Habit strength is predicted by activity dynamics in goal-directed brain systems during training.

PubMed

Zwosta, Katharina; Ruge, Hannes; Goschke, Thomas; Wolfensteller, Uta

2018-01-15

Previous neuroscientific research revealed insights into the brain networks supporting goal-directed and habitual behavior, respectively. However, it remains unclear how these contribute to inter-individual differences in habit strength which is relevant for understanding not only normal behavior but also more severe dysregulations between these types of action control, such as in addiction. In the present fMRI study, we trained subjects on approach and avoidance behavior for an extended period of time before testing the habit strength of the acquired stimulus-response associations. We found that stronger habits were associated with a stronger decrease in inferior parietal lobule activity for approach and avoidance behavior and weaker vmPFC activity at the end of training for avoidance behavior, areas associated with the anticipation of outcome identity and value. VmPFC in particular showed markedly different activity dynamics during the training of approach and avoidance behavior. Furthermore, while ongoing training was accompanied by increasing functional connectivity between posterior putamen and premotor cortex, consistent with previous assumptions about the neural basis of increasing habitualization, this was not predictive of later habit strength. Together, our findings suggest that inter-individual differences in habitual behavior are driven by differences in the persistent involvement of brain areas supporting goal-directed behavior during training. Copyright © 2017. Published by Elsevier Inc.

Performance predictions affect attentional processes of event-based prospective memory.

PubMed

Rummel, Jan; Kuhlmann, Beatrice G; Touron, Dayna R

2013-09-01

To investigate whether making performance predictions affects prospective memory (PM) processing, we asked one group of participants to predict their performance in a PM task embedded in an ongoing task and compared their performance with a control group that made no predictions. A third group gave not only PM predictions but also ongoing-task predictions. Exclusive PM predictions resulted in slower ongoing-task responding both in a nonfocal (Experiment 1) and in a focal (Experiment 2) PM task. Only in the nonfocal task was the additional slowing accompanied by improved PM performance. Even in the nonfocal task, however, was the correlation between ongoing-task speed and PM performance reduced after predictions, suggesting that the slowing was not completely functional for PM. Prediction-induced changes could be avoided by asking participants to additionally predict their performance in the ongoing task. In sum, the present findings substantiate a role of metamemory for attention-allocation strategies of PM. Copyright © 2013 Elsevier Inc. All rights reserved.

Medical aspects of pediatric rehabilitation after moderate to severe traumatic brain injury.

PubMed

Cantore, Lisa; Norwood, Kenneth; Patrick, Peter

2012-01-01

Recovery from severe traumatic brain injury (TBI) is prolonged, complicated and challenging. Medical rehabilitation is the bridge from acute medical care and stabilization to community reintegration. The process of caring for the recovering brain introduces unknown challenges of neural plasticity with demands to restore and to also move the child and family back to the developmental trajectory they once knew. While the ongoing focus is to maintain and advance medical stability, co- morbid conditions are addressed, and a plan for ongoing health is established. While no one manuscript can cover all of the medical aspects, this article will present in a "systems review" manner the most challenging and demanding medical conditions that children may confront following severe brain injury.

Predicting parenting stress in caregivers of children with brain tumours.

PubMed

Bennett, Emily; English, Martin William; Rennoldson, Michael; Starza-Smith, Arleta

2013-03-01

The purpose of the study was to identify factors that contribute to parenting stress in caregivers of children diagnosed with brain tumours. The study was cross-sectional and recruited 37 participants from a clinical database at a specialist children's hospital. Parents were sent questionnaires, which were used to measure factors related to stress in caregivers of children diagnosed with a brain tumour. Stress levels were measured using the Parenting Stress Index-Short Form (PSI/SF). Correlation analysis and multiple linear regression were used to examine the associations between parenting stress and coping styles, locus of control, parent-perceived child disability and time since diagnosis. Results revealed that 51% of parents were experiencing clinically significant levels of stress. The mean stress level of parents in the study was significantly higher than the PSI/SF norms (t = 4.7, p < .001). Regression analysis revealed that external locus of control and coping by accepting responsibility accounted for 67% of the variance in parenting stress. Other styles of coping, child behaviour problems and the amount of time since diagnosis were not found to be predictive of levels of parenting stress. There was a high prevalence of parenting stress in caregivers of children with a brain tumour. An external locus of control and coping by accepting responsibility increased the likelihood of elevated levels of stress. Results emphasised the importance of ongoing support for parents of children with brain tumours. Intervention might helpfully be centred on strategies to increase parents' internal locus of control. Copyright © 2012 John Wiley & Sons, Ltd.

Starting Smart: How Early Experiences Affect Brain Development. An Ounce of Prevention Fund Paper.

ERIC Educational Resources Information Center

Ounce of Prevention Fund.

Recent research has provided great insight into the impact of early experience on brain development. It is now believed that brain growth is highly dependent upon early experiences. Neurons allow communication and coordinated functioning among various brain areas. Brain development after birth consists of an ongoing process of wiring and rewiring…

Improving visual perception through neurofeedback

PubMed Central

Scharnowski, Frank; Hutton, Chloe; Josephs, Oliver; Weiskopf, Nikolaus; Rees, Geraint

2012-01-01

Perception depends on the interplay of ongoing spontaneous activity and stimulus-evoked activity in sensory cortices. This raises the possibility that training ongoing spontaneous activity alone might be sufficient for enhancing perceptual sensitivity. To test this, we trained human participants to control ongoing spontaneous activity in circumscribed regions of retinotopic visual cortex using real-time functional MRI based neurofeedback. After training, we tested participants using a new and previously untrained visual detection task that was presented at the visual field location corresponding to the trained region of visual cortex. Perceptual sensitivity was significantly enhanced only when participants who had previously learned control over ongoing activity were now exercising control, and only for that region of visual cortex. Our new approach allows us to non-invasively and non-pharmacologically manipulate regionally specific brain activity, and thus provide ‘brain training’ to deliver particular perceptual enhancements. PMID:23223302

Brain Functional Changes before, during, and after Clinical Pain.

PubMed

Hu, X; Racek, A J; Bellile, E; Nascimento, T D; Bender, M C; Toback, R L; Burnett, D; Khatib, L; McMahan, R; Kovelman, I; Ellwood, R P; DaSilva, A F

2018-05-01

This study used an emerging brain imaging technique, functional near-infrared spectroscopy (fNIRS), to investigate functional brain activation and connectivity that modulates sometimes traumatic pain experience in a clinical setting. Hemodynamic responses were recorded at bilateral somatosensory (S1) and prefrontal cortices (PFCs) from 12 patients with dentin hypersensitivity in a dental chair before, during, and after clinical pain. Clinical dental pain was triggered with 20 consecutive descending cold stimulations (32° to 0°C) to the affected teeth. We used a partial least squares path modeling framework to link patients' clinical pain experience with recorded hemodynamic responses at sequential stages and baseline resting-state functional connectivity (RSFC). Hemodynamic responses at PFC/S1 were sequentially elicited by expectation, cold detection, and pain perception at a high-level coefficient (coefficients: 0.92, 0.98, and 0.99, P < 0.05). We found that the pain ratings were positively affected only at a moderate level of coefficients by such sequence of functional activation (coefficient: 0.52, P < 0.05) and the baseline PFC-S1 RSFC (coefficient: 0.59, P < 0.05). Furthermore, when the dental pain had finally subsided, the PFC increased its functional connection with the affected S1 orofacial region contralateral to the pain stimulus and, in contrast, decreased with the ipsilateral homuncular S1 regions ( P < 0.05). Our study indicated for the first time that patients' clinical pain experience in the dental chair can be predicted concomitantly by their baseline functional connectivity between S1 and PFC, as well as their sequence of ongoing hemodynamic responses. In addition, this linked cascade of events had immediate after-effects on the patients' brain connectivity, even when clinical pain had already ceased. Our findings offer a better understating of the ongoing impact of affective and sensory experience in the brain before, during, and after clinical dental pain.

Predictive Suppression of Cortical Excitability and Its Deficit in Schizophrenia

PubMed Central

Schroeder, Charles E.; Leitman, David I.

2013-01-01

Recent neuroscience advances suggest that when interacting with our environment, along with previous experience, we use contextual cues and regularities to form predictions that guide our perceptions and actions. The goal of such active “predictive sensing” is to selectively enhance the processing and representation of behaviorally relevant information in an efficient manner. Since a hallmark of schizophrenia is impaired information selection, we tested whether this deficiency stems from dysfunctional predictive sensing by measuring the degree to which neuronal activity predicts relevant events. In healthy subjects, we established that these mechanisms are engaged in an effort-dependent manner and that, based on a correspondence between human scalp and intracranial nonhuman primate recordings, their main role is a predictive suppression of excitability in task-irrelevant regions. In contrast, schizophrenia patients displayed a reduced alignment of neuronal activity to attended stimuli, which correlated with their behavioral performance deficits and clinical symptoms. These results support the relevance of predictive sensing for normal and aberrant brain function, and highlight the importance of neuronal mechanisms that mold internal ongoing neuronal activity to model key features of the external environment. PMID:23843536

Correspondence Between Aberrant Intrinsic Network Connectivity and Gray-Matter Volume in the Ventral Brain of Preterm Born Adults.

PubMed

Bäuml, Josef G; Daamen, Marcel; Meng, Chun; Neitzel, Julia; Scheef, Lukas; Jaekel, Julia; Busch, Barbara; Baumann, Nicole; Bartmann, Peter; Wolke, Dieter; Boecker, Henning; Wohlschläger, Afra M; Sorg, Christian

2015-11-01

Widespread brain changes are present in preterm born infants, adolescents, and even adults. While neurobiological models of prematurity facilitate powerful explanations for the adverse effects of preterm birth on the developing brain at microscale, convincing linking principles at large-scale level to explain the widespread nature of brain changes are still missing. We investigated effects of preterm birth on the brain's large-scale intrinsic networks and their relation to brain structure in preterm born adults. In 95 preterm and 83 full-term born adults, structural and functional magnetic resonance imaging at-rest was used to analyze both voxel-based morphometry and spatial patterns of functional connectivity in ongoing blood oxygenation level-dependent activity. Differences in intrinsic functional connectivity (iFC) were found in cortical and subcortical networks. Structural differences were located in subcortical, temporal, and cingulate areas. Critically, for preterm born adults, iFC-network differences were overlapping and correlating with aberrant regional gray-matter (GM) volume specifically in subcortical and temporal areas. Overlapping changes were predicted by prematurity and in particular by neonatal medical complications. These results provide evidence that preterm birth has long-lasting effects on functional connectivity of intrinsic networks, and these changes are specifically related to structural alterations in ventral brain GM. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Cerebrospinal Fluid Biomarkers and Reserve Variables as Predictors of Future “Non-Cognitive” Outcomes of Alzheimer’s Disease

PubMed Central

Ingber, Adam P.; Hassenstab, Jason; Fagan, Anne M.; Benzinger, Tammie L.S.; Grant, Elizabeth A.; Holtzman, David M.; Morris, John C.; Roe, Catherine M.

2016-01-01

Background The influence of reserve variables and Alzheimer’s disease (AD) biomarkers on cognitive test performance has been fairly well-characterized. However, less is known about the influence of these factors on “non-cognitive” outcomes, including functional abilities and mood. Objective We examined whether cognitive and brain reserve variables mediate how AD biomarker levels in cognitively normal persons predict future changes in function, mood, and neuropsychiatric behavior. Methods Non-cognitive outcomes were examined in 328 individuals 50 years and older enrolled in ongoing studies of aging and dementia at the Knight Alzheimer Disease Research Center (ADRC). All participants were cognitively normal at baseline (Clinical Dementia Rating [CDR] 0), completed cerebrospinal fluid (CSF) and structural neuroimaging studies within one year of baseline, and were followed for an average of 4.6 annual visits. Linear mixed effects models explored how cognitive reserve and brain reserve variables mediate the relationships between AD biomarker levels and changes in function, mood, and neuropsychiatric behavior in cognitively normal participants. Results Education levels did not have a significant effect on predicting non-cognitive decline. However, participants with smaller brain volumes exhibited the worst outcomes on measures of mood, functional abilities, and behavioral disturbance. This effect was most pronounced in individuals who also had abnormal CSF biomarkers. Conclusions The findings suggest that brain reserve plays a stronger, or earlier, role than cognitive reserve in protecting against non-cognitive impairment in AD. PMID:27104893

Starting Smart: How Early Experiences Affect Brain Development. Second Edition.

ERIC Educational Resources Information Center

Hawley, Theresa

Based on recent research, it is now believed that brain growth is highly dependent upon children's early experiences. Neurons allow communication and coordinated functioning among various brain areas. Brain development after birth consists of an ongoing process of wiring and rewiring the connections among neurons. The forming and breaking of…

Changes in brain anatomy during the course of PTSD

PubMed Central

Cardenas, Valerie A.; Samuelson, Kristin; Lenoci, Maryann; Studholme, Colin; Neylan, Thomas C.; Marmar, Charles R.; Schuff, Norbert; Weiner, Michael W.

2011-01-01

The goal of this study was to determine whether PTSD was associated with an increase in time-related decline in macrostructural brain volume and whether these changes were associated with accelerated cognitive decline. To quantify brain structure, 3 dimensional T1-weighted MRI scans were performed at baseline and again after a minimum of 24 months in 25 patients with PTSD and 22 controls. Longitudinal changes in brain volume were measured using deformation morphometry. For the group as a whole PTSD+ patients did not show significant ongoing brain atrophy compared to PTSD-. PTSD+ patients were then subgrouped into those with decreasing or increasing symptoms. We found little evidence for brain markers of accelerated atrophy in PTSD+ veterans whose symptoms improved over time, with only a small left parietal region showing greater ongoing tissue loss than PTSD-. PTSD patients whose symptoms increased over time showed accelerated atrophy throughout the brain, particularly brainstem and frontal and temporal lobes. Lastly, for the sample as a whole greater rates of brain atrophy were associated with greater rates of decline in verbal memory and delayed facial recognition. PMID:21683556

Involvement of the anterior cingulate cortex in time-based prospective memory task monitoring: An EEG analysis of brain sources using Independent Component and Measure Projection Analysis

PubMed Central

Burgos, Pablo; Kilborn, Kerry; Evans, Jonathan J.

2017-01-01

Objective Time-based prospective memory (PM), remembering to do something at a particular moment in the future, is considered to depend upon self-initiated strategic monitoring, involving a retrieval mode (sustained maintenance of the intention) plus target checking (intermittent time checks). The present experiment was designed to explore what brain regions and brain activity are associated with these components of strategic monitoring in time-based PM tasks. Method 24 participants were asked to reset a clock every four minutes, while performing a foreground ongoing word categorisation task. EEG activity was recorded and data were decomposed into source-resolved activity using Independent Component Analysis. Common brain regions across participants, associated with retrieval mode and target checking, were found using Measure Projection Analysis. Results Participants decreased their performance on the ongoing task when concurrently performed with the time-based PM task, reflecting an active retrieval mode that relied on withdrawal of limited resources from the ongoing task. Brain activity, with its source in or near the anterior cingulate cortex (ACC), showed changes associated with an active retrieval mode including greater negative ERP deflections, decreased theta synchronization, and increased alpha suppression for events locked to the ongoing task while maintaining a time-based intention. Activity in the ACC was also associated with time-checks and found consistently across participants; however, we did not find an association with time perception processing per se. Conclusion The involvement of the ACC in both aspects of time-based PM monitoring may be related to different functions that have been attributed to it: strategic control of attention during the retrieval mode (distributing attentional resources between the ongoing task and the time-based task) and anticipatory/decision making processing associated with clock-checks. PMID:28863146

Does vigorous exercise have a neuroprotective effect in Parkinson disease?

PubMed Central

2011-01-01

Parkinson disease (PD) is progressive, with dementia and medication-refractory motor problems common reasons for late-stage nursing-home placement. Increasing evidence suggests that ongoing vigorous exercise/physical fitness may favorably influence this progression. Parkinsonian animal models reveal exercise-related protection from dopaminergic neurotoxins, apparently mediated by brain neurotrophic factors and neuroplasticity (predicted from in vitro studies). Similarly, exercise consistently improves cognition in animals, also linked to enhanced neuroplasticity and increased neurotrophic factor expression. In these animal models, immobilization has the opposite effect. Brain-derived neurotrophic factor (BDNF) may mediate at least some of this exercise benefit. In humans, exercise increases serum BDNF, and this is known to cross the blood–brain barrier. PD risk in humans is significantly reduced by midlife exercise, documented in large prospective studies. No studies have addressed whether exercise influences dementia risk in PD, but exercised patients with PD improve cognitive scores. Among seniors in general, exercise or physical fitness has not only been associated with better cognitive scores, but midlife exercise significantly reduces the later risk of both dementia and mild cognitive impairment. Finally, numerous studies in seniors with and without dementia have reported increased cerebral gray matter volumes associated with physical fitness or exercise. These findings have several implications for PD clinicians. 1) Ongoing vigorous exercise and physical fitness should be highly encouraged. 2) PD physical therapy programs should include structured, graduated fitness instruction and guidance for deconditioned patients with PD. 3) Levodopa and other forms of dopamine replenishment therapy should be utilized to achieve the maximum capability and motivation for patients to maintain fitness. PMID:21768599

Gut Microbes and the Brain: Paradigm Shift in Neuroscience

PubMed Central

Knight, Rob; Mazmanian, Sarkis K.; Cryan, John F.; Tillisch, Kirsten

2014-01-01

The discovery of the size and complexity of the human microbiome has resulted in an ongoing reevaluation of many concepts of health and disease, including diseases affecting the CNS. A growing body of preclinical literature has demonstrated bidirectional signaling between the brain and the gut microbiome, involving multiple neurocrine and endocrine signaling mechanisms. While psychological and physical stressors can affect the composition and metabolic activity of the gut microbiota, experimental changes to the gut microbiome can affect emotional behavior and related brain systems. These findings have resulted in speculation that alterations in the gut microbiome may play a pathophysiological role in human brain diseases, including autism spectrum disorder, anxiety, depression, and chronic pain. Ongoing large-scale population-based studies of the gut microbiome and brain imaging studies looking at the effect of gut microbiome modulation on brain responses to emotion-related stimuli are seeking to validate these speculations. This article is a summary of emerging topics covered in a symposium and is not meant to be a comprehensive review of the subject. PMID:25392516

Manipulating motor performance and memory through real-time fMRI neurofeedback.

PubMed

Scharnowski, Frank; Veit, Ralf; Zopf, Regine; Studer, Petra; Bock, Simon; Diedrichsen, Jörn; Goebel, Rainer; Mathiak, Klaus; Birbaumer, Niels; Weiskopf, Nikolaus

2015-05-01

Task performance depends on ongoing brain activity which can be influenced by attention, arousal, or motivation. However, such modulating factors of cognitive efficiency are unspecific, can be difficult to control, and are not suitable to facilitate neural processing in a regionally specific manner. Here, we non-pharmacologically manipulated regionally specific brain activity using technically sophisticated real-time fMRI neurofeedback. This was accomplished by training participants to simultaneously control ongoing brain activity in circumscribed motor and memory-related brain areas, namely the supplementary motor area and the parahippocampal cortex. We found that learned voluntary control over these functionally distinct brain areas caused functionally specific behavioral effects, i.e. shortening of motor reaction times and specific interference with memory encoding. The neurofeedback approach goes beyond improving cognitive efficiency by unspecific psychological factors such as attention, arousal, or motivation. It allows for directly manipulating sustained activity of task-relevant brain regions in order to yield specific behavioral or cognitive effects. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Manipulating motor performance and memory through real-time fMRI neurofeedback

PubMed Central

Scharnowski, Frank; Veit, Ralf; Zopf, Regine; Studer, Petra; Bock, Simon; Diedrichsen, Jörn; Goebel, Rainer; Mathiak, Klaus; Birbaumer, Niels; Weiskopf, Nikolaus

2015-01-01

Task performance depends on ongoing brain activity which can be influenced by attention, arousal, or motivation. However, such modulating factors of cognitive efficiency are unspecific, can be difficult to control, and are not suitable to facilitate neural processing in a regionally specific manner. Here, we non-pharmacologically manipulated regionally specific brain activity using technically sophisticated real-time fMRI neurofeedback. This was accomplished by training participants to simultaneously control ongoing brain activity in circumscribed motor and memory-related brain areas, namely the supplementary motor area and the parahippocampal cortex. We found that learned voluntary control over these functionally distinct brain areas caused functionally specific behavioral effects, i.e. shortening of motor reaction times and specific interference with memory encoding. The neurofeedback approach goes beyond improving cognitive efficiency by unspecific psychological factors such as attention, arousal, or motivation. It allows for directly manipulating sustained activity of task-relevant brain regions in order to yield specific behavioral or cognitive effects. PMID:25796342

Dissecting gene expression at the blood-brain barrier

PubMed Central

Huntley, Melanie A.; Bien-Ly, Nga; Daneman, Richard; Watts, Ryan J.

2014-01-01

The availability of genome-wide expression data for the blood-brain barrier is an invaluable resource that has recently enabled the discovery of several genes and pathways involved in the development and maintenance of the blood-brain barrier, particularly in rodent models. The broad distribution of published data sets represents a viable starting point for the molecular dissection of the blood-brain barrier and will further direct the discovery of novel mechanisms of blood-brain barrier formation and function. Technical advances in purifying brain endothelial cells, the key cell that forms the critical barrier, have allowed for greater specificity in gene expression comparisons with other central nervous system cell types, and more systematic characterizations of the molecular composition of the blood-brain barrier. Nevertheless, our understanding of how the blood-brain barrier changes during aging and disease is underrepresented. Blood-brain barrier data sets from a wider range of experimental paradigms and species, including invertebrates and primates, would be invaluable for investigating the function and evolution of the blood-brain barrier. Newer technologies in gene expression profiling, such as RNA-sequencing, now allow for finer resolution of transcriptomic changes, including isoform specificity and RNA-editing. As our field continues to utilize more advanced expression profiling in its ongoing efforts to elucidate the blood-brain barrier, including in disease and drug delivery, we will continue to see rapid advances in our understanding of the molecular mediators of barrier biology. We predict that the recently published data sets, combined with forthcoming genomic and proteomic blood-brain barrier data sets, will continue to fuel the molecular genetic revolution of blood-brain barrier biology. PMID:25414634

Neural Oscillations Carry Speech Rhythm through to Comprehension

PubMed Central

Peelle, Jonathan E.; Davis, Matthew H.

2012-01-01

A key feature of speech is the quasi-regular rhythmic information contained in its slow amplitude modulations. In this article we review the information conveyed by speech rhythm, and the role of ongoing brain oscillations in listeners’ processing of this content. Our starting point is the fact that speech is inherently temporal, and that rhythmic information conveyed by the amplitude envelope contains important markers for place and manner of articulation, segmental information, and speech rate. Behavioral studies demonstrate that amplitude envelope information is relied upon by listeners and plays a key role in speech intelligibility. Extending behavioral findings, data from neuroimaging – particularly electroencephalography (EEG) and magnetoencephalography (MEG) – point to phase locking by ongoing cortical oscillations to low-frequency information (~4–8 Hz) in the speech envelope. This phase modulation effectively encodes a prediction of when important events (such as stressed syllables) are likely to occur, and acts to increase sensitivity to these relevant acoustic cues. We suggest a framework through which such neural entrainment to speech rhythm can explain effects of speech rate on word and segment perception (i.e., that the perception of phonemes and words in connected speech is influenced by preceding speech rate). Neuroanatomically, acoustic amplitude modulations are processed largely bilaterally in auditory cortex, with intelligible speech resulting in differential recruitment of left-hemisphere regions. Notable among these is lateral anterior temporal cortex, which we propose functions in a domain-general fashion to support ongoing memory and integration of meaningful input. Together, the reviewed evidence suggests that low-frequency oscillations in the acoustic speech signal form the foundation of a rhythmic hierarchy supporting spoken language, mirrored by phase-locked oscillations in the human brain. PMID:22973251

Behavioral, Brain Imaging and Genomic Measures to Predict Functional Outcomes Post - Bed Rest and Spaceflight

NASA Technical Reports Server (NTRS)

Mulavara, A. P.; DeDios, Y. E.; Gadd, N. E.; Caldwell, E. E.; Batson, C. D.; Goel, R.; Seidler, R. D.; Oddsson, L.; Zanello, S.; Clarke, T.;

Embodied Anticipation: A Neurodevelopmental Interpretation

ERIC Educational Resources Information Center

Kinsbourne, Marcel; Jordan, J. Scott

2009-01-01

This article proposes an approach to the brain's role in communication that treats the brain as the vehicle of a multi-scale embodiment of anticipation. Instead of conceptualizing anticipation as something a brain is able to do when circumstances seem to require it, this study proposes that anticipation is continuous and ongoing because to…

The prestimulus default mode network state predicts cognitive task performance levels on a mental rotation task.

PubMed

Kamp, Tabea; Sorger, Bettina; Benjamins, Caroline; Hausfeld, Lars; Goebel, Rainer

2018-06-22

Linking individual task performance to preceding, regional brain activation is an ongoing goal of neuroscientific research. Recently, it could be shown that the activation and connectivity within large-scale brain networks prior to task onset influence performance levels. More specifically, prestimulus default mode network (DMN) effects have been linked to performance levels in sensory near-threshold tasks, as well as cognitive tasks. However, it still remains uncertain how the DMN state preceding cognitive tasks affects performance levels when the period between task trials is long and flexible, allowing participants to engage in different cognitive states. We here investigated whether the prestimulus activation and within-network connectivity of the DMN are predictive of the correctness and speed of task performance levels on a cognitive (match-to-sample) mental rotation task, employing a sparse event-related functional magnetic resonance imaging (fMRI) design. We found that prestimulus activation in the DMN predicted the speed of correct trials, with a higher amplitude preceding correct fast response trials compared to correct slow response trials. Moreover, we found higher connectivity within the DMN before incorrect trials compared to correct trials. These results indicate that pre-existing activation and connectivity states within the DMN influence task performance on cognitive tasks, both effecting the correctness and speed of task execution. The findings support existing theories and empirical work on relating mind-wandering and cognitive task performance to the DMN and expand these by establishing a relationship between the prestimulus DMN state and the speed of cognitive task performance. © 2018 The Authors. Brain and Behavior published by Wiley Periodicals, Inc.

A theory of how active behavior stabilises neural activity: Neural gain modulation by closed-loop environmental feedback

PubMed Central

2018-01-01

During active behaviours like running, swimming, whisking or sniffing, motor actions shape sensory input and sensory percepts guide future motor commands. Ongoing cycles of sensory and motor processing constitute a closed-loop feedback system which is central to motor control and, it has been argued, for perceptual processes. This closed-loop feedback is mediated by brainwide neural circuits but how the presence of feedback signals impacts on the dynamics and function of neurons is not well understood. Here we present a simple theory suggesting that closed-loop feedback between the brain/body/environment can modulate neural gain and, consequently, change endogenous neural fluctuations and responses to sensory input. We support this theory with modeling and data analysis in two vertebrate systems. First, in a model of rodent whisking we show that negative feedback mediated by whisking vibrissa can suppress coherent neural fluctuations and neural responses to sensory input in the barrel cortex. We argue this suppression provides an appealing account of a brain state transition (a marked change in global brain activity) coincident with the onset of whisking in rodents. Moreover, this mechanism suggests a novel signal detection mechanism that selectively accentuates active, rather than passive, whisker touch signals. This mechanism is consistent with a predictive coding strategy that is sensitive to the consequences of motor actions rather than the difference between the predicted and actual sensory input. We further support the theory by re-analysing previously published two-photon data recorded in zebrafish larvae performing closed-loop optomotor behaviour in a virtual swim simulator. We show, as predicted by this theory, that the degree to which each cell contributes in linking sensory and motor signals well explains how much its neural fluctuations are suppressed by closed-loop optomotor behaviour. More generally we argue that our results demonstrate the dependence of neural fluctuations, across the brain, on closed-loop brain/body/environment interactions strongly supporting the idea that brain function cannot be fully understood through open-loop approaches alone. PMID:29342146

A theory of how active behavior stabilises neural activity: Neural gain modulation by closed-loop environmental feedback.

PubMed

Buckley, Christopher L; Toyoizumi, Taro

2018-01-01

During active behaviours like running, swimming, whisking or sniffing, motor actions shape sensory input and sensory percepts guide future motor commands. Ongoing cycles of sensory and motor processing constitute a closed-loop feedback system which is central to motor control and, it has been argued, for perceptual processes. This closed-loop feedback is mediated by brainwide neural circuits but how the presence of feedback signals impacts on the dynamics and function of neurons is not well understood. Here we present a simple theory suggesting that closed-loop feedback between the brain/body/environment can modulate neural gain and, consequently, change endogenous neural fluctuations and responses to sensory input. We support this theory with modeling and data analysis in two vertebrate systems. First, in a model of rodent whisking we show that negative feedback mediated by whisking vibrissa can suppress coherent neural fluctuations and neural responses to sensory input in the barrel cortex. We argue this suppression provides an appealing account of a brain state transition (a marked change in global brain activity) coincident with the onset of whisking in rodents. Moreover, this mechanism suggests a novel signal detection mechanism that selectively accentuates active, rather than passive, whisker touch signals. This mechanism is consistent with a predictive coding strategy that is sensitive to the consequences of motor actions rather than the difference between the predicted and actual sensory input. We further support the theory by re-analysing previously published two-photon data recorded in zebrafish larvae performing closed-loop optomotor behaviour in a virtual swim simulator. We show, as predicted by this theory, that the degree to which each cell contributes in linking sensory and motor signals well explains how much its neural fluctuations are suppressed by closed-loop optomotor behaviour. More generally we argue that our results demonstrate the dependence of neural fluctuations, across the brain, on closed-loop brain/body/environment interactions strongly supporting the idea that brain function cannot be fully understood through open-loop approaches alone.

Physiological Observations and Omics to Develop Personalized Sensormotor Adaptability Countermeasures Using Bed Rest and Space Flight Data

NASA Technical Reports Server (NTRS)

Mulavara, A. P.; Seidler, R. D.; Feiveson, A.; Oddsson, L.; Zanello, S.; Oman, C. M.; Ploutz-Snyder, L.; Peters, B.; Cohen, H. S.; Reschke, M.;

Fast mental states decoding in mixed reality.

PubMed

De Massari, Daniele; Pacheco, Daniel; Malekshahi, Rahim; Betella, Alberto; Verschure, Paul F M J; Birbaumer, Niels; Caria, Andrea

2014-01-01

The combination of Brain-Computer Interface (BCI) technology, allowing online monitoring and decoding of brain activity, with virtual and mixed reality (MR) systems may help to shape and guide implicit and explicit learning using ecological scenarios. Real-time information of ongoing brain states acquired through BCI might be exploited for controlling data presentation in virtual environments. Brain states discrimination during mixed reality experience is thus critical for adapting specific data features to contingent brain activity. In this study we recorded electroencephalographic (EEG) data while participants experienced MR scenarios implemented through the eXperience Induction Machine (XIM). The XIM is a novel framework modeling the integration of a sensing system that evaluates and measures physiological and psychological states with a number of actuators and effectors that coherently reacts to the user's actions. We then assessed continuous EEG-based discrimination of spatial navigation, reading and calculation performed in MR, using linear discriminant analysis (LDA) and support vector machine (SVM) classifiers. Dynamic single trial classification showed high accuracy of LDA and SVM classifiers in detecting multiple brain states as well as in differentiating between high and low mental workload, using a 5 s time-window shifting every 200 ms. Our results indicate overall better performance of LDA with respect to SVM and suggest applicability of our approach in a BCI-controlled MR scenario. Ultimately, successful prediction of brain states might be used to drive adaptation of data representation in order to boost information processing in MR.

