Neural basis of postural instability identified by VTC and EEG

PubMed Central

Cao, Cheng; Jaiswal, Niharika; Newell, Karl M.

2010-01-01

In this study, we investigated the neural basis of virtual time to contact (VTC) and the hypothesis that VTC provides predictive information for future postural instability. A novel approach to differentiate stable pre-falling and transition-to-instability stages within a single postural trial while a subject was performing a challenging single leg stance with eyes closed was developed. Specifically, we utilized wavelet transform and stage segmentation algorithms using VTC time series data set as an input. The VTC time series was time-locked with multichannel (n = 64) EEG signals to examine its underlying neural substrates. To identify the focal sources of neural substrates of VTC, a two-step approach was designed combining the independent component analysis (ICA) and low-resolution tomography (LORETA) of multichannel EEG. There were two major findings: (1) a significant increase of VTC minimal values (along with enhanced variability of VTC) was observed during the transition-to-instability stage with progression to ultimate loss of balance and falling; and (2) this VTC dynamics was associated with pronounced modulation of EEG predominantly within theta, alpha and gamma frequency bands. The sources of this EEG modulation were identified at the cingulate cortex (ACC) and the junction of precuneus and parietal lobe, as well as at the occipital cortex. The findings support the hypothesis that the systematic increase of minimal values of VTC concomitant with modulation of EEG signals at the frontal-central and parietal–occipital areas serve collectively to predict the future instability in posture. PMID:19655130

Modelling innovation performance of European regions using multi-output neural networks

PubMed Central

Henriques, Roberto

2017-01-01

Regional innovation performance is an important indicator for decision-making regarding the implementation of policies intended to support innovation. However, patterns in regional innovation structures are becoming increasingly diverse, complex and nonlinear. To address these issues, this study aims to develop a model based on a multi-output neural network. Both intra- and inter-regional determinants of innovation performance are empirically investigated using data from the 4th and 5th Community Innovation Surveys of NUTS 2 (Nomenclature of Territorial Units for Statistics) regions. The results suggest that specific innovation strategies must be developed based on the current state of input attributes in the region. Thus, it is possible to develop appropriate strategies and targeted interventions to improve regional innovation performance. We demonstrate that support of entrepreneurship is an effective instrument of innovation policy. We also provide empirical support that both business and government R&D activity have a sigmoidal effect, implying that the most effective R&D support should be directed to regions with below-average and average R&D activity. We further show that the multi-output neural network outperforms traditional statistical and machine learning regression models. In general, therefore, it seems that the proposed model can effectively reflect both the multiple-output nature of innovation performance and the interdependency of the output attributes. PMID:28968449

Modelling innovation performance of European regions using multi-output neural networks.

PubMed

Hajek, Petr; Henriques, Roberto

2017-01-01

Regional innovation performance is an important indicator for decision-making regarding the implementation of policies intended to support innovation. However, patterns in regional innovation structures are becoming increasingly diverse, complex and nonlinear. To address these issues, this study aims to develop a model based on a multi-output neural network. Both intra- and inter-regional determinants of innovation performance are empirically investigated using data from the 4th and 5th Community Innovation Surveys of NUTS 2 (Nomenclature of Territorial Units for Statistics) regions. The results suggest that specific innovation strategies must be developed based on the current state of input attributes in the region. Thus, it is possible to develop appropriate strategies and targeted interventions to improve regional innovation performance. We demonstrate that support of entrepreneurship is an effective instrument of innovation policy. We also provide empirical support that both business and government R&D activity have a sigmoidal effect, implying that the most effective R&D support should be directed to regions with below-average and average R&D activity. We further show that the multi-output neural network outperforms traditional statistical and machine learning regression models. In general, therefore, it seems that the proposed model can effectively reflect both the multiple-output nature of innovation performance and the interdependency of the output attributes.

Regional and stage-specific effects of prospectively purified vascular cells on the adult V-SVZ neural stem cell lineage.

PubMed

Crouch, Elizabeth E; Liu, Chang; Silva-Vargas, Violeta; Doetsch, Fiona

2015-03-18

Adult neural stem cells reside in specialized niches. In the ventricular-subventricular zone (V-SVZ), quiescent neural stem cells (qNSCs) become activated (aNSCs), and generate transit amplifying cells (TACs), which give rise to neuroblasts that migrate to the olfactory bulb. The vasculature is an important component of the adult neural stem cell niche, but whether vascular cells in neurogenic areas are intrinsically different from those elsewhere in the brain is unknown. Moreover, the contribution of pericytes to the neural stem cell niche has not been defined. Here, we describe a rapid FACS purification strategy to simultaneously isolate primary endothelial cells and pericytes from brain microregions of nontransgenic mice using CD31 and CD13 as surface markers. We compared the effect of purified vascular cells from a neurogenic (V-SVZ) and non-neurogenic brain region (cortex) on the V-SVZ stem cell lineage in vitro. Endothelial and pericyte diffusible signals from both regions differentially promote the proliferation and neuronal differentiation of qNSCs, aNSCs, and TACs. Unexpectedly, diffusible cortical signals had the most potent effects on V-SVZ proliferation and neurogenesis, highlighting the intrinsic capacity of non-neurogenic vasculature to support stem cell behavior. Finally, we identify PlGF-2 as an endothelial-derived mitogen that promotes V-SVZ cell proliferation. This purification strategy provides a platform to define the functional and molecular contribution of vascular cells to stem cell niches and other brain regions under different physiological and pathological states. Copyright © 2015 the authors 0270-6474/15/354528-12$15.00/0.

Forecasting the daily electricity consumption in the Moscow region using artificial neural networks

NASA Astrophysics Data System (ADS)

Ivanov, V. V.; Kryanev, A. V.; Osetrov, E. S.

2017-07-01

In [1] we demonstrated the possibility in principle for short-term forecasting of daily volumes of passenger traffic in the Moscow metro with the help of artificial neural networks. During training and predicting, a set of the factors that affect the daily passenger traffic in the subway is passed to the input of the neural network. One of these factors is the daily power consumption in the Moscow region. Therefore, to predict the volume of the passenger traffic in the subway, we must first to solve the problem of forecasting the daily energy consumption in the Moscow region.

An artificial neural network system to identify alleles in reference electropherograms.

PubMed

Taylor, Duncan; Harrison, Ash; Powers, David

2017-09-01

Electropherograms are produced in great numbers in forensic DNA laboratories as part of everyday criminal casework. Before the results of these electropherograms can be used they must be scrutinised by analysts to determine what the identified data tells them about the underlying DNA sequences and what is purely an artefact of the DNA profiling process. This process of interpreting the electropherograms can be time consuming and is prone to subjective differences between analysts. Recently it was demonstrated that artificial neural networks could be used to classify information within an electropherogram as allelic (i.e. representative of a DNA fragment present in the DNA extract) or as one of several different categories of artefactual fluorescence that arise as a result of generating an electropherogram. We extend that work here to demonstrate a series of algorithms and artificial neural networks that can be used to identify peaks on an electropherogram and classify them. We demonstrate the functioning of the system on several profiles and compare the results to a leading commercial DNA profile reading system. Copyright © 2017 Elsevier B.V. All rights reserved.

A comparison of neural tube defects identified by two independent routine recording systems for congenital malformations in Northern Ireland.

PubMed

Nevin, N C; McDonald, J R; Walby, A L

1978-12-01

The efficiency of two systems for recording congenital malformations has been compared; one system, the Registrar General's Congenital Malformation Notification, is based on registering all malformed infants, and the other, the Child Health System, records all births. In Northern Ireland for three years [1974--1976], using multiple sources of ascertainment, a total of 686 infants with neural tube defects was identified among 79 783 live and stillbirths. The incidence for all neural tube defects in 8 60 per 1 000 births. The Registrar General's Congenital Malformation Notification System identified 83.6% whereas the Child Health System identified only 63.3% of all neural tube defects. Both systems together identified 86.2% of all neural tube defects. The two systems are suitable for monitoring of malformations and the addition of information from the Genetic Counselling Clinics would enhance the data for epidemiological studies.

Identification and characterization of secondary neural tube-derived embryonic neural stem cells in vitro.

PubMed

Shaker, Mohammed R; Kim, Joo Yeon; Kim, Hyun; Sun, Woong

2015-05-15

Secondary neurulation is an embryonic progress that gives rise to the secondary neural tube, the precursor of the lower spinal cord region. The secondary neural tube is derived from aggregated Sox2-expressing neural cells at the dorsal region of the tail bud, which eventually forms rosette or tube-like structures to give rise to neural tissues in the tail bud. We addressed whether the embryonic tail contains neural stem cells (NSCs), namely secondary NSCs (sNSCs), with the potential for self-renewal in vitro. Using in vitro neurosphere assays, neurospheres readily formed at the rosette and neural-tube levels, but less frequently at the tail bud tip level. Furthermore, we identified that sNSC-generated neurospheres were significantly smaller in size compared with cortical neurospheres. Interestingly, various cell cycle analyses revealed that this difference was not due to a reduction in the proliferation rate of NSCs, but rather the neuronal commitment of sNSCs, as sNSC-derived neurospheres contain more committed neuronal progenitor cells, even in the presence of epidermal growth factor (EGF) and basic fibroblast growth factor (bFGF). These results suggest that the higher tendency for sNSCs to spontaneously differentiate into progenitor cells may explain the limited expansion of the secondary neural tube during embryonic development.

Identifying a Network of Brain Regions Involved in Aversion-Related Processing: A Cross-Species Translational Investigation

PubMed Central

Hayes, Dave J.; Northoff, Georg

2011-01-01

The ability to detect and respond appropriately to aversive stimuli is essential for all organisms, from fruit flies to humans. This suggests the existence of a core neural network which mediates aversion-related processing. Human imaging studies on aversion have highlighted the involvement of various cortical regions, such as the prefrontal cortex, while animal studies have focused largely on subcortical regions like the periaqueductal gray and hypothalamus. However, whether and how these regions form a core neural network of aversion remains unclear. To help determine this, a translational cross-species investigation in humans (i.e., meta-analysis) and other animals (i.e., systematic review of functional neuroanatomy) was performed. Our results highlighted the recruitment of the anterior cingulate cortex, the anterior insula, and the amygdala as well as other subcortical (e.g., thalamus, midbrain) and cortical (e.g., orbitofrontal) regions in both animals and humans. Importantly, involvement of these regions remained independent of sensory modality. This study provides evidence for a core neural network mediating aversion in both animals and humans. This not only contributes to our understanding of the trans-species neural correlates of aversion but may also carry important implications for psychiatric disorders where abnormal aversive behavior can often be observed. PMID:22102836

Evaluation of a functional epigenetic approach to identify promoter region methylation in phaeochromocytoma and neuroblastoma

PubMed Central

Margetts, Caroline D E; Morris, Mark; Astuti, Dewi; Gentle, Dean C; Cascon, Alberto; McRonald, Fiona E; Catchpoole, Daniel; Robledo, Mercedes; Neumann, Hartmut P H; Latif, Farida; Maher, Eamonn R

2008-01-01

The molecular genetics of inherited phaeochromocytoma have received considerable attention, but the somatic genetic and epigenetic events that characterise tumourigenesis in sporadic phaeochromocytomas are less well defined. Previously, we found considerable overlap between patterns of promoter region tumour suppressor gene (TSG) hypermethylation in two neural crest tumours, neuroblastoma and phaeochromocytoma. In order to identify candidate biomarkers and epigenetically inactivated TSGs in phaeochromocytoma and neuroblastoma, we characterised changes in gene expression in three neuroblastoma cell lines after treatment with the demethylating agent 5-azacytidine. Promoter region methylation status was then determined for 28 genes that demonstrated increased expression after demethylation. Three genes HSP47, homeobox A9 (HOXA9) and opioid binding protein (OPCML) were methylated in >10% of phaeochromocytomas (52, 17 and 12% respectively). Two of the genes, epithelial membrane protein 3 (EMP3) and HSP47, demonstrated significantly more frequent methylation in neuroblastoma than phaeochromocytoma. These findings extend epigenotype of phaeochromocytoma and identify candidate genes implicated in sporadic phaeochromocytoma tumourigenesis. PMID:18499731

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.

Inversion of parameters for semiarid regions by a neural network

NASA Technical Reports Server (NTRS)

Zurk, Lisa M.; Davis, Daniel; Njoku, Eni G.; Tsang, Leung; Hwang, Jenq-Neng

1992-01-01

Microwave brightness temperatures obtained from a passive radiative transfer model are inverted through use of a neural network. The model is applicable to semiarid regions and produces dual-polarized brightness temperatures for 6.6-, 10.7-, and 37-GHz frequencies. A range of temperatures is generated by varying three geophysical parameters over acceptable ranges: soil moisture, vegetation moisture, and soil temperature. A multilayered perceptron (MLP) neural network is trained with a subset of the generated temperatures, and the remaining temperatures are inverted using a backpropagation method. Several synthetic terrains are devised and inverted by the network under local constraints. All the inversions show good agreement with the original geophysical parameters, falling within 5 percent of the actual value of the parameter range.

Identifying Neural Patterns of Functional Dyspepsia Using Multivariate Pattern Analysis: A Resting-State fMRI Study

PubMed Central

Liu, Peng; Qin, Wei; Wang, Jingjing; Zeng, Fang; Zhou, Guangyu; Wen, Haixia; von Deneen, Karen M.; Liang, Fanrong; Gong, Qiyong; Tian, Jie

2013-01-01

Background Previous imaging studies on functional dyspepsia (FD) have focused on abnormal brain functions during special tasks, while few studies concentrated on the resting-state abnormalities of FD patients, which might be potentially valuable to provide us with direct information about the neural basis of FD. The main purpose of the current study was thereby to characterize the distinct patterns of resting-state function between FD patients and healthy controls (HCs). Methodology/Principal Findings Thirty FD patients and thirty HCs were enrolled and experienced 5-mintue resting-state scanning. Based on the support vector machine (SVM), we applied multivariate pattern analysis (MVPA) to investigate the differences of resting-state function mapped by regional homogeneity (ReHo). A classifier was designed by using the principal component analysis and the linear SVM. Permutation test was then employed to identify the significant contribution to the final discrimination. The results displayed that the mean classifier accuracy was 86.67%, and highly discriminative brain regions mainly included the prefrontal cortex (PFC), orbitofrontal cortex (OFC), supplementary motor area (SMA), temporal pole (TP), insula, anterior/middle cingulate cortex (ACC/MCC), thalamus, hippocampus (HIPP)/parahippocamus (ParaHIPP) and cerebellum. Correlation analysis revealed significant correlations between ReHo values in certain regions of interest (ROI) and the FD symptom severity and/or duration, including the positive correlations between the dmPFC, pACC and the symptom severity; whereas, the positive correlations between the MCC, OFC, insula, TP and FD duration. Conclusions These findings indicated that significantly distinct patterns existed between FD patients and HCs during the resting-state, which could expand our understanding of the neural basis of FD. Meanwhile, our results possibly showed potential feasibility of functional magnetic resonance imaging diagnostic assay for FD. PMID

Identifying the Neural Substrates of Procrastination: a Resting-State fMRI Study.

PubMed

Zhang, Wenwen; Wang, Xiangpeng; Feng, Tingyong

2016-09-12

Procrastination is a prevalent problematic behavior that brings serious consequences to individuals who suffer from it. Although this phenomenon has received increasing attention from researchers, the underpinning neural substrates of it is poorly studied. To examine the neural bases subserving procrastination, the present study employed resting-state fMRI. The main results were as follows: (1) the behavioral procrastination was positively correlated with the regional activity of the ventromedial prefrontal cortex (vmPFC) and the parahippocampal cortex (PHC), while negatively correlated with that of the anterior prefrontal cortex (aPFC). (2) The aPFC-seed connectivity with the anterior medial prefrontal cortex and the posterior cingulate cortex was positively associated with procrastination. (3) The connectivity between vmPFC and several other regions, such as the dorsomedial prefrontal cortex, the bilateral inferior prefrontal cortex showed a negative association with procrastination. These results suggested that procrastination could be attributed to, on the one hand, hyper-activity of the default mode network (DMN) that overrides the prefrontal control signal; while on the other hand, the failure of top-down control exerted by the aPFC on the DMN. Therefore, the present study unravels the biomarkers of procrastination and provides treatment targets for procrastination prevention.

Identifying the Neural Substrates of Procrastination: a Resting-State fMRI Study

PubMed Central

Zhang, Wenwen; Wang, Xiangpeng; Feng, Tingyong

2016-01-01

Procrastination is a prevalent problematic behavior that brings serious consequences to individuals who suffer from it. Although this phenomenon has received increasing attention from researchers, the underpinning neural substrates of it is poorly studied. To examine the neural bases subserving procrastination, the present study employed resting-state fMRI. The main results were as follows: (1) the behavioral procrastination was positively correlated with the regional activity of the ventromedial prefrontal cortex (vmPFC) and the parahippocampal cortex (PHC), while negatively correlated with that of the anterior prefrontal cortex (aPFC). (2) The aPFC-seed connectivity with the anterior medial prefrontal cortex and the posterior cingulate cortex was positively associated with procrastination. (3) The connectivity between vmPFC and several other regions, such as the dorsomedial prefrontal cortex, the bilateral inferior prefrontal cortex showed a negative association with procrastination. These results suggested that procrastination could be attributed to, on the one hand, hyper-activity of the default mode network (DMN) that overrides the prefrontal control signal; while on the other hand, the failure of top-down control exerted by the aPFC on the DMN. Therefore, the present study unravels the biomarkers of procrastination and provides treatment targets for procrastination prevention. PMID:27616687

Identifying temporal and causal contributions of neural processes underlying the Implicit Association Test (IAT)

PubMed Central

Forbes, Chad E.; Cameron, Katherine A.; Grafman, Jordan; Barbey, Aron; Solomon, Jeffrey; Ritter, Walter; Ruchkin, Daniel S.

2012-01-01

The Implicit Association Test (IAT) is a popular behavioral measure that assesses the associative strength between outgroup members and stereotypical and counterstereotypical traits. Less is known, however, about the degree to which the IAT reflects automatic processing. Two studies examined automatic processing contributions to a gender-IAT using a data driven, social neuroscience approach. Performance on congruent (e.g., categorizing male names with synonyms of strength) and incongruent (e.g., categorizing female names with synonyms of strength) IAT blocks were separately analyzed using EEG (event-related potentials, or ERPs, and coherence; Study 1) and lesion (Study 2) methodologies. Compared to incongruent blocks, performance on congruent IAT blocks was associated with more positive ERPs that manifested in frontal and occipital regions at automatic processing speeds, occipital regions at more controlled processing speeds and was compromised by volume loss in the anterior temporal lobe (ATL), insula and medial PFC. Performance on incongruent blocks was associated with volume loss in supplementary motor areas, cingulate gyrus and a region in medial PFC similar to that found for congruent blocks. Greater coherence was found between frontal and occipital regions to the extent individuals exhibited more bias. This suggests there are separable neural contributions to congruent and incongruent blocks of the IAT but there is also a surprising amount of overlap. Given the temporal and regional neural distinctions, these results provide converging evidence that stereotypic associative strength assessed by the IAT indexes automatic processing to a degree. PMID:23226123

Crowd counting via region based multi-channel convolution neural network

NASA Astrophysics Data System (ADS)

Cao, Xiaoguang; Gao, Siqi; Bai, Xiangzhi

2017-11-01

This paper proposed a novel region based multi-channel convolution neural network architecture for crowd counting. In order to effectively solve the perspective distortion in crowd datasets with a great diversity of scales, this work combines the main channel and three branch channels. These channels extract both the global and region features. And the results are used to estimate density map. Moreover, kernels with ladder-shaped sizes are designed across all the branch channels, which generate adaptive region features. Also, branch channels use relatively deep and shallow network to achieve more accurate detector. By using these strategies, the proposed architecture achieves state-of-the-art performance on ShanghaiTech datasets and competitive performance on UCF_CC_50 datasets.

Machine learning of neural representations of suicide and emotion concepts identifies suicidal youth

PubMed Central

Just, Marcel Adam; Pan, Lisa; Cherkassky, Vladimir L.; McMakin, Dana; Cha, Christine; Nock, Matthew K.; Brent, David

2017-01-01

The clinical assessment of suicidal risk would be significantly complemented by a biologically-based measure that assesses alterations in the neural representations of concepts related to death and life in people who engage in suicidal ideation. This study used machine-learning algorithms (Gaussian Naïve Bayes) to identify such individuals (17 suicidal ideators vs 17 controls) with high (91%) accuracy, based on their altered fMRI neural signatures of death and life-related concepts. The most discriminating concepts were death, cruelty, trouble, carefree, good, and praise. A similar classification accurately (94%) discriminated 9 suicidal ideators who had made a suicide attempt from 8 who had not. Moreover, a major facet of the concept alterations was the evoked emotion, whose neural signature served as an alternative basis for accurate (85%) group classification. The study establishes a biological, neurocognitive basis for altered concept representations in participants with suicidal ideation, which enables highly accurate group membership classification. PMID:29367952

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

Generation of Regionally Specific Neural Progenitor Cells (NPCs) and Neurons from Human Pluripotent Stem Cells (hPSCs).

PubMed

Cutts, Josh; Brookhouser, Nicholas; Brafman, David A

2016-01-01

Neural progenitor cells (NPCs) derived from human pluripotent stem cells (hPSCs) are a multipotent cell population capable of long-term expansion and differentiation into a variety of neuronal subtypes. As such, NPCs have tremendous potential for disease modeling, drug screening, and regenerative medicine. Current methods for the generation of NPCs results in cell populations homogenous for pan-neural markers such as SOX1 and SOX2 but heterogeneous with respect to regional identity. In order to use NPCs and their neuronal derivatives to investigate mechanisms of neurological disorders and develop more physiologically relevant disease models, methods for generation of regionally specific NPCs and neurons are needed. Here, we describe a protocol in which exogenous manipulation of WNT signaling, through either activation or inhibition, during neural differentiation of hPSCs, promotes the formation of regionally homogenous NPCs and neuronal cultures. In addition, we provide methods to monitor and characterize the efficiency of hPSC differentiation to these regionally specific cell identities.

Neural dissociations in attitude strength: Distinct regions of cingulate cortex track ambivalence and certainty.

PubMed

Luttrell, Andrew; Stillman, Paul E; Hasinski, Adam E; Cunningham, William A

2016-04-01

People's behaviors are often guided by valenced responses to objects in the environment. Beyond positive and negative evaluations, attitudes research has documented the importance of attitude strength--qualities of an attitude that enhance or attenuate its impact and durability. Although neuroscience research has extensively investigated valence, little work exists on other related variables like metacognitive judgments about one's attitudes. It remains unclear, then, whether the various indicators of attitude strength represent a single underlying neural process or whether they reflect independent processes. To examine this, we used functional MRI (fMRI) to identify the neural correlates of attitude strength. Specifically, we focus on ambivalence and certainty, which represent metacognitive judgments that people can make about their evaluations. Although often correlated, prior neuroscience research suggests that these 2 attributes may have distinct neural underpinnings. We investigate this by having participants make evaluative judgments of visually presented words while undergoing fMRI. After scanning, participants rated the degree of ambivalence and certainty they felt regarding their attitudes toward each word. We found that these 2 judgments corresponded to distinct brain regions' activity during the process of evaluation. Ambivalence corresponded to activation in anterior cingulate cortex, dorsomedial prefrontal cortex, and posterior cingulate cortex. Certainty, however, corresponded to activation in unique areas of the precuneus/posterior cingulate cortex. These results support a model treating ambivalence and certainty as distinct, though related, attitude strength variables, and we discuss implications for both attitudes and neuroscience research. (c) 2016 APA, all rights reserved).

Regional estimation of groundwater arsenic concentrations through systematical dynamic-neural modeling

NASA Astrophysics Data System (ADS)

Chang, Fi-John; Chen, Pin-An; Liu, Chen-Wuing; Liao, Vivian Hsiu-Chuan; Liao, Chung-Min

2013-08-01

Arsenic (As) is an odorless semi-metal that occurs naturally in rock and soil, and As contamination in groundwater resources has become a serious threat to human health. Thus, assessing the spatial and temporal variability of As concentration is highly desirable, particularly in heavily As-contaminated areas. However, various difficulties may be encountered in the regional estimation of As concentration such as cost-intensive field monitoring, scarcity of field data, identification of important factors affecting As, over-fitting or poor estimation accuracy. This study develops a novel systematical dynamic-neural modeling (SDM) for effectively estimating regional As-contaminated water quality by using easily-measured water quality variables. To tackle the difficulties commonly encountered in regional estimation, the SDM comprises of a neural network and four statistical techniques: the Nonlinear Autoregressive with eXogenous input (NARX) network, Gamma test, cross-validation, Bayesian regularization method and indicator kriging (IK). For practical application, this study investigated a heavily As-contaminated area in Taiwan. The backpropagation neural network (BPNN) is adopted for comparison purpose. The results demonstrate that the NARX network (Root mean square error (RMSE): 95.11 μg l-1 for training; 106.13 μg l-1 for validation) outperforms the BPNN (RMSE: 121.54 μg l-1 for training; 143.37 μg l-1 for validation). The constructed SDM can provide reliable estimation (R2 > 0.89) of As concentration at ungauged sites based merely on three easily-measured water quality variables (Alk, Ca2+ and pH). In addition, risk maps under the threshold of the WHO drinking water standard (10 μg l-1) are derived by the IK to visually display the spatial and temporal variation of the As concentration in the whole study area at different time spans. The proposed SDM can be practically applied with satisfaction to the regional estimation in study areas of interest and the

Transcriptional response of Hoxb genes to retinoid signalling is regionally restricted along the neural tube rostrocaudal axis.

PubMed

Carucci, Nicoletta; Cacci, Emanuele; Nisi, Paola S; Licursi, Valerio; Paul, Yu-Lee; Biagioni, Stefano; Negri, Rodolfo; Rugg-Gunn, Peter J; Lupo, Giuseppe

2017-04-01

During vertebrate neural development, positional information is largely specified by extracellular morphogens. Their distribution, however, is very dynamic due to the multiple roles played by the same signals in the developing and adult neural tissue. This suggests that neural progenitors are able to modify their competence to respond to morphogen signalling and autonomously maintain positional identities after their initial specification. In this work, we take advantage of in vitro culture systems of mouse neural stem/progenitor cells (NSPCs) to show that NSPCs isolated from rostral or caudal regions of the mouse neural tube are differentially responsive to retinoic acid (RA), a pivotal morphogen for the specification of posterior neural fates. Hoxb genes are among the best known RA direct targets in the neural tissue, yet we found that RA could promote their transcription only in caudal but not in rostral NSPCs. Correlating with these effects, key RA-responsive regulatory regions in the Hoxb cluster displayed opposite enrichment of activating or repressing histone marks in rostral and caudal NSPCs. Finally, RA was able to strengthen Hoxb chromatin activation in caudal NSPCs, but was ineffective on the repressed Hoxb chromatin of rostral NSPCs. These results suggest that the response of NSPCs to morphogen signalling across the rostrocaudal axis of the neural tube may be gated by the epigenetic configuration of target patterning genes, allowing long-term maintenance of intrinsic positional values in spite of continuously changing extrinsic signals.

Neural representation of emotion regulation goals.

PubMed

Morawetz, Carmen; Bode, Stefan; Baudewig, Juergen; Jacobs, Arthur M; Heekeren, Hauke R

2016-02-01

The use of top-down cognitive control mechanisms to regulate emotional responses as circumstances change is critical for mental and physical health. Several theoretical models of emotion regulation have been postulated; it remains unclear, however, in which brain regions emotion regulation goals (e.g., the downregulation of fear) are represented. Here, we examined the neural mechanisms of regulating emotion using fMRI and identified brain regions representing reappraisal goals. Using a multimethodological analysis approach, combining standard activation-based and pattern-information analyses, we identified a distributed network of lateral frontal, temporal, and parietal regions implicated in reappraisal and within it, a core system that represents reappraisal goals in an abstract, stimulus-independent fashion. Within this core system, the neural pattern-separability in a subset of regions including the left inferior frontal gyrus, middle temporal gyrus, and inferior parietal lobe was related to the success in emotion regulation. Those brain regions might link the prefrontal control regions with the subcortical affective regions. Given the strong association of this subsystem with inner speech functions and semantic memory, we conclude that those cognitive mechanisms may be used for orchestrating emotion regulation. Hum Brain Mapp 37:600-620, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Response of neural reward regions to food cues in autism spectrum disorders

PubMed Central

2012-01-01

Background One hypothesis for the social deficits that characterize autism spectrum disorders (ASD) is diminished neural reward response to social interaction and attachment. Prior research using established monetary reward paradigms as a test of non-social reward to compare with social reward may involve confounds in the ability of individuals with ASD to utilize symbolic representation of money and the abstraction required to interpret monetary gains. Thus, a useful addition to our understanding of neural reward circuitry in ASD includes a characterization of the neural response to primary rewards. Method We asked 17 children with ASD and 18 children without ASD to abstain from eating for at least four hours before an MRI scan in which they viewed images of high-calorie foods. We assessed the neural reward network for increases in the blood oxygenation level dependent (BOLD) signal in response to the food images Results We found very similar patterns of increased BOLD signal to these images in the two groups; both groups showed increased BOLD signal in the bilateral amygdala, as well as in the nucleus accumbens, orbitofrontal cortex, and insula. Direct group comparisons revealed that the ASD group showed a stronger response to food cues in bilateral insula along the anterior-posterior gradient and in the anterior cingulate cortex than the control group, whereas there were no neural reward regions that showed higher activation for controls than for ASD. Conclusion These results suggest that neural response to primary rewards is not diminished but in fact shows an aberrant enhancement in children with ASD. PMID:22958533

Use of artificial neural networks to identify the origin of green macroalgae

NASA Astrophysics Data System (ADS)

Żbikowski, Radosław

2011-08-01

This study demonstrates application of artificial neural networks (ANNs) for identifying the origin of green macroalgae ( Enteromorpha sp. and Cladophora sp.) according to their concentrations of Cd, Cu, Ni, Zn, Mn, Pb, Na, Ca, K and Mg. Earlier studies confirmed that algae can be used for biomonitoring surveys of metal contaminants in coastal areas of the Southern Baltic. The same data sets were classified with the use of different structures of radial basis function (RBF) and multilayer perceptron (MLP) networks. The selected networks were able to classify the samples according to their geographical origin, i.e. Southern Baltic, Gulf of Gdańsk and Vistula Lagoon. Additionally in the case of macroalgae from the Gulf of Gdańsk, the networks enabled the discrimination of samples according to areas of contrasting levels of pollution. Hence this study shows that artificial neural networks can be a valuable tool in biomonitoring studies.

Genetic dissection of neural circuits underlying sexually dimorphic social behaviours

PubMed Central

Bayless, Daniel W.; Shah, Nirao M.

2016-01-01

The unique hormonal, genetic and epigenetic environments of males and females during development and adulthood shape the neural circuitry of the brain. These differences in neural circuitry result in sex-typical displays of social behaviours such as mating and aggression. Like other neural circuits, those underlying sex-typical social behaviours weave through complex brain regions that control a variety of diverse behaviours. For this reason, the functional dissection of neural circuits underlying sex-typical social behaviours has proved to be difficult. However, molecularly discrete neuronal subpopulations can be identified in the heterogeneous brain regions that control sex-typical social behaviours. In addition, the actions of oestrogens and androgens produce sex differences in gene expression within these brain regions, thereby highlighting the neuronal subpopulations most likely to control sexually dimorphic social behaviours. These conditions permit the implementation of innovative genetic approaches that, in mammals, are most highly advanced in the laboratory mouse. Such approaches have greatly advanced our understanding of the functional significance of sexually dimorphic neural circuits in the brain. In this review, we discuss the neural circuitry of sex-typical social behaviours in mice while highlighting the genetic technical innovations that have advanced the field. PMID:26833830

Neural Representations of Emotion Are Organized around Abstract Event Features

PubMed Central

Skerry, Amy E.; Saxe, Rebecca

2016-01-01

Summary Research on emotion attribution has tended to focus on the perception of overt expressions of at most five or six basic emotions. However, our ability to identify others' emotional states is not limited to perception of these canonical expressions. Instead, we make fine-grained inferences about what others feel based on the situations they encounter, relying on knowledge of the eliciting conditions for different emotions. In the present research, we provide convergent behavioral and neural evidence concerning the representations underlying these concepts. First, we find that patterns of activity in mentalizing regions contain information about subtle emotional distinctions conveyed through verbal descriptions of eliciting situations. Second, we identify a space of abstract situation features that well captures the emotion discriminations subjects make behaviorally and show that this feature space outperforms competing models in capturing the similarity space of neural patterns in these regions. Together, the data suggest that our knowledge of others' emotions is abstract and high dimensional, that brain regions selective for mental state reasoning support relatively subtle distinctions between emotion concepts, and that the neural representations in these regions are not reducible to more primitive affective dimensions such as valence and arousal. PMID:26212878

Application of artificial neural networks to identify equilibration in computer simulations

NASA Astrophysics Data System (ADS)

Leibowitz, Mitchell H.; Miller, Evan D.; Henry, Michael M.; Jankowski, Eric

2017-11-01

Determining which microstates generated by a thermodynamic simulation are representative of the ensemble for which sampling is desired is a ubiquitous, underspecified problem. Artificial neural networks are one type of machine learning algorithm that can provide a reproducible way to apply pattern recognition heuristics to underspecified problems. Here we use the open-source TensorFlow machine learning library and apply it to the problem of identifying which hypothetical observation sequences from a computer simulation are “equilibrated” and which are not. We generate training populations and test populations of observation sequences with embedded linear and exponential correlations. We train a two-neuron artificial network to distinguish the correlated and uncorrelated sequences. We find that this simple network is good enough for > 98% accuracy in identifying exponentially-decaying energy trajectories from molecular simulations.

Deinterlacing using modular neural network

NASA Astrophysics Data System (ADS)

Woo, Dong H.; Eom, Il K.; Kim, Yoo S.

2004-05-01

Deinterlacing is the conversion process from the interlaced scan to progressive one. While many previous algorithms that are based on weighted-sum cause blurring in edge region, deinterlacing using neural network can reduce the blurring through recovering of high frequency component by learning process, and is found robust to noise. In proposed algorithm, input image is divided into edge and smooth region, and then, to each region, one neural network is assigned. Through this process, each neural network learns only patterns that are similar, therefore it makes learning more effective and estimation more accurate. But even within each region, there are various patterns such as long edge and texture in edge region. To solve this problem, modular neural network is proposed. In proposed modular neural network, two modules are combined in output node. One is for low frequency feature of local area of input image, and the other is for high frequency feature. With this structure, each modular neural network can learn different patterns with compensating for drawback of counterpart. Therefore it can adapt to various patterns within each region effectively. In simulation, the proposed algorithm shows better performance compared with conventional deinterlacing methods and single neural network method.

Neural Correlates of Math Gains Vary Depending on Parental Socioeconomic Status (SES)

PubMed Central

Demir-Lira, Özlem Ece; Prado, Jérôme; Booth, James R.

2016-01-01

We used functional magnetic resonance imaging (fMRI) to examine the neural predictors of math development, and asked whether these predictors vary as a function of parental socioeconomic status (SES) in children ranging in age from 8 to 13 years. We independently localized brain regions subserving verbal versus spatial processing in order to characterize relations between activation in these regions during an arithmetic task and long-term change in math skill (up to 3 years). Neural predictors of math gains encompassed brain regions subserving both verbal and spatial processing, but the relation between relative reliance on these regions and math skill growth varied depending on parental SES. Activity in an area of the left inferior frontal gyrus (IFG) identified by the verbal localizer was related to greater growth in math skill at the higher end of the SES continuum, but lesser improvements at the lower end. Activity in an area of the right superior parietal cortex identified by the spatial localizer was related to greater growth in math skill at the lower end of the SES continuum, but lesser improvements at the higher end. Results highlight early neural mechanisms as possible neuromarkers of long-term arithmetic learning and suggest that neural predictors of math gains vary with parental SES. PMID:27378987

Acute stress evokes sexually dimorphic, stressor-specific patterns of neural activation across multiple limbic brain regions in adult rats.

PubMed

Sood, Ankit; Chaudhari, Karina; Vaidya, Vidita A

2018-03-01

Stress enhances the risk for psychiatric disorders such as anxiety and depression. Stress responses vary across sex and may underlie the heightened vulnerability to psychopathology in females. Here, we examined the influence of acute immobilization stress (AIS) and a two-day short-term forced swim stress (FS) on neural activation in multiple cortical and subcortical brain regions, implicated as targets of stress and in the regulation of neuroendocrine stress responses, in male and female rats using Fos as a neural activity marker. AIS evoked a sex-dependent pattern of neural activation within the cingulate and infralimbic subdivisions of the medial prefrontal cortex (mPFC), lateral septum (LS), habenula, and hippocampal subfields. The degree of neural activation in the mPFC, LS, and habenula was higher in males. Female rats exhibited reduced Fos positive cell numbers in the dentate gyrus hippocampal subfield, an effect not observed in males. We addressed whether the sexually dimorphic neural activation pattern noted following AIS was also observed with the short-term stress of FS. In the paraventricular nucleus of the hypothalamus and the amygdala, FS similar to AIS resulted in robust increases in neural activation in both sexes. The pattern of neural activation evoked by FS was distinct across sexes, with a heightened neural activation noted in the prelimbic mPFC subdivision and hippocampal subfields in females and differed from the pattern noted with AIS. This indicates that the sex differences in neural activation patterns observed within stress-responsive brain regions are dependent on the nature of stressor experience.

Forecasting solar proton event with artificial neural network

NASA Astrophysics Data System (ADS)

Gong, J.; Wang, J.; Xue, B.; Liu, S.; Zou, Z.

Solar proton event (SPE), relatively rare but popular in solar maximum, can bring hazard situation to spacecraft. As a special event, SPE always accompanies flare, which is also called proton flare. To produce such an eruptive event, large amount energy must be accumulated within the active region. So we can investigate the character of the active region and its evolving trend, together with other such as cm radio emission and soft X-ray background to evaluate the potential of SEP in chosen area. In order to summarize the omen of SPEs in the active regions behind the observed parameters, we employed AI technology. Full connecting neural network was chosen to fulfil this job. After constructing the network, we train it with 13 parameters that was able to exhibit the character of active regions and their evolution trend. More than 80 sets of event parameter were defined to teach the neural network to identify whether an active region was potential of SPE. Then we test this model with a data base consisting SPE and non-SPE cases that was not used to train the neural network. The result showed that 75% of the choice by the model was right.

Regional differences in the expression of laminin isoforms during mouse neural tube development

PubMed Central

Copp, Andrew J.; Carvalho, Rita; Wallace, Adam; Sorokin, Lydia; Sasaki, Takako; Greene, Nicholas D.E.; Ybot-Gonzalez, Patricia

2013-01-01

Many significant human birth defects originate around the time of neural tube closure or early during post-closure nervous system development. For example, failure of the neural tube to close generates anencephaly and spina bifida, faulty cell cycle progression is implicated in primary microcephaly, while defective migration of neuroblasts can lead to neuronal migration disorders such as lissencephaly. At the stage of neural tube closure, basement membranes are becoming organised around the neuroepithelium, and beneath the adjacent non-neural surface ectoderm. While there is circumstantial evidence to implicate basement membrane dynamics in neural tube and surface ectodermal development, we have an incomplete understanding of the molecular composition of basement membranes at this stage. In the present study, we examined the developing basement membranes of the mouse embryo at mid-gestation (embryonic day 9.5), with particular reference to laminin composition. We performed in situ hybridization to detect the mRNAs of all eleven individual laminin chains, and immunohistochemistry to identify which laminin chains are present in the basement membranes. From this information, we inferred the likely laminin variants and their tissues of origin: that is, whether a given basement membrane laminin is contributed by epithelium, mesenchyme, or both. Our findings reveal major differences in basement composition along the body axis, with the rostral neural tube (at mandibular arch and heart levels) exhibiting many distinct laminin variants, while the lumbar level where the neural tube is just closing shows a much simpler laminin profile. Moreover, there appears to be a marked difference in the extent to which the mesenchyme contributes laminin variants to the basement membrane, with potential contribution of several laminins rostrally, but no contribution caudally. This information paves the way towards a mechanistic analysis of basement membrane laminin function during early

Identifying the neural substrates of intrinsic motivation during task performance.

PubMed

Lee, Woogul; Reeve, Johnmarshall

2017-10-01

Intrinsic motivation is the inherent tendency to seek out novelty and challenge, to explore and investigate, and to stretch and extend one's capacities. When people imagine performing intrinsically motivating tasks, they show heightened anterior insular cortex (AIC) activity. To fully explain the neural system of intrinsic motivation, however, requires assessing neural activity while people actually perform intrinsically motivating tasks (i.e., while answering curiosity-inducing questions or solving competence-enabling anagrams). Using event-related functional magnetic resonance imaging, we found that the neural system of intrinsic motivation involves not only AIC activity, but also striatum activity and, further, AIC-striatum functional interactions. These findings suggest that subjective feelings of intrinsic satisfaction (associated with AIC activations), reward processing (associated with striatum activations), and their interactions underlie the actual experience of intrinsic motivation. These neural findings are consistent with the conceptualization of intrinsic motivation as the pursuit and satisfaction of subjective feelings (interest and enjoyment) as intrinsic rewards.

Efficient airport detection using region-based fully convolutional neural networks

NASA Astrophysics Data System (ADS)

Xin, Peng; Xu, Yuelei; Zhang, Xulei; Ma, Shiping; Li, Shuai; Lv, Chao

2018-04-01

This paper presents a model for airport detection using region-based fully convolutional neural networks. To achieve fast detection with high accuracy, we shared the conv layers between the region proposal procedure and the airport detection procedure and used graphics processing units (GPUs) to speed up the training and testing time. For lack of labeled data, we transferred the convolutional layers of ZF net pretrained by ImageNet to initialize the shared convolutional layers, then we retrained the model using the alternating optimization training strategy. The proposed model has been tested on an airport dataset consisting of 600 images. Experiments show that the proposed method can distinguish airports in our dataset from similar background scenes almost real-time with high accuracy, which is much better than traditional methods.

Regional Neural Response Differences in the Determination of Faces or Houses Positioned in a Wide Visual Field

PubMed Central

Wu, Jinglong; Chen, Kewei; Imajyo, Satoshi; Ohno, Seiichiro; Kanazawa, Susumu

2013-01-01

In human visual cortex, the primary visual cortex (V1) is considered to be essential for visual information processing; the fusiform face area (FFA) and parahippocampal place area (PPA) are considered as face-selective region and places-selective region, respectively. Recently, a functional magnetic resonance imaging (fMRI) study showed that the neural activity ratios between V1 and FFA were constant as eccentricities increasing in central visual field. However, in wide visual field, the neural activity relationships between V1 and FFA or V1 and PPA are still unclear. In this work, using fMRI and wide-view present system, we tried to address this issue by measuring neural activities in V1, FFA and PPA for the images of faces and houses aligning in 4 eccentricities and 4 meridians. Then, we further calculated ratio relative to V1 (RRV1) as comparing the neural responses amplitudes in FFA or PPA with those in V1. We found V1, FFA, and PPA showed significant different neural activities to faces and houses in 3 dimensions of eccentricity, meridian, and region. Most importantly, the RRV1s in FFA and PPA also exhibited significant differences in 3 dimensions. In the dimension of eccentricity, both FFA and PPA showed smaller RRV1s at central position than those at peripheral positions. In meridian dimension, both FFA and PPA showed larger RRV1s at upper vertical positions than those at lower vertical positions. In the dimension of region, FFA had larger RRV1s than PPA. We proposed that these differential RRV1s indicated FFA and PPA might have different processing strategies for encoding the wide field visual information from V1. These different processing strategies might depend on the retinal position at which faces or houses are typically observed in daily life. We posited a role of experience in shaping the information processing strategies in the ventral visual cortex. PMID:23991147

Neural representations of emotion are organized around abstract event features.

PubMed

Skerry, Amy E; Saxe, Rebecca

2015-08-03

Research on emotion attribution has tended to focus on the perception of overt expressions of at most five or six basic emotions. However, our ability to identify others' emotional states is not limited to perception of these canonical expressions. Instead, we make fine-grained inferences about what others feel based on the situations they encounter, relying on knowledge of the eliciting conditions for different emotions. In the present research, we provide convergent behavioral and neural evidence concerning the representations underlying these concepts. First, we find that patterns of activity in mentalizing regions contain information about subtle emotional distinctions conveyed through verbal descriptions of eliciting situations. Second, we identify a space of abstract situation features that well captures the emotion discriminations subjects make behaviorally and show that this feature space outperforms competing models in capturing the similarity space of neural patterns in these regions. Together, the data suggest that our knowledge of others' emotions is abstract and high dimensional, that brain regions selective for mental state reasoning support relatively subtle distinctions between emotion concepts, and that the neural representations in these regions are not reducible to more primitive affective dimensions such as valence and arousal. Copyright © 2015 Elsevier Ltd. All rights reserved.

An ensemble of dynamic neural network identifiers for fault detection and isolation of gas turbine engines.

PubMed

Amozegar, M; Khorasani, K

2016-04-01

In this paper, a new approach for Fault Detection and Isolation (FDI) of gas turbine engines is proposed by developing an ensemble of dynamic neural network identifiers. For health monitoring of the gas turbine engine, its dynamics is first identified by constructing three separate or individual dynamic neural network architectures. Specifically, a dynamic multi-layer perceptron (MLP), a dynamic radial-basis function (RBF) neural network, and a dynamic support vector machine (SVM) are trained to individually identify and represent the gas turbine engine dynamics. Next, three ensemble-based techniques are developed to represent the gas turbine engine dynamics, namely, two heterogeneous ensemble models and one homogeneous ensemble model. It is first shown that all ensemble approaches do significantly improve the overall performance and accuracy of the developed system identification scheme when compared to each of the stand-alone solutions. The best selected stand-alone model (i.e., the dynamic RBF network) and the best selected ensemble architecture (i.e., the heterogeneous ensemble) in terms of their performances in achieving an accurate system identification are then selected for solving the FDI task. The required residual signals are generated by using both a single model-based solution and an ensemble-based solution under various gas turbine engine health conditions. Our extensive simulation studies demonstrate that the fault detection and isolation task achieved by using the residuals that are obtained from the dynamic ensemble scheme results in a significantly more accurate and reliable performance as illustrated through detailed quantitative confusion matrix analysis and comparative studies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Identifying parameter regions for multistationarity

PubMed Central

Conradi, Carsten; Mincheva, Maya; Wiuf, Carsten

2017-01-01

Mathematical modelling has become an established tool for studying the dynamics of biological systems. Current applications range from building models that reproduce quantitative data to identifying systems with predefined qualitative features, such as switching behaviour, bistability or oscillations. Mathematically, the latter question amounts to identifying parameter values associated with a given qualitative feature. We introduce a procedure to partition the parameter space of a parameterized system of ordinary differential equations into regions for which the system has a unique or multiple equilibria. The procedure is based on the computation of the Brouwer degree, and it creates a multivariate polynomial with parameter depending coefficients. The signs of the coefficients determine parameter regions with and without multistationarity. A particular strength of the procedure is the avoidance of numerical analysis and parameter sampling. The procedure consists of a number of steps. Each of these steps might be addressed algorithmically using various computer programs and available software, or manually. We demonstrate our procedure on several models of gene transcription and cell signalling, and show that in many cases we obtain a complete partitioning of the parameter space with respect to multistationarity. PMID:28972969

Multimodal neural correlates of cognitive control in the Human Connectome Project.

PubMed

Lerman-Sinkoff, Dov B; Sui, Jing; Rachakonda, Srinivas; Kandala, Sridhar; Calhoun, Vince D; Barch, Deanna M

2017-12-01

Cognitive control is a construct that refers to the set of functions that enable decision-making and task performance through the representation of task states, goals, and rules. The neural correlates of cognitive control have been studied in humans using a wide variety of neuroimaging modalities, including structural MRI, resting-state fMRI, and task-based fMRI. The results from each of these modalities independently have implicated the involvement of a number of brain regions in cognitive control, including dorsal prefrontal cortex, and frontal parietal and cingulo-opercular brain networks. However, it is not clear how the results from a single modality relate to results in other modalities. Recent developments in multimodal image analysis methods provide an avenue for answering such questions and could yield more integrated models of the neural correlates of cognitive control. In this study, we used multiset canonical correlation analysis with joint independent component analysis (mCCA + jICA) to identify multimodal patterns of variation related to cognitive control. We used two independent cohorts of participants from the Human Connectome Project, each of which had data from four imaging modalities. We replicated the findings from the first cohort in the second cohort using both independent and predictive analyses. The independent analyses identified a component in each cohort that was highly similar to the other and significantly correlated with cognitive control performance. The replication by prediction analyses identified two independent components that were significantly correlated with cognitive control performance in the first cohort and significantly predictive of performance in the second cohort. These components identified positive relationships across the modalities in neural regions related to both dynamic and stable aspects of task control, including regions in both the frontal-parietal and cingulo-opercular networks, as well as regions

Neural correlates of eating disorders: translational potential

PubMed Central

McAdams, Carrie J; Smith, Whitney

2015-01-01

Eating disorders are complex and serious psychiatric illnesses whose etiology includes psychological, biological, and social factors. Treatment of eating disorders is challenging as there are few evidence-based treatments and limited understanding of the mechanisms that result in sustained recovery. In the last 20 years, we have begun to identify neural pathways that are altered in eating disorders. Consideration of how these pathways may contribute to an eating disorder can provide an understanding of expected responses to treatments. Eating disorder behaviors include restrictive eating, compulsive overeating, and purging behaviors after eating. Eating disorders are associated with changes in many neural systems. In this targeted review, we focus on three cognitive processes associated with neurocircuitry differences in subjects with eating disorders such as reward, decision-making, and social behavior. We briefly examine how each of these systems function in healthy people, using Neurosynth meta-analysis to identify key regions commonly implicated in these circuits. We review the evidence for disruptions of these regions and systems in eating disorders. Finally, we describe psychiatric and psychological treatments that are likely to function by impacting these regions. PMID:26767185

Single neural adaptive controller and neural network identifier based on PSO algorithm for spherical actuators with 3D magnet array

NASA Astrophysics Data System (ADS)

Yan, Liang; Zhang, Lu; Zhu, Bo; Zhang, Jingying; Jiao, Zongxia

2017-10-01

Permanent magnet spherical actuator (PMSA) is a multi-variable featured and inter-axis coupled nonlinear system, which unavoidably compromises its motion control implementation. Uncertainties such as external load and friction torque of ball bearing and manufacturing errors also influence motion performance significantly. Therefore, the objective of this paper is to propose a controller based on a single neural adaptive (SNA) algorithm and a neural network (NN) identifier optimized with a particle swarm optimization (PSO) algorithm to improve the motion stability of PMSA with three-dimensional magnet arrays. The dynamic model and computed torque model are formulated for the spherical actuator, and a dynamic decoupling control algorithm is developed. By utilizing the global-optimization property of the PSO algorithm, the NN identifier is trained to avoid locally optimal solution and achieve high-precision compensations to uncertainties. The employment of the SNA controller helps to reduce the effect of compensation errors and convert the system to a stable one, even if there is difference between the compensations and uncertainties due to external disturbances. A simulation model is established, and experiments are conducted on the research prototype to validate the proposed control algorithm. The amplitude of the parameter perturbation is set to 5%, 10%, and 15%, respectively. The strong robustness of the proposed hybrid algorithm is validated by the abundant simulation data. It shows that the proposed algorithm can effectively compensate the influence of uncertainties and eliminate the effect of inter-axis couplings of the spherical actuator.

Distinct Neural-Functional Effects of Treatments With Selective Serotonin Reuptake Inhibitors, Electroconvulsive Therapy, and Transcranial Magnetic Stimulation and Their Relations to Regional Brain Function in Major Depression: A Meta-analysis.

PubMed

Chau, David T; Fogelman, Phoebe; Nordanskog, Pia; Drevets, Wayne C; Hamilton, J Paul

2017-05-01

Functional neuroimaging studies have examined the neural substrates of treatments for major depressive disorder (MDD). Low sample size and methodological heterogeneity, however, undermine the generalizability of findings from individual studies. We conducted a meta-analysis to identify reliable neural changes resulting from different modes of treatment for MDD and compared them with each other and with reliable neural functional abnormalities observed in depressed versus control samples. We conducted a meta-analysis of studies reporting changes in brain activity (e.g., as indexed by positron emission tomography) following treatments with selective serotonin reuptake inhibitors (SSRIs), electroconvulsive therapy (ECT), or transcranial magnetic stimulation. Additionally, we examined the statistical reliability of overlap among thresholded meta-analytic SSRI, ECT, and transcranial magnetic stimulation maps as well as a map of abnormal neural function in MDD. Our meta-analysis revealed that 1) SSRIs decrease activity in the anterior insula, 2) ECT decreases activity in central nodes of the default mode network, 3) transcranial magnetic stimulation does not result in reliable neural changes, and 4) regional effects of these modes of treatment do not significantly overlap with each other or with regions showing reliable functional abnormality in MDD. SSRIs and ECT produce neurally distinct effects relative to each other and to the functional abnormalities implicated in depression. These treatments therefore may exert antidepressant effects by diminishing neural functions not implicated in depression but that nonetheless impact mood. We discuss how the distinct neural changes resulting from SSRIs and ECT can account for both treatment effects and side effects from these therapies as well as how to individualize these treatments. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Improved system identification using artificial neural networks and analysis of individual differences in responses of an identified neuron.

PubMed

Costalago Meruelo, Alicia; Simpson, David M; Veres, Sandor M; Newland, Philip L

2016-03-01

Mathematical modelling is used routinely to understand the coding properties and dynamics of responses of neurons and neural networks. Here we analyse the effectiveness of Artificial Neural Networks (ANNs) as a modelling tool for motor neuron responses. We used ANNs to model the synaptic responses of an identified motor neuron, the fast extensor motor neuron, of the desert locust in response to displacement of a sensory organ, the femoral chordotonal organ, which monitors movements of the tibia relative to the femur of the leg. The aim of the study was threefold: first to determine the potential value of ANNs as tools to model and investigate neural networks, second to understand the generalisation properties of ANNs across individuals and to different input signals and third, to understand individual differences in responses of an identified neuron. A metaheuristic algorithm was developed to design the ANN architectures. The performance of the models generated by the ANNs was compared with those generated through previous mathematical models of the same neuron. The results suggest that ANNs are significantly better than LNL and Wiener models in predicting specific neural responses to Gaussian White Noise, but not significantly different when tested with sinusoidal inputs. They are also able to predict responses of the same neuron in different individuals irrespective of which animal was used to develop the model, although notable differences between some individuals were evident. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Neural Crest Origins of the Neck and Shoulder

PubMed Central

Matsuoka, Toshiyuki; Ahlberg, Per E.; Kessaris, Nicoletta; Iannarelli, Palma; Dennehy, Ulla; Richardson, William D.; McMahon, Andrew P.; Koentges, Georgy

2005-01-01

Summary The neck and shoulder region of vertebrates has undergone a complex evolutionary history. In order to identify its underlying mechanisms we map the destinations of embryonic neural crest and mesodermal stem cells using novel Cre-recombinase mediated transgenesis. The single-cell resolution of this genetic labelling reveals cryptic cell boundaries traversing seemingly homogeneous skeleton of neck and shoulders. Within this complex assembly of bones and muscles we discern a precise code of connectivity that mesenchymal stem cells of neural crest and mesodermal origin both obey as they form muscle scaffolds. Neural crest anchors the head onto the anterior lining of the shoulder girdle, while a Hox gene controlled mesoderm links trunk muscles to the posterior neck and shoulder skeleton. The skeleton that we identify as neural crest is specifically affected in human Klippel-Feil syndrome, Sprengel’s deformity and Arnold-Chiari I/II malformation, providing first insights into their likely aetiology. We identify genes involved in the cellular modularity of neck and shoulder skeleton and propose a new methodology for determining skeletal homologies that is based on muscle attachments. This has allowed us to trace the whereabouts of the cleithrum, the major shoulder bone of extinct land vertebrate ancestors which appears to survive as the scapular spine in living mammals. PMID:16034409

Identifying environmental risk factors for human neural tube defects before and after folic acid supplementation

PubMed Central

Liao, Yilan; Wang, Jinfeng; Li, Xinhu; Guo, Yaoqin; Zheng, Xiaoying

2009-01-01

Background Birth defects are a major cause of infant mortality and disability in many parts of the world. Neural tube defects (NTDs) are one of the most common types of birth defects. In 2001, the Chinese population and family planning commission initiated a national intervention program for the prevention of birth defects. A key step in the program was the introduction of folic acid supplementation. Of interest in the present study was to determine whether folic acid supplementation has the same protective effect on NTDs under various geographical and socioeconomic conditions within the Chinese population and the nature in which the influence of environmental factors varied after folic acid supplementation. Methods In this study, Heshun was selected as the region of interest as a surrogate for helping to answer some of the questions raised in this study on the impact of the intervention program. Spatial filtering in combination with GIS software was used to detect annual potential clusters from 1998 to 2005 in Heshun, and Kruskal-wallis test and multivariate regression were applied to identify the environmental risk factors for NTDs among various regions. Results In 1998, a significant (p < 0.100) NTDs cluster was detected in the west of Heshun. After folic acid supplementation, the significant clusters gradually moved from west to east. However, during the study period, most of the clusters appeared in the middle region of Heshun where more than 95 percent of the coal mines of Heshun are located. For the analysis, buffer regions of the coal mine zone were built in a GIS environment. It was found that the correlations between environmental risk factors and NTDs vary among the buffer regions. Conclusion This suggests that the government needs to adapt the intervention measures according to local conditions. More attention needs to be paid to the poor and to people living in areas near coal mines. PMID:19835574

A Common Neural Code for Perceived and Inferred Emotion

PubMed Central

Saxe, Rebecca

2014-01-01

Although the emotions of other people can often be perceived from overt reactions (e.g., facial or vocal expressions), they can also be inferred from situational information in the absence of observable expressions. How does the human brain make use of these diverse forms of evidence to generate a common representation of a target's emotional state? In the present research, we identify neural patterns that correspond to emotions inferred from contextual information and find that these patterns generalize across different cues from which an emotion can be attributed. Specifically, we use functional neuroimaging to measure neural responses to dynamic facial expressions with positive and negative valence and to short animations in which the valence of a character's emotion could be identified only from the situation. Using multivoxel pattern analysis, we test for regions that contain information about the target's emotional state, identifying representations specific to a single stimulus type and representations that generalize across stimulus types. In regions of medial prefrontal cortex (MPFC), a classifier trained to discriminate emotional valence for one stimulus (e.g., animated situations) could successfully discriminate valence for the remaining stimulus (e.g., facial expressions), indicating a representation of valence that abstracts away from perceptual features and generalizes across different forms of evidence. Moreover, in a subregion of MPFC, this neural representation generalized to trials involving subjectively experienced emotional events, suggesting partial overlap in neural responses to attributed and experienced emotions. These data provide a step toward understanding how the brain transforms stimulus-bound inputs into abstract representations of emotion. PMID:25429141

Identifying autism from neural representations of social interactions: neurocognitive markers of autism.

PubMed

Just, Marcel Adam; Cherkassky, Vladimir L; Buchweitz, Augusto; Keller, Timothy A; Mitchell, Tom M

2014-01-01

Autism is a psychiatric/neurological condition in which alterations in social interaction (among other symptoms) are diagnosed by behavioral psychiatric methods. The main goal of this study was to determine how the neural representations and meanings of social concepts (such as to insult) are altered in autism. A second goal was to determine whether these alterations can serve as neurocognitive markers of autism. The approach is based on previous advances in fMRI analysis methods that permit (a) the identification of a concept, such as the thought of a physical object, from its fMRI pattern, and (b) the ability to assess the semantic content of a concept from its fMRI pattern. These factor analysis and machine learning methods were applied to the fMRI activation patterns of 17 adults with high-functioning autism and matched controls, scanned while thinking about 16 social interactions. One prominent neural representation factor that emerged (manifested mainly in posterior midline regions) was related to self-representation, but this factor was present only for the control participants, and was near-absent in the autism group. Moreover, machine learning algorithms classified individuals as autistic or control with 97% accuracy from their fMRI neurocognitive markers. The findings suggest that psychiatric alterations of thought can begin to be biologically understood by assessing the form and content of the altered thought's underlying brain activation patterns.

Identifying Autism from Neural Representations of Social Interactions: Neurocognitive Markers of Autism

PubMed Central

Just, Marcel Adam; Cherkassky, Vladimir L.; Buchweitz, Augusto; Keller, Timothy A.; Mitchell, Tom M.

2014-01-01

Autism is a psychiatric/neurological condition in which alterations in social interaction (among other symptoms) are diagnosed by behavioral psychiatric methods. The main goal of this study was to determine how the neural representations and meanings of social concepts (such as to insult) are altered in autism. A second goal was to determine whether these alterations can serve as neurocognitive markers of autism. The approach is based on previous advances in fMRI analysis methods that permit (a) the identification of a concept, such as the thought of a physical object, from its fMRI pattern, and (b) the ability to assess the semantic content of a concept from its fMRI pattern. These factor analysis and machine learning methods were applied to the fMRI activation patterns of 17 adults with high-functioning autism and matched controls, scanned while thinking about 16 social interactions. One prominent neural representation factor that emerged (manifested mainly in posterior midline regions) was related to self-representation, but this factor was present only for the control participants, and was near-absent in the autism group. Moreover, machine learning algorithms classified individuals as autistic or control with 97% accuracy from their fMRI neurocognitive markers. The findings suggest that psychiatric alterations of thought can begin to be biologically understood by assessing the form and content of the altered thought’s underlying brain activation patterns. PMID:25461818

Using c-Jun to identify fear extinction learning-specific patterns of neural activity that are affected by single prolonged stress.

