resting-state fMRI scan. Greater SCR reactivity (an increased number of task-related SCRs) to emotional images and stronger intrinsic salience network connectivity independently predicted more intense experiences of arousal. Salience network connectivity further moderated the effect of SCR reactivity: In individuals with weak salience network connectivity, SCR reactivity more significantly predicted arousal experience, whereas in those with strong salience network connectivity, SCR reactivity played little role in predicting arousal experience. This interaction illustrates the degeneracy in neural mechanisms driving individual differences in arousal experience and highlights the intricate interplay between connectivity in central visceromotor neural circuitry and peripherally expressed autonomic responses in shaping arousal experience. PMID:27991182

  18. Neural Network Development Tool (NETS)

    NASA Technical Reports Server (NTRS)

    Baffes, Paul T.

    1990-01-01

    Artificial neural networks formed from hundreds or thousands of simulated neurons, connected in manner similar to that in human brain. Such network models learning behavior. Using NETS involves translating problem to be solved into input/output pairs, designing network configuration, and training network. Written in C.

  19. Voltage-sensitive-dye imaging of microstimulation-evoked neural activity through intracortical horizontal and callosal connections in cat visual cortex.

    PubMed

    Suzurikawa, Jun; Tani, Toshiki; Nakao, Masayuki; Tanaka, Shigeru; Takahashi, Hirokazu

    2009-12-01

    Recently, intrinsic signal optical imaging has been widely used as a routine procedure for visualizing cortical functional maps. We do not, however, have a well-established imaging method for visualizing cortical functional connectivity indicating spatio-temporal patterns of activity propagation in the cerebral cortex. In the present study, we developed a novel experimental setup for investigating the propagation of neural activities combining the intracortical microstimulation (ICMS) technique with voltage sensitive dye (VSD) imaging, and demonstrated the feasibility of this setup applying to the measurement of time-dependent intra- and inter-hemispheric spread of ICMS-evoked excitation in the cat visual cortices, areas 17 and 18. A microelectrode array for the ICMS was inserted with a specially designed easy-to-detach electrode holder around the 17/18 transition zones (TZs), where the left and right hemispheres were interconnected via the corpus callosum. The microelectrode array was stably anchored in agarose without any holder, which enabled us to visualize evoked activities even in the vicinity of penetration sites as well as in a wide recording region that covered a part of both hemispheres. The VSD imaging could successfully visualize ICMS-evoked excitation and subsequent propagation in the visual cortices contralateral as well as ipsilateral to the ICMS. Using the orientation maps as positional references, we showed that the activity propagation patterns were consistent with previously reported anatomical patterns of intracortical and interhemispheric connections. This finding indicates that our experimental system can serve for the investigation of cortical functional connectivity.

  20. Automated radial basis function neural network based image classification system for diabetic retinopathy detection in retinal images

    NASA Astrophysics Data System (ADS)

    Anitha, J.; Vijila, C. Kezi Selva; Hemanth, D. Jude

    2010-02-01

    Diabetic retinopathy (DR) is a chronic eye disease for which early detection is highly essential to avoid any fatal results. Image processing of retinal images emerge as a feasible tool for this early diagnosis. Digital image processing techniques involve image classification which is a significant technique to detect the abnormality in the eye. Various automated classification systems have been developed in the recent years but most of them lack high classification accuracy. Artificial neural networks are the widely preferred artificial intelligence technique since it yields superior results in terms of classification accuracy. In this work, Radial Basis function (RBF) neural network based bi-level classification system is proposed to differentiate abnormal DR Images and normal retinal images. The results are analyzed in terms of classification accuracy, sensitivity and specificity. A comparative analysis is performed with the results of the probabilistic classifier namely Bayesian classifier to show the superior nature of neural classifier. Experimental results show promising results for the neural classifier in terms of the performance measures.

  1. Dishevelled is essential for neural connectivity and planar cell polarity in planarians.

    PubMed

    Almuedo-Castillo, Maria; Saló, Emili; Adell, Teresa

    2011-02-15

    The Wingless/Integrated (Wnt) signaling pathway controls multiple events during development and homeostasis. It comprises multiple branches, mainly classified according to their dependence on β-catenin activation. The Wnt/β-catenin branch is essential for the establishment of the embryonic anteroposterior (AP) body axis throughout the phylogenetic tree. It is also required for AP axis establishment during planarian regeneration. Wnt/β-catenin-independent signaling encompasses several different pathways, of which the most extensively studied is the planar cell polarity (PCP) pathway, which is responsible for planar polarization of cell structures within an epithelial sheet. Dishevelled (Dvl) is the hub of Wnt signaling because it regulates and channels the Wnt signal into every branch. Here, we analyze the role of Schmidtea mediterranea Dvl homologs (Smed-dvl-1 and Smed-dvl-2) using gene silencing. We demonstrate that in addition to a role in AP axis specification, planarian Dvls are involved in at least two different β-catenin-independent processes. First, they are essential for neural connectivity through Smed-wnt5 signaling. Second, Smed-dvl-2, together with the S. mediterranea homologs of Van-Gogh (Vang) and Diversin (Div), is required for apical positioning of the basal bodies of epithelial cells. These data represent evidence not only of the function of the PCP network in lophotrocozoans but of the involvement of the PCP core elements Vang and Div in apical positioning of the cilia.

  2. Dishevelled is essential for neural connectivity and planar cell polarity in planarians

    PubMed Central

    Almuedo-Castillo, Maria; Saló, Emili; Adell, Teresa

    2011-01-01

    The Wingless/Integrated (Wnt) signaling pathway controls multiple events during development and homeostasis. It comprises multiple branches, mainly classified according to their dependence on β-catenin activation. The Wnt/β-catenin branch is essential for the establishment of the embryonic anteroposterior (AP) body axis throughout the phylogenetic tree. It is also required for AP axis establishment during planarian regeneration. Wnt/β-catenin–independent signaling encompasses several different pathways, of which the most extensively studied is the planar cell polarity (PCP) pathway, which is responsible for planar polarization of cell structures within an epithelial sheet. Dishevelled (Dvl) is the hub of Wnt signaling because it regulates and channels the Wnt signal into every branch. Here, we analyze the role of Schmidtea mediterranea Dvl homologs (Smed-dvl-1 and Smed-dvl-2) using gene silencing. We demonstrate that in addition to a role in AP axis specification, planarian Dvls are involved in at least two different β-catenin–independent processes. First, they are essential for neural connectivity through Smed-wnt5 signaling. Second, Smed-dvl-2, together with the S. mediterranea homologs of Van-Gogh (Vang) and Diversin (Div), is required for apical positioning of the basal bodies of epithelial cells. These data represent evidence not only of the function of the PCP network in lophotrocozoans but of the involvement of the PCP core elements Vang and Div in apical positioning of the cilia. PMID:21282632

  3. Model for neural signaling leap statistics

    NASA Astrophysics Data System (ADS)

    Chevrollier, Martine; Oriá, Marcos

    2011-03-01

    We present a simple model for neural signaling leaps in the brain considering only the thermodynamic (Nernst) potential in neuron cells and brain temperature. We numerically simulated connections between arbitrarily localized neurons and analyzed the frequency distribution of the distances reached. We observed qualitative change between Normal statistics (with T = 37.5°C, awaken regime) and Lévy statistics (T = 35.5°C, sleeping period), characterized by rare events of long range connections.

  4. Autism spectrum disorder and early motor abnormalities: Connected or coincidental companions?

    PubMed

    Setoh, Peipei; Marschik, Peter B; Einspieler, Christa; Esposito, Gianluca

    2017-01-01

    Research in the past decade has produced a growing body of evidence showing that motor abnormalities in individuals with autism spectrum disorder (ASD) are the rule rather than the exception. The paper by Chinello and colleagues furthers our understanding of the importance of studying motor functions in ASD by testing a non-clinical population of parents-infant triads. Chinello and colleagues' findings seem to suggest that subclinical motor impairments may exist in the typical population with inherited non-clinical ASD traits. Chinello and colleagues' discovery also urges us to ask why motor abnormalities exist in typically developing infants when their parents present some subclinical ASD traits. We believe that there are at least two possibilities. In the first possible scenario, motor impairments and ASD traits form a single cluster of symptoms unique to a subgroup of individuals with autism. A second possible scenario is that motor atypicalities are the first warning signs of vulnerability often associated with atypical development. In conclusion, Chinello et al.'s findings inform us that subclinical atypical phenotypes such as sociocommunicative anomalies may be related to subclinical motor performances in the next generation. This adds to our knowledge by shedding some light on the relation of vulnerability in one domain with vulnerability in another domain. Copyright © 2016 Elsevier Ltd. All rights reserved.

  5. Distributed Neural Activity Patterns during Human-to-Human Competition

    PubMed Central

    Piva, Matthew; Zhang, Xian; Noah, J. Adam; Chang, Steve W. C.; Hirsch, Joy

    2017-01-01

    Interpersonal interaction is the essence of human social behavior. However, conventional neuroimaging techniques have tended to focus on social cognition in single individuals rather than on dyads or groups. As a result, relatively little is understood about the neural events that underlie face-to-face interaction. We resolved some of the technical obstacles inherent in studying interaction using a novel imaging modality and aimed to identify neural mechanisms engaged both within and across brains in an ecologically valid instance of interpersonal competition. Functional near-infrared spectroscopy was utilized to simultaneously measure hemodynamic signals representing neural activity in pairs of subjects playing poker against each other (human–human condition) or against computer opponents (human–computer condition). Previous fMRI findings concerning single subjects confirm that neural areas recruited during social cognition paradigms are individually sensitive to human–human and human–computer conditions. However, it is not known whether face-to-face interactions between opponents can extend these findings. We hypothesize distributed effects due to live processing and specific variations in across-brain coherence not observable in single-subject paradigms. Angular gyrus (AG), a component of the temporal-parietal junction (TPJ) previously found to be sensitive to socially relevant cues, was selected as a seed to measure within-brain functional connectivity. Increased connectivity was confirmed between AG and bilateral dorsolateral prefrontal cortex (dlPFC) as well as a complex including the left subcentral area (SCA) and somatosensory cortex (SS) during interaction with a human opponent. These distributed findings were supported by contrast measures that indicated increased activity at the left dlPFC and frontopolar area that partially overlapped with the region showing increased functional connectivity with AG. Across-brain analyses of neural coherence

  6. A new optimized GA-RBF neural network algorithm.

    PubMed

    Jia, Weikuan; Zhao, Dean; Shen, Tian; Su, Chunyang; Hu, Chanli; Zhao, Yuyan

    2014-01-01

    When confronting the complex problems, radial basis function (RBF) neural network has the advantages of adaptive and self-learning ability, but it is difficult to determine the number of hidden layer neurons, and the weights learning ability from hidden layer to the output layer is low; these deficiencies easily lead to decreasing learning ability and recognition precision. Aiming at this problem, we propose a new optimized RBF neural network algorithm based on genetic algorithm (GA-RBF algorithm), which uses genetic algorithm to optimize the weights and structure of RBF neural network; it chooses new ways of hybrid encoding and optimizing simultaneously. Using the binary encoding encodes the number of the hidden layer's neurons and using real encoding encodes the connection weights. Hidden layer neurons number and connection weights are optimized simultaneously in the new algorithm. However, the connection weights optimization is not complete; we need to use least mean square (LMS) algorithm for further leaning, and finally get a new algorithm model. Using two UCI standard data sets to test the new algorithm, the results show that the new algorithm improves the operating efficiency in dealing with complex problems and also improves the recognition precision, which proves that the new algorithm is valid.