Fast mental states decoding in mixed reality

PubMed Central

De Massari, Daniele; Pacheco, Daniel; Malekshahi, Rahim; Betella, Alberto; Verschure, Paul F. M. J.; Birbaumer, Niels; Caria, Andrea

2014-01-01

The combination of Brain-Computer Interface (BCI) technology, allowing online monitoring and decoding of brain activity, with virtual and mixed reality (MR) systems may help to shape and guide implicit and explicit learning using ecological scenarios. Real-time information of ongoing brain states acquired through BCI might be exploited for controlling data presentation in virtual environments. Brain states discrimination during mixed reality experience is thus critical for adapting specific data features to contingent brain activity. In this study we recorded electroencephalographic (EEG) data while participants experienced MR scenarios implemented through the eXperience Induction Machine (XIM). The XIM is a novel framework modeling the integration of a sensing system that evaluates and measures physiological and psychological states with a number of actuators and effectors that coherently reacts to the user's actions. We then assessed continuous EEG-based discrimination of spatial navigation, reading and calculation performed in MR, using linear discriminant analysis (LDA) and support vector machine (SVM) classifiers. Dynamic single trial classification showed high accuracy of LDA and SVM classifiers in detecting multiple brain states as well as in differentiating between high and low mental workload, using a 5 s time-window shifting every 200 ms. Our results indicate overall better performance of LDA with respect to SVM and suggest applicability of our approach in a BCI-controlled MR scenario. Ultimately, successful prediction of brain states might be used to drive adaptation of data representation in order to boost information processing in MR. PMID:25505878

Quantitative theory of driven nonlinear brain dynamics.

PubMed

Roberts, J A; Robinson, P A

2012-09-01

Strong periodic stimuli such as bright flashing lights evoke nonlinear responses in the brain and interact nonlinearly with ongoing cortical activity, but the underlying mechanisms for these phenomena are poorly understood at present. The dominant features of these experimentally observed dynamics are reproduced by the dynamics of a quantitative neural field model subject to periodic drive. Model power spectra over a range of drive frequencies show agreement with multiple features of experimental measurements, exhibiting nonlinear effects including entrainment over a range of frequencies around the natural alpha frequency f(α), subharmonic entrainment near 2f(α), and harmonic generation. Further analysis of the driven dynamics as a function of the drive parameters reveals rich nonlinear dynamics that is predicted to be observable in future experiments at high drive amplitude, including period doubling, bistable phase-locking, hysteresis, wave mixing, and chaos indicated by positive Lyapunov exponents. Moreover, photosensitive seizures are predicted for physiologically realistic model parameters yielding bistability between healthy and seizure dynamics. These results demonstrate the applicability of neural field models to the new regime of periodically driven nonlinear dynamics, enabling interpretation of experimental data in terms of specific generating mechanisms and providing new tests of the theory. Copyright © 2012 Elsevier Inc. All rights reserved.

Investigation into the efficacy of generating synthetic pathological oscillations for domain adaptation

NASA Astrophysics Data System (ADS)

Lewis, Rory; Ellenberger, James; Williams, Colton; White, Andrew M.

2013-11-01

In the ongoing investigation of integrating Knowledge Discovery in Databases (KDD) into neuroscience, we present a paper that facilitates overcoming the two challenges preventing this integration. Pathological oscillations found in the human brain are difficult to evaluate because 1) there is often no time to learn and train off of the same distribution in the fatally sick, and 2) sinusoidal signals found in the human brain are complex and transient in nature requiring large data sets to work with which are costly and often very expensive or impossible to acquire. Overcoming these challenges in today's neuro-intensive-care unit (ICU) requires insurmountable resources. For these reasons, optimizing KDD for pathological oscillations so machine learning systems can predict neuropathological states would be of immense value. Domain adaptation, which allows a way of predicting on a separate set of data than the training data, can theoretically overcome the first challenge. However, the challenge of acquiring large data sets that show whether domain adaptation is a good candidate to test in a live neuro ICU remains a challenge. To solve this conundrum, we present a methodology for generating synthesized neuropathological oscillations for domain adaptation.

Gut microbes and the brain: paradigm shift in neuroscience.

PubMed

Mayer, Emeran A; Knight, Rob; Mazmanian, Sarkis K; Cryan, John F; Tillisch, Kirsten

2014-11-12

The discovery of the size and complexity of the human microbiome has resulted in an ongoing reevaluation of many concepts of health and disease, including diseases affecting the CNS. A growing body of preclinical literature has demonstrated bidirectional signaling between the brain and the gut microbiome, involving multiple neurocrine and endocrine signaling mechanisms. While psychological and physical stressors can affect the composition and metabolic activity of the gut microbiota, experimental changes to the gut microbiome can affect emotional behavior and related brain systems. These findings have resulted in speculation that alterations in the gut microbiome may play a pathophysiological role in human brain diseases, including autism spectrum disorder, anxiety, depression, and chronic pain. Ongoing large-scale population-based studies of the gut microbiome and brain imaging studies looking at the effect of gut microbiome modulation on brain responses to emotion-related stimuli are seeking to validate these speculations. This article is a summary of emerging topics covered in a symposium and is not meant to be a comprehensive review of the subject. Copyright © 2014 the authors 0270-6474/14/3415490-07$15.00/0.

TBI Symptoms, Diagnosis, Treatment, Prevention

MedlinePlus

... Bar Home Current Issue Past Issues Cover Story: Traumatic Brain Injury TBI Symptoms, Diagnosis, Treatment, Prevention Past Issues / Fall ... very lucky in my ongoing recovery from the traumatic brain injury I suffered in Iraq." —Bob Woodruff Treatment Immediate ...

Brain-Dead Donors on Extracorporeal Membrane Oxygenation.

PubMed

Bronchard, Régis; Durand, Louise; Legeai, Camille; Cohen, Johana; Guerrini, Patrice; Bastien, Olivier

2017-10-01

To describe donors after brain death with ongoing extracorporeal membrane oxygenation and to analyze the outcome of organs transplanted from these donors. Retrospective analysis of the national information system run by the French Biomedicine Agency (CRISTAL database). National registry data of all donors after brain death in France and their organ recipients between 2007 and 2013. Donors after brain death and their organ recipients. None. During the study period, there were 22,270 brain-dead patients diagnosed in France, of whom 161 with extracorporeal membrane oxygenation. Among these patients, 64 donors on extracorporeal membrane oxygenation and 10,805 donors without extracorporeal membrane oxygenation had at least one organ retrieved. Donors on extracorporeal membrane oxygenation were significantly younger and had more severe intensive care medical conditions (hemodynamic, biological, renal, and liver insults) than donors without extracorporeal membrane oxygenation. One hundred nine kidneys, 37 livers, seven hearts, and one lung were successfully transplanted from donors on extracorporeal membrane oxygenation. We found no significant difference in 1-year kidney graft survival (p = 0.24) and function between recipients from donors on extracorporeal membrane oxygenation (92.7% [85.9-96.3%]) and matching recipients from donors without extracorporeal membrane oxygenation (95.4% [93.0-97.0%]). We also found no significant difference in 1-year liver recipient survival (p = 0.91): 86.5% (70.5-94.1) from donors on extracorporeal membrane oxygenation versus 80.7% (79.8-81.6) from donors without extracorporeal membrane oxygenation. Brain-dead patients with ongoing extracorporeal membrane oxygenation have more severe medical conditions than those without extracorporeal membrane oxygenation. However, kidney graft survival and function were no different than usual. Brain-dead patients with ongoing extracorporeal membrane oxygenation are suitable for organ procurement.

Toward noninvasive monitoring of ongoing electrical activity of human uterus and fetal heart and brain.

PubMed

Lew, S; Hämäläinen, M S; Okada, Y

2017-12-01

To evaluate whether a full-coverage fetal-maternal scanner can noninvasively monitor ongoing electrophysiological activity of maternal and fetal organs. A simulation study was carried out for a scanner with an array of magnetic field sensors placed all around the torso from the chest to the hip within a horizontal magnetic shielding enclosure. The magnetic fields from internal organs and an external noise source were computed for a pregnant woman with a 35-week old fetus. Signal processing methods were used to reject the external and internal interferences, to visualize uterine activity, and to detect activity of fetal heart and brain. External interference was reduced by a factor of 1000, sufficient for detecting signals from internal organs when combined with passive and active shielding. The scanner rejects internal interferences better than partial-coverage arrays. It can be used to estimate currents around the uterus. It clearly detects spontaneous activity from the fetal heart and brain without averaging and weaker evoked brain activity at all fetal head positions after averaging. The simulated device will be able to monitor the ongoing activity of the fetal and maternal organs. This type of scanner may become a novel tool in fetal medicine. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Reducing the Disruptive Effects of Interruptions With Noninvasive Brain Stimulation.

PubMed

Blumberg, Eric J; Foroughi, Cyrus K; Scheldrup, Melissa R; Peterson, Matthew S; Boehm-Davis, Debbie A; Parasuraman, Raja

2015-09-01

The authors determine whether transcranial direct current stimulation (tDCS) can reduce resumption time when an ongoing task is interrupted. Interruptions are common and disruptive. Working memory capacity has been shown to predict resumption lag (i.e., time to successfully resume a task after interruption). Given that tDCS applied to brain areas associated with working memory can enhance performance, tDCS has the potential to improve resumption lag when a task is interrupted. Participants were randomly assigned to one of four groups that received anodal (active) stimulation of 2 mA tDCS to one of two target brain regions, left and right dorsolateral prefrontal cortex (DLPFC), or to one of two control areas, active stimulation of the left primary motor cortex or sham stimulation of the right DLPFC, while completing a financial management task that was intermittently interrupted with math problem solving. Anodal stimulation to the right and left DLPFC significantly reduced resumption lags compared to the control conditions (sham and left motor cortex stimulation). Additionally, there was no speed-accuracy tradeoff (i.e., the improvement in resumption time was not accompanied by an increased error rate). Noninvasive brain stimulation can significantly decrease resumption lag (improve performance) after a task is interrupted. Noninvasive brain stimulation offers an easy-to-apply tool that can significantly improve interrupted task performance. © 2014, Human Factors and Ergonomics Society.

Spaceflight Effects on Neurocognitive Performance: Extent, Longevity and Neural Bases

NASA Technical Reports Server (NTRS)

Seidler, R. D.; Mulavara, A. P.; Koppelmans, V.; Kofman, I. S.; Cassady, K.; Yuan, P.; De Dios, Y. E.; Gadd, N.; Riascos, R. F.; Wood, S. J.;

AAV viral vector delivery to the brain by shape-conforming MR-guided infusions.

PubMed

Bankiewicz, Krystof S; Sudhakar, Vivek; Samaranch, Lluis; San Sebastian, Waldy; Bringas, John; Forsayeth, John

2016-10-28

Gene transfer technology offers great promise as a potential therapeutic approach to the brain but has to be viewed as a very complex technology. Success of ongoing clinical gene therapy trials depends on many factors such as selection of the correct genetic and anatomical target in the brain. In addition, selection of the viral vector capable of transfer of therapeutic gene into target cells, along with long-term expression that avoids immunotoxicity has to be established. As with any drug development strategy, delivery of gene therapy has to be consistent and predictable in each study subject. Failed drug and vector delivery will lead to failed clinical trials. In this article, we describe our experience with AAV viral vector delivery system, that allows us to optimize and monitor in real time viral vector administration into affected regions of the brain. In addition to discussing MRI-guided technology for administration of AAV vectors we have developed and now employ in current clinical trials, we also describe ways in which infusion cannula design and stereotactic trajectory may be used to maximize the anatomical coverage by using fluid backflow. This innovative approach enables more precise coverage by fitting the shape of the infusion to the shape of the anatomical target. Copyright © 2016 Elsevier B.V. All rights reserved.

Global integration of the hot-state brain network of appetite predicts short term weight loss in older adult.

PubMed

Paolini, Brielle M; Laurienti, Paul J; Simpson, Sean L; Burdette, Jonathan H; Lyday, Robert G; Rejeski, W Jack

2015-01-01

Obesity is a public health crisis in North America. While lifestyle interventions for weight loss (WL) remain popular, the rate of success is highly variable. Clearly, self-regulation of eating behavior is a challenge and patterns of activity across the brain may be an important determinant of success. The current study prospectively examined whether integration across the Hot-State Brain Network of Appetite (HBN-A) predicts WL after 6-months of treatment in older adults. Our metric for network integration was global efficiency (GE). The present work is a sub-study (n = 56) of an ongoing randomized clinical trial involving WL. Imaging involved a baseline food-cue visualization functional MRI (fMRI) scan following an overnight fast. Using graph theory to build functional brain networks, we demonstrated that regions of the HBN-A (insula, anterior cingulate cortex (ACC), superior temporal pole (STP), amygdala and the parahippocampal gyrus) were highly integrated as evidenced by the results of a principal component analysis (PCA). After accounting for known correlates of WL (baseline weight, age, sex, and self-regulatory efficacy) and treatment condition, which together contributed 36.9% of the variance in WL, greater GE in the HBN-A was associated with an additional 19% of the variance. The ACC of the HBN-A was the primary driver of this effect, accounting for 14.5% of the variance in WL when entered in a stepwise regression following the covariates, p = 0.0001. The HBN-A is comprised of limbic regions important in the processing of emotions and visceral sensations and the ACC is key for translating such processing into behavioral consequences. The improved integration of these regions may enhance awareness of body and emotional states leading to more successful self-regulation and to greater WL. This is the first study among older adults to prospectively demonstrate that, following an overnight fast, GE of the HBN-A during a food visualization task is predictive of WL.

A preliminary study of the effects of working memory training on brain function.

PubMed

Stevens, Michael C; Gaynor, Alexandra; Bessette, Katie L; Pearlson, Godfrey D

2016-06-01

Working memory (WM) training improves WM ability in Attention-Deficit/Hyperactivity Disorder (ADHD), but its efficacy for non-cognitive ADHD impairments ADHD has been sharply debated. The purpose of this preliminary study was to characterize WM training-related changes in ADHD brain function and see if they were linked to clinical improvement. We examined 18 adolescents diagnosed with DSM-IV Combined-subtype ADHD before and after 25 sessions of WM training using a frequently employed approach (Cogmed™) using a nonverbal Sternberg WM fMRI task, neuropsychological tests, and participant- and parent-reports of ADHD symptom severity and associated functional impairment. Whole brain SPM8 analyses identified ADHD activation deficits compared to 18 non-ADHD control participants, then tested whether impaired ADHD frontoparietal brain activation would increase following WM training. Post hoc tests examined the relationships between neural changes and neurocognitive or clinical improvements. As predicted, WM training increased WM performance, ADHD clinical functioning, and WM-related ADHD brain activity in several frontal, parietal and temporal lobe regions. Increased left inferior frontal sulcus region activity was seen in all Encoding, Maintenance, and Retrieval Sternberg task phases. ADHD symptom severity improvements were most often positively correlated with activation gains in brain regions known to be engaged for WM-related executive processing; improvement of different symptom types had different neural correlates. The responsiveness of both amodal WM frontoparietal circuits and executive process-specific WM brain regions was altered by WM training. The latter might represent a promising, relatively unexplored treatment target for researchers seeking to optimize clinical response in ongoing ADHD WM training development efforts.

A Case Study on the Professional Development of Elementary Teachers Related to Brain Research and the Strategies Used to Help Struggling Readers

ERIC Educational Resources Information Center

Denton, Valerie R.

2010-01-01

This case study examined the impact of classroom interventions for struggling readers as changed/improved by teachers who participated in ongoing professional development on brain research studies. It investigated how teachers' knowledge of brain research impacted their instruction and the interventions they implemented in elementary classrooms.…

[Digital electroencephalography in brain death diagnostics : Technical requirements and results of a survey on the compatibility with medical guidelines of digital EEG systems from providers in Germany].

PubMed

Walter, U; Noachtar, S; Hinrichs, H

2018-02-01

The guidelines of the German Medical Association and the German Society for Clinical Neurophysiology and Functional Imaging (DGKN) require a high procedural and technical standard for electroencephalography (EEG) as an ancillary method for diagnosing the irreversible cessation of brain function (brain death). Nowadays, digital EEG systems are increasingly being applied in hospitals. So far it is unclear to what extent the digital EEG systems currently marketed in Germany meet the guidelines for diagnosing brain death. In the present article, the technical und safety-related requirements for digital EEG systems and the EEG documentation for diagnosing brain death are described in detail. On behalf of the DGKN, the authors sent out a questionnaire to all identified distributors of digital EEG systems in Germany with respect to the following technical demands: repeated recording of the calibration signals during an ongoing EEG recording, repeated recording of all electrode impedances during an ongoing EEG recording, assessability of intrasystem noise and galvanic isolation of measurement earthing from earthing conductor (floating input). For 15 of the identified 20 different digital EEG systems the specifications were provided by the distributors (among them all distributors based in Germany). All of these EEG systems are provided with a galvanic isolation (floating input). The internal noise can be tested with all systems; however, some systems do not allow repeated recording of the calibration signals and/or the electrode impedances during an ongoing EEG recording. The majority but not all of the currently available digital EEG systems offered for clinical use are eligible for use in brain death diagnostics as per German guidelines.

Phase-Locked Loop for Precisely Timed Acoustic Stimulation during Sleep

PubMed Central

Santostasi, Giovanni; Malkani, Roneil; Riedner, Brady; Bellesi, Michele; Tononi, Giulio; Paller, Ken A.; Zee, Phyllis C.

2016-01-01

Background A Brain-Computer Interface could potentially enhance the various benefits of sleep. New Method We describe a strategy for enhancing slow-wave sleep (SWS) by stimulating the sleeping brain with periodic acoustic stimuli that produce resonance in the form of enhanced slow-wave activity in the electroencephalogram (EEG). The system delivers each acoustic stimulus at a particular phase of an electrophysiological rhythm using a Phase-Locked Loop (PLL). Results The PLL is computationally economical and well suited to follow and predict the temporal behavior of the EEG during slow-wave sleep. Comparison with Existing Methods Acoustic stimulation methods may be able to enhance SWS without the risks inherent in electrical stimulation or pharmacological methods. The PLL method differs from other acoustic stimulation methods that are based on detecting a single slow wave rather than modeling slow-wave activity over an extended period of time. Conclusions By providing real-time estimates of the phase of ongoing EEG oscillations, the PLL can rapidly adjust to physiological changes, thus opening up new possibilities to study brain dynamics during sleep. Future application of these methods hold promise for enhancing sleep quality and associated daytime behavior and improving physiologic function. PMID:26617321

The Protective Action Encoding of Serotonin Transients in the Human Brain.

PubMed

Moran, Rosalyn J; Kishida, Kenneth T; Lohrenz, Terry; Saez, Ignacio; Laxton, Adrian W; Witcher, Mark R; Tatter, Stephen B; Ellis, Thomas L; Phillips, Paul Em; Dayan, Peter; Montague, P Read

2018-05-01

The role of serotonin in human brain function remains elusive due, at least in part, to our inability to measure rapidly the local concentration of this neurotransmitter. We used fast-scan cyclic voltammetry to infer serotonergic signaling from the striatum of 14 brains of human patients with Parkinson's disease. Here we report these novel measurements and show that they correlate with outcomes and decisions in a sequential investment game. We find that serotonergic concentrations transiently increase as a whole following negative reward prediction errors, while reversing when counterfactual losses predominate. This provides initial evidence that the serotonergic system acts as an opponent to dopamine signaling, as anticipated by theoretical models. Serotonin transients on one trial were also associated with actions on the next trial in a manner that correlated with decreased exposure to poor outcomes. Thus, the fluctuations observed for serotonin appear to correlate with the inhibition of over-reactions and promote persistence of ongoing strategies in the face of short-term environmental changes. Together these findings elucidate a role for serotonin in the striatum, suggesting it encodes a protective action strategy that mitigates risk and modulates choice selection particularly following negative environmental events.

Is the Brain a Quantum Computer?

ERIC Educational Resources Information Center

Litt, Abninder; Eliasmith, Chris; Kroon, Frederick W.; Weinstein, Steven; Thagard, Paul

2006-01-01

We argue that computation via quantum mechanical processes is irrelevant to explaining how brains produce thought, contrary to the ongoing speculations of many theorists. First, quantum effects do not have the temporal properties required for neural information processing. Second, there are substantial physical obstacles to any organic…

Challenges associated with post-deployment screening for mild traumatic brain injury in military personnel.

PubMed

Iverson, Grant L; Langlois, Jean A; McCrea, Michael A; Kelly, James P

2009-11-01

There is ongoing debate regarding the epidemiology of mild traumatic brain injury (MTBI) in military personnel. Accurate and timely estimates of the incidence of brain injury and the prevalence of long-term problems associated with brain injuries among active duty service members and veterans are essential for (a) operational planning, and (b) to allocate sufficient resources for rehabilitation and ongoing services and supports. The purpose of this article is to discuss challenges associated with post-deployment screening for MTBI. Multiple screening methods have been used in military, Veterans Affairs, and independent studies, which complicate cross-study comparisons of the resulting epidemiological data. We believe that post-deployment screening is important and necessary--but no screening methodology will be flawless, and false positives and false negatives are inevitable. Additional research is necessary to refine the sequential screening methodology, with the goal of minimizing false negatives during initial post-deployment screening and minimizing false positives during follow-up evaluations.

10-Month-Old Infants Are Sensitive to the Time Course of Perceived Actions: Eye-Tracking and EEG Evidence.

PubMed

Bache, Cathleen; Springer, Anne; Noack, Hannes; Stadler, Waltraud; Kopp, Franziska; Lindenberger, Ulman; Werkle-Bergner, Markus

2017-01-01

Research has shown that infants are able to track a moving target efficiently - even if it is transiently occluded from sight. This basic ability allows prediction of when and where events happen in everyday life. Yet, it is unclear whether, and how, infants internally represent the time course of ongoing movements to derive predictions. In this study, 10-month-old crawlers observed the video of a same-aged crawling baby that was transiently occluded and reappeared in either a temporally continuous or non-continuous manner (i.e., delayed by 500 ms vs. forwarded by 500 ms relative to the real-time movement). Eye movement and rhythmic neural brain activity (EEG) were measured simultaneously. Eye movement analyses showed that infants were sensitive to slight temporal shifts in movement continuation after occlusion. Furthermore, brain activity associated with sensorimotor processing differed between observation of continuous and non-continuous movements. Early sensitivity to an action's timing may hence be explained within the internal real-time simulation account of action observation. Overall, the results support the hypothesis that 10-month-old infants are well prepared for internal representation of the time course of observed movements that are within the infants' current motor repertoire.

10-Month-Old Infants Are Sensitive to the Time Course of Perceived Actions: Eye-Tracking and EEG Evidence

PubMed Central

Bache, Cathleen; Springer, Anne; Noack, Hannes; Stadler, Waltraud; Kopp, Franziska; Lindenberger, Ulman; Werkle-Bergner, Markus

2017-01-01

Research has shown that infants are able to track a moving target efficiently – even if it is transiently occluded from sight. This basic ability allows prediction of when and where events happen in everyday life. Yet, it is unclear whether, and how, infants internally represent the time course of ongoing movements to derive predictions. In this study, 10-month-old crawlers observed the video of a same-aged crawling baby that was transiently occluded and reappeared in either a temporally continuous or non-continuous manner (i.e., delayed by 500 ms vs. forwarded by 500 ms relative to the real-time movement). Eye movement and rhythmic neural brain activity (EEG) were measured simultaneously. Eye movement analyses showed that infants were sensitive to slight temporal shifts in movement continuation after occlusion. Furthermore, brain activity associated with sensorimotor processing differed between observation of continuous and non-continuous movements. Early sensitivity to an action’s timing may hence be explained within the internal real-time simulation account of action observation. Overall, the results support the hypothesis that 10-month-old infants are well prepared for internal representation of the time course of observed movements that are within the infants’ current motor repertoire. PMID:28769831

Comprehension of Idioms in Turkish Aphasic Participants

ERIC Educational Resources Information Center

Aydin, Burcu; Barin, Muzaffer; Yagiz, Oktay

2017-01-01

Brain damaged participants offer an opportunity to evaluate the cognitive and linguistic processes and make assumptions about how the brain works. Cognitive linguists have been investigating the underlying mechanisms of idiom comprehension to unravel the ongoing debate on hemispheric specialization in figurative language comprehension. The aim of…

Neuroscience in Schools

ERIC Educational Resources Information Center

Schachter, Ron

2012-01-01

For generations, teachers in the early elementary years have urged their young pupils to use their brains. They're still offering the same encouragement, but nowadays they can know even more about what they're talking about. Recent advances in neuroscience--from detailed scans of the brain to ongoing research on teaching methods that increase…

State-Dependent Decoding Algorithms Improve the Performance of a Bidirectional BMI in Anesthetized Rats.

PubMed

De Feo, Vito; Boi, Fabio; Safaai, Houman; Onken, Arno; Panzeri, Stefano; Vato, Alessandro

2017-01-01

Brain-machine interfaces (BMIs) promise to improve the quality of life of patients suffering from sensory and motor disabilities by creating a direct communication channel between the brain and the external world. Yet, their performance is currently limited by the relatively small amount of information that can be decoded from neural activity recorded form the brain. We have recently proposed that such decoding performance may be improved when using state-dependent decoding algorithms that predict and discount the large component of the trial-to-trial variability of neural activity which is due to the dependence of neural responses on the network's current internal state. Here we tested this idea by using a bidirectional BMI to investigate the gain in performance arising from using a state-dependent decoding algorithm. This BMI, implemented in anesthetized rats, controlled the movement of a dynamical system using neural activity decoded from motor cortex and fed back to the brain the dynamical system's position by electrically microstimulating somatosensory cortex. We found that using state-dependent algorithms that tracked the dynamics of ongoing activity led to an increase in the amount of information extracted form neural activity by 22%, with a consequently increase in all of the indices measuring the BMI's performance in controlling the dynamical system. This suggests that state-dependent decoding algorithms may be used to enhance BMIs at moderate computational cost.

A preliminary study of the effects of working memory training on brain function in Attention-Deficit/Hyperactivity Disorder

PubMed Central

Stevens, Michael C.; Gaynor, Alexandra; Bessette, Katie L.; Pearlson, Godfrey D.

2015-01-01

Working memory (WM) training improves WM ability in Attention-Deficit/Hyperactivity Disorder (ADHD), but its efficacy for non-cognitive ADHD impairments ADHD has been sharply debated. The purpose of this preliminary study was to characterize WM training-related changes in ADHD brain function and see if they were linked to clinical improvement. We examined 18 adolescents diagnosed with DSM-IV Combined-subtype ADHD before and after 25 sessions of WM training using a frequently employed approach (CogmedTM) using a nonverbal Sternberg WM fMRI task, neuropsychological tests, and participant- and parent-reports of ADHD symptom severity and associated functional impairment. Whole brain SPM8 analyses identified ADHD activation deficits compared to 18 non-ADHD control participants, then tested whether impaired ADHD frontoparietal brain activation would increase following WM training. Post hoc tests examined the relationships between neural changes and neurocognitive or clinical improvements. As predicted, WM training increased WM performance, ADHD clinical functioning, and WM-related ADHD brain activity in several frontal, parietal and temporal lobe regions. Increased left inferior frontal sulcus region activity was seen in all Encoding, Maintenance, and Retrieval Sternberg task phases. ADHD symptom severity improvements were most often positively correlated with activation gains in brain regions known to be engaged for WM-related executive processing; improvement of different symptom types had different neural correlates. The responsiveness of both amodal WM frontoparietal circuits and executive process-specific WM brain regions was altered by WM training. The latter might represent a promising, relatively unexplored treatment target for researchers seeking to optimize clinical response in ongoing ADHD WM training development efforts. PMID:26138580

Development of In Vivo Biomarkers for Progressive Tau Pathology after Traumatic Brain Injury

DTIC Science & Technology

2015-02-01

distribution unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT Athletes in contact sports who have sustained multiple concussive traumatic brain...who have sustained multiple concussive traumatic brain injuries 15-17 may also be at risk for this condition. Currently, there are no methods to...repetitive concussive TBI in mice has been optimal. Ongoing efforts include development of more sensitive methods to detect tau, and combinations of

The influence of visual training on predicting complex action sequences.

PubMed

Cross, Emily S; Stadler, Waltraud; Parkinson, Jim; Schütz-Bosbach, Simone; Prinz, Wolfgang

2013-02-01

Linking observed and executable actions appears to be achieved by an action observation network (AON), comprising parietal, premotor, and occipitotemporal cortical regions of the human brain. AON engagement during action observation is thought to aid in effortless, efficient prediction of ongoing movements to support action understanding. Here, we investigate how the AON responds when observing and predicting actions we cannot readily reproduce before and after visual training. During pre- and posttraining neuroimaging sessions, participants watched gymnasts and wind-up toys moving behind an occluder and pressed a button when they expected each agent to reappear. Between scanning sessions, participants visually trained to predict when a subset of stimuli would reappear. Posttraining scanning revealed activation of inferior parietal, superior temporal, and cerebellar cortices when predicting occluded actions compared to perceiving them. Greater activity emerged when predicting untrained compared to trained sequences in occipitotemporal cortices and to a lesser degree, premotor cortices. The occipitotemporal responses when predicting untrained agents showed further specialization, with greater responses within body-processing regions when predicting gymnasts' movements and in object-selective cortex when predicting toys' movements. The results suggest that (1) select portions of the AON are recruited to predict the complex movements not easily mapped onto the observer's body and (2) greater recruitment of these AON regions supports prediction of less familiar sequences. We suggest that the findings inform both the premotor model of action prediction and the predictive coding account of AON function. Copyright © 2011 Wiley Periodicals, Inc.

A Role for New Brain Magnetic Resonance Imaging Modalities in Daily Clinical Practice: Protocol of the Prediction of Cognitive Recovery After Stroke (PROCRAS) Study.

PubMed

Aben, Hugo P; Reijmer, Yael D; Visser-Meily, Johanna Ma; Spikman, Jacoba M; de Bresser, Jeroen; Biessels, Geert Jan; de Kort, Paul Lm

2018-05-28

Cognitive impairment is common after acute ischemic stroke, affecting up to 75% of the patients. About half of the patients will show recovery, whereas the others will remain cognitively impaired or deteriorate. It is difficult to predict these different cognitive outcomes. The objective of this study is to investigate whether diffusion tensor imaging-based measures of brain connectivity predict cognitive recovery after 1 year, in addition to patient characteristics and stroke severity. A specific premise of the Prediction of Cognitive Recovery After Stroke (PROCRAS) study is that it is conducted in a daily practice setting. The PROCRAS study is a prospective, mono-center cohort study conducted in a large teaching hospital in the Netherlands. A total of 350 patients suffering from an ischemic stroke who screen positive for cognitive impairment on the Montreal Cognitive Assessment (MoCA<26) in the acute stage will undergo a 3Tesla-Magnetic Resonance Imaging (3T-MRI) with a diffusion-weighted sequence and a neuropsychological assessment. Patients will be classified as being unimpaired, as having a mild vascular cognitive disorder, or as having a major vascular cognitive disorder. One year after stroke, patients will undergo follow-up neuropsychological assessment. The primary endpoint is recovery of cognitive function 1 year after stroke in patients with a confirmed poststroke cognitive disorder. The secondary endpoint is deterioration of cognitive function in the first year after stroke. The study is already ongoing for 1.5 years, and thus far, 252 patients have provided written informed consent. Final results are expected in June 2019. The PROCRAS study will show the additional predictive value of diffusion tensor imaging-based measures of brain connectivity for cognitive outcome at 1 year in patients with a poststroke cognitive disorder in a daily clinical practice setting. RR1-10.2196/9431. ©Hugo P Aben, Yael D Reijmer, Johanna MA Visser-Meily, Jacoba M Spikman, Jeroen de Bresser, Geert Jan Biessels, Paul LM de Kort. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 28.05.2018.