PubMed

Knox, Dayan; Stanfield, Briana R; Staib, Jennifer M; David, Nina P; DePietro, Thomas; Chamness, Marisa; Schneider, Elizabeth K; Keller, Samantha M; Lawless, Caroline

2018-04-02

Neural circuits via which stress leads to disruptions in fear extinction is often explored in animal stress models. Using the single prolonged stress (SPS) model of post traumatic stress disorder and the immediate early gene (IEG) c-Fos as a measure of neural activity, we previously identified patterns of neural activity through which SPS disrupts extinction retention. However, none of these stress effects were specific to fear or extinction learning and memory. C-Jun is another IEG that is sometimes regulated in a different manner to c-Fos and could be used to identify emotional learning/memory specific patterns of neural activity that are sensitive to SPS. Animals were either fear conditioned (CS-fear) or presented with CSs only (CS-only) then subjected to extinction training and testing. C-Jun was then assayed within neural substrates critical for extinction memory. Inhibited c-Jun levels in the hippocampus (Hipp) and enhanced functional connectivity between the ventromedial prefrontal cortex (vmPFC) and basolateral amygdala (BLA) during extinction training was disrupted by SPS in the CS-fear group only. As a result, these effects were specific to emotional learning/memory. SPS also disrupted inhibited Hipp c-Jun levels, enhanced BLA c-Jun levels, and altered functional connectivity among the vmPFC, BLA, and Hipp during extinction testing in SPS rats in the CS-fear and CS-only groups. As a result, these effects were not specific to emotional learning/memory. Our findings suggest that SPS disrupts neural activity specific to extinction memory, but may also disrupt the retention of fear extinction by mechanisms that do not involve emotional learning/memory. Copyright © 2017 Elsevier B.V. All rights reserved.

Neural representations of the concepts in simple sentences: Concept activation prediction and context effects.

PubMed

Just, Marcel Adam; Wang, Jing; Cherkassky, Vladimir L

2017-08-15

Although it has been possible to identify individual concepts from a concept's brain activation pattern, there have been significant obstacles to identifying a proposition from its fMRI signature. Here we demonstrate the ability to decode individual prototype sentences from readers' brain activation patterns, by using theory-driven regions of interest and semantic properties. It is possible to predict the fMRI brain activation patterns evoked by propositions and words which are entirely new to the model with reliably above-chance rank accuracy. The two core components implemented in the model that reflect the theory were the choice of intermediate semantic features and the brain regions associated with the neurosemantic dimensions. This approach also predicts the neural representation of object nouns across participants, studies, and sentence contexts. Moreover, we find that the neural representation of an agent-verb-object proto-sentence is more accurately characterized by the neural signatures of its components as they occur in a similar context than by the neural signatures of these components as they occur in isolation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Classification of bifurcations regions in IVOCT images using support vector machine and artificial neural network models

NASA Astrophysics Data System (ADS)

Porto, C. D. N.; Costa Filho, C. F. F.; Macedo, M. M. G.; Gutierrez, M. A.; Costa, M. G. F.

2017-03-01

Studies in intravascular optical coherence tomography (IV-OCT) have demonstrated the importance of coronary bifurcation regions in intravascular medical imaging analysis, as plaques are more likely to accumulate in this region leading to coronary disease. A typical IV-OCT pullback acquires hundreds of frames, thus developing an automated tool to classify the OCT frames as bifurcation or non-bifurcation can be an important step to speed up OCT pullbacks analysis and assist automated methods for atherosclerotic plaque quantification. In this work, we evaluate the performance of two state-of-the-art classifiers, SVM and Neural Networks in the bifurcation classification task. The study included IV-OCT frames from 9 patients. In order to improve classification performance, we trained and tested the SVM with different parameters by means of a grid search and different stop criteria were applied to the Neural Network classifier: mean square error, early stop and regularization. Different sets of features were tested, using feature selection techniques: PCA, LDA and scalar feature selection with correlation. Training and test were performed in sets with a maximum of 1460 OCT frames. We quantified our results in terms of false positive rate, true positive rate, accuracy, specificity, precision, false alarm, f-measure and area under ROC curve. Neural networks obtained the best classification accuracy, 98.83%, overcoming the results found in literature. Our methods appear to offer a robust and reliable automated classification of OCT frames that might assist physicians indicating potential frames to analyze. Methods for improving neural networks generalization have increased the classification performance.

Molecular regionalization of the developing amphioxus neural tube challenges major partitions of the vertebrate brain.

PubMed

Albuixech-Crespo, Beatriz; López-Blanch, Laura; Burguera, Demian; Maeso, Ignacio; Sánchez-Arrones, Luisa; Moreno-Bravo, Juan Antonio; Somorjai, Ildiko; Pascual-Anaya, Juan; Puelles, Eduardo; Bovolenta, Paola; Garcia-Fernàndez, Jordi; Puelles, Luis; Irimia, Manuel; Ferran, José Luis

2017-04-01

All vertebrate brains develop following a common Bauplan defined by anteroposterior (AP) and dorsoventral (DV) subdivisions, characterized by largely conserved differential expression of gene markers. However, it is still unclear how this Bauplan originated during evolution. We studied the relative expression of 48 genes with key roles in vertebrate neural patterning in a representative amphioxus embryonic stage. Unlike nonchordates, amphioxus develops its central nervous system (CNS) from a neural plate that is homologous to that of vertebrates, allowing direct topological comparisons. The resulting genoarchitectonic model revealed that the amphioxus incipient neural tube is unexpectedly complex, consisting of several AP and DV molecular partitions. Strikingly, comparison with vertebrates indicates that the vertebrate thalamus, pretectum, and midbrain domains jointly correspond to a single amphioxus region, which we termed Di-Mesencephalic primordium (DiMes). This suggests that these domains have a common developmental and evolutionary origin, as supported by functional experiments manipulating secondary organizers in zebrafish and mice.

Molecular regionalization of the developing amphioxus neural tube challenges major partitions of the vertebrate brain

PubMed Central

Albuixech-Crespo, Beatriz; Maeso, Ignacio; Sánchez-Arrones, Luisa; Moreno-Bravo, Juan Antonio; Somorjai, Ildiko; Pascual-Anaya, Juan; Puelles, Eduardo; Bovolenta, Paola; Garcia-Fernàndez, Jordi; Puelles, Luis; Ferran, José Luis

2017-01-01

All vertebrate brains develop following a common Bauplan defined by anteroposterior (AP) and dorsoventral (DV) subdivisions, characterized by largely conserved differential expression of gene markers. However, it is still unclear how this Bauplan originated during evolution. We studied the relative expression of 48 genes with key roles in vertebrate neural patterning in a representative amphioxus embryonic stage. Unlike nonchordates, amphioxus develops its central nervous system (CNS) from a neural plate that is homologous to that of vertebrates, allowing direct topological comparisons. The resulting genoarchitectonic model revealed that the amphioxus incipient neural tube is unexpectedly complex, consisting of several AP and DV molecular partitions. Strikingly, comparison with vertebrates indicates that the vertebrate thalamus, pretectum, and midbrain domains jointly correspond to a single amphioxus region, which we termed Di-Mesencephalic primordium (DiMes). This suggests that these domains have a common developmental and evolutionary origin, as supported by functional experiments manipulating secondary organizers in zebrafish and mice. PMID:28422959

Neural activity in the reward-related brain regions predicts implicit self-esteem: A novel validity test of psychological measures using neuroimaging.

PubMed

Izuma, Keise; Kennedy, Kate; Fitzjohn, Alexander; Sedikides, Constantine; Shibata, Kazuhisa

2018-03-01

Self-esteem, arguably the most important attitudes an individual possesses, has been a premier research topic in psychology for more than a century. Following a surge of interest in implicit attitude measures in the 90s, researchers have tried to assess self-esteem implicitly to circumvent the influence of biases inherent in explicit measures. However, the validity of implicit self-esteem measures remains elusive. Critical tests are often inconclusive, as the validity of such measures is examined in the backdrop of imperfect behavioral measures. To overcome this serious limitation, we tested the neural validity of the most widely used implicit self-esteem measure, the implicit association test (IAT). Given the conceptualization of self-esteem as attitude toward the self, and neuroscience findings that the reward-related brain regions represent an individual's attitude or preference for an object when viewing its image, individual differences in implicit self-esteem should be associated with neural signals in the reward-related regions during passive-viewing of self-face (the most obvious representation of the self). Using multi-voxel pattern analysis (MVPA) on functional MRI (fMRI) data, we demonstrate that the neural signals in the reward-related regions were robustly associated with implicit (but not explicit) self-esteem, thus providing unique evidence for the neural validity of the self-esteem IAT. In addition, both implicit and explicit self-esteem were related, although differently, to neural signals in regions involved in self-processing. Our finding highlights the utility of neuroscience methods in addressing fundamental psychological questions and providing unique insights into important psychological constructs. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Region stability analysis and tracking control of memristive recurrent neural network.

PubMed

Bao, Gang; Zeng, Zhigang; Shen, Yanjun

2018-02-01

Memristor is firstly postulated by Leon Chua and realized by Hewlett-Packard (HP) laboratory. Research results show that memristor can be used to simulate the synapses of neurons. This paper presents a class of recurrent neural network with HP memristors. Firstly, it shows that memristive recurrent neural network has more compound dynamics than the traditional recurrent neural network by simulations. Then it derives that n dimensional memristive recurrent neural network is composed of [Formula: see text] sub neural networks which do not have a common equilibrium point. By designing the tracking controller, it can make memristive neural network being convergent to the desired sub neural network. At last, two numerical examples are given to verify the validity of our result. Copyright © 2017 Elsevier Ltd. All rights reserved.

Exploring the spatio-temporal neural basis of face learning

PubMed Central

Yang, Ying; Xu, Yang; Jew, Carol A.; Pyles, John A.; Kass, Robert E.; Tarr, Michael J.

2017-01-01

Humans are experts at face individuation. Although previous work has identified a network of face-sensitive regions and some of the temporal signatures of face processing, as yet, we do not have a clear understanding of how such face-sensitive regions support learning at different time points. To study the joint spatio-temporal neural basis of face learning, we trained subjects to categorize two groups of novel faces and recorded their neural responses using magnetoencephalography (MEG) throughout learning. A regression analysis of neural responses in face-sensitive regions against behavioral learning curves revealed significant correlations with learning in the majority of the face-sensitive regions in the face network, mostly between 150–250 ms, but also after 300 ms. However, the effect was smaller in nonventral regions (within the superior temporal areas and prefrontal cortex) than that in the ventral regions (within the inferior occipital gyri (IOG), midfusiform gyri (mFUS) and anterior temporal lobes). A multivariate discriminant analysis also revealed that IOG and mFUS, which showed strong correlation effects with learning, exhibited significant discriminability between the two face categories at different time points both between 150–250 ms and after 300 ms. In contrast, the nonventral face-sensitive regions, where correlation effects with learning were smaller, did exhibit some significant discriminability, but mainly after 300 ms. In sum, our findings indicate that early and recurring temporal components arising from ventral face-sensitive regions are critically involved in learning new faces. PMID:28570739

Exploring the spatio-temporal neural basis of face learning.

PubMed

Yang, Ying; Xu, Yang; Jew, Carol A; Pyles, John A; Kass, Robert E; Tarr, Michael J

2017-06-01

Humans are experts at face individuation. Although previous work has identified a network of face-sensitive regions and some of the temporal signatures of face processing, as yet, we do not have a clear understanding of how such face-sensitive regions support learning at different time points. To study the joint spatio-temporal neural basis of face learning, we trained subjects to categorize two groups of novel faces and recorded their neural responses using magnetoencephalography (MEG) throughout learning. A regression analysis of neural responses in face-sensitive regions against behavioral learning curves revealed significant correlations with learning in the majority of the face-sensitive regions in the face network, mostly between 150-250 ms, but also after 300 ms. However, the effect was smaller in nonventral regions (within the superior temporal areas and prefrontal cortex) than that in the ventral regions (within the inferior occipital gyri (IOG), midfusiform gyri (mFUS) and anterior temporal lobes). A multivariate discriminant analysis also revealed that IOG and mFUS, which showed strong correlation effects with learning, exhibited significant discriminability between the two face categories at different time points both between 150-250 ms and after 300 ms. In contrast, the nonventral face-sensitive regions, where correlation effects with learning were smaller, did exhibit some significant discriminability, but mainly after 300 ms. In sum, our findings indicate that early and recurring temporal components arising from ventral face-sensitive regions are critically involved in learning new faces.

Development of the posterior neural tube in human embryos.

PubMed

Saitsu, Hirotomo; Yamada, Shigehito; Uwabe, Chigako; Ishibashi, Makoto; Shiota, Kohei

2004-12-01

Development of the posterior neural tube (PNT) in human embryos is a complicated process that involves both primary and secondary neurulation. Because normal development of the PNT is not fully understood, pathogenesis of spinal neural tube defects remains elusive. To clarify the mechanism of PNT development, we histologically examined 20 human embryos around the stage of posterior neuropore closure and found that the developing PNT can be divided into three parts: 1) the most rostral region, which corresponds to the posterior part of the primary neural tube, 2) the junctional region of the primary and secondary neural tubes, and 3) the caudal region, which emerges from the neural cord. In the junctional region, the axially-condensed mesenchyme (AM) intervened between the neural plate/tube and the notochord at the stage of posterior neuropore closure, while the notochord was directly attached to the neural plate/tube in the most rostral region. A single cavity was found to be formed in the AM as the presumptive luminal surface cells were radially aligned in the junctional region prior to the formation of the neural cord. The single cavity was continuous with the central cavity of the primary neural tube. In contrast, multiple or isolated cavities were frequently observed in the caudal region of the PNT. Our observation suggests that the junctional region of the PNT is distinct from other regions in terms of the relationship with the notochord and the mode of cavitation during secondary neurulation.

Identifying Jets Using Artifical Neural Networks

NASA Astrophysics Data System (ADS)

Rosand, Benjamin; Caines, Helen; Checa, Sofia

2017-09-01

We investigate particle jet interactions with the Quark Gluon Plasma (QGP) using artificial neural networks modeled on those used in computer image recognition. We create jet images by binning jet particles into pixels and preprocessing every image. We analyzed the jets with a Multi-layered maxout network and a convolutional network. We demonstrate each network's effectiveness in differentiating simulated quenched jets from unquenched jets, and we investigate the method that the network uses to discriminate among different quenched jet simulations. Finally, we develop a greater understanding of the physics behind quenched jets by investigating what the network learnt as well as its effectiveness in differentiating samples. Yale College Freshman Summer Research Fellowship in the Sciences and Engineering.

Distributed Neural Processing Predictors of Multi-dimensional Properties of Affect

PubMed Central

Bush, Keith A.; Inman, Cory S.; Hamann, Stephan; Kilts, Clinton D.; James, G. Andrew

2017-01-01

Recent evidence suggests that emotions have a distributed neural representation, which has significant implications for our understanding of the mechanisms underlying emotion regulation and dysregulation as well as the potential targets available for neuromodulation-based emotion therapeutics. This work adds to this evidence by testing the distribution of neural representations underlying the affective dimensions of valence and arousal using representational models that vary in both the degree and the nature of their distribution. We used multi-voxel pattern classification (MVPC) to identify whole-brain patterns of functional magnetic resonance imaging (fMRI)-derived neural activations that reliably predicted dimensional properties of affect (valence and arousal) for visual stimuli viewed by a normative sample (n = 32) of demographically diverse, healthy adults. Inter-subject leave-one-out cross-validation showed whole-brain MVPC significantly predicted (p < 0.001) binarized normative ratings of valence (positive vs. negative, 59% accuracy) and arousal (high vs. low, 56% accuracy). We also conducted group-level univariate general linear modeling (GLM) analyses to identify brain regions whose response significantly differed for the contrasts of positive versus negative valence or high versus low arousal. Multivoxel pattern classifiers using voxels drawn from all identified regions of interest (all-ROIs) exhibited mixed performance; arousal was predicted significantly better than chance but worse than the whole-brain classifier, whereas valence was not predicted significantly better than chance. Multivoxel classifiers derived using individual ROIs generally performed no better than chance. Although performance of the all-ROI classifier improved with larger ROIs (generated by relaxing the clustering threshold), performance was still poorer than the whole-brain classifier. These findings support a highly distributed model of neural processing for the affective

Identifying regional opportunities for accelerated timber managemnet

Treesearch

David A. Gansner; Joseph E. Barnard; Samuel F. Gingrich; Samuel F. Gingrich

1973-01-01

Describes a procedure for identifying regional opportunities for accelerated timber management and demonstrates its application. Results provide a basis for rational choices among alternative management strategies and permit meaningful micro- and macro-evaluations of treatment response.

A common neural code for perceived and inferred emotion.

PubMed

Skerry, Amy E; Saxe, Rebecca

2014-11-26

Although the emotions of other people can often be perceived from overt reactions (e.g., facial or vocal expressions), they can also be inferred from situational information in the absence of observable expressions. How does the human brain make use of these diverse forms of evidence to generate a common representation of a target's emotional state? In the present research, we identify neural patterns that correspond to emotions inferred from contextual information and find that these patterns generalize across different cues from which an emotion can be attributed. Specifically, we use functional neuroimaging to measure neural responses to dynamic facial expressions with positive and negative valence and to short animations in which the valence of a character's emotion could be identified only from the situation. Using multivoxel pattern analysis, we test for regions that contain information about the target's emotional state, identifying representations specific to a single stimulus type and representations that generalize across stimulus types. In regions of medial prefrontal cortex (MPFC), a classifier trained to discriminate emotional valence for one stimulus (e.g., animated situations) could successfully discriminate valence for the remaining stimulus (e.g., facial expressions), indicating a representation of valence that abstracts away from perceptual features and generalizes across different forms of evidence. Moreover, in a subregion of MPFC, this neural representation generalized to trials involving subjectively experienced emotional events, suggesting partial overlap in neural responses to attributed and experienced emotions. These data provide a step toward understanding how the brain transforms stimulus-bound inputs into abstract representations of emotion. Copyright © 2014 the authors 0270-6474/14/3315997-12$15.00/0.

Quantitative analysis of bristle number in Drosophila mutants identifies genes involved in neural development

NASA Technical Reports Server (NTRS)

Norga, Koenraad K.; Gurganus, Marjorie C.; Dilda, Christy L.; Yamamoto, Akihiko; Lyman, Richard F.; Patel, Prajal H.; Rubin, Gerald M.; Hoskins, Roger A.; Mackay, Trudy F.; Bellen, Hugo J.

2003-01-01

BACKGROUND: The identification of the function of all genes that contribute to specific biological processes and complex traits is one of the major challenges in the postgenomic era. One approach is to employ forward genetic screens in genetically tractable model organisms. In Drosophila melanogaster, P element-mediated insertional mutagenesis is a versatile tool for the dissection of molecular pathways, and there is an ongoing effort to tag every gene with a P element insertion. However, the vast majority of P element insertion lines are viable and fertile as homozygotes and do not exhibit obvious phenotypic defects, perhaps because of the tendency for P elements to insert 5' of transcription units. Quantitative genetic analysis of subtle effects of P element mutations that have been induced in an isogenic background may be a highly efficient method for functional genome annotation. RESULTS: Here, we have tested the efficacy of this strategy by assessing the extent to which screening for quantitative effects of P elements on sensory bristle number can identify genes affecting neural development. We find that such quantitative screens uncover an unusually large number of genes that are known to function in neural development, as well as genes with yet uncharacterized effects on neural development, and novel loci. CONCLUSIONS: Our findings establish the use of quantitative trait analysis for functional genome annotation through forward genetics. Similar analyses of quantitative effects of P element insertions will facilitate our understanding of the genes affecting many other complex traits in Drosophila.

Mapping face categorization in the human ventral occipitotemporal cortex with direct neural intracranial recordings.

PubMed

Rossion, Bruno; Jacques, Corentin; Jonas, Jacques

2018-02-26

The neural basis of face categorization has been widely investigated with functional magnetic resonance imaging (fMRI), identifying a set of face-selective local regions in the ventral occipitotemporal cortex (VOTC). However, indirect recording of neural activity with fMRI is associated with large fluctuations of signal across regions, often underestimating face-selective responses in the anterior VOTC. While direct recording of neural activity with subdural grids of electrodes (electrocorticography, ECoG) or depth electrodes (stereotactic electroencephalography, SEEG) offers a unique opportunity to fill this gap in knowledge, these studies rather reveal widely distributed face-selective responses. Moreover, intracranial recordings are complicated by interindividual variability in neuroanatomy, ambiguity in definition, and quantification of responses of interest, as well as limited access to sulci with ECoG. Here, we propose to combine SEEG in large samples of individuals with fast periodic visual stimulation to objectively define, quantify, and characterize face categorization across the whole VOTC. This approach reconciles the wide distribution of neural face categorization responses with their (right) hemispheric and regional specialization, and reveals several face-selective regions in anterior VOTC sulci. We outline the challenges of this research program to understand the neural basis of face categorization and high-level visual recognition in general. © 2018 New York Academy of Sciences.

The mouse that roared: neural mechanisms of social hierarchy.

PubMed

Wang, Fei; Kessels, Helmut W; Hu, Hailan

2014-11-01

Hierarchical social status greatly influences behavior and health. Human and animal studies have begun to identify the brain regions that are activated during the formation of social hierarchies. They point towards the prefrontal cortex (PFC) as a central regulator, with brain areas upstream of the PFC conveying information about social status, and downstream brain regions executing dominance behavior. This review summarizes our current knowledge on the neural circuits that control social status. We discuss how the neural mechanisms for various types of dominance behavior can be studied in laboratory rodents by selective manipulation of neuronal activity or synaptic plasticity. These studies may help in finding the cause of social stress-related mental and physical health problems. Copyright © 2014 Elsevier Ltd. All rights reserved.

Age-Related Reversals in Neural Recruitment across Memory Retrieval Phases

PubMed Central

Kensinger, Elizabeth A.

2017-01-01

Over the last several decades, neuroimaging research has identified age-related neural changes that occur during cognitive tasks. These changes are used to help researchers identify functional changes that contribute to age-related impairments in cognitive performance. One commonly reported example of such a change is an age-related decrease in the recruitment of posterior sensory regions coupled with an increased recruitment of prefrontal regions across multiple cognitive tasks. This shift is often described as a compensatory recruitment of prefrontal regions due to age-related sensory-processing deficits in posterior regions. However, age is not only associated with spatial shifts in recruitment, but also with temporal shifts, in which younger and older adults recruit the same neural region at different points in a task trial. The current study examines the possible contribution of temporal modifications in the often-reported posterior–anterior shift. Participants, ages 19–85, took part in a memory retrieval task with a protracted retrieval trial consisting of an initial memory search phase and a subsequent detail elaboration phase. Age-related neural patterns during search replicated prior reports of age-related decreases in posterior recruitment and increases in prefrontal recruitment. However, during the later elaboration phase, the same posterior regions were associated with age-related increases in activation. Further, ROI and functional connectivity results suggest that these posterior regions function similarly during search and elaboration. These results suggest that the often-reported posterior–anterior shift may not reflect the inability of older adults to engage in sensory processing, but rather a change in when they recruit this processing. SIGNIFICANCE STATEMENT The current study provides evidence that the often-reported posterior–anterior shift in aging may not reflect a global sensory-processing deficit, as has often been reported, but

Regional shape-based feature space for segmenting biomedical images using neural networks

NASA Astrophysics Data System (ADS)

Sundaramoorthy, Gopal; Hoford, John D.; Hoffman, Eric A.

1993-07-01

In biomedical images, structure of interest, particularly the soft tissue structures, such as the heart, airways, bronchial and arterial trees often have grey-scale and textural characteristics similar to other structures in the image, making it difficult to segment them using only gray- scale and texture information. However, these objects can be visually recognized by their unique shapes and sizes. In this paper we discuss, what we believe to be, a novel, simple scheme for extracting features based on regional shapes. To test the effectiveness of these features for image segmentation (classification), we use an artificial neural network and a statistical cluster analysis technique. The proposed shape-based feature extraction algorithm computes regional shape vectors (RSVs) for all pixels that meet a certain threshold criteria. The distance from each such pixel to a boundary is computed in 8 directions (or in 26 directions for a 3-D image). Together, these 8 (or 26) values represent the pixel's (or voxel's) RSV. All RSVs from an image are used to train a multi-layered perceptron neural network which uses these features to 'learn' a suitable classification strategy. To clearly distinguish the desired object from other objects within an image, several examples from inside and outside the desired object are used for training. Several examples are presented to illustrate the strengths and weaknesses of our algorithm. Both synthetic and actual biomedical images are considered. Future extensions to this algorithm are also discussed.

Therapeutic physical exercise in neural injury: friend or foe?

PubMed

Park, Kanghui; Lee, Seunghoon; Hong, Yunkyung; Park, Sookyoung; Choi, Jeonghyun; Chang, Kyu-Tae; Kim, Joo-Heon; Hong, Yonggeun

2015-12-01

[Purpose] The intensity of therapeutic physical exercise is complex and sometimes controversial in patients with neural injuries. This review assessed whether therapeutic physical exercise is beneficial according to the intensity of the physical exercise. [Methods] The authors identified clinically or scientifically relevant articles from PubMed that met the inclusion criteria. [Results] Exercise training can improve body strength and lead to the physiological adaptation of skeletal muscles and the nervous system after neural injuries. Furthermore, neurophysiological and neuropathological studies show differences in the beneficial effects of forced therapeutic exercise in patients with severe or mild neural injuries. Forced exercise alters the distribution of muscle fiber types in patients with neural injuries. Based on several animal studies, forced exercise may promote functional recovery following cerebral ischemia via signaling molecules in ischemic brain regions. [Conclusions] This review describes several types of therapeutic forced exercise and the controversy regarding the therapeutic effects in experimental animals versus humans with neural injuries. This review also provides a therapeutic strategy for physical therapists that grades the intensity of forced exercise according to the level of neural injury.

Anomalous neural circuit function in schizophrenia during a virtual Morris water task.

PubMed

Folley, Bradley S; Astur, Robert; Jagannathan, Kanchana; Calhoun, Vince D; Pearlson, Godfrey D

2010-02-15

Previous studies have reported learning and navigation impairments in schizophrenia patients during virtual reality allocentric learning tasks. The neural bases of these deficits have not been explored using functional MRI despite well-explored anatomic characterization of these paradigms in non-human animals. Our objective was to characterize the differential distributed neural circuits involved in virtual Morris water task performance using independent component analysis (ICA) in schizophrenia patients and controls. Additionally, we present behavioral data in order to derive relationships between brain function and performance, and we have included a general linear model-based analysis in order to exemplify the incremental and differential results afforded by ICA. Thirty-four individuals with schizophrenia and twenty-eight healthy controls underwent fMRI scanning during a block design virtual Morris water task using hidden and visible platform conditions. Independent components analysis was used to deconstruct neural contributions to hidden and visible platform conditions for patients and controls. We also examined performance variables, voxel-based morphometry and hippocampal subparcellation, and regional BOLD signal variation. Independent component analysis identified five neural circuits. Mesial temporal lobe regions, including the hippocampus, were consistently task-related across conditions and groups. Frontal, striatal, and parietal circuits were recruited preferentially during the visible condition for patients, while frontal and temporal lobe regions were more saliently recruited by controls during the hidden platform condition. Gray matter concentrations and BOLD signal in hippocampal subregions were associated with task performance in controls but not patients. Patients exhibited impaired performance on the hidden and visible conditions of the task, related to negative symptom severity. While controls showed coupling between neural circuits, regional

Identifying the integrated neural networks involved in capsaicin-induced pain using fMRI in awake TRPV1 knockout and wild-type rats

PubMed Central

Yee, Jason R.; Kenkel, William; Caccaviello, John C.; Gamber, Kevin; Simmons, Phil; Nedelman, Mark; Kulkarni, Praveen; Ferris, Craig F.

2015-01-01

In the present study, we used functional MRI in awake rats to investigate the pain response that accompanies intradermal injection of capsaicin into the hindpaw. To this end, we used BOLD imaging together with a 3D segmented, annotated rat atlas and computational analysis to identify the integrated neural circuits involved in capsaicin-induced pain. The specificity of the pain response to capsaicin was tested in a transgenic model that contains a biallelic deletion of the gene encoding for the transient receptor potential cation channel subfamily V member 1 (TRPV1). Capsaicin is an exogenous ligand for the TRPV1 receptor, and in wild-type rats, activated the putative pain neural circuit. In addition, capsaicin-treated wild-type rats exhibited activation in brain regions comprising the Papez circuit and habenular system, systems that play important roles in the integration of emotional information, and learning and memory of aversive information, respectively. As expected, capsaicin administration to TRPV1-KO rats failed to elicit the robust BOLD activation pattern observed in wild-type controls. However, the intradermal injection of formalin elicited a significant activation of the putative pain pathway as represented by such areas as the anterior cingulate, somatosensory cortex, parabrachial nucleus, and periaqueductal gray. Notably, comparison of neural responses to capsaicin in wild-type vs. knock-out rats uncovered evidence that capsaicin may function in an antinociceptive capacity independent of TRPV1 signaling. Our data suggest that neuroimaging of pain in awake, conscious animals has the potential to inform the neurobiological basis of full and integrated perceptions of pain. PMID:25745388

Forecasting Flare Activity Using Deep Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Hernandez, T.

2017-12-01

Current operational flare forecasting relies on human morphological analysis of active regions and the persistence of solar flare activity through time (i.e. that the Sun will continue to do what it is doing right now: flaring or remaining calm). In this talk we present the results of applying deep Convolutional Neural Networks (CNNs) to the problem of solar flare forecasting. CNNs operate by training a set of tunable spatial filters that, in combination with neural layer interconnectivity, allow CNNs to automatically identify significant spatial structures predictive for classification and regression problems. We will start by discussing the applicability and success rate of the approach, the advantages it has over non-automated forecasts, and how mining our trained neural network provides a fresh look into the mechanisms behind magnetic energy storage and release.

Isolating Discriminant Neural Activity in the Presence of Eye Movements and Concurrent Task Demands

PubMed Central

Touryan, Jon; Lawhern, Vernon J.; Connolly, Patrick M.; Bigdely-Shamlo, Nima; Ries, Anthony J.

2017-01-01

A growing number of studies use the combination of eye-tracking and electroencephalographic (EEG) measures to explore the neural processes that underlie visual perception. In these studies, fixation-related potentials (FRPs) are commonly used to quantify early and late stages of visual processing that follow the onset of each fixation. However, FRPs reflect a mixture of bottom-up (sensory-driven) and top-down (goal-directed) processes, in addition to eye movement artifacts and unrelated neural activity. At present there is little consensus on how to separate this evoked response into its constituent elements. In this study we sought to isolate the neural sources of target detection in the presence of eye movements and over a range of concurrent task demands. Here, participants were asked to identify visual targets (Ts) amongst a grid of distractor stimuli (Ls), while simultaneously performing an auditory N-back task. To identify the discriminant activity, we used independent components analysis (ICA) for the separation of EEG into neural and non-neural sources. We then further separated the neural sources, using a modified measure-projection approach, into six regions of interest (ROIs): occipital, fusiform, temporal, parietal, cingulate, and frontal cortices. Using activity from these ROIs, we identified target from non-target fixations in all participants at a level similar to other state-of-the-art classification techniques. Importantly, we isolated the time course and spectral features of this discriminant activity in each ROI. In addition, we were able to quantify the effect of cognitive load on both fixation-locked potential and classification performance across regions. Together, our results show the utility of a measure-projection approach for separating task-relevant neural activity into meaningful ROIs within more complex contexts that include eye movements. PMID:28736519

Identifying apple surface defects using principal components analysis and artifical neural networks

USDA-ARS?s Scientific Manuscript database

Artificial neural networks and principal components were used to detect surface defects on apples in near-infrared images. Neural networks were trained and tested on sets of principal components derived from columns of pixels from images of apples acquired at two wavelengths (740 nm and 950 nm). I...

10 CFR 72.98 - Identifying regions around an ISFSI or MRS site.

Code of Federal Regulations, 2012 CFR

2012-01-01

... WASTE Siting Evaluation Factors § 72.98 Identifying regions around an ISFSI or MRS site. (a) The... ISFSI or MRS must be identified. (b) The potential regional impact due to the construction, operation or decommissioning of the ISFSI or MRS must be identified. The extent of regional impacts must be determined on the...

10 CFR 72.98 - Identifying regions around an ISFSI or MRS site.

Code of Federal Regulations, 2011 CFR

2011-01-01

... WASTE Siting Evaluation Factors § 72.98 Identifying regions around an ISFSI or MRS site. (a) The... ISFSI or MRS must be identified. (b) The potential regional impact due to the construction, operation or decommissioning of the ISFSI or MRS must be identified. The extent of regional impacts must be determined on the...

Influence of neural adaptation on dynamics and equilibrium state of neural activities in a ring neural network

NASA Astrophysics Data System (ADS)

Takiyama, Ken

2017-12-01

How neural adaptation affects neural information processing (i.e. the dynamics and equilibrium state of neural activities) is a central question in computational neuroscience. In my previous works, I analytically clarified the dynamics and equilibrium state of neural activities in a ring-type neural network model that is widely used to model the visual cortex, motor cortex, and several other brain regions. The neural dynamics and the equilibrium state in the neural network model corresponded to a Bayesian computation and statistically optimal multiple information integration, respectively, under a biologically inspired condition. These results were revealed in an analytically tractable manner; however, adaptation effects were not considered. Here, I analytically reveal how the dynamics and equilibrium state of neural activities in a ring neural network are influenced by spike-frequency adaptation (SFA). SFA is an adaptation that causes gradual inhibition of neural activity when a sustained stimulus is applied, and the strength of this inhibition depends on neural activities. I reveal that SFA plays three roles: (1) SFA amplifies the influence of external input in neural dynamics; (2) SFA allows the history of the external input to affect neural dynamics; and (3) the equilibrium state corresponds to the statistically optimal multiple information integration independent of the existence of SFA. In addition, the equilibrium state in a ring neural network model corresponds to the statistically optimal integration of multiple information sources under biologically inspired conditions, independent of the existence of SFA.

The neural substrates of action identification.

PubMed

Marsh, Abigail A; Kozak, Megan N; Wegner, Daniel M; Reid, Marguerite E; Yu, Henry H; Blair, R J R

2010-12-01

Mentalization is the process by which an observer views a target as possessing higher cognitive faculties such as goals, intentions and desires. Mentalization can be assessed using action identification paradigms, in which observers choose mentalistic (goals-focused) or mechanistic (action-focused) descriptions of targets' actions. Neural structures that play key roles in inferring goals and intentions from others' observed or imagined actions include temporo-parietal junction, ventral premotor cortex and extrastriate body area. We hypothesized that these regions play a role in action identification as well. Data collected using functional magnetic resonance imaging (fMRI) confirmed our predictions that activity in ventral premotor cortex and middle temporal gyrus near the extrastriate body area varies both as a function of the valence of the target and the extent to which actions are identified as goal-directed. In addition, the inferior parietal lobule is preferentially engaged when participants identify the actions of mentalized targets. Functional connectivity analyses suggest support from other regions, including the medial prefrontal cortex and amygdala, during mentalization. We found correlations between action identification and Autism Quotient scores, suggesting that understanding the neural correlates of action identification may enhance our understanding of the underpinnings of essential social cognitive processes.

Neural circuits in anxiety and stress disorders: a focused review

PubMed Central

Duval, Elizabeth R; Javanbakht, Arash; Liberzon, Israel

2015-01-01

Anxiety and stress disorders are among the most prevalent neuropsychiatric disorders. In recent years, multiple studies have examined brain regions and networks involved in anxiety symptomatology in an effort to better understand the mechanisms involved and to develop more effective treatments. However, much remains unknown regarding the specific abnormalities and interactions between networks of regions underlying anxiety disorder presentations. We examined recent neuroimaging literature that aims to identify neural mechanisms underlying anxiety, searching for patterns of neural dysfunction that might be specific to different anxiety disorder categories. Across different anxiety and stress disorders, patterns of hyperactivation in emotion-generating regions and hypoactivation in prefrontal/regulatory regions are common in the literature. Interestingly, evidence of differential patterns is also emerging, such that within a spectrum of disorders ranging from more fear-based to more anxiety-based, greater involvement of emotion-generating regions is reported in panic disorder and specific phobia, and greater involvement of prefrontal regions is reported in generalized anxiety disorder and posttraumatic stress disorder. We summarize the pertinent literature and suggest areas for continued investigation. PMID:25670901

Current steering to activate targeted neural pathways during deep brain stimulation of the subthalamic region

PubMed Central

Chaturvedi, Ashutosh; Foutz, Thomas J.; McIntyre, Cameron C.

2012-01-01

Deep brain stimulation (DBS) has steadily evolved into an established surgical therapy for numerous neurological disorders, most notably Parkinson’s disease (PD). Traditional DBS technology relies on voltage-controlled stimulation with a single source; however, recent engineering advances are providing current-controlled devices with multiple independent sources. These new stimulators deliver constant current to the brain tissue, irrespective of impedance changes that occur around the electrode, and enable more specific steering of current towards targeted regions of interest. In this study, we examined the impact of current steering between multiple electrode contacts to directly activate three distinct neural populations in the subthalamic region commonly stimulated for the treatment of PD: projection neurons of the subthalamic nucleus (STN), globus pallidus internus (GPi) fibers of the lenticular fasiculus, and internal capsule (IC) fibers of passage. We used three-dimensional finite element electric field models, along with detailed multi-compartment cable models of the three neural populations to determine their activations using a wide range of stimulation parameter settings. Our results indicate that selective activation of neural populations largely depends on the location of the active electrode(s). Greater activation of the GPi and STN populations (without activating any side-effect related IC fibers) was achieved by current steering with multiple independent sources, compared to a single current source. Despite this potential advantage, it remains to be seen if these theoretical predictions result in a measurable clinical effect that outweighs the added complexity of the expanded stimulation parameter search space generated by the more flexible technology. PMID:22277548

40 CFR 255.24 - Procedure for identifying interstate regions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 24 2010-07-01 2010-07-01 false Procedure for identifying interstate regions. 255.24 Section 255.24 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SOLID... recommendation, the local consensus, or a neighboring Governor's recommendation is that an interstate region be...

Neural Correlates of the Encoding of Multimodal Contextual Features

ERIC Educational Resources Information Center

Gottlieb, Lauren J.; Wong, Jenny; de Chastelaine, Marianne; Rugg, Michael D.

2012-01-01

Functional magnetic resonance imaging (fMRI) was employed to identify neural regions engaged during the encoding of contextual features belonging to different modalities. Subjects studied objects that were presented to the left or right of fixation. Each object was paired with its name, spoken in either a male or a female voice. The test…

Neural overlap in processing music and speech

PubMed Central

Peretz, Isabelle; Vuvan, Dominique; Lagrois, Marie-Élaine; Armony, Jorge L.

2015-01-01

Neural overlap in processing music and speech, as measured by the co-activation of brain regions in neuroimaging studies, may suggest that parts of the neural circuitries established for language may have been recycled during evolution for musicality, or vice versa that musicality served as a springboard for language emergence. Such a perspective has important implications for several topics of general interest besides evolutionary origins. For instance, neural overlap is an important premise for the possibility of music training to influence language acquisition and literacy. However, neural overlap in processing music and speech does not entail sharing neural circuitries. Neural separability between music and speech may occur in overlapping brain regions. In this paper, we review the evidence and outline the issues faced in interpreting such neural data, and argue that converging evidence from several methodologies is needed before neural overlap is taken as evidence of sharing. PMID:25646513

Neural markers of loss aversion in resting-state brain activity.

PubMed

Canessa, Nicola; Crespi, Chiara; Baud-Bovy, Gabriel; Dodich, Alessandra; Falini, Andrea; Antonellis, Giulia; Cappa, Stefano F

2017-02-01

Neural responses in striatal, limbic and somatosensory brain regions track individual differences in loss aversion, i.e. the higher sensitivity to potential losses compared with equivalent gains in decision-making under risk. The engagement of structures involved in the processing of aversive stimuli and experiences raises a further question, i.e. whether the tendency to avoid losses rather than acquire gains represents a transient fearful overreaction elicited by choice-related information, or rather a stable component of one's own preference function, reflecting a specific pattern of neural activity. We tested the latter hypothesis by assessing in 57 healthy human subjects whether the relationship between behavioral and neural loss aversion holds at rest, i.e. when the BOLD signal is collected during 5minutes of cross-fixation in the absence of an explicit task. Within the resting-state networks highlighted by a spatial group Independent Component Analysis (gICA), we found a significant correlation between strength of activity and behavioral loss aversion in the left ventral striatum and right posterior insula/supramarginal gyrus, i.e. the very same regions displaying a pattern of neural loss aversion during explicit choices. Cross-study analyses confirmed that this correlation holds when voxels identified by gICA are used as regions of interest in task-related activity and vice versa. These results suggest that the individual degree of (neural) loss aversion represents a stable dimension of decision-making, which reflects in specific metrics of intrinsic brain activity at rest possibly modulating cortical excitability at choice. Copyright © 2016 Elsevier Inc. All rights reserved.

The active principle region of Buyang Huanwu decoction induced differentiation of bone marrow-derived mesenchymal stem cells into neural-like cells

PubMed Central

Zheng, Jinghui; Wan, Yi; Chi, Jianhuai; Shen, Dekai; Wu, Tingting; Li, Weimin; Du, Pengcheng

2012-01-01

The present study induced in vitro-cultured passage 4 bone marrow-derived mesenchymal stem cells to differentiate into neural-like cells with a mixture of alkaloid, polysaccharide, aglycone, glycoside, essential oils, and effective components of Buyang Huanwu decoction (active principle region of decoction for invigorating yang for recuperation). After 28 days, nestin and neuron-specific enolase were expressed in the cytoplasm. Reverse transcription-PCR and western blot analyses showed that nestin and neuron-specific enolase mRNA and protein expression was greater in the active principle region group compared with the original formula group. Results demonstrated that the active principle region of Buyang Huanwu decoction induced greater differentiation of rat bone marrow-derived mesenchymal stem cells into neural-like cells in vitro than the original Buyang Huanwu decoction formula. PMID:25806066

Soy sauce classification by geographic region and fermentation based on artificial neural network and genetic algorithm.

PubMed

Xu, Libin; Li, Yang; Xu, Ning; Hu, Yong; Wang, Chao; He, Jianjun; Cao, Yueze; Chen, Shigui; Li, Dongsheng

2014-12-24

This work demonstrated the possibility of using artificial neural networks to classify soy sauce from China. The aroma profiles of different soy sauce samples were differentiated using headspace solid-phase microextraction. The soy sauce samples were analyzed by gas chromatography-mass spectrometry, and 22 and 15 volatile aroma compounds were selected for sensitivity analysis to classify the samples by fermentation and geographic region, respectively. The 15 selected samples can be classified by fermentation and geographic region with a prediction success rate of 100%. Furans and phenols represented the variables with the greatest contribution in classifying soy sauce samples by fermentation and geographic region, respectively.

Altered Synchronizations among Neural Networks in Geriatric Depression.

PubMed

Wang, Lihong; Chou, Ying-Hui; Potter, Guy G; Steffens, David C

2015-01-01

Although major depression has been considered as a manifestation of discoordinated activity between affective and cognitive neural networks, only a few studies have examined the relationships among neural networks directly. Because of the known disconnection theory, geriatric depression could be a useful model in studying the interactions among different networks. In the present study, using independent component analysis to identify intrinsically connected neural networks, we investigated the alterations in synchronizations among neural networks in geriatric depression to better understand the underlying neural mechanisms. Resting-state fMRI data was collected from thirty-two patients with geriatric depression and thirty-two age-matched never-depressed controls. We compared the resting-state activities between the two groups in the default-mode, central executive, attention, salience, and affective networks as well as correlations among these networks. The depression group showed stronger activity than the controls in an affective network, specifically within the orbitofrontal region. However, unlike the never-depressed controls, geriatric depression group lacked synchronized/antisynchronized activity between the affective network and the other networks. Those depressed patients with lower executive function has greater synchronization between the salience network with the executive and affective networks. Our results demonstrate the effectiveness of the between-network analyses in examining neural models for geriatric depression.

Altered Synchronizations among Neural Networks in Geriatric Depression

PubMed Central

Wang, Lihong; Chou, Ying-Hui; Potter, Guy G.; Steffens, David C.

2015-01-01

Although major depression has been considered as a manifestation of discoordinated activity between affective and cognitive neural networks, only a few studies have examined the relationships among neural networks directly. Because of the known disconnection theory, geriatric depression could be a useful model in studying the interactions among different networks. In the present study, using independent component analysis to identify intrinsically connected neural networks, we investigated the alterations in synchronizations among neural networks in geriatric depression to better understand the underlying neural mechanisms. Resting-state fMRI data was collected from thirty-two patients with geriatric depression and thirty-two age-matched never-depressed controls. We compared the resting-state activities between the two groups in the default-mode, central executive, attention, salience, and affective networks as well as correlations among these networks. The depression group showed stronger activity than the controls in an affective network, specifically within the orbitofrontal region. However, unlike the never-depressed controls, geriatric depression group lacked synchronized/antisynchronized activity between the affective network and the other networks. Those depressed patients with lower executive function has greater synchronization between the salience network with the executive and affective networks. Our results demonstrate the effectiveness of the between-network analyses in examining neural models for geriatric depression. PMID:26180795

The Differential Role of Verbal and Spatial Working Memory in the Neural Basis of Arithmetic

PubMed Central

Demir, Özlem Ece; Prado, Jérôme; Booth, James R.

2014-01-01

We examine the relations of verbal and spatial WM ability to the neural bases of arithmetic in school-age children. We independently localize brain regions subserving verbal versus spatial representations. For multiplication, higher verbal WM ability is associated with greater recruitment of the left temporal cortex, identified by the verbal localizer. For multiplication and subtraction, higher spatial WM ability is associated with greater recruitment of right parietal cortex, identified by the spatial localizer. Depending on their WM ability, children engage different neural systems that manipulate different representations to solve arithmetic problems. PMID:25144257

Neural dynamics based on the recognition of neural fingerprints

PubMed Central

Carrillo-Medina, José Luis; Latorre, Roberto

2015-01-01

Experimental evidence has revealed the existence of characteristic spiking features in different neural signals, e.g., individual neural signatures identifying the emitter or functional signatures characterizing specific tasks. These neural fingerprints may play a critical role in neural information processing, since they allow receptors to discriminate or contextualize incoming stimuli. This could be a powerful strategy for neural systems that greatly enhances the encoding and processing capacity of these networks. Nevertheless, the study of information processing based on the identification of specific neural fingerprints has attracted little attention. In this work, we study (i) the emerging collective dynamics of a network of neurons that communicate with each other by exchange of neural fingerprints and (ii) the influence of the network topology on the self-organizing properties within the network. Complex collective dynamics emerge in the network in the presence of stimuli. Predefined inputs, i.e., specific neural fingerprints, are detected and encoded into coexisting patterns of activity that propagate throughout the network with different spatial organization. The patterns evoked by a stimulus can survive after the stimulation is over, which provides memory mechanisms to the network. The results presented in this paper suggest that neural information processing based on neural fingerprints can be a plausible, flexible, and powerful strategy. PMID:25852531

Neural overlap in processing music and speech.

PubMed

Peretz, Isabelle; Vuvan, Dominique; Lagrois, Marie-Élaine; Armony, Jorge L

2015-03-19

Neural overlap in processing music and speech, as measured by the co-activation of brain regions in neuroimaging studies, may suggest that parts of the neural circuitries established for language may have been recycled during evolution for musicality, or vice versa that musicality served as a springboard for language emergence. Such a perspective has important implications for several topics of general interest besides evolutionary origins. For instance, neural overlap is an important premise for the possibility of music training to influence language acquisition and literacy. However, neural overlap in processing music and speech does not entail sharing neural circuitries. Neural separability between music and speech may occur in overlapping brain regions. In this paper, we review the evidence and outline the issues faced in interpreting such neural data, and argue that converging evidence from several methodologies is needed before neural overlap is taken as evidence of sharing. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Functional overlap of top-down emotion regulation and generation: an fMRI study identifying common neural substrates between cognitive reappraisal and cognitively generated emotions.

PubMed

Otto, Benjamin; Misra, Supriya; Prasad, Aditya; McRae, Kateri

2014-09-01

One factor that influences the success of emotion regulation is the manner in which the regulated emotion was generated. Recent research has suggested that reappraisal, a top-down emotion regulation strategy, is more effective in decreasing self-reported negative affect when emotions were generated from the top-down, versus the bottom-up. On the basis of a process overlap framework, we hypothesized that the neural regions active during reappraisal would overlap more with emotions that were generated from the top-down, rather than from the bottom-up. In addition, we hypothesized that increased neural overlap between reappraisal and the history effects of top-down emotion generation would be associated with increased reappraisal success. The results of several analyses suggested that reappraisal and emotions that were generated from the top-down share a core network of prefrontal, temporal, and cingulate regions. This overlap is specific; no such overlap was observed between reappraisal and emotions that were generated in a bottom-up fashion. This network consists of regions previously implicated in linguistic processing, cognitive control, and self-relevant appraisals, which are processes thought to be crucial to both reappraisal and top-down emotion generation. Furthermore, individuals with high reappraisal success demonstrated greater neural overlap between reappraisal and the history of top-down emotion generation than did those with low reappraisal success. The overlap of these key regions, reflecting overlapping processes, provides an initial insight into the mechanism by which generation history may facilitate emotion regulation.

Neural signatures of experimentally induced flow experiences identified in a typical fMRI block design with BOLD imaging

PubMed Central

Keller, Johannes; Grön, Georg

2016-01-01

Previously, experimentally induced flow experiences have been demonstrated with perfusion imaging during activation blocks of 3 min length to accommodate with the putatively slowly evolving “mood” characteristics of flow. Here, we used functional magnetic resonance imaging (fMRI) in a sample of 23 healthy, male participants to investigate flow in the context of a typical fMRI block design with block lengths as short as 30 s. To induce flow, demands of arithmetic tasks were automatically and continuously adjusted to the individual skill level. Compared against conditions of boredom and overload, experience of flow was evident from individuals’ reported subjective experiences and changes in electrodermal activity. Neural activation was relatively increased during flow, particularly in the anterior insula, inferior frontal gyri, basal ganglia and midbrain. Relative activation decreases during flow were observed in medial prefrontal and posterior cingulate cortex, and in the medial temporal lobe including the amygdala. Present findings suggest that even in the context of comparably short activation blocks flow can be reliably experienced and is associated with changes in neural activation of brain regions previously described. Possible mechanisms of interacting brain regions are outlined, awaiting further investigation which should now be possible given the greater temporal resolution compared with previous perfusion imaging. PMID:26508774

Detection of white matter lesion regions in MRI using SLIC0 and convolutional neural network.

PubMed

Diniz, Pedro Henrique Bandeira; Valente, Thales Levi Azevedo; Diniz, João Otávio Bandeira; Silva, Aristófanes Corrêa; Gattass, Marcelo; Ventura, Nina; Muniz, Bernardo Carvalho; Gasparetto, Emerson Leandro

2018-04-19

White matter lesions are non-static brain lesions that have a prevalence rate up to 98% in the elderly population. Because they may be associated with several brain diseases, it is important that they are detected as soon as possible. Magnetic Resonance Imaging (MRI) provides three-dimensional data with the possibility to detect and emphasize contrast differences in soft tissues, providing rich information about the human soft tissue anatomy. However, the amount of data provided for these images is far too much for manual analysis/interpretation, representing a difficult and time-consuming task for specialists. This work presents a computational methodology capable of detecting regions of white matter lesions of the brain in MRI of FLAIR modality. The techniques highlighted in this methodology are SLIC0 clustering for candidate segmentation and convolutional neural networks for candidate classification. The methodology proposed here consists of four steps: (1) images acquisition, (2) images preprocessing, (3) candidates segmentation and (4) candidates classification. The methodology was applied on 91 magnetic resonance images provided by DASA, and achieved an accuracy of 98.73%, specificity of 98.77% and sensitivity of 78.79% with 0.005 of false positives, without any false positives reduction technique, in detection of white matter lesion regions. It is demonstrated the feasibility of the analysis of brain MRI using SLIC0 and convolutional neural network techniques to achieve success in detection of white matter lesions regions. Copyright © 2018. Published by Elsevier B.V.

Neural pathway in the right hemisphere underlies verbal insight problem solving.

PubMed

Zhao, Q; Zhou, Z; Xu, H; Fan, W; Han, L

2014-01-03

Verbal insight problem solving means to break mental sets, to select the novel semantic information and to form novel, task-related associations. Although previous studies have identified the brain regions associated with these key processes, the interaction among these regions during insight is still unclear. In the present study, we explored the functional connectivity between the key regions during solving Chinese 'chengyu' riddles by using event-related functional magnetic resonance imaging. Results showed that both insight and noninsight solutions activated the bilateral inferior frontal gyri, middle temporal gyri and hippocampi, and these regions constituted a frontal to temporal to hippocampal neural pathway. Compared with noninsight solution, insight solution had a stronger functional connectivity between the inferior frontal gyrus and middle temporal gyrus in the right hemisphere. Our study reveals the neural pathway of information processing during verbal insight problem solving, and supports the right-hemisphere advantage theory of insight. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.

Transcriptional Profiling of Hypoxic Neural Stem Cells Identifies Calcineurin-NFATc4 Signaling as a Major Regulator of Neural Stem Cell Biology

PubMed Central

Moreno, Marta; Fernández, Virginia; Monllau, Josep M.; Borrell, Víctor; Lerin, Carles; de la Iglesia, Núria

2015-01-01

Summary Neural stem cells (NSCs) reside in a hypoxic microenvironment within the brain. However, the crucial transcription factors (TFs) that regulate NSC biology under physiologic hypoxia are poorly understood. Here we have performed gene set enrichment analysis (GSEA) of microarray datasets from hypoxic versus normoxic NSCs with the aim of identifying pathways and TFs that are activated under oxygen concentrations mimicking normal brain tissue microenvironment. Integration of TF target (TFT) and pathway enrichment analysis identified the calcium-regulated TF NFATc4 as a major candidate to regulate hypoxic NSC functions. Nfatc4 expression was coordinately upregulated by top hypoxia-activated TFs, while NFATc4 target genes were enriched in hypoxic NSCs. Loss-of-function analyses further revealed that the calcineurin-NFATc4 signaling axis acts as a major regulator of NSC self-renewal and proliferation in vitro and in vivo by promoting the expression of TFs, including Id2, that contribute to the maintenance of the NSC state. PMID:26235896

Cognitive deficits caused by prefrontal cortical and hippocampal neural disinhibition.

PubMed

Bast, Tobias; Pezze, Marie; McGarrity, Stephanie

2017-10-01

We review recent evidence concerning the significance of inhibitory GABA transmission and of neural disinhibition, that is, deficient GABA transmission, within the prefrontal cortex and the hippocampus, for clinically relevant cognitive functions. Both regions support important cognitive functions, including attention and memory, and their dysfunction has been implicated in cognitive deficits characterizing neuropsychiatric disorders. GABAergic inhibition shapes cortico-hippocampal neural activity, and, recently, prefrontal and hippocampal neural disinhibition has emerged as a pathophysiological feature of major neuropsychiatric disorders, especially schizophrenia and age-related cognitive decline. Regional neural disinhibition, disrupting spatio-temporal control of neural activity and causing aberrant drive of projections, may disrupt processing within the disinhibited region and efferent regions. Recent studies in rats showed that prefrontal and hippocampal neural disinhibition (by local GABA antagonist microinfusion) dysregulates burst firing, which has been associated with important aspects of neural information processing. Using translational tests of clinically relevant cognitive functions, these studies showed that prefrontal and hippocampal neural disinhibition disrupts regional cognitive functions (including prefrontal attention and hippocampal memory function). Moreover, hippocampal neural disinhibition disrupted attentional performance, which does not require the hippocampus but requires prefrontal-striatal circuits modulated by the hippocampus. However, some prefrontal and hippocampal functions (including inhibitory response control) are spared by regional disinhibition. We consider conceptual implications of these findings, regarding the distinct relationships of distinct cognitive functions to prefrontal and hippocampal GABA tone and neural activity. Moreover, the findings support the proposition that prefrontal and hippocampal neural disinhibition

Angiogenesis in the Developing Spinal Cord: Blood Vessel Exclusion from Neural Progenitor Region Is Mediated by VEGF and Its Antagonists

PubMed Central

Takahashi, Teruaki; Takase, Yuta; Yoshino, Takashi; Saito, Daisuke; Tadokoro, Ryosuke; Takahashi, Yoshiko

2015-01-01

Blood vessels in the central nervous system supply a considerable amount of oxygen via intricate vascular networks. We studied how the initial vasculature of the spinal cord is formed in avian (chicken and quail) embryos. Vascular formation in the spinal cord starts by the ingression of intra-neural vascular plexus (INVP) from the peri-neural vascular plexus (PNVP) that envelops the neural tube. At the ventral region of the PNVP, the INVP grows dorsally in the neural tube, and we observed that these vessels followed the defined path at the interface between the medially positioned and undifferentiated neural progenitor zone and the laterally positioned differentiated zone. When the interface between these two zones was experimentally displaced, INVP faithfully followed a newly formed interface, suggesting that the growth path of the INVP is determined by surrounding neural cells. The progenitor zone expressed mRNA of vascular endothelial growth factor-A whereas its receptor VEGFR2 and FLT-1 (VEGFR1), a decoy for VEGF, were expressed in INVP. By manipulating the neural tube with either VEGF or the soluble form of FLT-1, we found that INVP grew in a VEGF-dependent manner, where VEGF signals appear to be fine-tuned by counteractions with anti-angiogenic activities including FLT-1 and possibly semaphorins. These results suggest that the stereotypic patterning of early INVP is achieved by interactions between these vessels and their surrounding neural cells, where VEGF and its antagonists play important roles. PMID:25585380

Surface electromyographic amplitude does not identify differences in neural drive to synergistic muscles.

PubMed

Martinez-Valdes, Eduardo; Negro, Francesco; Falla, Deborah; De Nunzio, Alessandro Marco; Farina, Dario

2018-04-01

Surface electromyographic (EMG) signal amplitude is typically used to compare the neural drive to muscles. We experimentally investigated this association by studying the motor unit (MU) behavior and action potentials in the vastus medialis (VM) and vastus lateralis (VL) muscles. Eighteen participants performed isometric knee extensions at four target torques [10, 30, 50, and 70% of the maximum torque (MVC)] while high-density EMG signals were recorded from the VM and VL. The absolute EMG amplitude was greater for VM than VL ( P < 0.001), whereas the EMG amplitude normalized with respect to MVC was greater for VL than VM ( P < 0.04). Because differences in EMG amplitude can be due to both differences in the neural drive and in the size of the MU action potentials, we indirectly inferred the neural drives received by the two muscles by estimating the synaptic inputs received by the corresponding motor neuron pools. For this purpose, we analyzed the increase in discharge rate from recruitment to target torque for motor units matched by recruitment threshold in the two muscles. This analysis indicated that the two muscles received similar levels of neural drive. Nonetheless, the size of the MU action potentials was greater for VM than VL ( P < 0.001), and this difference explained most of the differences in EMG amplitude between the two muscles (~63% of explained variance). These results indicate that EMG amplitude, even following normalization, does not reflect the neural drive to synergistic muscles. Moreover, absolute EMG amplitude is mainly explained by the size of MU action potentials. NEW & NOTEWORTHY Electromyographic (EMG) amplitude is widely used to compare indirectly the strength of neural drive received by synergistic muscles. However, there are no studies validating this approach with motor unit data. Here, we compared between-muscles differences in surface EMG amplitude and motor unit behavior. The results clarify the limitations of surface EMG to

Neural correlates of nesting behavior in zebra finches (Taeniopygia guttata)

PubMed Central

Hall, Zachary J.; Bertin, Marion; Bailey, Ida E.; Meddle, Simone L.; Healy, Susan D.

2014-01-01

Nest building in birds involves a behavioral sequence (nest material collection and deposition in the nest) that offers a unique model for addressing how the brain sequences motor actions. In this study, we identified brain regions involved in nesting behavior in male and female zebra finches (Taeniopygia guttata). We used Fos immunohistochemistry to quantify production of the immediate early gene protein product Fos (a molecular indicator of neuronal activity) in the brain correlated this expression with the variation in nesting behavior. Using this technique, we found that neural circuitry involved in motor sequencing, social behavior, reward and motivation were active during nesting. Within pairs of nesting birds, the number of times a male picked up or deposited nesting material and the amount of time a female spent in the nest explained the variation in Fos expression in the anterior motor pathway, social behavior network, and reward neural circuits. Identification of the brain regions that are involved in nesting enables us to begin studying the roles of motor sequencing, context, and reward in construction behavior at the neural level. PMID:24508238

10 CFR 72.98 - Identifying regions around an ISFSI or MRS site.

Code of Federal Regulations, 2014 CFR

2014-01-01

... regional extent of external phenomena, man-made or natural, that are used as a basis for the design of the ISFSI or MRS must be identified. (b) The potential regional impact due to the construction, operation or decommissioning of the ISFSI or MRS must be identified. The extent of regional impacts must be determined on the...