  7. Temporal Information of Directed Causal Connectivity in Multi-Trial ERP Data using Partial Granger Causality.

    PubMed

    Youssofzadeh, Vahab; Prasad, Girijesh; Naeem, Muhammad; Wong-Lin, KongFatt

    2016-01-01

    Partial Granger causality (PGC) has been applied to analyse causal functional neural connectivity after effectively mitigating confounding influences caused by endogenous latent variables and exogenous environmental inputs. However, it is not known how this connectivity obtained from PGC evolves over time. Furthermore, PGC has yet to be tested on realistic nonlinear neural circuit models and multi-trial event-related potentials (ERPs) data. In this work, we first applied a time-domain PGC technique to evaluate simulated neural circuit models, and demonstrated that the PGC measure is more accurate and robust in detecting connectivity patterns as compared to conditional Granger causality and partial directed coherence, especially when the circuit is intrinsically nonlinear. Moreover, the connectivity in PGC settles faster into a stable and correct configuration over time. After method verification, we applied PGC to reveal the causal connections of ERP trials of a mismatch negativity auditory oddball paradigm. The PGC analysis revealed a significant bilateral but asymmetrical localised activity in the temporal lobe close to the auditory cortex, and causal influences in the frontal, parietal and cingulate cortical areas, consistent with previous studies. Interestingly, the time to reach a stable connectivity configuration (~250–300 ms) coincides with the deviation of ensemble ERPs of oddball from standard tones. Finally, using a sliding time window, we showed higher resolution dynamics of causal connectivity within an ERP trial. In summary, time-domain PGC is promising in deciphering directed functional connectivity in nonlinear and ERP trials accurately, and at a sufficiently early stage. This data-driven approach can reduce computational time, and determine the key architecture for neural circuit modeling.

  8. Left-Hemispheric Microstructural Abnormalities in Children With High Functioning Autism Spectrum Disorder

    PubMed Central

    Peterson, Daniel; Mahajan, Rajneesh; Crocetti, Deana; Mejia, Amanda; Mostofsky, Stewart

    2014-01-01

    Current theories of the neurobiological basis of Autism Spectrum Disorder (ASD) posit an altered pattern of connectivity in large-scale brain networks. Here we used Diffusion Tensor Imaging to investigate the microstructural properties of the white matter that mediates inter-regional connectivity in 36 high-functioning children with ASD (HF-ASD), as compared to 37 controls. By employing an atlas-based analysis using LDDMM registration, a widespread, but left-lateralized pattern of abnormalities was revealed. The Mean Diffusivity (MD) of water in the white matter of HF-ASD children was significantly elevated throughout the left hemisphere, particularly in the outer-zone cortical white matter. Across diagnostic groups there was a significant effect of age on left hemisphere MD, with a similar reduction in MD during childhood in both TD and HF-ASD children. The increased MD in children with HF-ASD suggests hypomyelination, and may reflect increased short-range cortico-cortical connections subsequent to early white matter overgrowth. These findings also highlight left hemispheric connectivity as relevant to the pathophysiology of ASD, and indicate that the spatial distribution of microstructural abnormalities in HF-ASD is widespread, and left-lateralized. This altered left-hemispheric connectivity may contribute to deficits in communication and praxis observed in ASD. PMID:25256103

  9. Male Killing Spiroplasma Preferentially Disrupts Neural Development in the Drosophila melanogaster Embryo

    PubMed Central

    Martin, Jennifer; Chong, Trisha; Ferree, Patrick M.

    2013-01-01

    Male killing bacteria such as Spiroplasma are widespread pathogens of numerous arthropods including Drosophila melanogaster. These maternally transmitted bacteria can bias host sex ratios toward the female sex in order to ‘selfishly’ enhance bacterial transmission. However, little is known about the specific means by which these pathogens disrupt host development in order to kill males. Here we show that a male-killing Spiroplasma strain severely disrupts nervous tissue development in male but not female D. melanogaster embryos. The neuroblasts, or neuron progenitors, form properly and their daughter cells differentiate into neurons of the ventral nerve chord. However, the neurons fail to pack together properly and they produce highly abnormal axons. In contrast, non-neural tissue, such as mesoderm, and body segmentation appear normal during this time, although the entire male embryo becomes highly abnormal during later stages. Finally, we found that Spiroplasma is altogether absent from the neural tissue but localizes within the gut and the epithelium immediately surrounding the neural tissue, suggesting that the bacterium secretes a toxin that affects neural tissue development across tissue boundaries. Together these findings demonstrate the unique ability of this insect pathogen to preferentially affect development of a specific embryonic tissue to induce male killing. PMID:24236124

  10. Recurrent Convolutional Neural Networks: A Better Model of Biological Object Recognition.

    PubMed

    Spoerer, Courtney J; McClure, Patrick; Kriegeskorte, Nikolaus

    2017-01-01

    Feedforward neural networks provide the dominant model of how the brain performs visual object recognition. However, these networks lack the lateral and feedback connections, and the resulting recurrent neuronal dynamics, of the ventral visual pathway in the human and non-human primate brain. Here we investigate recurrent convolutional neural networks with bottom-up (B), lateral (L), and top-down (T) connections. Combining these types of connections yields four architectures (B, BT, BL, and BLT), which we systematically test and compare. We hypothesized that recurrent dynamics might improve recognition performance in the challenging scenario of partial occlusion. We introduce two novel occluded object recognition tasks to test the efficacy of the models, digit clutter (where multiple target digits occlude one another) and digit debris (where target digits are occluded by digit fragments). We find that recurrent neural networks outperform feedforward control models (approximately matched in parametric complexity) at recognizing objects, both in the absence of occlusion and in all occlusion conditions. Recurrent networks were also found to be more robust to the inclusion of additive Gaussian noise. Recurrent neural networks are better in two respects: (1) they are more neurobiologically realistic than their feedforward counterparts; (2) they are better in terms of their ability to recognize objects, especially under challenging conditions. This work shows that computer vision can benefit from using recurrent convolutional architectures and suggests that the ubiquitous recurrent connections in biological brains are essential for task performance.

  11. Whole-brain functional connectivity identification of functional dyspepsia.

    PubMed

    Nan, Jiaofen; Liu, Jixin; Li, Guoying; Xiong, Shiwei; Yan, Xuemei; Yin, Qing; Zeng, Fang; von Deneen, Karen M; Liang, Fanrong; Gong, Qiyong; Qin, Wei; Tian, Jie

    2013-01-01

    Recent neuroimaging studies have shown local brain aberrations in functional dyspepsia (FD) patients, yet little attention has been paid to the whole-brain resting-state functional network abnormalities. The purpose of this study was to investigate whether FD disrupts the patterns of whole-brain networks and the abnormal functional connectivity could reflect the severity of the disease. The dysfunctional interactions between brain regions at rest were investigated in FD patients as compared with 40 age- and gender- matched healthy controls. Multivariate pattern analysis was used to evaluate the discriminative power of our results for classifying patients from controls. In our findings, the abnormal brain functional connections were mainly situated within or across the limbic/paralimbic system, the prefrontal cortex, the tempo-parietal areas and the visual cortex. About 96% of the subjects among the original dataset were correctly classified by a leave one-out cross-validation approach, and 88% accuracy was also validated in a replication dataset. The classification features were significantly associated with the patients' dyspepsia symptoms, the self-rating depression scale and self-rating anxiety scale, but it was not correlated with duration of FD patients (p>0.05). Our results may indicate the effectiveness of the altered brain functional connections reflecting the disease pathophysiology underling FD. These dysfunctional connections may be the epiphenomena or causative agents of FD, which may be affected by clinical severity and its related emotional dimension of the disease rather than the clinical course.

  12. Disambiguating brain functional connectivity.

    PubMed

    Duff, Eugene P; Makin, Tamar; Cottaar, Michiel; Smith, Stephen M; Woolrich, Mark W

    2018-06-01

    Functional connectivity (FC) analyses of correlations of neural activity are used extensively in neuroimaging and electrophysiology to gain insights into neural interactions. However, analyses assessing changes in correlation fail to distinguish effects produced by sources as different as changes in neural signal amplitudes or noise levels. This ambiguity substantially diminishes the value of FC for inferring system properties and clinical states. Network modelling approaches may avoid ambiguities, but require specific assumptions. We present an enhancement to FC analysis with improved specificity of inferences, minimal assumptions and no reduction in flexibility. The Additive Signal Change (ASC) approach characterizes FC changes into certain prevalent classes of signal change that involve the input of additional signal to existing activity. With FMRI data, the approach reveals a rich diversity of signal changes underlying measured changes in FC, suggesting that it could clarify our current understanding of FC changes in many contexts. The ASC method can also be used to disambiguate other measures of dependency, such as regression and coherence, providing a flexible tool for the analysis of neural data. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

  13. Aberrant functional connectivity of default-mode network in type 2 diabetes patients.

    PubMed

    Cui, Ying; Jiao, Yun; Chen, Hua-Jun; Ding, Jie; Luo, Bing; Peng, Cheng-Yu; Ju, Sheng-Hong; Teng, Gao-Jun

    2015-11-01

    Type 2 diabetes mellitus is associated with increased risk for dementia. Patients with impaired cognition often show default-mode network disruption. We aimed to investigate the integrity of a default-mode network in diabetic patients by using independent component analysis, and to explore the relationship between network abnormalities, neurocognitive performance and diabetic variables. Forty-two patients with type 2 diabetes and 42 well-matched healthy controls were included and underwent resting-state functional MRI in a 3 Tesla unit. Independent component analysis was adopted to extract the default-mode network, including its anterior and posterior components. Z-maps of both sub-networks were compared between the two groups and correlated with each clinical variable. Patients showed increased connectivity around the medial prefrontal cortex in the anterior sub-network, but decreased connectivity around the posterior cingulate cortex in the posterior sub-network. The decreased connectivity in the posterior part was significantly correlated with the score on Complex Figure Test-delay recall test (r = 0.359, p = 0.020), the time spent on Trail-Making Test-part B (r = -0.346, p = 0.025) and the insulin resistance level (r = -0.404, p = 0.024). Dissociation pattern in the default-mode network was found in diabetic patients, which might provide powerful new insights into the neural mechanisms that underlie the diabetes-related cognitive decline. • Type 2 diabetes mellitus is associated with impaired cognition • Default- mode network plays a central role in maintaining normal cognition • Network connectivity within the default mode was disrupted in type 2 diabetes patients • Decreased network connectivity was correlated with cognitive performance and insulin resistance level • Disrupted default-mode network might explain the impaired cognition in diabetic population.

  14. Improving Neural Recording Technology at the Nanoscale

    NASA Astrophysics Data System (ADS)

    Ferguson, John Eric

    Neural recording electrodes are widely used to study normal brain function (e.g., learning, memory, and sensation) and abnormal brain function (e.g., epilepsy, addiction, and depression) and to interface with the nervous system for neuroprosthetics. With a deep understanding of the electrode interface at the nanoscale and the use of novel nanofabrication processes, neural recording electrodes can be designed that surpass previous limits and enable new applications. In this thesis, I will discuss three projects. In the first project, we created an ultralow-impedance electrode coating by controlling the nanoscale texture of electrode surfaces. In the second project, we developed a novel nanowire electrode for long-term intracellular recordings. In the third project, we created a means of wirelessly communicating with ultra-miniature, implantable neural recording devices. The techniques developed for these projects offer significant improvements in the quality of neural recordings. They can also open the door to new types of experiments and medical devices, which can lead to a better understanding of the brain and can enable novel and improved tools for clinical applications.

  15. [Cognitive abnormalities and cannabis use].