Spontaneous pre-stimulus fluctuations in the activity of right fronto-parietal areas influence inhibitory control performance

PubMed Central

Chavan, Camille F.; Manuel, Aurelie L.; Mouthon, Michael; Spierer, Lucas

2013-01-01

Inhibitory control refers to the ability to suppress planned or ongoing cognitive or motor processes. Electrophysiological indices of inhibitory control failure have been found to manifest even before the presentation of the stimuli triggering the inhibition, suggesting that pre-stimulus brain-states modulate inhibition performance. However, previous electrophysiological investigations on the state-dependency of inhibitory control were based on averaged event-related potentials (ERPs), a method eliminating the variability in the ongoing brain activity not time-locked to the event of interest. These studies thus left unresolved whether spontaneous variations in the brain-state immediately preceding unpredictable inhibition-triggering stimuli also influence inhibitory control performance. To address this question, we applied single-trial EEG topographic analyses on the time interval immediately preceding NoGo stimuli in conditions where the responses to NoGo trials were correctly inhibited [correct rejection (CR)] vs. committed [false alarms (FAs)] during an auditory spatial Go/NoGo task. We found a specific configuration of the EEG voltage field manifesting more frequently before correctly inhibited responses to NoGo stimuli than before FAs. There was no evidence for an EEG topography occurring more frequently before FAs than before CR. The visualization of distributed electrical source estimations of the EEG topography preceding successful response inhibition suggested that it resulted from the activity of a right fronto-parietal brain network. Our results suggest that the fluctuations in the ongoing brain activity immediately preceding stimulus presentation contribute to the behavioral outcomes during an inhibitory control task. Our results further suggest that the state-dependency of sensory-cognitive processing might not only concern perceptual processes, but also high-order, top-down inhibitory control mechanisms. PMID:23761747

Predictive Coding or Evidence Accumulation? False Inference and Neuronal Fluctuations

PubMed Central

Friston, Karl J.; Kleinschmidt, Andreas

2010-01-01

Perceptual decisions can be made when sensory input affords an inference about what generated that input. Here, we report findings from two independent perceptual experiments conducted during functional magnetic resonance imaging (fMRI) with a sparse event-related design. The first experiment, in the visual modality, involved forced-choice discrimination of coherence in random dot kinematograms that contained either subliminal or periliminal motion coherence. The second experiment, in the auditory domain, involved free response detection of (non-semantic) near-threshold acoustic stimuli. We analysed fluctuations in ongoing neural activity, as indexed by fMRI, and found that neuronal activity in sensory areas (extrastriate visual and early auditory cortex) biases perceptual decisions towards correct inference and not towards a specific percept. Hits (detection of near-threshold stimuli) were preceded by significantly higher activity than both misses of identical stimuli or false alarms, in which percepts arise in the absence of appropriate sensory input. In accord with predictive coding models and the free-energy principle, this observation suggests that cortical activity in sensory brain areas reflects the precision of prediction errors and not just the sensory evidence or prediction errors per se. PMID:20369004

Cannabis Use and Memory Brain Function in Adolescent Boys: A Cross-Sectional Multicenter Functional Magnetic Resonance Imaging Study

ERIC Educational Resources Information Center

Jager, Gerry; Block, Robert I.; Luijten, Maartje; Ramsey, Nick F.

2010-01-01

Objective: Early-onset cannabis use has been associated with later use/abuse, mental health problems (psychosis, depression), and abnormal development of cognition and brain function. During adolescence, ongoing neurodevelopmental maturation and experience shape the neural circuitry underlying complex cognitive functions such as memory and…

Opaque for the Reader but Transparent for the Brain: Neural Signatures of Morphological Complexity

ERIC Educational Resources Information Center

Meinzer, Marcus; Lahiri, Aditi; Flaisch, Tobias; Hannemann, Ronny; Eulitz, Carsten

2009-01-01

Within linguistics, words with a complex internal structure are commonly assumed to be decomposed into their constituent morphemes (e.g., un-help-ful). Nevertheless, an ongoing debate concerns the brain structures that subserve this process. Using functional magnetic resonance imaging, the present study varied the internal complexity of derived…

Incorporating virtual reality graphics with brain imaging for assessment of sport-related concussions.

PubMed

Slobounov, Semyon; Sebastianelli, Wayne; Newell, Karl M

2011-01-01

There is a growing concern that traditional neuropsychological (NP) testing tools are not sensitive to detecting residual brain dysfunctions in subjects suffering from mild traumatic brain injuries (MTBI). Moreover, most MTBI patients are asymptomatic based on anatomical brain imaging (CT, MRI), neurological examinations and patients' subjective reports within 10 days post-injury. Our ongoing research has documented that residual balance and visual-kinesthetic dysfunctions along with its underlying alterations of neural substrates may be detected in "asymptomatic subjects" by means of Virtual Reality (VR) graphics incorporated with brain imaging (EEG) techniques.

Development of in Vivo Biomarkers for Progressive Tau Pathology after Traumatic Brain Injury

DTIC Science & Technology

2015-02-01

Athletes in contact sports who have sustained multiple concussive traumatic brain injuries are at high risk for delayed, progressive neurological and...11 or ‘punch drunk’ syndrome 9, 12. US military personnel 13, 14 and others who have sustained multiple concussive traumatic brain injuries 15-17...To date, none of the attempts to model progressive tau pathology after repetitive concussive TBI in mice has been optimal. Ongoing efforts include

Development of in Vivo Biomarkers for Progressive Tau Pathology after Traumatic Brain Injury

DTIC Science & Technology

2016-02-01

14. ABSTRACT Athletes in contact sports who have sustained multiple concussive traumatic brain injuries are at high risk for delayed, progressive...pugilistica 3, 11 or ‘punch drunk’ syndrome 9, 12. US military personnel 13, 14 and others who have sustained multiple concussive traumatic brain...Progress to date: To date, none of the attempts to model progressive tau pathology after repetitive concussive TBI in mice has been optimal. Ongoing

Using Brain–Computer Interfaces and Brain-State Dependent Stimulation as Tools in Cognitive Neuroscience

PubMed Central

Jensen, Ole; Bahramisharif, Ali; Oostenveld, Robert; Klanke, Stefan; Hadjipapas, Avgis; Okazaki, Yuka O.; van Gerven, Marcel A. J.

2011-01-01

Large efforts are currently being made to develop and improve online analysis of brain activity which can be used, e.g., for brain–computer interfacing (BCI). A BCI allows a subject to control a device by willfully changing his/her own brain activity. BCI therefore holds the promise as a tool for aiding the disabled and for augmenting human performance. While technical developments obviously are important, we will here argue that new insight gained from cognitive neuroscience can be used to identify signatures of neural activation which reliably can be modulated by the subject at will. This review will focus mainly on oscillatory activity in the alpha band which is strongly modulated by changes in covert attention. Besides developing BCIs for their traditional purpose, they might also be used as a research tool for cognitive neuroscience. There is currently a strong interest in how brain-state fluctuations impact cognition. These state fluctuations are partly reflected by ongoing oscillatory activity. The functional role of the brain state can be investigated by introducing stimuli in real-time to subjects depending on the actual state of the brain. This principle of brain-state dependent stimulation may also be used as a practical tool for augmenting human behavior. In conclusion, new approaches based on online analysis of ongoing brain activity are currently in rapid development. These approaches are amongst others informed by new insight gained from electroencephalography/magnetoencephalography studies in cognitive neuroscience and hold the promise of providing new ways for investigating the brain at work. PMID:21687463

Primary Auditory Cortex is Required for Anticipatory Motor Response.

PubMed

Li, Jingcheng; Liao, Xiang; Zhang, Jianxiong; Wang, Meng; Yang, Nian; Zhang, Jun; Lv, Guanghui; Li, Haohong; Lu, Jian; Ding, Ran; Li, Xingyi; Guang, Yu; Yang, Zhiqi; Qin, Han; Jin, Wenjun; Zhang, Kuan; He, Chao; Jia, Hongbo; Zeng, Shaoqun; Hu, Zhian; Nelken, Israel; Chen, Xiaowei

2017-06-01

The ability of the brain to predict future events based on the pattern of recent sensory experience is critical for guiding animal's behavior. Neocortical circuits for ongoing processing of sensory stimuli are extensively studied, but their contributions to the anticipation of upcoming sensory stimuli remain less understood. We, therefore, used in vivo cellular imaging and fiber photometry to record mouse primary auditory cortex to elucidate its role in processing anticipated stimulation. We found neuronal ensembles in layers 2/3, 4, and 5 which were activated in relationship to anticipated sound events following rhythmic stimulation. These neuronal activities correlated with the occurrence of anticipatory motor responses in an auditory learning task. Optogenetic manipulation experiments revealed an essential role of such neuronal activities in producing the anticipatory behavior. These results strongly suggest that the neural circuits of primary sensory cortex are critical for coding predictive information and transforming it into anticipatory motor behavior. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Restoring Behavior via Inverse Neurocontroller in a Lesioned Cortical Spiking Model Driving a Virtual Arm

PubMed Central

Dura-Bernal, Salvador; Li, Kan; Neymotin, Samuel A.; Francis, Joseph T.; Principe, Jose C.; Lytton, William W.

2016-01-01

Neural stimulation can be used as a tool to elicit natural sensations or behaviors by modulating neural activity. This can be potentially used to mitigate the damage of brain lesions or neural disorders. However, in order to obtain the optimal stimulation sequences, it is necessary to develop neural control methods, for example by constructing an inverse model of the target system. For real brains, this can be very challenging, and often unfeasible, as it requires repeatedly stimulating the neural system to obtain enough probing data, and depends on an unwarranted assumption of stationarity. By contrast, detailed brain simulations may provide an alternative testbed for understanding the interactions between ongoing neural activity and external stimulation. Unlike real brains, the artificial system can be probed extensively and precisely, and detailed output information is readily available. Here we employed a spiking network model of sensorimotor cortex trained to drive a realistic virtual musculoskeletal arm to reach a target. The network was then perturbed, in order to simulate a lesion, by either silencing neurons or removing synaptic connections. All lesions led to significant behvaioral impairments during the reaching task. The remaining cells were then systematically probed with a set of single and multiple-cell stimulations, and results were used to build an inverse model of the neural system. The inverse model was constructed using a kernel adaptive filtering method, and was used to predict the neural stimulation pattern required to recover the pre-lesion neural activity. Applying the derived neurostimulation to the lesioned network improved the reaching behavior performance. This work proposes a novel neurocontrol method, and provides theoretical groundwork on the use biomimetic brain models to develop and evaluate neurocontrollers that restore the function of damaged brain regions and the corresponding motor behaviors. PMID:26903796

The Effects of Spaceflight and a Spaceflight Analog on Neurocognitive Perfonnance: Extent, Longevity, and Neural Bases

NASA Technical Reports Server (NTRS)

Seidler, R. D.; Mulavara, A. P.; Koppelmans, V.; Erdeniz, B.; Kofman, I. S.; DeDios, Y. E.; Szecsy, D. L.; Riascos-Castaneda, R. F.; Wood, S. J.; Bloomberg, J. J.

2014-01-01

We are conducting ongoing experiments in which we are performing structural and functional magnetic resonance brain imaging to identify the relationships between changes in neurocognitive function and neural structural alterations following a six month International Space Station mission and following 70 days exposure to a spaceflight analog, head down tilt bedrest. Our central hypothesis is that measures of brain structure, function, and network integrity will change from pre to post intervention (spaceflight, bedrest). Moreover, we predict that these changes will correlate with indices of cognitive, sensory, and motor function in a neuroanatomically selective fashion. Our interdisciplinary approach utilizes cutting edge neuroimaging techniques and a broad ranging battery of sensory, motor, and cognitive assessments that will be conducted pre flight, during flight, and post flight to investigate potential neuroplastic and maladaptive brain changes in crewmembers following long-duration spaceflight. Success in this endeavor would 1) result in identification of the underlying neural mechanisms and operational risks of spaceflight-induced changes in behavior, and 2) identify whether a return to normative behavioral function following re-adaptation to Earth's gravitational environment is associated with a restitution of brain structure and function or instead is supported by substitution with compensatory brain processes. With the bedrest study, we will be able to determine the neural and neurocognitive effects of extended duration unloading, reduced sensory inputs, and increased cephalic fluid distribution. This will enable us to parse out the multiple mechanisms contributing to any spaceflight-induced neural structural and behavioral changes that we observe in the flight study. In this presentation I will discuss preliminary results from six participants who have undergone the bed rest protocol. These individuals show decrements in balance and functional mobility, and alterations in brain structure and function, in association with extended bed rest.

Brain Hemispheric Consensus and the Quality of Investment Decisions.

ERIC Educational Resources Information Center

Boyd, Michael

This on-going study explores the hypothesis that stock fund managers who underperform do so because they make bad decisions, and examines whether their choices can be improved by using a decision model that invokes principles of brain hemispheric consensus. The study, begun in fall 1999, involves two groups of business students: the control group…

"She Was a Little Social Butterfly": A Qualitative Analysis of Parent Perception of Social Functioning in Adolescent and Young Adult Brain Tumor Survivors.

PubMed

Wilford, Justin; Buchbinder, David; Fortier, Michelle A; Osann, Kathryn; Shen, Violet; Torno, Lilibeth; Sender, Leonard S; Parsons, Susan K; Wenzel, Lari

Psychosocial sequelae of diagnosis and treatment for childhood brain tumor survivors are significant, yet little is known about their impact on adolescent and young adult (AYA) brain tumor survivors. Interviews were conducted with parents of AYA brain tumor survivors with a focus on social functioning. Semistructured interviews were conducted with English- and Spanish-speaking parents of AYA brain tumor survivors ≥10 years of age who were >2 years postdiagnosis, and analyzed using emergent themes theoretically integrated with a social neuroscience model of social competence. Twenty parents representing 19 survivors with a survivor mean age 15.7 ± 3.3 years and 10.1 ± 4.8 years postdiagnosis were interviewed. Several themes relevant to the social neuroscience social competence model emerged. First, parents' perceptions of their children's impaired social functioning corroborated the model, particularly with regard to poor social adjustment, social withdrawal, impaired social information processing, and developmentally inappropriate peer communication. Second, ongoing physical and emotional sequelae of central nervous system insults were seen by parents as adversely affecting social functioning among survivors. Third, a disrupted family environment and ongoing parent psychosocial distress were experienced as salient features of daily life. We document that the aforementioned framework is useful for understanding the social impact of diagnosis and treatment on AYA brain tumor survivorship. Moreover, the framework highlights areas of intervention that may enhance social functioning for AYA brain tumor survivors.

Sensorimotor learning in children and adults: Exposure to frequency-altered auditory feedback during speech production.

PubMed

Scheerer, N E; Jacobson, D S; Jones, J A

2016-02-09

Auditory feedback plays an important role in the acquisition of fluent speech; however, this role may change once speech is acquired and individuals no longer experience persistent developmental changes to the brain and vocal tract. For this reason, we investigated whether the role of auditory feedback in sensorimotor learning differs across children and adult speakers. Participants produced vocalizations while they heard their vocal pitch predictably or unpredictably shifted downward one semitone. The participants' vocal pitches were measured at the beginning of each vocalization, before auditory feedback was available, to assess the extent to which the deviant auditory feedback modified subsequent speech motor commands. Sensorimotor learning was observed in both children and adults, with participants' initial vocal pitch increasing following trials where they were exposed to predictable, but not unpredictable, frequency-altered feedback. Participants' vocal pitch was also measured across each vocalization, to index the extent to which the deviant auditory feedback was used to modify ongoing vocalizations. While both children and adults were found to increase their vocal pitch following predictable and unpredictable changes to their auditory feedback, adults produced larger compensatory responses. The results of the current study demonstrate that both children and adults rapidly integrate information derived from their auditory feedback to modify subsequent speech motor commands. However, these results also demonstrate that children and adults differ in their ability to use auditory feedback to generate compensatory vocal responses during ongoing vocalization. Since vocal variability also differed across the children and adult groups, these results also suggest that compensatory vocal responses to frequency-altered feedback manipulations initiated at vocalization onset may be modulated by vocal variability. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.

Magnetic resonance spectroscopy of fiber tracts in children with traumatic brain injury: A combined MRS - Diffusion MRI study.

PubMed

Dennis, Emily L; Babikian, Talin; Alger, Jeffry; Rashid, Faisal; Villalon-Reina, Julio E; Jin, Yan; Olsen, Alexander; Mink, Richard; Babbitt, Christopher; Johnson, Jeffrey; Giza, Christopher C; Thompson, Paul M; Asarnow, Robert F

2018-05-10

Traumatic brain injury can cause extensive damage to the white matter (WM) of the brain. These disruptions can be especially damaging in children, whose brains are still maturing. Diffusion magnetic resonance imaging (dMRI) is the most commonly used method to assess WM organization, but it has limited resolution to differentiate causes of WM disruption. Magnetic resonance spectroscopy (MRS) yields spectra showing the levels of neurometabolites that can indicate neuronal/axonal health, inflammation, membrane proliferation/turnover, and other cellular processes that are on-going post-injury. Previous analyses on this dataset revealed a significant division within the msTBI patient group, based on interhemispheric transfer time (IHTT); one subgroup of patients (TBI-normal) showed evidence of recovery over time, while the other showed continuing degeneration (TBI-slow). We combined dMRI with MRS to better understand WM disruptions in children with moderate-severe traumatic brain injury (msTBI). Tracts with poorer WM organization, as shown by lower FA and higher MD and RD, also showed lower N-acetylaspartate (NAA), a marker of neuronal and axonal health and myelination. We did not find lower NAA in tracts with normal WM organization. Choline, a marker of inflammation, membrane turnover, or gliosis, did not show such associations. We further show that multi-modal imaging can improve outcome prediction over a single modality, as well as over earlier cognitive function measures. Our results suggest that demyelination plays an important role in WM disruption post-injury in a subgroup of msTBI children and indicate the utility of multi-modal imaging. © 2018 Wiley Periodicals, Inc.

Low-Frequency Cortical Oscillations Entrain to Subthreshold Rhythmic Auditory Stimuli

PubMed Central

Schroeder, Charles E.; Poeppel, David; van Atteveldt, Nienke

2017-01-01

Many environmental stimuli contain temporal regularities, a feature that can help predict forthcoming input. Phase locking (entrainment) of ongoing low-frequency neuronal oscillations to rhythmic stimuli is proposed as a potential mechanism for enhancing neuronal responses and perceptual sensitivity, by aligning high-excitability phases to events within a stimulus stream. Previous experiments show that rhythmic structure has a behavioral benefit even when the rhythm itself is below perceptual detection thresholds (ten Oever et al., 2014). It is not known whether this “inaudible” rhythmic sound stream also induces entrainment. Here we tested this hypothesis using magnetoencephalography and electrocorticography in humans to record changes in neuronal activity as subthreshold rhythmic stimuli gradually became audible. We found that significant phase locking to the rhythmic sounds preceded participants' detection of them. Moreover, no significant auditory-evoked responses accompanied this prethreshold entrainment. These auditory-evoked responses, distinguished by robust, broad-band increases in intertrial coherence, only appeared after sounds were reported as audible. Taken together with the reduced perceptual thresholds observed for rhythmic sequences, these findings support the proposition that entrainment of low-frequency oscillations serves a mechanistic role in enhancing perceptual sensitivity for temporally predictive sounds. This framework has broad implications for understanding the neural mechanisms involved in generating temporal predictions and their relevance for perception, attention, and awareness. SIGNIFICANCE STATEMENT The environment is full of rhythmically structured signals that the nervous system can exploit for information processing. Thus, it is important to understand how the brain processes such temporally structured, regular features of external stimuli. Here we report the alignment of slowly fluctuating oscillatory brain activity to external rhythmic structure before its behavioral detection. These results indicate that phase alignment is a general mechanism of the brain to process rhythmic structure and can occur without the perceptual detection of this temporal structure. PMID:28411273

Effects of One Year of Spaceflight on Neurocognitive Function

NASA Technical Reports Server (NTRS)

Seidler, R. D.; Mulavara, A. P.; Koppelmans, V.; Kofman, I. S.; Cassady, K.; Yuan , P.; De Dios, Y. E.; Gadd, N.; Riascos, R. F.; Wood, S. J.;

Vocal emotion of humanoid robots: a study from brain mechanism.

PubMed

Wang, Youhui; Hu, Xiaohua; Dai, Weihui; Zhou, Jie; Kuo, Taitzong

2014-01-01

Driven by rapid ongoing advances in humanoid robot, increasing attention has been shifted into the issue of emotion intelligence of AI robots to facilitate the communication between man-machines and human beings, especially for the vocal emotion in interactive system of future humanoid robots. This paper explored the brain mechanism of vocal emotion by studying previous researches and developed an experiment to observe the brain response by fMRI, to analyze vocal emotion of human beings. Findings in this paper provided a new approach to design and evaluate the vocal emotion of humanoid robots based on brain mechanism of human beings.

Temporal Dynamics of Late Second Language Acquisition: Evidence from Event-Related Brain Potentials

ERIC Educational Resources Information Center

Steinhauer, Karsten; White, Erin J.; Drury, John E.

2009-01-01

The ways in which age of acquisition (AoA) may affect (morpho)syntax in second language acquisition (SLA) are discussed. We suggest that event-related brain potentials (ERPs) provide an appropriate online measure to test some such effects. ERP findings of the past decade are reviewed with a focus on recent and ongoing research. It is concluded…

The role of vascular endothelial growth factor in neurodegeneration and cognitive decline: exploring interactions with biomarkers of Alzheimer disease.

PubMed

Hohman, Timothy J; Bell, Susan P; Jefferson, Angela L

2015-05-01

A subset of older adults present post mortem with Alzheimer disease (AD) pathologic features but without any significant clinical manifestation of dementia. Vascular endothelial growth factor (VEGF) has been implicated in staving off AD-related neurodegeneration. To evaluate whether VEGF levels are associated with brain aging outcomes (hippocampal volume and cognition) and to further evaluate whether VEGF modifies relations between AD biomarkers and brain aging outcomes. Biomarker analysis using neuroimaging and neuropsychological outcomes from the Alzheimer's Disease Neuroimaging Initiative. This prospective longitudinal study across North America included individuals with normal cognition (n = 90), mild cognitive impairment (n = 130), and AD (n = 59) and began in October 2004, with follow-up ongoing. Cerebrospinal fluid VEGF was cross-sectionally related to brain aging outcomes (hippocampal volume, episodic memory, and executive function) using a general linear model and longitudinally using mixed-effects regression. Alzheimer disease biomarker (cerebrospinal fluid β-amyloid 42 and total tau)-by-VEGF interactions evaluated the effect of VEGF on brain aging outcomes in the presence of enhanced AD biomarkers. Vascular endothelial growth factor was associated with baseline hippocampal volume (t277 = 2.62; P = .009), longitudinal hippocampal atrophy (t858 = 2.48; P = .01), and longitudinal decline in memory (t1629 = 4.09; P < .001) and executive function (t1616 = 3.00; P = .003). Vascular endothelial growth factor interacted with tau in predicting longitudinal hippocampal atrophy (t845 = 4.17; P < .001), memory decline (t1610 = 2.49; P = .01), and executive function decline (t1597 = 3.71; P < .001). Vascular endothelial growth factor interacted with β-amyloid 42 in predicting longitudinal memory decline (t1618 = -2.53; P = .01). Elevated cerebrospinal fluid VEGF was associated with more optimal brain aging in vivo. The neuroprotective effect appeared strongest in the presence of enhanced AD biomarkers, suggesting that VEGF may be particularly beneficial in individuals showing early hallmarks of the AD cascade. Future work should evaluate the interaction between VEGF expression in vitro and pathologic burden to address potential mechanisms.

Breathing as a Fundamental Rhythm of Brain Function.

PubMed

Heck, Detlef H; McAfee, Samuel S; Liu, Yu; Babajani-Feremi, Abbas; Rezaie, Roozbeh; Freeman, Walter J; Wheless, James W; Papanicolaou, Andrew C; Ruszinkó, Miklós; Sokolov, Yury; Kozma, Robert

2016-01-01

Ongoing fluctuations of neuronal activity have long been considered intrinsic noise that introduces unavoidable and unwanted variability into neuronal processing, which the brain eliminates by averaging across population activity (Georgopoulos et al., 1986; Lee et al., 1988; Shadlen and Newsome, 1994; Maynard et al., 1999). It is now understood, that the seemingly random fluctuations of cortical activity form highly structured patterns, including oscillations at various frequencies, that modulate evoked neuronal responses (Arieli et al., 1996; Poulet and Petersen, 2008; He, 2013) and affect sensory perception (Linkenkaer-Hansen et al., 2004; Boly et al., 2007; Sadaghiani et al., 2009; Vinnik et al., 2012; Palva et al., 2013). Ongoing cortical activity is driven by proprioceptive and interoceptive inputs. In addition, it is partially intrinsically generated in which case it may be related to mental processes (Fox and Raichle, 2007; Deco et al., 2011). Here we argue that respiration, via multiple sensory pathways, contributes a rhythmic component to the ongoing cortical activity. We suggest that this rhythmic activity modulates the temporal organization of cortical neurodynamics, thereby linking higher cortical functions to the process of breathing.

Humanoid infers Archimedes' principle: understanding physical relations and object affordances through cumulative learning experiences.

PubMed

Bhat, Ajaz Ahmad; Mohan, Vishwanathan; Sandini, Giulio; Morasso, Pietro

2016-07-01

Emerging studies indicate that several species such as corvids, apes and children solve 'The Crow and the Pitcher' task (from Aesop's Fables) in diverse conditions. Hidden beneath this fascinating paradigm is a fundamental question: by cumulatively interacting with different objects, how can an agent abstract the underlying cause-effect relations to predict and creatively exploit potential affordances of novel objects in the context of sought goals? Re-enacting this Aesop's Fable task on a humanoid within an open-ended 'learning-prediction-abstraction' loop, we address this problem and (i) present a brain-guided neural framework that emulates rapid one-shot encoding of ongoing experiences into a long-term memory and (ii) propose four task-agnostic learning rules (elimination, growth, uncertainty and status quo) that correlate predictions from remembered past experiences with the unfolding present situation to gradually abstract the underlying causal relations. Driven by the proposed architecture, the ensuing robot behaviours illustrated causal learning and anticipation similar to natural agents. Results further demonstrate that by cumulatively interacting with few objects, the predictions of the robot in case of novel objects converge close to the physical law, i.e. the Archimedes principle: this being independent of both the objects explored during learning and the order of their cumulative exploration. © 2016 The Author(s).

Simultaneous transcranial direct current stimulation (tDCS) and whole-head magnetoencephalography (MEG): assessing the impact of tDCS on slow cortical magnetic fields.

PubMed

Garcia-Cossio, Eliana; Witkowski, Matthias; Robinson, Stephen E; Cohen, Leonardo G; Birbaumer, Niels; Soekadar, Surjo R

2016-10-15

Transcranial direct current stimulation (tDCS) can influence cognitive, affective or motor brain functions. Whereas previous imaging studies demonstrated widespread tDCS effects on brain metabolism, direct impact of tDCS on electric or magnetic source activity in task-related brain areas could not be confirmed due to the difficulty to record such activity simultaneously during tDCS. The aim of this proof-of-principal study was to demonstrate the feasibility of whole-head source localization and reconstruction of neuromagnetic brain activity during tDCS and to confirm the direct effect of tDCS on ongoing neuromagnetic activity in task-related brain areas. Here we show for the first time that tDCS has an immediate impact on slow cortical magnetic fields (SCF, 0-4Hz) of task-related areas that are identical with brain regions previously described in metabolic neuroimaging studies. 14 healthy volunteers performed a choice reaction time (RT) task while whole-head magnetoencephalography (MEG) was recorded. Task-related source-activity of SCFs was calculated using synthetic aperture magnetometry (SAM) in absence of stimulation and while anodal, cathodal or sham tDCS was delivered over the right primary motor cortex (M1). Source reconstruction revealed task-related SCF modulations in brain regions that precisely matched prior metabolic neuroimaging studies. Anodal and cathodal tDCS had a polarity-dependent impact on RT and SCF in primary sensorimotor and medial centro-parietal cortices. Combining tDCS and whole-head MEG is a powerful approach to investigate the direct effects of transcranial electric currents on ongoing neuromagnetic source activity, brain function and behavior. Copyright © 2015 Elsevier Inc. All rights reserved.

Simultaneous transcranial direct current stimulation (tDCS) and whole-head magnetoencephalography (MEG): assessing the impact of tDCS on slow cortical magnetic fields

PubMed Central

Garcia-Cossio, Eliana; Witkowski, Matthias; Robinson, Stephen E.; Cohen, Leonardo G.; Birbaumer, Niels; Soekadar, Surjo R.

2016-01-01

Transcranial direct current stimulation (tDCS) can influence cognitive, affective or motor brain functions. Whereas previous imaging studies demonstrated widespread tDCS effects on brain metabolism, direct impact of tDCS on electric or magnetic source activity in task-related brain areas could not be confirmed due to the difficulty to record such activity simultaneously during tDCS. The aim of this proof-of-principal study was to demonstrate the feasibility of whole-head source localization and reconstruction of neuromagnetic brain activity during tDCS and to confirm the direct effect of tDCS on ongoing neuromagnetic activity in task-related brain areas. Here we show for the first time that tDCS has an immediate impact on slow cortical magnetic fields (SCF, 0–4 Hz) of task-related areas that are identical with brain regions previously described in metabolic neuroimaging studies. 14 healthy volunteers performed a choice reaction time (RT) task while whole-head magnetoencephalography (MEG) was recorded. Task-related source-activity of SCFs was calculated using synthetic aperture magnetometry (SAM) in absence of stimulation and while anodal, cathodal or sham tDCS was delivered over the right primary motor cortex (M1). Source reconstruction revealed task-related SCF modulations in brain regions that precisely matched prior metabolic neuroimaging studies. Anodal and cathodal tDCS had a polarity-dependent impact on RT and SCF in primary sensorimotor and medial centro-parietal cortices. Combining tDCS and whole-head MEG is a powerful approach to investigate the direct effects of transcranial electric currents on ongoing neuromagnetic source activity, brain function and behavior. PMID:26455796

Detecting ongoing intimate partner violence in the emergency department using a simple 4-question screen: the OVAT.

PubMed

Ernst, Amy A; Weiss, Steven J; Cham, Elaine; Hall, Louise; Nick, Todd G

2004-06-01

We wanted to prospectively evaluate the use of a brief screening tool for ongoing intimate partner violence (IPV), the OVAT, and to validate this tool against the present Index of Spouse Abuse (ISA). The design was a prospective survey during randomized 4-hour shifts in an urban emergency department setting. The scale consists of four questions developed based on our previous work. The ISA was compared as the gold standard for detection of present (ongoing) IPV. Of 362 eligible patients presenting during 75 randomized 4-hour shifts, 306 (85%) completed the study. The prevalence of ongoing IPV using the OVAT was 31% (95% CI 26% to 36%). For the ISA, the prevalence was 20% (95% CI 16% to 25%). Compared with the ISA, the sensitivity of the OVAT in detecting ongoing IPV was 86%, specificity 83%, negative predictive value 96%, positive predictive value 56%, with an accuracy of 84%. In conclusion, four brief questions can detect ongoing IPV to aid in identifying the victim.