10 CFR 72.98 - Identifying regions around an ISFSI or MRS site.

Code of Federal Regulations, 2013 CFR

2013-01-01

... regional extent of external phenomena, man-made or natural, that are used as a basis for the design of the ISFSI or MRS must be identified. (b) The potential regional impact due to the construction, operation or decommissioning of the ISFSI or MRS must be identified. The extent of regional impacts must be determined on the...

10 CFR 72.98 - Identifying regions around an ISFSI or MRS site.

Code of Federal Regulations, 2010 CFR

2010-01-01

... regional extent of external phenomena, man-made or natural, that are used as a basis for the design of the ISFSI or MRS must be identified. (b) The potential regional impact due to the construction, operation or decommissioning of the ISFSI or MRS must be identified. The extent of regional impacts must be determined on the...

Potential fault region detection in TFDS images based on convolutional neural network

NASA Astrophysics Data System (ADS)

Sun, Junhua; Xiao, Zhongwen

2016-10-01

In recent years, more than 300 sets of Trouble of Running Freight Train Detection System (TFDS) have been installed on railway to monitor the safety of running freight trains in China. However, TFDS is simply responsible for capturing, transmitting, and storing images, and fails to recognize faults automatically due to some difficulties such as such as the diversity and complexity of faults and some low quality images. To improve the performance of automatic fault recognition, it is of great importance to locate the potential fault areas. In this paper, we first introduce a convolutional neural network (CNN) model to TFDS and propose a potential fault region detection system (PFRDS) for simultaneously detecting four typical types of potential fault regions (PFRs). The experimental results show that this system has a higher performance of image detection to PFRs in TFDS. An average detection recall of 98.95% and precision of 100% are obtained, demonstrating the high detection ability and robustness against various poor imaging situations.

On structure-exploiting trust-region regularized nonlinear least squares algorithms for neural-network learning.

PubMed

Mizutani, Eiji; Demmel, James W

2003-01-01

This paper briefly introduces our numerical linear algebra approaches for solving structured nonlinear least squares problems arising from 'multiple-output' neural-network (NN) models. Our algorithms feature trust-region regularization, and exploit sparsity of either the 'block-angular' residual Jacobian matrix or the 'block-arrow' Gauss-Newton Hessian (or Fisher information matrix in statistical sense) depending on problem scale so as to render a large class of NN-learning algorithms 'efficient' in both memory and operation costs. Using a relatively large real-world nonlinear regression application, we shall explain algorithmic strengths and weaknesses, analyzing simulation results obtained by both direct and iterative trust-region algorithms with two distinct NN models: 'multilayer perceptrons' (MLP) and 'complementary mixtures of MLP-experts' (or neuro-fuzzy modular networks).

Neural Signature of DCD: A Critical Review of MRI Neuroimaging Studies

PubMed Central

Biotteau, Maëlle; Chaix, Yves; Blais, Mélody; Tallet, Jessica; Péran, Patrice; Albaret, Jean-Michel

2016-01-01

The most common neurodevelopmental disorders (e.g., developmental dyslexia (DD), autism, attention-deficit hyperactivity disorder (ADHD)) have been the subject of numerous neuroimaging studies, leading to certain brain regions being identified as neural correlates of these conditions, referring to a neural signature of disorders. Developmental coordination disorder (DCD), however, remains one of the least understood and studied neurodevelopmental disorders. Given the acknowledged link between motor difficulties and brain features, it is surprising that so few research studies have systematically explored the brains of children with DCD. The aim of the present review was to ascertain whether it is currently possible to identify a neural signature for DCD, based on the 14 magnetic resonance imaging neuroimaging studies that have been conducted in DCD to date. Our results indicate that several brain areas are unquestionably linked to DCD: cerebellum, basal ganglia, parietal lobe, and parts of the frontal lobe (medial orbitofrontal cortex and dorsolateral prefrontal cortex). However, research has been too sparse and studies have suffered from several limitations that constitute a serious obstacle to address the question of a well-established neural signature for DCD. PMID:28018285

IDENTIFYING IONIZED REGIONS IN NOISY REDSHIFTED 21 cm DATA SETS

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

Malloy, Matthew; Lidz, Adam, E-mail: mattma@sas.upenn.edu

One of the most promising approaches for studying reionization is to use the redshifted 21 cm line. Early generations of redshifted 21 cm surveys will not, however, have the sensitivity to make detailed maps of the reionization process, and will instead focus on statistical measurements. Here, we show that it may nonetheless be possible to directly identify ionized regions in upcoming data sets by applying suitable filters to the noisy data. The locations of prominent minima in the filtered data correspond well with the positions of ionized regions. In particular, we corrupt semi-numeric simulations of the redshifted 21 cm signalmore » during reionization with thermal noise at the level expected for a 500 antenna tile version of the Murchison Widefield Array (MWA), and mimic the degrading effects of foreground cleaning. Using a matched filter technique, we find that the MWA should be able to directly identify ionized regions despite the large thermal noise. In a plausible fiducial model in which {approx}20% of the volume of the universe is neutral at z {approx} 7, we find that a 500-tile MWA may directly identify as many as {approx}150 ionized regions in a 6 MHz portion of its survey volume and roughly determine the size of each of these regions. This may, in turn, allow interesting multi-wavelength follow-up observations, comparing galaxy properties inside and outside of ionized regions. We discuss how the optimal configuration of radio antenna tiles for detecting ionized regions with a matched filter technique differs from the optimal design for measuring power spectra. These considerations have potentially important implications for the design of future redshifted 21 cm surveys.« less

Neural Mechanism for Mirrored Self-face Recognition

PubMed Central

Sugiura, Motoaki; Miyauchi, Carlos Makoto; Kotozaki, Yuka; Akimoto, Yoritaka; Nozawa, Takayuki; Yomogida, Yukihito; Hanawa, Sugiko; Yamamoto, Yuki; Sakuma, Atsushi; Nakagawa, Seishu; Kawashima, Ryuta

2015-01-01

Self-face recognition in the mirror is considered to involve multiple processes that integrate 2 perceptual cues: temporal contingency of the visual feedback on one's action (contingency cue) and matching with self-face representation in long-term memory (figurative cue). The aim of this study was to examine the neural bases of these processes by manipulating 2 perceptual cues using a “virtual mirror” system. This system allowed online dynamic presentations of real-time and delayed self- or other facial actions. Perception-level processes were identified as responses to only a single perceptual cue. The effect of the contingency cue was identified in the cuneus. The regions sensitive to the figurative cue were subdivided by the response to a static self-face, which was identified in the right temporal, parietal, and frontal regions, but not in the bilateral occipitoparietal regions. Semantic- or integration-level processes, including amodal self-representation and belief validation, which allow modality-independent self-recognition and the resolution of potential conflicts between perceptual cues, respectively, were identified in distinct regions in the right frontal and insular cortices. The results are supportive of the multicomponent notion of self-recognition and suggest a critical role for contingency detection in the co-emergence of self-recognition and empathy in infants. PMID:24770712

Comprehensive neural networks for guilty feelings in young adults.

PubMed

Nakagawa, Seishu; Takeuchi, Hikaru; Taki, Yasuyuki; Nouchi, Rui; Sekiguchi, Atsushi; Kotozaki, Yuka; Miyauchi, Carlos Makoto; Iizuka, Kunio; Yokoyama, Ryoichi; Shinada, Takamitsu; Yamamoto, Yuki; Hanawa, Sugiko; Araki, Tsuyoshi; Hashizume, Hiroshi; Kunitoki, Keiko; Sassa, Yuko; Kawashima, Ryuta

2015-01-15

Feelings of guilt are associated with widespread self and social cognitions, e.g., empathy, moral reasoning, and punishment. Neural correlates directly related to the degree of feelings of guilt have not been detected, probably due to the small numbers of subjects, whereas there are growing numbers of neuroimaging studies of feelings of guilt. We hypothesized that the neural networks for guilty feelings are widespread and include the insula, inferior parietal lobule (IPL), amygdala, subgenual cingulate cortex (SCC), and ventromedial prefrontal cortex (vmPFC), which are essential for cognitions of guilt. We investigated the association between regional gray matter density (rGMD) and feelings of guilt in 764 healthy young students (422 males, 342 females; 20.7 ± 1.8 years) using magnetic resonance imaging and the guilty feeling scale (GFS) for the younger generation which comprises interpersonal situation (IPS) and rule-breaking situation (RBS) scores. Both the IPS and RBS were negatively related to the rGMD in the right posterior insula (PI). The IPS scores were negatively correlated with rGMD in the left anterior insula (AI), right IPL, and vmPFC using small volume correction. A post hoc analysis performed on the significant clusters identified through these analyses revealed that rGMD activity in the right IPL showed a significant negative association with the empathy quotient. These findings at the whole-brain level are the widespread comprehensive neural network regions for guilty feelings. Interestingly, the novel finding in this study is that the PI was implicated as a common region for feelings of guilt with interaction between the IPS and RBS. Additionally, the neural networks including the IPL were associated with empathy and with regions implicated in moral reasoning (AI and vmPFC), and punishment (AI). Copyright © 2014 Elsevier Inc. All rights reserved.

Coding of level of ambiguity within neural systems mediating choice.

PubMed

Lopez-Paniagua, Dan; Seger, Carol A

2013-01-01

Data from previous neuroimaging studies exploring neural activity associated with uncertainty suggest varying levels of activation associated with changing degrees of uncertainty in neural regions that mediate choice behavior. The present study used a novel task that parametrically controlled the amount of information hidden from the subject; levels of uncertainty ranged from full ambiguity (no information about probability of winning) through multiple levels of partial ambiguity, to a condition of risk only (zero ambiguity with full knowledge of the probability of winning). A parametric analysis compared a linear model in which weighting increased as a function of level of ambiguity, and an inverted-U quadratic models in which partial ambiguity conditions were weighted most heavily. Overall we found that risk and all levels of ambiguity recruited a common "fronto-parietal-striatal" network including regions within the dorsolateral prefrontal cortex, intraparietal sulcus, and dorsal striatum. Activation was greatest across these regions and additional anterior and superior prefrontal regions for the quadratic function which most heavily weighs trials with partial ambiguity. These results suggest that the neural regions involved in decision processes do not merely track the absolute degree ambiguity or type of uncertainty (risk vs. ambiguity). Instead, recruitment of prefrontal regions may result from greater degree of difficulty in conditions of partial ambiguity: when information regarding reward probabilities important for decision making is hidden or not easily obtained the subject must engage in a search for tractable information. Additionally, this study identified regions of activity related to the valuation of potential gains associated with stimuli or options (including the orbitofrontal and medial prefrontal cortices and dorsal striatum) and related to winning (including orbitofrontal cortex and ventral striatum).

Coding of level of ambiguity within neural systems mediating choice

PubMed Central

Lopez-Paniagua, Dan; Seger, Carol A.

2013-01-01

Data from previous neuroimaging studies exploring neural activity associated with uncertainty suggest varying levels of activation associated with changing degrees of uncertainty in neural regions that mediate choice behavior. The present study used a novel task that parametrically controlled the amount of information hidden from the subject; levels of uncertainty ranged from full ambiguity (no information about probability of winning) through multiple levels of partial ambiguity, to a condition of risk only (zero ambiguity with full knowledge of the probability of winning). A parametric analysis compared a linear model in which weighting increased as a function of level of ambiguity, and an inverted-U quadratic models in which partial ambiguity conditions were weighted most heavily. Overall we found that risk and all levels of ambiguity recruited a common “fronto—parietal—striatal” network including regions within the dorsolateral prefrontal cortex, intraparietal sulcus, and dorsal striatum. Activation was greatest across these regions and additional anterior and superior prefrontal regions for the quadratic function which most heavily weighs trials with partial ambiguity. These results suggest that the neural regions involved in decision processes do not merely track the absolute degree ambiguity or type of uncertainty (risk vs. ambiguity). Instead, recruitment of prefrontal regions may result from greater degree of difficulty in conditions of partial ambiguity: when information regarding reward probabilities important for decision making is hidden or not easily obtained the subject must engage in a search for tractable information. Additionally, this study identified regions of activity related to the valuation of potential gains associated with stimuli or options (including the orbitofrontal and medial prefrontal cortices and dorsal striatum) and related to winning (including orbitofrontal cortex and ventral striatum). PMID:24367286

Correlation approach to identify coding regions in DNA sequences

NASA Technical Reports Server (NTRS)

Ossadnik, S. M.; Buldyrev, S. V.; Goldberger, A. L.; Havlin, S.; Mantegna, R. N.; Peng, C. K.; Simons, M.; Stanley, H. E.

1994-01-01

Recently, it was observed that noncoding regions of DNA sequences possess long-range power-law correlations, whereas coding regions typically display only short-range correlations. We develop an algorithm based on this finding that enables investigators to perform a statistical analysis on long DNA sequences to locate possible coding regions. The algorithm is particularly successful in predicting the location of lengthy coding regions. For example, for the complete genome of yeast chromosome III (315,344 nucleotides), at least 82% of the predictions correspond to putative coding regions; the algorithm correctly identified all coding regions larger than 3000 nucleotides, 92% of coding regions between 2000 and 3000 nucleotides long, and 79% of coding regions between 1000 and 2000 nucleotides. The predictive ability of this new algorithm supports the claim that there is a fundamental difference in the correlation property between coding and noncoding sequences. This algorithm, which is not species-dependent, can be implemented with other techniques for rapidly and accurately locating relatively long coding regions in genomic sequences.

Signaling mechanisms regulating adult neural stem cells and neurogenesis

PubMed Central

Faigle, Roland; Song, Hongjun

2012-01-01

Background Adult neurogenesis occurs throughout life in discrete regions of the mammalian brain and is tightly regulated via both extrinsic environmental influences and intrinsic genetic factors. In recent years, several crucial signaling pathways have been identified in regulating self-renewal, proliferation, and differentiation of neural stem cells, as well as migration and functional integration of developing neurons in the adult brain. Scope of review Here we review our current understanding of signaling mechanisms, including Wnt, notch, sonic hedgehog, growth and neurotrophic factors, bone morphogenetic proteins, neurotransmitters, transcription factors, and epigenetic modulators, and crosstalk between these signaling pathways in the regulation of adult neurogenesis. We also highlight emerging principles in the vastly growing field of adult neural stem cell biology and neural plasticity. Major conclusions Recent methodological advances have enabled the field to identify signaling mechanisms that fine-tune and coordinate neurogenesis in the adult brain, leading to a better characterization of both cell-intrinsic and environmental cues defining the neurogenic niche. Significant questions related to niche cell identity and underlying regulatory mechanisms remain to be fully addressed and will be the focus of future studies. General significance A full understanding of the role and function of individual signaling pathways in regulating neural stem cells and generation and integration of newborn neurons in the adult brain may lead to targeted new therapies for neurological diseases in humans. PMID:22982587

Development of Neural Sensitivity to Face Identity Correlates with Perceptual Discriminability

PubMed Central

Barnett, Michael A.; Hartley, Jake; Gomez, Jesse; Stigliani, Anthony; Grill-Spector, Kalanit

2016-01-01

Face perception is subserved by a series of face-selective regions in the human ventral stream, which undergo prolonged development from childhood to adulthood. However, it is unknown how neural development of these regions relates to the development of face-perception abilities. Here, we used functional magnetic resonance imaging (fMRI) to measure brain responses of ventral occipitotemporal regions in children (ages, 5–12 years) and adults (ages, 19–34 years) when they viewed faces that parametrically varied in dissimilarity. Since similar faces generate lower responses than dissimilar faces due to fMRI adaptation, this design objectively evaluates neural sensitivity to face identity across development. Additionally, a subset of subjects participated in a behavioral experiment to assess perceptual discriminability of face identity. Our data reveal three main findings: (1) neural sensitivity to face identity increases with age in face-selective but not object-selective regions; (2) the amplitude of responses to faces increases with age in both face-selective and object-selective regions; and (3) perceptual discriminability of face identity is correlated with the neural sensitivity to face identity of face-selective regions. In contrast, perceptual discriminability is not correlated with the amplitude of response in face-selective regions or of responses of object-selective regions. These data suggest that developmental increases in neural sensitivity to face identity in face-selective regions improve perceptual discriminability of faces. Our findings significantly advance the understanding of the neural mechanisms of development of face perception and open new avenues for using fMRI adaptation to study the neural development of high-level visual and cognitive functions more broadly. SIGNIFICANCE STATEMENT Face perception, which is critical for daily social interactions, develops from childhood to adulthood. However, it is unknown what developmental changes in

Development of Neural Sensitivity to Face Identity Correlates with Perceptual Discriminability.

PubMed

Natu, Vaidehi S; Barnett, Michael A; Hartley, Jake; Gomez, Jesse; Stigliani, Anthony; Grill-Spector, Kalanit

2016-10-19

Face perception is subserved by a series of face-selective regions in the human ventral stream, which undergo prolonged development from childhood to adulthood. However, it is unknown how neural development of these regions relates to the development of face-perception abilities. Here, we used functional magnetic resonance imaging (fMRI) to measure brain responses of ventral occipitotemporal regions in children (ages, 5-12 years) and adults (ages, 19-34 years) when they viewed faces that parametrically varied in dissimilarity. Since similar faces generate lower responses than dissimilar faces due to fMRI adaptation, this design objectively evaluates neural sensitivity to face identity across development. Additionally, a subset of subjects participated in a behavioral experiment to assess perceptual discriminability of face identity. Our data reveal three main findings: (1) neural sensitivity to face identity increases with age in face-selective but not object-selective regions; (2) the amplitude of responses to faces increases with age in both face-selective and object-selective regions; and (3) perceptual discriminability of face identity is correlated with the neural sensitivity to face identity of face-selective regions. In contrast, perceptual discriminability is not correlated with the amplitude of response in face-selective regions or of responses of object-selective regions. These data suggest that developmental increases in neural sensitivity to face identity in face-selective regions improve perceptual discriminability of faces. Our findings significantly advance the understanding of the neural mechanisms of development of face perception and open new avenues for using fMRI adaptation to study the neural development of high-level visual and cognitive functions more broadly. Face perception, which is critical for daily social interactions, develops from childhood to adulthood. However, it is unknown what developmental changes in the brain lead to improved

The Effects of Age, Memory Performance, and Callosal Integrity on the Neural Correlates of Successful Associative Encoding

PubMed Central

Wang, Tracy H.; Minton, Brian; Muftuler, L. Tugan; Rugg, Michael D.

2011-01-01

This functional magnetic resonance imaging study investigated the relationship between the neural correlates of associative memory encoding, callosal integrity, and memory performance in older adults. Thirty-six older and 18 young subjects were scanned while making relational judgments on word pairs. Neural correlates of successful encoding (subsequent memory effects) were identified by contrasting the activity elicited by study pairs that were correctly identified as having been studied together with the activity elicited by pairs wrongly judged to have come from different study trials. Subsequent memory effects common to the 2 age groups were identified in several regions, including left inferior frontal gyrus and bilateral hippocampus. Negative effects (greater activity for forgotten than for remembered items) in default network regions in young subjects were reversed in the older group, and the amount of reversal correlated negatively with memory performance. Additionally, older subjects' subsequent memory effects in right frontal cortex correlated positively with anterior callosal integrity and negatively with memory performance. It is suggested that recruitment of right frontal cortex during verbal memory encoding may reflect the engagement of processes that compensate only partially for age-related neural degradation. PMID:21282317

Regional Seismic Methods of Identifying Explosions

NASA Astrophysics Data System (ADS)

Walter, W. R.; Ford, S. R.; Pasyanos, M.; Pyle, M. L.; Hauk, T. F.

2013-12-01

A lesson from the 2006, 2009 and 2013 DPRK declared nuclear explosion Ms:mb observations is that our historic collection of data may not be representative of future nuclear test signatures (e.g. Selby et al., 2012). To have confidence in identifying future explosions amongst the background of other seismic signals, we need to put our empirical methods on a firmer physical footing. Here we review the two of the main identification methods: 1) P/S ratios and 2) Moment Tensor techniques, which can be applied at the regional distance (200-1600 km) to very small events, improving nuclear explosion monitoring and confidence in verifying compliance with the Comprehensive Nuclear-Test-Ban Treaty (CTBT). Amplitude ratios of seismic P-to-S waves at sufficiently high frequencies (~>2 Hz) can identify explosions among a background of natural earthquakes (e.g. Walter et al., 1995). However the physical basis for the generation of explosion S-waves, and therefore the predictability of this P/S technique as a function of event properties such as size, depth, geology and path, remains incompletely understood. Calculated intermediate period (10-100s) waveforms from regional 1-D models can match data and provide moment tensor results that separate explosions from earthquakes and cavity collapses (e.g. Ford et al. 2009). However it has long been observed that some nuclear tests produce large Love waves and reversed Rayleigh waves that complicate moment tensor modeling. Again the physical basis for the generation of these effects from explosions remains incompletely understood. We are re-examining regional seismic data from a variety of nuclear test sites including the DPRK and the former Nevada Test Site (now the Nevada National Security Site (NNSS)). Newer relative amplitude techniques can be employed to better quantify differences between explosions and used to understand those differences in term of depth, media and other properties. We are also making use of the Source Physics

Cloud Classification in Polar and Desert Regions and Smoke Classification from Biomass Burning Using a Hierarchical Neural Network

NASA Technical Reports Server (NTRS)

Alexander, June; Corwin, Edward; Lloyd, David; Logar, Antonette; Welch, Ronald

1996-01-01

This research focuses on a new neural network scene classification technique. The task is to identify scene elements in Advanced Very High Resolution Radiometry (AVHRR) data from three scene types: polar, desert and smoke from biomass burning in South America (smoke). The ultimate goal of this research is to design and implement a computer system which will identify the clouds present on a whole-Earth satellite view as a means of tracking global climate changes. Previous research has reported results for rule-based systems (Tovinkere et at 1992, 1993) for standard back propagation (Watters et at. 1993) and for a hierarchical approach (Corwin et al 1994) for polar data. This research uses a hierarchical neural network with don't care conditions and applies this technique to complex scenes. A hierarchical neural network consists of a switching network and a collection of leaf networks. The idea of the hierarchical neural network is that it is a simpler task to classify a certain pattern from a subset of patterns than it is to classify a pattern from the entire set. Therefore, the first task is to cluster the classes into groups. The switching, or decision network, performs an initial classification by selecting a leaf network. The leaf networks contain a reduced set of similar classes, and it is in the various leaf networks that the actual classification takes place. The grouping of classes in the various leaf networks is determined by applying an iterative clustering algorithm. Several clustering algorithms were investigated, but due to the size of the data sets, the exhaustive search algorithms were eliminated. A heuristic approach using a confusion matrix from a lightly trained neural network provided the basis for the clustering algorithm. Once the clusters have been identified, the hierarchical network can be trained. The approach of using don't care nodes results from the difficulty in generating extremely complex surfaces in order to separate one class from

Southwest Region: A Report Identifying and Addressing the Educational Needs

ERIC Educational Resources Information Center

US Department of Education, 2011

2011-01-01

The Educational Technical Assistance Act of 2002, authorized the Southwest Regional Advisory Committee (RAC), whose members represent the states of Arkansas, Louisiana, New Mexico, Oklahoma, and Texas, to identify and prioritize the region's educational needs and recommend how those needs can be met. The Southwest RAC conducted three public…

Identifying Fossil Shell Resources via Geophysical Surveys: Chesapeake Bay Region, Virginia

DTIC Science & Technology

2016-05-01

ER D C/ CH L TR -1 6- 4 Chesapeake Fossil Shell Survey Identifying Fossil Shell Resources via Geophysical Surveys: Chesapeake Bay Region...other technical reports published by ERDC, visit the ERDC online library at http://acwc.sdp.sirsi.net/client/default. Chesapeake Fossil Shell...Survey ERDC/CHL TR-16-4 May 2016 Identifying Fossil Shell Resources via Geophysical Surveys: Chesapeake Bay Region, Virginia Heidi M. Wadman and Jesse

Isolation of a transcription factor expressed in neural crest from the region of 22q11 deleted in DiGeorge syndrome

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

Wadey, R.; Roberts, C.; Daw, S.

1994-09-01

Deletions within chromosome 22q11 cause a wide variety of birth defects including DiGeorge syndrome and Shprintzen syndrome. We have defined a commonly deleted region of over 2 Mb, and a critical region of 300 kb. A gene, TUPLE1, has been isolated from this critical region encoding a transcriptional regulator similar to the yeast HIR1 histone regulator gene. Since it has been suggested that DGS results from a defective neural crest, the expression of Tuple1 was examined in whole mouse and chick embryos, tissue sections and neural tube explants: Tuple1 is expressed in a dynamic pattern with high levels in regionsmore » containing migrating crest. Prior to crest migration Tuple1 is expressed in a rhombomere-specific expression pattern. Later Tuple1 is expressed in discrete domains within the developing neural tube. A remarkable feature of the experiments was the detection of a similar dynamic pattern with sense probe; i.e., there is an antisense Tuple1 transcript. This was confirmed using RPA. Tuple1 is being screened for mutations in non-deletion patients and constructs assembled for homologous recombination in ES cells. Tuple1 maps to MMU16 extending the homology of linkage with human chromosome 22. From these data we predict that the human homologue of the murine scid mutation maps to 22q11.« less

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

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.

Neural Markers in Pediatric Bipolar Disorder and Familial Risk for Bipolar Disorder.

PubMed

Wiggins, Jillian Lee; Brotman, Melissa A; Adleman, Nancy E; Kim, Pilyoung; Wambach, Caroline G; Reynolds, Richard C; Chen, Gang; Towbin, Kenneth; Pine, Daniel S; Leibenluft, Ellen

2017-01-01

Bipolar disorder (BD) is highly heritable. Neuroimaging studies comparing unaffected youth at high familial risk for BD (i.e., those with a first-degree relative with the disorder; termed "high-risk" [HR]) to "low-risk" (LR) youth (i.e., those without a first-degree relative with BD) and to patients with BD may help identify potential brain-based markers associated with risk (i.e., regions where HR+BD≠LR), resilience (HR≠BD+LR), or illness (BD≠HR+LR). During functional magnetic resonance imaging (fMRI), 99 youths (i.e., adolescents and young adults) aged 9.8 to 24.8 years (36 BD, 22 HR, 41 LR) performed a task probing face emotion labeling, previously shown to be impaired behaviorally in youth with BD and HR youth. We found three patterns of results. Candidate risk endophenotypes (i.e., where BD and HR shared deficits) included dysfunction in higher-order face processing regions (e.g., middle temporal gyrus, dorsolateral prefrontal cortex). Candidate resilience markers and disorder sequelae (where HR and BD, respectively, show unique alterations relative to the other two groups) included different patterns of neural responses across other regions mediating face processing (e.g., fusiform), executive function (e.g., inferior frontal gyrus), and social cognition (e.g., default network, superior temporal sulcus, temporo-parietal junction). If replicated in longitudinal studies and with additional populations, neural patterns suggesting risk endophenotypes could be used to identify individuals at risk for BD who may benefit from prevention measures. Moreover, information about risk and resilience markers could be used to develop novel treatments that recruit neural markers of resilience and attenuate neural patterns associated with risk. Clinical trial registration information-Studies of Brain Function and Course of Illness in Pediatric Bipolar Disorder and Child and Adolescent Bipolar Disorder Brain Imaging and Treatment Study; http://clinicaltrials.gov/; NCT

Neural codes of seeing architectural styles

PubMed Central

Choo, Heeyoung; Nasar, Jack L.; Nikrahei, Bardia; Walther, Dirk B.

2017-01-01

Images of iconic buildings, such as the CN Tower, instantly transport us to specific places, such as Toronto. Despite the substantial impact of architectural design on people’s visual experience of built environments, we know little about its neural representation in the human brain. In the present study, we have found patterns of neural activity associated with specific architectural styles in several high-level visual brain regions, but not in primary visual cortex (V1). This finding suggests that the neural correlates of the visual perception of architectural styles stem from style-specific complex visual structure beyond the simple features computed in V1. Surprisingly, the network of brain regions representing architectural styles included the fusiform face area (FFA) in addition to several scene-selective regions. Hierarchical clustering of error patterns further revealed that the FFA participated to a much larger extent in the neural encoding of architectural styles than entry-level scene categories. We conclude that the FFA is involved in fine-grained neural encoding of scenes at a subordinate-level, in our case, architectural styles of buildings. This study for the first time shows how the human visual system encodes visual aspects of architecture, one of the predominant and longest-lasting artefacts of human culture. PMID:28071765

Neural codes of seeing architectural styles.

PubMed

Choo, Heeyoung; Nasar, Jack L; Nikrahei, Bardia; Walther, Dirk B

2017-01-10

Images of iconic buildings, such as the CN Tower, instantly transport us to specific places, such as Toronto. Despite the substantial impact of architectural design on people's visual experience of built environments, we know little about its neural representation in the human brain. In the present study, we have found patterns of neural activity associated with specific architectural styles in several high-level visual brain regions, but not in primary visual cortex (V1). This finding suggests that the neural correlates of the visual perception of architectural styles stem from style-specific complex visual structure beyond the simple features computed in V1. Surprisingly, the network of brain regions representing architectural styles included the fusiform face area (FFA) in addition to several scene-selective regions. Hierarchical clustering of error patterns further revealed that the FFA participated to a much larger extent in the neural encoding of architectural styles than entry-level scene categories. We conclude that the FFA is involved in fine-grained neural encoding of scenes at a subordinate-level, in our case, architectural styles of buildings. This study for the first time shows how the human visual system encodes visual aspects of architecture, one of the predominant and longest-lasting artefacts of human culture.

Neural Correlates of Attitude Change Following Positive and Negative Advertisements

PubMed Central

Kato, Junko; Ide, Hiroko; Kabashima, Ikuo; Kadota, Hiroshi; Takano, Kouji; Kansaku, Kenji

2009-01-01

Understanding changes in attitudes towards others is critical to understanding human behaviour. Neuropolitical studies have found that the activation of emotion-related areas in the brain is linked to resilient political preferences, and neuroeconomic research has analysed the neural correlates of social preferences that favour or oppose consideration of intrinsic rewards. This study aims to identify the neural correlates in the prefrontal cortices of changes in political attitudes toward others that are linked to social cognition. Functional magnetic resonance imaging (fMRI) experiments have presented videos from previous electoral campaigns and television commercials for major cola brands and then used the subjects' self-rated affinity toward political candidates as behavioural indicators. After viewing negative campaign videos, subjects showing stronger fMRI activation in the dorsolateral prefrontal cortex lowered their ratings of the candidate they originally supported more than did those with smaller fMRI signal changes in the same region. Subjects showing stronger activation in the medial prefrontal cortex tended to increase their ratings more than did those with less activation. The same regions were not activated by viewing negative advertisements for cola. Correlations between the self-rated values and the neural signal changes underscore the metric representation of observed decisions (i.e., whether to support or not) in the brain. This indicates that neurometric analysis may contribute to the exploration of the neural correlates of daily social behaviour. PMID:19503749

Neural correlates of nesting behavior in zebra finches (Taeniopygia guttata).

PubMed

Hall, Zachary J; Bertin, Marion; Bailey, Ida E; Meddle, Simone L; Healy, Susan D

2014-05-01

Nest building in birds involves a behavioral sequence (nest material collection and deposition in the nest) that offers a unique model for addressing how the brain sequences motor actions. In this study, we identified brain regions involved in nesting behavior in male and female zebra finches (Taeniopygia guttata). We used Fos immunohistochemistry to quantify production of the immediate early gene protein product Fos (a molecular indicator of neuronal activity) in the brain correlated this expression with the variation in nesting behavior. Using this technique, we found that neural circuitry involved in motor sequencing, social behavior, reward and motivation were active during nesting. Within pairs of nesting birds, the number of times a male picked up or deposited nesting material and the amount of time a female spent in the nest explained the variation in Fos expression in the anterior motor pathway, social behavior network, and reward neural circuits. Identification of the brain regions that are involved in nesting enables us to begin studying the roles of motor sequencing, context, and reward in construction behavior at the neural level. Copyright © 2014 Elsevier B.V. All rights reserved.

Localization of synchronous cortical neural sources.

PubMed

Zerouali, Younes; Herry, Christophe L; Jemel, Boutheina; Lina, Jean-Marc

2013-03-01

Neural synchronization is a key mechanism to a wide variety of brain functions, such as cognition, perception, or memory. High temporal resolution achieved by EEG recordings allows the study of the dynamical properties of synchronous patterns of activity at a very fine temporal scale but with very low spatial resolution. Spatial resolution can be improved by retrieving the neural sources of EEG signal, thus solving the so-called inverse problem. Although many methods have been proposed to solve the inverse problem and localize brain activity, few of them target the synchronous brain regions. In this paper, we propose a novel algorithm aimed at localizing specifically synchronous brain regions and reconstructing the time course of their activity. Using multivariate wavelet ridge analysis, we extract signals capturing the synchronous events buried in the EEG and then solve the inverse problem on these signals. Using simulated data, we compare results of source reconstruction accuracy achieved by our method to a standard source reconstruction approach. We show that the proposed method performs better across a wide range of noise levels and source configurations. In addition, we applied our method on real dataset and identified successfully cortical areas involved in the functional network underlying visual face perception. We conclude that the proposed approach allows an accurate localization of synchronous brain regions and a robust estimation of their activity.

WNT/β-catenin signaling mediates human neural crest induction via a pre-neural border intermediate.

PubMed

Leung, Alan W; Murdoch, Barbara; Salem, Ahmed F; Prasad, Maneeshi S; Gomez, Gustavo A; García-Castro, Martín I

2016-02-01

Neural crest (NC) cells arise early in vertebrate development, migrate extensively and contribute to a diverse array of ectodermal and mesenchymal derivatives. Previous models of NC formation suggested derivation from neuralized ectoderm, via meso-ectodermal, or neural-non-neural ectoderm interactions. Recent studies using bird and amphibian embryos suggest an earlier origin of NC, independent of neural and mesodermal tissues. Here, we set out to generate a model in which to decipher signaling and tissue interactions involved in human NC induction. Our novel human embryonic stem cell (ESC)-based model yields high proportions of multipotent NC cells (expressing SOX10, PAX7 and TFAP2A) in 5 days. We demonstrate a crucial role for WNT/β-catenin signaling in launching NC development, while blocking placodal and surface ectoderm fates. We provide evidence of the delicate temporal effects of BMP and FGF signaling, and find that NC development is separable from neural and/or mesodermal contributions. We further substantiate the notion of a neural-independent origin of NC through PAX6 expression and knockdown studies. Finally, we identify a novel pre-neural border state characterized by early WNT/β-catenin signaling targets that displays distinct responses to BMP and FGF signaling from the traditional neural border genes. In summary, our work provides a fast and efficient protocol for human NC differentiation under signaling constraints similar to those identified in vivo in model organisms, and strengthens a framework for neural crest ontogeny that is separable from neural and mesodermal fates. © 2016. Published by The Company of Biologists Ltd.

Neural Mechanism for Mirrored Self-face Recognition.

PubMed

Sugiura, Motoaki; Miyauchi, Carlos Makoto; Kotozaki, Yuka; Akimoto, Yoritaka; Nozawa, Takayuki; Yomogida, Yukihito; Hanawa, Sugiko; Yamamoto, Yuki; Sakuma, Atsushi; Nakagawa, Seishu; Kawashima, Ryuta

2015-09-01

Self-face recognition in the mirror is considered to involve multiple processes that integrate 2 perceptual cues: temporal contingency of the visual feedback on one's action (contingency cue) and matching with self-face representation in long-term memory (figurative cue). The aim of this study was to examine the neural bases of these processes by manipulating 2 perceptual cues using a "virtual mirror" system. This system allowed online dynamic presentations of real-time and delayed self- or other facial actions. Perception-level processes were identified as responses to only a single perceptual cue. The effect of the contingency cue was identified in the cuneus. The regions sensitive to the figurative cue were subdivided by the response to a static self-face, which was identified in the right temporal, parietal, and frontal regions, but not in the bilateral occipitoparietal regions. Semantic- or integration-level processes, including amodal self-representation and belief validation, which allow modality-independent self-recognition and the resolution of potential conflicts between perceptual cues, respectively, were identified in distinct regions in the right frontal and insular cortices. The results are supportive of the multicomponent notion of self-recognition and suggest a critical role for contingency detection in the co-emergence of self-recognition and empathy in infants. © The Author 2014. Published by Oxford University Press.

A Study on Regional Frequency Analysis using Artificial Neural Network - the Sumjin River Basin

NASA Astrophysics Data System (ADS)

Jeong, C.; Ahn, J.; Ahn, H.; Heo, J. H.

2017-12-01

Regional frequency analysis means to make up for shortcomings in the at-site frequency analysis which is about a lack of sample size through the regional concept. Regional rainfall quantile depends on the identification of hydrologically homogeneous regions, hence the regional classification based on hydrological homogeneous assumption is very important. For regional clustering about rainfall, multidimensional variables and factors related geographical features and meteorological figure are considered such as mean annual precipitation, number of days with precipitation in a year and average maximum daily precipitation in a month. Self-Organizing Feature Map method which is one of the artificial neural network algorithm in the unsupervised learning techniques solves N-dimensional and nonlinear problems and be shown results simply as a data visualization technique. In this study, for the Sumjin river basin in South Korea, cluster analysis was performed based on SOM method using high-dimensional geographical features and meteorological factor as input data. then, for the results, in order to evaluate the homogeneity of regions, the L-moment based discordancy and heterogeneity measures were used. Rainfall quantiles were estimated as the index flood method which is one of regional rainfall frequency analysis. Clustering analysis using SOM method and the consequential variation in rainfall quantile were analyzed. This research was supported by a grant(2017-MPSS31-001) from Supporting Technology Development Program for Disaster Management funded by Ministry of Public Safety and Security(MPSS) of the Korean government.

The neural bases for valuing social equality.

PubMed

Aoki, Ryuta; Yomogida, Yukihito; Matsumoto, Kenji

2015-01-01

The neural basis of how humans value and pursue social equality has become a major topic in social neuroscience research. Although recent studies have identified a set of brain regions and possible mechanisms that are involved in the neural processing of equality of outcome between individuals, how the human brain processes equality of opportunity remains unknown. In this review article, first we describe the importance of the distinction between equality of outcome and equality of opportunity, which has been emphasized in philosophy and economics. Next, we discuss possible approaches for empirical characterization of human valuation of equality of opportunity vs. equality of outcome. Understanding how these two concepts are distinct and interact with each other may provide a better explanation of complex human behaviors concerning fairness and social equality. Copyright © 2014 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

Similar patterns of neural activity predict memory function during encoding and retrieval.

PubMed

Kragel, James E; Ezzyat, Youssef; Sperling, Michael R; Gorniak, Richard; Worrell, Gregory A; Berry, Brent M; Inman, Cory; Lin, Jui-Jui; Davis, Kathryn A; Das, Sandhitsu R; Stein, Joel M; Jobst, Barbara C; Zaghloul, Kareem A; Sheth, Sameer A; Rizzuto, Daniel S; Kahana, Michael J

2017-07-15

Neural networks that span the medial temporal lobe (MTL), prefrontal cortex, and posterior cortical regions are essential to episodic memory function in humans. Encoding and retrieval are supported by the engagement of both distinct neural pathways across the cortex and common structures within the medial temporal lobes. However, the degree to which memory performance can be determined by neural processing that is common to encoding and retrieval remains to be determined. To identify neural signatures of successful memory function, we administered a delayed free-recall task to 187 neurosurgical patients implanted with subdural or intraparenchymal depth electrodes. We developed multivariate classifiers to identify patterns of spectral power across the brain that independently predicted successful episodic encoding and retrieval. During encoding and retrieval, patterns of increased high frequency activity in prefrontal, MTL, and inferior parietal cortices, accompanied by widespread decreases in low frequency power across the brain predicted successful memory function. Using a cross-decoding approach, we demonstrate the ability to predict memory function across distinct phases of the free-recall task. Furthermore, we demonstrate that classifiers that combine information from both encoding and retrieval states can outperform task-independent models. These findings suggest that the engagement of a core memory network during either encoding or retrieval shapes the ability to remember the past, despite distinct neural interactions that facilitate encoding and retrieval. Copyright © 2017 Elsevier Inc. All rights reserved.

Neural Network Target Identification System for False Alarm Reduction

NASA Technical Reports Server (NTRS)

Ye, David; Edens, Weston; Lu, Thomas T.; Chao, Tien-Hsin

2009-01-01

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feed forward back propagation neural network (NN) is then trained to classify each feature vector and remove false positives. This paper discusses the test of the system performance and parameter optimizations process which adapts the system to various targets and datasets. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar image dataset.

A neural network approach to lung nodule segmentation

NASA Astrophysics Data System (ADS)

Hu, Yaoxiu; Menon, Prahlad G.

2016-03-01

Computed tomography (CT) imaging is a sensitive and specific lung cancer screening tool for the high-risk population and shown to be promising for detection of lung cancer. This study proposes an automatic methodology for detecting and segmenting lung nodules from CT images. The proposed methods begin with thorax segmentation, lung extraction and reconstruction of the original shape of the parenchyma using morphology operations. Next, a multi-scale hessian-based vesselness filter is applied to extract lung vasculature in lung. The lung vasculature mask is subtracted from the lung region segmentation mask to extract 3D regions representing candidate pulmonary nodules. Finally, the remaining structures are classified as nodules through shape and intensity features which are together used to train an artificial neural network. Up to 75% sensitivity and 98% specificity was achieved for detection of lung nodules in our testing dataset, with an overall accuracy of 97.62%+/-0.72% using 11 selected features as input to the neural network classifier, based on 4-fold cross-validation studies. Receiver operator characteristics for identifying nodules revealed an area under curve of 0.9476.

Neural correlates of sexual cue reactivity in individuals with and without compulsive sexual behaviours.

PubMed

Voon, Valerie; Mole, Thomas B; Banca, Paula; Porter, Laura; Morris, Laurel; Mitchell, Simon; Lapa, Tatyana R; Karr, Judy; Harrison, Neil A; Potenza, Marc N; Irvine, Michael

2014-01-01

Although compulsive sexual behaviour (CSB) has been conceptualized as a "behavioural" addiction and common or overlapping neural circuits may govern the processing of natural and drug rewards, little is known regarding the responses to sexually explicit materials in individuals with and without CSB. Here, the processing of cues of varying sexual content was assessed in individuals with and without CSB, focusing on neural regions identified in prior studies of drug-cue reactivity. 19 CSB subjects and 19 healthy volunteers were assessed using functional MRI comparing sexually explicit videos with non-sexual exciting videos. Ratings of sexual desire and liking were obtained. Relative to healthy volunteers, CSB subjects had greater desire but similar liking scores in response to the sexually explicit videos. Exposure to sexually explicit cues in CSB compared to non-CSB subjects was associated with activation of the dorsal anterior cingulate, ventral striatum and amygdala. Functional connectivity of the dorsal anterior cingulate-ventral striatum-amygdala network was associated with subjective sexual desire (but not liking) to a greater degree in CSB relative to non-CSB subjects. The dissociation between desire or wanting and liking is consistent with theories of incentive motivation underlying CSB as in drug addictions. Neural differences in the processing of sexual-cue reactivity were identified in CSB subjects in regions previously implicated in drug-cue reactivity studies. The greater engagement of corticostriatal limbic circuitry in CSB following exposure to sexual cues suggests neural mechanisms underlying CSB and potential biological targets for interventions.

Neural Networks

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

Smith, Patrick I.

2003-09-23

Physicists use large detectors to measure particles created in high-energy collisions at particle accelerators. These detectors typically produce signals indicating either where ionization occurs along the path of the particle, or where energy is deposited by the particle. The data produced by these signals is fed into pattern recognition programs to try to identify what particles were produced, and to measure the energy and direction of these particles. Ideally, there are many techniques used in this pattern recognition software. One technique, neural networks, is particularly suitable for identifying what type of particle caused by a set of energy deposits. Neuralmore » networks can derive meaning from complicated or imprecise data, extract patterns, and detect trends that are too complex to be noticed by either humans or other computer related processes. To assist in the advancement of this technology, Physicists use a tool kit to experiment with several neural network techniques. The goal of this research is interface a neural network tool kit into Java Analysis Studio (JAS3), an application that allows data to be analyzed from any experiment. As the final result, a physicist will have the ability to train, test, and implement a neural network with the desired output while using JAS3 to analyze the results or output. Before an implementation of a neural network can take place, a firm understanding of what a neural network is and how it works is beneficial. A neural network is an artificial representation of the human brain that tries to simulate the learning process [5]. It is also important to think of the word artificial in that definition as computer programs that use calculations during the learning process. In short, a neural network learns by representative examples. Perhaps the easiest way to describe the way neural networks learn is to explain how the human brain functions. The human brain contains billions of neural cells that are responsible for

Decoding Ventromedial Hypothalamic Neural Activity during Male Mouse Aggression

PubMed Central

Dollar, Piotr; Perona, Pietro

2014-01-01

The ventromedial hypothalamus, ventrolateral area (VMHvl) was identified recently as a critical locus for inter-male aggression. Optogenetic stimulation of VMHvl in male mice evokes attack toward conspecifics and inactivation of the region inhibits natural aggression, yet very little is known about its underlying neural activity. To understand its role in promoting aggression, we recorded and analyzed neural activity in the VMHvl in response to a wide range of social and nonsocial stimuli. Although response profiles of VMHvl neurons are complex and heterogeneous, we identified a subpopulation of neurons that respond maximally during investigation and attack of male conspecific mice and during investigation of a source of male mouse urine. These “male responsive” neurons in the VMHvl are tuned to both the inter-male distance and the animal's velocity during attack. Additionally, VMHvl activity predicts several parameters of future aggressive action, including the latency and duration of the next attack. Linear regression analysis further demonstrates that aggression-specific parameters, such as distance, movement velocity, and attack latency, can model ongoing VMHvl activity fluctuation during inter-male encounters. These results represent the first effort to understand the hypothalamic neural activity during social behaviors using quantitative tools and suggest an important role for the VMHvl in encoding movement, sensory, and motivation-related signals. PMID:24760856

Magnetoencephalographic Signals Identify Stages in Real-Life Decision Processes

PubMed Central

Braeutigam, Sven; Stins, John F.; Rose, Steven P. R.; Swithenby, Stephen J.; Ambler, Tim

2001-01-01

We used magnetoencephalography (MEG) to study the dynamics of neural responses in eight subjects engaged in shopping for day-to-day items from supermarket shelves. This behavior not only has personal and economic importance but also provides an example of an experience that is both personal and shared between individuals. The shopping experience enables the exploration of neural mechanisms underlying choice based on complex memories. Choosing among different brands of closely related products activated a robust sequence of signals within the first second after the presentation of the choice images. This sequence engaged first the visual cortex (80-100 ms), then as the images were analyzed, predominantly the left temporal regions (310-340 ms). At longer latency, characteristic neural activetion was found in motor speech areas (500-520 ms) for images requiring low salience choices with respect to previous (brand) memory, and in right parietal cortex for high salience choices (850-920 ms). We argue that the neural processes associated with the particular brand-choice stimulus can be separated into identifiable stages through observation of MEG responses and knowledge of functional anatomy. PMID:12018772

Neural Representations of Belief Concepts: A Representational Similarity Approach to Social Semantics

PubMed Central

Leshinskaya, Anna; Contreras, Juan Manuel; Caramazza, Alfonso; Mitchell, Jason P.

2017-01-01

Abstract The present experiment identified neural regions that represent a class of concepts that are independent of perceptual or sensory attributes. During functional magnetic resonance imaging scanning, participants viewed names of social groups (e.g. Atheists, Evangelicals, and Economists) and performed a one-back similarity judgment according to 1 of 2 dimensions of belief attributes: political orientation (Liberal to Conservative) or spiritualism (Spiritualist to Materialist). By generalizing across a wide variety of social groups that possess these beliefs, these attribute concepts did not coincide with any specific sensory quality, allowing us to target conceptual, rather than perceptual, representations. Multi-voxel pattern searchlight analysis was used to identify regions in which activation patterns distinguished the 2 ends of both dimensions: Conservative from Liberal social groups when participants focused on the political orientation dimension, and spiritual from Materialist groups when participants focused on the spiritualism dimension. A cluster in right precuneus exhibited such a pattern, indicating that it carries information about belief-attribute concepts and forms part of semantic memory—perhaps a component particularly concerned with psychological traits. This region did not overlap with the theory of mind network, which engaged nearby, but distinct, parts of precuneus. These findings have implications for the neural organization of conceptual knowledge, especially the understanding of social groups. PMID:28108495

The neural basis of monitoring goal progress

PubMed Central

Benn, Yael; Webb, Thomas L.; Chang, Betty P. I.; Sun, Yu-Hsuan; Wilkinson, Iain D.; Farrow, Tom F. D.

2014-01-01

The neural basis of progress monitoring has received relatively little attention compared to other sub-processes that are involved in goal directed behavior such as motor control and response inhibition. Studies of error-monitoring have identified the dorsal anterior cingulate cortex (dACC) as a structure that is sensitive to conflict detection, and triggers corrective action. However, monitoring goal progress involves monitoring correct as well as erroneous events over a period of time. In the present research, 20 healthy participants underwent functional magnetic resonance imagining (fMRI) while playing a game that involved monitoring progress toward either a numerical or a visuo-spatial target. The findings confirmed the role of the dACC in detecting situations in which the current state may conflict with the desired state, but also revealed activations in the frontal and parietal regions, pointing to the involvement of processes such as attention and working memory (WM) in monitoring progress over time. In addition, activation of the cuneus was associated with monitoring progress toward a specific target presented in the visual modality. This is the first time that activation in this region has been linked to higher-order processing of goal-relevant information, rather than low-level anticipation of visual stimuli. Taken together, these findings identify the neural substrates involved in monitoring progress over time, and how these extend beyond activations observed in conflict and error monitoring. PMID:25309380

Neural correlates of HIV risk feelings.

PubMed

Häcker, Frank E K; Schmälzle, Ralf; Renner, Britta; Schupp, Harald T

2015-04-01

Field studies on HIV risk perception suggest that people rely on impressions they have about the safety of their partner. The present fMRI study investigated the neural correlates of the intuitive perception of risk. First, during an implicit condition, participants viewed a series of unacquainted persons and performed a task unrelated to HIV risk. In the following explicit condition, participants evaluated the HIV risk for each presented person. Contrasting responses for high and low HIV risk revealed that risky stimuli evoked enhanced activity in the anterior insula and medial prefrontal regions, which are involved in salience processing and frequently activated by threatening and negative affect-related stimuli. Importantly, neural regions responding to explicit HIV risk judgments were also enhanced in the implicit condition, suggesting a neural mechanism for intuitive impressions of riskiness. Overall, these findings suggest the saliency network as neural correlate for the intuitive sensing of risk. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Neural dynamics underlying emotional transmissions between individuals

PubMed Central

Levit-Binnun, Nava; Hendler, Talma; Lerner, Yulia

2017-01-01

Abstract Emotional experiences are frequently shaped by the emotional responses of co-present others. Research has shown that people constantly monitor and adapt to the incoming social–emotional signals, even without face-to-face interaction. And yet, the neural processes underlying such emotional transmissions have not been directly studied. Here, we investigated how the human brain processes emotional cues which arrive from another, co-attending individual. We presented continuous emotional feedback to participants who viewed a movie in the scanner. Participants in the social group (but not in the control group) believed that the feedback was coming from another person who was co-viewing the same movie. We found that social–emotional feedback significantly affected the neural dynamics both in the core affect and in the medial pre-frontal regions. Specifically, the response time-courses in those regions exhibited increased similarity across recipients and increased neural alignment with the timeline of the feedback in the social compared with control group. Taken in conjunction with previous research, this study suggests that emotional cues from others shape the neural dynamics across the whole neural continuum of emotional processing in the brain. Moreover, it demonstrates that interpersonal neural alignment can serve as a neural mechanism through which affective information is conveyed between individuals. PMID:28575520

Augmenting Chinese hamster genome assembly by identifying regions of high confidence.

PubMed

Vishwanathan, Nandita; Bandyopadhyay, Arpan A; Fu, Hsu-Yuan; Sharma, Mohit; Johnson, Kathryn C; Mudge, Joann; Ramaraj, Thiruvarangan; Onsongo, Getiria; Silverstein, Kevin A T; Jacob, Nitya M; Le, Huong; Karypis, George; Hu, Wei-Shou

2016-09-01

Chinese hamster Ovary (CHO) cell lines are the dominant industrial workhorses for therapeutic recombinant protein production. The availability of genome sequence of Chinese hamster and CHO cells will spur further genome and RNA sequencing of producing cell lines. However, the mammalian genomes assembled using shot-gun sequencing data still contain regions of uncertain quality due to assembly errors. Identifying high confidence regions in the assembled genome will facilitate its use for cell engineering and genome engineering. We assembled two independent drafts of Chinese hamster genome by de novo assembly from shotgun sequencing reads and by re-scaffolding and gap-filling the draft genome from NCBI for improved scaffold lengths and gap fractions. We then used the two independent assemblies to identify high confidence regions using two different approaches. First, the two independent assemblies were compared at the sequence level to identify their consensus regions as "high confidence regions" which accounts for at least 78 % of the assembled genome. Further, a genome wide comparison of the Chinese hamster scaffolds with mouse chromosomes revealed scaffolds with large blocks of collinearity, which were also compiled as high-quality scaffolds. Genome scale collinearity was complemented with EST based synteny which also revealed conserved gene order compared to mouse. As cell line sequencing becomes more commonly practiced, the approaches reported here are useful for assessing the quality of assembly and potentially facilitate the engineering of cell lines. Copyright © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Regulating the dorsal neural tube expression of Ptf1a through a distal 3' enhancer.

PubMed

Mona, Bishakha; Avila, John M; Meredith, David M; Kollipara, Rahul K; Johnson, Jane E

2016-10-01

Generating the correct balance of inhibitory and excitatory neurons in a neural network is essential for normal functioning of a nervous system. The neural network in the dorsal spinal cord functions in somatosensation where it modulates and relays sensory information from the periphery. PTF1A is a key transcriptional regulator present in a specific subset of neural progenitor cells in the dorsal spinal cord, cerebellum and retina that functions to specify an inhibitory neuronal fate while suppressing excitatory neuronal fates. Thus, the regulation of Ptf1a expression is critical for determining mechanisms controlling neuronal diversity in these regions of the nervous system. Here we identify a sequence conserved, tissue-specific enhancer located 10.8kb 3' of the Ptf1a coding region that is sufficient to direct expression to dorsal neural tube progenitors that give rise to neurons in the dorsal spinal cord in chick and mouse. DNA binding motifs for Paired homeodomain (Pd-HD) and zinc finger (ZF) transcription factors are required for enhancer activity. Mutations in these sequences implicate the Pd-HD motif for activator function and the ZF motif for repressor function. Although no repressor transcription factor was identified, both PAX6 and SOX3 can increase enhancer activity in reporter assays. Thus, Ptf1a is regulated by active and repressive inputs integrated through multiple sequence elements within a highly conserved sequence downstream of the Ptf1a gene. Copyright © 2016 Elsevier Inc. All rights reserved.

Identifying Predictors, Moderators, and Mediators of Antidepressant Response in Major Depressive Disorder: Neuroimaging Approaches

PubMed Central

Phillips, Mary L.; Chase, Henry W.; Sheline, Yvette I.; Etkin, Amit; Almeida, Jorge R.C.; Deckersbach, Thilo; Trivedi, Madhukar H.

2015-01-01

Objective Despite significant advances in neuroscience and treatment development, no widely accepted biomarkers are available to inform diagnostics or identify preferred treatments for individuals with major depressive disorder. Method In this critical review, the authors examine the extent to which multimodal neuroimaging techniques can identify biomarkers reflecting key pathophysiologic processes in depression and whether such biomarkers may act as predictors, moderators, and mediators of treatment response that might facilitate development of personalized treatments based on a better understanding of these processes. Results The authors first highlight the most consistent findings from neuroimaging studies using different techniques in depression, including structural and functional abnormalities in two parallel neural circuits: serotonergically modulated implicit emotion regulation circuitry, centered on the amygdala and different regions in the medial prefrontal cortex; and dopaminergically modulated reward neural circuitry, centered on the ventral striatum and medial prefrontal cortex. They then describe key findings from the relatively small number of studies indicating that specific measures of regional function and, to a lesser extent, structure in these neural circuits predict treatment response in depression. Conclusions Limitations of existing studies include small sample sizes, use of only one neuroimaging modality, and a focus on identifying predictors rather than moderators and mediators of differential treatment response. By addressing these limitations and, most importantly, capitalizing on the benefits of multimodal neuroimaging, future studies can yield moderators and mediators of treatment response in depression to facilitate significant improvements in shorter- and longer-term clinical and functional outcomes. PMID:25640931

Chondroitin sulfate effects on neural stem cell differentiation.

PubMed

Canning, David R; Brelsford, Natalie R; Lovett, Neil W

2016-01-01

We have investigated the role chondroitin sulfate has on cell interactions during neural plate formation in the early chick embryo. Using tissue culture isolates from the prospective neural plate, we have measured neural gene expression profiles associated with neural stem cell differentiation. Removal of chondroitin sulfate from stage 4 neural plate tissue leads to altered associations of N-cadherin-positive neural progenitors and causes changes in the normal sequence of neural marker gene expression. Absence of chondroitin sulfate in the neural plate leads to reduced Sox2 expression and is accompanied by an increase in the expression of anterior markers of neural regionalization. Results obtained in this study suggest that the presence of chondroitin sulfate in the anterior chick embryo is instrumental in maintaining cells in the neural precursor state.

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.

Identification of the subthalamic nucleus in deep brain stimulation surgery with a novel wavelet-derived measure of neural background activity.

PubMed

Snellings, André; Sagher, Oren; Anderson, David J; Aldridge, J Wayne

2009-10-01

The authors developed a wavelet-based measure for quantitative assessment of neural background activity during intraoperative neurophysiological recordings so that the boundaries of the subthalamic nucleus (STN) can be more easily localized for electrode implantation. Neural electrophysiological data were recorded in 14 patients (20 tracks and 275 individual recording sites) with dopamine-sensitive idiopathic Parkinson disease during the target localization portion of deep brain stimulator implantation surgery. During intraoperative recording, the STN was identified based on audio and visual monitoring of neural firing patterns, kinesthetic tests, and comparisons between neural behavior and the known characteristics of the target nucleus. The quantitative wavelet-based measure was applied offline using commercially available software to measure the magnitude of the neural background activity, and the results of this analysis were compared with the intraoperative conclusions. Wavelet-derived estimates were also compared with power spectral density measurements. The wavelet-derived background levels were significantly higher in regions encompassed by the clinically estimated boundaries of the STN than in the surrounding regions (STN, 225 +/- 61 microV; ventral to the STN, 112 +/- 32 microV; and dorsal to the STN, 136 +/- 66 microV). In every track, the absolute maximum magnitude was found within the clinically identified STN. The wavelet-derived background levels provided a more consistent index with less variability than measurements with power spectral density. Wavelet-derived background activity can be calculated quickly, does not require spike sorting, and can be used to identify the STN reliably with very little subjective interpretation required. This method may facilitate the rapid intraoperative identification of STN borders.

The Polybasic Region of the Polysialyltransferase ST8Sia-IV Binds Directly to the Neural Cell Adhesion Molecule, NCAM.

PubMed

Bhide, Gaurang P; Prehna, Gerd; Ramirez, Benjamin E; Colley, Karen J

2017-03-14

Polysialic acid (polySia) is a unique post-translational modification found on a small set of mammalian glycoproteins. Composed of long chains of α2,8-linked sialic acid, this large, negatively charged polymer attenuates protein and cell adhesion and modulates signaling mediated by its carriers and proteins that interact with these carriers. PolySia is crucial for the proper development of the nervous system and is upregulated during tissue regeneration and in highly invasive cancers. Our laboratory has previously shown that the neural cell adhesion molecule, NCAM, has an acidic surface patch in its first fibronectin type III repeat (FN1) that is critical for the polysialylation of N-glycans on the adjacent immunoglobulin domain (Ig5). We have also identified a polysialyltransferase (polyST) polybasic region (PBR) that may mediate substrate recognition. However, a direct interaction between the NCAM FN1 acidic patch and the polyST PBR has yet to be demonstrated. Here, we have probed this interaction using isothermal titration calorimetry and nuclear magnetic resonance (NMR) spectroscopy. We observe direct and specific binding between FN1 and the PBR peptide that is dependent upon acidic residues in FN1 and basic residues of the PBR. NMR titration experiments verified the role of the FN1 acidic patch in the recognition of the PBR and suggest a conformational change of the Ig5-FN1 linker region following binding of the PBR to the acidic patch. Finally, mutation of residues identified by NMR titration experiments impacts NCAM polysialylation, supporting their mechanistic role in protein-specific polysialylation.

Incorporating deep learning with convolutional neural networks and position specific scoring matrices for identifying electron transport proteins.

PubMed

Le, Nguyen-Quoc-Khanh; Ho, Quang-Thai; Ou, Yu-Yen

2017-09-05

In several years, deep learning is a modern machine learning technique using in a variety of fields with state-of-the-art performance. Therefore, utilization of deep learning to enhance performance is also an important solution for current bioinformatics field. In this study, we try to use deep learning via convolutional neural networks and position specific scoring matrices to identify electron transport proteins, which is an important molecular function in transmembrane proteins. Our deep learning method can approach a precise model for identifying of electron transport proteins with achieved sensitivity of 80.3%, specificity of 94.4%, and accuracy of 92.3%, with MCC of 0.71 for independent dataset. The proposed technique can serve as a powerful tool for identifying electron transport proteins and can help biologists understand the function of the electron transport proteins. Moreover, this study provides a basis for further research that can enrich a field of applying deep learning in bioinformatics. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Psychophysiology of neural, cognitive and affective integration: fMRI and autonomic indicants

PubMed Central

Critchley, Hugo D.