    PubMed

    Solowij, Nadia; Pesa, Nicole

    2010-05-01

    Evidence that cannabis use impairs cognitive function in humans has been accumulating in recent decades. The purpose of this overview is to update knowledge in this area with new findings from the most recent literature. Literature searches were conducted using the Web of Science database up to February 2010. The terms searched were: "cannabi*" or "marijuana", and "cogniti*" or "memory" or "attention" or "executive function", and human studies were reviewed preferentially over the animal literature. Cannabis use impairs memory, attention, inhibitory control, executive functions and decision making, both during the period of acute intoxication and beyond, persisting for hours, days, weeks or more after the last use of cannabis. Pharmacological challenge studies in humans are elucidating the nature and neural substrates of cognitive changes associated with various cannabinoids. Long-term or heavy cannabis use appears to result in longer-lasting cognitive abnormalities and possibly structural brain alterations. Greater adverse cognitive effects are associated with cannabis use commencing in early adolescence. The endogenous cannabinoid system is involved in regulatory neural mechanisms that modulate processes underlying a range of cognitive functions that are impaired by cannabis. Deficits in human users most likely therefore reflect neuroadaptations and altered functioning of the endogenous cannabinoid system.

  16. Degraded attentional modulation of cortical neural populations in strabismic amblyopia

    PubMed Central

    Hou, Chuan; Kim, Yee-Joon; Lai, Xin Jie; Verghese, Preeti

    2016-01-01

    Behavioral studies have reported reduced spatial attention in amblyopia, a developmental disorder of spatial vision. However, the neural populations in the visual cortex linked with these behavioral spatial attention deficits have not been identified. Here, we use functional MRI–informed electroencephalography source imaging to measure the effect of attention on neural population activity in the visual cortex of human adult strabismic amblyopes who were stereoblind. We show that compared with controls, the modulatory effects of selective visual attention on the input from the amblyopic eye are substantially reduced in the primary visual cortex (V1) as well as in extrastriate visual areas hV4 and hMT+. Degraded attentional modulation is also found in the normal-acuity fellow eye in areas hV4 and hMT+ but not in V1. These results provide electrophysiological evidence that abnormal binocular input during a developmental critical period may impact cortical connections between the visual cortex and higher level cortices beyond the known amblyopic losses in V1 and V2, suggesting that a deficit of attentional modulation in the visual cortex is an important component of the functional impairment in amblyopia. Furthermore, we find that degraded attentional modulation in V1 is correlated with the magnitude of interocular suppression and the depth of amblyopia. These results support the view that the visual suppression often seen in strabismic amblyopia might be a form of attentional neglect of the visual input to the amblyopic eye. PMID:26885628

  17. Degraded attentional modulation of cortical neural populations in strabismic amblyopia.

    PubMed

    Hou, Chuan; Kim, Yee-Joon; Lai, Xin Jie; Verghese, Preeti

    2016-01-01

    Behavioral studies have reported reduced spatial attention in amblyopia, a developmental disorder of spatial vision. However, the neural populations in the visual cortex linked with these behavioral spatial attention deficits have not been identified. Here, we use functional MRI-informed electroencephalography source imaging to measure the effect of attention on neural population activity in the visual cortex of human adult strabismic amblyopes who were stereoblind. We show that compared with controls, the modulatory effects of selective visual attention on the input from the amblyopic eye are substantially reduced in the primary visual cortex (V1) as well as in extrastriate visual areas hV4 and hMT+. Degraded attentional modulation is also found in the normal-acuity fellow eye in areas hV4 and hMT+ but not in V1. These results provide electrophysiological evidence that abnormal binocular input during a developmental critical period may impact cortical connections between the visual cortex and higher level cortices beyond the known amblyopic losses in V1 and V2, suggesting that a deficit of attentional modulation in the visual cortex is an important component of the functional impairment in amblyopia. Furthermore, we find that degraded attentional modulation in V1 is correlated with the magnitude of interocular suppression and the depth of amblyopia. These results support the view that the visual suppression often seen in strabismic amblyopia might be a form of attentional neglect of the visual input to the amblyopic eye.

  18. Abnormal Resting-State Functional Connectivity of the Anterior Cingulate Cortex in Unilateral Chronic Tinnitus Patients

    PubMed Central

    Chen, Yu-Chen; Liu, Shenghua; Lv, Han; Bo, Fan; Feng, Yuan; Chen, Huiyou; Xu, Jin-Jing; Yin, Xindao; Wang, Shukui; Gu, Jian-Ping

    2018-01-01

    Purpose: The anterior cingulate cortex (ACC) has been suggested to be involved in chronic subjective tinnitus. Tinnitus may arise from aberrant functional coupling between the ACC and cerebral cortex. To explore this hypothesis, we used resting-state functional magnetic resonance imaging (fMRI) to illuminate the functional connectivity (FC) network of the ACC subregions in chronic tinnitus patients. Methods: Resting-state fMRI scans were obtained from 31 chronic right-sided tinnitus patients and 40 healthy controls (age, sex, and education well-matched) in this study. Rostral ACC and dorsal ACC were selected as seed regions to investigate the intrinsic FC with the whole brain. The resulting FC patterns were correlated with clinical tinnitus characteristics including the tinnitus duration and tinnitus distress. Results: Compared with healthy controls, chronic tinnitus patients showed disrupted FC patterns of ACC within several brain networks, including the auditory cortex, prefrontal cortex, visual cortex, and default mode network (DMN). The Tinnitus Handicap Questionnaires (THQ) scores showed positive correlations with increased FC between the rostral ACC and left precuneus (r = 0.507, p = 0.008) as well as the dorsal ACC and right inferior parietal lobe (r = 0.447, p = 0.022). Conclusions: Chronic tinnitus patients have abnormal FC networks originating from ACC to other selected brain regions that are associated with specific tinnitus characteristics. Resting-state ACC-cortical FC disturbances may play an important role in neuropathological features underlying chronic tinnitus. PMID:29410609

  19. Disrupted functional connectivity patterns of the insula subregions in drug-free major depressive disorder.

    PubMed

    Wang, Chao; Wu, Huawang; Chen, Fangfang; Xu, Jinping; Li, Hongming; Li, Hong; Wang, Jiaojian

    2018-07-01

    Major depressive disorder (MDD) is characterized by impairments in emotional and cognitive functions. Emerging studies have shown that cognition and emotion interact by reaching identical brain regions, and the insula is one such region with functional and structural heterogeneity. Although previous literatures have shown the role of insula in MDD,it remains unclear whether the insular subregions show differential change patterns in MDD. Using the resting-state fMRI data in a group of 23 drug-free MDD patients and 34 healthy controls (HCs), we investigated whether the abnormal connectivity patterns of insular sub-regions or any behavioural correlates can be detected in MDD. Further hierarchical cluster analysis was used to identify the functional connectivity-clustering patterns of insular sub-regions. Compared with HCs, the MDD exhibited higher connectivities between dorsal agranular insula and inferior parietal lobule and between ventral dysgranular and granular insula and thalamus/habehula, and lower connectivity of hypergranular insula to subgenual anterior cingulate cortex. Moreover, the three subregions with significant group differences were in three separate functional systems along anterior-to-posteior gradient. The anterior and middle insula showed positive correlation with depressive severity, while the posterior insular was to the contrary. The small and unbalanced sample size, only included moderate and severe depression and the possible inter-individual differences may limit the interpretability. These findings provided evidences for the MDD-related effects in functional connectivity patterns of insular subregions, and revealed that the subregions might be involved in different neural circuits associated with the contrary impacts on the depressive symptoms. Copyright © 2017 Elsevier B.V. All rights reserved.

  20. Neural circuits via which single prolonged stress exposure leads to fear extinction retention deficits.

    PubMed

    Knox, Dayan; Stanfield, Briana R; Staib, Jennifer M; David, Nina P; Keller, Samantha M; DePietro, Thomas

    2016-12-01

    Single prolonged stress (SPS) has been used to examine mechanisms via which stress exposure leads to post-traumatic stress disorder symptoms. SPS induces fear extinction retention deficits, but neural circuits critical for mediating these deficits are unknown. To address this gap, we examined the effect of SPS on neural activity in brain regions critical for extinction retention (i.e., fear extinction circuit). These were the ventral hippocampus (vHipp), dorsal hippocampus (dHipp), basolateral amygdala (BLA), prelimbic cortex (PL), and infralimbic cortex (IL). SPS or control rats were fear conditioned then subjected to extinction training and testing. Subsets of rats were euthanized after extinction training, extinction testing, or immediate removal from the housing colony (baseline condition) to assay c-Fos levels (measure of neural activity) in respective brain region. SPS induced extinction retention deficits. During extinction training SPS disrupted enhanced IL neural activity and inhibited BLA neural activity. SPS also disrupted inhibited BLA and vHipp neural activity during extinction testing. Statistical analyses suggested that SPS disrupted functional connectivity within the dHipp during extinction training and increased functional connectivity between the BLA and vHipp during extinction testing. Our findings suggest that SPS induces extinction retention deficits by disrupting both excitatory and inhibitory changes in neural activity within the fear extinction circuit and inducing changes in functional connectivity within the Hipp and BLA. © 2016 Knox et al.; Published by Cold Spring Harbor Laboratory Press.

  1. Fetal karyotyping for chromosome abnormalities after an unexplained elevated maternal serum alpha-fetoprotein screening.

    PubMed

    Feuchtbaum, L B; Cunningham, G; Waller, D K; Lustig, L S; Tompkinson, D G; Hook, E B

    1995-08-01

    To study the chromosome abnormality rate among women with elevated levels of maternal serum alpha-fetoprotein (MSAFP) and the types of chromosome abnormalities in this population, and to compare this rate with reports in the literature and the rate observed in the general population. We studied 8097 women who chose to undergo amniocentesis and fetal karyotyping after having an elevated MSAFP test of 2.5 multiples of the median (MOM) or higher. All abnormal karyotypes were reviewed and grouped according to whether the elevated MSAFP value could be explained by a ventral wall or neural tube defect. The overall chromosome abnormality rate was 13.83 per 1000 amniocenteses. The rate in the "unexplained" group was 10.92 per 1000 amniocenteses. Just over half (53%) of the abnormal karyotypes were autosomal anomalies, and 47% were sex chromosome abnormalities. The autosomal aneuploidies observed most frequently were triploidy and trisomy 13. The sex chromosome abnormalities observed most frequently were the XXY and XYY karyotypes. Women who have unexplained elevated MSAFP values of 2.5 MOM or greater have a twofold increase in the rate of chromosome abnormalities in their fetuses compared with the general population (P < or = .001). This rate is consistent with other studies that used a 2.5 MOM cutoff. Studies that used a 2.0 MOM cutoff have reported chromosome abnormality rates that do not vary from general population estimates.

  2. Unfolding the neutron spectrum of a NE213 scintillator using artificial neural networks.

    PubMed

    Sharghi Ido, A; Bonyadi, M R; Etaati, G R; Shahriari, M

    2009-10-01

    Artificial neural networks technology has been applied to unfold the neutron spectra from the pulse height distribution measured with NE213 liquid scintillator. Here, both the single and multi-layer perceptron neural network models have been implemented to unfold the neutron spectrum from an Am-Be neutron source. The activation function and the connectivity of the neurons have been investigated and the results have been analyzed in terms of the network's performance. The simulation results show that the neural network that utilizes the Satlins transfer function has the best performance. In addition, omitting the bias connection of the neurons improve the performance of the network. Also, the SCINFUL code is used for generating the response functions in the training phase of the process. Finally, the results of the neural network simulation have been compared with those of the FORIST unfolding code for both (241)Am-Be and (252)Cf neutron sources. The results of neural network are in good agreement with FORIST code.