Using Biophysical Models to Understand the Effect of tDCS on Neurorehabilitation: Searching for Optimal Covariates to Enhance Poststroke Recovery

PubMed Central

Malerba, Paola; Straudi, Sofia; Fregni, Felipe; Bazhenov, Maxim; Basaglia, Nino

2017-01-01

Stroke is a leading cause of worldwide disability, and up to 75% of survivors suffer from some degree of arm paresis. Recently, rehabilitation of stroke patients has focused on recovering motor skills by taking advantage of use-dependent neuroplasticity, where high-repetition of goal-oriented movement is at times combined with non-invasive brain stimulation, such as transcranial direct current stimulation (tDCS). Merging the two approaches is thought to provide outlasting clinical gains, by enhancing synaptic plasticity and motor relearning in the motor cortex primary area. However, this general approach has shown mixed results across the stroke population. In particular, stroke location has been found to correlate with the likelihood of success, which suggests that different patients might require different protocols. Understanding how motor rehabilitation and stimulation interact with ongoing neural dynamics is crucial to optimize rehabilitation strategies, but it requires theoretical and computational models to consider the multiple levels at which this complex phenomenon operate. In this work, we argue that biophysical models of cortical dynamics are uniquely suited to address this problem. Specifically, biophysical models can predict treatment efficacy by introducing explicit variables and dynamics for damaged connections, changes in neural excitability, neurotransmitters, neuromodulators, plasticity mechanisms, and repetitive movement, which together can represent brain state, effect of incoming stimulus, and movement-induced activity. In this work, we hypothesize that effects of tDCS depend on ongoing neural activity and that tDCS effects on plasticity may be also related to enhancing inhibitory processes. We propose a model design for each step of this complex system, and highlight strengths and limitations of the different modeling choices within our approach. Our theoretical framework proposes a change in paradigm, where biophysical models can contribute to the future design of novel protocols, in which combined tDCS and motor rehabilitation strategies are tailored to the ongoing dynamics that they interact with, by considering the known biophysical factors recruited by such protocols and their interaction. PMID:28280482

Molecular markers in pediatric neuro-oncology.

PubMed

Ichimura, Koichi; Nishikawa, Ryo; Matsutani, Masao

2012-09-01

Pediatric molecular neuro-oncology is a fast developing field. A multitude of molecular profiling studies in recent years has unveiled a number of genetic abnormalities unique to pediatric brain tumors. It has now become clear that brain tumors that arise in children have distinct pathogenesis and biology, compared with their adult counterparts, even for those with indistinguishable histopathology. Some of the molecular features are so specific to a particular type of tumors, such as the presence of the KIAA1549-BRAF fusion gene for pilocytic astrocytomas or SMARCB1 mutations for atypical teratoid/rhabdoid tumors, that they could practically serve as a diagnostic marker on their own. Expression profiling has resolved the existence of 4 molecular subgroups in medulloblastomas, which positively translated into improved prognostication for the patients. The currently available molecular markers, however, do not cover all tumors even within a single tumor entity. The molecular pathogenesis of a large number of pediatric brain tumors is still unaccounted for, and the hierarchy of tumors is likely to be more complex and intricate than currently acknowledged. One of the main tasks of future molecular analyses in pediatric neuro-oncology, including the ongoing genome sequencing efforts, is to elucidate the biological basis of those orphan tumors. The ultimate goal of molecular diagnostics is to accurately predict the clinical and biological behavior of any tumor by means of their molecular characteristics, which is hoped to eventually pave the way for individualized treatment.

Cognitive neuroscience 2.0: building a cumulative science of human brain function

PubMed Central

Yarkoni, Tal; Poldrack, Russell A.; Van Essen, David C.; Wager, Tor D.

2010-01-01

Cognitive neuroscientists increasingly recognize that continued progress in understanding human brain function will require not only the acquisition of new data, but also the synthesis and integration of data across studies and laboratories. Here we review ongoing efforts to develop a more cumulative science of human brain function. We discuss the rationale for an increased focus on formal synthesis of the cognitive neuroscience literature, provide an overview of recently developed tools and platforms designed to facilitate the sharing and integration of neuroimaging data, and conclude with a discussion of several emerging developments that hold even greater promise in advancing the study of human brain function. PMID:20884276

Vocal Emotion of Humanoid Robots: A Study from Brain Mechanism

PubMed Central

Wang, Youhui; Hu, Xiaohua; Zhou, Jie; Kuo, Taitzong

2014-01-01

Driven by rapid ongoing advances in humanoid robot, increasing attention has been shifted into the issue of emotion intelligence of AI robots to facilitate the communication between man-machines and human beings, especially for the vocal emotion in interactive system of future humanoid robots. This paper explored the brain mechanism of vocal emotion by studying previous researches and developed an experiment to observe the brain response by fMRI, to analyze vocal emotion of human beings. Findings in this paper provided a new approach to design and evaluate the vocal emotion of humanoid robots based on brain mechanism of human beings. PMID:24587712

Therapeutic Devices for Epilepsy

PubMed Central

Fisher, Robert S.

2011-01-01

Therapeutic devices provide new options for treating drug-resistant epilepsy. These devices act by a variety of mechanisms to modulate neuronal activity. Only vagus nerve stimulation, which continues to develop new technology, is approved for use in the United States. Deep brain stimulation (DBS) of anterior thalamus for partial epilepsy recently was approved in Europe and several other countries. Responsive neurostimulation, which delivers stimuli to one or two seizure foci in response to a detected seizure, recently completed a successful multicenter trial. Several other trials of brain stimulation are in planning or underway. Transcutaneous magnetic stimulation (TMS) may provide a noninvasive method to stimulate cortex. Controlled studies of TMS split on efficacy, and may depend on whether a seizure focus is near a possible region for stimulation. Seizure detection devices in the form of “shake” detectors via portable accelerometers can provide notification of an ongoing tonic-clonic seizure, or peace of mind in the absence of notification. Prediction of seizures from various aspects of EEG is in early stages. Prediction appears to be possible in a subpopulation of people with refractory seizures and a clinical trial of an implantable prediction device is underway. Cooling of neocortex or hippocampus reversibly can attenuate epileptiform EEG activity and seizures, but engineering problems remain in its implementation. Optogenetics is a new technique that can control excitability of specific populations of neurons with light. Inhibition of epileptiform activity has been demonstrated in hippocampal slices, but use in humans will require more work. In general, devices provide useful palliation for otherwise uncontrollable seizures, but with a different risk profile than with most drugs. Optimizing the place of devices in therapy for epilepsy will require further development and clinical experience. PMID:22367987

Parkinson's disease and systemic inflammation.

PubMed

Ferrari, Carina C; Tarelli, Rodolfo

2011-02-22

Peripheral inflammation triggers exacerbation in the central brain's ongoing damage in several neurodegenerative diseases. Systemic inflammatory stimulus induce a general response known as sickness behaviour, indicating that a peripheral stimulus can induce the synthesis of cytokines in the brain. In Parkinson's disease (PD), inflammation was mainly associated with microglia activation that can underlie the neurodegeneration of neurons in the substantia nigra (SN). Peripheral inflammation can transform the "primed" microglia into an "active" state, which can trigger stronger responses dealing with neurodegenerative processes. Numerous evidences show that systemic inflammatory processes exacerbate ongoing neurodegeneration in PD patient and animal models. Anti-inflammatory treatment in PD patients exerts a neuroprotective effect. In the present paper, we analyse the effect of peripheral infections in the etiology and progression in PD patients and animal models, suggesting that these peripheral immune challenges can exacerbate the symptoms in the disease.

Adolescent neural response to reward is related to participant sex and task motivation

PubMed Central

Alarcón, Gabriela; Cservenka, Anita; Nagel, Bonnie J.

2017-01-01

Risky decision making is prominent during adolescence, perhaps contributed to by heightened sensation seeking and ongoing maturation of reward and dopamine systems in the brain, which are, in part, modulated by sex hormones. In this study, we examined sex differences in the neural substrates of reward sensitivity during a risky decision-making task and hypothesized that compared with girls, boys would show heightened brain activation in reward-relevant regions, particularly the nucleus accumbens, during reward receipt. Further, we hypothesized that testosterone and estradiol levels would mediate this sex difference. Moreover, we predicted boys would make more risky choices on the task. While boys showed increased nucleus accumbens blood oxygen level-dependent (BOLD) response relative to girls, sex hormones did not mediate this effect. As predicted, boys made a higher percentage of risky decisions during the task. Interestingly, boys also self-reported more motivation to perform well and earn money on the task, while girls self-reported higher state anxiety prior to the scan session. Motivation to earn money partially mediated the effect of sex on nucleus accumbens activity during reward. Previous research shows that increased motivation and salience of reinforcers is linked with more robust striatal BOLD response, therefore psychosocial factors, in addition to sex, may play an important role in reward sensitivity. Elucidating neurobiological mechanisms that support adolescent sex differences in risky decision making has important implications for understanding individual differences that lead to advantageous and adverse behaviors that affect health outcomes. PMID:27816780

Advances in Aβ plaque detection and the value of knowing: overcoming challenges to improving patient outcomes in Alzheimer's disease.

PubMed

Jovalekic, Aleksandar; Bullich, Santiago; Catafau, Ana; de Santi, Susan

2016-12-01

Clinical diagnosis of Alzheimer's disease (AD) can be challenging as numerous diseases mimic the characteristics of AD. In this light, recent guidelines developed by different associations and working groups point out the need for biomarkers to support AD diagnosis. This paper discusses 18F-labeled radiotracers (which are indicated for PET imaging of the brain) and ongoing clinical studies that aim to generate new evidence for the usage of amyloid imaging. In addition to their relatively long half-life, these agents are known for their high sensitivity and high negative predictive values for detection of neuritic Aβ plaques. Comparisons with other biomarkers are provided and implications of diagnostic disclosures discussed. Finally, recent data from clinical trials underscore the importance of amyloid PET for detecting, quantifying and monitoring Aβ plaque deposits.

GI-POP: a combinational annotation and genomic island prediction pipeline for ongoing microbial genome projects.

PubMed

Lee, Chi-Ching; Chen, Yi-Ping Phoebe; Yao, Tzu-Jung; Ma, Cheng-Yu; Lo, Wei-Cheng; Lyu, Ping-Chiang; Tang, Chuan Yi

2013-04-10

Sequencing of microbial genomes is important because of microbial-carrying antibiotic and pathogenetic activities. However, even with the help of new assembling software, finishing a whole genome is a time-consuming task. In most bacteria, pathogenetic or antibiotic genes are carried in genomic islands. Therefore, a quick genomic island (GI) prediction method is useful for ongoing sequencing genomes. In this work, we built a Web server called GI-POP (http://gipop.life.nthu.edu.tw) which integrates a sequence assembling tool, a functional annotation pipeline, and a high-performance GI predicting module, in a support vector machine (SVM)-based method called genomic island genomic profile scanning (GI-GPS). The draft genomes of the ongoing genome projects in contigs or scaffolds can be submitted to our Web server, and it provides the functional annotation and highly probable GI-predicting results. GI-POP is a comprehensive annotation Web server designed for ongoing genome project analysis. Researchers can perform annotation and obtain pre-analytic information include possible GIs, coding/non-coding sequences and functional analysis from their draft genomes. This pre-analytic system can provide useful information for finishing a genome sequencing project. Copyright © 2012 Elsevier B.V. All rights reserved.

Brain mechanisms underlying cue-based memorizing during free viewing of movie Memento.

PubMed

Kauttonen, Janne; Hlushchuk, Yevhen; Jääskeläinen, Iiro P; Tikka, Pia

2018-05-15

How does the human brain recall and connect relevant memories with unfolding events? To study this, we presented 25 healthy subjects, during functional magnetic resonance imaging, the movie 'Memento' (director C. Nolan). In this movie, scenes are presented in chronologically reverse order with certain scenes briefly overlapping previously presented scenes. Such overlapping "key-frames" serve as effective memory cues for the viewers, prompting recall of relevant memories of the previously seen scene and connecting them with the concurrent scene. We hypothesized that these repeating key-frames serve as immediate recall cues and would facilitate reconstruction of the story piece-by-piece. The chronological version of Memento, shown in a separate experiment for another group of subjects, served as a control condition. Using multivariate event-related pattern analysis method and representational similarity analysis, focal fingerprint patterns of hemodynamic activity were found to emerge during presentation of key-frame scenes. This effect was present in higher-order cortical network with regions including precuneus, angular gyrus, cingulate gyrus, as well as lateral, superior, and middle frontal gyri within frontal poles. This network was right hemispheric dominant. These distributed patterns of brain activity appear to underlie ability to recall relevant memories and connect them with ongoing events, i.e., "what goes with what" in a complex story. Given the real-life likeness of cinematic experience, these results provide new insight into how the human brain recalls, given proper cues, relevant memories to facilitate understanding and prediction of everyday life events. Copyright © 2018 Elsevier Inc. All rights reserved.

Biomarkers and Stimulation Algorithms for Adaptive Brain Stimulation

PubMed Central

Hoang, Kimberly B.; Cassar, Isaac R.; Grill, Warren M.; Turner, Dennis A.

2017-01-01

The goal of this review is to describe in what ways feedback or adaptive stimulation may be delivered and adjusted based on relevant biomarkers. Specific treatment mechanisms underlying therapeutic brain stimulation remain unclear, in spite of the demonstrated efficacy in a number of nervous system diseases. Brain stimulation appears to exert widespread influence over specific neural networks that are relevant to specific disease entities. In awake patients, activation or suppression of these neural networks can be assessed by either symptom alleviation (i.e., tremor, rigidity, seizures) or physiological criteria, which may be predictive of expected symptomatic treatment. Secondary verification of network activation through specific biomarkers that are linked to symptomatic disease improvement may be useful for several reasons. For example, these biomarkers could aid optimal intraoperative localization, possibly improve efficacy or efficiency (i.e., reduced power needs), and provide long-term adaptive automatic adjustment of stimulation parameters. Possible biomarkers for use in portable or implanted devices span from ongoing physiological brain activity, evoked local field potentials (LFPs), and intermittent pathological activity, to wearable devices, biochemical, blood flow, optical, or magnetic resonance imaging (MRI) changes, temperature changes, or optogenetic signals. First, however, potential biomarkers must be correlated directly with symptom or disease treatment and network activation. Although numerous biomarkers are under consideration for a variety of stimulation indications the feasibility of these approaches has yet to be fully determined. Particularly, there are critical questions whether the use of adaptive systems can improve efficacy over continuous stimulation, facilitate adjustment of stimulation interventions and improve our understanding of the role of abnormal network function in disease mechanisms. PMID:29066947

Asymmetry of Neuronal Combinatorial Codes Arises from Minimizing Synaptic Weight Change.

PubMed

Leibold, Christian; Monsalve-Mercado, Mauro M

2016-08-01

Synaptic change is a costly resource, particularly for brain structures that have a high demand of synaptic plasticity. For example, building memories of object positions requires efficient use of plasticity resources since objects can easily change their location in space and yet we can memorize object locations. But how should a neural circuit ideally be set up to integrate two input streams (object location and identity) in case the overall synaptic changes should be minimized during ongoing learning? This letter provides a theoretical framework on how the two input pathways should ideally be specified. Generally the model predicts that the information-rich pathway should be plastic and encoded sparsely, whereas the pathway conveying less information should be encoded densely and undergo learning only if a neuronal representation of a novel object has to be established. As an example, we consider hippocampal area CA1, which combines place and object information. The model thereby provides a normative account of hippocampal rate remapping, that is, modulations of place field activity by changes of local cues. It may as well be applicable to other brain areas (such as neocortical layer V) that learn combinatorial codes from multiple input streams.

Handedness differences in information framing.

PubMed

Jasper, John D; Fournier, Candice; Christman, Stephen D

2014-02-01

Previous research has shown that strength of handedness predicts differences in sensory illusions, Stroop interference, episodic memory, and beliefs about body image. Recent evidence also suggests handedness differences in the susceptibility to common decision biases such as anchoring and sunk cost. The present paper extends this line of work to attribute framing effects. Sixty-three undergraduates were asked to advise a friend concerning the use of a safe allergy medication during pregnancy. A third of the participants received negatively-framed information concerning the fetal risk of the drug (1-3% chance of having a malformed child); another third received positively-framed information (97-99% chance of having a normal child); and the final third received no counseling information and served as the control. Results indicated that, as predicted, inconsistent (mixed)-handers were more responsive than consistent (strong)-handers to information changes and readily update their beliefs. Although not significant, the data also suggested that only inconsistent handers were affected by information framing. Theoretical implications as well as ongoing work in holistic versus analytic processing, contextual sensitivity, and brain asymmetry will be discussed. Copyright © 2013 Elsevier Inc. All rights reserved.

Inflammation and white matter degeneration persist for years after a single traumatic brain injury.

PubMed

Johnson, Victoria E; Stewart, Janice E; Begbie, Finn D; Trojanowski, John Q; Smith, Douglas H; Stewart, William

2013-01-01

A single traumatic brain injury is associated with an increased risk of dementia and, in a proportion of patients surviving a year or more from injury, the development of hallmark Alzheimer's disease-like pathologies. However, the pathological processes linking traumatic brain injury and neurodegenerative disease remain poorly understood. Growing evidence supports a role for neuroinflammation in the development of Alzheimer's disease. In contrast, little is known about the neuroinflammatory response to brain injury and, in particular, its temporal dynamics and any potential role in neurodegeneration. Cases of traumatic brain injury with survivals ranging from 10 h to 47 years post injury (n = 52) and age-matched, uninjured control subjects (n = 44) were selected from the Glasgow Traumatic Brain Injury archive. From these, sections of the corpus callosum and adjacent parasaggital cortex were examined for microglial density and morphology, and for indices of white matter pathology and integrity. With survival of ≥3 months from injury, cases with traumatic brain injury frequently displayed extensive, densely packed, reactive microglia (CR3/43- and/or CD68-immunoreactive), a pathology not seen in control subjects or acutely injured cases. Of particular note, these reactive microglia were present in 28% of cases with survival of >1 year and up to 18 years post-trauma. In cases displaying this inflammatory pathology, evidence of ongoing white matter degradation could also be observed. Moreover, there was a 25% reduction in the corpus callosum thickness with survival >1 year post-injury. These data present striking evidence of persistent inflammation and ongoing white matter degeneration for many years after just a single traumatic brain injury in humans. Future studies to determine whether inflammation occurs in response to or, conversely, promotes white matter degeneration will be important. These findings may provide parallels for studying neurodegenerative disease, with traumatic brain injury patients serving as a model for longitudinal investigations, in particular with a view to identifying potential therapeutic interventions.

On the same wavelength: predictable language enhances speaker-listener brain-to-brain synchrony in posterior superior temporal gyrus.

PubMed

Dikker, Suzanne; Silbert, Lauren J; Hasson, Uri; Zevin, Jason D

2014-04-30

Recent research has shown that the degree to which speakers and listeners exhibit similar brain activity patterns during human linguistic interaction is correlated with communicative success. Here, we used an intersubject correlation approach in fMRI to test the hypothesis that a listener's ability to predict a speaker's utterance increases such neural coupling between speakers and listeners. Nine subjects listened to recordings of a speaker describing visual scenes that varied in the degree to which they permitted specific linguistic predictions. In line with our hypothesis, the temporal profile of listeners' brain activity was significantly more synchronous with the speaker's brain activity for highly predictive contexts in left posterior superior temporal gyrus (pSTG), an area previously associated with predictive auditory language processing. In this region, predictability differentially affected the temporal profiles of brain responses in the speaker and listeners respectively, in turn affecting correlated activity between the two: whereas pSTG activation increased with predictability in the speaker, listeners' pSTG activity instead decreased for more predictable sentences. Listeners additionally showed stronger BOLD responses for predictive images before sentence onset, suggesting that highly predictable contexts lead comprehenders to preactivate predicted words.

Increased brain-predicted aging in treated HIV disease

PubMed Central

Underwood, Jonathan; Caan, Matthan W.A.; De Francesco, Davide; van Zoest, Rosan A.; Leech, Robert; Wit, Ferdinand W.N.M.; Portegies, Peter; Geurtsen, Gert J.; Schmand, Ben A.; Schim van der Loeff, Maarten F.; Franceschi, Claudio; Sabin, Caroline A.; Majoie, Charles B.L.M.; Winston, Alan; Reiss, Peter; Sharp, David J.

2017-01-01

Objective: To establish whether HIV disease is associated with abnormal levels of age-related brain atrophy, by estimating apparent brain age using neuroimaging and exploring whether these estimates related to HIV status, age, cognitive performance, and HIV-related clinical parameters. Methods: A large sample of virologically suppressed HIV-positive adults (n = 162, age 45–82 years) and highly comparable HIV-negative controls (n = 105) were recruited as part of the Comorbidity in Relation to AIDS (COBRA) collaboration. Using T1-weighted MRI scans, a machine-learning model of healthy brain aging was defined in an independent cohort (n = 2,001, aged 18–90 years). Neuroimaging data from HIV-positive and HIV-negative individuals were then used to estimate brain-predicted age; then brain-predicted age difference (brain-PAD = brain-predicted brain age − chronological age) scores were calculated. Neuropsychological and clinical assessments were also carried out. Results: HIV-positive individuals had greater brain-PAD score (mean ± SD 2.15 ± 7.79 years) compared to HIV-negative individuals (−0.87 ± 8.40 years; b = 3.48, p < 0.01). Increased brain-PAD score was associated with decreased performance in multiple cognitive domains (information processing speed, executive function, memory) and general cognitive performance across all participants. Brain-PAD score was not associated with age, duration of HIV infection, or other HIV-related measures. Conclusion: Increased apparent brain aging, predicted using neuroimaging, was observed in HIV-positive adults, despite effective viral suppression. Furthermore, the magnitude of increased apparent brain aging related to cognitive deficits. However, predicted brain age difference did not correlate with chronological age or duration of HIV infection, suggesting that HIV disease may accentuate rather than accelerate brain aging. PMID:28258081

Increased brain-predicted aging in treated HIV disease.

PubMed

Cole, James H; Underwood, Jonathan; Caan, Matthan W A; De Francesco, Davide; van Zoest, Rosan A; Leech, Robert; Wit, Ferdinand W N M; Portegies, Peter; Geurtsen, Gert J; Schmand, Ben A; Schim van der Loeff, Maarten F; Franceschi, Claudio; Sabin, Caroline A; Majoie, Charles B L M; Winston, Alan; Reiss, Peter; Sharp, David J

2017-04-04

To establish whether HIV disease is associated with abnormal levels of age-related brain atrophy, by estimating apparent brain age using neuroimaging and exploring whether these estimates related to HIV status, age, cognitive performance, and HIV-related clinical parameters. A large sample of virologically suppressed HIV-positive adults (n = 162, age 45-82 years) and highly comparable HIV-negative controls (n = 105) were recruited as part of the Comorbidity in Relation to AIDS (COBRA) collaboration. Using T1-weighted MRI scans, a machine-learning model of healthy brain aging was defined in an independent cohort (n = 2,001, aged 18-90 years). Neuroimaging data from HIV-positive and HIV-negative individuals were then used to estimate brain-predicted age; then brain-predicted age difference (brain-PAD = brain-predicted brain age - chronological age) scores were calculated. Neuropsychological and clinical assessments were also carried out. HIV-positive individuals had greater brain-PAD score (mean ± SD 2.15 ± 7.79 years) compared to HIV-negative individuals (-0.87 ± 8.40 years; b = 3.48, p < 0.01). Increased brain-PAD score was associated with decreased performance in multiple cognitive domains (information processing speed, executive function, memory) and general cognitive performance across all participants. Brain-PAD score was not associated with age, duration of HIV infection, or other HIV-related measures. Increased apparent brain aging, predicted using neuroimaging, was observed in HIV-positive adults, despite effective viral suppression. Furthermore, the magnitude of increased apparent brain aging related to cognitive deficits. However, predicted brain age difference did not correlate with chronological age or duration of HIV infection, suggesting that HIV disease may accentuate rather than accelerate brain aging. Copyright © 2017 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.

BrainNetCNN: Convolutional neural networks for brain networks; towards predicting neurodevelopment.

PubMed

Kawahara, Jeremy; Brown, Colin J; Miller, Steven P; Booth, Brian G; Chau, Vann; Grunau, Ruth E; Zwicker, Jill G; Hamarneh, Ghassan

2017-02-01

We propose BrainNetCNN, a convolutional neural network (CNN) framework to predict clinical neurodevelopmental outcomes from brain networks. In contrast to the spatially local convolutions done in traditional image-based CNNs, our BrainNetCNN is composed of novel edge-to-edge, edge-to-node and node-to-graph convolutional filters that leverage the topological locality of structural brain networks. We apply the BrainNetCNN framework to predict cognitive and motor developmental outcome scores from structural brain networks of infants born preterm. Diffusion tensor images (DTI) of preterm infants, acquired between 27 and 46 weeks gestational age, were used to construct a dataset of structural brain connectivity networks. We first demonstrate the predictive capabilities of BrainNetCNN on synthetic phantom networks with simulated injury patterns and added noise. BrainNetCNN outperforms a fully connected neural-network with the same number of model parameters on both phantoms with focal and diffuse injury patterns. We then apply our method to the task of joint prediction of Bayley-III cognitive and motor scores, assessed at 18 months of age, adjusted for prematurity. We show that our BrainNetCNN framework outperforms a variety of other methods on the same data. Furthermore, BrainNetCNN is able to identify an infant's postmenstrual age to within about 2 weeks. Finally, we explore the high-level features learned by BrainNetCNN by visualizing the importance of each connection in the brain with respect to predicting the outcome scores. These findings are then discussed in the context of the anatomy and function of the developing preterm infant brain. Copyright © 2016 Elsevier Inc. All rights reserved.

Hyperglycosylated human chorionic gonadotropin as an early predictor of pregnancy outcomes after in vitro fertilization.

PubMed

Chuan, Sandy; Homer, Michael; Pandian, Raj; Conway, Deirdre; Garzo, Gabriel; Yeo, Lisa; Su, H Irene

2014-02-01

To determine whether serum hyperglycosylated human chorionic gonadotropin (hhCG) measured as early as 9 days after egg retrieval can predict ongoing pregnancies after in vitro fertilization and fresh embryo transfer (IVF-ET). Cohort Academic assisted reproduction center. Consecutive patients undergoing IVF-ET INTERVENTION(S): Serum hhCG and hCG levels measured 9 (D9) and 16 (D16) days after egg retrieval Ongoing pregnancy beyond 9 weeks of gestation. Ongoing pregnancy (62 of 112 participants) was associated with higher D9 levels of hhCG and hCG. However, hhCG was detectable in all D9 OP samples, while hCG was detectable in only 22%. A D9 hhCG level of >110 pg/mL was 96% specific for an ongoing pregnancy, yielding a positive predictive value of 94%. Compared with the D9 hCG levels, hhCG was more sensitive and had a larger area under the curve (0.87 vs. 0.67, respectively). The diagnostic test characteristics were similar between the D16 hhCG and hCG levels. In patients undergoing assisted reproduction, a test to detect pregnancy early and predict outcomes is highly desirable, and hhCG is detectable in serum 9 days after egg retrieval IVF-ET cycles. In this early assessment, hhCG was superior to traditional hCG and highly predictive of ongoing pregnancies. Copyright © 2014 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Language and reading development in the brain today: neuromarkers and the case for prediction.

PubMed

Buchweitz, Augusto

2016-01-01

The goal of this article is to provide an account of language development in the brain using the new information about brain function gleaned from cognitive neuroscience. This account goes beyond describing the association between language and specific brain areas to advocate the possibility of predicting language outcomes using brain-imaging data. The goal is to address the current evidence about language development in the brain and prediction of language outcomes. Recent studies will be discussed in the light of the evidence generated for predicting language outcomes and using new methods of analysis of brain data. The present account of brain behavior will address: (1) the development of a hardwired brain circuit for spoken language; (2) the neural adaptation that follows reading instruction and fosters the "grafting" of visual processing areas of the brain onto the hardwired circuit of spoken language; and (3) the prediction of language development and the possibility of translational neuroscience. Brain imaging has allowed for the identification of neural indices (neuromarkers) that reflect typical and atypical language development; the possibility of predicting risk for language disorders has emerged. A mandate to develop a bridge between neuroscience and health and cognition-related outcomes may pave the way for translational neuroscience. Copyright © 2016 Sociedade Brasileira de Pediatria. Published by Elsevier Editora Ltda. All rights reserved.

Parkinson's Disease and Systemic Inflammation

PubMed Central

Ferrari, Carina C.; Tarelli, Rodolfo

2011-01-01

Peripheral inflammation triggers exacerbation in the central brain's ongoing damage in several neurodegenerative diseases. Systemic inflammatory stimulus induce a general response known as sickness behaviour, indicating that a peripheral stimulus can induce the synthesis of cytokines in the brain. In Parkinson's disease (PD), inflammation was mainly associated with microglia activation that can underlie the neurodegeneration of neurons in the substantia nigra (SN). Peripheral inflammation can transform the “primed” microglia into an “active” state, which can trigger stronger responses dealing with neurodegenerative processes. Numerous evidences show that systemic inflammatory processes exacerbate ongoing neurodegeneration in PD patient and animal models. Anti-inflammatory treatment in PD patients exerts a neuroprotective effect. In the present paper, we analyse the effect of peripheral infections in the etiology and progression in PD patients and animal models, suggesting that these peripheral immune challenges can exacerbate the symptoms in the disease. PMID:21403862

Academic Momentum at University/College: Exploring the Roles of Prior Learning, Life Experience, and Ongoing Performance in Academic Achievement across Time

ERIC Educational Resources Information Center

Martin, Andrew J.; Wilson, Rachel; Liem, Gregory Arief D.; Ginns, Paul

2014-01-01

In the context of "academic momentum," a longitudinal study of university students (N = 904) showed high school achievement and ongoing university achievement predicted subsequent achievement through university. However, the impact of high school achievement diminished, while additive effects of ongoing university achievement continued.…

Noninvasive measures of brain edema predict outcome in pediatric cerebral malaria.

PubMed

Kampondeni, Samuel D; Birbeck, Gretchen L; Seydel, Karl B; Beare, Nicholas A; Glover, Simon J; Hammond, Colleen A; Chilingulo, Cowles A; Taylor, Terrie E; Potchen, Michael J

2018-01-01

Increased brain volume (BV) and subsequent herniation are strongly associated with death in pediatric cerebral malaria (PCM), a leading killer of children in developing countries. Accurate noninvasive measures of BV are needed for optimal clinical trial design. Our objectives were to examine the performance of six different magnetic resonance imaging (MRI) BV quantification measures for predicting mortality in PCM and to review the advantages and disadvantages of each method. Receiver operator characteristics were generated from BV measures of MRIs of children admitted to an ongoing research project with PCM between 2009 and 2014. Fatal cases were matched to the next available survivor. A total of 78 MRIs of children aged 5 months to 13 years (mean 4.0 years), of which 45% were males, were included. Areas under the curve (AUC) with 95% confidence interval on measures from the initial MRIs were: Radiologist-derived score = 0.69 (0.58-0.79; P = 0.0037); prepontine cistern anteroposterior (AP) dimension = 0.70 (0.56-0.78; P = 0.0133); SamKam ratio [Rt. parietal lobe height/(prepontine AP dimension + fourth ventricle AP dimension)] = 0.74 (0.63-0.83; P = 0.0002); and global cerebrospinal fluid (CSF) space ascertained by ClearCanvas = 0.67 (0.55-0.77; P = 0.0137). For patients with serial MRIs ( n = 37), the day 2 global CSF space AUC was 0.87 (0.71-0.96; P < 0.001) and the recovery factor (CSF volume day 2/CSF volume day 1) was 0.91 (0.76-0.98; P < 0.0001). Poor prognosis is associated with radiologist score of ≥7; prepontine cistern dimension ≤3 mm; cisternal CSF volume ≤7.5 ml; SamKam ratio ≥6.5; and recovery factor ≤0.75. All noninvasive measures of BV performed well in predicting death and providing a proxy measure for brain volume. Initial MRI assessment may inform future clinical trials for subject selection, risk adjustment, or stratification. Measures of temporal change may be used to stage PCM.

A Dynamic Connectome Supports the Emergence of Stable Computational Function of Neural Circuits through Reward-Based Learning.