2009-01-01

Behaviour is shaped by environmental challenge in the context of homoeostatic need. Emotional and cognitive processes evoke patterned changes in bodily state that may signal emotional state to others. This dynamic modulation of visceral state is neurally mediated by sympathetic and parasympathetic divisions of the autonomic nervous system. Moreover neural afferents convey representations of the internal state of the body back to the brain to further influence emotion and cognition. Neuroimaging and lesion studies implicate specific regions of limbic forebrain in the behavioural generation of autonomic arousal states. Activity within these regions may predict emotion-specific autonomic response patterns within and between bodily organs, with implications for psychosomatic medicine. Feedback from the viscera is mapped hierarchically in the brain to influence efferent signals, and ultimately at the cortical level to engender and reinforce affective responses and subjective feeling states. Again neuroimaging and patient studies suggest discrete neural substrates for these representations, notably regions of insula and orbitofrontal cortex. Individual differences in conscious access to these interoceptive representations predict differences in emotional experience, but equally the misperception of heightened arousal level may evoke changes in emotional behaviour through engagement of the same neural centres. Perturbation of feedback may impair emotional reactivity and, in the context of inflammatory states give rise to cognitive, affective and psychomotor expressions of illness. Changes in visceral state during emotion may be mirrored in the responses of others, permitting a corresponding representation in the observer. The degree to which individuals are susceptible to this ‘contagion’ predicts individual differences in questionnaire ratings of empathy. Together these neuroimaging and clinical studies highlight the dynamic relationship between mind and body and

At the interface: convergence of neural regeneration and neural prostheses for restoration of function.

PubMed

Grill, W M; McDonald, J W; Peckham, P H; Heetderks, W; Kocsis, J; Weinrich, M

2001-01-01

The rapid pace of recent advances in development and application of electrical stimulation of the nervous system and in neural regeneration has created opportunities to combine these two approaches to restoration of function. This paper relates the discussion on this topic from a workshop at the International Functional Electrical Stimulation Society. The goals of this workshop were to discuss the current state of interaction between the fields of neural regeneration and neural prostheses and to identify potential areas of future research that would have the greatest impact on achieving the common goal of restoring function after neurological damage. Identified areas include enhancement of axonal regeneration with applied electric fields, development of hybrid neural interfaces combining synthetic silicon and biologically derived elements, and investigation of the role of patterned neural activity in regulating various neuronal processes and neurorehabilitation. Increased communication and cooperation between the two communities and recognition by each field that the other has something to contribute to their efforts are needed to take advantage of these opportunities. In addition, creative grants combining the two approaches and more flexible funding mechanisms to support the convergence of their perspectives are necessary to achieve common objectives.

Hierarchical modeling of molecular energies using a deep neural network

NASA Astrophysics Data System (ADS)

Lubbers, Nicholas; Smith, Justin S.; Barros, Kipton

2018-06-01

We introduce the Hierarchically Interacting Particle Neural Network (HIP-NN) to model molecular properties from datasets of quantum calculations. Inspired by a many-body expansion, HIP-NN decomposes properties, such as energy, as a sum over hierarchical terms. These terms are generated from a neural network—a composition of many nonlinear transformations—acting on a representation of the molecule. HIP-NN achieves the state-of-the-art performance on a dataset of 131k ground state organic molecules and predicts energies with 0.26 kcal/mol mean absolute error. With minimal tuning, our model is also competitive on a dataset of molecular dynamics trajectories. In addition to enabling accurate energy predictions, the hierarchical structure of HIP-NN helps to identify regions of model uncertainty.

Neural Correlates of Sexual Cue Reactivity in Individuals with and without Compulsive Sexual Behaviours

PubMed Central

Voon, Valerie; Mole, Thomas B.; Banca, Paula; Porter, Laura; Morris, Laurel; Mitchell, Simon; Lapa, Tatyana R.; Karr, Judy; Harrison, Neil A.; Potenza, Marc N.; Irvine, Michael

2014-01-01

Although compulsive sexual behaviour (CSB) has been conceptualized as a “behavioural” addiction and common or overlapping neural circuits may govern the processing of natural and drug rewards, little is known regarding the responses to sexually explicit materials in individuals with and without CSB. Here, the processing of cues of varying sexual content was assessed in individuals with and without CSB, focusing on neural regions identified in prior studies of drug-cue reactivity. 19 CSB subjects and 19 healthy volunteers were assessed using functional MRI comparing sexually explicit videos with non-sexual exciting videos. Ratings of sexual desire and liking were obtained. Relative to healthy volunteers, CSB subjects had greater desire but similar liking scores in response to the sexually explicit videos. Exposure to sexually explicit cues in CSB compared to non-CSB subjects was associated with activation of the dorsal anterior cingulate, ventral striatum and amygdala. Functional connectivity of the dorsal anterior cingulate-ventral striatum-amygdala network was associated with subjective sexual desire (but not liking) to a greater degree in CSB relative to non-CSB subjects. The dissociation between desire or wanting and liking is consistent with theories of incentive motivation underlying CSB as in drug addictions. Neural differences in the processing of sexual-cue reactivity were identified in CSB subjects in regions previously implicated in drug-cue reactivity studies. The greater engagement of corticostriatal limbic circuitry in CSB following exposure to sexual cues suggests neural mechanisms underlying CSB and potential biological targets for interventions. PMID:25013940

Estimates of global and regional prevalence of neural tube defects for 2015: a systematic analysis.

PubMed

Blencowe, Hannah; Kancherla, Vijaya; Moorthie, Sowmiya; Darlison, Matthew W; Modell, Bernadette

2018-02-01

Neural tube defects (NTDs) are associated with substantial mortality, morbidity, disability, and psychological and economic costs. Many are preventable with folic acid, and access to appropriate services for those affected can improve survival and quality of life. We used a compartmental model to estimate global and regional birth prevalence of NTDs (live births, stillbirths, and elective terminations of pregnancy) and subsequent under-5 mortality. Data were identified through web-based reviews of birth defect registry databases and systematic literature reviews. Meta-analyses were undertaken where appropriate. For 2015, our model estimated 260,100 (uncertainty interval (UI): 213,800-322,000) NTD-affected birth outcomes worldwide (prevalence 18.6 (15.3-23.0)/10,000 live births). Approximately 50% of cases were elective terminations of pregnancy for fetal anomalies (UI: 59,300 (47,900-74,500)) or stillbirths (57,800 (UI: 35,000-88,600)). Of NTD-affected live births, 117,900 (∼75%) (UI: 105,500-186,600) resulted in under-5 deaths. Our systematic review showed a paucity of high-quality data in the regions of the world with the highest burden. Despite knowledge about prevention, NTDs remain highly prevalent worldwide. Lack of surveillance and incomplete ascertainment of affected pregnancies make NTDs invisible to policy makers. Improved surveillance of all adverse outcomes is needed to improve the robustness of total NTD prevalence estimation, evaluate effectiveness of prevention through folic acid fortification, and improve outcomes through care and rehabilitation. © 2018 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals Inc. on behalf of New York Academy of Sciences.

DeepMoon: Convolutional neural network trainer to identify moon craters

NASA Astrophysics Data System (ADS)

Silburt, Ari; Zhu, Chenchong; Ali-Dib, Mohamad; Menou, Kristen; Jackson, Alan

2018-05-01

DeepMoon trains a convolutional neural net using data derived from a global digital elevation map (DEM) and catalog of craters to recognize craters on the Moon. The TensorFlow-based pipeline code is divided into three parts. The first generates a set images of the Moon randomly cropped from the DEM, with corresponding crater positions and radii. The second trains a convnet using this data, and the third validates the convnet's predictions.

Neural bases of ingroup altruistic motivation in soccer fans.

PubMed

Bortolini, Tiago; Bado, Patrícia; Hoefle, Sebastian; Engel, Annerose; Zahn, Roland; de Oliveira Souza, Ricardo; Dreher, Jean-Claude; Moll, Jorge

2017-11-23

Humans have a strong need to belong to social groups and a natural inclination to benefit ingroup members. Although the psychological mechanisms behind human prosociality have extensively been studied, the specific neural systems bridging group belongingness and altruistic motivation remain to be identified. Here, we used soccer fandom as an ecological framing of group membership to investigate the neural mechanisms underlying ingroup altruistic behaviour in male fans using event-related functional magnetic resonance. We designed an effort measure based on handgrip strength to assess the motivation to earn money (i) for oneself, (ii) for anonymous ingroup fans, or (iii) for a neutral group of anonymous non-fans. While overlapping valuation signals in the medial orbitofrontal cortex (mOFC) were observed for the three conditions, the subgenual cingulate cortex (SCC) exhibited increased functional connectivity with the mOFC as well as stronger hemodynamic responses for ingroup versus outgroup decisions. These findings indicate a key role for the SCC, a region previously implicated in altruistic decisions and group affiliation, in dovetailing altruistic motivations with neural valuation systems in real-life ingroup behaviour.

The challenges of neural mind-reading paradigms.

PubMed

Vilarroya, Oscar

2013-01-01

Neural mind-reading studies, based on multivariate pattern analysis (MVPA) methods, are providing exciting new studies. Some of the results obtained with these paradigms have raised high expectations, such as the possibility of creating brain reading devices. However, such hopes are based on the assumptions that: (a) the BOLD signal is a marker of neural activity; (b) the BOLD pattern identified by a MVPA is a neurally sound pattern; (c) the MVPA's feature space is a good mapping of the neural representation of a stimulus, and (d) the pattern identified by a MVPA corresponds to a representation. I examine here the challenges that still have to be met before fully accepting such assumptions.

Neural correlates of efficacy of voice therapy in Parkinson's disease identified by performance-correlation analysis.

PubMed

Narayana, Shalini; Fox, Peter T; Zhang, Wei; Franklin, Crystal; Robin, Donald A; Vogel, Deanie; Ramig, Lorraine O

2010-02-01

LSVT LOUD (Lee Silverman Voice Treatment) is efficacious in the treatment of speech disorders in idiopathic Parkinson's disease (IPD), particularly hypophonia. Functional imaging in patients with IPD has shown abnormalities in several speech regions and changes in these areas immediately following treatment. This study serves to extend the analysis by correlating changes of regional neural activity with the main behavioral change following treatment, namely, increased vocal intensity. Ten IPD participants with hypophonia were studied before and after LSVT LOUD. Cerebral blood flow during rest and reading conditions were measured by H(2)(15)O-positron emission tomography. Z-score images were generated by contrasting reading with rest conditions for pre- and post-LSVT LOUD sessions. Neuronal activity during reading in the pre- versus post-LSVT LOUD contrast was correlated with corresponding change in vocal intensity to generate correlation images. Behaviorally, vocal intensity for speech tasks increased significantly after LSVT LOUD. The contrast and correlation analyses indicate a treatment-dependent shift to the right hemisphere with modification in the speech motor regions as well as in prefrontal and temporal areas. We interpret the modification of activity in these regions to be a top-down effect of LSVT LOUD. The absence of an effect of LSVT LOUD on the basal ganglion supports this argument. Our findings indicate that the therapeutic effect of LSVT LOUD in IPD hypophonia results from a shift in cortical activity to the right hemisphere. These findings demonstrate that the short-term changes in the speech motor and multimodal integration areas can occur in a top-down manner. (c) 2009 Wiley-Liss, Inc.

Distinctive and common neural underpinnings of major depression, social anxiety, and their comorbidity

PubMed Central

Chen, Michael C.; Waugh, Christian E.; Joormann, Jutta; Gotlib, Ian H.

2015-01-01

Assessing neural commonalities and differences among depression, anxiety and their comorbidity is critical in developing a more integrative clinical neuroscience and in evaluating currently debated categorical vs dimensional approaches to psychiatric classification. Therefore, in this study, we sought to identify patterns of anomalous neural responding to criticism and praise that are specific to and common among major depressive disorder (MDD), social anxiety disorder (SAD) and comorbid MDD-SAD. Adult females who met formal diagnostic criteria for MDD, SAD or MDD-SAD and psychiatrically healthy participants underwent functional magnetic resonance imaging as they listened to statements directing praise or criticism at them or at another person. MDD groups showed reduced responding to praise across a distributed cortical network, an effect potentially mediated by thalamic nuclei undergirding arousal-mediated attention. SAD groups showed heightened anterior insula and decreased default-mode network response to criticism. The MDD-SAD group uniquely showed reduced responding to praise in the dorsal anterior cingulate cortex. Finally, all groups with psychopathology showed heightened response to criticism in a region of the superior frontal gyrus implicated in attentional gating. The present results suggest novel neural models of anhedonia in MDD, vigilance-withdrawal behaviors in SAD, and poorer outcome in MDD-SAD. Importantly, in identifying unique and common neural substrates of MDD and SAD, these results support a formulation in which common neural components represent general risk factors for psychopathology that, due to factors that are present at illness onset, lead to distinct forms of psychopathology with unique neural signatures. PMID:25038225

A Neural Network Approach for Identifying Particle Pitch Angle Distributions in Van Allen Probes Data

NASA Technical Reports Server (NTRS)

Souza, V. M.; Vieira, L. E. A.; Medeiros, C.; Da Silva, L. A.; Alves, L. R.; Koga, D.; Sibeck, D. G.; Walsh, B. M.; Kanekal, S. G.; Jauer, P. R.;

Neural Responses to Meaningless Pseudosigns: Evidence for Sign-Based Phonetic Processing in Superior Temporal Cortex

ERIC Educational Resources Information Center

Emmorey, Karen; Xu, Jiang; Braun, Allen

2011-01-01

To identify neural regions that automatically respond to linguistically structured, but meaningless manual gestures, 14 deaf native users of American Sign Language (ASL) and 14 hearing non-signers passively viewed pseudosigns (possible but non-existent ASL signs) and non-iconic ASL signs, in addition to a fixation baseline. For the contrast…

A neural measure of behavioral engagement: task-residual low-frequency blood oxygenation level-dependent activity in the precuneus.

PubMed

Zhang, Sheng; Li, Chiang-Shan Ray

2010-01-15

Brain imaging has provided a useful tool to examine the neural processes underlying human cognition. A critical question is whether and how task engagement influences the observed regional brain activations. Here we highlighted this issue and derived a neural measure of task engagement from the task-residual low-frequency blood oxygenation level-dependent (BOLD) activity in the precuneus. Using independent component analysis, we identified brain regions in the default circuit - including the precuneus and medial prefrontal cortex (mPFC) - showing greater activation during resting as compared to task residuals in 33 individuals. Time series correlations with the posterior cingulate cortex as the seed region showed that connectivity with the precuneus was significantly stronger during resting as compared to task residuals. We hypothesized that if the task-residual BOLD activity in the precuneus reflects engagement, it should account for a certain amount of variance in task-related regional brain activation. In an additional experiment of 59 individuals performing a stop signal task, we observed that the fractional amplitude of low-frequency fluctuation (fALFF) of the precuneus but not the mPFC accounted for approximately 10% of the variance in prefrontal activation related to attentional monitoring and response inhibition. Taken together, these results suggest that task-residual fALFF in the precuneus may be a potential indicator of task engagement. This measurement may serve as a useful covariate in identifying motivation-independent neural processes that underlie the pathogenesis of a psychiatric or neurological condition.

Neural priming in human frontal cortex: multiple forms of learning reduce demands on the prefrontal executive system.

PubMed

Race, Elizabeth A; Shanker, Shanti; Wagner, Anthony D

2009-09-01

Past experience is hypothesized to reduce computational demands in PFC by providing bottom-up predictive information that informs subsequent stimulus-action mapping. The present fMRI study measured cortical activity reductions ("neural priming"/"repetition suppression") during repeated stimulus classification to investigate the mechanisms through which learning from the past decreases demands on the prefrontal executive system. Manipulation of learning at three levels of representation-stimulus, decision, and response-revealed dissociable neural priming effects in distinct frontotemporal regions, supporting a multiprocess model of neural priming. Critically, three distinct patterns of neural priming were identified in lateral frontal cortex, indicating that frontal computational demands are reduced by three forms of learning: (a) cortical tuning of stimulus-specific representations, (b) retrieval of learned stimulus-decision mappings, and (c) retrieval of learned stimulus-response mappings. The topographic distribution of these neural priming effects suggests a rostrocaudal organization of executive function in lateral frontal cortex.

Neural Representations of Physics Concepts.

PubMed

Mason, Robert A; Just, Marcel Adam

2016-06-01

We used functional MRI (fMRI) to assess neural representations of physics concepts (momentum, energy, etc.) in juniors, seniors, and graduate students majoring in physics or engineering. Our goal was to identify the underlying neural dimensions of these representations. Using factor analysis to reduce the number of dimensions of activation, we obtained four physics-related factors that were mapped to sets of voxels. The four factors were interpretable as causal motion visualization, periodicity, algebraic form, and energy flow. The individual concepts were identifiable from their fMRI signatures with a mean rank accuracy of .75 using a machine-learning (multivoxel) classifier. Furthermore, there was commonality in participants' neural representation of physics; a classifier trained on data from all but one participant identified the concepts in the left-out participant (mean accuracy = .71 across all nine participant samples). The findings indicate that abstract scientific concepts acquired in an educational setting evoke activation patterns that are identifiable and common, indicating that science education builds abstract knowledge using inherent, repurposed brain systems. © The Author(s) 2016.

Getting the word out: neural correlates of enthusiastic message propagation.

PubMed

Falk, Emily B; O'Donnell, Matthew Brook; Lieberman, Matthew D

2012-01-01

What happens in the mind of a person who first hears a potentially exciting idea?We examined the neural precursors of spreading ideas with enthusiasm, and dissected enthusiasm into component processes that can be identified through automated linguistic analysis, gestalt human ratings of combined linguistic and non-verbal cues, and points of convergence/divergence between the two. We combined tools from natural language processing (NLP) with data gathered using fMRI to link the neurocognitive mechanisms that are set in motion during initial exposure to ideas and subsequent behaviors of these message communicators outside of the scanner. Participants' neural activity was recorded as they reviewed ideas for potential television show pilots. Participants' language from video-taped interviews collected post-scan was transcribed and given to an automated linguistic sentiment analysis (SA) classifier, which returned ratings for evaluative language (evaluative vs. descriptive) and valence (positive vs. negative). Separately, human coders rated the enthusiasm with which participants transmitted each idea. More positive sentiment ratings by the automated classifier were associated with activation in neural regions including medial prefrontal cortex; MPFC, precuneus/posterior cingulate cortex; PC/PCC, and medial temporal lobe; MTL. More evaluative, positive, descriptions were associated exclusively with neural activity in temporal-parietal junction (TPJ). Finally, human ratings indicative of more enthusiastic sentiment were associated with activation across these regions (MPFC, PC/PCC, DMPFC, TPJ, and MTL) as well as in ventral striatum (VS), inferior parietal lobule and premotor cortex. Taken together, these data demonstrate novel links between neural activity during initial idea encoding and the enthusiasm with which the ideas are subsequently delivered. This research lays the groundwork to use machine learning and neuroimaging data to study word of mouth communication and

Getting the word out: neural correlates of enthusiastic message propagation

PubMed Central

Falk, Emily B.; O'Donnell, Matthew Brook; Lieberman, Matthew D.

2012-01-01

What happens in the mind of a person who first hears a potentially exciting idea?We examined the neural precursors of spreading ideas with enthusiasm, and dissected enthusiasm into component processes that can be identified through automated linguistic analysis, gestalt human ratings of combined linguistic and non-verbal cues, and points of convergence/divergence between the two. We combined tools from natural language processing (NLP) with data gathered using fMRI to link the neurocognitive mechanisms that are set in motion during initial exposure to ideas and subsequent behaviors of these message communicators outside of the scanner. Participants' neural activity was recorded as they reviewed ideas for potential television show pilots. Participants' language from video-taped interviews collected post-scan was transcribed and given to an automated linguistic sentiment analysis (SA) classifier, which returned ratings for evaluative language (evaluative vs. descriptive) and valence (positive vs. negative). Separately, human coders rated the enthusiasm with which participants transmitted each idea. More positive sentiment ratings by the automated classifier were associated with activation in neural regions including medial prefrontal cortex; MPFC, precuneus/posterior cingulate cortex; PC/PCC, and medial temporal lobe; MTL. More evaluative, positive, descriptions were associated exclusively with neural activity in temporal-parietal junction (TPJ). Finally, human ratings indicative of more enthusiastic sentiment were associated with activation across these regions (MPFC, PC/PCC, DMPFC, TPJ, and MTL) as well as in ventral striatum (VS), inferior parietal lobule and premotor cortex. Taken together, these data demonstrate novel links between neural activity during initial idea encoding and the enthusiasm with which the ideas are subsequently delivered. This research lays the groundwork to use machine learning and neuroimaging data to study word of mouth communication and

Adolescents' emotional competence is associated with parents' neural sensitivity to emotions.

PubMed

Telzer, Eva H; Qu, Yang; Goldenberg, Diane; Fuligni, Andrew J; Galván, Adriana; Lieberman, Matthew D

2014-01-01

An essential component of youths' successful development is learning to appropriately respond to emotions, including the ability to recognize, identify, and describe one's feelings. Such emotional competence is thought to arise through the parent-child relationship. Yet, the mechanisms by which parents transmit emotional competence to their children are difficult to measure because they are often implicit, idiosyncratic, and not easily articulated by parents or children. In the current study, we used a multifaceted approach that went beyond self-report measures and examined whether parental neural sensitivity to emotions predicted their child's emotional competence. Twenty-two adolescent-parent dyads completed an fMRI scan during which they labeled the emotional expressions of negatively valenced faces. Results indicate that parents who recruited the amygdala, VLPFC, and brain regions involved in mentalizing (i.e., inferring others' emotional states) had adolescent children with greater emotional competence. These results held after controlling for parents' self-reports of emotional expressivity and adolescents' self-reports of the warmth and support of their parent relationships. In addition, adolescents recruited neural regions involved in mentalizing during affect labeling, which significantly mediated the associated between parental neural sensitivity and adolescents' emotional competence, suggesting that youth are modeling or referencing their parents' emotional profiles, thereby contributing to better emotional competence.

Adolescents’ emotional competence is associated with parents’ neural sensitivity to emotions

PubMed Central

Telzer, Eva H.; Qu, Yang; Goldenberg, Diane; Fuligni, Andrew J.; Galván, Adriana; Lieberman, Matthew D.

2014-01-01

An essential component of youths’ successful development is learning to appropriately respond to emotions, including the ability to recognize, identify, and describe one’s feelings. Such emotional competence is thought to arise through the parent–child relationship. Yet, the mechanisms by which parents transmit emotional competence to their children are difficult to measure because they are often implicit, idiosyncratic, and not easily articulated by parents or children. In the current study, we used a multifaceted approach that went beyond self-report measures and examined whether parental neural sensitivity to emotions predicted their child’s emotional competence. Twenty-two adolescent–parent dyads completed an fMRI scan during which they labeled the emotional expressions of negatively valenced faces. Results indicate that parents who recruited the amygdala, VLPFC, and brain regions involved in mentalizing (i.e., inferring others’ emotional states) had adolescent children with greater emotional competence. These results held after controlling for parents’ self-reports of emotional expressivity and adolescents’ self-reports of the warmth and support of their parent relationships. In addition, adolescents recruited neural regions involved in mentalizing during affect labeling, which significantly mediated the associated between parental neural sensitivity and adolescents’ emotional competence, suggesting that youth are modeling or referencing their parents’ emotional profiles, thereby contributing to better emotional competence. PMID:25100982

Computing with Neural Synchrony

PubMed Central

Brette, Romain

2012-01-01

Neurons communicate primarily with spikes, but most theories of neural computation are based on firing rates. Yet, many experimental observations suggest that the temporal coordination of spikes plays a role in sensory processing. Among potential spike-based codes, synchrony appears as a good candidate because neural firing and plasticity are sensitive to fine input correlations. However, it is unclear what role synchrony may play in neural computation, and what functional advantage it may provide. With a theoretical approach, I show that the computational interest of neural synchrony appears when neurons have heterogeneous properties. In this context, the relationship between stimuli and neural synchrony is captured by the concept of synchrony receptive field, the set of stimuli which induce synchronous responses in a group of neurons. In a heterogeneous neural population, it appears that synchrony patterns represent structure or sensory invariants in stimuli, which can then be detected by postsynaptic neurons. The required neural circuitry can spontaneously emerge with spike-timing-dependent plasticity. Using examples in different sensory modalities, I show that this allows simple neural circuits to extract relevant information from realistic sensory stimuli, for example to identify a fluctuating odor in the presence of distractors. This theory of synchrony-based computation shows that relative spike timing may indeed have computational relevance, and suggests new types of neural network models for sensory processing with appealing computational properties. PMID:22719243

NeuroMEMS: Neural Probe Microtechnologies

PubMed Central

HajjHassan, Mohamad; Chodavarapu, Vamsy; Musallam, Sam

2008-01-01

Neural probe technologies have already had a significant positive effect on our understanding of the brain by revealing the functioning of networks of biological neurons. Probes are implanted in different areas of the brain to record and/or stimulate specific sites in the brain. Neural probes are currently used in many clinical settings for diagnosis of brain diseases such as seizers, epilepsy, migraine, Alzheimer's, and dementia. We find these devices assisting paralyzed patients by allowing them to operate computers or robots using their neural activity. In recent years, probe technologies were assisted by rapid advancements in microfabrication and microelectronic technologies and thus are enabling highly functional and robust neural probes which are opening new and exciting avenues in neural sciences and brain machine interfaces. With a wide variety of probes that have been designed, fabricated, and tested to date, this review aims to provide an overview of the advances and recent progress in the microfabrication techniques of neural probes. In addition, we aim to highlight the challenges faced in developing and implementing ultra-long multi-site recording probes that are needed to monitor neural activity from deeper regions in the brain. Finally, we review techniques that can improve the biocompatibility of the neural probes to minimize the immune response and encourage neural growth around the electrodes for long term implantation studies. PMID:27873894

Discrete Neural Signatures of Basic Emotions.

PubMed

Saarimäki, Heini; Gotsopoulos, Athanasios; Jääskeläinen, Iiro P; Lampinen, Jouko; Vuilleumier, Patrik; Hari, Riitta; Sams, Mikko; Nummenmaa, Lauri

2016-06-01

Categorical models of emotions posit neurally and physiologically distinct human basic emotions. We tested this assumption by using multivariate pattern analysis (MVPA) to classify brain activity patterns of 6 basic emotions (disgust, fear, happiness, sadness, anger, and surprise) in 3 experiments. Emotions were induced with short movies or mental imagery during functional magnetic resonance imaging. MVPA accurately classified emotions induced by both methods, and the classification generalized from one induction condition to another and across individuals. Brain regions contributing most to the classification accuracy included medial and inferior lateral prefrontal cortices, frontal pole, precentral and postcentral gyri, precuneus, and posterior cingulate cortex. Thus, specific neural signatures across these regions hold representations of different emotional states in multimodal fashion, independently of how the emotions are induced. Similarity of subjective experiences between emotions was associated with similarity of neural patterns for the same emotions, suggesting a direct link between activity in these brain regions and the subjective emotional experience. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Parameter identifiability and regional calibration for reservoir inflow prediction

NASA Astrophysics Data System (ADS)

Kolberg, Sjur; Engeland, Kolbjørn; Tøfte, Lena S.; Bruland, Oddbjørn

2013-04-01

The large hydropower producer Statkraft is currently testing regional, distributed models for operational reservoir inflow prediction. The need for simultaneous forecasts and consistent updating in a large number of catchments supports the shift from catchment-oriented to regional models. Low-quality naturalized inflow series in the reservoir catchments further encourages the use of donor catchments and regional simulation for calibration purposes. MCMC based parameter estimation (the Dream algorithm; Vrugt et al, 2009) is adapted to regional parameter estimation, and implemented within the open source ENKI framework. The likelihood is based on the concept of effectively independent number of observations, spatially as well as in time. Marginal and conditional (around an optimum) parameter distributions for each catchment may be extracted, even though the MCMC algorithm itself is guided only by the regional likelihood surface. Early results indicate that the average performance loss associated with regional calibration (difference in Nash-Sutcliffe R2 between regionally and locally optimal parameters) is in the range of 0.06. The importance of the seasonal snow storage and melt in Norwegian mountain catchments probably contributes to the high degree of similarity among catchments. The evaluation continues for several regions, focusing on posterior parameter uncertainty and identifiability. Vrugt, J. A., C. J. F. ter Braak, C. G. H. Diks, B. A. Robinson, J. M. Hyman and D. Higdon: Accelerating Markov Chain Monte Carlo Simulation by Differential Evolution with Self-Adaptive Randomized Subspace Sampling. Int. J. of nonlinear sciences and numerical simulation 10, 3, 273-290, 2009.

The neural correlates of reciprocity are sensitive to prior experience of reciprocity.

PubMed

Cáceda, Ricardo; Prendes-Alvarez, Stefania; Hsu, Jung-Jiin; Tripathi, Shanti P; Kilts, Clint D; James, G Andrew

2017-08-14

Reciprocity is central to human relationships and is strongly influenced by multiple factors including the nature of social exchanges and their attendant emotional reactions. Despite recent advances in the field, the neural processes involved in this modulation of reciprocal behavior by ongoing social interaction are poorly understood. We hypothesized that activity within a discrete set of neural networks including a putative moral cognitive neural network is associated with reciprocity behavior. Nineteen healthy adults underwent functional magnetic resonance imaging scanning while playing the trustee role in the Trust Game. Personality traits and moral development were assessed. Independent component analysis was used to identify task-related functional brain networks and assess their relationship to behavior. The saliency network (insula and anterior cingulate) was positively correlated with reciprocity behavior. A consistent array of brain regions supports the engagement of emotional, self-referential and planning processes during social reciprocity behavior. Published by Elsevier B.V.

A mixture neural net for multispectral imaging spectrometer processing

NASA Technical Reports Server (NTRS)

Casasent, David; Slagle, Timothy

1990-01-01

Each spatial region viewed by an imaging spectrometer contains various elements in a mixture. The elements present and the amount of each are to be determined. A neural net solution is considered. Initial optical neural net hardware is described. The first simulations on the component requirements of a neural net are considered. The pseudoinverse solution is shown to not suffice, i.e. a neural net solution is required.

A pathway linking reward circuitry, impulsive sensation-seeking and risky decision-making in young adults: identifying neural markers for new interventions

PubMed Central

Chase, H W; Fournier, J C; Bertocci, M A; Greenberg, T; Aslam, H; Stiffler, R; Lockovich, J; Graur, S; Bebko, G; Forbes, E E; Phillips, M L

2017-01-01

High trait impulsive sensation seeking (ISS) is common in 18–25-year olds, and is associated with risky decision-making and deleterious outcomes. We examined relationships among: activity in reward regions previously associated with ISS during an ISS-relevant context, uncertain reward expectancy (RE), using fMRI; ISS impulsivity and sensation-seeking subcomponents; and risky decision-making in 100, transdiagnostically recruited 18–25-year olds. ISS, anhedonia, anxiety, depression and mania were measured using self-report scales; clinician-administered scales also assessed the latter four. A post-scan risky decision-making task measured ‘risky' (possible win/loss/mixed/neutral) fMRI-task versus ‘sure thing' stimuli. ‘Bias' reflected risky over safe choices. Uncertain RE-related activity in left ventrolateral prefrontal cortex and bilateral ventral striatum was positively associated with an ISS composite score, comprising impulsivity and sensation-seeking–fun-seeking subcomponents (ISSc; P⩽0.001). Bias positively associated with sensation seeking–experience seeking (ES; P=0.003). This relationship was moderated by ISSc (P=0.009): it was evident only in high ISSc individuals. Whole-brain analyses showed a positive relationship between: uncertain RE-related left ventrolateral prefrontal cortical activity and ISSc; uncertain RE-related visual attention and motor preparation neural network activity and ES; and uncertain RE-related dorsal anterior cingulate cortical activity and bias, specifically in high ISSc participants (all ps<0.05, peak-level, family-wise error corrected). We identify an indirect pathway linking greater levels of uncertain RE-related activity in reward, visual attention and motor networks with greater risky decision-making, via positive relationships with impulsivity, fun seeking and ES. These objective neural markers of high ISS can guide new treatment developments for young adults with high levels of this debilitating personality

Identification of the subthalamic nucleus in deep brain stimulation surgery with a novel wavelet-derived measure of neural background activity

PubMed Central

Snellings, André; Sagher, Oren; Anderson, David J.; Aldridge, J. Wayne

2016-01-01

Object A wavelet-based measure was developed to quantitatively assess neural background activity taken during surgical neurophysiological recordings to localize the boundaries of the subthalamic nucleus during target localization for deep brain stimulator implant surgery. Methods Neural electrophysiological data was recorded from 14 patients (20 tracks, n = 275 individual recording sites) with dopamine-sensitive idiopathic Parkinson’s disease during the target localization portion of deep brain stimulator implant surgery. During intraoperative recording the STN was identified based upon audio and visual monitoring of neural firing patterns, kinesthetic tests, and comparisons between neural behavior and known characteristics of the target nucleus. The quantitative wavelet-based measure was applied off-line using MATLAB software to measure the magnitude of the neural background activity, and the results of this analysis were compared to the intraoperative conclusions. Wavelet-derived estimates were compared to power spectral density measures. Results The wavelet-derived background levels were significantly higher in regions encompassed by the clinically estimated boundaries of the STN than in surrounding regions (STN: 225 ± 61 μV vs. ventral to STN: 112 ± 32 μV, and dorsal to STN: 136 ± 66 μV). In every track, the absolute maximum magnitude was found within the clinically identified STN. The wavelet-derived background levels provided a more consistent index with less variability than power spectral density. Conclusions The wavelet-derived background activity assessor can be calculated quickly, requires no spike sorting, and can be reliably used to identify the STN with very little subjective interpretation required. This method may facilitate rapid intraoperative identification of subthalamic nucleus borders. PMID:19344225

NLEAP/GIS approach for identifying and mitigating regional nitrate-nitrogen leaching

USGS Publications Warehouse

Shaffer, M.J.; Hall, M.D.; Wylie, B.K.; Wagner, D.G.; Corwin, D.L.; Loague, K.

1996-01-01

Improved simulation-based methodology is needed to help identify broad geographical areas where potential NO3-N leaching may be occurring from agriculture and suggest management alternatives that minimize the problem. The Nitrate Leaching and Economic Analysis Package (NLEAP) model was applied to estimate regional NO3-N leaching in eastern Colorado. Results show that a combined NLEAP/GIS technology can be used to identify potential NO3-N hot spots in shallow alluvial aquifers under irrigated agriculture. The NLEAP NO3-N Leached (NL) index provided the most promising single index followed by NO3-N Available for Leaching (NAL). The same combined technology also shows promise in identifying Best Management Practice (BMP) methods that help minimize NO3-N leaching in vulnerable areas. Future plans call for linkage of the NLEAP/GIS procedures with groundwater modeling to establish a mechanistic analysis of agriculture-aquifer interactions at a regional scale.

Neural Correlates of Efficacy of Voice Therapy in Parkinson’s Disease Identified by Performance–Correlation Analysis

PubMed Central

Narayana, Shalini; Fox, Peter T.; Zhang, Wei; Franklin, Crystal; Robin, Donald A.; Vogel, Deanie; Ramig, Lorraine O.

2009-01-01

LSVT® LOUD (Lee Silverman Voice Treatment) is efficacious in the treatment of speech disorders in idiopathic Parkinson’s disease (IPD), particularly hypophonia. Functional imaging in patients with IPD has shown abnormalities in several speech regions and changes in these areas immediately following treatment. This study serves to extend the analysis by correlating changes of regional neural activity with the main behavioral change following treatment, namely, increased vocal intensity. Ten IPD participants with hypophonia were studied before and after LSVT LOUD. Cerebral blood flow during rest and reading conditions were measured by H215O-positron emission tomography. Z-score images were generated by contrasting reading with rest conditions for pre- and post-LSVT LOUD sessions. Neuronal activity during reading in the pre- versus post-LSVT LOUD contrast was correlated with corresponding change in vocal intensity to generate correlation images. Behaviorally, vocal intensity for speech tasks increased significantly after LSVT LOUD. The contrast and correlation analyses indicate a treatment-dependent shift to the right hemisphere with modification in the speech motor regions as well as in prefrontal and temporal areas. We interpret the modification of activity in these regions to be a top–down effect of LSVT LOUD. The absence of an effect of LSVT LOUD on the basal ganglion supports this argument. Our findings indicate that the therapeutic effect of LSVT LOUD in IPD hypophonia results from a shift in cortical activity to the right hemisphere. These findings demonstrate that the short-term changes in the speech motor and multimodal integration areas can occur in a top–down manner. PMID:19639554

Neural signatures of lexical tone reading.

PubMed

Kwok, Veronica P Y; Wang, Tianfu; Chen, Siping; Yakpo, Kofi; Zhu, Linlin; Fox, Peter T; Tan, Li Hai

2015-01-01

Research on how lexical tone is neuroanatomically represented in the human brain is central to our understanding of cortical regions subserving language. Past studies have exclusively focused on tone perception of the spoken language, and little is known as to the lexical tone processing in reading visual words and its associated brain mechanisms. In this study, we performed two experiments to identify neural substrates in Chinese tone reading. First, we used a tone judgment paradigm to investigate tone processing of visually presented Chinese characters. We found that, relative to baseline, tone perception of printed Chinese characters were mediated by strong brain activation in bilateral frontal regions, left inferior parietal lobule, left posterior middle/medial temporal gyrus, left inferior temporal region, bilateral visual systems, and cerebellum. Surprisingly, no activation was found in superior temporal regions, brain sites well known for speech tone processing. In activation likelihood estimation (ALE) meta-analysis to combine results of relevant published studies, we attempted to elucidate whether the left temporal cortex activities identified in Experiment one is consistent with those found in previous studies of auditory lexical tone perception. ALE results showed that only the left superior temporal gyrus and putamen were critical in auditory lexical tone processing. These findings suggest that activation in the superior temporal cortex associated with lexical tone perception is modality-dependent. © 2014 Wiley Periodicals, Inc.

Identifying regions of interest in medical images using self-organizing maps.

PubMed

Teng, Wei-Guang; Chang, Ping-Lin

2012-10-01

Advances in data acquisition, processing and visualization techniques have had a tremendous impact on medical imaging in recent years. However, the interpretation of medical images is still almost always performed by radiologists. Developments in artificial intelligence and image processing have shown the increasingly great potential of computer-aided diagnosis (CAD). Nevertheless, it has remained challenging to develop a general approach to process various commonly used types of medical images (e.g., X-ray, MRI, and ultrasound images). To facilitate diagnosis, we recommend the use of image segmentation to discover regions of interest (ROI) using self-organizing maps (SOM). We devise a two-stage SOM approach that can be used to precisely identify the dominant colors of a medical image and then segment it into several small regions. In addition, by appropriately conducting the recursive merging steps to merge smaller regions into larger ones, radiologists can usually identify one or more ROIs within a medical image.

The Causal Inference of Cortical Neural Networks during Music Improvisations

PubMed Central

Wan, Xiaogeng; Crüts, Björn; Jensen, Henrik Jeldtoft

2014-01-01

We present an EEG study of two music improvisation experiments. Professional musicians with high level of improvisation skills were asked to perform music either according to notes (composed music) or in improvisation. Each piece of music was performed in two different modes: strict mode and “let-go” mode. Synchronized EEG data was measured from both musicians and listeners. We used one of the most reliable causality measures: conditional Mutual Information from Mixed Embedding (MIME), to analyze directed correlations between different EEG channels, which was combined with network theory to construct both intra-brain and cross-brain networks. Differences were identified in intra-brain neural networks between composed music and improvisation and between strict mode and “let-go” mode. Particular brain regions such as frontal, parietal and temporal regions were found to play a key role in differentiating the brain activities between different playing conditions. By comparing the level of degree centralities in intra-brain neural networks, we found a difference between the response of musicians and the listeners when comparing the different playing conditions. PMID:25489852

The causal inference of cortical neural networks during music improvisations.

PubMed

Wan, Xiaogeng; Crüts, Björn; Jensen, Henrik Jeldtoft

2014-01-01

We present an EEG study of two music improvisation experiments. Professional musicians with high level of improvisation skills were asked to perform music either according to notes (composed music) or in improvisation. Each piece of music was performed in two different modes: strict mode and "let-go" mode. Synchronized EEG data was measured from both musicians and listeners. We used one of the most reliable causality measures: conditional Mutual Information from Mixed Embedding (MIME), to analyze directed correlations between different EEG channels, which was combined with network theory to construct both intra-brain and cross-brain networks. Differences were identified in intra-brain neural networks between composed music and improvisation and between strict mode and "let-go" mode. Particular brain regions such as frontal, parietal and temporal regions were found to play a key role in differentiating the brain activities between different playing conditions. By comparing the level of degree centralities in intra-brain neural networks, we found a difference between the response of musicians and the listeners when comparing the different playing conditions.

Neural reactivation links unconscious thought to decision-making performance

PubMed Central

Bursley, James K.; Satpute, Ajay B.

2013-01-01

Brief periods of unconscious thought (UT) have been shown to improve decision making compared with making an immediate decision (ID). We reveal a neural mechanism for UT in decision making using blood oxygen level-dependent (BOLD) functional magnetic resonance imaging. Participants (N = 33) encoded information on a set of consumer products (e.g. 48 attributes describing four different cars), and we manipulated whether participants (i) consciously thought about this information (conscious thought), (ii) completed a difficult 2-back working memory task (UT) or (iii) made an immediate decision about the consumer products (ID) in a within-subjects blocked design. To differentiate UT neural activity from 2-back working memory neural activity, participants completed an independent 2-back task and this neural activity was subtracted from neural activity occurring during the UT 2-back task. Consistent with a neural reactivation account, we found that the same regions activated during the encoding of complex decision information (right dorsolateral prefrontal cortex and left intermediate visual cortex) continued to be activated during a subsequent 2-min UT period. Moreover, neural reactivation in these regions was predictive of subsequent behavioral decision-making performance after the UT period. These results provide initial evidence for post-encoding unconscious neural reactivation in facilitating decision making. PMID:23314012

Neural reactivation links unconscious thought to decision-making performance.

PubMed

Creswell, John David; Bursley, James K; Satpute, Ajay B

2013-12-01

Brief periods of unconscious thought (UT) have been shown to improve decision making compared with making an immediate decision (ID). We reveal a neural mechanism for UT in decision making using blood oxygen level-dependent (BOLD) functional magnetic resonance imaging. Participants (N = 33) encoded information on a set of consumer products (e.g. 48 attributes describing four different cars), and we manipulated whether participants (i) consciously thought about this information (conscious thought), (ii) completed a difficult 2-back working memory task (UT) or (iii) made an immediate decision about the consumer products (ID) in a within-subjects blocked design. To differentiate UT neural activity from 2-back working memory neural activity, participants completed an independent 2-back task and this neural activity was subtracted from neural activity occurring during the UT 2-back task. Consistent with a neural reactivation account, we found that the same regions activated during the encoding of complex decision information (right dorsolateral prefrontal cortex and left intermediate visual cortex) continued to be activated during a subsequent 2-min UT period. Moreover, neural reactivation in these regions was predictive of subsequent behavioral decision-making performance after the UT period. These results provide initial evidence for post-encoding unconscious neural reactivation in facilitating decision making.

From Connectivity Models to Region Labels: Identifying Foci of a Neurological Disorder

PubMed Central

Venkataraman, Archana; Kubicki, Marek; Golland, Polina

2014-01-01

We propose a novel approach to identify the foci of a neurological disorder based on anatomical and functional connectivity information. Specifically, we formulate a generative model that characterizes the network of abnormal functional connectivity emanating from the affected foci. This allows us to aggregate pairwise connectivity changes into a region-based representation of the disease. We employ the variational expectation-maximization algorithm to fit the model and subsequently identify both the afflicted regions and the differences in connectivity induced by the disorder. We demonstrate our method on a population study of schizophrenia. PMID:23864168

Positive mood enhances reward-related neural activity

PubMed Central

Nusslock, Robin

2016-01-01

Although behavioral research has shown that positive mood leads to desired outcomes in nearly every major life domain, no studies have directly examined the effects of positive mood on the neural processes underlying reward-related affect and goal-directed behavior. To address this gap, participants in the present fMRI study experienced either a positive (n = 20) or neutral (n = 20) mood induction and subsequently completed a monetary incentive delay task that assessed reward and loss processing. Consistent with prediction, positive mood elevated activity specifically during reward anticipation in corticostriatal neural regions that have been implicated in reward processing and goal-directed behavior, including the nucleus accumbens, caudate, lateral orbitofrontal cortex and putamen, as well as related paralimbic regions, including the anterior insula and ventromedial prefrontal cortex. These effects were not observed during reward outcome, loss anticipation or loss outcome. Critically, this is the first study to report that positive mood enhances reward-related neural activity. Our findings have implications for uncovering the neural mechanisms by which positive mood enhances goal-directed behavior, understanding the malleability of reward-related neural activity, and developing targeted treatments for psychiatric disorders characterized by deficits in reward processing. PMID:26833919

Decoding the neural signatures of emotions expressed through sound.

PubMed

Sachs, Matthew E; Habibi, Assal; Damasio, Antonio; Kaplan, Jonas T

2018-07-01

Effective social functioning relies in part on the ability to identify emotions from auditory stimuli and respond appropriately. Previous studies have uncovered brain regions engaged by the affective information conveyed by sound. But some of the acoustical properties of sounds that express certain emotions vary remarkably with the instrument used to produce them, for example the human voice or a violin. Do these brain regions respond in the same way to different emotions regardless of the sound source? To address this question, we had participants (N = 38, 20 females) listen to brief audio excerpts produced by the violin, clarinet, and human voice, each conveying one of three target emotions-happiness, sadness, and fear-while brain activity was measured with fMRI. We used multivoxel pattern analysis to test whether emotion-specific neural responses to the voice could predict emotion-specific neural responses to musical instruments and vice-versa. A whole-brain searchlight analysis revealed that patterns of activity within the primary and secondary auditory cortex, posterior insula, and parietal operculum were predictive of the affective content of sound both within and across instruments. Furthermore, classification accuracy within the anterior insula was correlated with behavioral measures of empathy. The findings suggest that these brain regions carry emotion-specific patterns that generalize across sounds with different acoustical properties. Also, individuals with greater empathic ability have more distinct neural patterns related to perceiving emotions. These results extend previous knowledge regarding how the human brain extracts emotional meaning from auditory stimuli and enables us to understand and connect with others effectively. Copyright © 2018 Elsevier Inc. All rights reserved.

Coupled neural systems underlie the production and comprehension of naturalistic narrative speech

PubMed Central

Silbert, Lauren J.; Honey, Christopher J.; Simony, Erez; Poeppel, David; Hasson, Uri

2014-01-01

Neuroimaging studies of language have typically focused on either production or comprehension of single speech utterances such as syllables, words, or sentences. In this study we used a new approach to functional MRI acquisition and analysis to characterize the neural responses during production and comprehension of complex real-life speech. First, using a time-warp based intrasubject correlation method, we identified all areas that are reliably activated in the brains of speakers telling a 15-min-long narrative. Next, we identified areas that are reliably activated in the brains of listeners as they comprehended that same narrative. This allowed us to identify networks of brain regions specific to production and comprehension, as well as those that are shared between the two processes. The results indicate that production of a real-life narrative is not localized to the left hemisphere but recruits an extensive bilateral network, which overlaps extensively with the comprehension system. Moreover, by directly comparing the neural activity time courses during production and comprehension of the same narrative we were able to identify not only the spatial overlap of activity but also areas in which the neural activity is coupled across the speaker’s and listener’s brains during production and comprehension of the same narrative. We demonstrate widespread bilateral coupling between production- and comprehension-related processing within both linguistic and nonlinguistic areas, exposing the surprising extent of shared processes across the two systems. PMID:25267658

Neural net controller for inlet pressure control of rocket engine testing

NASA Technical Reports Server (NTRS)

Trevino, Luis C.

1994-01-01

Many dynamic systems operate in select operating regions, each exhibiting characteristic modes of behavior. It is traditional to employ standard adjustable gain proportional-integral-derivative (PID) loops in such systems where no apriori model information is available. However, for controlling inlet pressure for rocket engine testing, problems in fine tuning, disturbance accommodation, and control gains for new profile operating regions (for research and development) are typically encountered. Because of the capability of capturing I/O peculiarities, using NETS, a back propagation trained neural network is specified. For select operating regions, the neural network controller is simulated to be as robust as the PID controller. For a comparative analysis, the higher order moment neural array (HOMNA) method is used to specify a second neural controller by extracting critical exemplars from the I/O data set. Furthermore, using the critical exemplars from the HOMNA method, a third neural controller is developed using NETS back propagation algorithm. All controllers are benchmarked against each other.

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

Shared molecular networks in orofacial and neural tube development.

PubMed

Kousa, Youssef A; Mansour, Tamer A; Seada, Haitham; Matoo, Samaneh; Schutte, Brian C

2017-01-30

Single genetic variants can affect multiple tissues during development. Thus it is possible that disruption of shared gene regulatory networks might underlie syndromic presentations. In this study, we explore this idea through examination of two critical developmental programs that control orofacial and neural tube development and identify shared regulatory factors and networks. Identification of these networks has the potential to yield additional candidate genes for poorly understood developmental disorders and assist in modeling and perhaps managing risk factors to prevent morbidly and mortality. We reviewed the literature to identify genes common between orofacial and neural tube defects and development. We then conducted a bioinformatic analysis to identify shared molecular targets and pathways in the development of these tissues. Finally, we examine publicly available RNA-Seq data to identify which of these genes are expressed in both tissues during development. We identify common regulatory factors in orofacial and neural tube development. Pathway enrichment analysis shows that folate, cancer and hedgehog signaling pathways are shared in neural tube and orofacial development. Developing neural tissues differentially express mouse exencephaly and cleft palate genes, whereas developing orofacial tissues were enriched for both clefting and neural tube defect genes. These data suggest that key developmental factors and pathways are shared between orofacial and neural tube defects. We conclude that it might be most beneficial to focus on common regulatory factors and pathways to better understand pathology and develop preventative measures for these birth defects. Birth Defects Research 109:169-179, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Parental Socioeconomic Status and the Neural Basis of Arithmetic: Differential Relations to Verbal and Visuo-spatial Representations

PubMed Central

Demir, Özlem Ece; Prado, Jérôme; Booth, James R.

2015-01-01

We examined the relation of parental socioeconomic status (SES) to the neural bases of subtraction in school-age children (9- to 12-year-olds). We independently localized brain regions subserving verbal versus visuo-spatial representations to determine whether the parental SES-related differences in children’s reliance on these neural representations vary as a function of math skill. At higher SES levels, higher skill was associated with greater recruitment of the left temporal cortex, identified by the verbal localizer. At lower SES levels, higher skill was associated with greater recruitment of right parietal cortex, identified by the visuo-spatial localizer. This suggests that depending on parental SES, children engage different neural systems to solve subtraction problems. Furthermore, SES was related to the activation in the left temporal and frontal cortex during the independent verbal localizer task, but it was not related to activation during the independent visuo-spatial localizer task. Differences in activation during the verbal localizer task in turn were related to differences in activation during the subtraction task in right parietal cortex. The relation was stronger at lower SES levels. This result suggests that SES-related differences in the visuo-spatial regions during subtraction might be based in SES-related verbal differences. PMID:25664675

The neural correlates of dreaming

PubMed Central

Siclari, F.; Baird, B.; Perogamvros, L.; Bernardi, G.; LaRocque, J. J.; Riedner, B.; Boly, M.; Postle, B. R.; Tononi, G.

2017-01-01

Consciousness never fades during wake. However, if awakened from sleep, sometimes we report dreams and sometimes no experiences. Traditionally, dreaming has been identified with REM sleep, characterized by a wake-like, globally ‘activated’, high-frequency EEG. However, dreaming also occurs in NREM sleep, characterized by prominent low-frequency activity. This challenges our understanding of the neural correlates of conscious experiences in sleep. Using high-density EEG, we contrasted the presence and absence of dreaming within NREM and REM sleep. In both NREM and REM sleep, reports of dream experience were associated with a local decrease in low-frequency activity in posterior cortical regions. High-frequency activity within these regions correlated with specific dream contents. Monitoring this posterior ‘hot zone’ predicted whether an individual reported dreaming or the absence of experiences during NREM sleep in real time, suggesting that it may constitute a core correlate of conscious experiences in sleep. PMID:28394322

The neural correlates of dreaming.

PubMed

Siclari, Francesca; Baird, Benjamin; Perogamvros, Lampros; Bernardi, Giulio; LaRocque, Joshua J; Riedner, Brady; Boly, Melanie; Postle, Bradley R; Tononi, Giulio

2017-06-01

Consciousness never fades during waking. However, when awakened from sleep, we sometimes recall dreams and sometimes recall no experiences. Traditionally, dreaming has been identified with rapid eye-movement (REM) sleep, characterized by wake-like, globally 'activated', high-frequency electroencephalographic activity. However, dreaming also occurs in non-REM (NREM) sleep, characterized by prominent low-frequency activity. This challenges our understanding of the neural correlates of conscious experiences in sleep. Using high-density electroencephalography, we contrasted the presence and absence of dreaming in NREM and REM sleep. In both NREM and REM sleep, reports of dream experience were associated with local decreases in low-frequency activity in posterior cortical regions. High-frequency activity in these regions correlated with specific dream contents. Monitoring this posterior 'hot zone' in real time predicted whether an individual reported dreaming or the absence of dream experiences during NREM sleep, suggesting that it may constitute a core correlate of conscious experiences in sleep.

Distinctive and common neural underpinnings of major depression, social anxiety, and their comorbidity.

PubMed

Hamilton, J Paul; Chen, Michael C; Waugh, Christian E; Joormann, Jutta; Gotlib, Ian H

2015-04-01

Assessing neural commonalities and differences among depression, anxiety and their comorbidity is critical in developing a more integrative clinical neuroscience and in evaluating currently debated categorical vs dimensional approaches to psychiatric classification. Therefore, in this study, we sought to identify patterns of anomalous neural responding to criticism and praise that are specific to and common among major depressive disorder (MDD), social anxiety disorder (SAD) and comorbid MDD-SAD. Adult females who met formal diagnostic criteria for MDD, SAD or MDD-SAD and psychiatrically healthy participants underwent functional magnetic resonance imaging as they listened to statements directing praise or criticism at them or at another person. MDD groups showed reduced responding to praise across a distributed cortical network, an effect potentially mediated by thalamic nuclei undergirding arousal-mediated attention. SAD groups showed heightened anterior insula and decreased default-mode network response to criticism. The MDD-SAD group uniquely showed reduced responding to praise in the dorsal anterior cingulate cortex. Finally, all groups with psychopathology showed heightened response to criticism in a region of the superior frontal gyrus implicated in attentional gating. The present results suggest novel neural models of anhedonia in MDD, vigilance-withdrawal behaviors in SAD, and poorer outcome in MDD-SAD. Importantly, in identifying unique and common neural substrates of MDD and SAD, these results support a formulation in which common neural components represent general risk factors for psychopathology that, due to factors that are present at illness onset, lead to distinct forms of psychopathology with unique neural signatures. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

A differential neural response to threatening and non-threatening negative facial expressions in paranoid and non-paranoid schizophrenics.

PubMed

Phillips, M L; Williams, L; Senior, C; Bullmore, E T; Brammer, M J; Andrew, C; Williams, S C; David, A S

1999-11-08

Several studies have demonstrated impaired facial expression recognition in schizophrenia. Few have examined the neural basis for this; none have compared the neural correlates of facial expression perception in different schizophrenic patient subgroups. We compared neural responses to facial expressions in 10 right-handed schizophrenic patients (five paranoid and five non-paranoid) and five normal volunteers using functional Magnetic Resonance Imaging (fMRI). In three 5-min experiments, subjects viewed alternating 30-s blocks of black-and-white facial expressions of either fear, anger or disgust contrasted with expressions of mild happiness. After scanning, subjects categorised each expression. All patients were less accurate in identifying expressions, and showed less activation to these stimuli than normals. Non-paranoids performed poorly in the identification task and failed to activate neural regions that are normally linked with perception of these stimuli. They categorised disgust as either anger or fear more frequently than paranoids, and demonstrated in response to disgust expressions activation in the amygdala, a region associated with perception of fearful faces. Paranoids were more accurate in recognising expressions, and demonstrated greater activation than non-paranoids to most stimuli. We provide the first evidence for a distinction between two schizophrenic patient subgroups on the basis of recognition of and neural response to different negative facial expressions.

Normalization as a canonical neural computation

PubMed Central

Carandini, Matteo; Heeger, David J.

2012-01-01

There is increasing evidence that the brain relies on a set of canonical neural computations, repeating them across brain regions and modalities to apply similar operations to different problems. A promising candidate for such a computation is normalization, in which the responses of neurons are divided by a common factor that typically includes the summed activity of a pool of neurons. Normalization was developed to explain responses in the primary visual cortex and is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions. Normalization may underlie operations such as the representation of odours, the modulatory effects of visual attention, the encoding of value and the integration of multisensory information. Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that it serves as a canonical neural computation. PMID:22108672

Neural mechanisms of movement planning: motor cortex and beyond.

PubMed

Svoboda, Karel; Li, Nuo

2018-04-01

Neurons in motor cortex and connected brain regions fire in anticipation of specific movements, long before movement occurs. This neural activity reflects internal processes by which the brain plans and executes volitional movements. The study of motor planning offers an opportunity to understand how the structure and dynamics of neural circuits support persistent internal states and how these states influence behavior. Recent advances in large-scale neural recordings are beginning to decipher the relationship of the dynamics of populations of neurons during motor planning and movements. New behavioral tasks in rodents, together with quantified perturbations, link dynamics in specific nodes of neural circuits to behavior. These studies reveal a neural network distributed across multiple brain regions that collectively supports motor planning. We review recent advances and highlight areas where further work is needed to achieve a deeper understanding of the mechanisms underlying motor planning and related cognitive processes. Copyright © 2017. Published by Elsevier Ltd.

Neural Basis of Interpersonal Traits in Neurodegenerative Diseases

PubMed Central

Sollberger, Marc; Stanley, Christine M.; Wilson, Stephen M.; Gyurak, Anett; Beckman, Victoria; Growdon, Matthew; Jang, Jung; Weiner, Michael W.; Miller, Bruce L.; Rankin, Katherine P.

2009-01-01

Several functional and structural imaging studies have investigated the neural basis of personality in healthy adults, but human lesions studies are scarce. Personality changes are a common symptom in patients with neurodegenerative diseases like frontotemporal dementia (FTD) and semantic dementia (SD), allowing a unique window into the neural basis of personality. In this study, we used the Interpersonal Adjective Scales to investigate the structural basis of eight interpersonal traits (dominance, arrogance, coldness, introversion, submissiveness, ingenuousness, warmth, and extraversion) in 257 subjects: 214 patients with neurodegenerative diseases such as FTD, SD, progressive non-fluent aphasia, Alzheimer’s disease, amnestic mild cognitive impairment, corticobasal degeneration, and progressive supranuclear palsy and 43 healthy elderly people. Measures of interpersonal traits were correlated with regional atrophy pattern using voxel-based morphometry (VBM) analysis of structural MR images. Interpersonal traits mapped onto distinct brain regions depending on the degree to which they involved agency and affiliation. Interpersonal traits high in agency related to left dorsolateral prefrontal and left lateral frontopolar regions, whereas interpersonal traits high in affiliation related to right ventromedial prefrontal and right anteromedial temporal regions. Consistent with the existing literature on neural networks underlying social cognition, these results indicate that brain regions related to externally-focused, executive control-related processes underlie agentic interpersonal traits such as dominance, whereas brain regions related to internally-focused, emotion- and reward-related processes underlie affiliative interpersonal traits such as warmth. In addition, these findings indicate that interpersonal traits are subserved by complex neural networks rather than discrete anatomic areas. PMID:19540253

SiNC: Saliency-injected neural codes for representation and efficient retrieval of medical radiographs

PubMed Central

Sajjad, Muhammad; Mehmood, Irfan; Baik, Sung Wook

2017-01-01

Medical image collections contain a wealth of information which can assist radiologists and medical experts in diagnosis and disease detection for making well-informed decisions. However, this objective can only be realized if efficient access is provided to semantically relevant cases from the ever-growing medical image repositories. In this paper, we present an efficient method for representing medical images by incorporating visual saliency and deep features obtained from a fine-tuned convolutional neural network (CNN) pre-trained on natural images. Saliency detector is employed to automatically identify regions of interest like tumors, fractures, and calcified spots in images prior to feature extraction. Neuronal activation features termed as neural codes from different CNN layers are comprehensively studied to identify most appropriate features for representing radiographs. This study revealed that neural codes from the last fully connected layer of the fine-tuned CNN are found to be the most suitable for representing medical images. The neural codes extracted from the entire image and salient part of the image are fused to obtain the saliency-injected neural codes (SiNC) descriptor which is used for indexing and retrieval. Finally, locality sensitive hashing techniques are applied on the SiNC descriptor to acquire short binary codes for allowing efficient retrieval in large scale image collections. Comprehensive experimental evaluations on the radiology images dataset reveal that the proposed framework achieves high retrieval accuracy and efficiency for scalable image retrieval applications and compares favorably with existing approaches. PMID:28771497

Developmental dissociation in the neural responses to simple multiplication and subtraction problems

PubMed Central

Prado, Jérôme; Mutreja, Rachna; Booth, James R.