  3. Constructive autoassociative neural network for facial recognition.

    PubMed

    Fernandes, Bruno J T; Cavalcanti, George D C; Ren, Tsang I

    2014-01-01

    Autoassociative artificial neural networks have been used in many different computer vision applications. However, it is difficult to define the most suitable neural network architecture because this definition is based on previous knowledge and depends on the problem domain. To address this problem, we propose a constructive autoassociative neural network called CANet (Constructive Autoassociative Neural Network). CANet integrates the concepts of receptive fields and autoassociative memory in a dynamic architecture that changes the configuration of the receptive fields by adding new neurons in the hidden layer, while a pruning algorithm removes neurons from the output layer. Neurons in the CANet output layer present lateral inhibitory connections that improve the recognition rate. Experiments in face recognition and facial expression recognition show that the CANet outperforms other methods presented in the literature.

  4. Neural signatures of cognitive and emotional biases in depression

    PubMed Central

    Fossati, Philippe

    2008-01-01

    Functional brain imaging studies suggest that depression is a system-level disorder affecting discrete but functionally linked cortical and limbic structures, with abnormalities in the anterior cingulate, lateral, ami medial prefrontal cortex, amygdala, ami hippocampus. Within this circuitry, abnormal corticolimbic interactions underlie cognitive deficits ami emotional impairment in depression. Depression involves biases toward processing negative emotional information and abnormal self-focus in response to emotional stimuli. These biases in depression could reflect excessive analytical self-focus in depression, as well as impaired cognitive control of emotional response to negative stimuli. By combining structural and functional investigations, brain imaging studies mav help to generate novel antidepressant treatments that regulate structural and factional plasticity within the neural network regulating mood and affective behavior.

  5. Working Memory-Related Effective Connectivity in Huntington's Disease Patients.

    PubMed

    Lahr, Jacob; Minkova, Lora; Tabrizi, Sarah J; Stout, Julie C; Klöppel, Stefan; Scheller, Elisa

    2018-01-01

    Huntington's disease (HD) is a genetically caused neurodegenerative disorder characterized by heterogeneous motor, psychiatric, and cognitive symptoms. Although motor symptoms may be the most prominent presentation, cognitive symptoms such as memory deficits and executive dysfunction typically co-occur. We used functional magnetic resonance imaging (fMRI) and task fMRI-based dynamic causal modeling (DCM) to evaluate HD-related changes in the neural network underlying working memory (WM). Sixty-four pre-symptomatic HD mutation carriers (preHD), 20 patients with early manifest HD symptoms (earlyHD), and 83 healthy control subjects performed an n -back fMRI task with two levels of WM load. Effective connectivity was assessed in five predefined regions of interest, comprising bilateral inferior parietal cortex, left anterior cingulate cortex, and bilateral dorsolateral prefrontal cortex. HD mutation carriers performed less accurately and more slowly at high WM load compared with the control group. While between-group comparisons of brain activation did not reveal differential recruitment of the cortical WM network in mutation carriers, comparisons of brain connectivity as identified with DCM revealed a number of group differences across the whole WM network. Most strikingly, we observed decreasing connectivity from several regions toward right dorsolateral prefrontal cortex (rDLPFC) in preHD and even more so in earlyHD. The deterioration in rDLPFC connectivity complements results from previous studies and might mirror beginning cortical neural decline at premanifest and early manifest stages of HD. We were able to characterize effective connectivity in a WM network of HD mutation carriers yielding further insight into patterns of cognitive decline and accompanying neural deterioration.

  6. Postotic and preotic cranial neural crest cells differently contribute to thyroid development.

    PubMed

    Maeda, Kazuhiro; Asai, Rieko; Maruyama, Kazuaki; Kurihara, Yukiko; Nakanishi, Toshio; Kurihara, Hiroki; Miyagawa-Tomita, Sachiko

    2016-01-01

    Thyroid development and formation vary among species, but in most species the thyroid morphogenesis consists of five stages: specification, budding, descent, bilobation and folliculogenesis. The detailed mechanisms of these stages have not been fully clarified. During early development, the cranial neural crest (CNC) contributes to the thyroid gland. The removal of the postotic CNC (corresponding to rhombomeres 6, 7 and 8, also known as the cardiac neural crest) results in abnormalities of the cardiovascular system, thymus, parathyroid glands, and thyroid gland. To investigate the influence of the CNC on thyroid bilobation process, we divided the CNC into two regions, the postotic CNC and the preotic CNC (from the mesencephalon to rhombomere 5) regions and examined. We found that preotic CNC-ablated embryos had a unilateral thyroid lobe, and confirmed the presence of a single lobe or the absence of lobes in postotic CNC-ablated chick embryos. The thyroid anlage in each region-ablated embryos was of a normal size at the descent stage, but at a later stage, the thyroid in preotic CNC-ablated embryos was of a normal size, conflicting with a previous report in which the thyroid was reduced in size in the postotic CNC-ablated embryos. The postotic CNC cells differentiated into connective tissues of the thyroid in quail-to-chick chimeras. In contrast, the preotic CNC cells did not differentiate into connective tissues of the thyroid. We found that preotic CNC cells encompassed the thyroid anlage from the specification stage to the descent stage. Finally, we found that endothelin-1 and endothelin type A receptor-knockout mice and bosentan (endothelin receptor antagonist)-treated chick embryos showed bilobation anomalies that included single-lobe formation. Therefore, not only the postotic CNC, but also the preotic CNC plays an important role in thyroid morphogenesis. Copyright © 2015 Elsevier Inc. All rights reserved.

  7. Establishment of high reciprocal connectivity between clonal cortical neurons is regulated by the Dnmt3b DNA methyltransferase and clustered protocadherins.

    PubMed

    Tarusawa, Etsuko; Sanbo, Makoto; Okayama, Atsushi; Miyashita, Toshio; Kitsukawa, Takashi; Hirayama, Teruyoshi; Hirabayashi, Takahiro; Hasegawa, Sonoko; Kaneko, Ryosuke; Toyoda, Shunsuke; Kobayashi, Toshihiro; Kato-Itoh, Megumi; Nakauchi, Hiromitsu; Hirabayashi, Masumi; Yagi, Takeshi; Yoshimura, Yumiko

    2016-12-02

    The specificity of synaptic connections is fundamental for proper neural circuit function. Specific neuronal connections that underlie information processing in the sensory cortex are initially established without sensory experiences to a considerable extent, and then the connections are individually refined through sensory experiences. Excitatory neurons arising from the same single progenitor cell are preferentially connected in the postnatal cortex, suggesting that cell lineage contributes to the initial wiring of neurons. However, the postnatal developmental process of lineage-dependent connection specificity is not known, nor how clonal neurons, which are derived from the same neural stem cell, are stamped with the identity of their common neural stem cell and guided to form synaptic connections. We show that cortical excitatory neurons that arise from the same neural stem cell and reside within the same layer preferentially establish reciprocal synaptic connections in the mouse barrel cortex. We observed a transient increase in synaptic connections between clonal but not nonclonal neuron pairs during postnatal development, followed by selective stabilization of the reciprocal connections between clonal neuron pairs. Furthermore, we demonstrate that selective stabilization of the reciprocal connections between clonal neuron pairs is impaired by the deficiency of DNA methyltransferase 3b (Dnmt3b), which determines DNA-methylation patterns of genes in stem cells during early corticogenesis. Dnmt3b regulates the postnatal expression of clustered protocadherin (cPcdh) isoforms, a family of adhesion molecules. We found that cPcdh deficiency in clonal neuron pairs impairs the whole process of the formation and stabilization of connections to establish lineage-specific connection reciprocity. Our results demonstrate that local, reciprocal neural connections are selectively formed and retained between clonal neurons in layer 4 of the barrel cortex during postnatal

  8. Neural circuitry of emotional face processing in autism spectrum disorders.

    PubMed

    Monk, Christopher S; Weng, Shih-Jen; Wiggins, Jillian Lee; Kurapati, Nikhil; Louro, Hugo M C; Carrasco, Melisa; Maslowsky, Julie; Risi, Susan; Lord, Catherine

    2010-03-01

    Autism spectrum disorders (ASD) are associated with severe impairments in social functioning. Because faces provide nonverbal cues that support social interactions, many studies of ASD have examined neural structures that process faces, including the amygdala, ventromedial prefrontal cortex and superior and middle temporal gyri. However, increases or decreases in activation are often contingent on the cognitive task. Specifically, the cognitive domain of attention influences group differences in brain activation. We investigated brain function abnormalities in participants with ASD using a task that monitored attention bias to emotional faces. Twenty-four participants (12 with ASD, 12 controls) completed a functional magnetic resonance imaging study while performing an attention cuing task with emotional (happy, sad, angry) and neutral faces. In response to emotional faces, those in the ASD group showed greater right amygdala activation than those in the control group. A preliminary psychophysiological connectivity analysis showed that ASD participants had stronger positive right amygdala and ventromedial prefrontal cortex coupling and weaker positive right amygdala and temporal lobe coupling than controls. There were no group differences in the behavioural measure of attention bias to the emotional faces. The small sample size may have affected our ability to detect additional group differences. When attention bias to emotional faces was equivalent between ASD and control groups, ASD was associated with greater amygdala activation. Preliminary analyses showed that ASD participants had stronger connectivity between the amygdala ventromedial prefrontal cortex (a network implicated in emotional modulation) and weaker connectivity between the amygdala and temporal lobe (a pathway involved in the identification of facial expressions, although areas of group differences were generally in a more anterior region of the temporal lobe than what is typically reported for

  9. Mesodermal expression of integrin α5β1 regulates neural crest development and cardiovascular morphogenesis

    PubMed Central

    Liang, Dong; Wang, Xia; Mittal, Ashok; Dhiman, Sonam; Hou, Shuan-Yu; Degenhardt, Karl; Astrof, Sophie

    2014-01-01

    Integrin α5-null embryos die in mid-gestation from severe defects in cardiovascular morphogenesis, which stem from defective development of the neural crest, heart and vasculature. To investigate the role of integrin α5β1 in cardiovascular development, we used the Mesp1Cre knock-in strain of mice to ablate integrin α5 in the anterior mesoderm, which gives rise to all of the cardiac and many of the vascular and muscle lineages in the anterior portion of the embryo. Surprisingly, we found that mutant embryos displayed numerous defects related to the abnormal development of the neural crest such as cleft palate, ventricular septal defect, abnormal development of hypoglossal nerves, and defective remodeling of the aortic arch arteries. We found that defects in arch artery remodeling stem from the role of mesodermal integrin α5β1 in neural crest proliferation and differentiation into vascular smooth muscle cells, while proliferation of pharyngeal mesoderm and differentiation of mesodermal derivatives into vascular smooth muscle cells was not defective. Taken together our studies demonstrate a requisite role for mesodermal integrin α5β1 in signaling between the mesoderm and the neural crest, thereby regulating neural crest-dependent morphogenesis of essential embryonic structures. PMID:25242040

  10. Whole brain resting-state analysis reveals decreased functional connectivity in major depression.

    PubMed

    Veer, Ilya M; Beckmann, Christian F; van Tol, Marie-José; Ferrarini, Luca; Milles, Julien; Veltman, Dick J; Aleman, André; van Buchem, Mark A; van der Wee, Nic J; Rombouts, Serge A R B

    2010-01-01

    Recently, both increases and decreases in resting-state functional connectivity have been found in major depression. However, these studies only assessed functional connectivity within a specific network or between a few regions of interest, while comorbidity and use of medication was not always controlled for. Therefore, the aim of the current study was to investigate whole-brain functional connectivity, unbiased by a priori definition of regions or networks of interest, in medication-free depressive patients without comorbidity. We analyzed resting-state fMRI data of 19 medication-free patients with a recent diagnosis of major depression (within 6 months before inclusion) and no comorbidity, and 19 age- and gender-matched controls. Independent component analysis was employed on the concatenated data sets of all participants. Thirteen functionally relevant networks were identified, describing the entire study sample. Next, individual representations of the networks were created using a dual regression method. Statistical inference was subsequently done on these spatial maps using voxel-wise permutation tests. Abnormal functional connectivity was found within three resting-state networks in depression: (1) decreased bilateral amygdala and left anterior insula connectivity in an affective network, (2) reduced connectivity of the left frontal pole in a network associated with attention and working memory, and (3) decreased bilateral lingual gyrus connectivity within ventromedial visual regions. None of these effects were associated with symptom severity or gray matter density. We found abnormal resting-state functional connectivity not previously associated with major depression, which might relate to abnormal affect regulation and mild cognitive deficits, both associated with the symptomatology of the disorder.