PubMed

Kappel, David; Legenstein, Robert; Habenschuss, Stefan; Hsieh, Michael; Maass, Wolfgang

2018-01-01

Synaptic connections between neurons in the brain are dynamic because of continuously ongoing spine dynamics, axonal sprouting, and other processes. In fact, it was recently shown that the spontaneous synapse-autonomous component of spine dynamics is at least as large as the component that depends on the history of pre- and postsynaptic neural activity. These data are inconsistent with common models for network plasticity and raise the following questions: how can neural circuits maintain a stable computational function in spite of these continuously ongoing processes, and what could be functional uses of these ongoing processes? Here, we present a rigorous theoretical framework for these seemingly stochastic spine dynamics and rewiring processes in the context of reward-based learning tasks. We show that spontaneous synapse-autonomous processes, in combination with reward signals such as dopamine, can explain the capability of networks of neurons in the brain to configure themselves for specific computational tasks, and to compensate automatically for later changes in the network or task. Furthermore, we show theoretically and through computer simulations that stable computational performance is compatible with continuously ongoing synapse-autonomous changes. After reaching good computational performance it causes primarily a slow drift of network architecture and dynamics in task-irrelevant dimensions, as observed for neural activity in motor cortex and other areas. On the more abstract level of reinforcement learning the resulting model gives rise to an understanding of reward-driven network plasticity as continuous sampling of network configurations.

A Dynamic Connectome Supports the Emergence of Stable Computational Function of Neural Circuits through Reward-Based Learning

PubMed Central

Habenschuss, Stefan; Hsieh, Michael

2018-01-01

Synaptic connections between neurons in the brain are dynamic because of continuously ongoing spine dynamics, axonal sprouting, and other processes. In fact, it was recently shown that the spontaneous synapse-autonomous component of spine dynamics is at least as large as the component that depends on the history of pre- and postsynaptic neural activity. These data are inconsistent with common models for network plasticity and raise the following questions: how can neural circuits maintain a stable computational function in spite of these continuously ongoing processes, and what could be functional uses of these ongoing processes? Here, we present a rigorous theoretical framework for these seemingly stochastic spine dynamics and rewiring processes in the context of reward-based learning tasks. We show that spontaneous synapse-autonomous processes, in combination with reward signals such as dopamine, can explain the capability of networks of neurons in the brain to configure themselves for specific computational tasks, and to compensate automatically for later changes in the network or task. Furthermore, we show theoretically and through computer simulations that stable computational performance is compatible with continuously ongoing synapse-autonomous changes. After reaching good computational performance it causes primarily a slow drift of network architecture and dynamics in task-irrelevant dimensions, as observed for neural activity in motor cortex and other areas. On the more abstract level of reinforcement learning the resulting model gives rise to an understanding of reward-driven network plasticity as continuous sampling of network configurations. PMID:29696150

Predictive modeling of neuroanatomic structures for brain atrophy detection

NASA Astrophysics Data System (ADS)

Hu, Xintao; Guo, Lei; Nie, Jingxin; Li, Kaiming; Liu, Tianming

2010-03-01

In this paper, we present an approach of predictive modeling of neuroanatomic structures for the detection of brain atrophy based on cross-sectional MRI image. The underlying premise of applying predictive modeling for atrophy detection is that brain atrophy is defined as significant deviation of part of the anatomy from what the remaining normal anatomy predicts for that part. The steps of predictive modeling are as follows. The central cortical surface under consideration is reconstructed from brain tissue map and Regions of Interests (ROI) on it are predicted from other reliable anatomies. The vertex pair-wise distance between the predicted vertex and the true one within the abnormal region is expected to be larger than that of the vertex in normal brain region. Change of white matter/gray matter ratio within a spherical region is used to identify the direction of vertex displacement. In this way, the severity of brain atrophy can be defined quantitatively by the displacements of those vertices. The proposed predictive modeling method has been evaluated by using both simulated atrophies and MRI images of Alzheimer's disease.

MemBrain: An Easy-to-Use Online Webserver for Transmembrane Protein Structure Prediction

NASA Astrophysics Data System (ADS)

Yin, Xi; Yang, Jing; Xiao, Feng; Yang, Yang; Shen, Hong-Bin

2018-03-01

Membrane proteins are an important kind of proteins embedded in the membranes of cells and play crucial roles in living organisms, such as ion channels, transporters, receptors. Because it is difficult to determinate the membrane protein's structure by wet-lab experiments, accurate and fast amino acid sequence-based computational methods are highly desired. In this paper, we report an online prediction tool called MemBrain, whose input is the amino acid sequence. MemBrain consists of specialized modules for predicting transmembrane helices, residue-residue contacts and relative accessible surface area of α-helical membrane proteins. MemBrain achieves a prediction accuracy of 97.9% of A TMH, 87.1% of A P, 3.2 ± 3.0 of N-score, 3.1 ± 2.8 of C-score. MemBrain-Contact obtains 62%/64.1% prediction accuracy on training and independent dataset on top L/5 contact prediction, respectively. And MemBrain-Rasa achieves Pearson correlation coefficient of 0.733 and its mean absolute error of 13.593. These prediction results provide valuable hints for revealing the structure and function of membrane proteins. MemBrain web server is free for academic use and available at www.csbio.sjtu.edu.cn/bioinf/MemBrain/. [Figure not available: see fulltext.

What Costs Do Reveal and Moving beyond the Cost Debate: Reply to Einstein and McDaniel (2010)

ERIC Educational Resources Information Center

Smith, Rebekah E.

2010-01-01

Einstein et al. (2005) predicted no cost to an ongoing task when a prospective memory task met certain criteria. Smith, Hunt, McVay, and McConnell (2007) used prospective memory tasks that met these criteria and found a cost to the ongoing task, contrary to Einstein et al.'s prediction. Einstein and McDaniel (2010) correctly noted that there are…

Anti-Müllerian hormone concentrations and antral follicle counts for the prediction of pregnancy outcomes after intrauterine insemination.

PubMed

Moro, Francesca; Tropea, Anna; Scarinci, Elisa; Leoncini, Emanuele; Boccia, Stefania; Federico, Alex; Alesiani, Ornella; Lanzone, Antonio; Apa, Rosanna

2016-04-01

To evaluate anti-Müllerian hormone (AMH) concentrations and antral follicle counts (AFCs) in the prediction of pregnancy outcomes after controlled ovarian stimulation among women undergoing intrauterine insemination. A retrospective study included women with unexplained infertility aged 41years or younger who attended a fertility clinic in Italy between December 2009 and May 2014. Ovarian stimulation was achieved with recombinant follicle-stimulating hormone or highly purified human menopausal gonadotropin. Receiver operating characteristic curves were generated to predict ongoing pregnancy. The primary outcome was the association between AMH/AFC and ongoing pregnancy, and was assessed by logistic regression. Overall, 276 women were included, of whom 43 (15.6%) achieved ongoing pregnancy. Multivariate analysis showed that women with a serum day-3 concentration of AMH higher than 2.3ng/mL were more likely to have ongoing pregnancy than were those with a concentration lower than 2.3ng/mL (odds ratio 5.84, 95% confidence interval 2.38-14.31; P<0.001). No associations were recorded for AFCs. AMH should be used to predict the pregnancy outcome of intrauterine insemination. Copyright © 2015 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.

Humanoid infers Archimedes' principle: understanding physical relations and object affordances through cumulative learning experiences

PubMed Central

2016-01-01

Emerging studies indicate that several species such as corvids, apes and children solve ‘The Crow and the Pitcher’ task (from Aesop's Fables) in diverse conditions. Hidden beneath this fascinating paradigm is a fundamental question: by cumulatively interacting with different objects, how can an agent abstract the underlying cause–effect relations to predict and creatively exploit potential affordances of novel objects in the context of sought goals? Re-enacting this Aesop's Fable task on a humanoid within an open-ended ‘learning–prediction–abstraction’ loop, we address this problem and (i) present a brain-guided neural framework that emulates rapid one-shot encoding of ongoing experiences into a long-term memory and (ii) propose four task-agnostic learning rules (elimination, growth, uncertainty and status quo) that correlate predictions from remembered past experiences with the unfolding present situation to gradually abstract the underlying causal relations. Driven by the proposed architecture, the ensuing robot behaviours illustrated causal learning and anticipation similar to natural agents. Results further demonstrate that by cumulatively interacting with few objects, the predictions of the robot in case of novel objects converge close to the physical law, i.e. the Archimedes principle: this being independent of both the objects explored during learning and the order of their cumulative exploration. PMID:27466440

Immediate, irreversible, posttraumatic coma: a review indicating that bilateral brainstem injury rather than widespread hemispheric damage is essential for its production.

PubMed

Rosenblum, William I

2015-03-01

Traumatic brain injury may result in immediate long-lasting coma. Much attention has been given to predicting this outcome from the initial examination because these predictions can guide future treatment and interactions with the patient's family. Reports of diffuse axonal injury in these cases have ascribed the coma to widespread damage in the deep white matter that disconnects the hemispheres from the ascending arousal system (AAS). However, brainstem lesions are also present in such cases, and the AAS may be interrupted at the brainstem level. This review examines autopsy and imaging literature that assesses the presence, extent, and predictive value of lesions in both sites. The evidence suggests that diffuse injury to the deep white matter is not the usual cause of immediate long-lasting posttraumatic coma. Instead, brainstem lesions in the rostral pons or midbrain are almost always the cause but only if the lesions are bilateral. Moreover, recovery is possible if critical brainstem inputs to the AAS are spared. The precise localization of the latter is subject to ongoing investigation with advanced imaging techniques using magnets of very high magnetic gradients. Limited availability of this equipment plus the need to verify the findings continue to require meticulous autopsy examination.

Brain age predicts mortality

PubMed Central

Cole, J H; Ritchie, S J; Bastin, M E; Valdés Hernández, M C; Muñoz Maniega, S; Royle, N; Corley, J; Pattie, A; Harris, S E; Zhang, Q; Wray, N R; Redmond, P; Marioni, R E; Starr, J M; Cox, S R; Wardlaw, J M; Sharp, D J; Deary, I J

2018-01-01

Age-associated disease and disability are placing a growing burden on society. However, ageing does not affect people uniformly. Hence, markers of the underlying biological ageing process are needed to help identify people at increased risk of age-associated physical and cognitive impairments and ultimately, death. Here, we present such a biomarker, ‘brain-predicted age’, derived using structural neuroimaging. Brain-predicted age was calculated using machine-learning analysis, trained on neuroimaging data from a large healthy reference sample (N=2001), then tested in the Lothian Birth Cohort 1936 (N=669), to determine relationships with age-associated functional measures and mortality. Having a brain-predicted age indicative of an older-appearing brain was associated with: weaker grip strength, poorer lung function, slower walking speed, lower fluid intelligence, higher allostatic load and increased mortality risk. Furthermore, while combining brain-predicted age with grey matter and cerebrospinal fluid volumes (themselves strong predictors) not did improve mortality risk prediction, the combination of brain-predicted age and DNA-methylation-predicted age did. This indicates that neuroimaging and epigenetics measures of ageing can provide complementary data regarding health outcomes. Our study introduces a clinically-relevant neuroimaging ageing biomarker and demonstrates that combining distinct measurements of biological ageing further helps to determine risk of age-related deterioration and death. PMID:28439103

Quantitative structural MRI for early detection of Alzheimer’s disease

PubMed Central

McEvoy, Linda K; Brewer, James B

2011-01-01

Alzheimer’s disease (AD) is a common progressive neurodegenerative disorder that is not currently diagnosed until a patient reaches the stage of dementia. There is a pressing need to identify AD at an earlier stage, so that treatment, when available, can begin early. Quantitative structural MRI is sensitive to the neurodegeneration that occurs in mild and preclinical AD, and is predictive of decline to dementia in individuals with mild cognitive impairment. Objective evidence of ongoing brain atrophy will be critical for risk/benefit decisions once potentially aggressive, disease-modifying treatments become available. Recent advances have paved the way for the use of quantitative structural MRI in clinical practice, and initial clinical use has been promising. However, further experience with these measures in the relatively unselected patient populations seen in clinical practice is needed to complete translation of the recent enormous advances in scientific knowledge of AD into the clinical realm. PMID:20977326

Theta oscillations locked to intended actions rhythmically modulate perception.

PubMed

Tomassini, Alice; Ambrogioni, Luca; Medendorp, W Pieter; Maris, Eric

2017-07-07

Ongoing brain oscillations are known to influence perception, and to be reset by exogenous stimulations. Voluntary action is also accompanied by prominent rhythmic activity, and recent behavioral evidence suggests that this might be coupled with perception. Here, we reveal the neurophysiological underpinnings of this sensorimotor coupling in humans. We link the trial-by-trial dynamics of EEG oscillatory activity during movement preparation to the corresponding dynamics in perception, for two unrelated visual and motor tasks. The phase of theta oscillations (~4 Hz) predicts perceptual performance, even >1 s before movement. Moreover, theta oscillations are phase-locked to the onset of the movement. Remarkably, the alignment of theta phase and its perceptual relevance unfold with similar non-monotonic profiles, suggesting their relatedness. The present work shows that perception and movement initiation are automatically synchronized since the early stages of motor planning through neuronal oscillatory activity in the theta range.

Real-time fMRI: a tool for local brain regulation.

PubMed

Caria, Andrea; Sitaram, Ranganatha; Birbaumer, Niels

2012-10-01

Real-time fMRI permits simultaneous measurement and observation of brain activity during an ongoing task. One of the most challenging applications of real-time fMRI in neuroscientific and clinical research is the possibility of acquiring volitional control of localized brain activity using real-time fMRI-based neurofeedback protocols. Real-time fMRI allows the experimenter to noninvasively manipulate brain activity as an independent variable to observe the effects on behavior. Real-time fMRI neurofeedback studies demonstrated that learned control of the local brain activity leads to specific changes in behavior. Here, the authors describe the implementation and application of real-time fMRI with particular emphasis on the self-regulation of local brain activity and the investigation of brain-function relationships. Real-time fMRI represents a promising new approach to cognitive neuroscience that could complement traditional neuroimaging techniques by providing more causal insights into the functional role of circumscribed brain regions in behavior.

The Nervous System and Metabolic Dysregulation: Emerging Evidence Converges on Ketogenic Diet Therapy

PubMed Central

Ruskin, David N.; Masino, Susan A.

2012-01-01

A link between metabolism and brain function is clear. Since ancient times, epileptic seizures were noted as treatable with fasting, and historical observations of the therapeutic benefits of fasting on epilepsy were confirmed nearly 100 years ago. Shortly thereafter a high fat, low-carbohydrate ketogenic diet (KD) debuted as a therapy to reduce seizures. This strict regimen could mimic the metabolic effects of fasting while allowing adequate caloric intake for ongoing energy demands. Today, KD therapy, which forces predominantly ketone-based rather than glucose-based metabolism, is now well-established as highly successful in reducing seizures. Cellular metabolic dysfunction in the nervous system has been recognized as existing side-by-side with nervous system disorders – although often with much less obvious cause-and-effect as the relationship between fasting and seizures. Rekindled interest in metabolic and dietary therapies for brain disorders complements new insight into their mechanisms and broader implications. Here we describe the emerging relationship between a KD and adenosine as a way to reset brain metabolism and neuronal activity and disrupt a cycle of dysfunction. We also provide an overview of the effects of a KD on cognition and recent data on the effects of a KD on pain, and explore the relative time course quantified among hallmark metabolic changes, altered neuron function and altered animal behavior assessed after diet administration. We predict continued applications of metabolic therapies in treating dysfunction including and beyond the nervous system. PMID:22470316

Effects of global warming on fish reproductive endocrine axis, with special emphasis in pejerrey Odontesthes bonariensis.

PubMed

Miranda, Leandro Andrés; Chalde, Tomás; Elisio, Mariano; Strüssmann, Carlos Augusto

2013-10-01

The ongoing of global warming trend has led to an increase in temperature of several water bodies. Reproduction in fish, compared with other physiological processes, only occurs in a bounded temperature range; therefore, small changes in water temperature could significantly affect this process. This review provides evidence that fish reproduction may be directly affected by further global warming and that abnormal high water temperature impairs the expression of important genes throughout the brain-pituitary-gonad axis. In all fishes studied, gonads seem to be the organ more readily damaged by heat treatments through the inhibition of the gene expression and subsequent synthesis of different gonadal steroidogenic enzymes. In view of the feedback role of sex steroids upon the synthesis and release of GnRH and GtHs in fish, it is possible that the inhibition observed at brain and pituitary levels in treated fish is consequence of the sharp decrease in plasma steroids levels. Results of in vitro studies on the inhibition of pejerrey gonad aromatase expression by high temperature corroborate that ovary functions are directly disrupted by high temperature independently of the brain-pituitary axis. For the reproductive responses obtained in laboratory fish studies, it is plausible to predict changes in the timing and magnitude of reproductive activity or even the total failure of spawning season may occur in warm years, reducing annual reproductive output and affecting future populations. Copyright © 2013 Elsevier Inc. All rights reserved.

Molecular markers in pediatric neuro-oncology

PubMed Central

Ichimura, Koichi; Nishikawa, Ryo; Matsutani, Masao

2012-01-01

Pediatric molecular neuro-oncology is a fast developing field. A multitude of molecular profiling studies in recent years has unveiled a number of genetic abnormalities unique to pediatric brain tumors. It has now become clear that brain tumors that arise in children have distinct pathogenesis and biology, compared with their adult counterparts, even for those with indistinguishable histopathology. Some of the molecular features are so specific to a particular type of tumors, such as the presence of the KIAA1549-BRAF fusion gene for pilocytic astrocytomas or SMARCB1 mutations for atypical teratoid/rhabdoid tumors, that they could practically serve as a diagnostic marker on their own. Expression profiling has resolved the existence of 4 molecular subgroups in medulloblastomas, which positively translated into improved prognostication for the patients. The currently available molecular markers, however, do not cover all tumors even within a single tumor entity. The molecular pathogenesis of a large number of pediatric brain tumors is still unaccounted for, and the hierarchy of tumors is likely to be more complex and intricate than currently acknowledged. One of the main tasks of future molecular analyses in pediatric neuro-oncology, including the ongoing genome sequencing efforts, is to elucidate the biological basis of those orphan tumors. The ultimate goal of molecular diagnostics is to accurately predict the clinical and biological behavior of any tumor by means of their molecular characteristics, which is hoped to eventually pave the way for individualized treatment. PMID:23095836

Evidence from a rare case study for Hebbian-like changes in structural connectivity induced by long-term deep brain stimulation.

PubMed

van Hartevelt, Tim J; Cabral, Joana; Møller, Arne; FitzGerald, James J; Green, Alexander L; Aziz, Tipu Z; Deco, Gustavo; Kringelbach, Morten L

2015-01-01

It is unclear whether Hebbian-like learning occurs at the level of long-range white matter connections in humans, i.e., where measurable changes in structural connectivity (SC) are correlated with changes in functional connectivity. However, the behavioral changes observed after deep brain stimulation (DBS) suggest the existence of such Hebbian-like mechanisms occurring at the structural level with functional consequences. In this rare case study, we obtained the full network of white matter connections of one patient with Parkinson's disease (PD) before and after long-term DBS and combined it with a computational model of ongoing activity to investigate the effects of DBS-induced long-term structural changes. The results show that the long-term effects of DBS on resting-state functional connectivity is best obtained in the computational model by changing the structural weights from the subthalamic nucleus (STN) to the putamen and the thalamus in a Hebbian-like manner. Moreover, long-term DBS also significantly changed the SC towards normality in terms of model-based measures of segregation and integration of information processing, two key concepts of brain organization. This novel approach using computational models to model the effects of Hebbian-like changes in SC allowed us to causally identify the possible underlying neural mechanisms of long-term DBS using rare case study data. In time, this could help predict the efficacy of individual DBS targeting and identify novel DBS targets.

Time course of clinical change following neurofeedback.

PubMed

Rance, Mariela; Walsh, Christopher; Sukhodolsky, Denis G; Pittman, Brian; Qiu, Maolin; Kichuk, Stephen A; Wasylink, Suzanne; Koller, William N; Bloch, Michael; Gruner, Patricia; Scheinost, Dustin; Pittenger, Christopher; Hampson, Michelle

2018-05-02

Neurofeedback - learning to modulate brain function through real-time monitoring of current brain state - is both a powerful method to perturb and probe brain function and an exciting potential clinical tool. For neurofeedback effects to be useful clinically, they must persist. Here we examine the time course of symptom change following neurofeedback in two clinical populations, combining data from two ongoing neurofeedback studies. This analysis reveals a shared pattern of symptom change, in which symptoms continue to improve for weeks after neurofeedback. This time course has several implications for future neurofeedback studies. Most neurofeedback studies are not designed to test an intervention with this temporal pattern of response. We recommend that new studies incorporate regular follow-up of subjects for weeks or months after the intervention to ensure that the time point of greatest effect is sampled. Furthermore, this time course of continuing clinical change has implications for crossover designs, which may attribute long-term, ongoing effects of real neurofeedback to the control intervention that follows. Finally, interleaving neurofeedback sessions with assessments and examining when clinical improvement peaks may not be an appropriate approach to determine the optimal number of sessions for an application. Copyright © 2018 Elsevier Inc. All rights reserved.

Novel treatment strategies for brain tumors and metastases

PubMed Central

El-Habashy, Salma E.; Nazief, Alaa M.; Adkins, Chris E.; Wen, Ming Ming; El-Kamel, Amal H.; Hamdan, Ahmed M.; Hanafy, Amira S.; Terrell, Tori O.; Mohammad, Afroz S.; Lockman, Paul R.; Nounou, Mohamed Ismail

2015-01-01

This review summarizes patent applications in the past 5 years for the management of brain tumors and metastases. Most of the recent patents discuss one of the following strategies: the development of new drug entities that specifically target the brain cells, the blood–brain barrier and the tumor cells, tailor-designing a novel carrier system that is able to perform multitasks and multifunction as a drug carrier, targeting vehicle and even as a diagnostic tool, direct conjugation of a US FDA approved drug with a targeting moiety, diagnostic moiety or PK modifying moiety, or the use of innovative nontraditional approaches such as genetic engineering, stem cells and vaccinations. Until now, there has been no optimal strategy to deliver therapeutic agents to the CNS for the treatment of brain tumors and metastases. Intensive research efforts are actively ongoing to take brain tumor targeting, and novel and targeted CNS delivery systems to potential clinical application. PMID:24998288

How environment and genes shape the adolescent brain.

PubMed

Paus, Tomáš

2013-07-01

This article is part of a Special Issue "Puberty and Adolescence". This review provides a conceptual framework for the study of factors--in our genes and environment--that shape the adolescent brain. I start by pointing out that brain phenotypes obtained with magnetic resonance imaging are complex traits reflecting the interplay of genes and the environment. In some cases, variations in the structural phenotypes observed during adolescence have their origin in the pre-natal or early post-natal periods. I then emphasize the bidirectional nature of brain-behavior relationships observed during this period of human development, where function may be more likely to influence structure rather than vice versa. In the main part of this article, I review our ongoing work on the influence of gonadal hormones on the adolescent brain. I also discuss the importance of social context and brain plasticity on shaping the relevant neural circuits. Copyright © 2013 Elsevier Inc. All rights reserved.

Anatomical connectivity influences both intra- and inter-brain synchronizations.

PubMed

Dumas, Guillaume; Chavez, Mario; Nadel, Jacqueline; Martinerie, Jacques

2012-01-01

Recent development in diffusion spectrum brain imaging combined to functional simulation has the potential to further our understanding of how structure and dynamics are intertwined in the human brain. At the intra-individual scale, neurocomputational models have already started to uncover how the human connectome constrains the coordination of brain activity across distributed brain regions. In parallel, at the inter-individual scale, nascent social neuroscience provides a new dynamical vista of the coupling between two embodied cognitive agents. Using EEG hyperscanning to record simultaneously the brain activities of subjects during their ongoing interaction, we have previously demonstrated that behavioral synchrony correlates with the emergence of inter-brain synchronization. However, the functional meaning of such synchronization remains to be specified. Here, we use a biophysical model to quantify to what extent inter-brain synchronizations are related to the anatomical and functional similarity of the two brains in interaction. Pairs of interacting brains were numerically simulated and compared to real data. Results show a potential dynamical property of the human connectome to facilitate inter-individual synchronizations and thus may partly account for our propensity to generate dynamical couplings with others.

Prediction of standard-dose brain PET image by using MRI and low-dose brain [18F]FDG PET images.

PubMed

Kang, Jiayin; Gao, Yaozong; Shi, Feng; Lalush, David S; Lin, Weili; Shen, Dinggang

2015-09-01

Positron emission tomography (PET) is a nuclear medical imaging technology that produces 3D images reflecting tissue metabolic activity in human body. PET has been widely used in various clinical applications, such as in diagnosis of brain disorders. High-quality PET images play an essential role in diagnosing brain diseases/disorders. In practice, in order to obtain high-quality PET images, a standard-dose radionuclide (tracer) needs to be used and injected into a living body. As a result, it will inevitably increase the patient's exposure to radiation. One solution to solve this problem is predicting standard-dose PET images using low-dose PET images. As yet, no previous studies with this approach have been reported. Accordingly, in this paper, the authors propose a regression forest based framework for predicting a standard-dose brain [(18)F]FDG PET image by using a low-dose brain [(18)F]FDG PET image and its corresponding magnetic resonance imaging (MRI) image. The authors employ a regression forest for predicting the standard-dose brain [(18)F]FDG PET image by low-dose brain [(18)F]FDG PET and MRI images. Specifically, the proposed method consists of two main steps. First, based on the segmented brain tissues (i.e., cerebrospinal fluid, gray matter, and white matter) in the MRI image, the authors extract features for each patch in the brain image from both low-dose PET and MRI images to build tissue-specific models that can be used to initially predict standard-dose brain [(18)F]FDG PET images. Second, an iterative refinement strategy, via estimating the predicted image difference, is used to further improve the prediction accuracy. The authors evaluated their algorithm on a brain dataset, consisting of 11 subjects with MRI, low-dose PET, and standard-dose PET images, using leave-one-out cross-validations. The proposed algorithm gives promising results with well-estimated standard-dose brain [(18)F]FDG PET image and substantially enhanced image quality of low-dose brain [(18)F]FDG PET image. In this paper, the authors propose a framework to generate standard-dose brain [(18)F]FDG PET image using low-dose brain [(18)F]FDG PET and MRI images. Both the visual and quantitative results indicate that the standard-dose brain [(18)F]FDG PET can be well-predicted using MRI and low-dose brain [(18)F]FDG PET.

Prediction of standard-dose brain PET image by using MRI and low-dose brain [18F]FDG PET images

PubMed Central

Kang, Jiayin; Gao, Yaozong; Shi, Feng; Lalush, David S.; Lin, Weili; Shen, Dinggang

2015-01-01

Purpose: Positron emission tomography (PET) is a nuclear medical imaging technology that produces 3D images reflecting tissue metabolic activity in human body. PET has been widely used in various clinical applications, such as in diagnosis of brain disorders. High-quality PET images play an essential role in diagnosing brain diseases/disorders. In practice, in order to obtain high-quality PET images, a standard-dose radionuclide (tracer) needs to be used and injected into a living body. As a result, it will inevitably increase the patient’s exposure to radiation. One solution to solve this problem is predicting standard-dose PET images using low-dose PET images. As yet, no previous studies with this approach have been reported. Accordingly, in this paper, the authors propose a regression forest based framework for predicting a standard-dose brain [18F]FDG PET image by using a low-dose brain [18F]FDG PET image and its corresponding magnetic resonance imaging (MRI) image. Methods: The authors employ a regression forest for predicting the standard-dose brain [18F]FDG PET image by low-dose brain [18F]FDG PET and MRI images. Specifically, the proposed method consists of two main steps. First, based on the segmented brain tissues (i.e., cerebrospinal fluid, gray matter, and white matter) in the MRI image, the authors extract features for each patch in the brain image from both low-dose PET and MRI images to build tissue-specific models that can be used to initially predict standard-dose brain [18F]FDG PET images. Second, an iterative refinement strategy, via estimating the predicted image difference, is used to further improve the prediction accuracy. Results: The authors evaluated their algorithm on a brain dataset, consisting of 11 subjects with MRI, low-dose PET, and standard-dose PET images, using leave-one-out cross-validations. The proposed algorithm gives promising results with well-estimated standard-dose brain [18F]FDG PET image and substantially enhanced image quality of low-dose brain [18F]FDG PET image. Conclusions: In this paper, the authors propose a framework to generate standard-dose brain [18F]FDG PET image using low-dose brain [18F]FDG PET and MRI images. Both the visual and quantitative results indicate that the standard-dose brain [18F]FDG PET can be well-predicted using MRI and low-dose brain [18F]FDG PET. PMID:26328979

Prediction of standard-dose brain PET image by using MRI and low-dose brain [{sup 18}F]FDG PET images

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

Kang, Jiayin; Gao, Yaozong; Shi, Feng

Purpose: Positron emission tomography (PET) is a nuclear medical imaging technology that produces 3D images reflecting tissue metabolic activity in human body. PET has been widely used in various clinical applications, such as in diagnosis of brain disorders. High-quality PET images play an essential role in diagnosing brain diseases/disorders. In practice, in order to obtain high-quality PET images, a standard-dose radionuclide (tracer) needs to be used and injected into a living body. As a result, it will inevitably increase the patient’s exposure to radiation. One solution to solve this problem is predicting standard-dose PET images using low-dose PET images. Asmore » yet, no previous studies with this approach have been reported. Accordingly, in this paper, the authors propose a regression forest based framework for predicting a standard-dose brain [{sup 18}F]FDG PET image by using a low-dose brain [{sup 18}F]FDG PET image and its corresponding magnetic resonance imaging (MRI) image. Methods: The authors employ a regression forest for predicting the standard-dose brain [{sup 18}F]FDG PET image by low-dose brain [{sup 18}F]FDG PET and MRI images. Specifically, the proposed method consists of two main steps. First, based on the segmented brain tissues (i.e., cerebrospinal fluid, gray matter, and white matter) in the MRI image, the authors extract features for each patch in the brain image from both low-dose PET and MRI images to build tissue-specific models that can be used to initially predict standard-dose brain [{sup 18}F]FDG PET images. Second, an iterative refinement strategy, via estimating the predicted image difference, is used to further improve the prediction accuracy. Results: The authors evaluated their algorithm on a brain dataset, consisting of 11 subjects with MRI, low-dose PET, and standard-dose PET images, using leave-one-out cross-validations. The proposed algorithm gives promising results with well-estimated standard-dose brain [{sup 18}F]FDG PET image and substantially enhanced image quality of low-dose brain [{sup 18}F]FDG PET image. Conclusions: In this paper, the authors propose a framework to generate standard-dose brain [{sup 18}F]FDG PET image using low-dose brain [{sup 18}F]FDG PET and MRI images. Both the visual and quantitative results indicate that the standard-dose brain [{sup 18}F]FDG PET can be well-predicted using MRI and low-dose brain [{sup 18}F]FDG PET.« less

Animal imaging studies of potential brain damage

NASA Astrophysics Data System (ADS)

Gatley, S. J.; Vazquez, M. E.; Rice, O.

To date, animal studies have not been able to predict the likelihood of problems in human neurological health due to HZE particle exposure during space missions outside the Earth's magnetosphere. In ongoing studies in mice, we have demonstrated that cocaine stimulated locomotor activity is reduced by a moderate dose (120 cGy) of 1 GeV 56Fe particles. We postulate that imaging experiments in animals may provide more sensitive and earlier indicators of damage due to HZE particles than behavioral tests. Since the small size of the mouse brain is not well suited to the spatial resolution offered by microPET, we are now repeating some of our studies in a rat model. We anticipate that this will enable us to identify imaging correlates of behavioral endpoints. A specific hypothesis of our studies is that changes in the metabolic rate for glucose in striatum of animals will be correlated with alterations in locomotor activity. We will also evaluate whether the neuroprotective drug L-deprenyl reduces the effect of radiation on locomotor activity. In addition, we will conduct microPET studies of brain monoamine oxidase A and monoamine oxidase B in rats before and at various times after irradiation with HZE particles. The hypothesis is that monoamine oxidase A, which is located in nerve terminals, will be unchanged or decreased after irradiation, while monoamine oxidase B, which is located in glial cells, will be increased after irradiation. Neurochemical effects that could be measured using PET could in principle be applied in astronauts, in terms of detecting and monitoring subtle neurological damage that might have occurred during long space missions. More speculative uses of PET are in screening candidates for prolonged space missions (for example, for adequate reserve in critical brain circuits) and in optimizing medications to treat impairments after missions.