2014-01-01

Mastering single-digit arithmetic during school years is commonly thought to depend upon an increasing reliance on verbally memorized facts. An alternative model, however, posits that fluency in single-digit arithmetic might also be achieved via the increasing use of efficient calculation procedures. To test between these hypotheses, we used a cross-sectional design to measure the neural activity associated with single-digit subtraction and multiplication in 34 children from 2nd to 7th grade. The neural correlates of language and numerical processing were also identified in each child via localizer scans. Although multiplication and subtraction were undistinguishable in terms of behavior, we found a striking developmental dissociation in their neural correlates. First, we observed grade-related increases of activity for multiplication, but not for subtraction, in a language-related region of the left temporal cortex. Second, we found grade-related increases of activity for subtraction, but not for multiplication, in a region of the right parietal cortex involved in the procedural manipulation of numerical quantities. The present results suggest that fluency in simple arithmetic in children may be achieved by both increasing reliance on verbal retrieval and by greater use of efficient quantity-based procedures, depending on the operation. PMID:25089323

Forecasting ENSO events: A neural network-extended EOF approach

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

Tangang, F.T.; Tang, B.; Monahan, A.H.

The authors constructed neural network models to forecast the sea surface temperature anomalies (SSTA) for three regions: Nino 4. Nino 3.5, and Nino 3, representing the western-central, the central, and the eastern-central parts of the equatorial Pacific Ocean, respectively. The inputs were the extended empirical orthogonal functions (EEOF) of the sea level pressure (SLP) field that covered the tropical Indian and Pacific Oceans and evolved for a duration of 1 yr. The EEOFs greatly reduced the size of the neural networks from those of the authors` earlier papers using EOFs. The Nino 4 region appeared to be the best forecastedmore » region, with useful skills up to a year lead time for the 1982-93 forecast period. By network pruning analysis and spectral analysis, four important inputs were identified: modes 1, 2, and 6 of the SLP EEOFs and the SSTA persistence. Mode 1 characterized the low-frequency oscillation (LFO, with 4-5-yr period), and was seen as the typical ENSO signal, while mode 2, with a period of 2-5 yr, characterized the quasi-biennial oscillation (QBO) plus the LFO. Mode 6 was dominated by decadal and interdecadal variations. Thus, forecasting ENSO required information from the QBO, and the decadal-interdecadal oscillations. The nonlinearity of the networks tended to increase with lead time and to become stronger for the eastern regions of the equatorial Pacific Ocean. 35 refs., 14 figs., 4 tabs.« less

The Use of Neural Networks in Identifying Error Sources in Satellite-Derived Tropical SST Estimates

PubMed Central

Lee, Yung-Hsiang; Ho, Chung-Ru; Su, Feng-Chun; Kuo, Nan-Jung; Cheng, Yu-Hsin

2011-01-01

An neural network model of data mining is used to identify error sources in satellite-derived tropical sea surface temperature (SST) estimates from thermal infrared sensors onboard the Geostationary Operational Environmental Satellite (GOES). By using the Back Propagation Network (BPN) algorithm, it is found that air temperature, relative humidity, and wind speed variation are the major factors causing the errors of GOES SST products in the tropical Pacific. The accuracy of SST estimates is also improved by the model. The root mean square error (RMSE) for the daily SST estimate is reduced from 0.58 K to 0.38 K and mean absolute percentage error (MAPE) is 1.03%. For the hourly mean SST estimate, its RMSE is also reduced from 0.66 K to 0.44 K and the MAPE is 1.3%. PMID:22164030

Application of selection mapping to identify genomic regions associated with dairy production in sheep.

PubMed

Gutiérrez-Gil, Beatriz; Arranz, Juan Jose; Pong-Wong, Ricardo; García-Gámez, Elsa; Kijas, James; Wiener, Pamela

2014-01-01

In Europe, especially in Mediterranean areas, the sheep has been traditionally exploited as a dual purpose species, with income from both meat and milk. Modernization of husbandry methods and the establishment of breeding schemes focused on milk production have led to the development of "dairy breeds." This study investigated selective sweeps specifically related to dairy production in sheep by searching for regions commonly identified in different European dairy breeds. With this aim, genotypes from 44,545 SNP markers covering the sheep autosomes were analysed in both European dairy and non-dairy sheep breeds using two approaches: (i) identification of genomic regions showing extreme genetic differentiation between each dairy breed and a closely related non-dairy breed, and (ii) identification of regions with reduced variation (heterozygosity) in the dairy breeds using two methods. Regions detected in at least two breeds (breed pairs) by the two approaches (genetic differentiation and at least one of the heterozygosity-based analyses) were labeled as core candidate convergence regions and further investigated for candidate genes. Following this approach six regions were detected. For some of them, strong candidate genes have been proposed (e.g. ABCG2, SPP1), whereas some other genes designated as candidates based on their association with sheep and cattle dairy traits (e.g. LALBA, DGAT1A) were not associated with a detectable sweep signal. Few of the identified regions were coincident with QTL previously reported in sheep, although many of them corresponded to orthologous regions in cattle where QTL for dairy traits have been identified. Due to the limited number of QTL studies reported in sheep compared with cattle, the results illustrate the potential value of selection mapping to identify genomic regions associated with dairy traits in sheep.

Application of Selection Mapping to Identify Genomic Regions Associated with Dairy Production in Sheep

PubMed Central

Gutiérrez-Gil, Beatriz; Arranz, Juan Jose; Pong-Wong, Ricardo; García-Gámez, Elsa; Kijas, James; Wiener, Pamela

2014-01-01

In Europe, especially in Mediterranean areas, the sheep has been traditionally exploited as a dual purpose species, with income from both meat and milk. Modernization of husbandry methods and the establishment of breeding schemes focused on milk production have led to the development of “dairy breeds.” This study investigated selective sweeps specifically related to dairy production in sheep by searching for regions commonly identified in different European dairy breeds. With this aim, genotypes from 44,545 SNP markers covering the sheep autosomes were analysed in both European dairy and non-dairy sheep breeds using two approaches: (i) identification of genomic regions showing extreme genetic differentiation between each dairy breed and a closely related non-dairy breed, and (ii) identification of regions with reduced variation (heterozygosity) in the dairy breeds using two methods. Regions detected in at least two breeds (breed pairs) by the two approaches (genetic differentiation and at least one of the heterozygosity-based analyses) were labeled as core candidate convergence regions and further investigated for candidate genes. Following this approach six regions were detected. For some of them, strong candidate genes have been proposed (e.g. ABCG2, SPP1), whereas some other genes designated as candidates based on their association with sheep and cattle dairy traits (e.g. LALBA, DGAT1A) were not associated with a detectable sweep signal. Few of the identified regions were coincident with QTL previously reported in sheep, although many of them corresponded to orthologous regions in cattle where QTL for dairy traits have been identified. Due to the limited number of QTL studies reported in sheep compared with cattle, the results illustrate the potential value of selection mapping to identify genomic regions associated with dairy traits in sheep. PMID:24788864

Fgfr1 regulates patterning of the pharyngeal region

PubMed Central

Trokovic, Nina; Trokovic, Ras; Mai, Petra; Partanen, Juha

2003-01-01

Development of the pharyngeal region depends on the interaction and integration of different cell populations, including surface ectoderm, foregut endoderm, paraxial mesoderm, and neural crest. Mice homozygous for a hypomorphic allele of Fgfr1 have craniofacial defects, some of which appeared to result from a failure in the early development of the second branchial arch. A stream of neural crest cells was found to originate from the rhombomere 4 region and migrate toward the second branchial arch in the mutants. Neural crest cells mostly failed to enter the second arch, however, but accumulated in a region proximal to it. Both rescue of the hypomorphic Fgfr1 allele and inactivation of a conditional Fgfr1 allele specifically in neural crest cells indicated that Fgfr1 regulates the entry of neural crest cells into the second branchial arch non-cell-autonomously. Gene expression in the pharyngeal ectoderm overlying the developing second branchial arch was affected in the hypomorphic Fgfr1 mutants at a stage prior to neural crest entry. Our results indicate that Fgfr1 patterns the pharyngeal region to create a permissive environment for neural crest cell migration. PMID:12514106

The use of neural networks and texture analysis for rapid objective selection of regions of interest in cytoskeletal images.

PubMed

Derkacs, Amanda D Felder; Ward, Samuel R; Lieber, Richard L

2012-02-01

Understanding cytoskeletal dynamics in living tissue is prerequisite to understanding mechanisms of injury, mechanotransduction, and mechanical signaling. Real-time visualization is now possible using transfection with plasmids that encode fluorescent cytoskeletal proteins. Using this approach with the muscle-specific intermediate filament protein desmin, we found that a green fluorescent protein-desmin chimeric protein was unevenly distributed throughout the muscle fiber, resulting in some image areas that were saturated as well as others that lacked any signal. Our goal was to analyze the muscle fiber cytoskeletal network quantitatively in an unbiased fashion. To objectively select areas of the muscle fiber that are suitable for analysis, we devised a method that provides objective classification of regions of images of striated cytoskeletal structures into "usable" and "unusable" categories. This method consists of a combination of spatial analysis of the image using Fourier methods along with a boosted neural network that "decides" on the quality of the image based on previous training. We trained the neural network using the expert opinion of three scientists familiar with these types of images. We found that this method was over 300 times faster than manual classification and that it permitted objective and accurate classification of image regions.

Compounds with species and cell type specific toxicity identified in a 2000 compound drug screen of neural stem cells and rat mixed cortical neurons.

PubMed

Malik, Nasir; Efthymiou, Anastasia G; Mather, Karly; Chester, Nathaniel; Wang, Xiantao; Nath, Avindra; Rao, Mahendra S; Steiner, Joseph P

2014-12-01

Human primary neural tissue is a vital component for the quick and simple determination of chemical compound neurotoxicity in vitro. In particular, such tissue would be ideal for high-throughput screens that can be used to identify novel neurotoxic or neurotherapeutic compounds. We have previously established a high-throughput screening platform using human induced pluripotent stem cell (iPSC)-derived neural stem cells (NSCs) and neurons. In this study, we conducted a 2000 compound screen with human NSCs and rat cortical cells to identify compounds that are selectively toxic to each group. Approximately 100 of the tested compounds showed specific toxicity to human NSCs. A secondary screen of a small subset of compounds from the primary screen on human iPSCs, NSC-derived neurons, and fetal astrocytes validated the results from >80% of these compounds with some showing cell specific toxicity. Amongst those compounds were several cardiac glycosides, all of which were selectively toxic to the human cells. As the screen was able to reliably identify neurotoxicants, many with species and cell-type specificity, this study demonstrates the feasibility of this NSC-driven platform for higher-throughput neurotoxicity screens. Published by Elsevier B.V.

Neural basis for dynamic updating of object representation in visual working memory.

PubMed

Takahama, Sachiko; Miyauchi, Satoru; Saiki, Jun

2010-02-15

In real world, objects have multiple features and change dynamically. Thus, object representations must satisfy dynamic updating and feature binding. Previous studies have investigated the neural activity of dynamic updating or feature binding alone, but not both simultaneously. We investigated the neural basis of feature-bound object representation in a dynamically updating situation by conducting a multiple object permanence tracking task, which required observers to simultaneously process both the maintenance and dynamic updating of feature-bound objects. Using an event-related design, we separated activities during memory maintenance and change detection. In the search for regions showing selective activation in dynamic updating of feature-bound objects, we identified a network during memory maintenance that was comprised of the inferior precentral sulcus, superior parietal lobule, and middle frontal gyrus. In the change detection period, various prefrontal regions, including the anterior prefrontal cortex, were activated. In updating object representation of dynamically moving objects, the inferior precentral sulcus closely cooperates with a so-called "frontoparietal network", and subregions of the frontoparietal network can be decomposed into those sensitive to spatial updating and feature binding. The anterior prefrontal cortex identifies changes in object representation by comparing memory and perceptual representations rather than maintaining object representations per se, as previously suggested. Copyright 2009 Elsevier Inc. All rights reserved.

Neural Systems for Speech and Song in Autism

ERIC Educational Resources Information Center

Lai, Grace; Pantazatos, Spiro P.; Schneider, Harry; Hirsch, Joy

2012-01-01

Despite language disabilities in autism, music abilities are frequently preserved. Paradoxically, brain regions associated with these functions typically overlap, enabling investigation of neural organization supporting speech and song in autism. Neural systems sensitive to speech and song were compared in low-functioning autistic and age-matched…

Dissociating neural markers of stimulus memorability and subjective recognition during episodic retrieval.

PubMed

Bainbridge, Wilma A; Rissman, Jesse

2018-06-06

While much of memory research takes an observer-centric focus looking at participant performance, recent work has pinpointed important item-centric effects on memory, or how intrinsically memorable a given stimulus is. However, little is known about the neural correlates of memorability during memory retrieval, or how such correlates relate to subjective memory behavior. Here, stimuli and blood-oxygen-level dependent data from a prior functional magnetic resonance imaging (fMRI) study were reanalyzed using a memorability-based framework. In that study, sixteen participants studied 200 novel face images and were scanned while making recognition memory judgments on those faces, interspersed with 200 unstudied faces. In the current investigation, memorability scores for those stimuli were obtained through an online crowd-sourced (N = 740) continuous recognition test that measured each image's corrected recognition rate. Representational similarity analyses were conducted across the brain to identify regions wherein neural pattern similarity tracked item-specific effects (stimulus memorability) versus observer-specific effects (individual memory performance). We find two non-overlapping sets of regions, with memorability-related information predominantly represented within ventral and medial temporal regions and memory retrieval outcome-related information within fronto-parietal regions. These memorability-based effects persist regardless of image history, implying that coding of stimulus memorability may be a continuous and automatic perceptual process.

Childhood Social Inequalities Influences Neural Processes in Young Adult Caregiving

PubMed Central

Kim, Pilyoung; Ho, S. Shaun; Evans, Gary W.; Liberzon, Israel; Swain, James E.

2016-01-01

Childhood poverty is associated with harsh parenting with a risk of transmission to the next generation. This prospective study examined the relations between childhood poverty and non-parent adults’ neural responses to infant cry sounds. While no main effects of poverty were revealed in contrasts of infant cry vs. acoustically matched white noise, a gender by childhood poverty interaction emerged. In females, childhood poverty was associated with increased neural activations in the posterior insula, striatum, calcarine sulcus, hippocampus and fusiform gyrus, while, in males, childhood poverty was associated with reduced levels of neural responses to infant cry in the same regions. Irrespective of gender, neural activation in these regions was associated with higher levels of annoyance with the cry sound and reduced desire to approach the crying infant. The findings suggest gender differences in neural and emotional responses to infant cry sounds among young adults growing up in poverty. PMID:25981334

Identifying the origin of waterbird carcasses in Lake Michigan using a neural network source tracking model

USGS Publications Warehouse

Kenow, Kevin P.; Ge, Zhongfu; Fara, Luke J.; Houdek, Steven C.; Lubinski, Brian R.

2016-01-01

Avian botulism type E is responsible for extensive waterbird mortality on the Great Lakes, yet the actual site of toxin exposure remains unclear. Beached carcasses are often used to describe the spatial aspects of botulism mortality outbreaks, but lack specificity of offshore toxin source locations. We detail methodology for developing a neural network model used for predicting waterbird carcass motions in response to wind, wave, and current forcing, in lieu of a complex analytical relationship. This empirically trained model uses current velocity, wind velocity, significant wave height, and wave peak period in Lake Michigan simulated by the Great Lakes Coastal Forecasting System. A detailed procedure is further developed to use the model for back-tracing waterbird carcasses found on beaches in various parts of Lake Michigan, which was validated using drift data for radiomarked common loon (Gavia immer) carcasses deployed at a variety of locations in northern Lake Michigan during September and October of 2013. The back-tracing model was further used on 22 non-radiomarked common loon carcasses found along the shoreline of northern Lake Michigan in October and November of 2012. The model-estimated origins of those cases pointed to some common source locations offshore that coincide with concentrations of common loons observed during aerial surveys. The neural network source tracking model provides a promising approach for identifying locations of botulinum neurotoxin type E intoxication and, in turn, contributes to developing an understanding of the dynamics of toxin production and possible trophic transfer pathways.

An automated high throughput screening-compatible assay to identify regulators of stem cell neural differentiation.

PubMed

Casalino, Laura; Magnani, Dario; De Falco, Sandro; Filosa, Stefania; Minchiotti, Gabriella; Patriarca, Eduardo J; De Cesare, Dario

2012-03-01

The use of Embryonic Stem Cells (ESCs) holds considerable promise both for drug discovery programs and the treatment of degenerative disorders in regenerative medicine approaches. Nevertheless, the successful use of ESCs is still limited by the lack of efficient control of ESC self-renewal and differentiation capabilities. In this context, the possibility to modulate ESC biological properties and to obtain homogenous populations of correctly specified cells will help developing physiologically relevant screens, designed for the identification of stem cell modulators. Here, we developed a high throughput screening-suitable ESC neural differentiation assay by exploiting the Cell(maker) robotic platform and demonstrated that neural progenies can be generated from ESCs in complete automation, with high standards of accuracy and reliability. Moreover, we performed a pilot screening providing proof of concept that this assay allows the identification of regulators of ESC neural differentiation in full automation.

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.

Neural substrates of driving behaviour

PubMed Central

Spiers, Hugo J.; Maguire, Eleanor A.

2007-01-01

Driving a vehicle is an indispensable daily behaviour for many people, yet we know little about how it is supported by the brain. Given that driving in the real world involves the engagement of many cognitive systems that rapidly change to meet varying environmental demands, identifying its neural basis presents substantial problems. By employing a unique combination of functional magnetic resonance imaging (fMRI), an accurate interactive virtual simulation of a bustling central London (UK) and a retrospective verbal report protocol, we surmounted these difficulties. We identified different events that characterise the driving process on a second by second basis and the brain regions that underlie them. Prepared actions such as starting, turning, reversing and stopping were associated with a common network comprised of premotor, parietal and cerebellar regions. Each prepared action also recruited additional brain areas. We also observed unexpected hazardous events such as swerving and avoiding collisions that were associated with activation of lateral occipital and parietal regions, insula, as well as a more posterior region in the medial premotor cortex than prepared actions. By contrast, planning future actions and monitoring fellow road users were associated with activity in superior parietal, lateral occipital cortices and the cerebellum. The anterior pre-SMA was also recruited during action planning. The right lateral prefrontal cortex was specifically engaged during the processing of road traffic rules. By systematically characterising the brain dynamics underlying naturalistic driving behaviour in a real city, our findings may have implications for how driving competence is considered in the context of neurological damage. PMID:17412611

Cognitive Neural Prosthetics

PubMed Central

Andersen, Richard A.; Hwang, Eun Jung; Mulliken, Grant H.

2010-01-01

The cognitive neural prosthetic (CNP) is a very versatile method for assisting paralyzed patients and patients with amputations. The CNP records the cognitive state of the subject, rather than signals strictly related to motor execution or sensation. We review a number of high-level cortical signals and their application for CNPs, including intention, motor imagery, decision making, forward estimation, executive function, attention, learning, and multi-effector movement planning. CNPs are defined by the cognitive function they extract, not the cortical region from which the signals are recorded. However, some cortical areas may be better than others for particular applications. Signals can also be extracted in parallel from multiple cortical areas using multiple implants, which in many circumstances can increase the range of applications of CNPs. The CNP approach relies on scientific understanding of the neural processes involved in cognition, and many of the decoding algorithms it uses also have parallels to underlying neural circuit functions. PMID:19575625

Deep learning in the small sample size setting: cascaded feed forward neural networks for medical image segmentation

NASA Astrophysics Data System (ADS)

Gaonkar, Bilwaj; Hovda, David; Martin, Neil; Macyszyn, Luke

2016-03-01

Deep Learning, refers to large set of neural network based algorithms, have emerged as promising machine- learning tools in the general imaging and computer vision domains. Convolutional neural networks (CNNs), a specific class of deep learning algorithms, have been extremely effective in object recognition and localization in natural images. A characteristic feature of CNNs, is the use of a locally connected multi layer topology that is inspired by the animal visual cortex (the most powerful vision system in existence). While CNNs, perform admirably in object identification and localization tasks, typically require training on extremely large datasets. Unfortunately, in medical image analysis, large datasets are either unavailable or are extremely expensive to obtain. Further, the primary tasks in medical imaging are organ identification and segmentation from 3D scans, which are different from the standard computer vision tasks of object recognition. Thus, in order to translate the advantages of deep learning to medical image analysis, there is a need to develop deep network topologies and training methodologies, that are geared towards medical imaging related tasks and can work in a setting where dataset sizes are relatively small. In this paper, we present a technique for stacked supervised training of deep feed forward neural networks for segmenting organs from medical scans. Each `neural network layer' in the stack is trained to identify a sub region of the original image, that contains the organ of interest. By layering several such stacks together a very deep neural network is constructed. Such a network can be used to identify extremely small regions of interest in extremely large images, inspite of a lack of clear contrast in the signal or easily identifiable shape characteristics. What is even more intriguing is that the network stack achieves accurate segmentation even when it is trained on a single image with manually labelled ground truth. We validate

Simple Model for Identifying Critical Regions in Atrial Fibrillation

NASA Astrophysics Data System (ADS)

Christensen, Kim; Manani, Kishan A.; Peters, Nicholas S.

2015-01-01

Atrial fibrillation (AF) is the most common abnormal heart rhythm and the single biggest cause of stroke. Ablation, destroying regions of the atria, is applied largely empirically and can be curative but with a disappointing clinical success rate. We design a simple model of activation wave front propagation on an anisotropic structure mimicking the branching network of heart muscle cells. This integration of phenomenological dynamics and pertinent structure shows how AF emerges spontaneously when the transverse cell-to-cell coupling decreases, as occurs with age, beyond a threshold value. We identify critical regions responsible for the initiation and maintenance of AF, the ablation of which terminates AF. The simplicity of the model allows us to calculate analytically the risk of arrhythmia and express the threshold value of transversal cell-to-cell coupling as a function of the model parameters. This threshold value decreases with increasing refractory period by reducing the number of critical regions which can initiate and sustain microreentrant circuits. These biologically testable predictions might inform ablation therapies and arrhythmic risk assessment.

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.

The neural correlates of risk propensity in males and females using resting-state fMRI

PubMed Central

Zhou, Yuan; Li, Shu; Dunn, John; Li, Huandong; Qin, Wen; Zhu, Maohu; Rao, Li-Lin; Song, Ming; Yu, Chunshui; Jiang, Tianzi

2014-01-01

Men are more risk prone than women, but the underlying basis remains unclear. To investigate this question, we developed a trait-like measure of risk propensity which we correlated with resting-state functional connectivity to identify sex differences. Specifically, we used short- and long-range functional connectivity densities to identify associated brain regions and examined their functional connectivities in resting-state functional magnetic resonance imaging (fMRI) data collected from a large sample of healthy young volunteers. We found that men had a higher level of general risk propensity (GRP) than women. At the neural level, although they shared a common neural correlate of GRP in a network centered at the right inferior frontal gyrus, men and women differed in a network centered at the right secondary somatosensory cortex, which included the bilateral dorsal anterior/middle insular cortices and the dorsal anterior cingulate cortex. In addition, men and women differed in a local network centered at the left inferior orbitofrontal cortex. Most of the regions identified by this resting-state fMRI study have been previously implicated in risk processing when people make risky decisions. This study provides a new perspective on the brain-behavioral relationships in risky decision making and contributes to our understanding of sex differences in risk propensity. PMID:24478649

Implicit motor learning promotes neural efficiency during laparoscopy.

PubMed

Zhu, Frank F; Poolton, Jamie M; Wilson, Mark R; Hu, Yong; Maxwell, Jon P; Masters, Rich S W

2011-09-01

An understanding of differences in expert and novice neural behavior can inform surgical skills training. Outside the surgical domain, electroencephalographic (EEG) coherence analyses have shown that during motor performance, experts display less coactivation between the verbal-analytic and motor planning regions than their less skilled counterparts. Reduced involvement of verbal-analytic processes suggests greater neural efficiency. The authors tested the utility of an implicit motor learning intervention specifically devised to promote neural efficiency by reducing verbal-analytic involvement in laparoscopic performance. In this study, 18 novices practiced a movement pattern on a laparoscopic trainer with either conscious awareness of the movement pattern (explicit motor learning) or suppressed awareness of the movement pattern (implicit motor learning). In a retention test, movement accuracy was compared between the conditions, and coactivation (EEG coherence) was assessed between the motor planning (Fz) region and both the verbal-analytic (T3) and the visuospatial (T4) cortical regions (T3-Fz and T4-Fz, respectively). Movement accuracy in the conditions was not different in a retention test (P = 0.231). Findings showed that the EEG coherence scores for the T3-Fz regions were lower for the implicit learners than for the explicit learners (P = 0.027), but no differences were apparent for the T4-Fz regions (P = 0.882). Implicit motor learning reduced EEG coactivation between verbal-analytic and motor planning regions, suggesting that verbal-analytic processes were less involved in laparoscopic performance. The findings imply that training techniques that discourage nonessential coactivation during motor performance may provide surgeons with more neural resources with which to manage other aspects of surgery.

Unraveling the neural basis of insect navigation.

PubMed

Heinze, Stanley

2017-12-01

One of the defining features of animals is their ability to navigate their environment. Using behavioral experiments this topic has been under intense investigation for nearly a century. In insects, this work has largely focused on the remarkable homing abilities of ants and bees. More recently, the neural basis of navigation shifted into the focus of attention. Starting with revealing the neurons that process the sensory signals used for navigation, in particular polarized skylight, migratory locusts became the key species for delineating navigation-relevant regions of the insect brain. Over the last years, this work was used as a basis for research in the fruit fly Drosophila and extraordinary progress has been made in illuminating the neural underpinnings of navigational processes. With increasingly detailed understanding of navigation circuits, we can begin to ask whether there is a fundamentally shared concept underlying all navigation behavior across insects. This review highlights recent advances and puts them into the context of the behavioral work on ants and bees, as well as the circuits involved in polarized-light processing. A region of the insect brain called the central complex emerges as the common substrate for guiding navigation and its highly organized neuroarchitecture provides a framework for future investigations potentially suited to explain all insect navigation behavior at the level of identified neurons. Copyright © 2017 Elsevier Inc. All rights reserved.

Neural Correlates of Verb Argument Structure Processing

PubMed Central

Thompson, Cynthia K.; Bonakdarpour, Borna; Fix, Stephen C.; Blumenfeld, Henrike K.; Parrish, Todd B.; Gitelman, Darren R.; Mesulam, M.-Marsel

2008-01-01

Neuroimaging and lesion studies suggest that processing of word classes, such as verbs and nouns, is associated with distinct neural mechanisms. Such studies also suggest that subcategories within these broad word class categories are differentially processed in the brain. Within the class of verbs, argument structure provides one linguistic dimension that distinguishes among verb exemplars, with some requiring more complex argument structure entries than others. This study examined the neural instantiation of verbs by argument structure complexity: one-, two-, and three-argument verbs. Stimuli of each type, along with nouns and pseudowords, were presented for lexical decision using an event-related functional magnetic resonance imaging design. Results for 14 young normal participants indicated largely overlapping activation maps for verbs and nouns, with no areas of significant activation for verbs compared to nouns, or vice versa. Pseudowords also engaged neural tissue overlapping with that for both word classes, with more widespread activation noted in visual, motor, and peri-sylvian regions. Examination of verbs by argument structure revealed activation of the supramarginal and angular gyri, limited to the left hemisphere only when verbs with two obligatory arguments were compared to verbs with a single argument. However, bilateral activation was noted when both two- and three-argument verbs were compared to one-argument verbs. These findings suggest that posterior peri-sylvian regions are engaged for processing argument structure information associated with verbs, with increasing neural tissue in the inferior parietal region associated with increasing argument structure complexity. These findings are consistent with processing accounts, which suggest that these regions are crucial for semantic integration. PMID:17958479

Neural sources of performance decline during continuous multitasking

PubMed Central

Al-Hashimi, Omar; Zanto, Theodore P.; Gazzaley, Adam

2018-01-01

Multitasking performance costs have largely been characterized by experiments that involve two overlapping and punctuated perceptual stimuli, as well as punctuated responses to each task. Here, participants engaged in a continuous performance paradigm during fMRI recording to identify neural signatures associated with multitasking costs under more natural conditions. Our results demonstrated that only a single brain region, the superior parietal lobule (SPL), exhibited a significant relationship with multitasking performance, such that increased activation in the multitasking condition versus the singletasking condition was associated with higher task performance (i.e., least multitasking cost). Together, these results support previous research indicating that parietal regions underlie multitasking abilities and that performance costs are related to a bottleneck in control processes involving the SPL that serves to divide attention between two tasks. PMID:26159323

Common and Distinct Neural Mechanisms of Attentional Switching and Response Conflict

PubMed Central

Kim, Chobok; Johnson, Nathan F.; Gold, Brian T.

2012-01-01

The human capacities for overcoming prepotent actions and flexibly switching between tasks represent cornerstones of cognitive control. Functional neuroimaging has implicated a diverse set of brain regions contributing to each of these cognitive control processes. However, the extent to which attentional switching and response conflict draw on shared or distinct neural mechanisms remains unclear. The current study examined the neural correlates of response conflict and attentional switching using event-related functional magnetic resonance imaging (fMRI) and a fully randomized 2×2 design. We manipulated an arrow-word version of the Stroop task to measure conflict and switching in the context of a single task decision, in response to a common set of stimuli. Under these common conditions, both behavioral and imaging data showed significant main effects of conflict and switching but no interaction. However, conjunction analyses identified frontal regions involved in both switching and response conflict, including the dorsal anterior cingulate cortex (dACC) and left inferior frontal junction. In addition, connectivity analyses demonstrated task-dependent functional connectivity patterns between dACC and inferior temporal cortex for attentional switching and between dACC and posterior parietal cortex for response conflict. These results suggest that the brain makes use of shared frontal regions, but can dynamically modulate the connectivity patterns of some of those regions, to deal with attentional switching and response conflict. PMID:22750124

A Study for the Feature Selection to Identify GIEMSA-Stained Human Chromosomes Based on Artificial Neural Network

DTIC Science & Technology

2001-10-25

neural network (ANN) has been adopted for the human chromosome classification. It is important to select optimum features for training neural network...Many studies for computer-based chromosome analysis have shown that it is possible to classify chromosomes into 24 subgroups. In addition, artificial

A quantitative framework to evaluate modeling of cortical development by neural stem cells

PubMed Central

Stein, Jason L.; de la Torre-Ubieta, Luis; Tian, Yuan; Parikshak, Neelroop N.; Hernandez, Israel A.; Marchetto, Maria C.; Baker, Dylan K.; Lu, Daning; Hinman, Cassidy R.; Lowe, Jennifer K.; Wexler, Eric M.; Muotri, Alysson R.; Gage, Fred H.; Kosik, Kenneth S.; Geschwind, Daniel H.

2014-01-01

Summary Neural stem cells have been adopted to model a wide range of neuropsychiatric conditions in vitro. However, how well such models correspond to in vivo brain has not been evaluated in an unbiased, comprehensive manner. We used transcriptomic analyses to compare in vitro systems to developing human fetal brain and observed strong conservation of in vivo gene expression and network architecture in differentiating primary human neural progenitor cells (phNPCs). Conserved modules are enriched in genes associated with ASD, supporting the utility of phNPCs for studying neuropsychiatric disease. We also developed and validated a machine learning approach called CoNTExT that identifies the developmental maturity and regional identity of in vitro models. We observed strong differences between in vitro models, including hiPSC-derived neural progenitors from multiple laboratories. This work provides a systems biology framework for evaluating in vitro systems and supports their value in studying the molecular mechanisms of human neurodevelopmental disease. PMID:24991955

Neural correlates of treatment response in depressed bipolar adolescents during emotion processing.

PubMed

Diler, Rasim Somer; Ladouceur, Cecile D; Segreti, Annamaria; Almeida, Jorge R C; Birmaher, Boris; Axelson, David A; Phillips, Mary L; Pan, Lisa A

2013-06-01

Depressive mood in adolescents with bipolar disorder (BDd) is associated with significant morbidity and mortality, but we have limited information about neural correlates of depression and treatment response in BDd. Ten adolescents with BDd (8 females, mean age = 15.6 ± 0.9) completed two (fearful and happy) face gender labeling fMRI experiments at baseline and after 6-weeks of open treatment. Whole-brain analysis was used at baseline to compare their neural activity with those of 10 age and sex-matched healthy controls (HC). For comparisons of the neural activity at baseline and after treatment of youth with BDd, region of interest analysis for dorsal/ventral prefrontal, anterior cingulate, and amygdala activity, and significant regions identified by wholebrain analysis between BDd and HC were analyzed. There was significant improvement in depression scores (mean percentage change on the Child Depression Rating Scale-Revised 57 % ± 28). Neural activity after treatment was decreased in left occipital cortex in the intense fearful experiment, but increased in left insula, left cerebellum, and right ventrolateral prefrontal cortex in the intense happy experiment. Greater improvement in depression was associated with baseline higher activity in ventral ACC to mild happy faces. Study sample size was relatively small for subgroup analysis and consisted of mainly female adolescents that were predominantly on psychotropic medications during scanning. Our results of reduced negative emotion processing versus increased positive emotion processing after treatment of depression (improvement of cognitive bias to negative and away from positive) are consistent with the improvement of depression according to Beck's cognitive theory.

Intergenerational neural mediators of early-life anxious temperament.

PubMed

Fox, Andrew S; Oler, Jonathan A; Shackman, Alexander J; Shelton, Steven E; Raveendran, Muthuswamy; McKay, D Reese; Converse, Alexander K; Alexander, Andrew; Davidson, Richard J; Blangero, John; Rogers, Jeffrey; Kalin, Ned H

2015-07-21

Understanding the heritability of neural systems linked to psychopathology is not sufficient to implicate them as intergenerational neural mediators. By closely examining how individual differences in neural phenotypes and psychopathology cosegregate as they fall through the family tree, we can identify the brain systems that underlie the parent-to-child transmission of psychopathology. Although research has identified genes and neural circuits that contribute to the risk of developing anxiety and depression, the specific neural systems that mediate the inborn risk for these debilitating disorders remain unknown. In a sample of 592 young rhesus monkeys that are part of an extended multigenerational pedigree, we demonstrate that metabolism within a tripartite prefrontal-limbic-midbrain circuit mediates some of the inborn risk for developing anxiety and depression. Importantly, although brain volume is highly heritable early in life, it is brain metabolism-not brain structure-that is the critical intermediary between genetics and the childhood risk to develop stress-related psychopathology.

Estimating the functional dimensionality of neural representations.

PubMed

Ahlheim, Christiane; Love, Bradley C

2018-06-07

Recent advances in multivariate fMRI analysis stress the importance of information inherent to voxel patterns. Key to interpreting these patterns is estimating the underlying dimensionality of neural representations. Dimensions may correspond to psychological dimensions, such as length and orientation, or involve other coding schemes. Unfortunately, the noise structure of fMRI data inflates dimensionality estimates and thus makes it difficult to assess the true underlying dimensionality of a pattern. To address this challenge, we developed a novel approach to identify brain regions that carry reliable task-modulated signal and to derive an estimate of the signal's functional dimensionality. We combined singular value decomposition with cross-validation to find the best low-dimensional projection of a pattern of voxel-responses at a single-subject level. Goodness of the low-dimensional reconstruction is measured as Pearson correlation with a test set, which allows to test for significance of the low-dimensional reconstruction across participants. Using hierarchical Bayesian modeling, we derive the best estimate and associated uncertainty of underlying dimensionality across participants. We validated our method on simulated data of varying underlying dimensionality, showing that recovered dimensionalities match closely true dimensionalities. We then applied our method to three published fMRI data sets all involving processing of visual stimuli. The results highlight three possible applications of estimating the functional dimensionality of neural data. Firstly, it can aid evaluation of model-based analyses by revealing which areas express reliable, task-modulated signal that could be missed by specific models. Secondly, it can reveal functional differences across brain regions. Thirdly, knowing the functional dimensionality allows assessing task-related differences in the complexity of neural patterns. Copyright © 2018 The Authors. Published by Elsevier Inc. All

Theory of mind in schizophrenia: exploring neural mechanisms of belief attribution.

PubMed

Lee, Junghee; Quintana, Javier; Nori, Poorang; Green, Michael F

2011-01-01

Although previous behavioral studies have shown that schizophrenia patients have impaired theory of mind (ToM), the neural mechanisms associated with this impairment are poorly understood. This study aimed to identify the neural mechanisms of ToM in schizophrenia, using functional magnetic resonance imaging (fMRI) with a belief attribution task. In the scanner, 12 schizophrenia patients and 13 healthy control subjects performed the belief attribution task with three conditions: a false belief condition, a false photograph condition, and a simple reading condition. For the false belief versus simple reading conditions, schizophrenia patients showed reduced neural activation in areas including the temporoparietal junction (TPJ) and medial prefrontal cortex (MPFC) compared with controls. Further, during the false belief versus false photograph conditions, we observed increased activations in the TPJ and the MPFC in healthy controls, but not in schizophrenia patients. For the false photograph versus simple reading condition, both groups showed comparable neural activations. Schizophrenia patients showed reduced task-related activation in the TPJ and the MPFC during the false belief condition compared with controls, but not for the false photograph condition. This pattern suggests that reduced activation in these regions is associated with, and specific to, impaired ToM in schizophrenia.

Theory of mind in schizophrenia: Exploring neural mechanisms of belief attribution

PubMed Central

Lee, Junghee; Quintana, Javier; Nori, Poorang; Green, Michael F.

2014-01-01

Background Although previous behavioral studies have shown that schizophrenia patients have impaired theory of mind (ToM), the neural mechanisms associated with this impairment are poorly understood. This study aimed to identify the neural mechanisms of ToM in schizophrenia using functional magnetic resonance imaging (fMRI) with a Belief Attribution Task. Methods In the scanner, 12 schizophrenia patients and 13 healthy control subjects performed the Belief Attribution Task with 3 conditions: a false belief condition, a false photograph condition, and a simple reading condition. Results For the false belief vs. simple reading conditions, schizophrenia patients showed reduced neural activation in areas including the temporo-parietal junction (TPJ) and medial prefrontal cortex (MPFC) compared with controls. Further, during the false belief vs. false photograph conditions we observed increased activations in the TPJ and the MPFC in healthy controls, but not in schizophrenia patients. For the false photograph vs. simple reading condition, both groups showed comparable neural activations. Conclusions Schizophrenia patients showed reduced task-related activation in the TPJ and the MPFC during the false belief condition compared with controls, but not for the false photograph condition. This pattern suggests that reduced activation in these regions is associated with, and specific to, impaired ToM in schizophrenia. PMID:22050432

Neural Effects of Short-Term Training on Working Memory

PubMed Central

Buschkuehl, Martin; Garcia, Luis Hernandez; Jaeggi, Susanne M.; Bernard, Jessica A.; Jonides, John

2014-01-01

Working memory training has been the focus of intense research interest. Despite accumulating behavioral work, knowledge about the neural mechanisms underlying training effects is scarce. Here we show that seven days of training on an n back task lead to substantial performance improvements in the trained task; furthermore, the experimental group shows cross modal transfer as compared to an active control group. In addition, there are two neural effects that emerged as a function of training: first, increased perfusion during task performance in selected regions, reflecting a neural response to cope with high task demand; second, increased blood flow at rest in regions where training effects were apparent. We also found that perfusion at rest was correlated with task proficiency, probably reflecting an improved neural readiness to perform. Our findings are discussed within the context of the available neuroimaging literature on n back training. PMID:24496717

A recurrent neural network for nonlinear optimization with a continuously differentiable objective function and bound constraints.

PubMed

Liang, X B; Wang, J

2000-01-01

This paper presents a continuous-time recurrent neural-network model for nonlinear optimization with any continuously differentiable objective function and bound constraints. Quadratic optimization with bound constraints is a special problem which can be solved by the recurrent neural network. The proposed recurrent neural network has the following characteristics. 1) It is regular in the sense that any optimum of the objective function with bound constraints is also an equilibrium point of the neural network. If the objective function to be minimized is convex, then the recurrent neural network is complete in the sense that the set of optima of the function with bound constraints coincides with the set of equilibria of the neural network. 2) The recurrent neural network is primal and quasiconvergent in the sense that its trajectory cannot escape from the feasible region and will converge to the set of equilibria of the neural network for any initial point in the feasible bound region. 3) The recurrent neural network has an attractivity property in the sense that its trajectory will eventually converge to the feasible region for any initial states even at outside of the bounded feasible region. 4) For minimizing any strictly convex quadratic objective function subject to bound constraints, the recurrent neural network is globally exponentially stable for almost any positive network parameters. Simulation results are given to demonstrate the convergence and performance of the proposed recurrent neural network for nonlinear optimization with bound constraints.

Distributed neural system for emotional intelligence revealed by lesion mapping.

PubMed

Barbey, Aron K; Colom, Roberto; Grafman, Jordan

2014-03-01

Cognitive neuroscience has made considerable progress in understanding the neural architecture of human intelligence, identifying a broadly distributed network of frontal and parietal regions that support goal-directed, intelligent behavior. However, the contributions of this network to social and emotional aspects of intellectual function remain to be well characterized. Here we investigated the neural basis of emotional intelligence in 152 patients with focal brain injuries using voxel-based lesion-symptom mapping. Latent variable modeling was applied to obtain measures of emotional intelligence, general intelligence and personality from the Mayer, Salovey, Caruso Emotional Intelligence Test (MSCEIT), the Wechsler Adult Intelligence Scale and the Neuroticism-Extroversion-Openness Inventory, respectively. Regression analyses revealed that latent scores for measures of general intelligence and personality reliably predicted latent scores for emotional intelligence. Lesion mapping results further indicated that these convergent processes depend on a shared network of frontal, temporal and parietal brain regions. The results support an integrative framework for understanding the architecture of executive, social and emotional processes and make specific recommendations for the interpretation and application of the MSCEIT to the study of emotional intelligence in health and disease.

Distributed neural system for emotional intelligence revealed by lesion mapping

PubMed Central

Colom, Roberto; Grafman, Jordan

2014-01-01

Cognitive neuroscience has made considerable progress in understanding the neural architecture of human intelligence, identifying a broadly distributed network of frontal and parietal regions that support goal-directed, intelligent behavior. However, the contributions of this network to social and emotional aspects of intellectual function remain to be well characterized. Here we investigated the neural basis of emotional intelligence in 152 patients with focal brain injuries using voxel-based lesion-symptom mapping. Latent variable modeling was applied to obtain measures of emotional intelligence, general intelligence and personality from the Mayer, Salovey, Caruso Emotional Intelligence Test (MSCEIT), the Wechsler Adult Intelligence Scale and the Neuroticism-Extroversion-Openness Inventory, respectively. Regression analyses revealed that latent scores for measures of general intelligence and personality reliably predicted latent scores for emotional intelligence. Lesion mapping results further indicated that these convergent processes depend on a shared network of frontal, temporal and parietal brain regions. The results support an integrative framework for understanding the architecture of executive, social and emotional processes and make specific recommendations for the interpretation and application of the MSCEIT to the study of emotional intelligence in health and disease. PMID:23171618

An Introduction to Neural Networks for Hearing Aid Noise Recognition.

ERIC Educational Resources Information Center

Kim, Jun W.; Tyler, Richard S.

1995-01-01

This article introduces the use of multilayered artificial neural networks in hearing aid noise recognition. It reviews basic principles of neural networks, and offers an example of an application in which a neural network is used to identify the presence or absence of noise in speech. The ability of neural networks to "learn" the…

A Survey of Neural Network Publications.

ERIC Educational Resources Information Center

Vijayaraman, Bindiganavale S.; Osyk, Barbara

This paper is a survey of publications on artificial neural networks published in business journals for the period ending July 1996. Its purpose is to identify and analyze trends in neural network research during that period. This paper shows which topics have been heavily researched, when these topics were researched, and how that research has…

"Neural overlap of L1 and L2 semantic representations across visual and auditory modalities: a decoding approach".

PubMed

Van de Putte, Eowyn; De Baene, Wouter; Price, Cathy J; Duyck, Wouter

2018-05-01

This study investigated whether brain activity in Dutch-French bilinguals during semantic access to concepts from one language could be used to predict neural activation during access to the same concepts from another language, in different language modalities/tasks. This was tested using multi-voxel pattern analysis (MVPA), within and across language comprehension (word listening and word reading) and production (picture naming). It was possible to identify the picture or word named, read or heard in one language (e.g. maan, meaning moon) based on the brain activity in a distributed bilateral brain network while, respectively, naming, reading or listening to the picture or word in the other language (e.g. lune). The brain regions identified differed across tasks. During picture naming, brain activation in the occipital and temporal regions allowed concepts to be predicted across languages. During word listening and word reading, across-language predictions were observed in the rolandic operculum and several motor-related areas (pre- and postcentral, the cerebellum). In addition, across-language predictions during reading were identified in regions typically associated with semantic processing (left inferior frontal, middle temporal cortex, right cerebellum and precuneus) and visual processing (inferior and middle occipital regions and calcarine sulcus). Furthermore, across modalities and languages, the left lingual gyrus showed semantic overlap across production and word reading. These findings support the idea of at least partially language- and modality-independent semantic neural representations. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Identifying Potential Regions of Copy Number Variation for Bipolar Disorder

PubMed Central

Chen, Yi-Hsuan; Lu, Ru-Band; Hung, Hung; Kuo, Po-Hsiu

2014-01-01

Bipolar disorder is a complex psychiatric disorder with high heritability, but its genetic determinants are still largely unknown. Copy number variation (CNV) is one of the sources to explain part of the heritability. However, it is a challenge to estimate discrete values of the copy numbers using continuous signals calling from a set of markers, and to simultaneously perform association testing between CNVs and phenotypic outcomes. The goal of the present study is to perform a series of data filtering and analysis procedures using a DNA pooling strategy to identify potential CNV regions that are related to bipolar disorder. A total of 200 normal controls and 200 clinically diagnosed bipolar patients were recruited in this study, and were randomly divided into eight control and eight case pools. Genome-wide genotyping was employed using Illumina Human Omni1-Quad array with approximately one million markers for CNV calling. We aimed at setting a series of criteria to filter out the signal noise of marker data and to reduce the chance of false-positive findings for CNV regions. We first defined CNV regions for each pool. Potential CNV regions were reported based on the different patterns of CNV status between cases and controls. Genes that were mapped into the potential CNV regions were examined with association testing, Gene Ontology enrichment analysis, and checked with existing literature for their associations with bipolar disorder. We reported several CNV regions that are related to bipolar disorder. Two CNV regions on chromosome 11 and 22 showed significant signal differences between cases and controls (p < 0.05). Another five CNV regions on chromosome 6, 9, and 19 were overlapped with results in previous CNV studies. Experimental validation of two CNV regions lent some support to our reported findings. Further experimental and replication studies could be designed for these selected regions. PMID:27605030

Influence of aging on the neural correlates of autobiographical, episodic, and semantic memory retrieval.

PubMed

St-Laurent, Marie; Abdi, Hervé; Burianová, Hana; Grady, Cheryl L

2011-12-01

We used fMRI to assess the neural correlates of autobiographical, semantic, and episodic memory retrieval in healthy young and older adults. Participants were tested with an event-related paradigm in which retrieval demand was the only factor varying between trials. A spatio-temporal partial least square analysis was conducted to identify the main patterns of activity characterizing the groups across conditions. We identified brain regions activated by all three memory conditions relative to a control condition. This pattern was expressed equally in both age groups and replicated previous findings obtained in a separate group of younger adults. We also identified regions whose activity differentiated among the different memory conditions. These patterns of differentiation were expressed less strongly in the older adults than in the young adults, a finding that was further confirmed by a barycentric discriminant analysis. This analysis showed an age-related dedifferentiation in autobiographical and episodic memory tasks but not in the semantic memory task or the control condition. These findings suggest that the activation of a common memory retrieval network is maintained with age, whereas the specific aspects of brain activity that differ with memory content are more vulnerable and less selectively engaged in older adults. Our results provide a potential neural mechanism for the well-known age differences in episodic/autobiographical memory, and preserved semantic memory, observed when older adults are compared with younger adults.

Optical neural network system for pose determination of spinning satellites

NASA Technical Reports Server (NTRS)

Lee, Andrew; Casasent, David

1990-01-01

An optical neural network architecture and algorithm based on a Hopfield optimization network are presented for multitarget tracking. This tracker utilizes a neuron for every possible target track, and a quadratic energy function of neural activities which is minimized using gradient descent neural evolution. The neural net tracker is demonstrated as part of a system for determining position and orientation (pose) of spinning satellites with respect to a robotic spacecraft. The input to the system is time sequence video from a single camera. Novelty detection and filtering are utilized to locate and segment novel regions from the input images. The neural net multitarget tracker determines the correspondences (or tracks) of the novel regions as a function of time, and hence the paths of object (satellite) parts. The path traced out by a given part or region is approximately elliptical in image space, and the position, shape and orientation of the ellipse are functions of the satellite geometry and its pose. Having a geometric model of the satellite, and the elliptical path of a part in image space, the three-dimensional pose of the satellite is determined. Digital simulation results using this algorithm are presented for various satellite poses and lighting conditions.

Differences in the neural correlates of frontal lobe tests.

PubMed

Matsuoka, Teruyuki; Kato, Yuka; Imai, Ayu; Fujimoto, Hiroshi; Shibata, Keisuke; Nakamura, Kaeko; Yamada, Kei; Narumoto, Jin

2018-01-01

The Executive Interview (EXIT25), the executive clock-drawing task (CLOX1), and the Frontal Assessment Battery (FAB) are used to assess executive function at the bedside. These tests assess distinct psychometric properties. The aim of this study was to examine differences in the neural correlates of the EXIT25, CLOX1, and FAB based on magnetic resonance imaging. Fifty-eight subjects (30 with Alzheimer's disease, 10 with mild cognitive impairment, and 18 healthy controls) participated in this study. Multiple regression analyses were performed to examine the brain regions correlated with the EXIT25, CLOX1, and FAB scores. Age, gender, and years of education were included as covariates. Statistical thresholds were set to uncorrected P-values of 0.001 at the voxel level and 0.05 at the cluster level. The EXIT25 score correlated inversely with the regional grey matter volume in the left lateral frontal lobe (Brodmann areas 6, 9, 44, and 45). The CLOX1 score correlated positively with the regional grey matter volume in the right orbitofrontal cortex (Brodmann area 11) and the left supramarginal gyrus (Brodmann area 40). The FAB score correlated positively with the regional grey matter volume in the right precentral gyrus (Brodmann area 6). The left lateral frontal lobe (Brodmann area 9) and the right lateral frontal lobe (Brodmann area 46) were identified as common brain regions that showed association with EXIT25, CLOX1, and FAB based only a voxel-level threshold. The results of this study suggest that the EXIT25, CLOX1, and FAB may be associated with the distinct neural correlates of the frontal cortex. © 2018 Japanese Psychogeriatric Society.

Neural Bases Of Food Perception: Coordinate-Based Meta-Analyses Of Neuroimaging Studies In Multiple Modalities

PubMed Central

Huerta, Claudia I; Sarkar, Pooja R; Duong, Timothy Q.; Laird, Angela R; Fox, Peter T

2013-01-01

Objective The purpose of this study was to compare the results of the three food-cue paradigms most commonly used for functional neuroimaging studies to determine: i) commonalities and differences in the neural response patterns by paradigm; and, ii) the relative robustness and reliability of responses to each paradigm. Design and Methods functional magnetic resonance imaging (fMRI) studies using standardized stereotactic coordinates to report brain responses to food cues were identified using on-line databases. Studies were grouped by food-cue modality as: i) tastes (8 studies); ii) odors (8 studies); and, iii) images (11 studies). Activation likelihood estimation (ALE) was used to identify statistically reliable regional responses within each stimulation paradigm. Results Brain response distributions were distinctly different for the three stimulation modalities, corresponding to known differences in location of the respective primary and associative cortices. Visual stimulation induced the most robust and extensive responses. The left anterior insula was the only brain region reliably responding to all three stimulus categories. Conclusions These findings suggest visual food-cue paradigm as promising candidate for imaging studies addressing the neural substrate of therapeutic interventions. PMID:24174404

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…

Neural mechanisms of social dominance

PubMed Central

Watanabe, Noriya; Yamamoto, Miyuki

2015-01-01

In a group setting, individuals' perceptions of their own level of dominance or of the dominance level of others, and the ability to adequately control their behavior based on these perceptions are crucial for living within a social environment. Recent advances in neural imaging and molecular technology have enabled researchers to investigate the neural substrates that support the perception of social dominance and the formation of a social hierarchy in humans. At the systems' level, recent studies showed that dominance perception is represented in broad brain regions which include the amygdala, hippocampus, striatum, and various cortical networks such as the prefrontal, and parietal cortices. Additionally, neurotransmitter systems such as the dopaminergic and serotonergic systems, modulate and are modulated by the formation of the social hierarchy in a group. While these monoamine systems have a wide distribution and multiple functions, it was recently found that the Neuropeptide B/W contributes to the perception of dominance and is present in neurons that have a limited projection primarily to the amygdala. The present review discusses the specific roles of these neural regions and neurotransmitter systems in the perception of dominance and in hierarchy formation. PMID:26136644

Detection of mass regions in mammograms by bilateral analysis adapted to breast density using similarity indexes and convolutional neural networks.

PubMed

Bandeira Diniz, João Otávio; Bandeira Diniz, Pedro Henrique; Azevedo Valente, Thales Levi; Corrêa Silva, Aristófanes; de Paiva, Anselmo Cardoso; Gattass, Marcelo

2018-03-01

The processing of medical image is an important tool to assist in minimizing the degree of uncertainty of the specialist, while providing specialists with an additional source of detect and diagnosis information. Breast cancer is the most common type of cancer that affects the female population around the world. It is also the most deadly type of cancer among women. It is the second most common type of cancer among all others. The most common examination to diagnose breast cancer early is mammography. In the last decades, computational techniques have been developed with the purpose of automatically detecting structures that maybe associated with tumors in mammography examination. This work presents a computational methodology to automatically detection of mass regions in mammography by using a convolutional neural network. The materials used in this work is the DDSM database. The method proposed consists of two phases: training phase and test phase. The training phase has 2 main steps: (1) create a model to classify breast tissue into dense and non-dense (2) create a model to classify regions of breast into mass and non-mass. The test phase has 7 step: (1) preprocessing; (2) registration; (3) segmentation; (4) first reduction of false positives; (5) preprocessing of regions segmented; (6) density tissue classification (7) second reduction of false positives where regions will be classified into mass and non-mass. The proposed method achieved 95.6% of accuracy in classify non-dense breasts tissue and 97,72% accuracy in classify dense breasts. To detect regions of mass in non-dense breast, the method achieved a sensitivity value of 91.5%, and specificity value of 90.7%, with 91% accuracy. To detect regions in dense breasts, our method achieved 90.4% of sensitivity and 96.4% of specificity, with accuracy of 94.8%. According to the results achieved by CNN, we demonstrate the feasibility of using convolutional neural networks on medical image processing techniques for

The neural correlates of gist-based true and false recognition

PubMed Central

Gutchess, Angela H.; Schacter, Daniel L.

2012-01-01

When information is thematically related to previously studied information, gist-based processes contribute to false recognition. Using functional MRI, we examined the neural correlates of gist-based recognition as a function of increasing numbers of studied exemplars. Sixteen participants incidentally encoded small, medium, and large sets of pictures, and we compared the neural response at recognition using parametric modulation analyses. For hits, regions in middle occipital, middle temporal, and posterior parietal cortex linearly modulated their activity according to the number of related encoded items. For false alarms, visual, parietal, and hippocampal regions were modulated as a function of the encoded set size. The present results are consistent with prior work in that the neural regions supporting veridical memory also contribute to false memory for related information. The results also reveal that these regions respond to the degree of relatedness among similar items, and implicate perceptual and constructive processes in gist-based false memory. PMID:22155331

Dynamic decomposition of spatiotemporal neural signals

PubMed Central

2017-01-01

Neural signals are characterized by rich temporal and spatiotemporal dynamics that reflect the organization of cortical networks. Theoretical research has shown how neural networks can operate at different dynamic ranges that correspond to specific types of information processing. Here we present a data analysis framework that uses a linearized model of these dynamic states in order to decompose the measured neural signal into a series of components that capture both rhythmic and non-rhythmic neural activity. The method is based on stochastic differential equations and Gaussian process regression. Through computer simulations and analysis of magnetoencephalographic data, we demonstrate the efficacy of the method in identifying meaningful modulations of oscillatory signals corrupted by structured temporal and spatiotemporal noise. These results suggest that the method is particularly suitable for the analysis and interpretation of complex temporal and spatiotemporal neural signals. PMID:28558039

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.

Machine Vision Within The Framework Of Collective Neural Assemblies

NASA Astrophysics Data System (ADS)

Gupta, Madan M.; Knopf, George K.

1990-03-01

The proposed mechanism for designing a robust machine vision system is based on the dynamic activity generated by the various neural populations embedded in nervous tissue. It is postulated that a hierarchy of anatomically distinct tissue regions are involved in visual sensory information processing. Each region may be represented as a planar sheet of densely interconnected neural circuits. Spatially localized aggregates of these circuits represent collective neural assemblies. Four dynamically coupled neural populations are assumed to exist within each assembly. In this paper we present a state-variable model for a tissue sheet derived from empirical studies of population dynamics. Each population is modelled as a nonlinear second-order system. It is possible to emulate certain observed physiological and psychophysiological phenomena of biological vision by properly programming the interconnective gains . Important early visual phenomena such as temporal and spatial noise insensitivity, contrast sensitivity and edge enhancement will be discussed for a one-dimensional tissue model.

Neural Categorization of Vibrotactile Frequency in Flutter and Vibration Stimulations: An fMRI Study.

PubMed

Kim, Junsuk; Chung, Yoon Gi; Chung, Soon-Cheol; Bulthoff, Heinrich H; Kim, Sung-Phil

2016-01-01

As the use of wearable haptic devices with vibrating alert features is commonplace, an understanding of the perceptual categorization of vibrotactile frequencies has become important. This understanding can be substantially enhanced by unveiling how neural activity represents vibrotactile frequency information. Using functional magnetic resonance imaging (fMRI), this study investigated categorical clustering patterns of the frequency-dependent neural activity evoked by vibrotactile stimuli with gradually changing frequencies from 20 to 200 Hz. First, a searchlight multi-voxel pattern analysis (MVPA) was used to find brain regions exhibiting neural activities associated with frequency information. We found that the contralateral postcentral gyrus (S1) and the supramarginal gyrus (SMG) carried frequency-dependent information. Next, we applied multidimensional scaling (MDS) to find low-dimensional neural representations of different frequencies obtained from the multi-voxel activity patterns within these regions. The clustering analysis on the MDS results showed that neural activity patterns of 20-100 Hz and 120-200 Hz were divided into two distinct groups. Interestingly, this neural grouping conformed to the perceptual frequency categories found in the previous behavioral studies. Our findings therefore suggest that neural activity patterns in the somatosensory cortical regions may provide a neural basis for the perceptual categorization of vibrotactile frequency.

Neural networks mediating sentence reading in the deaf

PubMed Central

Hirshorn, Elizabeth A.; Dye, Matthew W. G.; Hauser, Peter C.; Supalla, Ted R.; Bavelier, Daphne

2014-01-01

The present work addresses the neural bases of sentence reading in deaf populations. To better understand the relative role of deafness and spoken language knowledge in shaping the neural networks that mediate sentence reading, three populations with different degrees of English knowledge and depth of hearing loss were included—deaf signers, oral deaf and hearing individuals. The three groups were matched for reading comprehension and scanned while reading sentences. A similar neural network of left perisylvian areas was observed, supporting the view of a shared network of areas for reading despite differences in hearing and English knowledge. However, differences were observed, in particular in the auditory cortex, with deaf signers and oral deaf showing greatest bilateral superior temporal gyrus (STG) recruitment as compared to hearing individuals. Importantly, within deaf individuals, the same STG area in the left hemisphere showed greater recruitment as hearing loss increased. To further understand the functional role of such auditory cortex re-organization after deafness, connectivity analyses were performed from the STG regions identified above. Connectivity from the left STG toward areas typically associated with semantic processing (BA45 and thalami) was greater in deaf signers and in oral deaf as compared to hearing. In contrast, connectivity from left STG toward areas identified with speech-based processing was greater in hearing and in oral deaf as compared to deaf signers. These results support the growing literature indicating recruitment of auditory areas after congenital deafness for visually-mediated language functions, and establish that both auditory deprivation and language experience shape its functional reorganization. Implications for differential reliance on semantic vs. phonological pathways during reading in the three groups is discussed. PMID:24959127

Neural Mechanisms of Selective Visual Attention.

PubMed

Moore, Tirin; Zirnsak, Marc

2017-01-03

Selective visual attention describes the tendency of visual processing to be confined largely to stimuli that are relevant to behavior. It is among the most fundamental of cognitive functions, particularly in humans and other primates for whom vision is the dominant sense. We review recent progress in identifying the neural mechanisms of selective visual attention. We discuss evidence from studies of different varieties of selective attention and examine how these varieties alter the processing of stimuli by neurons within the visual system, current knowledge of their causal basis, and methods for assessing attentional dysfunctions. In addition, we identify some key questions that remain in identifying the neural mechanisms that give rise to the selective processing of visual information.

The neural bases underlying social risk perception in purchase decisions.