  11. Whole Brain Resting-State Analysis Reveals Decreased Functional Connectivity in Major Depression

    PubMed Central

    Veer, Ilya M.; Beckmann, Christian F.; van Tol, Marie-José; Ferrarini, Luca; Milles, Julien; Veltman, Dick J.; Aleman, André; van Buchem, Mark A.; van der Wee, Nic J.; Rombouts, Serge A.R.B.

    2010-01-01

    Recently, both increases and decreases in resting-state functional connectivity have been found in major depression. However, these studies only assessed functional connectivity within a specific network or between a few regions of interest, while comorbidity and use of medication was not always controlled for. Therefore, the aim of the current study was to investigate whole-brain functional connectivity, unbiased by a priori definition of regions or networks of interest, in medication-free depressive patients without comorbidity. We analyzed resting-state fMRI data of 19 medication-free patients with a recent diagnosis of major depression (within 6 months before inclusion) and no comorbidity, and 19 age- and gender-matched controls. Independent component analysis was employed on the concatenated data sets of all participants. Thirteen functionally relevant networks were identified, describing the entire study sample. Next, individual representations of the networks were created using a dual regression method. Statistical inference was subsequently done on these spatial maps using voxel-wise permutation tests. Abnormal functional connectivity was found within three resting-state networks in depression: (1) decreased bilateral amygdala and left anterior insula connectivity in an affective network, (2) reduced connectivity of the left frontal pole in a network associated with attention and working memory, and (3) decreased bilateral lingual gyrus connectivity within ventromedial visual regions. None of these effects were associated with symptom severity or gray matter density. We found abnormal resting-state functional connectivity not previously associated with major depression, which might relate to abnormal affect regulation and mild cognitive deficits, both associated with the symptomatology of the disorder. PMID:20941370

  12. Resting-state hemodynamics are spatiotemporally coupled to synchronized and symmetric neural activity in excitatory neurons.

    PubMed

    Ma, Ying; Shaik, Mohammed A; Kozberg, Mariel G; Kim, Sharon H; Portes, Jacob P; Timerman, Dmitriy; Hillman, Elizabeth M C

    2016-12-27

    Brain hemodynamics serve as a proxy for neural activity in a range of noninvasive neuroimaging techniques including functional magnetic resonance imaging (fMRI). In resting-state fMRI, hemodynamic fluctuations have been found to exhibit patterns of bilateral synchrony, with correlated regions inferred to have functional connectivity. However, the relationship between resting-state hemodynamics and underlying neural activity has not been well established, making the neural underpinnings of functional connectivity networks unclear. In this study, neural activity and hemodynamics were recorded simultaneously over the bilateral cortex of awake and anesthetized Thy1-GCaMP mice using wide-field optical mapping. Neural activity was visualized via selective expression of the calcium-sensitive fluorophore GCaMP in layer 2/3 and 5 excitatory neurons. Characteristic patterns of resting-state hemodynamics were accompanied by more rapidly changing bilateral patterns of resting-state neural activity. Spatiotemporal hemodynamics could be modeled by convolving this neural activity with hemodynamic response functions derived through both deconvolution and gamma-variate fitting. Simultaneous imaging and electrophysiology confirmed that Thy1-GCaMP signals are well-predicted by multiunit activity. Neurovascular coupling between resting-state neural activity and hemodynamics was robust and fast in awake animals, whereas coupling in urethane-anesthetized animals was slower, and in some cases included lower-frequency (<0.04 Hz) hemodynamic fluctuations that were not well-predicted by local Thy1-GCaMP recordings. These results support that resting-state hemodynamics in the awake and anesthetized brain are coupled to underlying patterns of excitatory neural activity. The patterns of bilaterally-symmetric spontaneous neural activity revealed by wide-field Thy1-GCaMP imaging may depict the neural foundation of functional connectivity networks detected in resting-state fMRI.

  13. Resting-state hemodynamics are spatiotemporally coupled to synchronized and symmetric neural activity in excitatory neurons

    PubMed Central

    Ma, Ying; Shaik, Mohammed A.; Kozberg, Mariel G.; Portes, Jacob P.; Timerman, Dmitriy

    2016-01-01

    Brain hemodynamics serve as a proxy for neural activity in a range of noninvasive neuroimaging techniques including functional magnetic resonance imaging (fMRI). In resting-state fMRI, hemodynamic fluctuations have been found to exhibit patterns of bilateral synchrony, with correlated regions inferred to have functional connectivity. However, the relationship between resting-state hemodynamics and underlying neural activity has not been well established, making the neural underpinnings of functional connectivity networks unclear. In this study, neural activity and hemodynamics were recorded simultaneously over the bilateral cortex of awake and anesthetized Thy1-GCaMP mice using wide-field optical mapping. Neural activity was visualized via selective expression of the calcium-sensitive fluorophore GCaMP in layer 2/3 and 5 excitatory neurons. Characteristic patterns of resting-state hemodynamics were accompanied by more rapidly changing bilateral patterns of resting-state neural activity. Spatiotemporal hemodynamics could be modeled by convolving this neural activity with hemodynamic response functions derived through both deconvolution and gamma-variate fitting. Simultaneous imaging and electrophysiology confirmed that Thy1-GCaMP signals are well-predicted by multiunit activity. Neurovascular coupling between resting-state neural activity and hemodynamics was robust and fast in awake animals, whereas coupling in urethane-anesthetized animals was slower, and in some cases included lower-frequency (<0.04 Hz) hemodynamic fluctuations that were not well-predicted by local Thy1-GCaMP recordings. These results support that resting-state hemodynamics in the awake and anesthetized brain are coupled to underlying patterns of excitatory neural activity. The patterns of bilaterally-symmetric spontaneous neural activity revealed by wide-field Thy1-GCaMP imaging may depict the neural foundation of functional connectivity networks detected in resting-state fMRI. PMID:27974609

  14. Altered functional connectivity in early Alzheimer's disease: a resting-state fMRI study.

    PubMed

    Wang, Kun; Liang, Meng; Wang, Liang; Tian, Lixia; Zhang, Xinqing; Li, Kuncheng; Jiang, Tianzi

    2007-10-01

    Previous studies have led to the proposal that patients with Alzheimer's disease (AD) may have disturbed functional connectivity between different brain regions. Furthermore, recent resting-state functional magnetic resonance imaging (fMRI) studies have also shown that low-frequency (<0.08 Hz) fluctuations (LFF) of the blood oxygenation level-dependent signals were abnormal in several brain areas of AD patients. However, few studies have investigated disturbed LFF connectivity in AD patients. By using resting-state fMRI, this study sought to investigate the abnormal functional connectivities throughout the entire brain of early AD patients, and analyze the global distribution of these abnormalities. For this purpose, the authors divided the whole brain into 116 regions and identified abnormal connectivities by comparing the correlation coefficients of each pair. Compared with healthy controls, AD patients had decreased positive correlations between the prefrontal and parietal lobes, but increased positive correlations within the prefrontal lobe, parietal lobe, and occipital lobe. The AD patients also had decreased negative correlations (closer to zero) between two intrinsically anti-correlated networks that had previously been found in the resting brain. By using resting-state fMRI, our results supported previous studies that have reported an anterior-posterior disconnection phenomenon and increased within-lobe functional connectivity in AD patients. In addition, the results also suggest that AD may disturb the correlation/anti-correlation effect in the two intrinsically anti-correlated networks. Wiley-Liss, Inc.

  15. The Laplacian spectrum of neural networks

    PubMed Central

    de Lange, Siemon C.; de Reus, Marcel A.; van den Heuvel, Martijn P.

    2014-01-01

    The brain is a complex network of neural interactions, both at the microscopic and macroscopic level. Graph theory is well suited to examine the global network architecture of these neural networks. Many popular graph metrics, however, encode average properties of individual network elements. Complementing these “conventional” graph metrics, the eigenvalue spectrum of the normalized Laplacian describes a network's structure directly at a systems level, without referring to individual nodes or connections. In this paper, the Laplacian spectra of the macroscopic anatomical neuronal networks of the macaque and cat, and the microscopic network of the Caenorhabditis elegans were examined. Consistent with conventional graph metrics, analysis of the Laplacian spectra revealed an integrative community structure in neural brain networks. Extending previous findings of overlap of network attributes across species, similarity of the Laplacian spectra across the cat, macaque and C. elegans neural networks suggests a certain level of consistency in the overall architecture of the anatomical neural networks of these species. Our results further suggest a specific network class for neural networks, distinct from conceptual small-world and scale-free models as well as several empirical networks. PMID:24454286

  16. Intra-regional and inter-regional abnormalities and cognitive control deficits in young adult smokers.

    PubMed

    Feng, Dan; Yuan, Kai; Li, Yangding; Cai, Chenxi; Yin, Junsen; Bi, Yanzhi; Cheng, Jiadong; Guan, Yanyan; Shi, Sha; Yu, Dahua; Jin, Chenwang; Lu, Xiaoqi; Qin, Wei; Tian, Jie

    2016-06-01

    Tobacco use during later adolescence and young adulthood may cause serious neurophysiological changes; rationally, it is extremely important to study the relationship between brain dysfunction and behavioral performances in young adult smokers. Previous resting state studies investigated the neural mechanisms in smokers. Unfortunately, few studies focused on spontaneous activity differences between young adult smokers and nonsmokers from both intra-regional and inter-regional levels, less is known about the association between resting state abnormalities and behavioral deficits. Therefore, we used fractional amplitude of low frequency fluctuation (fALFF) and resting state functional connectivity (RSFC) to investigate the resting state spontaneous activity differences between young adult smokers and nonsmokers. A correlation analysis was carried out to assess the relationship between neuroimaging findings and clinical information (pack-years, cigarette dependence, age of onset and craving score) as well as cognitive control deficits measured by the Stroop task. Consistent with previous addiction findings, our results revealed the resting state abnormalities within frontostriatal circuits, i.e., enhanced spontaneous activity of the caudate and reduced functional strength between the caudate and anterior cingulate cortex (ACC) in young adult smokers. Moreover, the fALFF values of the caudate were correlated with craving and RSFC strength between the caudate and ACC was associated with the cognitive control impairments in young adult smokers. Our findings could lead to a better understanding of intrinsic functional architecture of baseline brain activity in young smokers by providing regional and brain circuit spontaneous neuronal activity properties as well as their association with cognitive control impairments.