Perfusion Neuroimaging Abnormalities Alone Distinguish National Football League Players from a Healthy Population.

PubMed

Amen, Daniel G; Willeumier, Kristen; Omalu, Bennet; Newberg, Andrew; Raghavendra, Cauligi; Raji, Cyrus A

2016-04-25

National Football League (NFL) players are exposed to multiple head collisions during their careers. Increasing awareness of the adverse long-term effects of repetitive head trauma has raised substantial concern among players, medical professionals, and the general public. To determine whether low perfusion in specific brain regions on neuroimaging can accurately separate professional football players from healthy controls. A cohort of retired and current NFL players (n = 161) were recruited in a longitudinal study starting in 2009 with ongoing interval follow up. A healthy control group (n = 124) was separately recruited for comparison. Assessments included medical examinations, neuropsychological tests, and perfusion neuroimaging with single photon emission computed tomography (SPECT). Perfusion estimates of each scan were quantified using a standard atlas. We hypothesized that hypoperfusion particularly in the orbital frontal, anterior cingulate, anterior temporal, hippocampal, amygdala, insular, caudate, superior/mid occipital, and cerebellar sub-regions alone would reliably separate controls from NFL players. Cerebral perfusion differences were calculated using a one-way ANOVA and diagnostic separation was determined with discriminant and automatic linear regression predictive models. NFL players showed lower cerebral perfusion on average (p < 0.01) in 36 brain regions. The discriminant analysis subsequently distinguished NFL players from controls with 90% sensitivity, 86% specificity, and 94% accuracy (95% CI 95-99). Automatic linear modeling achieved similar results. Inclusion of age and clinical co-morbidities did not improve diagnostic classification. Specific brain regions commonly damaged in traumatic brain injury show abnormally low perfusion on SPECT in professional NFL players. These same regions alone can distinguish this group from healthy subjects with high diagnostic accuracy. This study carries implications for the neurological safety of NFL players.

Perfusion Neuroimaging Abnormalities Alone Distinguish National Football League Players from a Healthy Population

PubMed Central

Amen, Daniel G.; Willeumier, Kristen; Omalu, Bennet; Newberg, Andrew; Raghavendra, Cauligi; Raji, Cyrus A.

2016-01-01

Background: National Football League (NFL) players are exposed to multiple head collisions during their careers. Increasing awareness of the adverse long-term effects of repetitive head trauma has raised substantial concern among players, medical professionals, and the general public. Objective: To determine whether low perfusion in specific brain regions on neuroimaging can accurately separate professional football players from healthy controls. Method: A cohort of retired and current NFL players (n = 161) were recruited in a longitudinal study starting in 2009 with ongoing interval follow up. A healthy control group (n = 124) was separately recruited for comparison. Assessments included medical examinations, neuropsychological tests, and perfusion neuroimaging with single photon emission computed tomography (SPECT). Perfusion estimates of each scan were quantified using a standard atlas. We hypothesized that hypoperfusion particularly in the orbital frontal, anterior cingulate, anterior temporal, hippocampal, amygdala, insular, caudate, superior/mid occipital, and cerebellar sub-regions alone would reliably separate controls from NFL players. Cerebral perfusion differences were calculated using a one-way ANOVA and diagnostic separation was determined with discriminant and automatic linear regression predictive models. Results: NFL players showed lower cerebral perfusion on average (p < 0.01) in 36 brain regions. The discriminant analysis subsequently distinguished NFL players from controls with 90% sensitivity, 86% specificity, and 94% accuracy (95% CI 95-99). Automatic linear modeling achieved similar results. Inclusion of age and clinical co-morbidities did not improve diagnostic classification. Conclusion: Specific brain regions commonly damaged in traumatic brain injury show abnormally low perfusion on SPECT in professional NFL players. These same regions alone can distinguish this group from healthy subjects with high diagnostic accuracy. This study carries implications for the neurological safety of NFL players. PMID:27128374

Psychoradiology: The Frontier of Neuroimaging in Psychiatry

PubMed Central

Lui, Su; Zhou, Xiaohong Joe; Sweeney, John A.

2016-01-01

Unlike neurologic conditions, such as brain tumors, dementia, and stroke, the neural mechanisms for all psychiatric disorders remain unclear. A large body of research obtained with structural and functional magnetic resonance imaging, positron emission tomography/single photon emission computed tomography, and optical imaging has demonstrated regional and illness-specific brain changes at the onset of psychiatric disorders and in individuals at risk for such disorders. Many studies have shown that psychiatric medications induce specific measurable changes in brain anatomy and function that are related to clinical outcomes. As a result, a new field of radiology, termed psychoradiology, seems primed to play a major clinical role in guiding diagnostic and treatment planning decisions in patients with psychiatric disorders. This article will present the state of the art in this area, as well as perspectives regarding preparations in the field of radiology for its evolution. Furthermore, this article will (a) give an overview of the imaging and analysis methods for psychoradiology; (b) review the most robust and important radiologic findings and their potential clinical value from studies of major psychiatric disorders, such as depression and schizophrenia; and (c) describe the main challenges and future directions in this field. An ongoing and iterative process of developing biologically based nomenclatures with which to delineate psychiatric disorders and translational research to predict and track response to different therapeutic drugs is laying the foundation for a shift in diagnostic practice in psychiatry from a psychologic symptom–based approach to an imaging-based approach over the next generation. This shift will require considerable innovations for the acquisition, analysis, and interpretation of brain images, all of which will undoubtedly require the active involvement of radiologists. © RSNA, 2016 Online supplemental material is available for this article. PMID:27755933

Long-range functional interactions of anterior insula and medial frontal cortex are differently modulated by visuospatial and inductive reasoning tasks.

PubMed

Ebisch, Sjoerd J H; Mantini, Dante; Romanelli, Roberta; Tommasi, Marco; Perrucci, Mauro G; Romani, Gian Luca; Colom, Roberto; Saggino, Aristide

2013-09-01

The brain is organized into functionally specific networks as characterized by intrinsic functional relationships within discrete sets of brain regions. However, it is poorly understood whether such functional networks are dynamically organized according to specific task-states. The anterior insular cortex (aIC)-dorsal anterior cingulate cortex (dACC)/medial frontal cortex (mFC) network has been proposed to play a central role in human cognitive abilities. The present functional magnetic resonance imaging (fMRI) study aimed at testing whether functional interactions of the aIC-dACC/mFC network in terms of temporally correlated patterns of neural activity across brain regions are dynamically modulated by transitory, ongoing task demands. For this purpose, functional interactions of the aIC-dACC/mFC network are compared during two distinguishable fluid reasoning tasks, Visualization and Induction. The results show an increased functional coupling of bilateral aIC with visual cortices in the occipital lobe during the Visualization task, whereas coupling of mFC with right anterior frontal cortex was enhanced during the Induction task. These task-specific modulations of functional interactions likely reflect ability related neural processing. Furthermore, functional connectivity strength between right aIC and right dACC/mFC reliably predicts general task performance. The findings suggest that the analysis of long-range functional interactions may provide complementary information about brain-behavior relationships. On the basis of our results, it is proposed that the aIC-dACC/mFC network contributes to the integration of task-common and task-specific information based on its within-network as well as its between-network dynamic functional interactions. Copyright © 2013 Elsevier Inc. All rights reserved.

Adolescent neural response to reward is related to participant sex and task motivation.

PubMed

Alarcón, Gabriela; Cservenka, Anita; Nagel, Bonnie J

2017-02-01

Risky decision making is prominent during adolescence, perhaps contributed to by heightened sensation seeking and ongoing maturation of reward and dopamine systems in the brain, which are, in part, modulated by sex hormones. In this study, we examined sex differences in the neural substrates of reward sensitivity during a risky decision-making task and hypothesized that compared with girls, boys would show heightened brain activation in reward-relevant regions, particularly the nucleus accumbens, during reward receipt. Further, we hypothesized that testosterone and estradiol levels would mediate this sex difference. Moreover, we predicted boys would make more risky choices on the task. While boys showed increased nucleus accumbens blood oxygen level-dependent (BOLD) response relative to girls, sex hormones did not mediate this effect. As predicted, boys made a higher percentage of risky decisions during the task. Interestingly, boys also self-reported more motivation to perform well and earn money on the task, while girls self-reported higher state anxiety prior to the scan session. Motivation to earn money partially mediated the effect of sex on nucleus accumbens activity during reward. Previous research shows that increased motivation and salience of reinforcers is linked with more robust striatal BOLD response, therefore psychosocial factors, in addition to sex, may play an important role in reward sensitivity. Elucidating neurobiological mechanisms that support adolescent sex differences in risky decision making has important implications for understanding individual differences that lead to advantageous and adverse behaviors that affect health outcomes. Copyright © 2016 Elsevier Inc. All rights reserved.

Neural oscillatory deficits in schizophrenia predict behavioral and neurocognitive impairments

PubMed Central

Martínez, Antígona; Gaspar, Pablo A.; Hillyard, Steven A.; Bickel, Stephan; Lakatos, Peter; Dias, Elisa C.; Javitt, Daniel C.

2015-01-01

Paying attention to visual stimuli is typically accompanied by event-related desynchronizations (ERD) of ongoing alpha (7–14 Hz) activity in visual cortex. The present study used time-frequency based analyses to investigate the role of impaired alpha ERD in visual processing deficits in schizophrenia (Sz). Subjects viewed sinusoidal gratings of high (HSF) and low (LSF) spatial frequency (SF) designed to test functioning of the parvo- vs. magnocellular pathways, respectively. Patients with Sz and healthy controls paid attention selectively to either the LSF or HSF gratings which were presented in random order. Event-related brain potentials (ERPs) were recorded to all stimuli. As in our previous study, it was found that Sz patients were selectively impaired at detecting LSF target stimuli and that ERP amplitudes to LSF stimuli were diminished, both for the early sensory-evoked components and for the attend minus unattend difference component (the Selection Negativity), which is generally regarded as a specific index of feature-selective attention. In the time-frequency domain, the differential ERP deficits to LSF stimuli were echoed in a virtually absent theta-band phase locked response to both unattended and attended LSF stimuli (along with relatively intact theta-band activity for HSF stimuli). In contrast to the theta-band evoked responses which were tightly stimulus locked, stimulus-induced desynchronizations of ongoing alpha activity were not tightly stimulus locked and were apparent only in induced power analyses. Sz patients were significantly impaired in the attention-related modulation of ongoing alpha activity for both HSF and LSF stimuli. These deficits correlated with patients’ behavioral deficits in visual information processing as well as with visually based neurocognitive deficits. These findings suggest an additional, pathway-independent, mechanism by which deficits in early visual processing contribute to overall cognitive impairment in Sz. PMID:26190988

Subcortical processing of speech regularities underlies reading and music aptitude in children.

PubMed

Strait, Dana L; Hornickel, Jane; Kraus, Nina

2011-10-17

Neural sensitivity to acoustic regularities supports fundamental human behaviors such as hearing in noise and reading. Although the failure to encode acoustic regularities in ongoing speech has been associated with language and literacy deficits, how auditory expertise, such as the expertise that is associated with musical skill, relates to the brainstem processing of speech regularities is unknown. An association between musical skill and neural sensitivity to acoustic regularities would not be surprising given the importance of repetition and regularity in music. Here, we aimed to define relationships between the subcortical processing of speech regularities, music aptitude, and reading abilities in children with and without reading impairment. We hypothesized that, in combination with auditory cognitive abilities, neural sensitivity to regularities in ongoing speech provides a common biological mechanism underlying the development of music and reading abilities. We assessed auditory working memory and attention, music aptitude, reading ability, and neural sensitivity to acoustic regularities in 42 school-aged children with a wide range of reading ability. Neural sensitivity to acoustic regularities was assessed by recording brainstem responses to the same speech sound presented in predictable and variable speech streams. Through correlation analyses and structural equation modeling, we reveal that music aptitude and literacy both relate to the extent of subcortical adaptation to regularities in ongoing speech as well as with auditory working memory and attention. Relationships between music and speech processing are specifically driven by performance on a musical rhythm task, underscoring the importance of rhythmic regularity for both language and music. These data indicate common brain mechanisms underlying reading and music abilities that relate to how the nervous system responds to regularities in auditory input. Definition of common biological underpinnings for music and reading supports the usefulness of music for promoting child literacy, with the potential to improve reading remediation.

Immunological thresholds in neurological gene therapy: highly efficient elimination of transduced cells might be related to the specific formation of immunological synapses between T cells and virus-infected brain cells

PubMed Central

Barcia, Carlos; Gerdes, Christian; Xiong, Wei-Dong; Thomas, Clare E.; Liu, Chunyan; Kroeger, Kurt M.; Castro, Maria G.; Lowenstein, Pedro R.

2007-01-01

First-generation adenovirus can be engineered with powerful promoters to drive expression of therapeutic transgenes. Numerous clinical trials for glioblastoma multiforme using first generation adenoviral vectors have either been performed or are ongoing, including an ongoing, Phase III, multicenter trial in Europe and Israel (Ark Therapeutics, Inc.). Although in the absence of anti-adenovirus immune responses expression in the brain lasts 6–18 months, systemic infection with adenovirus induces immune responses that inhibit dramatically therapeutic transgene expression from first generation adenoviral vectors, thus, potentially compromising therapeutic efficacy. Here, we show evidence of an immunization threshold for the dose that generates an immune response strong enough to eliminate transgene expression from the CNS. For the systemic immunization to eliminate transgene expression from the brain, ≥1 × 107 infectious units (iu) of adenovirus need to be used as immunogen. Furthermore, this immune response eliminates >90% of transgene expression from 1 × 107–1 × 10³ iu of vector injected into the striatum 60 days earlier. Importantly, elimination of transgene expression is independent of the nature of the promoter that drives transgene expression and is accompanied by brain infiltration of CD8+ T cells and macrophages. In conclusion, once the threshold for systemic immunization (i.e. 1 × 107 iu) is crossed, the immune response eliminates transgene expression by >90% even from brains that receive as little as 1000 iu of adenoviral vectors, independently of the type of promoter that drives expression. PMID:18084640

Effect of type of cue, type of response, time delay and two different ongoing tasks on prospective memory functioning after acquired brain injury.

PubMed

Raskin, Sarah A; Buckheit, Carol A; Waxman, Amanda

2012-01-01

Failures of prospective memory (PM) are one of the most frequent, and least studied, sequelae of brain injury. PM, also referred to as memory for intentions, is the ability to remember to carry out a future task. Successful completion of a PM task requires the ability to monitor time, keep the action to be performed periodically in awareness, remember the task to be performed, and initiate the action. Although PM has been shown to be a common difficulty after brain injury, it remains unknown which aspects of performance are impaired. In this study, the performance of 25 individuals with brain injury and that of 25 healthy participants were measured separately on the following variables: time until completion of the task, difficulty of the ongoing task being performed while waiting, whether the task to be performed is an action or is verbal, and whether the cue to perform the task is the passing of a particular amount of time (e.g., 10 minutes) or is an external cue (e.g., an alarm sounding). Individuals with brain injury demonstrated impairment compared to healthy adults on virtually all variables. PM performance was also compared to a battery of standard neuropsychological measures of attention, memory, and executive functions, and to self-report measures of PM functioning, in order to determine the underlying cognitive deficits responsible for poor PM performance, if any. PM performance was correlated with measures of executive functioning but not to self-report measures of PM functioning. Implications are discussed in terms of cognitive rehabilitation recommendations.

Inducible Glutamate Oxaloacetate Transaminase as a Therapeutic Target Against Ischemic Stroke

PubMed Central

Khanna, Savita; Briggs, Zachary

2015-01-01

Abstract Significance: Glutamate serves multi-faceted (patho)physiological functions in the central nervous system as the most abundant excitatory neurotransmitter and under pathological conditions as a potent neurotoxin. Regarding the latter, elevated extracellular glutamate is known to play a central role in ischemic stroke brain injury. Recent Advances: Glutamate oxaloacetate transaminase (GOT) has emerged as a new therapeutic target in protecting against ischemic stroke injury. Oxygen-sensitive induction of GOT expression and activity during ischemic stroke lowers glutamate levels at the stroke site while sustaining adenosine triphosphate levels in brain. The energy demands of the brain are among the highest of all organs underscoring the need to quickly mobilize alternative carbon skeletons for metabolism in the absence of glucose during ischemic stroke. Recent work builds on the important observation of Hans Krebs that GOT-mediated metabolism of glutamate generates tri-carboxylic acid (TCA) cycle intermediates in brain tissue. Taken together, outcomes suggest GOT may enable the transformative switch of otherwise excitotoxic glutamate into life-sustaining TCA cycle intermediates during ischemic stroke. Critical Issues: Neuroprotective strategies that focus solely on blocking mechanisms of glutamate-mediated excitotoxicity have historically failed in clinical trials. That GOT can enable glutamate to assume the role of a survival factor represents a paradigm shift necessary to develop the overall significance of glutamate in stroke biology. Future Directions: Ongoing efforts are focused to develop the therapeutic significance of GOT in stroke-affected brain. Small molecules that target induction of GOT expression and activity in the ischemic penumbra are the focus of ongoing studies. Antioxid. Redox Signal. 22, 175–186. PMID:25343301

Predictive value of serum progesterone level on β-hCG check day in women with previous repeated miscarriages after in vitro fertilization.

PubMed

Kim, Yong Jin; Shin, Jung Ho; Hur, Jun Yong; Kim, Hoon; Ku, Seung-Yup; Suh, Chang Suk

2017-01-01

To evaluate the predictive value of the progesterone level at the beta-human chorionic gonadotropin (β-hCG) check day for ongoing pregnancy maintenance in in vitro fertilization (IVF) cycles in women with previous unexplained repeated miscarriages. One hundred and forty-eight women, with visible gestational sac after IVF, were recruited in this observational study. All subjects had unexplained recurrent miscarriages in more than two previous IVF cycles. The progesterone level at the β-hCG check day (i.e. 14 days after oocyte retrieval) was assessed. The area under the curve (AUC) of the progesterone level was evaluated to predict the ongoing pregnancy or miscarriage outcomes. The overall ongoing pregnancy rate was 60.8% (90/148). The cut-off value with β-hCG levels higher than 126.5 mIU/mL and with progesterone levels higher than 25.2 ng/mL could be the predictive factors for ongoing pregnancy maintenance (AUC = 0.788 and 0.826; sensitivity = 0.788 and 0.723; specificity = 0.689 and 0.833; P < 0.0001 and P < 0.0001, respectively). The miscarriage rates were 19.5% (15/77) in the women with β-hCG > 126.5 mIU/mL and 13.0% (10/77) in those with > 25.2 ng/mL. In the comparison of the ROC curves between both values, a similar significance was found. The subjects with β-hCG > 126.5 mIU/mL and progesterone > 25.2 ng/mL showed higher ongoing pregnancy rates [98.0% (49/50) vs. 41.8% (41/98)] than those with β-hCG ≤ 126.5 mIU/mL or progesterone ≤ 25.2 ng/mL. The progesterone level at 14 days after oocyte retrieval can be a good predictive marker for ongoing pregnancy maintenance in women with repeated IVF failure with miscarriage, together with the β-hCG level. The combined cut-off value of progesterone > 25.2 ng/mL and β-hCG > 126.5 mIU/mL may suggest a good prognosis.

Categorization of multiple sclerosis relapse subtypes by B cell profiling in the blood.

PubMed

Hohmann, Christopher; Milles, Bianca; Schinke, Michael; Schroeter, Michael; Ulzheimer, Jochen; Kraft, Peter; Kleinschnitz, Christoph; Lehmann, Paul V; Kuerten, Stefanie

2014-09-16

B cells are attracting increasing attention in the pathogenesis of multiple sclerosis (MS). B cell-targeted therapies with monoclonal antibodies or plasmapheresis have been shown to be successful in a subset of patients. Here, patients with either relapsing-remitting (n = 24) or secondary progressive (n = 6) MS presenting with an acute clinical relapse were screened for their B cell reactivity to brain antigens and were re-tested three to nine months later. Enzyme-linked immunospot technique (ELISPOT) was used to identify brain-reactive B cells in peripheral blood mononuclear cells (PBMC) directly ex vivo and after 96 h of polyclonal stimulation. Clinical severity of symptoms was determined using the Expanded Disability Status Scale (EDSS). Nine patients displayed B cells in the blood producing brain-specific antibodies directly ex vivo. Six patients were classified as B cell positive donors only after polyclonal B cell stimulation. In 15 patients a B cell response to brain antigens was absent. Based on the autoreactive B cell response we categorized MS relapses into three different patterns. Patients who displayed brain-reactive B cell responses both directly ex vivo and after polyclonal stimulation (pattern I) were significantly younger than patients in whom only memory B cell responses were detectable or entirely absent (patterns II and III; p = 0.003). In one patient a conversion to a positive B cell response as measured directly ex vivo and subsequently also after polyclonal stimulation was associated with the development of a clinical relapse. The evaluation of the predictive value of a brain antigen-specific B cell response showed that seven of eight patients (87.5%) with a pattern I response encountered a clinical relapse during the observation period of 10 months, compared to two of five patients (40%) with a pattern II and three of 14 patients (21.4%) with a pattern III response (p = 0.0005; hazard ratio 6.08 (95% confidence interval 1.87-19.77). Our data indicate actively ongoing B cell-mediated immunity against brain antigens in a subset of MS patients that may be causative of clinical relapses and provide new diagnostic and therapeutic options for a subset of patients.

Prediction of individual brain maturity using fMRI.

PubMed

Dosenbach, Nico U F; Nardos, Binyam; Cohen, Alexander L; Fair, Damien A; Power, Jonathan D; Church, Jessica A; Nelson, Steven M; Wig, Gagan S; Vogel, Alecia C; Lessov-Schlaggar, Christina N; Barnes, Kelly Anne; Dubis, Joseph W; Feczko, Eric; Coalson, Rebecca S; Pruett, John R; Barch, Deanna M; Petersen, Steven E; Schlaggar, Bradley L

2010-09-10

Group functional connectivity magnetic resonance imaging (fcMRI) studies have documented reliable changes in human functional brain maturity over development. Here we show that support vector machine-based multivariate pattern analysis extracts sufficient information from fcMRI data to make accurate predictions about individuals' brain maturity across development. The use of only 5 minutes of resting-state fcMRI data from 238 scans of typically developing volunteers (ages 7 to 30 years) allowed prediction of individual brain maturity as a functional connectivity maturation index. The resultant functional maturation curve accounted for 55% of the sample variance and followed a nonlinear asymptotic growth curve shape. The greatest relative contribution to predicting individual brain maturity was made by the weakening of short-range functional connections between the adult brain's major functional networks.

Auditory cortical activity after intracortical microstimulation and its role for sensory processing and learning.

PubMed

Deliano, Matthias; Scheich, Henning; Ohl, Frank W

2009-12-16

Several studies have shown that animals can learn to make specific use of intracortical microstimulation (ICMS) of sensory cortex within behavioral tasks. Here, we investigate how the focal, artificial activation by ICMS leads to a meaningful, behaviorally interpretable signal. In natural learning, this involves large-scale activity patterns in widespread brain-networks. We therefore trained gerbils to discriminate closely neighboring ICMS sites within primary auditory cortex producing evoked responses largely overlapping in space. In parallel, during training, we recorded electrocorticograms (ECoGs) at high spatial resolution. Applying a multivariate classification procedure, we identified late spatial patterns that emerged with discrimination learning from the ongoing poststimulus ECoG. These patterns contained information about the preceding conditioned stimulus, and were associated with a subsequent correct behavioral response by the animal. Thereby, relevant pattern information was mainly carried by neuron populations outside the range of the lateral spatial spread of ICMS-evoked cortical activation (approximately 1.2 mm). This demonstrates that the stimulated cortical area not only encoded information about the stimulation sites by its focal, stimulus-driven activation, but also provided meaningful signals in its ongoing activity related to the interpretation of ICMS learned by the animal. This involved the stimulated area as a whole, and apparently required large-scale integration in the brain. However, ICMS locally interfered with the ongoing cortical dynamics by suppressing pattern formation near the stimulation sites. The interaction between ICMS and ongoing cortical activity has several implications for the design of ICMS protocols and cortical neuroprostheses, since the meaningful interpretation of ICMS depends on this interaction.

Network structure shapes spontaneous functional connectivity dynamics.

PubMed

Shen, Kelly; Hutchison, R Matthew; Bezgin, Gleb; Everling, Stefan; McIntosh, Anthony R

2015-04-08

The structural organization of the brain constrains the range of interactions between different regions and shapes ongoing information processing. Therefore, it is expected that large-scale dynamic functional connectivity (FC) patterns, a surrogate measure of coordination between brain regions, will be closely tied to the fiber pathways that form the underlying structural network. Here, we empirically examined the influence of network structure on FC dynamics by comparing resting-state FC (rsFC) obtained using BOLD-fMRI in macaques (Macaca fascicularis) to structural connectivity derived from macaque axonal tract tracing studies. Consistent with predictions from simulation studies, the correspondence between rsFC and structural connectivity increased as the sample duration increased. Regions with reciprocal structural connections showed the most stable rsFC across time. The data suggest that the transient nature of FC is in part dependent on direct underlying structural connections, but also that dynamic coordination can occur via polysynaptic pathways. Temporal stability was found to be dependent on structural topology, with functional connections within the rich-club core exhibiting the greatest stability over time. We discuss these findings in light of highly variable functional hubs. The results further elucidate how large-scale dynamic functional coordination exists within a fixed structural architecture. Copyright © 2015 the authors 0270-6474/15/355579-10$15.00/0.

Macroscopic phase-resetting curves for spiking neural networks

NASA Astrophysics Data System (ADS)

Dumont, Grégory; Ermentrout, G. Bard; Gutkin, Boris

2017-10-01

The study of brain rhythms is an open-ended, and challenging, subject of interest in neuroscience. One of the best tools for the understanding of oscillations at the single neuron level is the phase-resetting curve (PRC). Synchronization in networks of neurons, effects of noise on the rhythms, effects of transient stimuli on the ongoing rhythmic activity, and many other features can be understood by the PRC. However, most macroscopic brain rhythms are generated by large populations of neurons, and so far it has been unclear how the PRC formulation can be extended to these more common rhythms. In this paper, we describe a framework to determine a macroscopic PRC (mPRC) for a network of spiking excitatory and inhibitory neurons that generate a macroscopic rhythm. We take advantage of a thermodynamic approach combined with a reduction method to simplify the network description to a small number of ordinary differential equations. From this simplified but exact reduction, we can compute the mPRC via the standard adjoint method. Our theoretical findings are illustrated with and supported by numerical simulations of the full spiking network. Notably our mPRC framework allows us to predict the difference between effects of transient inputs to the excitatory versus the inhibitory neurons in the network.

Profiling biomarkers of traumatic axonal injury: From mouse to man.

PubMed

Manivannan, Susruta; Makwana, Milan; Ahmed, Aminul Islam; Zaben, Malik

2018-05-18

Traumatic brain injury (TBI) poses a major public health problem on a global scale. Its burden results from high mortality and significant morbidity in survivors. This stems, in part, from an ongoing inadequacy in diagnostic and prognostic indicators despite significant technological advances. Traumatic axonal injury (TAI) is a key driver of the ongoing pathological process following TBI, causing chronic neurological deficits and disability. The science underpinning biomarkers of TAI has been a subject of many reviews in recent literature. However, in this review we provide a comprehensive account of biomarkers from animal models to clinical studies, bridging the gap between experimental science and clinical medicine. We have discussed pathogenesis, temporal kinetics, relationships to neuro-imaging, and, most importantly, clinical applicability in order to provide a holistic perspective of how this could improve TBI diagnosis and predict clinical outcome in a real-life setting. We conclude that early and reliable identification of axonal injury post-TBI with the help of body fluid biomarkers could enhance current care of TBI patients by (i) increasing speed and accuracy of diagnosis, (ii) providing invaluable prognostic information, (iii) allow efficient allocation of rehabilitation services, and (iv) provide potential therapeutic targets. The optimal model for assessing TAI is likely to involve multiple components, including several blood biomarkers and neuro-imaging modalities, at different time points. Copyright © 2018. Published by Elsevier B.V.

New insights into action-perception coupling.

PubMed

Feldman, Anatol G

2009-03-01

According to a view that has dominated the field for over a century, the brain programs muscle commands and uses a copy of these commands [efference copy (EC)] to adjust not only resulting motor action but also ongoing perception. This view was helpful in formulating several classical problems of action and perception: (1) the posture-movement problem of how movements away from a stable posture can be made without evoking resistance of posture-stabilizing mechanisms resulting from intrinsic muscle and reflex properties; (2) the problem of kinesthesia or why our sense of limb position is good despite ambiguous positional information delivered by proprioceptive and cutaneous signals; (3) the problem of visual space constancy or why the world is perceived as stable while its retinal image shifts following changes in gaze. On closer inspection, the EC theory actually does not solve these problems in a physiologically feasible way. Here solutions to these problems are proposed based on the advanced formulation of the equilibrium-point hypothesis that suggests that action and perception are accomplished in a common spatial frame of reference selected by the brain from a set of available frames. Experimental data suggest that the brain is also able to translate or/and rotate the selected frame of reference by modifying its major attributes-the origin, metrics and orientation-and thus substantially influence action and perception. Because of this ability, such frames are called physical to distinguish them from symbolic or mathematical frames that are used to describe system behavior without influencing this behavior. Experimental data also imply that once a frame of reference is chosen, its attributes are modified in a feedforward way, thus enabling the brain to act in an anticipatory and predictive manner. This approach is extended to sense of effort, kinesthetic illusions, phantom limb and phantom body phenomena. It also addresses the question of why retinal images of objects are sensed as objects located in the external, physical world, rather than in internal representations of the brain.

Investigation of mindfulness meditation practitioners with voxel-based morphometry

PubMed Central

Hölzel, Britta K.; Ott, Ulrich; Gard, Tim; Hempel, Hannes; Weygandt, Martin; Morgen, Katrin; Vaitl, Dieter

2008-01-01

Mindfulness meditators practice the non-judgmental observation of the ongoing stream of internal experiences as they arise. Using voxel-based morphometry, this study investigated MRI brain images of 20 mindfulness (Vipassana) meditators (mean practice 8.6 years; 2 h daily) and compared the regional gray matter concentration to that of non-meditators matched for sex, age, education and handedness. Meditators were predicted to show greater gray matter concentration in regions that are typically activated during meditation. Results confirmed greater gray matter concentration for meditators in the right anterior insula, which is involved in interoceptive awareness. This group difference presumably reflects the training of bodily awareness during mindfulness meditation. Furthermore, meditators had greater gray matter concentration in the left inferior temporal gyrus and right hippocampus. Both regions have previously been found to be involved in meditation. The mean value of gray matter concentration in the left inferior temporal gyrus was predictable by the amount of meditation training, corroborating the assumption of a causal impact of meditation training on gray matter concentration in this region. Results suggest that meditation practice is associated with structural differences in regions that are typically activated during meditation and in regions that are relevant for the task of meditation. PMID:19015095

Brain-machine interfaces can accelerate clarification of the principal mysteries and real plasticity of the brain.

PubMed

Sakurai, Yoshio

2014-01-01

This perspective emphasizes that the brain-machine interface (BMI) research has the potential to clarify major mysteries of the brain and that such clarification of the mysteries by neuroscience is needed to develop BMIs. I enumerate five principal mysteries. The first is "how is information encoded in the brain?" This is the fundamental question for understanding what our minds are and is related to the verification of Hebb's cell assembly theory. The second is "how is information distributed in the brain?" This is also a reconsideration of the functional localization of the brain. The third is "what is the function of the ongoing activity of the brain?" This is the problem of how the brain is active during no-task periods and what meaning such spontaneous activity has. The fourth is "how does the bodily behavior affect the brain function?" This is the problem of brain-body interaction, and obtaining a new "body" by a BMI leads to a possibility of changes in the owner's brain. The last is "to what extent can the brain induce plasticity?" Most BMIs require changes in the brain's neuronal activity to realize higher performance, and the neuronal operant conditioning inherent in the BMIs further enhances changes in the activity.