PubMed

Yokoyama, Ryoichi; Nozawa, Takayuki; Sugiura, Motoaki; Yomogida, Yukihito; Takeuchi, Hikaru; Akimoto, Yoritaka; Shibuya, Satoru; Kawashima, Ryuta

2014-05-01

Social considerations significantly influence daily purchase decisions, and the perception of social risk (i.e., the anticipated disapproval of others) is crucial in dissuading consumers from making purchases. However, the neural basis for consumers' perception of social risk remains undiscovered, and this novel study clarifies the relevant neural processes. A total of 26 volunteers were scanned while they evaluated purchase intention of products (purchase intention task) and their anticipation of others' disapproval for possessing a product (social risk task), using functional magnetic resonance imaging (fMRI). The fMRI data from the purchase intention task was used to identify the brain region associated with perception of social risk during purchase decision making by using subjective social risk ratings for a parametric modulation analysis. Furthermore, we aimed to explore if there was a difference between participants' purchase decisions and their explicit evaluations of social risk, with reference to the neural activity associated with social risk perception. For this, subjective social risk ratings were used for a parametric modulation analysis on fMRI data from the social risk task. Analysis of the purchase intention task revealed a significant positive correlation between ratings of social risk and activity in the anterior insula, an area of the brain that is known as part of the emotion-related network. Analysis of the social risk task revealed a significant positive correlation between ratings of social risk and activity in the temporal parietal junction and the medial prefrontal cortex, which are known as theory-of-mind regions. Our results suggest that the anterior insula processes consumers' social risk implicitly to prompt consumers not to buy socially unacceptable products, whereas ToM-related regions process such risk explicitly in considering the anticipated disapproval of others. These findings may prove helpful in understanding the mental

Classification of 2-dimensional array patterns: assembling many small neural networks is better than using a large one.

PubMed

Chen, Liang; Xue, Wei; Tokuda, Naoyuki

2010-08-01

In many pattern classification/recognition applications of artificial neural networks, an object to be classified is represented by a fixed sized 2-dimensional array of uniform type, which corresponds to the cells of a 2-dimensional grid of the same size. A general neural network structure, called an undistricted neural network, which takes all the elements in the array as inputs could be used for problems such as these. However, a districted neural network can be used to reduce the training complexity. A districted neural network usually consists of two levels of sub-neural networks. Each of the lower level neural networks, called a regional sub-neural network, takes the elements in a region of the array as its inputs and is expected to output a temporary class label, called an individual opinion, based on the partial information of the entire array. The higher level neural network, called an assembling sub-neural network, uses the outputs (opinions) of regional sub-neural networks as inputs, and by consensus derives the label decision for the object. Each of the sub-neural networks can be trained separately and thus the training is less expensive. The regional sub-neural networks can be trained and performed in parallel and independently, therefore a high speed can be achieved. We prove theoretically in this paper, using a simple model, that a districted neural network is actually more stable than an undistricted neural network in noisy environments. We conjecture that the result is valid for all neural networks. This theory is verified by experiments involving gender classification and human face recognition. We conclude that a districted neural network is highly recommended for neural network applications in recognition or classification of 2-dimensional array patterns in highly noisy environments. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

A review on cluster estimation methods and their application to neural spike data.

PubMed

Zhang, James; Nguyen, Thanh; Cogill, Steven; Bhatti, Asim; Luo, Lingkun; Yang, Samuel; Nahavandi, Saeid

2018-06-01

The extracellular action potentials recorded on an electrode result from the collective simultaneous electrophysiological activity of an unknown number of neurons. Identifying and assigning these action potentials to their firing neurons-'spike sorting'-is an indispensable step in studying the function and the response of an individual or ensemble of neurons to certain stimuli. Given the task of neural spike sorting, the determination of the number of clusters (neurons) is arguably the most difficult and challenging issue, due to the existence of background noise and the overlap and interactions among neurons in neighbouring regions. It is not surprising that some researchers still rely on visual inspection by experts to estimate the number of clusters in neural spike sorting. Manual inspection, however, is not suitable to processing the vast, ever-growing amount of neural data. To address this pressing need, in this paper, thirty-three clustering validity indices have been comprehensively reviewed and implemented to determine the number of clusters in neural datasets. To gauge the suitability of the indices to neural spike data, and inform the selection process, we then calculated the indices by applying k-means clustering to twenty widely used synthetic neural datasets and one empirical dataset, and compared the performance of these indices against pre-existing ground truth labels. The results showed that the top five validity indices work consistently well across variations in noise level, both for the synthetic datasets and the real dataset. Using these top performing indices provides strong support for the determination of the number of neural clusters, which is essential in the spike sorting process.

Neural mechanisms of planning: A computational analysis using event-related fMRI

PubMed Central

Fincham, Jon M.; Carter, Cameron S.; van Veen, Vincent; Stenger, V. Andrew; Anderson, John R.

2002-01-01

To investigate the neural mechanisms of planning, we used a novel adaptation of the Tower of Hanoi (TOH) task and event-related functional MRI. Participants were trained in applying a specific strategy to an isomorph of the five-disk TOH task. After training, participants solved novel problems during event-related functional MRI. A computational cognitive model of the task was used to generate a reference time series representing the expected blood oxygen level-dependent response in brain areas involved in the manipulation and planning of goals. This time series was used as one term within a general linear modeling framework to identify brain areas in which the time course of activity varied as a function of goal-processing events. Two distinct time courses of activation were identified, one in which activation varied parametrically with goal-processing operations, and the other in which activation became pronounced only during goal-processing intensive trials. Regions showing the parametric relationship comprised a frontoparietal system and include right dorsolateral prefrontal cortex [Brodmann's area (BA 9)], bilateral parietal (BA 40/7), and bilateral premotor (BA 6) areas. Regions preferentially engaged only during goal-intensive processing include left inferior frontal gyrus (BA 44). The implications of these results for the current model, as well as for our understanding of the neural mechanisms of planning and functional specialization of the prefrontal cortex, are discussed. PMID:11880658

Neural Mechanisms of Cognitive Reappraisal of Negative Self-Beliefs in Social Anxiety Disorder

PubMed Central

Goldin, Philippe R.; Ball, Tali M.; Werner, Kelly; Heimberg, Richard; Gross, James J.

2009-01-01

Background Social anxiety disorder (SAD) is characterized by distorted negative self-beliefs (NSBs) which are thought to enhance emotional reactivity, interfere with emotion regulation, and undermine social functioning. Cognitive reappraisal is a type of emotion regulation used to alter NSBs, with the goal of modulating emotional reactivity. Despite its relevance, little is known about the neural bases and temporal features of cognitive reappraisal in patients with SAD. Methods Twenty-seven patients with SAD and 27 healthy controls (HC) were trained to react and to implement cognitive reappraisal in order to down-regulate negative emotional reactivity to NSBs while undergoing functional magnetic resonance imaging and providing ratings of negative emotion experience. Results Behaviorally, compared with HC, patients with SAD reported greater negative emotion both while reacting to and reappraising NSBs. However, when cued, participants in both groups were able to use cognitive reappraisal to decrease emotion. Neurally, reacting to NSBs resulted in early amygdala response in both groups. Reappraising NSBs resulted in greater early cognitive control, language, and visual processing in HC, but greater late cognitive control, visceral, and visual processing in patients with SAD. Functional connectivity analysis during reappraisal identified more regulatory regions inversely related to left amygdala in HCs than in patients with SAD. Reappraisal-related brain regions that differentiated patients and controls were associated with negative emotion ratings and cognitive reappraisal self-efficacy. Conclusions Findings regarding cognitive reappraisal suggest neural timing, connectivity, and brain-behavioral associations specific to patients with SAD, and elucidate neural mechanisms that might serve as biomarkers of interventions for SAD. PMID:19717138

Neural sources of performance decline during continuous multitasking.

PubMed

Al-Hashimi, Omar; Zanto, Theodore P; Gazzaley, Adam

2015-10-01

Multitasking performance costs have largely been characterized by experiments that involve two overlapping and punctuated perceptual stimuli, as well as punctuated responses to each task. Here, participants engaged in a continuous performance paradigm during fMRI recording to identify neural signatures associated with multitasking costs under more natural conditions. Our results demonstrated that only a single brain region, the superior parietal lobule (SPL), exhibited a significant relationship with multitasking performance, such that increased activation in the multitasking condition versus the singletasking condition was associated with higher task performance (i.e., least multitasking cost). Together, these results support previous research indicating that parietal regions underlie multitasking abilities and that performance costs are related to a bottleneck in control processes involving the SPL that serves to divide attention between two tasks. Copyright © 2015. Published by Elsevier Ltd.

Maximum entropy methods for extracting the learned features of deep neural networks.

PubMed

Finnegan, Alex; Song, Jun S

2017-10-01

New architectures of multilayer artificial neural networks and new methods for training them are rapidly revolutionizing the application of machine learning in diverse fields, including business, social science, physical sciences, and biology. Interpreting deep neural networks, however, currently remains elusive, and a critical challenge lies in understanding which meaningful features a network is actually learning. We present a general method for interpreting deep neural networks and extracting network-learned features from input data. We describe our algorithm in the context of biological sequence analysis. Our approach, based on ideas from statistical physics, samples from the maximum entropy distribution over possible sequences, anchored at an input sequence and subject to constraints implied by the empirical function learned by a network. Using our framework, we demonstrate that local transcription factor binding motifs can be identified from a network trained on ChIP-seq data and that nucleosome positioning signals are indeed learned by a network trained on chemical cleavage nucleosome maps. Imposing a further constraint on the maximum entropy distribution also allows us to probe whether a network is learning global sequence features, such as the high GC content in nucleosome-rich regions. This work thus provides valuable mathematical tools for interpreting and extracting learned features from feed-forward neural networks.

Multipotent Caudal Neural Progenitors Derived from Human Pluripotent Stem Cells That Give Rise to Lineages of the Central and Peripheral Nervous System

PubMed Central

Hasegawa, Kouichi; Menheniott, Trevelyan; Rollo, Ben; Zhang, Dongcheng; Hough, Shelley; Alshawaf, Abdullah; Febbraro, Fabia; Ighaniyan, Samiramis; Leung, Jessie; Elliott, David A.; Newgreen, Donald F.; Pera, Martin F.

2015-01-01

Abstract The caudal neural plate is a distinct region of the embryo that gives rise to major progenitor lineages of the developing central and peripheral nervous system, including neural crest and floor plate cells. We show that dual inhibition of the glycogen synthase kinase 3β and activin/nodal pathways by small molecules differentiate human pluripotent stem cells (hPSCs) directly into a preneuroepithelial progenitor population we named “caudal neural progenitors” (CNPs). CNPs coexpress caudal neural plate and mesoderm markers, and, share high similarities to embryonic caudal neural plate cells in their lineage differentiation potential. Exposure of CNPs to BMP2/4, sonic hedgehog, or FGF2 signaling efficiently directs their fate to neural crest/roof plate cells, floor plate cells, and caudally specified neuroepithelial cells, respectively. Neural crest derived from CNPs differentiated to neural crest derivatives and demonstrated extensive migratory properties in vivo. Importantly, we also determined the key extrinsic factors specifying CNPs from human embryonic stem cell include FGF8, canonical WNT, and IGF1. Our studies are the first to identify a multipotent neural progenitor derived from hPSCs, that is the precursor for major neural lineages of the embryonic caudal neural tube. Stem Cells 2015;33:1759–1770 PMID:25753817

DMRfinder: efficiently identifying differentially methylated regions from MethylC-seq data.

PubMed

Gaspar, John M; Hart, Ronald P

2017-11-29

DNA methylation is an epigenetic modification that is studied at a single-base resolution with bisulfite treatment followed by high-throughput sequencing. After alignment of the sequence reads to a reference genome, methylation counts are analyzed to determine genomic regions that are differentially methylated between two or more biological conditions. Even though a variety of software packages is available for different aspects of the bioinformatics analysis, they often produce results that are biased or require excessive computational requirements. DMRfinder is a novel computational pipeline that identifies differentially methylated regions efficiently. Following alignment, DMRfinder extracts methylation counts and performs a modified single-linkage clustering of methylation sites into genomic regions. It then compares methylation levels using beta-binomial hierarchical modeling and Wald tests. Among its innovative attributes are the analyses of novel methylation sites and methylation linkage, as well as the simultaneous statistical analysis of multiple sample groups. To demonstrate its efficiency, DMRfinder is benchmarked against other computational approaches using a large published dataset. Contrasting two replicates of the same sample yielded minimal genomic regions with DMRfinder, whereas two alternative software packages reported a substantial number of false positives. Further analyses of biological samples revealed fundamental differences between DMRfinder and another software package, despite the fact that they utilize the same underlying statistical basis. For each step, DMRfinder completed the analysis in a fraction of the time required by other software. Among the computational approaches for identifying differentially methylated regions from high-throughput bisulfite sequencing datasets, DMRfinder is the first that integrates all the post-alignment steps in a single package. Compared to other software, DMRfinder is extremely efficient and unbiased in

Vehicle Detection in Aerial Images Based on Region Convolutional Neural Networks and Hard Negative Example Mining.

PubMed

Tang, Tianyu; Zhou, Shilin; Deng, Zhipeng; Zou, Huanxin; Lei, Lin

2017-02-10

Detecting vehicles in aerial imagery plays an important role in a wide range of applications. The current vehicle detection methods are mostly based on sliding-window search and handcrafted or shallow-learning-based features, having limited description capability and heavy computational costs. Recently, due to the powerful feature representations, region convolutional neural networks (CNN) based detection methods have achieved state-of-the-art performance in computer vision, especially Faster R-CNN. However, directly using it for vehicle detection in aerial images has many limitations: (1) region proposal network (RPN) in Faster R-CNN has poor performance for accurately locating small-sized vehicles, due to the relatively coarse feature maps; and (2) the classifier after RPN cannot distinguish vehicles and complex backgrounds well. In this study, an improved detection method based on Faster R-CNN is proposed in order to accomplish the two challenges mentioned above. Firstly, to improve the recall, we employ a hyper region proposal network (HRPN) to extract vehicle-like targets with a combination of hierarchical feature maps. Then, we replace the classifier after RPN by a cascade of boosted classifiers to verify the candidate regions, aiming at reducing false detection by negative example mining. We evaluate our method on the Munich vehicle dataset and the collected vehicle dataset, with improvements in accuracy and robustness compared to existing methods.

Neural control of vascular reactions: impact of emotion and attention.

PubMed

Okon-Singer, Hadas; Mehnert, Jan; Hoyer, Jana; Hellrung, Lydia; Schaare, Herma Lina; Dukart, Juergen; Villringer, Arno

2014-03-19

This study investigated the neural regions involved in blood pressure reactions to negative stimuli and their possible modulation by attention. Twenty-four healthy human subjects (11 females; age = 24.75 ± 2.49 years) participated in an affective perceptual load task that manipulated attention to negative/neutral distractor pictures. fMRI data were collected simultaneously with continuous recording of peripheral arterial blood pressure. A parametric modulation analysis examined the impact of attention and emotion on the relation between neural activation and blood pressure reactivity during the task. When attention was available for processing the distractor pictures, negative pictures resulted in behavioral interference, neural activation in brain regions previously related to emotion, a transient decrease of blood pressure, and a positive correlation between blood pressure response and activation in a network including prefrontal and parietal regions, the amygdala, caudate, and mid-brain. These effects were modulated by attention; behavioral and neural responses to highly negative distractor pictures (compared with neutral pictures) were smaller or diminished, as was the negative blood pressure response when the central task involved high perceptual load. Furthermore, comparing high and low load revealed enhanced activation in frontoparietal regions implicated in attention control. Our results fit theories emphasizing the role of attention in the control of behavioral and neural reactions to irrelevant emotional distracting information. Our findings furthermore extend the function of attention to the control of autonomous reactions associated with negative emotions by showing altered blood pressure reactions to emotional stimuli, the latter being of potential clinical relevance.

Neural Correlates of Direct and Indirect Suppression of Autobiographical Memories

PubMed Central

Noreen, Saima; O’Connor, Akira R.; MacLeod, Malcolm D.

2016-01-01

Research indicates that there are two possible mechanisms by which particular target memories can be intentionally forgotten. Direct suppression, which involves the suppression of the unwanted memory directly, and is dependent on a fronto-hippocampal modulatory process, and, memory substitution, which includes directing one’s attention to an alternative memory in order to prevent the unwanted memory from coming to mind, and involves engaging the caudal prefrontal cortex (cPFC) and the mid-ventrolateral prefrontal cortex (VLPFC) regions. Research to date, however, has investigated the neural basis of memory suppression of relatively simple information. The aim of the current study was to use fMRI to identify the neural mechanisms associated with the suppression of autobiographical memories. In the present study, 22 participants generated memories in response to a series of cue words. In a second session, participants learnt these cue-memory pairings, and were subsequently presented with a cue word and asked either to recall (think) or to suppress (no-think) the associated memory, or to think of an alternative memory in order to suppress the original memory (memory-substitution). Our findings demonstrated successful forgetting effects in the no-think and memory substitution conditions. Although we found no activation in the dorsolateral prefrontal cortex, there was reduced hippocampal activation during direct suppression. In the memory substitution condition, however, we failed to find increased activation in the cPFC and VLPFC regions. Our findings suggest that the suppression of autobiographical memories may rely on different neural mechanisms to those established for other types of material in memory. PMID:27047412

Neural Correlates of Direct and Indirect Suppression of Autobiographical Memories.

PubMed

Noreen, Saima; O'Connor, Akira R; MacLeod, Malcolm D

2016-01-01

Research indicates that there are two possible mechanisms by which particular target memories can be intentionally forgotten. Direct suppression, which involves the suppression of the unwanted memory directly, and is dependent on a fronto-hippocampal modulatory process, and, memory substitution, which includes directing one's attention to an alternative memory in order to prevent the unwanted memory from coming to mind, and involves engaging the caudal prefrontal cortex (cPFC) and the mid-ventrolateral prefrontal cortex (VLPFC) regions. Research to date, however, has investigated the neural basis of memory suppression of relatively simple information. The aim of the current study was to use fMRI to identify the neural mechanisms associated with the suppression of autobiographical memories. In the present study, 22 participants generated memories in response to a series of cue words. In a second session, participants learnt these cue-memory pairings, and were subsequently presented with a cue word and asked either to recall (think) or to suppress (no-think) the associated memory, or to think of an alternative memory in order to suppress the original memory (memory-substitution). Our findings demonstrated successful forgetting effects in the no-think and memory substitution conditions. Although we found no activation in the dorsolateral prefrontal cortex, there was reduced hippocampal activation during direct suppression. In the memory substitution condition, however, we failed to find increased activation in the cPFC and VLPFC regions. Our findings suggest that the suppression of autobiographical memories may rely on different neural mechanisms to those established for other types of material in memory.

Redistribution of neural phase coherence reflects establishment of feedforward map in speech motor adaptation

PubMed Central

Sengupta, Ranit

2015-01-01

Despite recent progress in our understanding of sensorimotor integration in speech learning, a comprehensive framework to investigate its neural basis is lacking at behaviorally relevant timescales. Structural and functional imaging studies in humans have helped us identify brain networks that support speech but fail to capture the precise spatiotemporal coordination within the networks that takes place during speech learning. Here we use neuronal oscillations to investigate interactions within speech motor networks in a paradigm of speech motor adaptation under altered feedback with continuous recording of EEG in which subjects adapted to the real-time auditory perturbation of a target vowel sound. As subjects adapted to the task, concurrent changes were observed in the theta-gamma phase coherence during speech planning at several distinct scalp regions that is consistent with the establishment of a feedforward map. In particular, there was an increase in coherence over the central region and a decrease over the fronto-temporal regions, revealing a redistribution of coherence over an interacting network of brain regions that could be a general feature of error-based motor learning in general. Our findings have implications for understanding the neural basis of speech motor learning and could elucidate how transient breakdown of neuronal communication within speech networks relates to speech disorders. PMID:25632078

Theory of Mind: A Neural Prediction Problem

PubMed Central

Koster-Hale, Jorie; Saxe, Rebecca

2014-01-01

Predictive coding posits that neural systems make forward-looking predictions about incoming information. Neural signals contain information not about the currently perceived stimulus, but about the difference between the observed and the predicted stimulus. We propose to extend the predictive coding framework from high-level sensory processing to the more abstract domain of theory of mind; that is, to inferences about others’ goals, thoughts, and personalities. We review evidence that, across brain regions, neural responses to depictions of human behavior, from biological motion to trait descriptions, exhibit a key signature of predictive coding: reduced activity to predictable stimuli. We discuss how future experiments could distinguish predictive coding from alternative explanations of this response profile. This framework may provide an important new window on the neural computations underlying theory of mind. PMID:24012000

Identifying Unstable Regions of Proteins Involved in Misfolding Diseases

NASA Astrophysics Data System (ADS)

Guest, Will; Cashman, Neil; Plotkin, Steven

2009-05-01

Protein misfolding is a necessary step in the pathogenesis of many diseases, including Creutzfeldt-Jakob disease (CJD) and familial amyotrophic lateral sclerosis (fALS). Identifying unstable structural elements in their causative proteins elucidates the early events of misfolding and presents targets for inhibition of the disease process. An algorithm was developed to calculate the Gibbs free energy of unfolding for all sequence-contiguous regions of a protein using three methods to parameterize energy changes: a modified G=o model, changes in solvent-accessible surface area, and all-atoms molecular dynamics. The entropic effects of disulfide bonds and post-translational modifications are treated analytically. It incorporates a novel method for finding local dielectric constants inside a protein to accurately handle charge effects. We have predicted the unstable parts of prion protein and superoxide dismutase 1, the proteins involved in CJD and fALS respectively, and have used these regions as epitopes to prepare antibodies that are specific to the misfolded conformation and show promise as therapeutic agents.

Discrete Neural Correlates for the Recognition of Negative Emotions: Insights from Frontotemporal Dementia

PubMed Central

Kumfor, Fiona; Irish, Muireann; Hodges, John R.; Piguet, Olivier

2013-01-01

Patients with frontotemporal dementia have pervasive changes in emotion recognition and social cognition, yet the neural changes underlying these emotion processing deficits remain unclear. The multimodal system model of emotion proposes that basic emotions are dependent on distinct brain regions, which undergo significant pathological changes in frontotemporal dementia. As such, this syndrome may provide important insight into the impact of neural network degeneration upon the innate ability to recognise emotions. This study used voxel-based morphometry to identify discrete neural correlates involved in the recognition of basic emotions (anger, disgust, fear, sadness, surprise and happiness) in frontotemporal dementia. Forty frontotemporal dementia patients (18 behavioural-variant, 11 semantic dementia, 11 progressive nonfluent aphasia) and 27 healthy controls were tested on two facial emotion recognition tasks: The Ekman 60 and Ekman Caricatures. Although each frontotemporal dementia group showed impaired recognition of negative emotions, distinct associations between emotion-specific task performance and changes in grey matter intensity emerged. Fear recognition was associated with the right amygdala; disgust recognition with the left insula; anger recognition with the left middle and superior temporal gyrus; and sadness recognition with the left subcallosal cingulate, indicating that discrete neural substrates are necessary for emotion recognition in frontotemporal dementia. The erosion of emotion-specific neural networks in neurodegenerative disorders may produce distinct profiles of performance that are relevant to understanding the neurobiological basis of emotion processing. PMID:23805313

Common and distinct neural mechanisms of attentional switching and response conflict.

PubMed

Kim, Chobok; Johnson, Nathan F; Gold, Brian T

2012-08-21

The human capacities for overcoming prepotent actions and flexibly switching between tasks represent cornerstones of cognitive control. Functional neuroimaging has implicated a diverse set of brain regions contributing to each of these cognitive control processes. However, the extent to which attentional switching and response conflict draw on shared or distinct neural mechanisms remains unclear. The current study examined the neural correlates of response conflict and attentional switching using event-related functional magnetic resonance imaging (fMRI) and a fully randomized 2×2 design. We manipulated an arrow-word version of the Stroop task to measure conflict and switching in the context of a single task decision, in response to a common set of stimuli. Under these common conditions, both behavioral and imaging data showed significant main effects of conflict and switching but no interaction. However, conjunction analyses identified frontal regions involved in both switching and response conflict, including the dorsal anterior cingulate cortex (dACC) and left inferior frontal junction. In addition, connectivity analyses demonstrated task-dependent functional connectivity patterns between dACC and inferior temporal cortex for attentional switching and between dACC and posterior parietal cortex for response conflict. These results suggest that the brain makes use of shared frontal regions, but can dynamically modulate the connectivity patterns of some of those regions, to deal with attentional switching and response conflict. Copyright © 2012 Elsevier B.V. All rights reserved.

[The mechanism and function of hippocampal neural oscillation].

PubMed

Lu, Ning; Xing, Dan-Qin; Sheng, Tao; Lu, Wei

2017-10-25

Neural oscillation is rhythmic or repetitive neural activity in the central nervous system that is usually generated by oscillatory activity of neuronal ensembles, reflecting regular and synchronized activities within these cell populations. According to several oscillatory bands covering frequencies from approximately 0.5 Hz to >100 Hz, neural oscillations are usually classified as delta oscillation (0.5-3 Hz), theta oscillation (4-12 Hz), beta oscillation (12-30 Hz), gamma oscillation (30-100 Hz) and sharp-wave ripples (>100 Hz ripples superimposed on 0.01-3 Hz sharp waves). Neural oscillation in different frequencies can be detected in different brain regions of human and animal during perception, motion and sleep, and plays an essential role in cognition, learning and memory process. In this review, we summarize recent findings on neural oscillations in hippocampus, as well as the mechanism and function of hippocampal theta oscillation, gamma oscillation and sharp-wave ripples. This review may yield new insights into the functions of neural oscillation in general.

Using Neural Networks to Describe Tracer Correlations

NASA Technical Reports Server (NTRS)

Lary, D. J.; Mueller, M. D.; Mussa, H. Y.

2003-01-01

Neural networks are ideally suited to describe the spatial and temporal dependence of tracer-tracer correlations. The neural network performs well even in regions where the correlations are less compact and normally a family of correlation curves would be required. For example, the CH4-N2O correlation can be well described using a neural network trained with the latitude, pressure, time of year, and CH4 volume mixing ratio (v.m.r.). In this study a neural network using Quickprop learning and one hidden layer with eight nodes was able to reproduce the CH4-N2O correlation with a correlation co- efficient of 0.9995. Such an accurate representation of tracer-tracer correlations allows more use to be made of long-term datasets to constrain chemical models. Such as the dataset from the Halogen Occultation Experiment (HALOE) which has continuously observed CH4, (but not N2O) from 1991 till the present. The neural network Fortran code used is available for download.

Differences in Neural Activity when Processing Emotional Arousal and Valence in Autism Spectrum Disorders

PubMed Central

Tseng, Angela; Wang, Zhishun; Huo, Yuankai; Goh, Suzanne; Russell, James A.; Peterson, Bradley S.

2016-01-01

Individuals with autism spectrum disorders (ASD) often have difficulty recognizing and interpreting facial expressions of emotion, which may impair their ability to navigate and communicate successfully in their social, interpersonal environments. Characterizing specific differences between individuals with ASD and their typically-developing (TD) counterparts in the neural activity subserving their experience of emotional faces may provide distinct targets for ASD interventions. Thus we used functional magnetic resonance imaging (fMRI) and a parametric experimental design to identify brain regions in which neural activity correlated with ratings of arousal and valence for a broad range of emotional faces. Participants (51 ASD, 84 TD) were group-matched by age, sex, IQ, race, and socioeconomic status. Using task-related change in blood-oxygen-level-dependent (BOLD) fMRI signal as a measure, and covarying for age, sex, FSIQ, and ADOS scores, we detected significant differences across diagnostic groups in the neural activity subserving the dimension of arousal but not valence. BOLD-signal in TD participants correlated inversely with ratings of arousal in regions associated primarily with attentional functions, whereas BOLD-signal in ASD participants correlated positively with arousal ratings in regions commonly associated with impulse control and default-mode activity. Only minor differences were detected between groups in the BOLD signal correlates of valence ratings. Our findings provide unique insight into the emotional experiences of individuals with ASD. Although behavioral responses to face-stimuli were comparable across diagnostic groups, the corresponding neural activity for our ASD and TD groups differed dramatically. The near absence of group differences for valence correlates and the presence of strong group differences for arousal correlates suggest that individuals with ASD are not atypical in all aspects of emotion-processing. Studying these similarities

Deep learning for predicting the monsoon over the homogeneous regions of India

NASA Astrophysics Data System (ADS)

Saha, Moumita; Mitra, Pabitra; Nanjundiah, Ravi S.

2017-06-01

Indian monsoon varies in its nature over the geographical regions. Predicting the rainfall not just at the national level, but at the regional level is an important task. In this article, we used a deep neural network, namely, the stacked autoencoder to automatically identify climatic factors that are capable of predicting the rainfall over the homogeneous regions of India. An ensemble regression tree model is used for monsoon prediction using the identified climatic predictors. The proposed model provides forecast of the monsoon at a long lead time which supports the government to implement appropriate policies for the economic growth of the country. The monsoon of the central, north-east, north-west, and south-peninsular India regions are predicted with errors of 4.1%, 5.1%, 5.5%, and 6.4%, respectively. The identified predictors show high skill in predicting the regional monsoon having high variability. The proposed model is observed to be competitive with the state-of-the-art prediction models.

Neural crest contributions to the lamprey head

NASA Technical Reports Server (NTRS)

McCauley, David W.; Bronner-Fraser, Marianne

2003-01-01

The neural crest is a vertebrate-specific cell population that contributes to the facial skeleton and other derivatives. We have performed focal DiI injection into the cranial neural tube of the developing lamprey in order to follow the migratory pathways of discrete groups of cells from origin to destination and to compare neural crest migratory pathways in a basal vertebrate to those of gnathostomes. The results show that the general pathways of cranial neural crest migration are conserved throughout the vertebrates, with cells migrating in streams analogous to the mandibular and hyoid streams. Caudal branchial neural crest cells migrate ventrally as a sheet of cells from the hindbrain and super-pharyngeal region of the neural tube and form a cylinder surrounding a core of mesoderm in each pharyngeal arch, similar to that seen in zebrafish and axolotl. In addition to these similarities, we also uncovered important differences. Migration into the presumptive caudal branchial arches of the lamprey involves both rostral and caudal movements of neural crest cells that have not been described in gnathostomes, suggesting that barriers that constrain rostrocaudal movement of cranial neural crest cells may have arisen after the agnathan/gnathostome split. Accordingly, neural crest cells from a single axial level contributed to multiple arches and there was extensive mixing between populations. There was no apparent filling of neural crest derivatives in a ventral-to-dorsal order, as has been observed in higher vertebrates, nor did we find evidence of a neural crest contribution to cranial sensory ganglia. These results suggest that migratory constraints and additional neural crest derivatives arose later in gnathostome evolution.

Greater neural pattern similarity across repetitions is associated with better memory.

PubMed

Xue, Gui; Dong, Qi; Chen, Chuansheng; Lu, Zhonglin; Mumford, Jeanette A; Poldrack, Russell A

2010-10-01

Repeated study improves memory, but the underlying neural mechanisms of this improvement are not well understood. Using functional magnetic resonance imaging and representational similarity analysis of brain activity, we found that, compared with forgotten items, subsequently remembered faces and words showed greater similarity in neural activation across multiple study in many brain regions, including (but not limited to) the regions whose mean activities were correlated with subsequent memory. This result addresses a longstanding debate in the study of memory by showing that successful episodic memory encoding occurs when the same neural representations are more precisely reactivated across study episodes, rather than when patterns of activation are more variable across time.

Processing the Bouguer anomaly map of Biga and the surrounding area by the cellular neural network: application to the southwestern Marmara region

NASA Astrophysics Data System (ADS)

Aydogan, D.

2007-04-01

An image processing technique called the cellular neural network (CNN) approach is used in this study to locate geological features giving rise to gravity anomalies such as faults or the boundary of two geologic zones. CNN is a stochastic image processing technique based on template optimization using the neighborhood relationships of cells. These cells can be characterized by a functional block diagram that is typical of neural network theory. The functionality of CNN is described in its entirety by a number of small matrices (A, B and I) called the cloning template. CNN can also be considered to be a nonlinear convolution of these matrices. This template describes the strength of the nearest neighbor interconnections in the network. The recurrent perceptron learning algorithm (RPLA) is used in optimization of cloning template. The CNN and standard Canny algorithms were first tested on two sets of synthetic gravity data with the aim of checking the reliability of the proposed approach. The CNN method was compared with classical derivative techniques by applying the cross-correlation method (CC) to the same anomaly map as this latter approach can detect some features that are difficult to identify on the Bouguer anomaly maps. This approach was then applied to the Bouguer anomaly map of Biga and its surrounding area, in Turkey. Structural features in the area between Bandirma, Biga, Yenice and Gonen in the southwest Marmara region are investigated by applying the CNN and CC to the Bouguer anomaly map. Faults identified by these algorithms are generally in accordance with previously mapped surface faults. These examples show that the geologic boundaries can be detected from Bouguer anomaly maps using the cloning template approach. A visual evaluation of the outputs of the CNN and CC approaches is carried out, and the results are compared with each other. This approach provides quantitative solutions based on just a few assumptions, which makes the method more

Psychopathic traits linked to alterations in neural activity during personality judgments of self and others.

PubMed

Deming, Philip; Philippi, Carissa L; Wolf, Richard C; Dargis, Monika; Kiehl, Kent A; Koenigs, Michael

2018-01-01

Psychopathic individuals are notorious for their grandiose sense of self-worth and disregard for the welfare of others. One potential psychological mechanism underlying these traits is the relative consideration of "self" versus "others". Here we used task-based functional magnetic resonance imaging (fMRI) to identify neural responses during personality trait judgments about oneself and a familiar other in a sample of adult male incarcerated offenders ( n  = 57). Neural activity was regressed on two clusters of psychopathic traits: Factor 1 (e.g., egocentricity and lack of empathy) and Factor 2 (e.g., impulsivity and irresponsibility). Contrary to our hypotheses, Factor 1 scores were not significantly related to neural activity during self- or other-judgments. However, Factor 2 traits were associated with diminished activation to self-judgments, in relation to other-judgments, in bilateral posterior cingulate cortex and right temporoparietal junction. These findings highlight cortical regions associated with a dimension of social-affective cognition that may underlie psychopathic individuals' impulsive traits.

Neural correlates of empathic accuracy in adolescence

PubMed Central

Kral, Tammi R A; Solis, Enrique; Mumford, Jeanette A; Schuyler, Brianna S; Flook, Lisa; Rifken, Katharine; Patsenko, Elena G

2017-01-01

Abstract Empathy, the ability to understand others’ emotions, can occur through perspective taking and experience sharing. Neural systems active when adults empathize include regions underlying perspective taking (e.g. medial prefrontal cortex; MPFC) and experience sharing (e.g. inferior parietal lobule; IPL). It is unknown whether adolescents utilize networks implicated in both experience sharing and perspective taking when accurately empathizing. This question is critical given the importance of accurately understanding others’ emotions for developing and maintaining adaptive peer relationships during adolescence. We extend the literature on empathy in adolescence by determining the neural basis of empathic accuracy, a behavioral assay of empathy that does not bias participants toward the exclusive use of perspective taking or experience sharing. Participants (N = 155, aged 11.1–15.5 years) watched videos of ‘targets’ describing emotional events and continuously rated the targets’ emotions during functional magnetic resonance imaging scanning. Empathic accuracy related to activation in regions underlying perspective taking (MPFC, temporoparietal junction and superior temporal sulcus), while activation in regions underlying experience sharing (IPL, anterior cingulate cortex and anterior insula) related to lower empathic accuracy. These results provide novel insight into the neural basis of empathic accuracy in adolescence and suggest that perspective taking processes may be effective for increasing empathy. PMID:28981837

Changes in the interaction of resting-state neural networks from adolescence to adulthood.

PubMed

Stevens, Michael C; Pearlson, Godfrey D; Calhoun, Vince D

2009-08-01

This study examined how the mutual interactions of functionally integrated neural networks during resting-state fMRI differed between adolescence and adulthood. Independent component analysis (ICA) was used to identify functionally connected neural networks in 100 healthy participants aged 12-30 years. Hemodynamic timecourses that represented integrated neural network activity were analyzed with tools that quantified system "causal density" estimates, which indexed the proportion of significant Granger causality relationships among system nodes. Mutual influences among networks decreased with age, likely reflecting stronger within-network connectivity and more efficient between-network influences with greater development. Supplemental tests showed that this normative age-related reduction in causal density was accompanied by fewer significant connections to and from each network, regional increases in the strength of functional integration within networks, and age-related reductions in the strength of numerous specific system interactions. The latter included paths between lateral prefrontal-parietal circuits and "default mode" networks. These results contribute to an emerging understanding that activity in widely distributed networks thought to underlie complex cognition influences activity in other networks. (c) 2009 Wiley-Liss, Inc.

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

A review on cluster estimation methods and their application to neural spike data

NASA Astrophysics Data System (ADS)

Zhang, James; Nguyen, Thanh; Cogill, Steven; Bhatti, Asim; Luo, Lingkun; Yang, Samuel; Nahavandi, Saeid

2018-06-01

The extracellular action potentials recorded on an electrode result from the collective simultaneous electrophysiological activity of an unknown number of neurons. Identifying and assigning these action potentials to their firing neurons—‘spike sorting’—is an indispensable step in studying the function and the response of an individual or ensemble of neurons to certain stimuli. Given the task of neural spike sorting, the determination of the number of clusters (neurons) is arguably the most difficult and challenging issue, due to the existence of background noise and the overlap and interactions among neurons in neighbouring regions. It is not surprising that some researchers still rely on visual inspection by experts to estimate the number of clusters in neural spike sorting. Manual inspection, however, is not suitable to processing the vast, ever-growing amount of neural data. To address this pressing need, in this paper, thirty-three clustering validity indices have been comprehensively reviewed and implemented to determine the number of clusters in neural datasets. To gauge the suitability of the indices to neural spike data, and inform the selection process, we then calculated the indices by applying k-means clustering to twenty widely used synthetic neural datasets and one empirical dataset, and compared the performance of these indices against pre-existing ground truth labels. The results showed that the top five validity indices work consistently well across variations in noise level, both for the synthetic datasets and the real dataset. Using these top performing indices provides strong support for the determination of the number of neural clusters, which is essential in the spike sorting process.

Practical method to identify orbital anomaly as spacecraft breakup in the geostationary region

NASA Astrophysics Data System (ADS)

Hanada, Toshiya; Uetsuhara, Masahiko; Nakaniwa, Yoshitaka

2012-07-01

Identifying a spacecraft breakup is an essential issue to define the current orbital debris environment. This paper proposes a practical method to identify an orbital anomaly, which appears as a significant discontinuity in the observation data, as a spacecraft breakup. The proposed method is applicable to orbital anomalies in the geostationary region. Long-term orbital evolutions of breakup fragments may conclude that their orbital planes will converge into several corresponding regions in inertial space even if the breakup epoch is not specified. This empirical method combines the aforementioned conclusion with the search strategy developed at Kyushu University, which can identify origins of observed objects as fragments released from a specified spacecraft. This practical method starts with selecting a spacecraft that experienced an orbital anomaly, and formulates a hypothesis to generate fragments from the anomaly. Then, the search strategy is applied to predict the behavior of groups of fragments hypothetically generated. Outcome of this predictive analysis specifies effectively when, where and how we should conduct optical measurements using ground-based telescopes. Objects detected based on the outcome are supposed to be from the anomaly, so that we can confirm the anomaly as a spacecraft breakup to release the detected objects. This paper also demonstrates observation planning for a spacecraft anomaly in the geostationary region.

Neural activation during delay discounting is associated with 6-month change in risky sexual behavior in adolescents.

PubMed

Gardiner, Casey K; Karoly, Hollis C; Thayer, Rachel E; Gillman, Arielle S; Sabbineni, Amithrupa; Bryan, Angela D

2018-04-19

Identifying cognitive and neural mechanisms of decision making in adolescence can enhance understanding of, and interventions to reduce, risky health behaviors in adolescence. Delay discounting, or the propensity to discount the magnitude of temporally distal rewards, has been associated with diverse health risk behaviors, including risky sex. This cognitive process involves recruitment of reward and cognitive control brain regions, which develop on different trajectories in adolescence and are also implicated in real-world risky decision making. However, no extant research has examined how neural activation during delay discounting is associated with adolescents' risky sexual behavior. To determine whether a relationship exists between adolescents' risky sexual behavior and neural activation during delay discounting. Adolescent participants completed a delay discounting paradigm during functional magnetic resonance imaging (fMRI) scanning, and they reported risky sexual behavior at baseline, 3-, 6-, 9-, and 12-month follow-up time points. Latent growth curve models were employed to determine relationships between brain activation during delay discounting and change in risky sexual behavior over time. Greater activation in brain regions associated with reward and cognitive control (caudate, putamen, nucleus accumbens, anterior cingulate, insula, orbitofrontal cortex, inferior frontal gyrus, dorsolateral prefrontal cortex) during delay discounting was associated with lower mean levels of risky sexual behavior but greater growth over the period from baseline to 6 months. Neural activation during delay discounting is cross-sectionally and prospectively associated with risky sexual behavior in adolescence, highlighting a neural basis of risky decision-making as well as opportunities for early identification and intervention.

Genome-wide association study identifies 74 loci associated with educational attainment

PubMed Central

Okbay, Aysu; Beauchamp, Jonathan P.; Fontana, Mark A.; Lee, James J.; Pers, Tune H.; Rietveld, Cornelius A.; Turley, Patrick; Chen, Guo-Bo; Emilsson, Valur; Meddens, S. Fleur W.; Oskarsson, Sven; Pickrell, Joseph K.; Thom, Kevin; Timshel, Pascal; de Vlaming, Ronald; Abdellaoui, Abdel; Ahluwalia, Tarunveer S.; Bacelis, Jonas; Baumbach, Clemens; Bjornsdottir, Gyda; Brandsma, Johannes H.; Concas, Maria Pina; Derringer, Jaime; Furlotte, Nicholas A.; Galesloot, Tessel E.; Girotto, Giorgia; Gupta, Richa; Hall, Leanne M.; Harris, Sarah E.; Hofer, Edith; Horikoshi, Momoko; Huffman, Jennifer E.; Kaasik, Kadri; Kalafati, Ioanna P.; Karlsson, Robert; Kong, Augustine; Lahti, Jari; van der Lee, Sven J.; de Leeuw, Christiaan; Lind, Penelope A.; Lindgren, Karl-Oskar; Liu, Tian; Mangino, Massimo; Marten, Jonathan; Mihailov, Evelin; Miller, Michael B.; van der Most, Peter J.; Oldmeadow, Christopher; Payton, Antony; Pervjakova, Natalia; Peyrot, Wouter J.; Qian, Yong; Raitakari, Olli; Rueedi, Rico; Salvi, Erika; Schmidt, Börge; Schraut, Katharina E.; Shi, Jianxin; Smith, Albert V.; Poot, Raymond A.; Pourcain, Beate; Teumer, Alexander; Thorleifsson, Gudmar; Verweij, Niek; Vuckovic, Dragana; Wellmann, Juergen; Westra, Harm-Jan; Yang, Jingyun; Zhao, Wei; Zhu, Zhihong; Alizadeh, Behrooz Z.; Amin, Najaf; Bakshi, Andrew; Baumeister, Sebastian E.; Biino, Ginevra; Bønnelykke, Klaus; Boyle, Patricia A.; Campbell, Harry; Cappuccio, Francesco P.; Davies, Gail; De Neve, Jan-Emmanuel; Deloukas, Panos; Demuth, Ilja; Ding, Jun; Eibich, Peter; Eisele, Lewin; Eklund, Niina; Evans68, David M.; Faul, Jessica D.; Feitosa, Mary F.; Forstner, Andreas J.; Gandin, Ilaria; Gunnarsson, Bjarni; Halldórsson, Bjarni V.; Harris, Tamara B.; Heath, Andrew C.; Hocking, Lynne J.; Holliday, Elizabeth G.; Homuth, Georg; Horan, Michael A.; Hottenga, Jouke-Jan; de Jager, Philip L.; Joshi, Peter K.; Jugessur, Astanand; Kaakinen, Marika A.; Kähönen, Mika; Kanoni, Stavroula; Keltigangas-Järvinen, Liisa; Kiemeney, Lambertus A.L.M.; Kolcic, Ivana; Koskinen, Seppo; Kraja, Aldi T.; Kroh, Martin; Kutalik, Zoltan; Latvala, Antti; Launer, Lenore J.; Lebreton, Maël P.; Levinson, Douglas F.; Lichtenstein, Paul; Lichtner, Peter; Liewald, David C.M.; Loukola, Anu; Madden, Pamela A.; Mägi, Reedik; Mäki-Opas, Tomi; Marioni, Riccardo E.; Marques-Vidal, Pedro; Meddens, Gerardus A.; McMahon, George; Meisinger, Christa; Meitinger, Thomas; Milaneschi, Yusplitri; Milani, Lili; Montgomery, Grant W.; Myhre, Ronny; Nelson, Christopher P.; Nyholt, Dale R.; Ollier, William E.R.; Palotie, Aarno; Paternoster, Lavinia; Pedersen, Nancy L.; Petrovic, Katja E.; Porteous, David J.; Räikkönen, Katri; Ring, Susan M.; Robino, Antonietta; Rostapshova, Olga; Rudan, Igor; Rustichini, Aldo; Salomaa, Veikko; Sanders, Alan R.; Sarin, Antti-Pekka; Schmidt, Helena; Scott, Rodney J.; Smith, Blair H.; Smith, Jennifer A.; Staessen, Jan A.; Steinhagen-Thiessen, Elisabeth; Strauch, Konstantin; Terracciano, Antonio; Tobin, Martin D.; Ulivi, Sheila; Vaccargiu, Simona; Quaye, Lydia; van Rooij, Frank J.A.; Venturini, Cristina; Vinkhuyzen, Anna A.E.; Völker, Uwe; Völzke, Henry; Vonk, Judith M.; Vozzi, Diego; Waage, Johannes; Ware, Erin B.; Willemsen, Gonneke; Attia, John R.; Bennett, David A.; Berger, Klaus; Bertram, Lars; Bisgaard, Hans; Boomsma, Dorret I.; Borecki, Ingrid B.; Bultmann, Ute; Chabris, Christopher F.; Cucca, Francesco; Cusi, Daniele; Deary, Ian J.; Dedoussis, George V.; van Duijn, Cornelia M.; Eriksson, Johan G.; Franke, Barbara; Franke, Lude; Gasparini, Paolo; Gejman, Pablo V.; Gieger, Christian; Grabe, Hans-Jörgen; Gratten, Jacob; Groenen, Patrick J.F.; Gudnason, Vilmundur; van der Harst, Pim; Hayward, Caroline; Hinds, David A.; Hoffmann, Wolfgang; Hyppönen, Elina; Iacono, William G.; Jacobsson, Bo; Järvelin, Marjo-Riitta; Jöckel, Karl-Heinz; Kaprio, Jaakko; Kardia, Sharon L.R.; Lehtimäki, Terho; Lehrer, Steven F.; Magnusson, Patrik K.E.; Martin, Nicholas G.; McGue, Matt; Metspalu, Andres; Pendleton, Neil; Penninx, Brenda W.J.H.; Perola, Markus; Pirastu, Nicola; Pirastu, Mario; Polasek, Ozren; Posthuma, Danielle; Power, Christine; Province, Michael A.; Samani, Nilesh J.; Schlessinger, David; Schmidt, Reinhold; Sørensen, Thorkild I.A.; Spector, Tim D.; Stefansson, Kari; Thorsteinsdottir, Unnur; Thurik, A. Roy; Timpson, Nicholas J.; Tiemeier, Henning; Tung, Joyce Y.; Uitterlinden, André G.; Vitart, Veronique; Vollenweider, Peter; Weir, David R.; Wilson, James F.; Wright, Alan F.; Conley, Dalton C.; Krueger, Robert F.; Smith, George Davey; Hofman, Albert; Laibson, David I.; Medland, Sarah E.; Meyer, Michelle N.; Yang, Jian; Johannesson, Magnus; Visscher, Peter M.; Esko, Tõnu; Koellinger, Philipp D.; Cesarini, David; Benjamin, Daniel J.

2016-01-01

Summary Educational attainment (EA) is strongly influenced by social and other environmental factors, but genetic factors are also estimated to account for at least 20% of the variation across individuals1. We report the results of a genome-wide association study (GWAS) for EA that extends our earlier discovery sample1,2 of 101,069 individuals to 293,723 individuals, and a replication in an independent sample of 111,349 individuals from the UK Biobank. We now identify 74 genome-wide significant loci associated with number of years of schooling completed. Single-nucleotide polymorphisms (SNPs) associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioral phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because EA is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric disease. PMID:27225129

Genome-wide association study identifies 74 loci associated with educational attainment.

PubMed

Okbay, Aysu; Beauchamp, Jonathan P; Fontana, Mark Alan; Lee, James J; Pers, Tune H; Rietveld, Cornelius A; Turley, Patrick; Chen, Guo-Bo; Emilsson, Valur; Meddens, S Fleur W; Oskarsson, Sven; Pickrell, Joseph K; Thom, Kevin; Timshel, Pascal; de Vlaming, Ronald; Abdellaoui, Abdel; Ahluwalia, Tarunveer S; Bacelis, Jonas; Baumbach, Clemens; Bjornsdottir, Gyda; Brandsma, Johannes H; Pina Concas, Maria; Derringer, Jaime; Furlotte, Nicholas A; Galesloot, Tessel E; Girotto, Giorgia; Gupta, Richa; Hall, Leanne M; Harris, Sarah E; Hofer, Edith; Horikoshi, Momoko; Huffman, Jennifer E; Kaasik, Kadri; Kalafati, Ioanna P; Karlsson, Robert; Kong, Augustine; Lahti, Jari; van der Lee, Sven J; deLeeuw, Christiaan; Lind, Penelope A; Lindgren, Karl-Oskar; Liu, Tian; Mangino, Massimo; Marten, Jonathan; Mihailov, Evelin; Miller, Michael B; van der Most, Peter J; Oldmeadow, Christopher; Payton, Antony; Pervjakova, Natalia; Peyrot, Wouter J; Qian, Yong; Raitakari, Olli; Rueedi, Rico; Salvi, Erika; Schmidt, Börge; Schraut, Katharina E; Shi, Jianxin; Smith, Albert V; Poot, Raymond A; St Pourcain, Beate; Teumer, Alexander; Thorleifsson, Gudmar; Verweij, Niek; Vuckovic, Dragana; Wellmann, Juergen; Westra, Harm-Jan; Yang, Jingyun; Zhao, Wei; Zhu, Zhihong; Alizadeh, Behrooz Z; Amin, Najaf; Bakshi, Andrew; Baumeister, Sebastian E; Biino, Ginevra; Bønnelykke, Klaus; Boyle, Patricia A; Campbell, Harry; Cappuccio, Francesco P; Davies, Gail; De Neve, Jan-Emmanuel; Deloukas, Panos; Demuth, Ilja; Ding, Jun; Eibich, Peter; Eisele, Lewin; Eklund, Niina; Evans, David M; Faul, Jessica D; Feitosa, Mary F; Forstner, Andreas J; Gandin, Ilaria; Gunnarsson, Bjarni; Halldórsson, Bjarni V; Harris, Tamara B; Heath, Andrew C; Hocking, Lynne J; Holliday, Elizabeth G; Homuth, Georg; Horan, Michael A; Hottenga, Jouke-Jan; de Jager, Philip L; Joshi, Peter K; Jugessur, Astanand; Kaakinen, Marika A; Kähönen, Mika; Kanoni, Stavroula; Keltigangas-Järvinen, Liisa; Kiemeney, Lambertus A L M; Kolcic, Ivana; Koskinen, Seppo; Kraja, Aldi T; Kroh, Martin; Kutalik, Zoltan; Latvala, Antti; Launer, Lenore J; Lebreton, Maël P; Levinson, Douglas F; Lichtenstein, Paul; Lichtner, Peter; Liewald, David C M; Loukola, Anu; Madden, Pamela A; Mägi, Reedik; Mäki-Opas, Tomi; Marioni, Riccardo E; Marques-Vidal, Pedro; Meddens, Gerardus A; McMahon, George; Meisinger, Christa; Meitinger, Thomas; Milaneschi, Yusplitri; Milani, Lili; Montgomery, Grant W; Myhre, Ronny; Nelson, Christopher P; Nyholt, Dale R; Ollier, William E R; Palotie, Aarno; Paternoster, Lavinia; Pedersen, Nancy L; Petrovic, Katja E; Porteous, David J; Räikkönen, Katri; Ring, Susan M; Robino, Antonietta; Rostapshova, Olga; Rudan, Igor; Rustichini, Aldo; Salomaa, Veikko; Sanders, Alan R; Sarin, Antti-Pekka; Schmidt, Helena; Scott, Rodney J; Smith, Blair H; Smith, Jennifer A; Staessen, Jan A; Steinhagen-Thiessen, Elisabeth; Strauch, Konstantin; Terracciano, Antonio; Tobin, Martin D; Ulivi, Sheila; Vaccargiu, Simona; Quaye, Lydia; van Rooij, Frank J A; Venturini, Cristina; Vinkhuyzen, Anna A E; Völker, Uwe; Völzke, Henry; Vonk, Judith M; Vozzi, Diego; Waage, Johannes; Ware, Erin B; Willemsen, Gonneke; Attia, John R; Bennett, David A; Berger, Klaus; Bertram, Lars; Bisgaard, Hans; Boomsma, Dorret I; Borecki, Ingrid B; Bültmann, Ute; Chabris, Christopher F; Cucca, Francesco; Cusi, Daniele; Deary, Ian J; Dedoussis, George V; van Duijn, Cornelia M; Eriksson, Johan G; Franke, Barbara; Franke, Lude; Gasparini, Paolo; Gejman, Pablo V; Gieger, Christian; Grabe, Hans-Jörgen; Gratten, Jacob; Groenen, Patrick J F; Gudnason, Vilmundur; van der Harst, Pim; Hayward, Caroline; Hinds, David A; Hoffmann, Wolfgang; Hyppönen, Elina; Iacono, William G; Jacobsson, Bo; Järvelin, Marjo-Riitta; Jöckel, Karl-Heinz; Kaprio, Jaakko; Kardia, Sharon L R; Lehtimäki, Terho; Lehrer, Steven F; Magnusson, Patrik K E; Martin, Nicholas G; McGue, Matt; Metspalu, Andres; Pendleton, Neil; Penninx, Brenda W J H; Perola, Markus; Pirastu, Nicola; Pirastu, Mario; Polasek, Ozren; Posthuma, Danielle; Power, Christine; Province, Michael A; Samani, Nilesh J; Schlessinger, David; Schmidt, Reinhold; Sørensen, Thorkild I A; Spector, Tim D; Stefansson, Kari; Thorsteinsdottir, Unnur; Thurik, A Roy; Timpson, Nicholas J; Tiemeier, Henning; Tung, Joyce Y; Uitterlinden, André G; Vitart, Veronique; Vollenweider, Peter; Weir, David R; Wilson, James F; Wright, Alan F; Conley, Dalton C; Krueger, Robert F; Davey Smith, George; Hofman, Albert; Laibson, David I; Medland, Sarah E; Meyer, Michelle N; Yang, Jian; Johannesson, Magnus; Visscher, Peter M; Esko, Tõnu; Koellinger, Philipp D; Cesarini, David; Benjamin, Daniel J

2016-05-26

Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases.

Examining Neural Correlates of Psychopathology Using a Lesion-Based Approach.

PubMed

Calamia, Matthew; Markon, Kristian E; Sutterer, Matthew J; Tranel, Daniel

2018-06-22

Studies of individuals with focal brain damage have long been used to expand understanding of the neural basis of psychopathology. However, most previous studies were conducted using small sample sizes and relatively coarse methods for measuring psychopathology or mapping brain-behavior relationships. Here, we examined the factor structure and neural correlates of psychopathology in 232 individuals with focal brain damage, using their responses to the Minnesota Multiphasic Personality Inventory-2-Restructured Form (MMPI-2-RF). Factor analysis and voxel-based lesion symptom mapping were used to examine the structure and neural correlates of psychopathology in this sample. Consistent with existing MMPI-2-RF literature, separate internalizing, externalizing, and psychotic symptom dimensions were found. In addition, a somatic dimension likely reflecting neurological symptoms was identified. Damage to the medial temporal lobe, including the hippocampus, was associated with scales related to both internalizing problems and psychoticism. Damage to the medial temporal lobe and orbitofrontal cortex was associated with both a general distrust of others and beliefs that one is being personally targeted by others. These findings provide evidence for the critical role of dysfunction in specific frontal and temporal regions in the development of psychopathology. Copyright © 2018. Published by Elsevier Ltd.

Molecular profiling of aged neural progenitors identifies Dbx2 as a candidate regulator of age-associated neurogenic decline.

PubMed

Lupo, Giuseppe; Nisi, Paola S; Esteve, Pilar; Paul, Yu-Lee; Novo, Clara Lopes; Sidders, Ben; Khan, Muhammad A; Biagioni, Stefano; Liu, Hai-Kun; Bovolenta, Paola; Cacci, Emanuele; Rugg-Gunn, Peter J

2018-06-01

Adult neurogenesis declines with aging due to the depletion and functional impairment of neural stem/progenitor cells (NSPCs). An improved understanding of the underlying mechanisms that drive age-associated neurogenic deficiency could lead to the development of strategies to alleviate cognitive impairment and facilitate neuroregeneration. An essential step towards this aim is to investigate the molecular changes that occur in NSPC aging on a genomewide scale. In this study, we compare the transcriptional, histone methylation and DNA methylation signatures of NSPCs derived from the subventricular zone (SVZ) of young adult (3 months old) and aged (18 months old) mice. Surprisingly, the transcriptional and epigenomic profiles of SVZ-derived NSPCs are largely unchanged in aged cells. Despite the global similarities, we detect robust age-dependent changes at several hundred genes and regulatory elements, thereby identifying putative regulators of neurogenic decline. Within this list, the homeobox gene Dbx2 is upregulated in vitro and in vivo, and its promoter region has altered histone and DNA methylation levels, in aged NSPCs. Using functional in vitro assays, we show that elevated Dbx2 expression in young adult NSPCs promotes age-related phenotypes, including the reduced proliferation of NSPC cultures and the altered transcript levels of age-associated regulators of NSPC proliferation and differentiation. Depleting Dbx2 in aged NSPCs caused the reverse gene expression changes. Taken together, these results provide new insights into the molecular programmes that are affected during mouse NSPC aging, and uncover a new functional role for Dbx2 in promoting age-related neurogenic decline. © 2018 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.

Racial bias in neural empathic responses to pain.

PubMed

Contreras-Huerta, Luis Sebastian; Baker, Katharine S; Reynolds, Katherine J; Batalha, Luisa; Cunnington, Ross

2013-01-01

Recent studies have shown that perceiving the pain of others activates brain regions in the observer associated with both somatosensory and affective-motivational aspects of pain, principally involving regions of the anterior cingulate and anterior insula cortex. The degree of these empathic neural responses is modulated by racial bias, such that stronger neural activation is elicited by observing pain in people of the same racial group compared with people of another racial group. The aim of the present study was to examine whether a more general social group category, other than race, could similarly modulate neural empathic responses and perhaps account for the apparent racial bias reported in previous studies. Using a minimal group paradigm, we assigned participants to one of two mixed-race teams. We use the term race to refer to the Chinese or Caucasian appearance of faces and whether the ethnic group represented was the same or different from the appearance of the participant' own face. Using fMRI, we measured neural empathic responses as participants observed members of their own group or other group, and members of their own race or other race, receiving either painful or non-painful touch. Participants showed clear group biases, with no significant effect of race, on behavioral measures of implicit (affective priming) and explicit group identification. Neural responses to observed pain in the anterior cingulate cortex, insula cortex, and somatosensory areas showed significantly greater activation when observing pain in own-race compared with other-race individuals, with no significant effect of minimal groups. These results suggest that racial bias in neural empathic responses is not influenced by minimal forms of group categorization, despite the clear association participants showed with in-group more than out-group members. We suggest that race may be an automatic and unconscious mechanism that drives the initial neural responses to observed pain in

Racial Bias in Neural Empathic Responses to Pain

PubMed Central

Contreras-Huerta, Luis Sebastian; Baker, Katharine S.; Reynolds, Katherine J.; Batalha, Luisa; Cunnington, Ross

2013-01-01

Recent studies have shown that perceiving the pain of others activates brain regions in the observer associated with both somatosensory and affective-motivational aspects of pain, principally involving regions of the anterior cingulate and anterior insula cortex. The degree of these empathic neural responses is modulated by racial bias, such that stronger neural activation is elicited by observing pain in people of the same racial group compared with people of another racial group. The aim of the present study was to examine whether a more general social group category, other than race, could similarly modulate neural empathic responses and perhaps account for the apparent racial bias reported in previous studies. Using a minimal group paradigm, we assigned participants to one of two mixed-race teams. We use the term race to refer to the Chinese or Caucasian appearance of faces and whether the ethnic group represented was the same or different from the appearance of the participant' own face. Using fMRI, we measured neural empathic responses as participants observed members of their own group or other group, and members of their own race or other race, receiving either painful or non-painful touch. Participants showed clear group biases, with no significant effect of race, on behavioral measures of implicit (affective priming) and explicit group identification. Neural responses to observed pain in the anterior cingulate cortex, insula cortex, and somatosensory areas showed significantly greater activation when observing pain in own-race compared with other-race individuals, with no significant effect of minimal groups. These results suggest that racial bias in neural empathic responses is not influenced by minimal forms of group categorization, despite the clear association participants showed with in-group more than out-group members. We suggest that race may be an automatic and unconscious mechanism that drives the initial neural responses to observed pain in

Visual motion imagery neurofeedback based on the hMT+/V5 complex: evidence for a feedback-specific neural circuit involving neocortical and cerebellar regions.