  17. Neural Network Modeling of UH-60A Pilot Vibration

    NASA Technical Reports Server (NTRS)

    Kottapalli, Sesi

    2003-01-01

    Full-scale flight-test pilot floor vibration is modeled using neural networks and full-scale wind tunnel test data for low speed level flight conditions. Neural network connections between the wind tunnel test data and the tlxee flight test pilot vibration components (vertical, lateral, and longitudinal) are studied. Two full-scale UH-60A Black Hawk databases are used. The first database is the NASMArmy UH-60A Airloads Program flight test database. The second database is the UH-60A rotor-only wind tunnel database that was acquired in the NASA Ames SO- by 120- Foot Wind Tunnel with the Large Rotor Test Apparatus (LRTA). Using neural networks, the flight-test pilot vibration is modeled using the wind tunnel rotating system hub accelerations, and separately, using the hub loads. The results show that the wind tunnel rotating system hub accelerations and the operating parameters can represent the flight test pilot vibration. The six components of the wind tunnel N/rev balance-system hub loads and the operating parameters can also represent the flight test pilot vibration. The present neural network connections can significandy increase the value of wind tunnel testing.

  18. Neural Activity When People Solve Verbal Problems with Insight

    PubMed Central

    Bowden, Edward M; Haberman, Jason; Frymiare, Jennifer L; Arambel-Liu, Stella; Greenblatt, Richard; Reber, Paul J

    2004-01-01

    People sometimes solve problems with a unique process called insight, accompanied by an “Aha!” experience. It has long been unclear whether different cognitive and neural processes lead to insight versus noninsight solutions, or if solutions differ only in subsequent subjective feeling. Recent behavioral studies indicate distinct patterns of performance and suggest differential hemispheric involvement for insight and noninsight solutions. Subjects solved verbal problems, and after each correct solution indicated whether they solved with or without insight. We observed two objective neural correlates of insight. Functional magnetic resonance imaging (Experiment 1) revealed increased activity in the right hemisphere anterior superior temporal gyrus for insight relative to noninsight solutions. The same region was active during initial solving efforts. Scalp electroencephalogram recordings (Experiment 2) revealed a sudden burst of high-frequency (gamma-band) neural activity in the same area beginning 0.3 s prior to insight solutions. This right anterior temporal area is associated with making connections across distantly related information during comprehension. Although all problem solving relies on a largely shared cortical network, the sudden flash of insight occurs when solvers engage distinct neural and cognitive processes that allow them to see connections that previously eluded them. PMID:15094802

  19. Theory of Mind and the Whole Brain Functional Connectivity: Behavioral and Neural Evidences with the Amsterdam Resting State Questionnaire.

    PubMed

    Marchetti, Antonella; Baglio, Francesca; Costantini, Isa; Dipasquale, Ottavia; Savazzi, Federica; Nemni, Raffaello; Sangiuliano Intra, Francesca; Tagliabue, Semira; Valle, Annalisa; Massaro, Davide; Castelli, Ilaria

    2015-01-01

    A topic of common interest to psychologists and philosophers is the spontaneous flow of thoughts when the individual is awake but not involved in cognitive demands. This argument, classically referred to as the "stream of consciousness" of James, is now known in the psychological literature as "Mind-Wandering." Although of great interest, this construct has been scarcely investigated so far. Diaz et al. (2013) created the Amsterdam Resting State Questionnaire (ARSQ), composed of 27 items, distributed in seven factors: discontinuity of mind, theory of mind (ToM), self, planning, sleepiness, comfort, and somatic awareness. The present study aims at: testing psychometric properties of the ARSQ in a sample of 670 Italian subjects; exploring the neural correlates of a subsample of participants (N = 28) divided into two groups on the basis of the scores obtained in the ToM factor. Results show a satisfactory reliability of the original factional structure in the Italian sample. In the subjects with a high mean in the ToM factor compared to low mean subjects, functional MRI revealed: a network (48 nodes) with higher functional connectivity (FC) with a dominance of the left hemisphere; an increased within-lobe FC in frontal and insular lobes. In both neural and behavioral terms, our results support the idea that the mind, which does not rest even when explicitly asked to do so, has various and interesting mentalistic-like contents.

  20. Effect of dilution in asymmetric recurrent neural networks.

    PubMed

    Folli, Viola; Gosti, Giorgio; Leonetti, Marco; Ruocco, Giancarlo

    2018-04-16

    We study with numerical simulation the possible limit behaviors of synchronous discrete-time deterministic recurrent neural networks composed of N binary neurons as a function of a network's level of dilution and asymmetry. The network dilution measures the fraction of neuron couples that are connected, and the network asymmetry measures to what extent the underlying connectivity matrix is asymmetric. For each given neural network, we study the dynamical evolution of all the different initial conditions, thus characterizing the full dynamical landscape without imposing any learning rule. Because of the deterministic dynamics, each trajectory converges to an attractor, that can be either a fixed point or a limit cycle. These attractors form the set of all the possible limit behaviors of the neural network. For each network we then determine the convergence times, the limit cycles' length, the number of attractors, and the sizes of the attractors' basin. We show that there are two network structures that maximize the number of possible limit behaviors. The first optimal network structure is fully-connected and symmetric. On the contrary, the second optimal network structure is highly sparse and asymmetric. The latter optimal is similar to what observed in different biological neuronal circuits. These observations lead us to hypothesize that independently from any given learning model, an efficient and effective biologic network that stores a number of limit behaviors close to its maximum capacity tends to develop a connectivity structure similar to one of the optimal networks we found. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  1. Evidence of a dissociation pattern in resting-state default mode network connectivity in first-episode, treatment-naive major depression patients.

    PubMed

    Zhu, Xueling; Wang, Xiang; Xiao, Jin; Liao, Jian; Zhong, Mingtian; Wang, Wei; Yao, Shuqiao

    2012-04-01

    Imaging studies have shown that major depressive disorder (MDD) is associated with altered activity patterns of the default mode network (DMN). However, the neural correlates of the resting-state DMN and MDD-related pathopsychological characteristics, such as depressive rumination and overgeneral autobiographical memory (OGM) phenomena, still remain unclear. Using independent component analysis, we analyzed resting-state functional magnetic resonance imaging data obtained from 35 first-episode, treatment-naive young adults with MDD and from 35 matched healthy control subjects. Patients with MDD exhibited higher levels of rumination and OGM than did the control subjects. We observed increased functional connectivity in the anterior medial cortex regions (especially the medial prefrontal cortex and anterior cingulate cortex) and decreased functional connectivity in the posterior medial cortex regions (especially the posterior cingulate cortex/precuneus) in MDD patients compared with control subjects. In the depressed group, the increased functional connectivity in the anterior medial cortex correlated positively with rumination score, while the decreased functional connectivity in the posterior medial cortex correlated negatively with OGM score. We report dissociation between anterior and posterior functional connectivity in resting-state DMNs of first-episode, treatment-naive young adults with MDD. Increased functional connectivity in anterior medial regions of the resting-state DMN was associated with rumination, whereas decreased functional connectivity in posterior medial regions was associated with OGM. These results provide new evidence for the importance of the DMN in the pathophysiology of MDD and suggest that abnormal DMN activity may be an MDD trait. Copyright © 2012 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  2. Pdgfrα functions in endothelial-derived cells to regulate neural crest cells and the development of the great arteries.

    PubMed

    Aghajanian, Haig; Cho, Young Kuk; Rizer, Nicholas W; Wang, Qiaohong; Li, Li; Degenhardt, Karl; Jain, Rajan

    2017-09-01

    Originating as a single vessel emerging from the embryonic heart, the truncus arteriosus must septate and remodel into the aorta and pulmonary artery to support postnatal life. Defective remodeling or septation leads to abnormalities collectively known as conotruncal defects, which are associated with significant mortality and morbidity. Multiple populations of cells must interact to coordinate outflow tract remodeling, and the cardiac neural crest has emerged as particularly important during this process. Abnormalities in the cardiac neural crest have been implicated in the pathogenesis of multiple conotruncal defects, including persistent truncus arteriosus, double outlet right ventricle and tetralogy of Fallot. However, the role of the neural crest in the pathogenesis of another conotruncal abnormality, transposition of the great arteries, is less well understood. In this report, we demonstrate an unexpected role of Pdgfra in endothelial cells and their derivatives during outflow tract development. Loss of Pdgfra in endothelium and endothelial-derived cells results in double outlet right ventricle and transposition of the great arteries. Our data suggest that loss of Pdgfra in endothelial-derived mesenchyme in the outflow tract endocardial cushions leads to a secondary defect in neural crest migration during development. © 2017. Published by The Company of Biologists Ltd.

  3. [Measurement and performance analysis of functional neural network].

    PubMed

    Li, Shan; Liu, Xinyu; Chen, Yan; Wan, Hong

    2018-04-01

    The measurement of network is one of the important researches in resolving neuronal population information processing mechanism using complex network theory. For the quantitative measurement problem of functional neural network, the relation between the measure indexes, i.e. the clustering coefficient, the global efficiency, the characteristic path length and the transitivity, and the network topology was analyzed. Then, the spike-based functional neural network was established and the simulation results showed that the measured network could represent the original neural connections among neurons. On the basis of the former work, the coding of functional neural network in nidopallium caudolaterale (NCL) about pigeon's motion behaviors was studied. We found that the NCL functional neural network effectively encoded the motion behaviors of the pigeon, and there were significant differences in four indexes among the left-turning, the forward and the right-turning. Overall, the establishment method of spike-based functional neural network is available and it is an effective tool to parse the brain information processing mechanism.

  4. Neural networks within multi-core optic fibers.

    PubMed

    Cohen, Eyal; Malka, Dror; Shemer, Amir; Shahmoon, Asaf; Zalevsky, Zeev; London, Michael

    2016-07-07

    Hardware implementation of artificial neural networks facilitates real-time parallel processing of massive data sets. Optical neural networks offer low-volume 3D connectivity together with large bandwidth and minimal heat production in contrast to electronic implementation. Here, we present a conceptual design for in-fiber optical neural networks. Neurons and synapses are realized as individual silica cores in a multi-core fiber. Optical signals are transferred transversely between cores by means of optical coupling. Pump driven amplification in erbium-doped cores mimics synaptic interactions. We simulated three-layered feed-forward neural networks and explored their capabilities. Simulations suggest that networks can differentiate between given inputs depending on specific configurations of amplification; this implies classification and learning capabilities. Finally, we tested experimentally our basic neuronal elements using fibers, couplers, and amplifiers, and demonstrated that this configuration implements a neuron-like function. Therefore, devices similar to our proposed multi-core fiber could potentially serve as building blocks for future large-scale small-volume optical artificial neural networks.

  5. Linear analysis of auto-organization in Hebbian neural networks.

    PubMed

    Carlos Letelier, J; Mpodozis, J

    1995-01-01

    The self-organization of neurotopies where neural connections follow Hebbian dynamics is framed in terms of linear operator theory. A general and exact equation describing the time evolution of the overall synaptic strength connecting two neural laminae is derived. This linear matricial equation, which is similar to the equations used to describe oscillating systems in physics, is modified by the introduction of non-linear terms, in order to capture self-organizing (or auto-organizing) processes. The behavior of a simple and small system, that contains a non-linearity that mimics a metabolic constraint, is analyzed by computer simulations. The emergence of a simple "order" (or degree of organization) in this low-dimensionality model system is discussed.

  6. Unjoined primary and secondary neural tubes: junctional neural tube defect, a new form of spinal dysraphism caused by disturbance of junctional neurulation.