Using connectome-based predictive modeling to predict individual behavior from brain connectivity

PubMed Central

Shen, Xilin; Finn, Emily S.; Scheinost, Dustin; Rosenberg, Monica D.; Chun, Marvin M.; Papademetris, Xenophon; Constable, R Todd

2017-01-01

Neuroimaging is a fast developing research area where anatomical and functional images of human brains are collected using techniques such as functional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), and electroencephalography (EEG). Technical advances and large-scale datasets have allowed for the development of models capable of predicting individual differences in traits and behavior using brain connectivity measures derived from neuroimaging data. Here, we present connectome-based predictive modeling (CPM), a data-driven protocol for developing predictive models of brain-behavior relationships from connectivity data using cross-validation. This protocol includes the following steps: 1) feature selection, 2) feature summarization, 3) model building, and 4) assessment of prediction significance. We also include suggestions for visualizing the most predictive features (i.e., brain connections). The final result should be a generalizable model that takes brain connectivity data as input and generates predictions of behavioral measures in novel subjects, accounting for a significant amount of the variance in these measures. It has been demonstrated that the CPM protocol performs equivalently or better than most of the existing approaches in brain-behavior prediction. However, because CPM focuses on linear modeling and a purely data-driven driven approach, neuroscientists with limited or no experience in machine learning or optimization would find it easy to implement the protocols. Depending on the volume of data to be processed, the protocol can take 10–100 minutes for model building, 1–48 hours for permutation testing, and 10–20 minutes for visualization of results. PMID:28182017

Dyscalculia in Harrow

ERIC Educational Resources Information Center

Messenger, Chris; Emerson, Jane; Bird, Ronit

2007-01-01

In this article, the authors offer three definitions of dyscalculia, then describe the background and initial progress of the Harrow Dyscalculia Project. Their project in Harrow is associated with ongoing research into numeracy and brain development led by Brian Butterworth, Professor of Cognitive Neuropsychology at UCL. Pupils from Harrow schools…

The brain's connective core and its role in animal cognition

PubMed Central

Shanahan, Murray

2012-01-01

This paper addresses the question of how the brain of an animal achieves cognitive integration—that is to say how it manages to bring its fullest resources to bear on an ongoing situation. To fully exploit its cognitive resources, whether inherited or acquired through experience, it must be possible for unanticipated coalitions of brain processes to form. This facilitates the novel recombination of the elements of an existing behavioural repertoire, and thereby enables innovation. But in a system comprising massively many anatomically distributed assemblies of neurons, it is far from clear how such open-ended coalition formation is possible. The present paper draws on contemporary findings in brain connectivity and neurodynamics, as well as the literature of artificial intelligence, to outline a possible answer in terms of the brain's most richly connected and topologically central structures, its so-called connective core. PMID:22927569

Multimodal Approaches to Define Network Oscillations in Depression

PubMed Central

Smart, Otis Lkuwamy; Tiruvadi, Vineet Ravi; Mayberg, Helen S.

2018-01-01

The renaissance in the use of encephalography-based research methods to probe the pathophysiology of neuropsychiatric disorders is well afoot and continues to advance. Building on the platform of neuroimaging evidence on brain circuit models, magnetoencephalography, scalp electroencephalography, and even invasive electroencephalography are now being used to characterize brain network dysfunctions that underlie major depressive disorder using brain oscillation measurements and associated treatment responses. Such multiple encephalography modalities provide avenues to study pathologic network dynamics with high temporal resolution and over long time courses, opportunities to complement neuroimaging methods and findings, and new approaches to identify quantitative biomarkers that indicate critical targets for brain therapy. Such goals have been facilitated by the ongoing testing of novel invasive neuromodulation therapies, notably, deep brain stimulation, where clinically relevant treatment effects can be monitored at multiple brain sites in a time-locked causal manner. We review key brain rhythms identified in major depressive disorder as foundation for development of putative biomarkers for objectively evaluating neuromodulation success and for guiding deep brain stimulation or other target-based neuromodulation strategies for treatment-resistant depression patients. PMID:25681871

Prediction of brain deformations and risk of traumatic brain injury due to closed-head impact: quantitative analysis of the effects of boundary conditions and brain tissue constitutive model.

PubMed

Wang, Fang; Han, Yong; Wang, Bingyu; Peng, Qian; Huang, Xiaoqun; Miller, Karol; Wittek, Adam

2018-05-12

In this study, we investigate the effects of modelling choices for the brain-skull interface (layers of tissues between the brain and skull that determine boundary conditions for the brain) and the constitutive model of brain parenchyma on the brain responses under violent impact as predicted using computational biomechanics model. We used the head/brain model from Total HUman Model for Safety (THUMS)-extensively validated finite element model of the human body that has been applied in numerous injury biomechanics studies. The computations were conducted using a well-established nonlinear explicit dynamics finite element code LS-DYNA. We employed four approaches for modelling the brain-skull interface and four constitutive models for the brain tissue in the numerical simulations of the experiments on post-mortem human subjects exposed to violent impacts reported in the literature. The brain-skull interface models included direct representation of the brain meninges and cerebrospinal fluid, outer brain surface rigidly attached to the skull, frictionless sliding contact between the brain and skull, and a layer of spring-type cohesive elements between the brain and skull. We considered Ogden hyperviscoelastic, Mooney-Rivlin hyperviscoelastic, neo-Hookean hyperviscoelastic and linear viscoelastic constitutive models of the brain tissue. Our study indicates that the predicted deformations within the brain and related brain injury criteria are strongly affected by both the approach of modelling the brain-skull interface and the constitutive model of the brain parenchyma tissues. The results suggest that accurate prediction of deformations within the brain and risk of brain injury due to violent impact using computational biomechanics models may require representation of the meninges and subarachnoidal space with cerebrospinal fluid in the model and application of hyperviscoelastic (preferably Ogden-type) constitutive model for the brain tissue.

Predicting Intracranial Pressure and Brain Tissue Oxygen Crises in Patients With Severe Traumatic Brain Injury.

PubMed

Myers, Risa B; Lazaridis, Christos; Jermaine, Christopher M; Robertson, Claudia S; Rusin, Craig G

2016-09-01

To develop computer algorithms that can recognize physiologic patterns in traumatic brain injury patients that occur in advance of intracranial pressure and partial brain tissue oxygenation crises. The automated early detection of crisis precursors can provide clinicians with time to intervene in order to prevent or mitigate secondary brain injury. A retrospective study was conducted from prospectively collected physiologic data. intracranial pressure, and partial brain tissue oxygenation crisis events were defined as intracranial pressure of greater than or equal to 20 mm Hg lasting at least 15 minutes and partial brain tissue oxygenation value of less than 10 mm Hg for at least 10 minutes, respectively. The physiologic data preceding each crisis event were used to identify precursors associated with crisis onset. Multivariate classification models were applied to recorded data in 30-minute epochs of time to predict crises between 15 and 360 minutes in the future. The neurosurgical unit of Ben Taub Hospital (Houston, TX). Our cohort consisted of 817 subjects with severe traumatic brain injury. Our algorithm can predict the onset of intracranial pressure crises with 30-minute advance warning with an area under the receiver operating characteristic curve of 0.86 using only intracranial pressure measurements and time since last crisis. An analogous algorithm can predict the start of partial brain tissue oxygenation crises with 30-minute advanced warning with an area under the receiver operating characteristic curve of 0.91. Our algorithms provide accurate and timely predictions of intracranial hypertension and tissue hypoxia crises in patients with severe traumatic brain injury. Almost all of the information needed to predict the onset of these events is contained within the signal of interest and the time since last crisis.

What Costs Do Reveal and Moving Beyond the Cost Debate: Reply to Einstein and McDaniel (in press)

PubMed Central

Smith, Rebekah E.

2010-01-01

Einstein et al., (2005) predicted no cost to an ongoing task when a prospective memory task meet certain criteria. Smith et al. (2007) used prospective memory tasks that met these criteria and found a cost to the ongoing task, contrary to Einstein et al.'s prediction. Einstein and McDaniel (in press) correctly note that there are limitations to using ongoing task performance as a measure of the processes that contribute to prospective memory performance, however, the alternatives suggested by Einstein and McDaniel all focus on ongoing task performance and therefore do not move beyond the cost debate. This article describes why the Smith et al. findings are important, provides recommendations for issues to consider when investigating cost, and discusses individual cost measures. Finally, noting the blurry distinction between Einstein and McDaniel's description of the reflexive associative processes and preparatory attentional processes and difficulties in extending the multiprocess view to nonlaboratory tasks, suggestions are made for moving beyond the cost debate. PMID:20852726

A method for closed-loop presentation of sensory stimuli conditional on the internal brain-state of awake animals

PubMed Central

Rutishauser, Ueli; Kotowicz, Andreas; Laurent, Gilles

2013-01-01

Brain activity often consists of interactions between internal—or on-going—and external—or sensory—activity streams, resulting in complex, distributed patterns of neural activity. Investigation of such interactions could benefit from closed-loop experimental protocols in which one stream can be controlled depending on the state of the other. We describe here methods to present rapid and precisely timed visual stimuli to awake animals, conditional on features of the animal’s on-going brain state; those features are the presence, power and phase of oscillations in local field potentials (LFP). The system can process up to 64 channels in real time. We quantified its performance using simulations, synthetic data and animal experiments (chronic recordings in the dorsal cortex of awake turtles). The delay from detection of an oscillation to the onset of a visual stimulus on an LCD screen was 47.5 ms and visual-stimulus onset could be locked to the phase of ongoing oscillations at any frequency ≤40 Hz. Our software’s architecture is flexible, allowing on-the-fly modifications by experimenters and the addition of new closed-loop control and analysis components through plugins. The source code of our system “StimOMatic” is available freely as open-source. PMID:23473800

Human Brain Modeling with Its Anatomical Structure and Realistic Material Properties for Brain Injury Prediction.

PubMed

Atsumi, Noritoshi; Nakahira, Yuko; Tanaka, Eiichi; Iwamoto, Masami

2018-05-01

Impairments of executive brain function after traumatic brain injury (TBI) due to head impacts in traffic accidents need to be obviated. Finite element (FE) analyses with a human brain model facilitate understanding of the TBI mechanisms. However, conventional brain FE models do not suitably describe the anatomical structure in the deep brain, which is a critical region for executive brain function, and the material properties of brain parenchyma. In this study, for better TBI prediction, a novel brain FE model with anatomical structure in the deep brain was developed. The developed model comprises a constitutive model of brain parenchyma considering anisotropy and strain rate dependency. Validation was performed against postmortem human subject test data associated with brain deformation during head impact. Brain injury analyses were performed using head acceleration curves obtained from reconstruction analysis of rear-end collision with a human whole-body FE model. The difference in structure was found to affect the regions of strain concentration, while the difference in material model contributed to the peak strain value. The injury prediction result by the proposed model was consistent with the characteristics in the neuroimaging data of TBI patients due to traffic accidents.

Ongoing child welfare services: Understanding the relationship of worker and organizational characteristics to service provision.

PubMed

Lwin, Kristen; Fluke, John; Trocmé, Nico; Fallon, Barbara; Mishna, Faye

2018-06-01

Ongoing child welfare services are put in place after completion of the initial maltreatment investigation when there is a perceived need to mitigate the risk of future harm. The knowledge of how clinical, worker, and organizational characteristics interact with this decision to provide ongoing child welfare services is not well integrated in the research literature. Using secondary data from the Canadian Incidence Study of Reported Child Abuse and Neglect-2008, this study's primary objective is to understand the relationship of clinical, worker, and organizational characteristics to the decision to transfer a case to ongoing child welfare services and their relative contribution to the transfer decision in Canada. Findings indicate that several clinical level variables are associated with families receiving ongoing services. Additionally, organizational factors, such as type of services offered by the organization and the number of employee support programs available to workers, significantly predicted the decision to transfer a case to ongoing services. While no worker factors, such as education, amount of training, experience, or caseload, were associated with ongoing service receipt, the intraclass correlation coefficient of the final three-level parsimonious model indicated substantial clustering at the worker level. Results indicate that Canadian child welfare workers make decisions differently based on factors not available in the current study and that what would be deemed as important worker characteristics do not necessarily predict this outcome. Findings and implications for future research are discussed. Copyright © 2018 Elsevier Ltd. All rights reserved.

Neurotechnology: a new approach for treating brain disorders.

PubMed

Robson, John A; Davenport, R John

2014-05-01

Advances in neuroscience, engineering and computer technologies are creating opportunities to connect the brain directly to devices to treat a variety of disorders, both neurological and psychiatric. They are opening a new field of neuroscience called "neurotechnology." This article reviews efforts in this area that are ongoing at Brown University and the hospitals affiliated with Brown's Alpert Medical School. Two general approaches are being used. One uses advanced electrodes to "sense" the activity of many individual neurons in the cerebral cortex and then use that activity for therapeutic purposes. The other uses various types of devices to stimulate specific networks in the brain in order to restore normal function and alleviate symptoms.

Chronic systemic IL-1β exacerbates central neuroinflammation independently of the blood-brain barrier integrity.

PubMed

Murta, Verónica; Farías, María Isabel; Pitossi, Fernando Juan; Ferrari, Carina Cintia

2015-01-15

Peripheral circulating cytokines are involved in immune to brain communication and systemic inflammation is considered a risk factor for flaring up the symptoms in most neurodegenerative diseases. We induced both central inflammatory demyelinating lesion, and systemic inflammation with an interleukin-1β expressing adenovector. The peripheral pro-inflammatory stimulus aggravated the ongoing central lesion independently of the blood-brain barrier (BBB) integrity. This model allows studying the role of specific molecules and cells (neutrophils) from the innate immune system, in the relationship between central and peripheral communication, and on relapsing episodes of demyelinating lesions, along with the role of BBB integrity. Copyright © 2014 Elsevier B.V. All rights reserved.

Effects of penetrating traumatic brain injury on event segmentation and memory.

PubMed

Zacks, Jeffrey M; Kurby, Christopher A; Landazabal, Claudia S; Krueger, Frank; Grafman, Jordan

2016-01-01

Penetrating traumatic brain injury (pTBI) is associated with deficits in cognitive tasks including comprehension and memory, and also with impairments in tasks of daily living. In naturalistic settings, one important component of cognitive task performance is event segmentation, the ability to parse the ongoing stream of behavior into meaningful units. Event segmentation ability is associated with memory performance and with action control, but is not well assessed by standard neuropsychological assessments or laboratory tasks. Here, we measured event segmentation and memory in a sample of 123 male military veterans aged 59-81 who had suffered a traumatic brain injury as young men, and 34 demographically similar controls. Participants watched movies of everyday activities and segmented them to identify fine-grained or coarse-grained events, and then completed tests of recognition memory for pictures from the movies and of memory for the temporal order of actions in the movies. Lesion location and volume were assessed with computed tomography (CT) imaging. Patients with traumatic brain injury were impaired on event segmentation. Those with larger lesions had larger impairments for fine segmentation and also impairments for both memory measures. Further, the degree of memory impairment was statistically mediated by the degree of event segmentation impairment. There was some evidence that lesions to the ventromedial prefrontal cortex (vmPFC) selectively impaired coarse segmentation; however, lesions outside of a priori regions of interest also were associated with impaired segmentation. One possibility is that the effect of vmPFC damage reflects the role of prefrontal event knowledge representations in ongoing comprehension. These results suggest that assessment of naturalistic event comprehension can be a valuable component of cognitive assessment in cases of traumatic brain injury, and that interventions aimed at event segmentation could be clinically helpful. Copyright © 2015 Elsevier Ltd. All rights reserved.

Dissociable effects of local inhibitory and excitatory theta-burst stimulation on large-scale brain dynamics

PubMed Central

Sale, Martin V.; Lord, Anton; Zalesky, Andrew; Breakspear, Michael; Mattingley, Jason B.

2015-01-01

Normal brain function depends on a dynamic balance between local specialization and large-scale integration. It remains unclear, however, how local changes in functionally specialized areas can influence integrated activity across larger brain networks. By combining transcranial magnetic stimulation with resting-state functional magnetic resonance imaging, we tested for changes in large-scale integration following the application of excitatory or inhibitory stimulation on the human motor cortex. After local inhibitory stimulation, regions encompassing the sensorimotor module concurrently increased their internal integration and decreased their communication with other modules of the brain. There were no such changes in modular dynamics following excitatory stimulation of the same area of motor cortex nor were there changes in the configuration and interactions between core brain hubs after excitatory or inhibitory stimulation of the same area. These results suggest the existence of selective mechanisms that integrate local changes in neural activity, while preserving ongoing communication between brain hubs. PMID:25717162

The biology and therapeutic management of melanoma brain metastases.

PubMed

Abate-Daga, Daniel; Ramello, Maria C; Smalley, Inna; Forsyth, Peter A; Smalley, Keiran S M

2018-07-01

The recent years have seen significant progress in the development of systemic therapies to treat patients with advanced melanoma. Use of these new treatment modalities, which include immune checkpoint inhibitors and small molecule BRAF inhibitors, lead to increased overall survival and better outcomes. Although revolutionary, these therapies are often less effective against melanoma brain metastases, and frequently the CNS is the major site of treatment failure. The development of brain metastases remains a serious complication of advanced melanoma that is associated with significant morbidity and mortality. New approaches to both prevent the development of brain metastases and treat established disease are urgently needed. In this review we will outline the mechanisms underlying the development of melanoma brain metastases and will discuss how new insights into metastasis biology are driving the development of new therapeutic strategies. Finally, we will describe the latest data from the ongoing clinical trials for patients with melanoma brain metastases. Copyright © 2018 Elsevier Inc. All rights reserved.

MR brain volumetric measurements are predictive of neurobehavioral impairment in the HIV-1 transgenic rat.

PubMed

Casas, Rafael; Muthusamy, Siva; Wakim, Paul G; Sinharay, Sanhita; Lentz, Margaret R; Reid, William C; Hammoud, Dima A

2018-01-01

HIV infection is known to be associated with brain volume loss, even in optimally treated patients. In this study, we assessed whether dynamic brain volume changes over time are predictive of neurobehavorial performance in the HIV-1 transgenic (Tg) rat, a model of treated HIV-positive patients. Cross-sectional brain MRI imaging was first performed comparing Tg and wild type (WT) rats at 3 and 19 months of age. Longitudinal MRI and neurobehavioral testing of another group of Tg and WT rats was then performed from 5 to 23 weeks of age. Whole brain and subregional image segmentation was used to assess the rate of brain growth over time. We used repeated-measures mixed models to assess differences in brain volumes and to establish how predictive the volume differences are of specific neurobehavioral deficits. Cross-sectional imaging showed smaller whole brain volumes in Tg compared to WT rats at 3 and at 19 months of age. Longitudinally, Tg brain volumes were smaller than age-matched WT rats at all time points, starting as early as 5 weeks of age. The Tg striatal growth rate delay between 5 and 9 weeks of age was greater than that of the whole brain. Striatal volume in combination with genotype was the most predictive of rota-rod scores and in combination with genotype and age was the most predictive of total exploratory activity scores in the Tg rats. The disproportionately delayed striatal growth compared to whole brain between 5 and 9 weeks of age and the role of striatal volume in predicting neurobehavioral deficits suggest an important role of the dopaminergic system in HIV associated neuropathology. This might explain problems with motor coordination and executive decisions in this animal model. Smaller brain and subregional volumes and neurobehavioral deficits were seen as early as 5 weeks of age, suggesting an early brain insult in the Tg rat. Neuroprotective therapy testing in this model should thus target this early stage of development, before brain damage becomes irreversible.

The Developmental Cognitive Neuroscience of Functional Connectivity

ERIC Educational Resources Information Center

Stevens, Michael C.

2009-01-01

Developmental cognitive neuroscience is a rapidly growing field that examines the relationships between biological development and cognitive ability. In the past decade, there has been ongoing refinement of concepts and methodology related to the study of "functional connectivity" among distributed brain regions believed to underlie cognition and…

At the Tip of an Iceberg: Prenatal Marijuana and Its Possible Relation to Neuropsychiatric Outcome in the Offspring.

PubMed

Alpár, Alán; Di Marzo, Vincenzo; Harkany, Tibor

2016-04-01

Endocannabinoids regulate brain development via modulating neural proliferation, migration, and the differentiation of lineage-committed cells. In the fetal nervous system, (endo)cannabinoid-sensing receptors and the enzymatic machinery of endocannabinoid metabolism exhibit a cellular distribution map different from that in the adult, implying distinct functions. Notably, cannabinoid receptors serve as molecular targets for the psychotropic plant-derived cannabis constituent Δ(9)-tetrahydrocannainol, as well as synthetic derivatives (designer drugs). Over 180 million people use cannabis for recreational or medical purposes globally. Recreational cannabis is recognized as a niche drug for adolescents and young adults. This review combines data from human and experimental studies to show that long-term and heavy cannabis use during pregnancy can impair brain maturation and predispose the offspring to neurodevelopmental disorders. By discussing the mechanisms of cannabinoid receptor-mediated signaling events at critical stages of fetal brain development, we organize histopathologic, biochemical, molecular, and behavioral findings into a logical hypothesis predicting neuronal vulnerability to and attenuated adaptation toward environmental challenges (stress, drug exposure, medication) in children affected by in utero cannabinoid exposure. Conversely, we suggest that endocannabinoid signaling can be an appealing druggable target to dampen neuronal activity if pre-existing pathologies associate with circuit hyperexcitability. Yet, we warn that the lack of critical data from longitudinal follow-up studies precludes valid conclusions on possible delayed and adverse side effects. Overall, our conclusion weighs in on the ongoing public debate on cannabis legalization, particularly in medical contexts. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

The negotiated equilibrium model of spinal cord function.

PubMed

Wolpaw, Jonathan R

2018-04-16

The belief that the spinal cord is hardwired is no longer tenable. Like the rest of the CNS, the spinal cord changes during growth and aging, when new motor behaviours are acquired, and in response to trauma and disease. This paper describes a new model of spinal cord function that reconciles its recently appreciated plasticity with its long recognized reliability as the final common pathway for behaviour. According to this model, the substrate of each motor behaviour comprises brain and spinal plasticity: the plasticity in the brain induces and maintains the plasticity in the spinal cord. Each time a behaviour occurs, the spinal cord provides the brain with performance information that guides changes in the substrate of the behaviour. All the behaviours in the repertoire undergo this process concurrently; each repeatedly induces plasticity to preserve its key features despite the plasticity induced by other behaviours. The aggregate process is a negotiation among the behaviours: they negotiate the properties of the spinal neurons and synapses that they all use. The ongoing negotiation maintains the spinal cord in an equilibrium - a negotiated equilibrium - that serves all the behaviours. This new model of spinal cord function is supported by laboratory and clinical data, makes predictions borne out by experiment, and underlies a new approach to restoring function to people with neuromuscular disorders. Further studies are needed to test its generality, to determine whether it may apply to other CNS areas such as the cerebral cortex, and to develop its therapeutic implications. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Examining the link between adolescent brain development and risk taking from a social-developmental perspective.

PubMed

Willoughby, Teena; Good, Marie; Adachi, Paul J C; Hamza, Chloe; Tavernier, Royette

2013-12-01

The adolescent age period is often characterized as a health paradox because it is a time of extensive increases in physical and mental capabilities, yet overall mortality/morbidity rates increase significantly from childhood to adolescence, often due to preventable causes such as risk taking. Asynchrony in developmental time courses between the affective/approach and cognitive control brain systems, as well as the ongoing maturation of neural connectivity are thought to lead to increased vulnerability for risk taking in adolescence. A critical analysis of the frequency of risk taking behaviors, as well as mortality and morbidity rates across the lifespan, however, challenges the hypothesis that the peak of risk taking occurs in middle adolescence when the asynchrony between the different developmental time courses of the affective/approach and cognitive control systems is the largest. In fact, the highest levels of risk taking behaviors, such as alcohol and drug use, often occur among emerging adults (e.g., university/college students), and highlight the role of the social context in predicting risk taking behavior. Moreover, risk taking is not always unregulated or impulsive. Future research should broaden the scope of risk taking to include risks that are relevant to older adults, such as risky financial investing, gambling, and marital infidelity. In addition, a lifespan perspective, with a focus on how associations between neural systems and behavior are moderated by context and trait-level characteristics, and which includes diverse samples (e.g., divorced individuals), will help to address some important limitations in the adolescent brain development and risk taking literature. Copyright © 2013 Elsevier Inc. All rights reserved.

Spatiotemporal dynamics of optogenetically induced and spontaneous seizure transitions in primary generalized epilepsy

PubMed Central

Truccolo, Wilson; Wang, Jing; Nurmikko, Arto V.

2014-01-01

Transitions into primary generalized epileptic seizures occur abruptly and synchronously across the brain. Their potential triggers remain unknown. We used optogenetics to causally test the hypothesis that rhythmic population bursting of excitatory neurons in a local neocortical region can rapidly trigger absence seizures. Most previous studies have been purely correlational, and it remains unclear whether epileptiform events induced by rhythmic stimulation (e.g., sensory/electrical) mimic actual spontaneous seizures, especially regarding their spatiotemporal dynamics. In this study, we used a novel combination of intracortical optogenetic stimulation and microelectrode array recordings in freely moving WAG/Rij rats, a model of absence epilepsy with a cortical focus in the somatosensory cortex (SI). We report three main findings: 1) Brief rhythmic bursting, evoked by optical stimulation of neocortical excitatory neurons at frequencies around 10 Hz, induced seizures consisting of self-sustained spike-wave discharges (SWDs) for about 10% of stimulation trials. The probability of inducing seizures was frequency-dependent, reaching a maximum at 10 Hz. 2) Local field potential power before stimulation and response amplitudes during stimulation both predicted seizure induction, demonstrating a modulatory effect of brain states and neural excitation levels. 3) Evoked responses during stimulation propagated as cortical waves, likely reaching the cortical focus, which in turn generated self-sustained SWDs after stimulation was terminated. Importantly, SWDs during induced and spontaneous seizures propagated with the same spatiotemporal dynamics. Our findings demonstrate that local rhythmic bursting of excitatory neurons in neocortex at particular frequencies, under susceptible ongoing brain states, is sufficient to trigger primary generalized seizures with stereotypical spatiotemporal dynamics. PMID:25552645

Predictors of cerebral microembolization during phased radiofrequency ablation of atrial fibrillation: role of the ongoing rhythm and the site of energy delivery.

PubMed

Nagy-Balo, Edina; Kiss, Alexandra; Condie, Catherine; Stewart, Mark; Edes, Istvan; Csanadi, Zoltan

2014-11-01

Pulmonary vein isolation with phased radiofrequency current and use of a pulmonary vein ablation catheter (PVAC) has recently been associated with a high incidence of clinically silent brain infarcts on diffusion-weighted magnetic resonance imaging, and a high microembolic signal (MES) count detected by transcranial Doppler. We investigated the potential effects of the ongoing rhythm and the target vein during energy delivery (ED) on MES generation during PVAC ablations. A total of 735 EDs during 48 PVAC ablations were analyzed. MES counts were recorded for each ED and time-stamped for correlation with the ongoing rhythm and the target vein for each ED. Significantly higher MES counts were observed during ablations of the left-sided as compared with the right-sided pulmonary veins (P = 0.0003). Similarly, higher MES counts were detected during EDs in atrial fibrillation as compared with sinus rhythm when the temperature was >56°C (P < 0.0001). The ongoing rhythm had no effect on the number of MESs at lower temperatures during ablation. Both the ongoing rhythm during ED and the site of ablation influence microembolus generation during PVAC ablation procedures. ©2014 Wiley Periodicals, Inc.

The Royal Road to Time: How Understanding of the Evolution of Time in the Brain Addresses Memory, Dreaming, Flow, and Other Psychological Phenomena.

PubMed

Hancock, Peter A

2015-01-01

It has been claimed that dreams are the royal road to the unconscious mind. The present work argues that dreams and associated brain states such as memory, attention, flow, and perhaps even consciousness itself arise from diverse conflicts over control of time in the brain. Dreams are the brain's offline efforts to distill projections of the future, while memory represents the vestiges of the past successes and survived failures of those and other conscious projections. Memory thus acts to inform and improve the prediction of possible future states through the use of conscious prospects (planning) and unconscious prospective memory (dreams). When successful, these prospects result in states of flow for conscious planning and déjà vu for its unconscious comparator. In consequence, and contrary to normal expectation, memory is overwhelmingly oriented to deal with the future. Consciousness is the comparable process operating in the present moment. Thus past, present, and future are homeomorphic with the parts of memory (episodic and autobiographical) that recall a personal past, consciousness, and the differing dimensions of prospective memory to plan for future circumstances, respectively. Dreaming (i.e., unconscious prospective memory), has the luxury to run multiple "what if" simulations of many possible futures, essentially offline. I explicate these propositions and their relations to allied constructs such as déjà vu and flow. More generally, I propose that what appear to us as a range of normal psychological experiences are actually manifestations of an ongoing pathological battle for control within the brain. The landscape of this conflict is time. I suggest that there are at least 3 general systems bidding for this control, and in the process of evolution, each system has individually conferred a sequentially increasing survival advantage, but only at the expense of a still incomplete functional integration. Through juxtaposition of these respective brain systems, I endeavor to resolve some fundamental paradoxes and conundrums expressed in the basic psychological and behavioral processes of sleep, consciousness, and memory. The implication of this conceptual framework for the overall conception of time is then briefly adumbrated.

Cortical and subcortical predictive dynamics and learning during perception, cognition, emotion and action

PubMed Central

Grossberg, Stephen

2009-01-01

An intimate link exists between the predictive and learning processes in the brain. Perceptual/cognitive and spatial/motor processes use complementary predictive mechanisms to learn, recognize, attend and plan about objects in the world, determine their current value, and act upon them. Recent neural models clarify these mechanisms and how they interact in cortical and subcortical brain regions. The present paper reviews and synthesizes data and models of these processes, and outlines a unified theory of predictive brain processing. PMID:19528003

Translational research in brain metastasis is identifying molecular pathways that may lead to the development of new therapeutic strategies

PubMed Central

Gril, Brunilde; Evans, Lynda; Palmieri, Diane; Steeg, Patricia S.

2010-01-01

Central nervous system (CNS) or brain metastasis is an emerging area of interest in organ-specific metastasis research. Lung and breast cancers are the most common types of primary tumors to develop brain metastases. This disease complication contributes significantly to the morbidity and mortality of both of these common cancers; as such, brain metastasis is designated an unmet medical need by the US Food and Drug Administration. Recently, an increase in incidence of CNS disease has been noted in the literature for breast cancer, while it has been an ongoing major complication from lung cancer. Progress in treating brain metastases has been hampered by a lack of model systems, a lack of human tissue samples, and the exclusion of brain metastatic patients from many clinical trials. While each of those is significant, the major impediment to effectively treating brain metastatic disease is the blood–brain barrier (BBB). This barrier excludes most chemotherapeutics from the brain and creates a sanctuary site for metastatic tumors. Recent findings on the biology of this disease and translational leads identified by molecular studies are discussed in this article. PMID:20303257

Translational research in brain metastasis is identifying molecular pathways that may lead to the development of new therapeutic strategies.