PubMed

Banca, Paula; Sousa, Teresa; Duarte, Isabel Catarina; Castelo-Branco, Miguel

2015-12-01

Current approaches in neurofeedback/brain-computer interface research often focus on identifying, on a subject-by-subject basis, the neural regions that are best suited for self-driven modulation. It is known that the hMT+/V5 complex, an early visual cortical region, is recruited during explicit and implicit motion imagery, in addition to real motion perception. This study tests the feasibility of training healthy volunteers to regulate the level of activation in their hMT+/V5 complex using real-time fMRI neurofeedback and visual motion imagery strategies. We functionally localized the hMT+/V5 complex to further use as a target region for neurofeedback. An uniform strategy based on motion imagery was used to guide subjects to neuromodulate hMT+/V5. We found that 15/20 participants achieved successful neurofeedback. This modulation led to the recruitment of a specific network as further assessed by psychophysiological interaction analysis. This specific circuit, including hMT+/V5, putative V6 and medial cerebellum was activated for successful neurofeedback runs. The putamen and anterior insula were recruited for both successful and non-successful runs. Our findings indicate that hMT+/V5 is a region that can be modulated by focused imagery and that a specific cortico-cerebellar circuit is recruited during visual motion imagery leading to successful neurofeedback. These findings contribute to the debate on the relative potential of extrinsic (sensory) versus intrinsic (default-mode) brain regions in the clinical application of neurofeedback paradigms. This novel circuit might be a good target for future neurofeedback approaches that aim, for example, the training of focused attention in disorders such as ADHD.

Visual motion imagery neurofeedback based on the hMT+/V5 complex: evidence for a feedback-specific neural circuit involving neocortical and cerebellar regions

NASA Astrophysics Data System (ADS)

Banca, Paula; Sousa, Teresa; Catarina Duarte, Isabel; Castelo-Branco, Miguel

2015-12-01

Objective. Current approaches in neurofeedback/brain-computer interface research often focus on identifying, on a subject-by-subject basis, the neural regions that are best suited for self-driven modulation. It is known that the hMT+/V5 complex, an early visual cortical region, is recruited during explicit and implicit motion imagery, in addition to real motion perception. This study tests the feasibility of training healthy volunteers to regulate the level of activation in their hMT+/V5 complex using real-time fMRI neurofeedback and visual motion imagery strategies. Approach. We functionally localized the hMT+/V5 complex to further use as a target region for neurofeedback. An uniform strategy based on motion imagery was used to guide subjects to neuromodulate hMT+/V5. Main results. We found that 15/20 participants achieved successful neurofeedback. This modulation led to the recruitment of a specific network as further assessed by psychophysiological interaction analysis. This specific circuit, including hMT+/V5, putative V6 and medial cerebellum was activated for successful neurofeedback runs. The putamen and anterior insula were recruited for both successful and non-successful runs. Significance. Our findings indicate that hMT+/V5 is a region that can be modulated by focused imagery and that a specific cortico-cerebellar circuit is recruited during visual motion imagery leading to successful neurofeedback. These findings contribute to the debate on the relative potential of extrinsic (sensory) versus intrinsic (default-mode) brain regions in the clinical application of neurofeedback paradigms. This novel circuit might be a good target for future neurofeedback approaches that aim, for example, the training of focused attention in disorders such as ADHD.

A similarity based approach to identify homogeneous regions for seasonal forecasting

NASA Astrophysics Data System (ADS)

Schick, Simon; Rössler, Ole; Weingartner, Rolf

2015-04-01

Seasonal runoff forecasting using statistical models is challenged by a large number of candidate predictors and a general weak predictor-predictand relationship. As the area of the target basin increases, often also the available data sets do, thus reinforcing the predictor selection challenge. We propose an approach which follows the idea of 'divide and conquer' as developed in computational sciences and machine learning: First, the macroscale target basin is partitioned into homogeneous regions using all its gauged mesoscale subbasins. Second, one representative subbasin per homogeneous region is identified, for which models are fitted and applied. Third, the resulting forecasts are combined at the scale of the macroscale target basin. This approach requires a suitable method to identify homogeneous regions and representative subbasins. We suggest a way based on hydrological similarity, as catchment similarity estimated with respect to physiographic-climatic descriptors does not necessarily imply similar runoff response. Each descriptor is derived from daily runoff series and aimed to reflect a specific catchment characteristic: autocorrelation coefficient, parameters of fitted Gamma distribution and low/high flow indices (based on daily runoff values) fluctuation of the standard deviation within the yearly cycle (based on weekly runoff values) dominant harmonics obtained from the discrete Fourier transform (based on monthly runoff values) long term trend (based on yearly runoff values) Where necessary, the runoff series first need to be standardized, aggregated, detrended or deseasonalized. As a preliminary study we present the results of a cluster analysis for the Swiss Rhine River as macroscale target basin, which leads to about 40 mesoscale subbasins with runoff series for the period 1991-2010. Problems we have to address include the choice of a clustering algorithm, the identification of an appropriate number of regions and the selection of representative

Functional and structural neural alterations in Internet gaming disorder: A systematic review and meta-analysis.

PubMed

Yao, Yuan-Wei; Liu, Lu; Ma, Shan-Shan; Shi, Xin-Hui; Zhou, Nan; Zhang, Jin-Tao; Potenza, Marc N

2017-12-01

This meta-analytic study aimed to identify the common and specific neural alterations in Internet gaming disorder (IGD) across different domains and modalities. Two separate meta-analyses for functional neural activation and gray-matter volume were conducted. Sub-meta-analyses for the domains of reward, cold-executive, and hot-executive functions were also performed, respectively. IGD subjects, compared with healthy controls, showed: (1) hyperactivation in the anterior and posterior cingulate cortices, caudate, posterior inferior frontal gyrus (IFG), which were mainly associated with studies measuring reward and cold-executive functions; and, (2) hypoactivation in the anterior IFG in relation to hot-executive function, the posterior insula, somatomotor and somatosensory cortices in relation to reward function. Furthermore, IGD subjects showed reduced gray-matter volume in the anterior cingulate, orbitofrontal, dorsolateral prefrontal, and premotor cortices. These findings suggest that IGD is associated with both functional and structural neural alterations in fronto-striatal and fronto-cingulate regions. Moreover, multi-domain assessments capture different aspects of neural alterations in IGD, which may be helpful for developing effective interventions targeting specific functions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Demonstration of a neural circuit critical for imprinting behavior in chicks.

PubMed

Nakamori, Tomoharu; Sato, Katsushige; Atoji, Yasuro; Kanamatsu, Tomoyuki; Tanaka, Kohichi; Ohki-Hamazaki, Hiroko

2010-03-24

Imprinting behavior in birds is elicited by visual and/or auditory cues. It has been demonstrated previously that visual cues are recognized and processed in the visual Wulst (VW), and imprinting memory is stored in the intermediate medial mesopallium (IMM) of the telencephalon. Alteration of neural responses in these two regions according to imprinting has been reported, yet direct evidence of the neural circuit linking these two regions is lacking. Thus, it remains unclear how memory is formed and expressed in this circuit. Here, we present anatomical as well as physiological evidence of the neural circuit connecting the VW and IMM and show that imprinting training during the critical period strengthens and refines this circuit. A functional connection established by imprint training resulted in an imprinting behavior. After the closure of the critical period, training could not activate this circuit nor induce the imprinting behavior. Glutamatergic neurons in the ventroposterior region of the VW, the core region of the hyperpallium densocellulare (HDCo), sent their axons to the periventricular part of the HD, just dorsal and afferent to the IMM. We found that the HDCo is important in imprinting behavior. The refinement and/or enhancement of this neural circuit are attributed to increased activity of HDCo cells, and the activity depended on NR2B-containing NMDA receptors. These findings show a neural connection in the telencephalon in Aves and demonstrate that NR2B function is indispensable for the plasticity of HDCo cells, which are key mediators of imprinting.

A Genome-Wide Association Study Identifies Multiple Regions Associated with Head Size in Catfish

PubMed Central

Geng, Xin; Liu, Shikai; Yao, Jun; Bao, Lisui; Zhang, Jiaren; Li, Chao; Wang, Ruijia; Sha, Jin; Zeng, Peng; Zhi, Degui; Liu, Zhanjiang

2016-01-01

Skull morphology is fundamental to evolution and the biological adaptation of species to their environments. With aquaculture fish species, head size is also important for economic reasons because it has a direct impact on fillet yield. However, little is known about the underlying genetic basis of head size. Catfish is the primary aquaculture species in the United States. In this study, we performed a genome-wide association study using the catfish 250K SNP array with backcross hybrid catfish to map the QTL for head size (head length, head width, and head depth). One significantly associated region on linkage group (LG) 7 was identified for head length. In addition, LGs 7, 9, and 16 contain suggestively associated regions for head length. For head width, significantly associated regions were found on LG9, and additional suggestively associated regions were identified on LGs 5 and 7. No region was found associated with head depth. Head size genetic loci were mapped in catfish to genomic regions with candidate genes involved in bone development. Comparative analysis indicated that homologs of several candidate genes are also involved in skull morphology in various other species ranging from amphibian to mammalian species, suggesting possible evolutionary conservation of those genes in the control of skull morphologies. PMID:27558670

Neural correlates of own- and other-race face recognition in children: A functional near-infrared spectroscopy study

PubMed Central

Ding, Xiao Pan; Fu, Genyue; Lee, Kang

2013-01-01

The present study used the functional Near-infrared Spectroscopy (fNIRS) methodology to investigate the neural correlates of elementary school children’s own- and other-race face processing. An old-new paradigm was used to assess children’s recognition ability of own- and other-race faces. FNIRS data revealed that other-race faces elicited significantly greater [oxy-Hb] changes than own-race faces in the right middle frontal gyrus and inferior frontal gyrus regions (BA9) and the left cuneus (BA18). With increased age, the [oxy-Hb] activity differences between own- and other-race faces, or the neural other-race effect (NORE), underwent significant changes in these two cortical areas: at younger ages, the neural response to the other-race faces was modestly greater than that to the own-race faces, but with increased age, the neural response to the own-race faces became increasingly greater than that to the other-race faces. Moreover, these areas had strong regional functional connectivity with a swath of the cortical regions in terms of the neural other-race effect that also changed with increased age. We also found significant and positive correlations between the behavioral other-race effect (reaction time) and the neural other-race effect in the right middle frontal gyrus and inferior frontal gyrus regions (BA9). These results taken together suggest that children, like adults, devote different amounts of neural resources to processing own- and other-race faces, but the size and direction of the neural other-race effect and associated functional regional connectivity change with increased age. PMID:23891903

Neural correlates of own- and other-race face recognition in children: a functional near-infrared spectroscopy study.

PubMed

Ding, Xiao Pan; Fu, Genyue; Lee, Kang

2014-01-15

The present study used the functional Near-infrared Spectroscopy (fNIRS) methodology to investigate the neural correlates of elementary school children's own- and other-race face processing. An old-new paradigm was used to assess children's recognition ability of own- and other-race faces. FNIRS data revealed that other-race faces elicited significantly greater [oxy-Hb] changes than own-race faces in the right middle frontal gyrus and inferior frontal gyrus regions (BA9) and the left cuneus (BA18). With increased age, the [oxy-Hb] activity differences between own- and other-race faces, or the neural other-race effect (NORE), underwent significant changes in these two cortical areas: at younger ages, the neural response to the other-race faces was modestly greater than that to the own-race faces, but with increased age, the neural response to the own-race faces became increasingly greater than that to the other-race faces. Moreover, these areas had strong regional functional connectivity with a swath of the cortical regions in terms of the neural other-race effect that also changed with increased age. We also found significant and positive correlations between the behavioral other-race effect (reaction time) and the neural other-race effect in the right middle frontal gyrus and inferior frontal gyrus regions (BA9). These results taken together suggest that children, like adults, devote different amounts of neural resources to processing own- and other-race faces, but the size and direction of the neural other-race effect and associated functional regional connectivity change with increased age. © 2013.

A state space approach for piecewise-linear recurrent neural networks for identifying computational dynamics from neural measurements.

PubMed

Durstewitz, Daniel

2017-06-01

The computational and cognitive properties of neural systems are often thought to be implemented in terms of their (stochastic) network dynamics. Hence, recovering the system dynamics from experimentally observed neuronal time series, like multiple single-unit recordings or neuroimaging data, is an important step toward understanding its computations. Ideally, one would not only seek a (lower-dimensional) state space representation of the dynamics, but would wish to have access to its statistical properties and their generative equations for in-depth analysis. Recurrent neural networks (RNNs) are a computationally powerful and dynamically universal formal framework which has been extensively studied from both the computational and the dynamical systems perspective. Here we develop a semi-analytical maximum-likelihood estimation scheme for piecewise-linear RNNs (PLRNNs) within the statistical framework of state space models, which accounts for noise in both the underlying latent dynamics and the observation process. The Expectation-Maximization algorithm is used to infer the latent state distribution, through a global Laplace approximation, and the PLRNN parameters iteratively. After validating the procedure on toy examples, and using inference through particle filters for comparison, the approach is applied to multiple single-unit recordings from the rodent anterior cingulate cortex (ACC) obtained during performance of a classical working memory task, delayed alternation. Models estimated from kernel-smoothed spike time data were able to capture the essential computational dynamics underlying task performance, including stimulus-selective delay activity. The estimated models were rarely multi-stable, however, but rather were tuned to exhibit slow dynamics in the vicinity of a bifurcation point. In summary, the present work advances a semi-analytical (thus reasonably fast) maximum-likelihood estimation framework for PLRNNs that may enable to recover relevant aspects

Do Political and Economic Choices Rely on Common Neural Substrates? A Systematic Review of the Emerging Neuropolitics Literature.

PubMed

Krastev, Sekoul; McGuire, Joseph T; McNeney, Denver; Kable, Joseph W; Stolle, Dietlind; Gidengil, Elisabeth; Fellows, Lesley K

2016-01-01

The methods of cognitive neuroscience are beginning to be applied to the study of political behavior. The neural substrates of value-based decision-making have been extensively examined in economic contexts; this might provide a powerful starting point for understanding political decision-making. Here, we asked to what extent the neuropolitics literature to date has used conceptual frameworks and experimental designs that make contact with the reward-related approaches that have dominated decision neuroscience. We then asked whether the studies of political behavior that can be considered in this light implicate the brain regions that have been associated with subjective value related to "economic" reward. We performed a systematic literature review to identify papers addressing the neural substrates of political behavior and extracted the fMRI studies reporting behavioral measures of subjective value as defined in decision neuroscience studies of reward. A minority of neuropolitics studies met these criteria and relatively few brain activation foci from these studies overlapped with regions where activity has been related to subjective value. These findings show modest influence of reward-focused decision neuroscience on neuropolitics research to date. Whether the neural substrates of subjective value identified in economic choice paradigms generalize to political choice thus remains an open question. We argue that systematically addressing the commonalities and differences in these two classes of value-based choice will be important in developing a more comprehensive model of the brain basis of human decision-making.

Do Political and Economic Choices Rely on Common Neural Substrates? A Systematic Review of the Emerging Neuropolitics Literature

PubMed Central

Krastev, Sekoul; McGuire, Joseph T.; McNeney, Denver; Kable, Joseph W.; Stolle, Dietlind; Gidengil, Elisabeth; Fellows, Lesley K.

2016-01-01

The methods of cognitive neuroscience are beginning to be applied to the study of political behavior. The neural substrates of value-based decision-making have been extensively examined in economic contexts; this might provide a powerful starting point for understanding political decision-making. Here, we asked to what extent the neuropolitics literature to date has used conceptual frameworks and experimental designs that make contact with the reward-related approaches that have dominated decision neuroscience. We then asked whether the studies of political behavior that can be considered in this light implicate the brain regions that have been associated with subjective value related to “economic” reward. We performed a systematic literature review to identify papers addressing the neural substrates of political behavior and extracted the fMRI studies reporting behavioral measures of subjective value as defined in decision neuroscience studies of reward. A minority of neuropolitics studies met these criteria and relatively few brain activation foci from these studies overlapped with regions where activity has been related to subjective value. These findings show modest influence of reward-focused decision neuroscience on neuropolitics research to date. Whether the neural substrates of subjective value identified in economic choice paradigms generalize to political choice thus remains an open question. We argue that systematically addressing the commonalities and differences in these two classes of value-based choice will be important in developing a more comprehensive model of the brain basis of human decision-making. PMID:26941703

Neural Patterns of the Implicit Association Test

PubMed Central

Healy, Graham F.; Boran, Lorraine; Smeaton, Alan F.

2015-01-01

The Implicit Association Test (IAT) is a reaction time based categorization task that measures the differential associative strength between bipolar targets and evaluative attribute concepts as an approach to indexing implicit beliefs or biases. An open question exists as to what exactly the IAT measures, and here EEG (Electroencephalography) has been used to investigate the time course of ERPs (Event-related Potential) indices and implicated brain regions in the IAT. IAT-EEG research identifies a number of early (250–450 ms) negative ERPs indexing early-(pre-response) processing stages of the IAT. ERP activity in this time range is known to index processes related to cognitive control and semantic processing. A central focus of these efforts has been to use IAT-ERPs to delineate the implicit and explicit factors contributing to measured IAT effects. Increasing evidence indicates that cognitive control (and related top-down modulation of attention/perceptual processing) may be components in the effective measurement of IAT effects, as factors such as physical setting or task instruction can change an IAT measurement. In this study we further implicate the role of proactive cognitive control and top-down modulation of attention/perceptual processing in the IAT-EEG. We find statistically significant relationships between D-score (a reaction-time based measure of the IAT-effect) and early ERP-time windows, indicating where more rapid word categorizations driving the IAT effect are present, they are at least partly explainable by neural activity not significantly correlated with the IAT measurement itself. Using LORETA, we identify a number of brain regions driving these ERP-IAT relationships notably involving left-temporal, insular, cingulate, medial frontal and parietal cortex in time regions corresponding to the N2- and P3-related activity. The identified brain regions involved with reduced reaction times on congruent blocks coincide with those of previous studies

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.

Cell delamination in the mesencephalic neural fold and its implication for the origin of ectomesenchyme

PubMed Central

Lee, Raymond Teck Ho; Nagai, Hiroki; Nakaya, Yukiko; Sheng, Guojun; Trainor, Paul A.; Weston, James A.; Thiery, Jean Paul

2013-01-01

The neural crest is a transient structure unique to vertebrate embryos that gives rise to multiple lineages along the rostrocaudal axis. In cranial regions, neural crest cells are thought to differentiate into chondrocytes, osteocytes, pericytes and stromal cells, which are collectively termed ectomesenchyme derivatives, as well as pigment and neuronal derivatives. There is still no consensus as to whether the neural crest can be classified as a homogenous multipotent population of cells. This unresolved controversy has important implications for the formation of ectomesenchyme and for confirmation of whether the neural fold is compartmentalized into distinct domains, each with a different repertoire of derivatives. Here we report in mouse and chicken that cells in the neural fold delaminate over an extended period from different regions of the cranial neural fold to give rise to cells with distinct fates. Importantly, cells that give rise to ectomesenchyme undergo epithelial-mesenchymal transition from a lateral neural fold domain that does not express definitive neural markers, such as Sox1 and N-cadherin. Additionally, the inference that cells originating from the cranial neural ectoderm have a common origin and cell fate with trunk neural crest cells prompted us to revisit the issue of what defines the neural crest and the origin of the ectomesenchyme. PMID:24198279

In silico lineage tracing through single cell transcriptomics identifies a neural stem cell population in planarians.

PubMed

Molinaro, Alyssa M; Pearson, Bret J

2016-04-27

The planarian Schmidtea mediterranea is a master regenerator with a large adult stem cell compartment. The lack of transgenic labeling techniques in this animal has hindered the study of lineage progression and has made understanding the mechanisms of tissue regeneration a challenge. However, recent advances in single-cell transcriptomics and analysis methods allow for the discovery of novel cell lineages as differentiation progresses from stem cell to terminally differentiated cell. Here we apply pseudotime analysis and single-cell transcriptomics to identify adult stem cells belonging to specific cellular lineages and identify novel candidate genes for future in vivo lineage studies. We purify 168 single stem and progeny cells from the planarian head, which were subjected to single-cell RNA sequencing (scRNAseq). Pseudotime analysis with Waterfall and gene set enrichment analysis predicts a molecularly distinct neoblast sub-population with neural character (νNeoblasts) as well as a novel alternative lineage. Using the predicted νNeoblast markers, we demonstrate that a novel proliferative stem cell population exists adjacent to the brain. scRNAseq coupled with in silico lineage analysis offers a new approach for studying lineage progression in planarians. The lineages identified here are extracted from a highly heterogeneous dataset with minimal prior knowledge of planarian lineages, demonstrating that lineage purification by transgenic labeling is not a prerequisite for this approach. The identification of the νNeoblast lineage demonstrates the usefulness of the planarian system for computationally predicting cellular lineages in an adult context coupled with in vivo verification.

Neural substrates of decision-making.

PubMed

Broche-Pérez, Y; Herrera Jiménez, L F; Omar-Martínez, E

2016-06-01

Decision-making is the process of selecting a course of action from among 2 or more alternatives by considering the potential outcomes of selecting each option and estimating its consequences in the short, medium and long term. The prefrontal cortex (PFC) has traditionally been considered the key neural structure in decision-making process. However, new studies support the hypothesis that describes a complex neural network including both cortical and subcortical structures. The aim of this review is to summarise evidence on the anatomical structures underlying the decision-making process, considering new findings that support the existence of a complex neural network that gives rise to this complex neuropsychological process. Current evidence shows that the cortical structures involved in decision-making include the orbitofrontal cortex (OFC), anterior cingulate cortex (ACC), and dorsolateral prefrontal cortex (DLPFC). This process is assisted by subcortical structures including the amygdala, thalamus, and cerebellum. Findings to date show that both cortical and subcortical brain regions contribute to the decision-making process. The neural basis of decision-making is a complex neural network of cortico-cortical and cortico-subcortical connections which includes subareas of the PFC, limbic structures, and the cerebellum. Copyright © 2014 Sociedad Española de Neurología. Published by Elsevier España, S.L.U. All rights reserved.

Neural crest specification and migration independently require NSD3-related lysine methyltransferase activity

PubMed Central

Jacques-Fricke, Bridget T.; Gammill, Laura S.

2014-01-01

Neural crest precursors express genes that cause them to become migratory, multipotent cells, distinguishing them from adjacent stationary neural progenitors in the neurepithelium. Histone methylation spatiotemporally regulates neural crest gene expression; however, the protein methyltransferases active in neural crest precursors are unknown. Moreover, the regulation of methylation during the dynamic process of neural crest migration is unclear. Here we show that the lysine methyltransferase NSD3 is abundantly and specifically expressed in premigratory and migratory neural crest cells. NSD3 expression commences before up-regulation of neural crest genes, and NSD3 is necessary for expression of the neural plate border gene Msx1, as well as the key neural crest transcription factors Sox10, Snail2, Sox9, and FoxD3, but not gene expression generally. Nevertheless, only Sox10 histone H3 lysine 36 dimethylation requires NSD3, revealing unexpected complexity in NSD3-dependent neural crest gene regulation. In addition, by temporally limiting expression of a dominant negative to migratory stages, we identify a novel, direct requirement for NSD3-related methyltransferase activity in neural crest migration. These results identify NSD3 as the first protein methyltransferase essential for neural crest gene expression during specification and show that NSD3-related methyltransferase activity independently regulates migration. PMID:25318671

From neural-based object recognition toward microelectronic eyes

NASA Technical Reports Server (NTRS)

Sheu, Bing J.; Bang, Sa Hyun

1994-01-01

Engineering neural network systems are best known for their abilities to adapt to the changing characteristics of the surrounding environment by adjusting system parameter values during the learning process. Rapid advances in analog current-mode design techniques have made possible the implementation of major neural network functions in custom VLSI chips. An electrically programmable analog synapse cell with large dynamic range can be realized in a compact silicon area. New designs of the synapse cells, neurons, and analog processor are presented. A synapse cell based on Gilbert multiplier structure can perform the linear multiplication for back-propagation networks. A double differential-pair synapse cell can perform the Gaussian function for radial-basis network. The synapse cells can be biased in the strong inversion region for high-speed operation or biased in the subthreshold region for low-power operation. The voltage gain of the sigmoid-function neurons is externally adjustable which greatly facilitates the search of optimal solutions in certain networks. Various building blocks can be intelligently connected to form useful industrial applications. Efficient data communication is a key system-level design issue for large-scale networks. We also present analog neural processors based on perceptron architecture and Hopfield network for communication applications. Biologically inspired neural networks have played an important role towards the creation of powerful intelligent machines. Accuracy, limitations, and prospects of analog current-mode design of the biologically inspired vision processing chips and cellular neural network chips are key design issues.

Regional Homogeneity Predicts Creative Insight: A Resting-State fMRI Study.

PubMed

Lin, Jiabao; Cui, Xuan; Dai, Xiaoying; Mo, Lei

2018-01-01

Creative insight plays an important role in our daily life. Previous studies have investigated the neural correlates of creative insight by functional magnetic resonance imaging (fMRI), however, the intrinsic resting-state brain activity associated with creative insight is still unclear. In the present study, we used regional homogeneity (ReHo) as an index in resting-state fMRI (rs-fMRI) to identify brain regions involved in individual differences in creative insight, which was compued by the response time (RT) of creative Chinese character chunk decomposition. The findings indicated that ReHo in the anterior cingulate cortex (ACC)/caudate nucleus (CN) and angular gyrus (AG)/superior temporal gyrus (STG)/inferior parietal lobe (IPL) negatively predicted creative insight. Furthermore, these findings suggested that spontaneous brain activity in multiple regions related to breaking and establishing mental sets, goal-directed solutions exploring, shifting attention, forming new associations and emotion experience contributes to creative insight. In conclusion, the present study provides new evidence to further understand the cognitive processing and neural correlates of creative insight.

Targeting Neural Endophenotypes of Eating Disorders with Non-invasive Brain Stimulation

PubMed Central

Dunlop, Katharine A.; Woodside, Blake; Downar, Jonathan

2016-01-01

The term “eating disorders” (ED) encompasses a wide variety of disordered eating and compensatory behaviors, and so the term is associated with considerable clinical and phenotypic heterogeneity. This heterogeneity makes optimizing treatment techniques difficult. One class of treatments is non-invasive brain stimulation (NIBS). NIBS, including repetitive transcranial magnetic stimulation (rTMS) and transcranial direct current stimulation (tDCS), are accessible forms of neuromodulation that alter the cortical excitability of a target brain region. It is crucial for NIBS to be successful that the target is well selected for the patient population in question. Targets may best be selected by stepping back from conventional DSM-5 diagnostic criteria to identify neural substrates of more basic phenotypes, including behavior related to rewards and punishment, cognitive control, and social processes. These phenotypic dimensions have been recently laid out by the Research Domain Criteria (RDoC) initiative. Consequently, this review is intended to identify potential dimensions as outlined by the RDoC and the underlying behavioral and neurobiological targets associated with ED. This review will also identify candidate targets for NIBS based on these dimensions and review the available literature on rTMS and tDCS in ED. This review systematically reviews abnormal neural circuitry in ED within the RDoC framework, and also systematically reviews the available literature investigating NIBS as a treatment for ED. PMID:26909013

Technologies for imaging neural activity in large volumes

PubMed Central

Ji, Na; Freeman, Jeremy; Smith, Spencer L.

2017-01-01

Neural circuitry has evolved to form distributed networks that act dynamically across large volumes. Collecting data from individual planes, conventional microscopy cannot sample circuitry across large volumes at the temporal resolution relevant to neural circuit function and behaviors. Here, we review emerging technologies for rapid volume imaging of neural circuitry. We focus on two critical challenges: the inertia of optical systems, which limits image speed, and aberrations, which restrict the image volume. Optical sampling time must be long enough to ensure high-fidelity measurements, but optimized sampling strategies and point spread function engineering can facilitate rapid volume imaging of neural activity within this constraint. We also discuss new computational strategies for the processing and analysis of volume imaging data of increasing size and complexity. Together, optical and computational advances are providing a broader view of neural circuit dynamics, and help elucidate how brain regions work in concert to support behavior. PMID:27571194

Neural signatures of social conformity: A coordinate-based activation likelihood estimation meta-analysis of functional brain imaging studies.

PubMed

Wu, Haiyan; Luo, Yi; Feng, Chunliang

2016-12-01

People often align their behaviors with group opinions, known as social conformity. Many neuroscience studies have explored the neuropsychological mechanisms underlying social conformity. Here we employed a coordinate-based meta-analysis on neuroimaging studies of social conformity with the purpose to reveal the convergence of the underlying neural architecture. We identified a convergence of reported activation foci in regions associated with normative decision-making, including ventral striatum (VS), dorsal posterior medial frontal cortex (dorsal pMFC), and anterior insula (AI). Specifically, consistent deactivation of VS and activation of dorsal pMFC and AI are identified when people's responses deviate from group opinions. In addition, the deviation-related responses in dorsal pMFC predict people's conforming behavioral adjustments. These are consistent with current models that disagreement with others might evoke "error" signals, cognitive imbalance, and/or aversive feelings, which are plausibly detected in these brain regions as control signals to facilitate subsequent conforming behaviors. Finally, group opinions result in altered neural correlates of valuation, manifested as stronger responses of VS to stimuli endorsed than disliked by others. Copyright © 2016 Elsevier Ltd. All rights reserved.

Digital transcriptome profiling of normal and glioblastoma-derived neural stem cells identifies genes associated with patient survival

PubMed Central

2012-01-01

Background Glioblastoma multiforme, the most common type of primary brain tumor in adults, is driven by cells with neural stem (NS) cell characteristics. Using derivation methods developed for NS cells, it is possible to expand tumorigenic stem cells continuously in vitro. Although these glioblastoma-derived neural stem (GNS) cells are highly similar to normal NS cells, they harbor mutations typical of gliomas and initiate authentic tumors following orthotopic xenotransplantation. Here, we analyzed GNS and NS cell transcriptomes to identify gene expression alterations underlying the disease phenotype. Methods Sensitive measurements of gene expression were obtained by high-throughput sequencing of transcript tags (Tag-seq) on adherent GNS cell lines from three glioblastoma cases and two normal NS cell lines. Validation by quantitative real-time PCR was performed on 82 differentially expressed genes across a panel of 16 GNS and 6 NS cell lines. The molecular basis and prognostic relevance of expression differences were investigated by genetic characterization of GNS cells and comparison with public data for 867 glioma biopsies. Results Transcriptome analysis revealed major differences correlated with glioma histological grade, and identified misregulated genes of known significance in glioblastoma as well as novel candidates, including genes associated with other malignancies or glioma-related pathways. This analysis further detected several long non-coding RNAs with expression profiles similar to neighboring genes implicated in cancer. Quantitative PCR validation showed excellent agreement with Tag-seq data (median Pearson r = 0.91) and discerned a gene set robustly distinguishing GNS from NS cells across the 22 lines. These expression alterations include oncogene and tumor suppressor changes not detected by microarray profiling of tumor tissue samples, and facilitated the identification of a GNS expression signature strongly associated with patient survival (P = 1e

Neural loss aversion differences between depression patients and healthy individuals: A functional MRI investigation.

PubMed

Chandrasekhar Pammi, V S; Pillai Geethabhavan Rajesh, Purushothaman; Kesavadas, Chandrasekharan; Rappai Mary, Paramban; Seema, Satish; Radhakrishnan, Ashalatha; Sitaram, Ranganatha

2015-04-01

Neuroeconomics employs neuroscience techniques to explain decision-making behaviours. Prospect theory, a prominent model of decision-making, features a value function with parameters for risk and loss aversion. Recent work with normal participants identified activation related to loss aversion in brain regions including the amygdala, ventral striatum, and ventromedial prefrontal cortex. However, the brain network for loss aversion in pathologies such as depression has yet to be identified. The aim of the current study is to employ the value function from prospect theory to examine behavioural and neural manifestations of loss aversion in depressed and healthy individuals to identify the neurobiological markers of loss aversion in economic behaviour. We acquired behavioural data and fMRI scans while healthy controls and patients with depression performed an economic decision-making task. Behavioural loss aversion was higher in patients with depression than in healthy controls. fMRI results revealed that the two groups shared a brain network for value function including right ventral striatum, ventromedial prefrontal cortex, and right amygdala. However, the neural loss aversion results revealed greater activations in the right dorsal striatum and the right anterior insula for controls compared with patients with depression, and higher activations in the midbrain region ventral tegmental area for patients with depression compared with controls. These results suggest that while the brain network for loss aversion is shared between depressed and healthy individuals, some differences exist with respect to differential activation of additional areas. Our findings are relevant to identifying neurobiological markers for altered decision-making in the depressed. © The Author(s) 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Dissociation of neural mechanisms underlying orientation processing in humans

PubMed Central

Ling, Sam; Pearson, Joel; Blake, Randolph

2009-01-01

Summary Orientation selectivity is a fundamental, emergent property of neurons in early visual cortex, and discovery of that property [1, 2] dramatically shaped how we conceptualize visual processing [3–6]. However, much remains unknown about the neural substrates of these basic building blocks of perception, and what is known primarily stems from animal physiology studies. To probe the neural concomitants of orientation processing in humans, we employed repetitive transcranial magnetic stimulation (rTMS) to attenuate neural responses evoked by stimuli presented within a local region of the visual field. Previous physiological studies have shown that rTMS can significantly suppress the neuronal spiking activity, hemodynamic responses, and local field potentials within a focused cortical region [7, 8]. By suppressing neural activity with rTMS, we were able to dissociate components of the neural circuitry underlying two distinct aspects of orientation processing: selectivity and contextual effects. Orientation selectivity gauged by masking was unchanged by rTMS, whereas an otherwise robust orientation repulsion illusion was weakened following rTMS. This dissociation implies that orientation processing relies on distinct mechanisms, only one of which was impacted by rTMS. These results are consistent with models positing that orientation selectivity is largely governed by the patterns of convergence of thalamic afferents onto cortical neurons, with intracortical activity then shaping population responses contained within those orientation-selective cortical neurons. PMID:19682905

Common capacity-limited neural mechanisms of selective attention and spatial working memory encoding

PubMed Central

Fusser, Fabian; Linden, David E J; Rahm, Benjamin; Hampel, Harald; Haenschel, Corinna; Mayer, Jutta S

2011-01-01

One characteristic feature of visual working memory (WM) is its limited capacity, and selective attention has been implicated as limiting factor. A possible reason why attention constrains the number of items that can be encoded into WM is that the two processes share limited neural resources. Functional magnetic resonance imaging (fMRI) studies have indeed demonstrated commonalities between the neural substrates of WM and attention. Here we investigated whether such overlapping activations reflect interacting neural mechanisms that could result in capacity limitations. To independently manipulate the demands on attention and WM encoding within one single task, we combined visual search and delayed discrimination of spatial locations. Participants were presented with a search array and performed easy or difficult visual search in order to encode one, three or five positions of target items into WM. Our fMRI data revealed colocalised activation for attention-demanding visual search and WM encoding in distributed posterior and frontal regions. However, further analysis yielded two patterns of results. Activity in prefrontal regions increased additively with increased demands on WM and attention, indicating regional overlap without functional interaction. Conversely, the WM load-dependent activation in visual, parietal and premotor regions was severely reduced during high attentional demand. We interpret this interaction as indicating the sites of shared capacity-limited neural resources. Our findings point to differential contributions of prefrontal and posterior regions to the common neural mechanisms that support spatial WM encoding and attention, providing new imaging evidence for attention-based models of WM encoding. PMID:21781193

Wise promotes coalescence of cells of neural crest and placode origins in the trigeminal region during head development.

PubMed

Shigetani, Yasuyo; Howard, Sara; Guidato, Sonia; Furushima, Kenryo; Abe, Takaya; Itasaki, Nobue

2008-07-15

While most cranial ganglia contain neurons of either neural crest or placodal origin, neurons of the trigeminal ganglion derive from both populations. The Wnt signaling pathway is known to be required for the development of neural crest cells and for trigeminal ganglion formation, however, migrating neural crest cells do not express any known Wnt ligands. Here we demonstrate that Wise, a Wnt modulator expressed in the surface ectoderm overlying the trigeminal ganglion, play a role in promoting the assembly of placodal and neural crest cells. When overexpressed in chick, Wise causes delamination of ectodermal cells and attracts migrating neural crest cells. Overexpression of Wise is thus sufficient to ectopically induce ganglion-like structures consisting of both origins. The function of Wise is likely synergized with Wnt6, expressed in an overlapping manner with Wise in the surface ectoderm. Electroporation of morpholino antisense oligonucleotides against Wise and Wnt6 causes decrease in the contact of neural crest cells with the delaminated placode-derived cells. In addition, targeted deletion of Wise in mouse causes phenotypes that can be explained by a decrease in the contribution of neural crest cells to the ophthalmic lobe of the trigeminal ganglion. These data suggest that Wise is able to function cell non-autonomously on neural crest cells and promote trigeminal ganglion formation.

Secondary neurulation: Fate-mapping and gene manipulation of the neural tube in tail bud.

PubMed

Shimokita, Eisuke; Takahashi, Yoshiko

2011-04-01

The body tail is a characteristic trait of vertebrates, which endows the animals with a variety of locomotive functions. During embryogenesis, the tail develops from the tail bud, where neural and mesodermal tissues make a major contribution. The neural tube in the tail bud develops by the process known as secondary neurulation (SN), where mesenchymal cells undergo epithelialization and tubulogenesis. These processes contrast with the well known primary neurulation, which is achieved by invagination of an epithelial cell sheet. In this study we have identified the origin of SN-undergoing cells, which is located caudo-medially to Hensen's node of early chicken embryo. This region is distinctly fate-mapped from tail-forming mesoderm. The identification of the presumptive SN region has allowed us to target this region with exogenous genes using in ovo electroporation techniques. The SN-transgenesis has further enabled an exploration of molecular mechanisms underlying mesenchymal-to-epithelial transition during SN, where activity levels of Cdc42 and Rac1 are critical. This is the first demonstration of molecular and cellular analyses of SN, which can be performed at a high resolution separately from tail-forming mesoderm. © 2011 The Authors. Journal compilation © 2011 Japanese Society of Developmental Biologists.

Transduction of NeuroD2 protein induced neural cell differentiation.

PubMed

Noda, Tomohide; Kawamura, Ryuzo; Funabashi, Hisakage; Mie, Masayasu; Kobatake, Eiry

2006-11-01

NeuroD2, one of the neurospecific basic helix-loop-helix transcription factors, has the ability to induce neural differentiation in undifferentiated cells. In this paper, we show that transduction of NeuroD2 protein induced mouse neuroblastoma cell line N1E-115 into neural differentiation. NeuroD2 has two basic-rich domains, one is nuclear localization signal (NLS) and the other is basic region of basic helix-loop-helix (basic). We constructed some mutants of NeuroD2, ND2(Delta100-115) (lack of NLS), ND2(Delta123-134) (lack of basic) and ND2(Delta100-134) (lack of both NLS and basic) for transduction experiments. Using these proteins, we have shown that NLS region of NeuroD2 plays a role of protein transduction. Continuous addition of NeuroD2 protein resulted in N1E-115 cells adopting neural morphology after 4 days and Tau mRNA expression was increased. These results suggest that neural differentiation can be induced by direct addition of NeuroD2 protein.

Comparison of Navigation-Related Brain Regions in Migratory versus Non-Migratory Noctuid Moths

PubMed Central

de Vries, Liv; Pfeiffer, Keram; Trebels, Björn; Adden, Andrea K.; Green, Ken; Warrant, Eric; Heinze, Stanley

2017-01-01

Brain structure and function are tightly correlated across all animals. While these relations are ultimately manifestations of differently wired neurons, many changes in neural circuit architecture lead to larger-scale alterations visible already at the level of brain regions. Locating such differences has served as a beacon for identifying brain areas that are strongly associated with the ecological needs of a species—thus guiding the way towards more detailed investigations of how brains underlie species-specific behaviors. Particularly in relation to sensory requirements, volume-differences in neural tissue between closely related species reflect evolutionary investments that correspond to sensory abilities. Likewise, memory-demands imposed by lifestyle have revealed similar adaptations in regions associated with learning. Whether this is also the case for species that differ in their navigational strategy is currently unknown. While the brain regions associated with navigational control in insects have been identified (central complex (CX), lateral complex (LX) and anterior optic tubercles (AOTU)), it remains unknown in what way evolutionary investments have been made to accommodate particularly demanding navigational strategies. We have thus generated average-shape atlases of navigation-related brain regions of a migratory and a non-migratory noctuid moth and used volumetric analysis to identify differences. We further compared the results to identical data from Monarch butterflies. Whereas we found differences in the size of the nodular unit of the AOTU, the LX and the protocerebral bridge (PB) between the two moths, these did not unambiguously reflect migratory behavior across all three species. We conclude that navigational strategy, at least in the case of long-distance migration in lepidopteran insects, is not easily deductible from overall neuropil anatomy. This suggests that the adaptations needed to ensure successful migratory behavior are found in

Cellular basis of neuroepithelial bending during mouse spinal neural tube closure

PubMed Central

McShane, Suzanne G.; Molè, Matteo A.; Savery, Dawn; Greene, Nicholas D. E; Tam, Patrick P.L.; Copp, Andrew J.

2015-01-01

Summary Bending of the neural plate at paired dorsolateral hinge points (DLHPs) is required for neural tube closure in the spinal region of the mouse embryo. As a step towards understanding the morphogenetic mechanism of DLHP development, we examined variations in neural plate cellular architecture and proliferation during closure. Neuroepithelial cells within the median hinge point (MHP) contain nuclei that are mainly basally located and undergo relatively slow proliferation, with a 7 h cell cycle length. In contrast, cells in the dorsolateral neuroepithelium, including the DLHP, exhibit nuclei distributed throughout the apico-basal axis and undergo rapid proliferation, with a 4 h cell cycle length. As the neural folds elevate, cell numbers increase to a greater extent in the dorsolateral neural plate that contacts the surface ectoderm, compared with the more ventromedial neural plate where cells contact paraxial mesoderm and notochord. This marked increase in dorsolateral cell number cannot be accounted for solely on the basis of enhanced cell proliferation in this region. We hypothesised that neuroepithelial cells may translocate in a ventral-to-dorsal direction as DLHP formation occurs, and this was confirmed by vital cell labelling in cultured embryos. The translocation of cells into the neural fold, together with its more rapid cell proliferation, leads to an increase in cell density dorsolaterally compared with the more ventromedial neural plate. These findings suggest a model in which DLHP formation may proceed through ‘buckling’ of the neuroepithelium at a dorso-ventral boundary marked by a change in cell-packing density. PMID:26079577

Neural Correlates of Intolerance of Uncertainty in Clinical Disorders.

PubMed

Wever, Mirjam; Smeets, Paul; Sternheim, Lot

2015-01-01

Intolerance of uncertainty is a key contributor to anxiety-related disorders. Recent studies highlight its importance in other clinical disorders. The link between its clinical presentation and the underlying neural correlates remains unclear. This review summarizes the emerging literature on the neural correlates of intolerance of uncertainty. In conclusion, studies focusing on the neural correlates of this construct are sparse, and findings are inconsistent across disorders. Future research should identify neural correlates of intolerance of uncertainty in more detail. This may unravel the neurobiology of a wide variety of clinical disorders and pave the way for novel therapeutic targets.

Report: Inconsistencies With EPA Policy Identified in Region 10's Biweekly Pay Cap Waiver Process

EPA Pesticide Factsheets

Report #18-P-0068, January 12, 2018. We identified issues with documentation and review of biweekly pay cap waivers at Region 10, resulting from a lack of an internal policy or process. Region 10 recently issued a new procedure that addresses our concerns.

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.

Task modulations of racial bias in neural responses to others' suffering.

PubMed

Sheng, Feng; Liu, Qiang; Li, Hong; Fang, Fang; Han, Shihui

2014-03-01

Recent event related brain potential research observed a greater frontal activity to pain expressions of racial in-group than out-group members and such racial bias in neural responses to others' suffering was modulated by task demands that emphasize race identity or painful feeling. However, as pain expressions activate multiple brain regions in the pain matrix, it remains unclear which part of the neural circuit in response to others' suffering undergoes modulations by task demands. We scanned Chinese adults, using functional MRI, while they categorized Asian and Caucasian faces with pain or neutral expressions in terms of race or identified painful feelings of each individual face. We found that pain vs. neutral expressions of Asian but not Caucasian faces activated the anterior cingulate (ACC) and anterior insular (AI) activity during race judgments. However, pain compared to race judgments increased ACC and AI activity to pain expressions of Caucasian but not Asian faces. Moreover, race judgments induced increased activity in the dorsal medial prefrontal cortex whereas pain judgments increased activity in the bilateral temporoparietal junction. The results suggest that task demands emphasizing an individual's painful feeling increase ACC/AI activities to pain expressions of racial out-group members and reduce the racial bias in empathic neural responses. © 2013.

A sequence-based hybrid predictor for identifying conformationally ambivalent regions in proteins.

PubMed

Liu, Yu-Cheng; Yang, Meng-Han; Lin, Win-Li; Huang, Chien-Kang; Oyang, Yen-Jen

2009-12-03

Proteins are dynamic macromolecules which may undergo conformational transitions upon changes in environment. As it has been observed in laboratories that protein flexibility is correlated to essential biological functions, scientists have been designing various types of predictors for identifying structurally flexible regions in proteins. In this respect, there are two major categories of predictors. One category of predictors attempts to identify conformationally flexible regions through analysis of protein tertiary structures. Another category of predictors works completely based on analysis of the polypeptide sequences. As the availability of protein tertiary structures is generally limited, the design of predictors that work completely based on sequence information is crucial for advances of molecular biology research. In this article, we propose a novel approach to design a sequence-based predictor for identifying conformationally ambivalent regions in proteins. The novelty in the design stems from incorporating two classifiers based on two distinctive supervised learning algorithms that provide complementary prediction powers. Experimental results show that the overall performance delivered by the hybrid predictor proposed in this article is superior to the performance delivered by the existing predictors. Furthermore, the case study presented in this article demonstrates that the proposed hybrid predictor is capable of providing the biologists with valuable clues about the functional sites in a protein chain. The proposed hybrid predictor provides the users with two optional modes, namely, the high-sensitivity mode and the high-specificity mode. The experimental results with an independent testing data set show that the proposed hybrid predictor is capable of delivering sensitivity of 0.710 and specificity of 0.608 under the high-sensitivity mode, while delivering sensitivity of 0.451 and specificity of 0.787 under the high-specificity mode. Though

Neural networks for self-learning control systems

NASA Technical Reports Server (NTRS)

Nguyen, Derrick H.; Widrow, Bernard

1990-01-01

It is shown how a neural network can learn of its own accord to control a nonlinear dynamic system. An emulator, a multilayered neural network, learns to identify the system's dynamic characteristics. The controller, another multilayered neural network, next learns to control the emulator. The self-trained controller is then used to control the actual dynamic system. The learning process continues as the emulator and controller improve and track the physical process. An example is given to illustrate these ideas. The 'truck backer-upper,' a neural network controller that steers a trailer truck while the truck is backing up to a loading dock, is demonstrated. The controller is able to guide the truck to the dock from almost any initial position. The technique explored should be applicable to a wide variety of nonlinear control problems.

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.

Neural activity in the posterior superior temporal region during eye contact perception correlates with autistic traits.

PubMed

Hasegawa, Naoya; Kitamura, Hideaki; Murakami, Hiroatsu; Kameyama, Shigeki; Sasagawa, Mutsuo; Egawa, Jun; Endo, Taro; Someya, Toshiyuki

2013-08-09

The present study investigated the relationship between neural activity associated with gaze processing and autistic traits in typically developed subjects using magnetoencephalography. Autistic traits in 24 typically developed college students with normal intelligence were assessed using the Autism Spectrum Quotient (AQ). The Minimum Current Estimates method was applied to estimate the cortical sources of magnetic responses to gaze stimuli. These stimuli consisted of apparent motion of the eyes, displaying direct or averted gaze motion. Results revealed gaze-related brain activations in the 150-250 ms time window in the right posterior superior temporal sulcus (pSTS), and in the 150-450 ms time window in medial prefrontal regions. In addition, the mean amplitude in the 150-250 ms time window in the right pSTS region was modulated by gaze direction, and its activity in response to direct gaze stimuli correlated with AQ score. pSTS activation in response to direct gaze is thought to be related to higher-order social processes. Thus, these results suggest that brain activity linking eye contact and social signals is associated with autistic traits in a typical population. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Neural microgenesis of personally familiar face recognition

PubMed Central

Ramon, Meike; Vizioli, Luca; Liu-Shuang, Joan; Rossion, Bruno

2015-01-01

Despite a wealth of information provided by neuroimaging research, the neural basis of familiar face recognition in humans remains largely unknown. Here, we isolated the discriminative neural responses to unfamiliar and familiar faces by slowly increasing visual information (i.e., high-spatial frequencies) to progressively reveal faces of unfamiliar or personally familiar individuals. Activation in ventral occipitotemporal face-preferential regions increased with visual information, independently of long-term face familiarity. In contrast, medial temporal lobe structures (perirhinal cortex, amygdala, hippocampus) and anterior inferior temporal cortex responded abruptly when sufficient information for familiar face recognition was accumulated. These observations suggest that following detailed analysis of individual faces in core posterior areas of the face-processing network, familiar face recognition emerges categorically in medial temporal and anterior regions of the extended cortical face network. PMID:26283361

Neural microgenesis of personally familiar face recognition.

PubMed

Ramon, Meike; Vizioli, Luca; Liu-Shuang, Joan; Rossion, Bruno

2015-09-01

Despite a wealth of information provided by neuroimaging research, the neural basis of familiar face recognition in humans remains largely unknown. Here, we isolated the discriminative neural responses to unfamiliar and familiar faces by slowly increasing visual information (i.e., high-spatial frequencies) to progressively reveal faces of unfamiliar or personally familiar individuals. Activation in ventral occipitotemporal face-preferential regions increased with visual information, independently of long-term face familiarity. In contrast, medial temporal lobe structures (perirhinal cortex, amygdala, hippocampus) and anterior inferior temporal cortex responded abruptly when sufficient information for familiar face recognition was accumulated. These observations suggest that following detailed analysis of individual faces in core posterior areas of the face-processing network, familiar face recognition emerges categorically in medial temporal and anterior regions of the extended cortical face network.

Neural correlates of trust.

PubMed

Krueger, Frank; McCabe, Kevin; Moll, Jorge; Kriegeskorte, Nikolaus; Zahn, Roland; Strenziok, Maren; Heinecke, Armin; Grafman, Jordan

2007-12-11

Trust is a critical social process that helps us to cooperate with others and is present to some degree in all human interaction. However, the underlying brain mechanisms of conditional and unconditional trust in social reciprocal exchange are still obscure. Here, we used hyperfunctional magnetic resonance imaging, in which two strangers interacted online with one another in a sequential reciprocal trust game while their brains were simultaneously scanned. By designing a nonanonymous, alternating multiround game, trust became bidirectional, and we were able to quantify partnership building and maintenance. Using within- and between-brain analyses, an examination of functional brain activity supports the hypothesis that the preferential activation of different neuronal systems implements these two trust strategies. We show that the paracingulate cortex is critically involved in building a trust relationship by inferring another person's intentions to predict subsequent behavior. This more recently evolved brain region can be differently engaged to interact with more primitive neural systems in maintaining conditional and unconditional trust in a partnership. Conditional trust selectively activated the ventral tegmental area, a region linked to the evaluation of expected and realized reward, whereas unconditional trust selectively activated the septal area, a region linked to social attachment behavior. The interplay of these neural systems supports reciprocal exchange that operates beyond the immediate spheres of kinship, one of the distinguishing features of the human species.

Neural correlates of trust

PubMed Central

Krueger, Frank; McCabe, Kevin; Moll, Jorge; Kriegeskorte, Nikolaus; Zahn, Roland; Strenziok, Maren; Heinecke, Armin; Grafman, Jordan

2007-01-01

Trust is a critical social process that helps us to cooperate with others and is present to some degree in all human interaction. However, the underlying brain mechanisms of conditional and unconditional trust in social reciprocal exchange are still obscure. Here, we used hyperfunctional magnetic resonance imaging, in which two strangers interacted online with one another in a sequential reciprocal trust game while their brains were simultaneously scanned. By designing a nonanonymous, alternating multiround game, trust became bidirectional, and we were able to quantify partnership building and maintenance. Using within- and between-brain analyses, an examination of functional brain activity supports the hypothesis that the preferential activation of different neuronal systems implements these two trust strategies. We show that the paracingulate cortex is critically involved in building a trust relationship by inferring another person's intentions to predict subsequent behavior. This more recently evolved brain region can be differently engaged to interact with more primitive neural systems in maintaining conditional and unconditional trust in a partnership. Conditional trust selectively activated the ventral tegmental area, a region linked to the evaluation of expected and realized reward, whereas unconditional trust selectively activated the septal area, a region linked to social attachment behavior. The interplay of these neural systems supports reciprocal exchange that operates beyond the immediate spheres of kinship, one of the distinguishing features of the human species. PMID:18056800

An RNA-binding protein, Qki5, regulates embryonic neural stem cells through pre-mRNA processing in cell adhesion signaling.

PubMed

Hayakawa-Yano, Yoshika; Suyama, Satoshi; Nogami, Masahiro; Yugami, Masato; Koya, Ikuko; Furukawa, Takako; Zhou, Li; Abe, Manabu; Sakimura, Kenji; Takebayashi, Hirohide; Nakanishi, Atsushi; Okano, Hideyuki; Yano, Masato

2017-09-15

Cell type-specific transcriptomes are enabled by the action of multiple regulators, which are frequently expressed within restricted tissue regions. In the present study, we identify one such regulator, Quaking 5 (Qki5), as an RNA-binding protein (RNABP) that is expressed in early embryonic neural stem cells and subsequently down-regulated during neurogenesis. mRNA sequencing analysis in neural stem cell culture indicates that Qki proteins play supporting roles in the neural stem cell transcriptome and various forms of mRNA processing that may result from regionally restricted expression and subcellular localization. Also, our in utero electroporation gain-of-function study suggests that the nuclear-type Qki isoform Qki5 supports the neural stem cell state. We next performed in vivo transcriptome-wide protein-RNA interaction mapping to search for direct targets of Qki5 and elucidate how Qki5 regulates neural stem cell function. Combined with our transcriptome analysis, this mapping analysis yielded a bona fide map of Qki5-RNA interaction at single-nucleotide resolution, the identification of 892 Qki5 direct target genes, and an accurate Qki5-dependent alternative splicing rule in the developing brain. Last, our target gene list provides the first compelling evidence that Qki5 is associated with specific biological events; namely, cell-cell adhesion. This prediction was confirmed by histological analysis of mice in which Qki proteins were genetically ablated, which revealed disruption of the apical surface of the lateral wall in the developing brain. These data collectively indicate that Qki5 regulates communication between neural stem cells by mediating numerous RNA processing events and suggest new links between splicing regulation and neural stem cell states. © 2017 Hayakawa-Yano et al.; Published by Cold Spring Harbor Laboratory Press.

Function of FEZF1 during early neural differentiation of human embryonic stem cells.

PubMed

Liu, Xin; Su, Pei; Lu, Lisha; Feng, Zicen; Wang, Hongtao; Zhou, Jiaxi

2018-01-01

The understanding of the mechanism underlying human neural development has been hampered due to lack of a cellular system and complicated ethical issues. Human embryonic stem cells (hESCs) provide an invaluable model for dissecting human development because of unlimited self-renewal and the capacity to differentiate into nearly all cell types in the human body. In this study, using a chemical defined neural induction protocol and molecular profiling, we identified Fez family zinc finger 1 (FEZF1) as a potential regulator of early human neural development. FEZF1 is rapidly up-regulated during neural differentiation in hESCs and expressed before PAX6, a well-established marker of early human neural induction. We generated FEZF1-knockout H1 hESC lines using CRISPR-CAS9 technology and found that depletion of FEZF1 abrogates neural differentiation of hESCs. Moreover, loss of FEZF1 impairs the pluripotency exit of hESCs during neural specification, which partially explains the neural induction defect caused by FEZF1 deletion. However, enforced expression of FEZF1 itself fails to drive neural differentiation in hESCs, suggesting that FEZF1 is necessary but not sufficient for neural differentiation from hESCs. Taken together, our findings identify one of the earliest regulators expressed upon neural induction and provide insight into early neural development in human.

Use of macroinvertebrates to identify cultivated wetlands in the Prairie Pothole Region

USGS Publications Warehouse

Euliss, Ned H.; Mushet, David M.; Johnson, Douglas H.

2001-01-01

We evaluated the use of macroinvertebrates as a potential tool to identify dry and intensively farmed temporary and seasonal wetlands in the Prairie Pothole Region. The techniques we designed and evaluated used the dried remains of invertebrates or their egg banks in soils as indicators of wetlands. For both the dried remains of invertebrates and their egg banks, we weighted each taxon according to its affinity for wetlands or uplands. Our study clearly demonstrated that shells, exoskeletons, head capsules, eggs, and other remains of macroinvertebrates can be used to identify wetlands, even when they are dry, intensively farmed, and difficult to identify as wetlands using standard criteria (i.e., hydrology, hydrophytic vegetation, and hydric soils). Although both dried remains and egg banks identified wetlands, the combination was more useful, especially for identifying drained or filled wetlands. We also evaluated the use of coarse taxonomic groupings to stimulate use of the technique by nonspecialists and obtained satisfactory results in most situations.

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.

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

Incremental evolution of the neural crest, neural crest cells and neural crest-derived skeletal tissues

PubMed Central

Hall, Brian K; Gillis, J Andrew

2013-01-01

Urochordates (ascidians) have recently supplanted cephalochordates (amphioxus) as the extant sister taxon of vertebrates. Given that urochordates possess migratory cells that have been classified as ‘neural crest-like’– and that cephalochordates lack such cells – this phylogenetic hypothesis may have significant implications with respect to the origin of the neural crest and neural crest-derived skeletal tissues in vertebrates. We present an overview of the genes and gene regulatory network associated with specification of the neural crest in vertebrates. We then use these molecular data – alongside cell behaviour, cell fate and embryonic context – to assess putative antecedents (latent homologues) of the neural crest or neural crest cells in ascidians and cephalochordates. Ascidian migratory mesenchymal cells – non-pigment-forming trunk lateral line cells and pigment-forming ‘neural crest-like cells’ (NCLC) – are unlikely latent neural crest cell homologues. Rather, Snail-expressing cells at the neural plate of border of urochordates and cephalochordates likely represent the extent of neural crest elaboration in non-vertebrate chordates. We also review evidence for the evolutionary origin of two neural crest-derived skeletal tissues – cartilage and dentine. Dentine is a bona fide vertebrate novelty, and dentine-secreting odontoblasts represent a cell type that is exclusively derived from the neural crest. Cartilage, on the other hand, likely has a much deeper origin within the Metazoa. The mesodermally derived cellular cartilages of some protostome invertebrates are much more similar to vertebrate cartilage than is the acellular ‘cartilage-like’ tissue in cephalochordate pharyngeal arches. Cartilage, therefore, is not a vertebrate novelty, and a well-developed chondrogenic program was most likely co-opted from mesoderm to the neural crest along the vertebrate stem. We conclude that the neural crest is a vertebrate novelty, but that neural

Mitogenic signals and transforming potential of Nyk, a newly identified neural cell adhesion molecule-related receptor tyrosine kinase.

PubMed Central

Ling, L; Kung, H J

1995-01-01

Nyk/Mer is a recently identified receptor tyrosine kinase with neural cell adhesion molecule-like structure (two immunoglobulin G-like domains and two fibronectin III-like domains) in its extracellular region and belongs to the Ufo/Axl family of receptors. The ligand for Nyk/Mer is presently unknown, as are the signal transduction pathways mediated by this receptor. We constructed and expressed a chimeric receptor (Fms-Nyk) composed of the extracellular domain of the human colony-stimulating factor 1 receptor (Fms) and the transmembrane and cytoplasmic domains of human Nyk/Mer in NIH 3T3 fibroblasts in order to investigate the mitogenic signaling and biochemical properties of Nyk/Mer. Colony-stimulating factor 1 stimulation of the Fms-Nyk chimeric receptor in transfected NIH 3T3 fibroblasts leads to a transformed phenotype and generates a proliferative response in the absence of other growth factors. We show that phospholipase C gamma, phosphatidylinositol 3-kinase/p70 S6 kinase, Shc, Grb2, Raf-1, and mitogen-activated protein kinase are downstream components of the Nyk/Mer signal transduction pathways. In addition, Nyk/Mer weakly activates p90rsk, while stress-activated protein kinase, Ras GTPase-activating protein (GAP), and GAP-associated p62 and p190 proteins are not activated or tyrosine phosphorylated by Nyk/Mer. An analysis comparing the Nyk/Mer signal cascade with that of the epidermal growth factor receptor indicates substrate preferences by these two receptors. Our results provide a detailed description of the Nyk/Mer signaling pathways. Given the structural similarity between the Ufo/Axl family receptors, some of the information may also be applied to other members of this receptor tyrosine kinase family. PMID:8524223

The neural signature of emotional memories in serial crimes.