    PubMed

    Eibach, Sebastian; Moes, Greg; Hou, Yong Jin; Zovickian, John; Pang, Dachling

    2017-10-01

    Primary and secondary neurulation are the two known processes that form the central neuraxis of vertebrates. Human phenotypes of neural tube defects (NTDs) mostly fall into two corresponding categories consistent with the two types of developmental sequence: primary NTD features an open skin defect, an exposed, unclosed neural plate (hence an open neural tube defect, or ONTD), and an unformed or poorly formed secondary neural tube, and secondary NTD with no skin abnormality (hence a closed NTD) and a malformed conus caudal to a well-developed primary neural tube. We encountered three cases of a previously unrecorded form of spinal dysraphism in which the primary and secondary neural tubes are individually formed but are physically separated far apart and functionally disconnected from each other. One patient was operated on, in whom both the lumbosacral spinal cord from primary neurulation and the conus from secondary neurulation are each anatomically complete and endowed with functioning segmental motor roots tested by intraoperative triggered electromyography and direct spinal cord stimulation. The remarkable feature is that the two neural tubes are unjoined except by a functionally inert, probably non-neural band. The developmental error of this peculiar malformation probably occurs during the critical transition between the end of primary and the beginning of secondary neurulation, in a stage aptly called junctional neurulation. We describe the current knowledge concerning junctional neurulation and speculate on the embryogenesis of this new class of spinal dysraphism, which we call junctional neural tube defect.

  7. Neural coding in graphs of bidirectional associative memories.

    PubMed

    Bouchain, A David; Palm, Günther

    2012-01-24

    In the last years we have developed large neural network models for the realization of complex cognitive tasks in a neural network architecture that resembles the network of the cerebral cortex. We have used networks of several cortical modules that contain two populations of neurons (one excitatory, one inhibitory). The excitatory populations in these so-called "cortical networks" are organized as a graph of Bidirectional Associative Memories (BAMs), where edges of the graph correspond to BAMs connecting two neural modules and nodes of the graph correspond to excitatory populations with associative feedback connections (and inhibitory interneurons). The neural code in each of these modules consists essentially of the firing pattern of the excitatory population, where mainly it is the subset of active neurons that codes the contents to be represented. The overall activity can be used to distinguish different properties of the patterns that are represented which we need to distinguish and control when performing complex tasks like language understanding with these cortical networks. The most important pattern properties or situations are: exactly fitting or matching input, incomplete information or partially matching pattern, superposition of several patterns, conflicting information, and new information that is to be learned. We show simple simulations of these situations in one area or module and discuss how to distinguish these situations based on the overall internal activation of the module. This article is part of a Special Issue entitled "Neural Coding". Copyright © 2011 Elsevier B.V. All rights reserved.

  8. Disrupted white matter structural connectivity in heroin abusers.

    PubMed

    Sun, Yan; Wang, Gui-Bin; Lin, Qi-Xiang; Lu, Lin; Shu, Ni; Meng, Shi-Qiu; Wang, Jun; Han, Hong-Bin; He, Yong; Shi, Jie

    2017-01-01

    Neurocognitive impairment is one of the factors that put heroin abusers at greater risk for relapse, and deficits in related functional brain connections have been found. However, the alterations in structural brain connections that may underlie these functional and neurocognitive impairments remain largely unknown. In the present study, we investigated topological organization alterations in the structural network of white matter in heroin abusers and examined the relationships between the network changes and clinical measures. We acquired diffusion tensor imaging datasets from 76 heroin abusers and 78 healthy controls. Network-based statistic was applied to identify alterations in interregional white matter connectivity, and graph theory methods were used to analyze the properties of global networks. The participants also completed a battery of neurocognitive measures. One increased subnetwork characterizing widespread abnormalities in structural connectivity was present in heroin users, which mainly composed of default-mode, attentional and visual systems. The connection strength was positively correlated with increases in fractional anisotropy in heroin abusers. Intriguingly, the changes in within-frontal and within-temporal connections in heroin abusers were significantly correlated with daily heroin dosage and impulsivity scores, respectively. These findings suggest that heroin abusers have extensive abnormal white matter connectivity, which may mediate the relationship between heroin dependence and clinical measures. The increase in white matter connectivity may be attributable to the inefficient microstructure integrity of white matter. The present findings extend our understanding of cerebral structural disruptions that underlie neurocognitive and functional deficits in heroin addiction and provide circuit-level markers for this chronic disorder. © 2015 Society for the Study of Addiction.

  9. Abnormal medial prefrontal cortex activity in heavy cannabis users during conscious emotional evaluation.

    PubMed

    Wesley, Michael J; Lile, Joshua A; Hanlon, Colleen A; Porrino, Linda J

    2016-03-01

    Long-term heavy cannabis users (cannabis users) who are not acutely intoxicated have diminished subconscious neural responsiveness to affective stimuli. This study sought to determine if abnormal processing extends to the conscious evaluation of emotional stimuli. Functional magnetic resonance imaging (fMRI) was used to examine brain activity as cannabis users (N = 16) and non-cannabis-using controls (N = 17) evaluated and categorized standardized International Affective Picture System (IAPS) stimuli. Individual judgments were used to isolate activity during the evaluation of emotional (i.e., emotional evaluation) or neutral (i.e., neutral evaluation) stimuli. Within- and between-group analyses were performed. Both groups judged the same stimuli as emotional and had activations in visual, midbrain, and middle cingulate cortices during emotional evaluation, relative to neutral. Within-group analyses also revealed amygdalar and inferior frontal gyrus activations in controls, but not cannabis users, and medial prefrontal cortex (mPFC) deactivations in cannabis users, but not controls, during emotional evaluation, relative to neutral. Between-group comparisons found that mPFC activity during positive and negative evaluation was significantly hypoactive in cannabis users, relative to controls. Abnormal neural processing of affective content extends to the level of consciousness in cannabis users. The hypoactive mPFC responses observed resembles the attenuated mPFC responses found during increased non-affective cognitive load in prior research. These findings suggest that abnormal mPFC singling in cannabis users during emotional evaluation might be associated with increased non-affective cognitive load.

  10. Differences in neural responses to ipsilateral stimuli in wide-view fields between face- and house-selective areas

    PubMed Central

    Li, Ting; Niu, Yan; Xiang, Jie; Cheng, Junjie; Liu, Bo; Zhang, Hui; Yan, Tianyi; Kanazawa, Susumu; Wu, Jinglong

    2018-01-01

    Category-selective brain areas exhibit varying levels of neural activity to ipsilaterally presented stimuli. However, in face- and house-selective areas, the neural responses evoked by ipsilateral stimuli in the peripheral visual field remain unclear. In this study, we displayed face and house images using a wide-view visual presentation system while performing functional magnetic resonance imaging (fMRI). The face-selective areas (fusiform face area (FFA) and occipital face area (OFA)) exhibited intense neural responses to ipsilaterally presented images, whereas the house-selective areas (parahippocampal place area (PPA) and transverse occipital sulcus (TOS)) exhibited substantially smaller and even negative neural responses to the ipsilaterally presented images. We also found that the category preferences of the contralateral and ipsilateral neural responses were similar. Interestingly, the face- and house-selective areas exhibited neural responses to ipsilateral images that were smaller than the responses to the contralateral images. Multi-voxel pattern analysis (MVPA) was implemented to evaluate the difference between the contralateral and ipsilateral responses. The classification accuracies were much greater than those expected by chance. The classification accuracies in the FFA were smaller than those in the PPA and TOS. The closer eccentricities elicited greater classification accuracies in the PPA and TOS. We propose that these ipsilateral neural responses might be interpreted by interhemispheric communication through intrahemispheric connectivity of white matter connection and interhemispheric connectivity via the corpus callosum and occipital white matter connection. Furthermore, the PPA and TOS likely have weaker interhemispheric communication than the FFA and OFA, particularly in the peripheral visual field. PMID:29451872

  11. Temporal lobe abnormalities in semantic processing by criminal psychopaths as revealed by functional magnetic resonance imaging.

    PubMed

    Kiehl, Kent A; Smith, Andra M; Mendrek, Adrianna; Forster, Bruce B; Hare, Robert D; Liddle, Peter F

    2004-04-30

    We tested the hypothesis that psychopathy is associated with abnormalities in semantic processing of linguistic information. Functional magnetic resonance imaging (fMRI) was used to elucidate and characterize the neural architecture underlying lexico-semantic processes in criminal psychopathic individuals and in a group of matched control participants. Participants performed a lexical decision task in which blocks of linguistic stimuli alternated with a resting baseline condition. In each lexical decision block, the stimuli were either concrete words and pseudowords or abstract words and pseudowords. Consistent with our hypothesis, psychopathic individuals, relative to controls, showed poorer behavioral performance for processing abstract words. Analysis of the fMRI data for both groups indicated that processing of word stimuli, compared with the resting baseline condition, was associated with neural activation in bilateral fusiform gyrus, anterior cingulate, left middle temporal gyrus, right posterior superior temporal gyrus, and left and right inferior frontal gyrus. Analyses confirmed our prediction that psychopathic individuals would fail to show the appropriate neural differentiation between abstract and concrete stimuli in the right anterior temporal gyrus and surrounding cortex. The results are consistent with other studies of semantic processing in psychopathy and support the theory that psychopathy is associated with right hemisphere abnormalities for processing conceptually abstract material.

  12. Temporal lobe abnormalities in semantic processing by criminal psychopaths as revealed by functional magnetic resonance imaging.

    PubMed

    Kiehl, Kent A; Smith, Andra M; Mendrek, Adrianna; Forster, Bruce B; Hare, Robert D; Liddle, Peter F

    2004-01-15

    We tested the hypothesis that psychopathy is associated with abnormalities in semantic processing of linguistic information. Functional magnetic resonance imaging (fMRI) was used to elucidate and characterize the neural architecture underlying lexico-semantic processes in criminal psychopathic individuals and in a group of matched control participants. Participants performed a lexical decision task in which blocks of linguistic stimuli alternated with a resting baseline condition. In each lexical decision block, the stimuli were either concrete words and pseudowords or abstract words and pseudowords. Consistent with our hypothesis, psychopathic individuals, relative to controls, showed poorer behavioral performance for processing abstract words. Analysis of the fMRI data for both groups indicated that processing of word stimuli, compared with the resting baseline condition, was associated with neural activation in bilateral fusiform gyrus, anterior cingulate, left middle temporal gyrus, right posterior superior temporal gyrus, and left and right inferior frontal gyrus. Analyses confirmed our prediction that psychopathic individuals would fail to show the appropriate neural differentiation between abstract and concrete stimuli in the right anterior temporal gyrus and surrounding cortex. The results are consistent with other studies of semantic processing in psychopathy and support the theory that psychopathy is associated with right hemisphere abnormalities for processing conceptually abstract material.

  13. Efficient self-organizing multilayer neural network for nonlinear system modeling.

    PubMed

    Han, Hong-Gui; Wang, Li-Dan; Qiao, Jun-Fei

    2013-07-01

    It has been shown extensively that the dynamic behaviors of a neural system are strongly influenced by the network architecture and learning process. To establish an artificial neural network (ANN) with self-organizing architecture and suitable learning algorithm for nonlinear system modeling, an automatic axon-neural network (AANN) is investigated in the following respects. First, the network architecture is constructed automatically to change both the number of hidden neurons and topologies of the neural network during the training process. The approach introduced in adaptive connecting-and-pruning algorithm (ACP) is a type of mixed mode operation, which is equivalent to pruning or adding the connecting of the neurons, as well as inserting some required neurons directly. Secondly, the weights are adjusted, using a feedforward computation (FC) to obtain the information for the gradient during learning computation. Unlike most of the previous studies, AANN is able to self-organize the architecture and weights, and to improve the network performances. Also, the proposed AANN has been tested on a number of benchmark problems, ranging from nonlinear function approximating to nonlinear systems modeling. The experimental results show that AANN can have better performances than that of some existing neural networks. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

  14. Functional connectivity mapping of regions associated with self- and other-processing.

    PubMed

    Murray, Ryan J; Debbané, Martin; Fox, Peter T; Bzdok, Danilo; Eickhoff, Simon B

    2015-04-01

    Neuroscience literature increasingly suggests a conceptual self composed of interacting neural regions, rather than independent local activations, yet such claims have yet to be investigated. We, thus, combined task-dependent meta-analytic connectivity modeling (MACM) with task-independent resting-state (RS) connectivity analysis to delineate the neural network of the self, across both states. Given psychological evidence implicating the self's interdependence on social information, we also delineated the neural network underlying conceptual other-processing. To elucidate the relation between the self-/other-networks and their function, we mined the MACM metadata to generate a cognitive-behavioral profile for an empirically identified region specific to conceptual self, the pregenual anterior cingulate (pACC), and conceptual other, posterior cingulate/precuneus (PCC/PC). Mining of 7,200 published, task-dependent, neuroimaging studies, using healthy human subjects, yielded 193 studies activating the self-related seed and were conjoined with RS connectivity analysis to delineate a differentiated self-network composed of the pACC (seed) and anterior insula, relative to other functional connectivity. Additionally, 106 studies activating the other-related seed were conjoined with RS connectivity analysis to delineate a differentiated other-network of PCC/PC (seed) and angular gyrus/temporoparietal junction, relative to self-functional connectivity. The self-network seed related to emotional conflict resolution and motivational processing, whereas the other-network seed related to socially oriented processing and contextual information integration. Notably, our findings revealed shared RS connectivity between ensuing self-/other-networks within the ventromedial prefrontal cortex and medial orbitofrontal cortex, suggesting self-updating via integration of self-relevant social information. We, therefore, present initial neurobiological evidence corroborating the increasing

  15. Altered amygdala-prefrontal connectivity during emotion perception in schizophrenia.

    PubMed

    Bjorkquist, Olivia A; Olsen, Emily K; Nelson, Brady D; Herbener, Ellen S

    2016-08-01

    Individuals with schizophrenia evidence impaired emotional functioning. Abnormal amygdala activity has been identified as an etiological factor underlying affective impairment in this population, but the exact nature remains unclear. The current study utilized psychophysiological interaction analyses to examine functional connectivity between the amygdala and medial prefrontal cortex (mPFC) during an emotion perception task. Participants with schizophrenia (SZ) and healthy controls (HC) viewed and rated positive, negative, and neutral images while undergoing functional neuroimaging. Results revealed a significant group difference in right amygdala-mPFC connectivity during perception of negative versus neutral images. Specifically, HC participants demonstrated positive functional coupling between the amygdala and mPFC, consistent with co-active processing of salient information. In contrast, SZ participants evidenced negative functional coupling, consistent with top-down inhibition of the amygdala by the mPFC. A significant positive correlation between connectivity strength during negative image perception and clinician-rated social functioning was also observed in SZ participants, such that weaker right amygdala-mPFC coupling during negative compared to neutral image perception was associated with poorer social functioning. Overall, results suggest that emotional dysfunction and associated deficits in functional outcome in schizophrenia may relate to abnormal interactions between the amygdala and mPFC during perception of emotional stimuli. This study adds to the growing literature on abnormal functional connections in schizophrenia and supports the functional disconnection hypothesis of schizophrenia. Copyright © 2016 Elsevier B.V. All rights reserved.

  16. Temporal and spectral characteristics of dynamic functional connectivity between resting-state networks reveal information beyond static connectivity

    PubMed Central

    Yeh, Hsiang J.; Guindani, Michele; Vannucci, Marina; Haneef, Zulfi; Stern, John M.

    2018-01-01

    Estimation of functional connectivity (FC) has become an increasingly powerful tool for investigating healthy and abnormal brain function. Static connectivity, in particular, has played a large part in guiding conclusions from the majority of resting-state functional MRI studies. However, accumulating evidence points to the presence of temporal fluctuations in FC, leading to increasing interest in estimating FC as a dynamic quantity. One central issue that has arisen in this new view of connectivity is the dramatic increase in complexity caused by dynamic functional connectivity (dFC) estimation. To computationally handle this increased complexity, a limited set of dFC properties, primarily the mean and variance, have generally been considered. Additionally, it remains unclear how to integrate the increased information from dFC into pattern recognition techniques for subject-level prediction. In this study, we propose an approach to address these two issues based on a large number of previously unexplored temporal and spectral features of dynamic functional connectivity. A Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model is used to estimate time-varying patterns of functional connectivity between resting-state networks. Time-frequency analysis is then performed on dFC estimates, and a large number of previously unexplored temporal and spectral features drawn from signal processing literature are extracted for dFC estimates. We apply the investigated features to two neurologic populations of interest, healthy controls and patients with temporal lobe epilepsy, and show that the proposed approach leads to substantial increases in predictive performance compared to both traditional estimates of static connectivity as well as current approaches to dFC. Variable importance is assessed and shows that there are several quantities that can be extracted from dFC signal which are more informative than the traditional mean or variance of dFC. This work

  17. Extrinsic and Intrinsic Brain Network Connectivity Maintains Cognition across the Lifespan Despite Accelerated Decay of Regional Brain Activation.

    PubMed

    Tsvetanov, Kamen A; Henson, Richard N A; Tyler, Lorraine K; Razi, Adeel; Geerligs, Linda; Ham, Timothy E; Rowe, James B

    2016-03-16

    The maintenance of wellbeing across the lifespan depends on the preservation of cognitive function. We propose that successful cognitive aging is determined by interactions both within and between large-scale functional brain networks. Such connectivity can be estimated from task-free functional magnetic resonance imaging (fMRI), also known as resting-state fMRI (rs-fMRI). However, common correlational methods are confounded by age-related changes in the neurovascular signaling. To estimate network interactions at the neuronal rather than vascular level, we used generative models that specified both the neural interactions and a flexible neurovascular forward model. The networks' parameters were optimized to explain the spectral dynamics of rs-fMRI data in 602 healthy human adults from population-based cohorts who were approximately uniformly distributed between 18 and 88 years (www.cam-can.com). We assessed directed connectivity within and between three key large-scale networks: the salience network, dorsal attention network, and default mode network. We found that age influences connectivity both within and between these networks, over and above the effects on neurovascular coupling. Canonical correlation analysis revealed that the relationship between network connectivity and cognitive function was age-dependent: cognitive performance relied on neural dynamics more strongly in older adults. These effects were driven partly by reduced stability of neural activity within all networks, as expressed by an accelerated decay of neural information. Our findings suggest that the balance of excitatory connectivity between networks, and the stability of intrinsic neural representations within networks, changes with age. The cognitive function of older adults becomes increasingly dependent on these factors. Maintaining cognitive function is critical to successful aging. To study the neural basis of cognitive function across the lifespan, we studied a large population

  18. Extrinsic and Intrinsic Brain Network Connectivity Maintains Cognition across the Lifespan Despite Accelerated Decay of Regional Brain Activation

    PubMed Central

    Henson, Richard N.A.; Tyler, Lorraine K.; Razi, Adeel; Geerligs, Linda; Ham, Timothy E.; Rowe, James B.

    2016-01-01

    The maintenance of wellbeing across the lifespan depends on the preservation of cognitive function. We propose that successful cognitive aging is determined by interactions both within and between large-scale functional brain networks. Such connectivity can be estimated from task-free functional magnetic resonance imaging (fMRI), also known as resting-state fMRI (rs-fMRI). However, common correlational methods are confounded by age-related changes in the neurovascular signaling. To estimate network interactions at the neuronal rather than vascular level, we used generative models that specified both the neural interactions and a flexible neurovascular forward model. The networks' parameters were optimized to explain the spectral dynamics of rs-fMRI data in 602 healthy human adults from population-based cohorts who were approximately uniformly distributed between 18 and 88 years (www.cam-can.com). We assessed directed connectivity within and between three key large-scale networks: the salience network, dorsal attention network, and default mode network. We found that age influences connectivity both within and between these networks, over and above the effects on neurovascular coupling. Canonical correlation analysis revealed that the relationship between network connectivity and cognitive function was age-dependent: cognitive performance relied on neural dynamics more strongly in older adults. These effects were driven partly by reduced stability of neural activity within all networks, as expressed by an accelerated decay of neural information. Our findings suggest that the balance of excitatory connectivity between networks, and the stability of intrinsic neural representations within networks, changes with age. The cognitive function of older adults becomes increasingly dependent on these factors. SIGNIFICANCE STATEMENT Maintaining cognitive function is critical to successful aging. To study the neural basis of cognitive function across the lifespan, we studied a

  19. Socioeconomic disadvantage and neural development from infancy through early childhood.

    PubMed

    Chin-Lun Hung, Galen; Hahn, Jill; Alamiri, Bibi; Buka, Stephen L; Goldstein, Jill M; Laird, Nan; Nelson, Charles A; Smoller, Jordan W; Gilman, Stephen E

    2015-12-01

    Early social experiences are believed to shape neurodevelopment, with potentially lifelong consequences. Yet minimal evidence exists regarding the role of the social environment on children's neural functioning, a core domain of neurodevelopment. We analysed data from 36 443 participants in the United States Collaborative Perinatal Project, a socioeconomically diverse pregnancy cohort conducted between 1959 and 1974. Study outcomes included: physician (neurologist or paediatrician)-rated neurological abnormality neonatally and thereafter at 4 months and 1 and 7 years; indicators of neurological hard signs and soft signs; and indicators of autonomic nervous system function. Children born to socioeconomically disadvantaged parents were more likely to exhibit neurological abnormalities at 4 months [odds ratio (OR) = 1.20; 95% confidence interval (CI) = 1.06, 1.37], 1 year (OR = 1.35; CI = 1.17, 1.56), and 7 years (OR = 1.67; CI = 1.48, 1.89), and more likely to exhibit neurological hard signs (OR = 1.39; CI = 1.10, 1.76), soft signs (OR = 1.26; CI = 1.09, 1.45) and autonomic nervous system dysfunctions at 7 years. Pregnancy and delivery complications, themselves associated with socioeconomic disadvantage, did not account for the higher risks of neurological abnormalities among disadvantaged children. Parental socioeconomic disadvantage was, independently from pregnancy and delivery complications, associated with abnormal child neural development during the first 7 years of life. These findings reinforce the importance of the early environment for neurodevelopment generally, and expand knowledge regarding the domains of neurodevelopment affected by environmental conditions. Further work is needed to determine the mechanisms linking socioeconomic disadvantage with children's neural functioning, the timing of such mechanisms and their potential reversibility. Published by Oxford University Press on behalf of the International

  20. Hardware Acceleration of Adaptive Neural Algorithms.

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    James, Conrad D.

    As tradit ional numerical computing has faced challenges, researchers have turned towards alternative computing approaches to reduce power - per - computation metrics and improve algorithm performance. Here, we describe an approach towards non - conventional computing that strengthens the connection between machine learning and neuroscience concepts. The Hardware Acceleration of Adaptive Neural Algorithms (HAANA) project ha s develop ed neural machine learning algorithms and hardware for applications in image processing and cybersecurity. While machine learning methods are effective at extracting relevant features from many types of data, the effectiveness of these algorithms degrades when subjected to real - worldmore » conditions. Our team has generated novel neural - inspired approa ches to improve the resiliency and adaptability of machine learning algorithms. In addition, we have also designed and fabricated hardware architectures and microelectronic devices specifically tuned towards the training and inference operations of neural - inspired algorithms. Finally, our multi - scale simulation framework allows us to assess the impact of microelectronic device properties on algorithm performance.« less