PubMed

Chassy, Philippe

2017-10-01

Neural plasticity is the process whereby semantic information and emotional responses are stored in neural networks. It is hypothesized that the neural networks built over time to encode the sexual fantasies that motivate serial killers to act should display a unique, detectable activation pattern. The pathological neural watermark hypothesis posits that such networks comprise activation of brain sites that reflect four cognitive components: autobiographical memory, sexual arousal, aggression, and control over aggression. The neural sites performing these cognitive functions have been successfully identified by previous research. The key findings are reviewed to hypothesise the typical pattern of activity that serial killers should display. Through the integration of biological findings into one framework, the neural approach proposed in this paper is in stark contrast with the many theories accounting for serial killers that offer non-medical taxonomies. The pathological neural watermark hypothesis offers a new framework to understand and detect deviant individuals. The technical and legal issues are briefly discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Physics instruction induces changes in neural knowledge representation during successive stages of learning.

PubMed

Mason, Robert A; Just, Marcel Adam

2015-05-01

Incremental instruction on the workings of a set of mechanical systems induced a progression of changes in the neural representations of the systems. The neural representations of four mechanical systems were assessed before, during, and after three phases of incremental instruction (which first provided information about the system components, then provided partial causal information, and finally provided full functional information). In 14 participants, the neural representations of four systems (a bathroom scale, a fire extinguisher, an automobile braking system, and a trumpet) were assessed using three recently developed techniques: (1) machine learning and classification of multi-voxel patterns; (2) localization of consistently responding voxels; and (3) representational similarity analysis (RSA). The neural representations of the systems progressed through four stages, or states, involving spatially and temporally distinct multi-voxel patterns: (1) initially, the representation was primarily visual (occipital cortex); (2) it subsequently included a large parietal component; (3) it eventually became cortically diverse (frontal, parietal, temporal, and medial frontal regions); and (4) at the end, it demonstrated a strong frontal cortex weighting (frontal and motor regions). At each stage of knowledge, it was possible for a classifier to identify which one of four mechanical systems a participant was thinking about, based on their brain activation patterns. The progression of representational states was suggestive of progressive stages of learning: (1) encoding information from the display; (2) mental animation, possibly involving imagining the components moving; (3) generating causal hypotheses associated with mental animation; and finally (4) determining how a person (probably oneself) would interact with the system. This interpretation yields an initial, cortically-grounded, theory of learning of physical systems that potentially can be related to cognitive

Neural Networks Involved in Adolescent Reward Processing: An Activation Likelihood Estimation Meta-Analysis of Functional Neuroimaging Studies

PubMed Central

Silverman, Merav H.; Jedd, Kelly; Luciana, Monica

2015-01-01

Behavioral responses to, and the neural processing of, rewards change dramatically during adolescence and may contribute to observed increases in risk-taking during this developmental period. Functional MRI (fMRI) studies suggest differences between adolescents and adults in neural activation during reward processing, but findings are contradictory, and effects have been found in non-predicted directions. The current study uses an activation likelihood estimation (ALE) approach for quantitative meta-analysis of functional neuroimaging studies to: 1) confirm the network of brain regions involved in adolescents’ reward processing, 2) identify regions involved in specific stages (anticipation, outcome) and valence (positive, negative) of reward processing, and 3) identify differences in activation likelihood between adolescent and adult reward-related brain activation. Results reveal a subcortical network of brain regions involved in adolescent reward processing similar to that found in adults with major hubs including the ventral and dorsal striatum, insula, and posterior cingulate cortex (PCC). Contrast analyses find that adolescents exhibit greater likelihood of activation in the insula while processing anticipation relative to outcome and greater likelihood of activation in the putamen and amygdala during outcome relative to anticipation. While processing positive compared to negative valence, adolescents show increased likelihood for activation in the posterior cingulate cortex (PCC) and ventral striatum. Contrasting adolescent reward processing with the existing ALE of adult reward processing (Liu et al., 2011) reveals increased likelihood for activation in limbic, frontolimbic, and striatal regions in adolescents compared with adults. Unlike adolescents, adults also activate executive control regions of the frontal and parietal lobes. These findings support hypothesized elevations in motivated activity during adolescence. PMID:26254587

Using imagination to understand the neural basis of episodic memory

PubMed Central

Hassabis, Demis; Kumaran, Dharshan; Maguire, Eleanor A.

2008-01-01

Functional MRI (fMRI) studies investigating the neural basis of episodic memory recall, and the related task of thinking about plausible personal future events, have revealed a consistent network of associated brain regions. Surprisingly little, however, is understood about the contributions individual brain areas make to the overall recollective experience. In order to examine this, we employed a novel fMRI paradigm where subjects had to imagine fictitious experiences. In contrast to future thinking, this results in experiences that are not explicitly temporal in nature or as reliant on self-processing. By using previously imagined fictitious experiences as a comparison for episodic memories, we identified the neural basis of a key process engaged in common, namely scene construction, involving the generation, maintenance and visualisation of complex spatial contexts. This was associated with activations in a distributed network, including hippocampus, parahippocampal gyrus, and retrosplenial cortex. Importantly, we disambiguated these common effects from episodic memory-specific responses in anterior medial prefrontal cortex, posterior cingulate cortex and precuneus. These latter regions may support self-schema and familiarity processes, and contribute to the brain's ability to distinguish real from imaginary memories. We conclude that scene construction constitutes a common process underlying episodic memory and imagination of fictitious experiences, and suggest it may partially account for the similar brain networks implicated in navigation, episodic future thinking, and the default mode. We suggest that further brain regions are co-opted into this core network in a task-specific manner to support functions such as episodic memory that may have additional requirements. PMID:18160644

Using imagination to understand the neural basis of episodic memory.

PubMed

Hassabis, Demis; Kumaran, Dharshan; Maguire, Eleanor A

2007-12-26

Functional MRI (fMRI) studies investigating the neural basis of episodic memory recall, and the related task of thinking about plausible personal future events, have revealed a consistent network of associated brain regions. Surprisingly little, however, is understood about the contributions individual brain areas make to the overall recollective experience. To examine this, we used a novel fMRI paradigm in which subjects had to imagine fictitious experiences. In contrast to future thinking, this results in experiences that are not explicitly temporal in nature or as reliant on self-processing. By using previously imagined fictitious experiences as a comparison for episodic memories, we identified the neural basis of a key process engaged in common, namely scene construction, involving the generation, maintenance and visualization of complex spatial contexts. This was associated with activations in a distributed network, including hippocampus, parahippocampal gyrus, and retrosplenial cortex. Importantly, we disambiguated these common effects from episodic memory-specific responses in anterior medial prefrontal cortex, posterior cingulate cortex and precuneus. These latter regions may support self-schema and familiarity processes, and contribute to the brain's ability to distinguish real from imaginary memories. We conclude that scene construction constitutes a common process underlying episodic memory and imagination of fictitious experiences, and suggest it may partially account for the similar brain networks implicated in navigation, episodic future thinking, and the default mode. We suggest that additional brain regions are co-opted into this core network in a task-specific manner to support functions such as episodic memory that may have additional requirements.

Neural signatures of experience-based improvements in deterministic decision-making

PubMed Central

Tremel, Joshua J.; Laurent, Patryk A.; Wolk, David A.; Wheeler, Mark E.; Fiez, Julie A.

2016-01-01

Feedback about our choices is a crucial part of how we gather information and learn from our environment. It provides key information about decision experiences that can be used to optimize future choices. However, our understanding of the processes through which feedback translates into improved decision-making is lacking. Using neuroimaging (fMRI) and cognitive models of decision-making and learning, we examined the influence of feedback on multiple aspects of decision processes across learning. Subjects learned correct choices to a set of 50 word pairs across eight repetitions of a concurrent discrimination task. Behavioral measures were then analyzed with both a drift-diffusion model and a reinforcement learning model. Parameter values from each were then used as fMRI regressors to identify regions whose activity fluctuates with specific cognitive processes described by the models. The patterns of intersecting neural effects across models support two main inferences about the influence of feedback on decision-making. First, frontal, anterior insular, fusiform, and caudate nucleus regions behave like performance monitors, reflecting errors in performance predictions that signal the need for changes in control over decision-making. Second, temporoparietal, supplementary motor, and putamen regions behave like mnemonic storage sites, reflecting differences in learned item values that inform optimal decision choices. As information about optimal choices is accrued, these neural systems dynamically adjust, likely shifting the burden of decision processing from controlled performance monitoring to bottom-up, stimulus-driven choice selection. Collectively, the results provide a detailed perspective on the fundamental ability to use past experiences to improve future decisions. PMID:27523644

Neural Modeling and Imaging of the Cortical Interactions Underlying Syllable Production

ERIC Educational Resources Information Center

Guenther, Frank H.; Ghosh, Satrajit S.; Tourville, Jason A.

2006-01-01

This paper describes a neural model of speech acquisition and production that accounts for a wide range of acoustic, kinematic, and neuroimaging data concerning the control of speech movements. The model is a neural network whose components correspond to regions of the cerebral cortex and cerebellum, including premotor, motor, auditory, and…

Neural evidence that human emotions share core affective properties.

PubMed

Wilson-Mendenhall, Christine D; Barrett, Lisa Feldman; Barsalou, Lawrence W

2013-06-01

Research on the "emotional brain" remains centered around the idea that emotions like fear, happiness, and sadness result from specialized and distinct neural circuitry. Accumulating behavioral and physiological evidence suggests, instead, that emotions are grounded in core affect--a person's fluctuating level of pleasant or unpleasant arousal. A neuroimaging study revealed that participants' subjective ratings of valence (i.e., pleasure/displeasure) and of arousal evoked by various fear, happiness, and sadness experiences correlated with neural activity in specific brain regions (orbitofrontal cortex and amygdala, respectively). We observed these correlations across diverse instances within each emotion category, as well as across instances from all three categories. Consistent with a psychological construction approach to emotion, the results suggest that neural circuitry realizes more basic processes across discrete emotions. The implicated brain regions regulate the body to deal with the world, producing the affective changes at the core of emotions and many other psychological phenomena.

Neural Evidence that Human Emotions Share Core Affective Properties

PubMed Central

Wilson-Mendenhall, Christine D.; Barrett, Lisa Feldman; Barsalou, Lawrence W.

2014-01-01

Research on the “emotional brain” remains centered around the idea that emotions like fear, happiness, and sadness result from specialized and distinct neural circuitry. Accumulating behavioral and physiological evidence suggests, instead, that emotions are grounded in core affect – a person's fluctuating level of pleasant or unpleasant arousal. A neuroimaging study revealed that participants' subjective ratings of valence (i.e., pleasure/displeasure) and of arousal evoked by various fear, happiness, and sadness experiences correlated with neural activity in specific brain regions (orbitofrontal cortex and amygdala, respectively). We observed these correlations across diverse instances within each emotion category, as well as across instances from all three categories. Consistent with a psychological construction approach to emotion, the results suggest that neural circuitry realizes more basic processes across discrete emotions. The implicated brain regions regulate the body to deal with the world, producing the affective changes at the core of emotions and many other psychological phenomena. PMID:23603916

Neural Correlates of Belief and Emotion Attribution in Schizophrenia.

PubMed

Lee, Junghee; Horan, William P; Wynn, Jonathan K; Green, Michael F

2016-01-01

Impaired mental state attribution is a core social cognitive deficit in schizophrenia. With functional magnetic resonance imaging (fMRI), this study examined the extent to which the core neural system of mental state attribution is involved in mental state attribution, focusing on belief attribution and emotion attribution. Fifteen schizophrenia outpatients and 14 healthy controls performed two mental state attribution tasks in the scanner. In a Belief Attribution Task, after reading a short vignette, participants were asked infer either the belief of a character (a false belief condition) or a physical state of an affair (a false photograph condition). In an Emotion Attribution Task, participants were asked either to judge whether character(s) in pictures felt unpleasant, pleasant, or neutral emotion (other condition) or to look at pictures that did not have any human characters (view condition). fMRI data were analyzing focusing on a priori regions of interest (ROIs) of the core neural systems of mental state attribution: the medial prefrontal cortex (mPFC), temporoparietal junction (TPJ) and precuneus. An exploratory whole brain analysis was also performed. Both patients and controls showed greater activation in all four ROIs during the Belief Attribution Task than the Emotion Attribution Task. Patients also showed less activation in the precuneus and left TPJ compared to controls during the Belief Attribution Task. No significant group difference was found during the Emotion Attribution Task in any of ROIs. An exploratory whole brain analysis showed a similar pattern of neural activations. These findings suggest that while schizophrenia patients rely on the same neural network as controls do when attributing beliefs of others, patients did not show reduced activation in the key regions such as the TPJ. Further, this study did not find evidence for aberrant neural activation during emotion attribution or recruitment of compensatory brain regions in schizophrenia.

Neural Correlates of Belief and Emotion Attribution in Schizophrenia

PubMed Central

Lee, Junghee; Horan, William P.; Wynn, Jonathan K.; Green, Michael F.

2016-01-01

Impaired mental state attribution is a core social cognitive deficit in schizophrenia. With functional magnetic resonance imaging (fMRI), this study examined the extent to which the core neural system of mental state attribution is involved in mental state attribution, focusing on belief attribution and emotion attribution. Fifteen schizophrenia outpatients and 14 healthy controls performed two mental state attribution tasks in the scanner. In a Belief Attribution Task, after reading a short vignette, participants were asked infer either the belief of a character (a false belief condition) or a physical state of an affair (a false photograph condition). In an Emotion Attribution Task, participants were asked either to judge whether character(s) in pictures felt unpleasant, pleasant, or neutral emotion (other condition) or to look at pictures that did not have any human characters (view condition). fMRI data were analyzing focusing on a priori regions of interest (ROIs) of the core neural systems of mental state attribution: the medial prefrontal cortex (mPFC), temporoparietal junction (TPJ) and precuneus. An exploratory whole brain analysis was also performed. Both patients and controls showed greater activation in all four ROIs during the Belief Attribution Task than the Emotion Attribution Task. Patients also showed less activation in the precuneus and left TPJ compared to controls during the Belief Attribution Task. No significant group difference was found during the Emotion Attribution Task in any of ROIs. An exploratory whole brain analysis showed a similar pattern of neural activations. These findings suggest that while schizophrenia patients rely on the same neural network as controls do when attributing beliefs of others, patients did not show reduced activation in the key regions such as the TPJ. Further, this study did not find evidence for aberrant neural activation during emotion attribution or recruitment of compensatory brain regions in schizophrenia

Differences in neural activity when processing emotional arousal and valence in autism spectrum disorders.

PubMed

Tseng, Angela; Wang, Zhishun; Huo, Yuankai; Goh, Suzanne; Russell, James A; Peterson, Bradley S

2016-02-01

Individuals with autism spectrum disorders (ASD) often have difficulty recognizing and interpreting facial expressions of emotion, which may impair their ability to navigate and communicate successfully in their social, interpersonal environments. Characterizing specific differences between individuals with ASD and their typically developing (TD) counterparts in the neural activity subserving their experience of emotional faces may provide distinct targets for ASD interventions. Thus we used functional magnetic resonance imaging (fMRI) and a parametric experimental design to identify brain regions in which neural activity correlated with ratings of arousal and valence for a broad range of emotional faces. Participants (51 ASD, 84 TD) were group-matched by age, sex, IQ, race, and socioeconomic status. Using task-related change in blood-oxygen-level-dependent (BOLD) fMRI signal as a measure, and covarying for age, sex, FSIQ, and ADOS scores, we detected significant differences across diagnostic groups in the neural activity subserving the dimension of arousal but not valence. BOLD-signal in TD participants correlated inversely with ratings of arousal in regions associated primarily with attentional functions, whereas BOLD-signal in ASD participants correlated positively with arousal ratings in regions commonly associated with impulse control and default-mode activity. Only minor differences were detected between groups in the BOLD signal correlates of valence ratings. Our findings provide unique insight into the emotional experiences of individuals with ASD. Although behavioral responses to face-stimuli were comparable across diagnostic groups, the corresponding neural activity for our ASD and TD groups differed dramatically. The near absence of group differences for valence correlates and the presence of strong group differences for arousal correlates suggest that individuals with ASD are not atypical in all aspects of emotion-processing. Studying these similarities

Neural reactivity to reward in school-age offspring of depressed mothers.

PubMed

Wiggins, Jillian Lee; Schwartz, Karen T G; Kryza-Lacombe, Maria; Spechler, Philip A; Blankenship, Sarah L; Dougherty, Lea R

2017-05-01

Identifying neural profiles predictive of future psychopathology in at-risk individuals is important to efficiently direct preventive care. Alterations in reward processing may be a risk factor for depression. The current study characterized neural substrates of reward processing in children at low- and high-risk for psychopathology due to maternal depression status. Children with (n=27) and without (n=19) maternal depression (ages 5.9-9.6 years) performed a monetary incentive delay task in which they received rewards, if they successfully hit a target, or no reward regardless of performance, during fMRI acquisition. Multiple dorsal prefrontal, temporal, and striatal regions showed significant Group (high- vs. low-risk)×Performance (hit vs. miss)×Condition (no reward vs. reward) interactions in a whole-brain analysis. All regions exhibited similar patterns, whereby the high-risk group showed blunted activation differences between trials with vs. without rewards when participants hit the target. Moreover, high-risk children showed activation differences between trials with vs. without rewards in the opposite direction, compared to the low-risk group, when they missed the target. This study had a modest sample size, though larger than existing studies. Children with maternal depression are at elevated risk for future psychopathology, yet not all experience clinically significant symptoms; longitudinal research is necessary to fully track the pathway from risk to disorder. Children of depressed mothers exhibited attenuated neural activation differences and activation patterns opposite to children without depressed mothers. Our findings may provide targets for hypothesis-driven preventive interventions and lead to earlier identification of individuals at risk. Copyright © 2017 Elsevier B.V. All rights reserved.

Neural Repetition Effects in the Medial Temporal Lobe Complex are Modulated by Previous Encoding Experience

PubMed Central

Greene, Ciara M.; Soto, David

2012-01-01

It remains an intriguing question why the medial temporal lobe (MTL) can display either attenuation or enhancement of neural activity following repetition of previously studied items. To isolate the role of encoding experience itself, we assessed neural repetition effects in the absence of any ongoing task demand or intentional orientation to retrieve. Experiment 1 showed that the hippocampus and surrounding MTL regions displayed neural repetition suppression (RS) upon repetition of past items that were merely attended during an earlier study phase but this was not the case following re-occurrence of items that had been encoded into working memory (WM). In this latter case a trend toward neural repetition enhancement (RE) was observed, though this was highly variable across individuals. Interestingly, participants with a higher degree of neural RE in the MTL complex displayed higher memory sensitivity in a later, surprise recognition test. Experiment 2 showed that massive exposure at encoding effected a change in the neural architecture supporting incidental repetition effects, with regions of the posterior parietal and ventral-frontal cortex in addition to the hippocampus displaying neural RE, while no neural RS was observed. The nature of encoding experience therefore modulates the expression of neural repetition effects in the MTL and the neocortex in the absence of memory goals. PMID:22829892

The neural basis of responsibility attribution in decision-making.

PubMed

Li, Peng; Shen, Yue; Sui, Xue; Chen, Changming; Feng, Tingyong; Li, Hong; Holroyd, Clay

2013-01-01

Social responsibility links personal behavior with societal expectations and plays a key role in affecting an agent's emotional state following a decision. However, the neural basis of responsibility attribution remains unclear. In two previous event-related brain potential (ERP) studies we found that personal responsibility modulated outcome evaluation in gambling tasks. Here we conducted a functional magnetic resonance imaging (fMRI) study to identify particular brain regions that mediate responsibility attribution. In a context involving team cooperation, participants completed a task with their teammates and on each trial received feedback about team success and individual success sequentially. We found that brain activity differed between conditions involving team success vs. team failure. Further, different brain regions were associated with reinforcement of behavior by social praise vs. monetary reward. Specifically, right temporoparietal junction (RTPJ) was associated with social pride whereas dorsal striatum and dorsal anterior cingulate cortex (ACC) were related to reinforcement of behaviors leading to personal gain. The present study provides evidence that the RTPJ is an important region for determining whether self-generated behaviors are deserving of praise in a social context.

Neural network-based sliding mode control for atmospheric-actuated spacecraft formation using switching strategy

NASA Astrophysics Data System (ADS)

Sun, Ran; Wang, Jihe; Zhang, Dexin; Shao, Xiaowei

2018-02-01

This paper presents an adaptive neural networks-based control method for spacecraft formation with coupled translational and rotational dynamics using only aerodynamic forces. It is assumed that each spacecraft is equipped with several large flat plates. A coupled orbit-attitude dynamic model is considered based on the specific configuration of atmospheric-based actuators. For this model, a neural network-based adaptive sliding mode controller is implemented, accounting for system uncertainties and external perturbations. To avoid invalidation of the neural networks destroying stability of the system, a switching control strategy is proposed which combines an adaptive neural networks controller dominating in its active region and an adaptive sliding mode controller outside the neural active region. An optimal process is developed to determine the control commands for the plates system. The stability of the closed-loop system is proved by a Lyapunov-based method. Comparative results through numerical simulations illustrate the effectiveness of executing attitude control while maintaining the relative motion, and higher control accuracy can be achieved by using the proposed neural-based switching control scheme than using only adaptive sliding mode controller.

Trait Approach and Avoidance Motivation: Lateralized Neural Activity Associated with Executive Function

PubMed Central

Spielberg, Jeffrey M.; Miller, Gregory A.; Engels, Anna S.; Herrington, John D.; Sutton, Bradley P.; Banich, Marie T.; Heller, Wendy

2010-01-01

Motivation and executive function are both necessary for the completion of goal-directed behavior. Research investigating the manner in which these processes interact is beginning to emerge and has implicated middle frontal gyrus (MFG) as a site of interaction for relevant neural mechanisms. However, this research has focused on state motivation, and it has not examined functional lateralization. The present study examined the impact of trait levels of approach and avoidance motivation on neural processes associated with executive function. Functional magnetic resonance imaging was conducted while participants performed a color-word Stroop task. Analyses identified brain regions in which trait approach and avoidance motivation (measured by questionnaires) moderated activation associated with executive control. Approach was hypothesized to be associated with left-lateralized MFG activation, whereas avoidance was hypothesized to be associated with right-lateralized MFG activation. Results supported both hypotheses. Present findings implicate areas of middle frontal gyrus in top-down control to guide behavior in accordance with motivational goals. PMID:20728552

From homeostasis to behavior: Balanced activity in an exploration of embodied dynamic environmental-neural interaction.

PubMed

Hellyer, Peter John; Clopath, Claudia; Kehagia, Angie A; Turkheimer, Federico E; Leech, Robert

2017-08-01

In recent years, there have been many computational simulations of spontaneous neural dynamics. Here, we describe a simple model of spontaneous neural dynamics that controls an agent moving in a simple virtual environment. These dynamics generate interesting brain-environment feedback interactions that rapidly destabilize neural and behavioral dynamics demonstrating the need for homeostatic mechanisms. We investigate roles for homeostatic plasticity both locally (local inhibition adjusting to balance excitatory input) as well as more globally (regional "task negative" activity that compensates for "task positive", sensory input in another region) balancing neural activity and leading to more stable behavior (trajectories through the environment). Our results suggest complementary functional roles for both local and macroscale mechanisms in maintaining neural and behavioral dynamics and a novel functional role for macroscopic "task-negative" patterns of activity (e.g., the default mode network).

Intelligence moderates neural responses to monetary reward and punishment.

PubMed

Hawes, Daniel R; DeYoung, Colin G; Gray, Jeremy R; Rustichini, Aldo

2014-05-01

The relations between intelligence (IQ) and neural responses to monetary gains and losses were investigated in a simple decision task. In 94 healthy adults, typical responses of striatal blood oxygen level-dependent (BOLD) signal after monetary reward and punishment were weaker for subjects with higher IQ. IQ-moderated differential responses to gains and losses were also found for regions in the medial prefrontal cortex, posterior cingulate cortex, and left inferior frontal cortex. These regions have previously been identified with the subjective utility of monetary outcomes. Analysis of subjects' behavior revealed a correlation between IQ and the extent to which choices were related to experienced decision outcomes in preceding trials. Specifically, higher IQ predicted behavior to be more strongly correlated with an extended period of previously experienced decision outcomes, whereas lower IQ predicted behavior to be correlated exclusively to the most recent decision outcomes. We link these behavioral and imaging findings to a theoretical model capable of describing a role for intelligence during the evaluation of rewards generated by unknown probabilistic processes. Our results demonstrate neural differences in how people of different intelligence respond to experienced monetary rewards and punishments. Our theoretical discussion offers a functional description for how these individual differences may be linked to choice behavior. Together, our results and model support the hypothesis that observed correlations between intelligence and preferences may be rooted in the way decision outcomes are experienced ex post, rather than deriving exclusively from how choices are evaluated ex ante.

Neural Activations of Guided Imagery and Music in Negative Emotional Processing: A Functional MRI Study.

PubMed

Lee, Sang Eun; Han, Yeji; Park, HyunWook

2016-01-01

The Bonny Method of Guided Imagery and Music uses music and imagery to access and explore personal emotions associated with episodic memories. Understanding the neural mechanism of guided imagery and music (GIM) as combined stimuli for emotional processing informs clinical application. We performed functional magnetic resonance imaging (fMRI) to demonstrate neural mechanisms of GIM for negative emotional processing when personal episodic memory is recalled and re-experienced through GIM processes. Twenty-four healthy volunteers participated in the study, which used classical music and verbal instruction stimuli to evoke negative emotions. To analyze the neural mechanism, activated regions associated with negative emotional and episodic memory processing were extracted by conducting volume analyses for the contrast between GIM and guided imagery (GI) or music (M). The GIM stimuli showed increased activation over the M-only stimuli in five neural regions associated with negative emotional and episodic memory processing, including the left amygdala, left anterior cingulate gyrus, left insula, bilateral culmen, and left angular gyrus (AG). Compared with GI alone, GIM showed increased activation in three regions associated with episodic memory processing in the emotional context, including the right posterior cingulate gyrus, bilateral parahippocampal gyrus, and AG. No neural regions related to negative emotional and episodic memory processing showed more activation for M and GI than for GIM. As a combined multimodal stimulus, GIM may increase neural activations related to negative emotions and episodic memory processing. Findings suggest a neural basis for GIM with personal episodic memories affecting cortical and subcortical structures and functions. © the American Music Therapy Association 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Application of heterogeneous pulse coupled neural network in image quantization

NASA Astrophysics Data System (ADS)

Huang, Yi; Ma, Yide; Li, Shouliang; Zhan, Kun

2016-11-01

On the basis of the different strengths of synaptic connections between actual neurons, this paper proposes a heterogeneous pulse coupled neural network (HPCNN) algorithm to perform quantization on images. HPCNNs are developed from traditional pulse coupled neural network (PCNN) models, which have different parameters corresponding to different image regions. This allows pixels of different gray levels to be classified broadly into two categories: background regional and object regional. Moreover, an HPCNN also satisfies human visual characteristics. The parameters of the HPCNN model are calculated automatically according to these categories, and quantized results will be optimal and more suitable for humans to observe. At the same time, the experimental results of natural images from the standard image library show the validity and efficiency of our proposed quantization method.

Recurrent NTRK1 Gene Fusions Define a Novel Subset of Locally Aggressive Lipofibromatosis-like Neural Tumors.

PubMed

Agaram, Narasimhan P; Zhang, Lei; Sung, Yun-Shao; Chen, Chun-Liang; Chung, Catherine T; Antonescu, Cristina R; Fletcher, Christopher Dm

2016-10-01

The family of pediatric fibroblastic and myofibroblastic proliferations encompasses a wide spectrum of pathologic entities with overlapping morphologies and ill-defined genetic abnormalities. Among the superficial lesions, lipofibromatosis (LPF), composed of an admixture of adipose tissue and fibroblastic elements, in the past has been variously classified as infantile fibromatosis or fibrous hamartoma of infancy. In this regard, we have encountered a group of superficial soft tissue tumors occurring in children and young adults, with a notably infiltrative growth pattern reminiscent of LPF, variable cytologic atypia, and a distinct immunoprofile of S100 protein and CD34 reactivity, suggestive of neural differentiation. SOX10 and melanocytic markers were negative in all cases tested. In contrast, a control group of classic LPF displayed bland, monomorphic histology and lacked S100 protein immunoreactivity. To define the pathogenetic abnormalities in these seemingly distinctive groups, we performed RNA sequencing for fusion gene discovery in 2 cases each, followed by screening for any novel alterations identified in a larger cohort representing both entities. The 2 index LPF-like neural tumors (LPF-NT) showed TPR-NTRK1 and TPM3-NTRK1 gene fusions, which were further validated by fluorescence in situ hybridization (FISH) and reverse transcription polymerase chain reaction. Subsequent FISH screening of 14 LPF-NT identified recurrent NTRK1 gene rearrangements in 10 (71%) cases. Of the NTRK1-negative LPF-NT cases, 1 case each showed ROS1 and ALK gene rearrangements. In contrast, none of the 25 classic LPFs showed NTRK1 gene rearrangements, although regional abnormalities were noted in the 1q21-22 region by FISH in a majority of cases. Furthermore, NTRK1 immunostaining was positive only in NTRK1-rearranged S100-positive LPF-NT but negative in classic LPF. These results suggest that NTRK1 oncogenic activation through gene fusion defines a novel and distinct subset of soft

Conducting Polymers for Neural Prosthetic and Neural Interface Applications

PubMed Central

2015-01-01

Neural interfacing devices are an artificial mechanism for restoring or supplementing the function of the nervous system lost as a result of injury or disease. Conducting polymers (CPs) are gaining significant attention due to their capacity to meet the performance criteria of a number of neuronal therapies including recording and stimulating neural activity, the regeneration of neural tissue and the delivery of bioactive molecules for mediating device-tissue interactions. CPs form a flexible platform technology that enables the development of tailored materials for a range of neuronal diagnostic and treatment therapies. In this review the application of CPs for neural prostheses and other neural interfacing devices are discussed, with a specific focus on neural recording, neural stimulation, neural regeneration, and therapeutic drug delivery. PMID:26414302

Comparative transcriptome analysis in induced neural stem cells reveals defined neural cell identities in vitro and after transplantation into the adult rodent brain.

PubMed

Hallmann, Anna-Lena; Araúzo-Bravo, Marcos J; Zerfass, Christina; Senner, Volker; Ehrlich, Marc; Psathaki, Olympia E; Han, Dong Wook; Tapia, Natalia; Zaehres, Holm; Schöler, Hans R; Kuhlmann, Tanja; Hargus, Gunnar

2016-05-01

Reprogramming technology enables the production of neural progenitor cells (NPCs) from somatic cells by direct transdifferentiation. However, little is known on how neural programs in these induced neural stem cells (iNSCs) differ from those of alternative stem cell populations in vitro and in vivo. Here, we performed transcriptome analyses on murine iNSCs in comparison to brain-derived neural stem cells (NSCs) and pluripotent stem cell-derived NPCs, which revealed distinct global, neural, metabolic and cell cycle-associated marks in these populations. iNSCs carried a hindbrain/posterior cell identity, which could be shifted towards caudal, partially to rostral but not towards ventral fates in vitro. iNSCs survived after transplantation into the rodent brain and exhibited in vivo-characteristics, neural and metabolic programs similar to transplanted NSCs. However, iNSCs vastly retained caudal identities demonstrating cell-autonomy of regional programs in vivo. These data could have significant implications for a variety of in vitro- and in vivo-applications using iNSCs. Copyright © 2016 Roslin Cells Ltd. Published by Elsevier B.V. All rights reserved.

Spatially Nonlinear Interdependence of Alpha-Oscillatory Neural Networks under Chan Meditation

PubMed Central

Chang, Chih-Hao

2013-01-01

This paper reports the results of our investigation of the effects of Chan meditation on brain electrophysiological behaviors from the viewpoint of spatially nonlinear interdependence among regional neural networks. Particular emphasis is laid on the alpha-dominated EEG (electroencephalograph). Continuous-time wavelet transform was adopted to detect the epochs containing substantial alpha activities. Nonlinear interdependence quantified by similarity index S(X∣Y), the influence of source signal Y on sink signal X, was applied to the nonlinear dynamical model in phase space reconstructed from multichannel EEG. Experimental group involved ten experienced Chan-Meditation practitioners, while control group included ten healthy subjects within the same age range, yet, without any meditation experience. Nonlinear interdependence among various cortical regions was explored for five local neural-network regions, frontal, posterior, right-temporal, left-temporal, and central regions. In the experimental group, the inter-regional interaction was evaluated for the brain dynamics under three different stages, at rest (stage R, pre-meditation background recording), in Chan meditation (stage M), and the unique Chakra-focusing practice (stage C). Experimental group exhibits stronger interactions among various local neural networks at stages M and C compared with those at stage R. The intergroup comparison demonstrates that Chan-meditation brain possesses better cortical inter-regional interactions than the resting brain of control group. PMID:24489583

CD24 Expression Identifies Teratogen-Sensitive Fetal Neural Stem Cell Subpopulations: Evidence from Developmental Ethanol Exposure and Orthotopic Cell Transfer Models

PubMed Central

Tingling, Joseph D.; Bake, Shameena; Holgate, Rhonda; Rawlings, Jeremy; Nagsuk, Phillips P.; Chandrasekharan, Jayashree; Schneider, Sarah L.; Miranda, Rajesh C.

2013-01-01

Background Ethanol is a potent teratogen. Its adverse neural effects are partly mediated by disrupting fetal neurogenesis. The teratogenic process is poorly understood, and vulnerable neurogenic stages have not been identified. Identifying these is a prerequisite for therapeutic interventions to mitigate effects of teratogen exposures. Methods We used flow cytometry and qRT-PCR to screen fetal mouse-derived neurosphere cultures for ethanol-sensitive neural stem cell (NSC) subpopulations, to study NSC renewal and differentiation. The identity of vulnerable NSC populations was validated in vivo, using a maternal ethanol exposure model. Finally, the effect of ethanol exposure on the ability of vulnerable NSC subpopulations to integrate into the fetal neurogenic environment was assessed following ultrasound guided, adoptive transfer. Results Ethanol decreased NSC mRNAs for c-kit, Musashi-1and GFAP. The CD24+ NSC population, specifically the CD24+CD15+ double-positive subpopulation, was selectively decreased by ethanol. Maternal ethanol exposure also resulted in decreased fetal forebrain CD24 expression. Ethanol pre-exposed CD24+ cells exhibited increased proliferation, and deficits in cell-autonomous and cue-directed neuronal differentiation, and following orthotopic transplantation into naïve fetuses, were unable to integrate into neurogenic niches. CD24depleted cells retained neurosphere regeneration capacity, but following ethanol exposure, generated increased numbers of CD24+ cells relative to controls. Conclusions Neuronal lineage committed CD24+ cells exhibit specific vulnerability, and ethanol exposure persistently impairs this population’s cell-autonomous differentiation capacity. CD24+ cells may additionally serve as quorum sensors within neurogenic niches; their loss, leading to compensatory NSC activation, perhaps depleting renewal capacity. These data collectively advance a mechanistic hypothesis for teratogenesis leading to microencephaly. PMID:23894503

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.

The Potential Neural Mechanisms of Acute Indirect Vibration

PubMed Central

2011-01-01

There is strong evidence to suggest that acute indirect vibration acts on muscle to enhance force, power, flexibility, balance and proprioception suggesting neural enhancement. Nevertheless, the neural mechanism(s) of vibration and its potentiating effect have received little attention. One proposal suggests that spinal reflexes enhance muscle contraction through a reflex activity known as tonic vibration stretch reflex (TVR), which increases muscle activation. However, TVR is based on direct, brief, and high frequency vibration (>100 Hz) which differs to indirect vibration, which is applied to the whole body or body parts at lower vibration frequency (5-45 Hz). Likewise, muscle tuning and neuromuscular aspects are other candidate mechanisms used to explain the vibration phenomenon. But there is much debate in terms of identifying which neural mechanism(s) are responsible for acute vibration; due to a number of studies using various vibration testing protocols. These protocols include: different methods of application, vibration variables, training duration, exercise types and a range of population groups. Therefore, the neural mechanism of acute vibration remain equivocal, but spinal reflexes, muscle tuning and neuromuscular aspects are all viable factors that may contribute in different ways to increasing muscular performance. Additional research is encouraged to determine which neural mechanism(s) and their contributions are responsible for acute vibration. Testing variables and vibration applications need to be standardised before reaching a consensus on which neural mechanism(s) occur during and post-vibration. Key points There is strong evidence to suggest that acute indirect vibration acts on muscle to enhance force, power, flexibility, balance and proprioception, but little attention has been given to the neural mechanism(s) of acute indirect vibration. Current findings suggest that acute vibration exposure may cause a neural response, but there is little

Neural correlates of phonetic convergence and speech imitation.

PubMed

Garnier, Maëva; Lamalle, Laurent; Sato, Marc

2013-01-01

Speakers unconsciously tend to mimic their interlocutor's speech during communicative interaction. This study aims at examining the neural correlates of phonetic convergence and deliberate imitation, in order to explore whether imitation of phonetic features, deliberate, or unconscious, might reflect a sensory-motor recalibration process. Sixteen participants listened to vowels with pitch varying around the average pitch of their own voice, and then produced the identified vowels, while their speech was recorded and their brain activity was imaged using fMRI. Three degrees and types of imitation were compared (unconscious, deliberate, and inhibited) using a go-nogo paradigm, which enabled the comparison of brain activations during the whole imitation process, its active perception step, and its production. Speakers followed the pitch of voices they were exposed to, even unconsciously, without being instructed to do so. After being informed about this phenomenon, 14 participants were able to inhibit it, at least partially. The results of whole brain and ROI analyses support the fact that both deliberate and unconscious imitations are based on similar neural mechanisms and networks, involving regions of the dorsal stream, during both perception and production steps of the imitation process. While no significant difference in brain activation was found between unconscious and deliberate imitations, the degree of imitation, however, appears to be determined by processes occurring during the perception step. Four regions of the dorsal stream: bilateral auditory cortex, bilateral supramarginal gyrus (SMG), and left Wernicke's area, indeed showed an activity that correlated significantly with the degree of imitation during the perception step.

Neural correlates of phonetic convergence and speech imitation

PubMed Central

Garnier, Maëva; Lamalle, Laurent; Sato, Marc

2013-01-01

Speakers unconsciously tend to mimic their interlocutor's speech during communicative interaction. This study aims at examining the neural correlates of phonetic convergence and deliberate imitation, in order to explore whether imitation of phonetic features, deliberate, or unconscious, might reflect a sensory-motor recalibration process. Sixteen participants listened to vowels with pitch varying around the average pitch of their own voice, and then produced the identified vowels, while their speech was recorded and their brain activity was imaged using fMRI. Three degrees and types of imitation were compared (unconscious, deliberate, and inhibited) using a go-nogo paradigm, which enabled the comparison of brain activations during the whole imitation process, its active perception step, and its production. Speakers followed the pitch of voices they were exposed to, even unconsciously, without being instructed to do so. After being informed about this phenomenon, 14 participants were able to inhibit it, at least partially. The results of whole brain and ROI analyses support the fact that both deliberate and unconscious imitations are based on similar neural mechanisms and networks, involving regions of the dorsal stream, during both perception and production steps of the imitation process. While no significant difference in brain activation was found between unconscious and deliberate imitations, the degree of imitation, however, appears to be determined by processes occurring during the perception step. Four regions of the dorsal stream: bilateral auditory cortex, bilateral supramarginal gyrus (SMG), and left Wernicke's area, indeed showed an activity that correlated significantly with the degree of imitation during the perception step. PMID:24062704

Msx1-Positive Progenitors in the Retinal Ciliary Margin Give Rise to Both Neural and Non-neural Progenies in Mammals.

PubMed

Bélanger, Marie-Claude; Robert, Benoit; Cayouette, Michel

2017-01-23

In lower vertebrates, stem/progenitor cells located in a peripheral domain of the retina, called the ciliary margin zone (CMZ), cooperate with retinal domain progenitors to build the mature neural retina. In mammals, it is believed that the CMZ lacks neurogenic potential and that the retina develops from one pool of multipotent retinal progenitor cells (RPCs). Here we identify a population of Msx1-expressing progenitors in the mouse CMZ that is both molecularly and functionally distinct from RPCs. Using genetic lineage tracing, we report that Msx1 progenitors have unique developmental properties compared with RPCs. Msx1 lineages contain both neural retina and non-neural ciliary epithelial progenies and overall generate fewer photoreceptors than classical RPC lineages. Furthermore, we show that the endocytic adaptor protein Numb regulates the balance between neural and non-neural fates in Msx1 progenitors. These results uncover a population of CMZ progenitors, distinct from classical RPCs, that also contributes to mammalian retinogenesis. Copyright © 2017 Elsevier Inc. All rights reserved.

Optogenetic dissection of neural circuits underlying emotional valence and motivated behaviors

PubMed Central

Nieh, Edward H.; Kim, Sung-Yon; Namburi, Praneeth; Tye, Kay M.

2014-01-01

The neural circuits underlying emotional valence and motivated behaviors are several synapses away from both defined sensory inputs and quantifiable motor outputs. Electrophysiology has provided us with a suitable means for observing neural activity during behavior, but methods for controlling activity for the purpose of studying motivated behaviors have been inadequate: electrical stimulation lacks cellular specificity and pharmacological manipulation lacks temporal resolution. The recent emergence of optogenetic tools provides a new means for establishing causal relationships between neural activity and behavior. Optogenetics, the use of genetically-encodable light-activated proteins, permits the modulation of specific neural circuit elements with millisecond precision. The ability to control individual cell types, and even projections between distal regions, allows us to investigate functional connectivity in a causal manner. The greatest consequence of controlling neural activity with finer precision has been the characterization of individual neural circuits within anatomical brain regions as defined functional units. Within the mesolimbic dopamine system, optogenetics has helped separate subsets of dopamine neurons with distinct functions for reward, aversion and salience processing, elucidated GABA neuronal effects on behavior, and characterized connectivity with forebrain and cortical structures. Within the striatum, optogenetics has confirmed the opposing relationship between direct and indirect pathway medium spiny neurons (MSNs), in addition to characterizing the inhibition of MSNs by cholinergic interneurons. Within the hypothalamus, optogenetics has helped overcome the heterogeneity in neuronal cell-type and revealed distinct circuits mediating aggression and feeding. Within the amygdala, optogenetics has allowed the study of intra-amygdala microcircuitry as well as interconnections with distal regions involved in fear and anxiety. In this review, we

The neural circuits that generate tics in Tourette's syndrome.

PubMed

Wang, Zhishun; Maia, Tiago V; Marsh, Rachel; Colibazzi, Tiziano; Gerber, Andrew; Peterson, Bradley S

2011-12-01

The purpose of this study was to examine neural activity and connectivity within cortico-striato-thalamo-cortical circuits and to reveal circuit-based neural mechanisms that govern tic generation in Tourette's syndrome. Functional magnetic resonance imaging data were acquired from 13 individuals with Tourette's syndrome and 21 healthy comparison subjects during spontaneous or simulated tics. Independent component analysis with hierarchical partner matching was used to isolate neural activity within functionally distinct regions of cortico-striato-thalamo-cortical circuits. Granger causality was used to investigate causal interactions among these regions. The Tourette's syndrome group exhibited stronger neural activity and interregional causality than healthy comparison subjects throughout all portions of the motor pathway, including the sensorimotor cortex, putamen, pallidum, and substantia nigra. Activity in these areas correlated positively with the severity of tic symptoms. Activity within the Tourette's syndrome group was stronger during spontaneous tics than during voluntary tics in the somatosensory and posterior parietal cortices, putamen, and amygdala/hippocampus complex, suggesting that activity in these regions may represent features of the premonitory urges that generate spontaneous tic behaviors. In contrast, activity was weaker in the Tourette's syndrome group than in the healthy comparison group within portions of cortico-striato-thalamo-cortical circuits that exert top-down control over motor pathways (the caudate and anterior cingulate cortex), and progressively less activity in these regions accompanied more severe tic symptoms, suggesting that faulty activity in these circuits may result in their failure to control tic behaviors or the premonitory urges that generate them. Our findings, taken together, suggest that tics are caused by the combined effects of excessive activity in motor pathways and reduced activation in control portions of cortico

Monitoring Neural Activity with Bioluminescence during Natural Behavior

PubMed Central

Naumann, Eva A.; Kampff, Adam R.; Prober, David A.; Schier, Alexander F.; Engert, Florian

2010-01-01

Existing techniques for monitoring neural activity in awake, freely behaving vertebrates are invasive and difficult to target to genetically identified neurons. Here we describe the use of bioluminescence to non-invasively monitor the activity of genetically specified neurons in freely behaving zebrafish. Transgenic fish expressing the Ca2+-sensitive photoprotein GFP-apoAequorin (GA) in most neurons generated large and fast bioluminescent signals related to neural activity, neuroluminescence, that could be recorded continuously for many days. To test the limits of this technique, GA was specifically targeted to the hypocretin-positive neurons of the hypothalamus. We found that neuroluminescence generated by this group of ~20 neurons was associated with periods of increased locomotor activity and identified two classes of neural activity corresponding to distinct swim latencies. Thus, our neuroluminescence assay can report, with high temporal resolution and sensitivity, the activity of small subsets of neurons during unrestrained behavior. PMID:20305645

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

Sex differences in the neural basis of emotional memories.

PubMed

Canli, Turhan; Desmond, John E; Zhao, Zuo; Gabrieli, John D E

2002-08-06

Psychological studies have found better memory in women than men for emotional events, but the neural basis for this difference is unknown. We used event-related functional MRI to assess whether sex differences in memory for emotional stimuli is associated with activation of different neural systems in men and women. Brain activation in 12 men and 12 women was recorded while they rated their experience of emotional arousal in response to neutral and emotionally negative pictures. In a recognition memory test 3 weeks after scanning, highly emotional pictures were remembered best, and remembered better by women than by men. Men and women activated different neural circuits to encode stimuli effectively into memory even when the analysis was restricted to pictures rated equally arousing by both groups. Men activated significantly more structures than women in a network that included the right amygdala, whereas women activated significantly fewer structures in a network that included the left amygdala. Women had significantly more brain regions where activation correlated with both ongoing evaluation of emotional experience and with subsequent memory for the most emotionally arousing pictures. Greater overlap in brain regions sensitive to current emotion and contributing to subsequent memory may be a neural mechanism for emotions to enhance memory more powerfully in women than in men.

Culture, gaze and the neural processing of fear expressions

PubMed Central

Franklin, Robert G.; Rule, Nicholas O.; Freeman, Jonathan B.; Kveraga, Kestutis; Hadjikhani, Nouchine; Yoshikawa, Sakiko; Ambady, Nalini

2010-01-01

The direction of others’ eye gaze has important influences on how we perceive their emotional expressions. Here, we examined differences in neural activation to direct- versus averted-gaze fear faces as a function of culture of the participant (Japanese versus US Caucasian), culture of the stimulus face (Japanese versus US Caucasian), and the relation between the two. We employed a previously validated paradigm to examine differences in neural activation in response to rapidly presented direct- versus averted-fear expressions, finding clear evidence for a culturally determined role of gaze in the processing of fear. Greater neural responsivity was apparent to averted- versus direct-gaze fear in several regions related to face and emotion processing, including bilateral amygdalae, when posed on same-culture faces, whereas greater response to direct- versus averted-gaze fear was apparent in these same regions when posed on other-culture faces. We also found preliminary evidence for intercultural variation including differential responses across participants to Japanese versus US Caucasian stimuli, and to a lesser degree differences in how Japanese and US Caucasian participants responded to these stimuli. These findings reveal a meaningful role of culture in the processing of eye gaze and emotion, and highlight their interactive influences in neural processing. PMID:20019073

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

The behavioural patterns and neural correlates of concrete and abstract verb processing in aphasia: A novel verb semantic battery.

PubMed

Alyahya, Reem S W; Halai, Ajay D; Conroy, Paul; Lambon Ralph, Matthew A

2018-01-01

Typically, processing is more accurate and efficient for concrete than abstract concepts in both healthy adults and individuals with aphasia. While, concreteness effects have been thoroughly documented with respect to noun processing, other words classes have received little attention despite tending to be less concrete than nouns. The aim of the current study was to explore concrete-abstract differences in verbs and identify their neural correlates in post-stroke aphasia. Given the dearth of comprehension tests for verbs, a battery of neuropsychological tests was developed in this study to assess the comprehension of concrete and abstract verbs. Specifically, a sensitive verb synonym judgment test was generated that varied both the items' imageability and frequency, and a picture-to-word matching test with numerous concrete verbs. Normative data were then collected and the tests were administered to a cohort of 48 individuals with chronic post-stroke aphasia to explore the behavioural patterns and neural correlates of verb processing. The results revealed significantly better comprehension of concrete than abstract verbs, aligning with the existing aphasiological literature on noun processing. In addition, the patients performed better during verb comprehension than verb production. Lesion-symptom correlational analyses revealed common areas that support processing of concrete and abstract verbs, including the left anterior temporal lobe, posterior supramarginal gyrus and superior lateral occipital cortex. A direct contrast between them revealed additional regions with graded differences. Specifically, the left frontal regions were associated with processing abstract verbs; whereas, the left posterior temporal and occipital regions were associated with processing concrete verbs. Moreover, overlapping and distinct neural correlates were identified in association with the comprehension and production of concrete verbs. These patient findings align with data from

Determining coding CpG islands by identifying regions significant for pattern statistics on Markov chains.

PubMed

Singer, Meromit; Engström, Alexander; Schönhuth, Alexander; Pachter, Lior

2011-09-23

Recent experimental and computational work confirms that CpGs can be unmethylated inside coding exons, thereby showing that codons may be subjected to both genomic and epigenomic constraint. It is therefore of interest to identify coding CpG islands (CCGIs) that are regions inside exons enriched for CpGs. The difficulty in identifying such islands is that coding exons exhibit sequence biases determined by codon usage and constraints that must be taken into account. We present a method for finding CCGIs that showcases a novel approach we have developed for identifying regions of interest that are significant (with respect to a Markov chain) for the counts of any pattern. Our method begins with the exact computation of tail probabilities for the number of CpGs in all regions contained in coding exons, and then applies a greedy algorithm for selecting islands from among the regions. We show that the greedy algorithm provably optimizes a biologically motivated criterion for selecting islands while controlling the false discovery rate. We applied this approach to the human genome (hg18) and annotated CpG islands in coding exons. The statistical criterion we apply to evaluating islands reduces the number of false positives in existing annotations, while our approach to defining islands reveals significant numbers of undiscovered CCGIs in coding exons. Many of these appear to be examples of functional epigenetic specialization in coding exons.

Identifying regions vulnerable to habitat degradation under future irrigation scenarios

NASA Astrophysics Data System (ADS)

Terrado, Marta; Sabater, Sergi; Acuña, Vicenç

2016-11-01

The loss and degradation of natural habitats is a primary cause of biodiversity decline. The increasing impacts of climate and land use change affect water availability, ultimately decreasing agricultural production. Areas devoted to irrigation have been increased to compensate this reduction, causing habitat and biodiversity losses, especially in regions undergoing severe water stress. These effects might intensify under global change, probably contributing to a decrease in habitat quality. We selected four European river basins across a gradient of water scarcity and irrigation agriculture. The habitat quality in the basins was assessed as a function of habitat suitability and threats under current and future global change scenarios of irrigation. Results revealed that the most threatened regions under future scenarios of global change were among those suffering of water scarcity and with bigger areas devoted to irrigation. Loss of habitat quality reached 10% in terrestrial and 25% in aquatic ecosystems under climate change scenarios involving drier conditions. The aquatic habitats were the most degraded in all scenarios, since they were affected by threats from both the terrestrial and the aquatic parts of the basin. By identifying in advance the regions most vulnerable to habitat and biodiversity loss, our approach can assist decision makers in deciding the conservation actions to be prioritized for mitigation and adaptation to the effects of climate change, particularly front the development of irrigation plans.

Maternal Neural Responses to Infant Cries and Faces: Relationships with Substance Use

PubMed Central

Landi, Nicole; Montoya, Jessica; Kober, Hedy; Rutherford, Helena J. V.; Mencl, W. Einar; Worhunsky, Patrick D.; Potenza, Marc N.; Mayes, Linda C.

2011-01-01

Substance abuse in pregnant and recently post-partum women is a major public health concern because of effects on the infant and on the ability of the adult to care for the infant. In addition to the negative health effects of teratogenic substances on fetal development, substance use can contribute to difficulties associated with the social and behavioral aspects of parenting. Neural circuits associated with parenting behavior overlap with circuits involved in addiction (e.g., frontal, striatal, and limbic systems) and thus may be co-opted for the craving/reward cycle associated with substance use and abuse and be less available for parenting. The current study investigates the degree to which neural circuits associated with parenting are disrupted in mothers who are substance-using. Specifically, we used functional magnetic resonance imaging to examine the neural response to emotional infant cues (faces and cries) in substance-using compared to non-using mothers. In response to both faces (of varying emotional valence) and cries (of varying distress levels), substance-using mothers evidenced reduced neural activation in regions that have been previously implicated in reward and motivation as well as regions involved in cognitive control. Specifically, in response to faces, substance users showed reduced activation in prefrontal regions, including the dorsolateral and ventromedial prefrontal cortices, as well as visual processing (occipital lobes) and limbic regions (parahippocampus and amygdala). Similarly, in response to infant cries, substance-using mothers showed reduced activation relative to non-using mothers in prefrontal regions, auditory sensory processing regions, insula and limbic regions (parahippocampus and amygdala). These findings suggest that infant stimuli may be less salient for substance-using mothers, and such reduced saliency may impair developing infant-caregiver attachment and the ability of mothers to respond appropriately to their infants

Shared beliefs enhance shared feelings: religious/irreligious identifications modulate empathic neural responses.

PubMed

Huang, Siyuan; Han, Shihui

2014-01-01

Recent neuroimaging research has revealed stronger empathic neural responses to same-race compared to other-race individuals. Is the in-group favouritism in empathic neural responses specific to race identification or a more general effect of social identification-including those based on religious/irreligious beliefs? The present study investigated whether and how intergroup relationships based on religious/irreligious identifications modulate empathic neural responses to others' pain expressions. We recorded event-related brain potentials from Chinese Christian and atheist participants while they perceived pain or neutral expressions of Chinese faces that were marked as being Christians or atheists. We found that both Christian and atheist participants showed stronger neural activity to pain (versus neutral) expressions at 132-168 ms and 200-320 ms over the frontal region to those with the same (versus different) religious/irreligious beliefs. The in-group favouritism in empathic neural responses was also evident in a later time window (412-612 ms) over the central/parietal regions in Christian but not in atheist participants. Our results indicate that the intergroup relationship based on shared beliefs, either religious or irreligious, can lead to in-group favouritism in empathy for others' suffering.

Statistical downscaling of precipitation using long short-term memory recurrent neural networks

NASA Astrophysics Data System (ADS)

Misra, Saptarshi; Sarkar, Sudeshna; Mitra, Pabitra

2017-11-01

Hydrological impacts of global climate change on regional scale are generally assessed by downscaling large-scale climatic variables, simulated by General Circulation Models (GCMs), to regional, small-scale hydrometeorological variables like precipitation, temperature, etc. In this study, we propose a new statistical downscaling model based on Recurrent Neural Network with Long Short-Term Memory which captures the spatio-temporal dependencies in local rainfall. The previous studies have used several other methods such as linear regression, quantile regression, kernel regression, beta regression, and artificial neural networks. Deep neural networks and recurrent neural networks have been shown to be highly promising in modeling complex and highly non-linear relationships between input and output variables in different domains and hence we investigated their performance in the task of statistical downscaling. We have tested this model on two datasets—one on precipitation in Mahanadi basin in India and the second on precipitation in Campbell River basin in Canada. Our autoencoder coupled long short-term memory recurrent neural network model performs the best compared to other existing methods on both the datasets with respect to temporal cross-correlation, mean squared error, and capturing the extremes.

Concurrent OCT imaging of stimulus evoked retinal neural activation and hemodynamic responses

NASA Astrophysics Data System (ADS)

Son, Taeyoon; Wang, Benquan; Lu, Yiming; Chen, Yanjun; Cao, Dingcai; Yao, Xincheng

2017-02-01

It is well established that major retinal diseases involve distortions of the retinal neural physiology and blood vascular structures. However, the details of distortions in retinal neurovascular coupling associated with major eye diseases are not well understood. In this study, a multi-modal optical coherence tomography (OCT) imaging system was developed to enable concurrent imaging of retinal neural activity and vascular hemodynamics. Flicker light stimulation was applied to mouse retinas to evoke retinal neural responses and hemodynamic changes. The OCT images were acquired continuously during the pre-stimulation, light-stimulation, and post-stimulation phases. Stimulus-evoked intrinsic optical signals (IOSs) and hemodynamic changes were observed over time in blood-free and blood regions, respectively. Rapid IOSs change occurred almost immediately after stimulation. Both positive and negative signals were observed in adjacent retinal areas. The hemodynamic changes showed time delays after stimulation. The signal magnitudes induced by light stimulation were observed in blood regions and did not show significant changes in blood-free regions. These differences may arise from different mechanisms in blood vessels and neural tissues in response to light stimulation. These characteristics agreed well with our previous observations in mouse retinas. Further development of the multimodal OCT may provide a new imaging method for studying how retinal structures and metabolic and neural functions are affected by age-related macular degeneration (AMD), glaucoma, diabetic retinopathy (DR), and other diseases, which promises novel noninvasive biomarkers for early disease detection and reliable treatment evaluations of eye diseases.

Markov chain-incorporated and synthetic data-supported conditional artificial neural network models for forecasting monthly precipitation in arid regions

NASA Astrophysics Data System (ADS)

Aksoy, Hafzullah; Dahamsheh, Ahmad

2018-07-01

For forecasting monthly precipitation in an arid region, the feed forward back-propagation, radial basis function and generalized regression artificial neural networks (ANNs) are used in this study. The ANN models are improved after incorporation of a Markov chain-based algorithm (MC-ANNs) with which the percentage of dry months is forecasted perfectly, thus generation of any non-physical negative precipitation is eliminated. Due to the fact that recorded precipitation time series are usually shorter than the length needed for a proper calibration of ANN models, synthetic monthly precipitation data are generated by Thomas-Fiering model to further improve the performance of forecasting. For case studies from Jordan, it is seen that only a slightly better performance is achieved with the use of MC and synthetic data. A conditional statement is, therefore, established and imbedded into the ANN models after the incorporation of MC and support of synthetic data, to substantially improve the ability of the models for forecasting monthly precipitation in arid regions.

Identifying open magnetic field regions of the Sun and their heliospheric counterparts

NASA Astrophysics Data System (ADS)

Krista, L. D.; Reinard, A.

2017-12-01

Open magnetic regions on the Sun are either long-lived (coronal holes) or transient (dimmings) in nature. Both phenomena are fundamental to our understanding of the solar behavior as a whole. Coronal holes are the sources of high-speed solar wind streams that cause recurrent geomagnetic storms. Furthermore, the variation of coronal hole properties (area, location, magnetic field strength) over the solar activity cycle is an important marker of the global evolution of the solar magnetic field. Dimming regions, on the other hand, are short-lived coronal holes that often emerge in the wake of solar eruptions. By analyzing their physical properties and their temporal evolution, we aim to understand their connection with their eruptive counterparts (flares and coronal mass ejections) and predict the possibility of a geomagnetic storm. The author developed the Coronal Hole Automated Recognition and Monitoring (CHARM) and the Coronal Dimming Tracker (CoDiT) algorithms. These tools not only identify but track the evolution of open magnetic field regions. CHARM also provides daily coronal hole maps, that are used for forecasts at the NOAA Space Weather Prediction Center. Our goal is to better understand the processes that give rise to eruptive and non-eruptive open field regions and investigate how these regions evolve over time and influence space weather.

Dynamic Neural State Identification in Deep Brain Local Field Potentials of Neuropathic Pain.

PubMed

Luo, Huichun; Huang, Yongzhi; Du, Xueying; Zhang, Yunpeng; Green, Alexander L; Aziz, Tipu Z; Wang, Shouyan

2018-01-01

In neuropathic pain, the neurophysiological and neuropathological function of the ventro-posterolateral nucleus of the thalamus (VPL) and the periventricular gray/periaqueductal gray area (PVAG) involves multiple frequency oscillations. Moreover, oscillations related to pain perception and modulation change dynamically over time. Fluctuations in these neural oscillations reflect the dynamic neural states of the nucleus. In this study, an approach to classifying the synchronization level was developed to dynamically identify the neural states. An oscillation extraction model based on windowed wavelet packet transform was designed to characterize the activity level of oscillations. The wavelet packet coefficients sparsely represented the activity level of theta and alpha oscillations in local field potentials (LFPs). Then, a state discrimination model was designed to calculate an adaptive threshold to determine the activity level of oscillations. Finally, the neural state was represented by the activity levels of both theta and alpha oscillations. The relationship between neural states and pain relief was further evaluated. The performance of the state identification approach achieved sensitivity and specificity beyond 80% in simulation signals. Neural states of the PVAG and VPL were dynamically identified from LFPs of neuropathic pain patients. The occurrence of neural states based on theta and alpha oscillations were correlated to the degree of pain relief by deep brain stimulation. In the PVAG LFPs, the occurrence of the state with high activity levels of theta oscillations independent of alpha and the state with low-level alpha and high-level theta oscillations were significantly correlated with pain relief by deep brain stimulation. This study provides a reliable approach to identifying the dynamic neural states in LFPs with a low signal-to-noise ratio by using sparse representation based on wavelet packet transform. Furthermore, it may advance closed-loop deep