PubMed

Gril, Brunilde; Evans, Lynda; Palmieri, Diane; Steeg, Patricia S

2010-05-01

Central nervous system (CNS) or brain metastasis is an emerging area of interest in organ-specific metastasis research. Lung and breast cancers are the most common types of primary tumors to develop brain metastases. This disease complication contributes significantly to the morbidity and mortality of both of these common cancers; as such, brain metastasis is designated an unmet medical need by the US Food and Drug Administration (FDA). Recently, an increase in incidence of CNS disease has been noted in the literature for breast cancer, while it has been an ongoing major complication from lung cancer. Progress in treating brain metastases has been hampered by a lack of model systems, a lack of human tissue samples, and the exclusion of brain metastatic patients from many clinical trials. While each of those is significant, the major impediment to effectively treating brain metastatic disease is the blood-brain barrier (BBB). This barrier excludes most chemotherapeutics from the brain and creates a sanctuary site for metastatic tumors. Recent findings on the biology of this disease and translational leads identified by molecular studies are discussed in this article. Published by Elsevier Ltd.

The role of auditory transient and deviance processing in distraction of task performance: a combined behavioral and event-related brain potential study

PubMed Central

Berti, Stefan

2013-01-01

Distraction of goal-oriented performance by a sudden change in the auditory environment is an everyday life experience. Different types of changes can be distracting, including a sudden onset of a transient sound and a slight deviation of otherwise regular auditory background stimulation. With regard to deviance detection, it is assumed that slight changes in a continuous sequence of auditory stimuli are detected by a predictive coding mechanisms and it has been demonstrated that this mechanism is capable of distracting ongoing task performance. In contrast, it is open whether transient detection—which does not rely on predictive coding mechanisms—can trigger behavioral distraction, too. In the present study, the effect of rare auditory changes on visual task performance is tested in an auditory-visual cross-modal distraction paradigm. The rare changes are either embedded within a continuous standard stimulation (triggering deviance detection) or are presented within an otherwise silent situation (triggering transient detection). In the event-related brain potentials, deviants elicited the mismatch negativity (MMN) while transients elicited an enhanced N1 component, mirroring pre-attentive change detection in both conditions but on the basis of different neuro-cognitive processes. These sensory components are followed by attention related ERP components including the P3a and the reorienting negativity (RON). This demonstrates that both types of changes trigger switches of attention. Finally, distraction of task performance is observable, too, but the impact of deviants is higher compared to transients. These findings suggest different routes of distraction allowing for the automatic processing of a wide range of potentially relevant changes in the environment as a pre-requisite for adaptive behavior. PMID:23874278

Early Discharge After Primary Percutaneous Coronary Intervention: The Added Value of N‐Terminal Pro–Brain Natriuretic Peptide to the Zwolle Risk Score

PubMed Central

Schellings, Dirk A. A. M.; Adiyaman, Ahmet; Giannitsis, Evangelos; Hamm, Christian; Suryapranata, Harry; ten Berg, Jurrien M.; Hoorntje, Jan C. A.; van‘t Hof, Arnoud W. J.

2014-01-01

Background The Zwolle Risk Score (ZRS) identifies ST‐elevation myocardial infarction (STEMI) patients treated with primary percutaneous coronary intervention (PPCI) eligible for early discharge. We aimed to investigate whether baseline N‐terminal pro–brain natriuretic peptide (NT‐proBNP) is also able to identify these patients and could improve future risk strategies. Methods and Results PPCI patients included in the Ongoing Tirofiban in Myocardial Infarction Evaluation (On‐TIME) II study were candidates (N=861). We analyzed whether ZRS and baseline NT‐proBNP predicted 30‐day mortality and assessed the occurrence of major adverse cardiac events (MACEs) and major bleeding. Receiver operating characteristic curve analysis was used to assess discriminative accuracy for ZRS, NT‐pro‐BNP, and their combination. After multiple imputation, 845 patients were included. Both ZRS >3 (hazard ratio [HR]=9.42; P<0.001) and log NT‐pro‐BNP (HR=2.61; P<0.001) values were associated with 30‐day mortality. On multivariate analysis, both the ZRS (HR=1.41; 95% confidence interval [CI]=1.27 to 1.56; P<0.001) and log NT‐proBNP (HR=2.09; 95% CI=1.59 to 2.74; P<0.001) independently predicted death at 30 days. The area under the curve for 30‐day mortality for combined ZRS/NT‐proBNP was 0.94 (95% CI=0.90 to 0.99), with optimal predictive values of a ZRS ≥2 and a NT‐proBNP value of ≥200 pg/mL. Using these cut‐off values, 64% of the study population could be identified as very low risk with zero mortality at 30 days follow‐up and low occurrence of MACEs and major bleeding between 48 hours and 10 days (1.3% and 0.6%, respectively). Conclusion Baseline NT‐proBNP identifies a large group of low‐risk patients who may be eligible for early (48‐ to 72‐hour) discharge, whereas optimal predictive accuracy is reached by the combination of both baseline NT‐proBNP and ZRS. PMID:25389283

Prognostic models for predicting posttraumatic seizures during acute hospitalization, and at 1 and 2 years following traumatic brain injury.

PubMed

Ritter, Anne C; Wagner, Amy K; Szaflarski, Jerzy P; Brooks, Maria M; Zafonte, Ross D; Pugh, Mary Jo V; Fabio, Anthony; Hammond, Flora M; Dreer, Laura E; Bushnik, Tamara; Walker, William C; Brown, Allen W; Johnson-Greene, Doug; Shea, Timothy; Krellman, Jason W; Rosenthal, Joseph A

2016-09-01

Posttraumatic seizures (PTS) are well-recognized acute and chronic complications of traumatic brain injury (TBI). Risk factors have been identified, but considerable variability in who develops PTS remains. Existing PTS prognostic models are not widely adopted for clinical use and do not reflect current trends in injury, diagnosis, or care. We aimed to develop and internally validate preliminary prognostic regression models to predict PTS during acute care hospitalization, and at year 1 and year 2 postinjury. Prognostic models predicting PTS during acute care hospitalization and year 1 and year 2 post-injury were developed using a recent (2011-2014) cohort from the TBI Model Systems National Database. Potential PTS predictors were selected based on previous literature and biologic plausibility. Bivariable logistic regression identified variables with a p-value < 0.20 that were used to fit initial prognostic models. Multivariable logistic regression modeling with backward-stepwise elimination was used to determine reduced prognostic models and to internally validate using 1,000 bootstrap samples. Fit statistics were calculated, correcting for overfitting (optimism). The prognostic models identified sex, craniotomy, contusion load, and pre-injury limitation in learning/remembering/concentrating as significant PTS predictors during acute hospitalization. Significant predictors of PTS at year 1 were subdural hematoma (SDH), contusion load, craniotomy, craniectomy, seizure during acute hospitalization, duration of posttraumatic amnesia, preinjury mental health treatment/psychiatric hospitalization, and preinjury incarceration. Year 2 significant predictors were similar to those of year 1: SDH, intraparenchymal fragment, craniotomy, craniectomy, seizure during acute hospitalization, and preinjury incarceration. Corrected concordance (C) statistics were 0.599, 0.747, and 0.716 for acute hospitalization, year 1, and year 2 models, respectively. The prognostic model for PTS during acute hospitalization did not discriminate well. Year 1 and year 2 models showed fair to good predictive validity for PTS. Cranial surgery, although medically necessary, requires ongoing research regarding potential benefits of increased monitoring for signs of epileptogenesis, PTS prophylaxis, and/or rehabilitation/social support. Future studies should externally validate models and determine clinical utility. Wiley Periodicals, Inc. © 2016 International League Against Epilepsy.

Found in translation: Understanding the biology and behavior of experimental traumatic brain injury.

PubMed

Bondi, Corina O; Semple, Bridgette D; Noble-Haeusslein, Linda J; Osier, Nicole D; Carlson, Shaun W; Dixon, C Edward; Giza, Christopher C; Kline, Anthony E

2015-11-01

The aim of this review is to discuss in greater detail the topics covered in the recent symposium entitled "Traumatic brain injury: laboratory and clinical perspectives," presented at the 2014 International Behavioral Neuroscience Society annual meeting. Herein, we review contemporary laboratory models of traumatic brain injury (TBI) including common assays for sensorimotor and cognitive behavior. New modalities to evaluate social behavior after injury to the developing brain, as well as the attentional set-shifting test (AST) as a measure of executive function in TBI, will be highlighted. Environmental enrichment (EE) will be discussed as a preclinical model of neurorehabilitation, and finally, an evidence-based approach to sports-related concussion will be considered. The review consists predominantly of published data, but some discussion of ongoing or future directions is provided. Copyright © 2014 Elsevier Ltd. All rights reserved.

Co-Occurrence of Developmental Disorders: The Case of Developmental Dyscalculia

ERIC Educational Resources Information Center

Rubinsten, Orly

2009-01-01

Five to seven percent of children experience severe difficulties in learning mathematics and/or reading. Current trials that are focused on identifying biological markers suggest that these learning disabilities, known as Developmental Dyscalculia (DD) and Dyslexia (for reading), are due to underlying brain dysfunctions. One ongoing controversy…

Error-Related Electrocortical Responses in 10-Year-Old Children and Young Adults

ERIC Educational Resources Information Center

Santesso, Diane L.; Segalowitz, Sidney J.; Schmidt, Louis A.

2006-01-01

Recent anatomical and electrophysiological evidence suggests that the anterior cingulate cortex (ACC) is relatively late to mature. This brain region appears to be critical for monitoring, evaluating, and adjusting ongoing behaviors. This monitoring elicits characteristic ERP components including the error-related negativity (ERN), error…

Commentary on "Trauma to the Psyche and Soma"

ERIC Educational Resources Information Center

Bryant, Richard A.; Hopwood, Sally

2006-01-01

This case report addresses assessment and treatment considerations for a patient suffering from posttraumatic stress disorder (PTSD) in the context of mild traumatic brain injury and ongoing pain. Management of this case is based on the application of evidence-based therapy, and of cognitive behaviour therapy, for PTSD reduction. Assessment and…

Cannabis and alcohol use, and the developing brain.

PubMed

Meruelo, A D; Castro, N; Cota, C I; Tapert, S F

2017-05-15

Sex hormones and white (and grey) matter in the limbic system, cortex and other brain regions undergo changes during adolescence. Some of these changes include ongoing white matter myelination and sexually dimorphic features in grey and white matter. Adolescence is also a period of vulnerability when many are first exposed to alcohol and cannabis, which appear to influence the developing brain. Neuropsychological studies have provided considerable understanding of the effects of alcohol and cannabis on the brain. Advances in neuroimaging have allowed examination of neuroanatomic changes, metabolic and neurotransmitter activity, and neuronal activation during adolescent brain development and substance use. In this review, we examine major differences in brain development between users and non-users, and recent findings on the influence of cannabis and alcohol on the adolescent brain. We also discuss associations that appear to resolve following short-term abstinence, and attentional deficits that appear to persist. These findings can be useful in guiding earlier educational interventions for adolescents, and clarifying the neural sequelae of early alcohol and cannabis use to the general public. Copyright © 2017 Elsevier B.V. All rights reserved.

Immunotherapy targeting immune check-point(s) in brain metastases.

PubMed

Di Giacomo, Anna Maria; Valente, Monica; Covre, Alessia; Danielli, Riccardo; Maio, Michele

2017-08-01

Immunotherapy with monoclonal antibodies (mAb) directed to different immune check-point(s) is showing a significant clinical impact in a growing number of human tumors of different histotype, both in terms of disease response and long-term survival patients. In this rapidly changing scenario, treatment of brain metastases remains an high unmeet medical need, and the efficacy of immunotherapy in these highly dismal clinical setting remains to be largely demonstrated. Nevertheless, up-coming observations are beginning to suggest a clinical potential of cancer immunotherapy also in brain metastases, regardless the underlying tumor histotype. These observations remain to be validated in larger clinical trials eventually designed also to address the efficacy of therapeutic mAb to immune check-point(s) within multimodality therapies for brain metastases. Noteworthy, the initial proofs of efficacy on immunotherapy in central nervous system metastases are already fostering clinical trials investigating its therapeutic potential also in primary brain tumors. We here review ongoing immunotherapeutic approaches to brain metastases and primary brain tumors, and the foreseeable strategies to overcome their main biologic hurdles and clinical challenges. Copyright © 2017 Elsevier Ltd. All rights reserved.

Cannabis and Alcohol Use, and the Developing Brain

PubMed Central

Meruelo, AD; Castro, N; Cota, CI; Tapert, SF

2017-01-01

Sex hormones and white (and grey) matter in the limbic system, cortex and other brain regions undergo changes during adolescence. Some of these changes include ongoing white matter myelination and sexually dimorphic features in grey and white matter. Adolescence is also a period of vulnerability when many are first exposed to alcohol and cannabis, which appear to influence the developing brain. Neuropsychological studies have provided considerable understanding of the effects of alcohol and cannabis on the brain. Advances in neuroimaging have allowed examination of neuroanatomic changes, metabolic and neurotransmitter activity, and neuronal activation during adolescent brain development and substance use. In this review, we examine major differences in brain development between users and non-users, and recent findings on the influence of cannabis and alcohol on the adolescent brain. We also discuss associations that appear to resolve following short-term abstinence, and attentional deficits that appear to persist. These findings can be useful in guiding earlier educational interventions for adolescents, and clarifying the neural sequelae of early alcohol and cannabis use to the general public. PMID:28223098

SPECT-imaging of activity-dependent changes in regional cerebral blood flow induced by electrical and optogenetic self-stimulation in mice.

PubMed

Kolodziej, Angela; Lippert, Michael; Angenstein, Frank; Neubert, Jenni; Pethe, Annette; Grosser, Oliver S; Amthauer, Holger; Schroeder, Ulrich H; Reymann, Klaus G; Scheich, Henning; Ohl, Frank W; Goldschmidt, Jürgen

2014-12-01

Electrical and optogenetic methods for brain stimulation are widely used in rodents for manipulating behavior and analyzing functional connectivities in neuronal circuits. High-resolution in vivo imaging of the global, brain-wide, activation patterns induced by these stimulations has remained challenging, in particular in awake behaving mice. We here mapped brain activation patterns in awake, intracranially self-stimulating mice using a novel protocol for single-photon emission computed tomography (SPECT) imaging of regional cerebral blood flow (rCBF). Mice were implanted with either electrodes for electrical stimulation of the medial forebrain bundle (mfb-microstim) or with optical fibers for blue-light stimulation of channelrhodopsin-2 expressing neurons in the ventral tegmental area (vta-optostim). After training for self-stimulation by current or light application, respectively, mice were implanted with jugular vein catheters and intravenously injected with the flow tracer 99m-technetium hexamethylpropyleneamine oxime (99mTc-HMPAO) during seven to ten minutes of intracranial self-stimulation or ongoing behavior without stimulation. The 99mTc-brain distributions were mapped in anesthetized animals after stimulation using multipinhole SPECT. Upon self-stimulation rCBF strongly increased at the electrode tip in mfb-microstim mice. In vta-optostim mice peak activations were found outside the stimulation site. Partly overlapping brain-wide networks of activations and deactivations were found in both groups. When testing all self-stimulating mice against all controls highly significant activations were found in the rostromedial nucleus accumbens shell. SPECT-imaging of rCBF using intravenous tracer-injection during ongoing behavior is a new tool for imaging regional brain activation patterns in awake behaving rodents providing higher spatial and temporal resolutions than 18F-2-fluoro-2-dexoyglucose positron emission tomography. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Top-down predictions in the cognitive brain

PubMed Central

Kveraga, Kestutis; Ghuman, Avniel S.; Bar, Moshe

2007-01-01

The human brain is not a passive organ simply waiting to be activated by external stimuli. Instead, it is proposed tat the brain continuously employs memory of past experiences to interpret sensory information and predict the immediately relevant future. This review concentrates on visual recognition as the model system for developing and testing ideas about the role and mechanisms of top-down predictions in the brain. We cover relevant behavioral, computational and neural aspects. These ideas are then extended to other domains. The basic elements of this proposal include analogical mapping, associative representations and the generation of predictions. Connections to a host of cognitive processes will be made and implications to several mental disorders will be proposed. PMID:17923222

Prediction of brain tissue temperature using near-infrared spectroscopy.

PubMed

Holper, Lisa; Mitra, Subhabrata; Bale, Gemma; Robertson, Nicola; Tachtsidis, Ilias

2017-04-01

Broadband near-infrared spectroscopy (NIRS) can provide an endogenous indicator of tissue temperature based on the temperature dependence of the water absorption spectrum. We describe a first evaluation of the calibration and prediction of brain tissue temperature obtained during hypothermia in newborn piglets (animal dataset) and rewarming in newborn infants (human dataset) based on measured body (rectal) temperature. The calibration using partial least squares regression proved to be a reliable method to predict brain tissue temperature with respect to core body temperature in the wavelength interval of 720 to 880 nm with a strong mean predictive power of [Formula: see text] (animal dataset) and [Formula: see text] (human dataset). In addition, we applied regression receiver operating characteristic curves for the first time to evaluate the temperature prediction, which provided an overall mean error bias between NIRS predicted brain temperature and body temperature of [Formula: see text] (animal dataset) and [Formula: see text] (human dataset). We discuss main methodological aspects, particularly the well-known aspect of over- versus underestimation between brain and body temperature, which is relevant for potential clinical applications.

Prediction complements explanation in understanding the developing brain.

PubMed

Rosenberg, Monica D; Casey, B J; Holmes, Avram J

2018-02-21

A central aim of human neuroscience is understanding the neurobiology of cognition and behavior. Although we have made significant progress towards this goal, reliance on group-level studies of the developed adult brain has limited our ability to explain population variability and developmental changes in neural circuitry and behavior. In this review, we suggest that predictive modeling, a method for predicting individual differences in behavior from brain features, can complement descriptive approaches and provide new ways to account for this variability. Highlighting the outsized scientific and clinical benefits of prediction in developmental populations including adolescence, we show that predictive brain-based models are already providing new insights on adolescent-specific risk-related behaviors. Together with large-scale developmental neuroimaging datasets and complementary analytic approaches, predictive modeling affords us the opportunity and obligation to identify novel treatment targets and individually tailor the course of interventions for developmental psychopathologies that impact so many young people today.

Brain size predicts problem-solving ability in mammalian carnivores

PubMed Central

Benson-Amram, Sarah; Dantzer, Ben; Stricker, Gregory; Swanson, Eli M.; Holekamp, Kay E.

2016-01-01

Despite considerable interest in the forces shaping the relationship between brain size and cognitive abilities, it remains controversial whether larger-brained animals are, indeed, better problem-solvers. Recently, several comparative studies have revealed correlations between brain size and traits thought to require advanced cognitive abilities, such as innovation, behavioral flexibility, invasion success, and self-control. However, the general assumption that animals with larger brains have superior cognitive abilities has been heavily criticized, primarily because of the lack of experimental support for it. Here, we designed an experiment to inquire whether specific neuroanatomical or socioecological measures predict success at solving a novel technical problem among species in the mammalian order Carnivora. We presented puzzle boxes, baited with food and scaled to accommodate body size, to members of 39 carnivore species from nine families housed in multiple North American zoos. We found that species with larger brains relative to their body mass were more successful at opening the boxes. In a subset of species, we also used virtual brain endocasts to measure volumes of four gross brain regions and show that some of these regions improve model prediction of success at opening the boxes when included with total brain size and body mass. Socioecological variables, including measures of social complexity and manual dexterity, failed to predict success at opening the boxes. Our results, thus, fail to support the social brain hypothesis but provide important empirical support for the relationship between relative brain size and the ability to solve this novel technical problem. PMID:26811470

Brain size predicts problem-solving ability in mammalian carnivores.

PubMed

Benson-Amram, Sarah; Dantzer, Ben; Stricker, Gregory; Swanson, Eli M; Holekamp, Kay E

2016-03-01

Despite considerable interest in the forces shaping the relationship between brain size and cognitive abilities, it remains controversial whether larger-brained animals are, indeed, better problem-solvers. Recently, several comparative studies have revealed correlations between brain size and traits thought to require advanced cognitive abilities, such as innovation, behavioral flexibility, invasion success, and self-control. However, the general assumption that animals with larger brains have superior cognitive abilities has been heavily criticized, primarily because of the lack of experimental support for it. Here, we designed an experiment to inquire whether specific neuroanatomical or socioecological measures predict success at solving a novel technical problem among species in the mammalian order Carnivora. We presented puzzle boxes, baited with food and scaled to accommodate body size, to members of 39 carnivore species from nine families housed in multiple North American zoos. We found that species with larger brains relative to their body mass were more successful at opening the boxes. In a subset of species, we also used virtual brain endocasts to measure volumes of four gross brain regions and show that some of these regions improve model prediction of success at opening the boxes when included with total brain size and body mass. Socioecological variables, including measures of social complexity and manual dexterity, failed to predict success at opening the boxes. Our results, thus, fail to support the social brain hypothesis but provide important empirical support for the relationship between relative brain size and the ability to solve this novel technical problem.

Brain-machine interfaces can accelerate clarification of the principal mysteries and real plasticity of the brain

PubMed Central

Sakurai, Yoshio

2014-01-01

This perspective emphasizes that the brain-machine interface (BMI) research has the potential to clarify major mysteries of the brain and that such clarification of the mysteries by neuroscience is needed to develop BMIs. I enumerate five principal mysteries. The first is “how is information encoded in the brain?” This is the fundamental question for understanding what our minds are and is related to the verification of Hebb’s cell assembly theory. The second is “how is information distributed in the brain?” This is also a reconsideration of the functional localization of the brain. The third is “what is the function of the ongoing activity of the brain?” This is the problem of how the brain is active during no-task periods and what meaning such spontaneous activity has. The fourth is “how does the bodily behavior affect the brain function?” This is the problem of brain-body interaction, and obtaining a new “body” by a BMI leads to a possibility of changes in the owner’s brain. The last is “to what extent can the brain induce plasticity?” Most BMIs require changes in the brain’s neuronal activity to realize higher performance, and the neuronal operant conditioning inherent in the BMIs further enhances changes in the activity. PMID:24904323

Translational Modeling in Schizophrenia: Predicting Human Dopamine D2 Receptor Occupancy.

PubMed

Johnson, Martin; Kozielska, Magdalena; Pilla Reddy, Venkatesh; Vermeulen, An; Barton, Hugh A; Grimwood, Sarah; de Greef, Rik; Groothuis, Geny M M; Danhof, Meindert; Proost, Johannes H

2016-04-01

To assess the ability of a previously developed hybrid physiology-based pharmacokinetic-pharmacodynamic (PBPKPD) model in rats to predict the dopamine D2 receptor occupancy (D2RO) in human striatum following administration of antipsychotic drugs. A hybrid PBPKPD model, previously developed using information on plasma concentrations, brain exposure and D2RO in rats, was used as the basis for the prediction of D2RO in human. The rat pharmacokinetic and brain physiology parameters were substituted with human population pharmacokinetic parameters and human physiological information. To predict the passive transport across the human blood-brain barrier, apparent permeability values were scaled based on rat and human brain endothelial surface area. Active efflux clearance in brain was scaled from rat to human using both human brain endothelial surface area and MDR1 expression. Binding constants at the D2 receptor were scaled based on the differences between in vitro and in vivo systems of the same species. The predictive power of this physiology-based approach was determined by comparing the D2RO predictions with the observed human D2RO of six antipsychotics at clinically relevant doses. Predicted human D2RO was in good agreement with clinically observed D2RO for five antipsychotics. Models using in vitro information predicted human D2RO well for most of the compounds evaluated in this analysis. However, human D2RO was under-predicted for haloperidol. The rat hybrid PBPKPD model structure, integrated with in vitro information and human pharmacokinetic and physiological information, constitutes a scientific basis to predict the time course of D2RO in man.

Auditory closed-loop stimulation of the sleep slow oscillation enhances memory.

PubMed

Ngo, Hong-Viet V; Martinetz, Thomas; Born, Jan; Mölle, Matthias

2013-05-08

Brain rhythms regulate information processing in different states to enable learning and memory formation. The <1 Hz sleep slow oscillation hallmarks slow-wave sleep and is critical to memory consolidation. Here we show in sleeping humans that auditory stimulation in phase with the ongoing rhythmic occurrence of slow oscillation up states profoundly enhances the slow oscillation rhythm, phase-coupled spindle activity, and, consequently, the consolidation of declarative memory. Stimulation out of phase with the ongoing slow oscillation rhythm remained ineffective. Closed-loop in-phase stimulation provides a straight-forward tool to enhance sleep rhythms and their functional efficacy. Copyright © 2013 Elsevier Inc. All rights reserved.

The Amsterdam Resting-State Questionnaire reveals multiple phenotypes of resting-state cognition

PubMed Central

Diaz, B. Alexander; Van Der Sluis, Sophie; Moens, Sarah; Benjamins, Jeroen S.; Migliorati, Filippo; Stoffers, Diederick; Den Braber, Anouk; Poil, Simon-Shlomo; Hardstone, Richard; Van't Ent, Dennis; Boomsma, Dorret I.; De Geus, Eco; Mansvelder, Huibert D.; Van Someren, Eus J. W.; Linkenkaer-Hansen, Klaus

2013-01-01

Resting-state neuroimaging is a dominant paradigm for studying brain function in health and disease. It is attractive for clinical research because of its simplicity for patients, straightforward standardization, and sensitivity to brain disorders. Importantly, non-sensory experiences like mind wandering may arise from ongoing brain activity. However, little is known about the link between ongoing brain activity and cognition, as phenotypes of resting-state cognition—and tools to quantify them—have been lacking. To facilitate rapid and structured measurements of resting-state cognition we developed a 50-item self-report survey, the Amsterdam Resting-State Questionnaire (ARSQ). Based on ARSQ data from 813 participants assessed after 5 min eyes-closed rest in their home, we identified seven dimensions of resting-state cognition using factor analysis: Discontinuity of Mind, Theory of Mind, Self, Planning, Sleepiness, Comfort, and Somatic Awareness. Further, we showed that the structure of cognition was similar during resting-state fMRI and EEG, and that the test-retest correlations were remarkably high for all dimensions. To explore whether inter-individual variation of resting-state cognition is related to health status, we correlated ARSQ-derived factor scores with psychometric scales measuring depression, anxiety, and sleep quality. Mental health correlated positively with Comfort and negatively with Discontinuity of Mind. Finally, we show that sleepiness may partially explain a resting-state EEG profile previously associated with Alzheimer's disease. These findings indicate that the ARSQ readily provides information about cognitive phenotypes and that it is a promising tool for research on the neural correlates of resting-state cognition in health and disease. PMID:23964225

Single severe traumatic brain injury produces progressive pathology with ongoing contralateral white matter damage one year after injury.

PubMed

Pischiutta, Francesca; Micotti, Edoardo; Hay, Jennifer R; Marongiu, Ines; Sammali, Eliana; Tolomeo, Daniele; Vegliante, Gloria; Stocchetti, Nino; Forloni, Gianluigi; De Simoni, Maria-Grazia; Stewart, William; Zanier, Elisa R

2018-02-01

There is increasing recognition that traumatic brain injury (TBI) may initiate long-term neurodegenerative processes, particularly chronic traumatic encephalopathy. However, insight into the mechanisms transforming an initial biomechanical injury into a neurodegenerative process remain elusive, partly as a consequence of the paucity of informative pre-clinical models. This study shows the functional, whole brain imaging and neuropathological consequences at up to one year survival from single severe TBI by controlled cortical impact in mice. TBI mice displayed persistent sensorimotor and cognitive deficits. Longitudinal T2 weighted magnetic resonance imaging (MRI) showed progressive ipsilateral (il) cortical, hippocampal and striatal volume loss, with diffusion tensor imaging demonstrating decreased fractional anisotropy (FA) at up to one year in the il-corpus callosum (CC: -30%) and external capsule (EC: -21%). Parallel neuropathological studies indicated reduction in neuronal density, with evidence of microgliosis and astrogliosis in the il-cortex, with further evidence of microgliosis and astrogliosis in the il-thalamus. One year after TBI there was also a decrease in FA in the contralateral (cl) CC (-17%) and EC (-13%), corresponding to histopathological evidence of white matter loss (cl-CC: -68%; cl-EC: -30%) associated with ongoing microgliosis and astrogliosis. These findings indicate that a single severe TBI induces bilateral, long-term and progressive neuropathology at up to one year after injury. These observations support this model as a suitable platform for exploring the mechanistic link between acute brain injury and late and persistent neurodegeneration. Copyright © 2017 Elsevier Inc. All rights reserved.

Salient sounds activate human visual cortex automatically.

PubMed

McDonald, John J; Störmer, Viola S; Martinez, Antigona; Feng, Wenfeng; Hillyard, Steven A

2013-05-22

Sudden changes in the acoustic environment enhance perceptual processing of subsequent visual stimuli that appear in close spatial proximity. Little is known, however, about the neural mechanisms by which salient sounds affect visual processing. In particular, it is unclear whether such sounds automatically activate visual cortex. To shed light on this issue, this study examined event-related brain potentials (ERPs) that were triggered either by peripheral sounds that preceded task-relevant visual targets (Experiment 1) or were presented during purely auditory tasks (Experiments 2-4). In all experiments the sounds elicited a contralateral ERP over the occipital scalp that was localized to neural generators in extrastriate visual cortex of the ventral occipital lobe. The amplitude of this cross-modal ERP was predictive of perceptual judgments about the contrast of colocalized visual targets. These findings demonstrate that sudden, intrusive sounds reflexively activate human visual cortex in a spatially specific manner, even during purely auditory tasks when the sounds are not relevant to the ongoing task.

Salient sounds activate human visual cortex automatically

PubMed Central

McDonald, John J.; Störmer, Viola S.; Martinez, Antigona; Feng, Wenfeng; Hillyard, Steven A.

2013-01-01

Sudden changes in the acoustic environment enhance perceptual processing of subsequent visual stimuli that appear in close spatial proximity. Little is known, however, about the neural mechanisms by which salient sounds affect visual processing. In particular, it is unclear whether such sounds automatically activate visual cortex. To shed light on this issue, the present study examined event-related brain potentials (ERPs) that were triggered either by peripheral sounds that preceded task-relevant visual targets (Experiment 1) or were presented during purely auditory tasks (Experiments 2, 3, and 4). In all experiments the sounds elicited a contralateral ERP over the occipital scalp that was localized to neural generators in extrastriate visual cortex of the ventral occipital lobe. The amplitude of this cross-modal ERP was predictive of perceptual judgments about the contrast of co-localized visual targets. These findings demonstrate that sudden, intrusive sounds reflexively activate human visual cortex in a spatially specific manner, even during purely auditory tasks when the sounds are not relevant to the ongoing task. PMID:23699530

The future of blood-based biomarkers for Alzheimer’s disease

PubMed Central

Henriksen, Kim; O’Bryant, Sid E.; Hampel, Harald; Trojanowski, John Q.; Montine, Thomas J.; Jeromin, Andreas; Blennow, Kaj; Lönneborg, Anders; Wyss-Coray, Tony; Soares, Holly; Bazenet, Chantal; Sjögren, Magnus; Hu, William; Lovestone, Simon; Karsdal, Morten A.; Weiner, Michael W.

2014-01-01

Treatment of Alzheimer’s disease (AD) is significantly hampered by the lack of easily accessible biomarkers that can detect disease presence and predict disease risk reliably. Fluid biomarkers of AD currently provide indications of disease stage; however, they are not robust predictors of disease progression or treatment response, and most are measured in cerebrospinal fluid, which limits their applicability. With these aspects in mind, the aim of this article is to underscore the concerted efforts of the Blood-Based Biomarker Interest Group, an international working group of experts in the field. The points addressed include: (1) the major challenges in the development of blood-based biomarkers of AD, including patient heterogeneity, inclusion of the “right” control population, and the blood– brain barrier; (2) the need for a clear definition of the purpose of the individual markers (e.g., prognostic, diagnostic, or monitoring therapeutic efficacy); (3) a critical evaluation of the ongoing biomarker approaches; and (4) highlighting the need for standardization of preanalytical variables and analytical methodologies used by the field. PMID:23850333

Mind Reading and Writing: The Future of Neurotechnology.

PubMed

Roelfsema, Pieter R; Denys, Damiaan; Klink, P Christiaan

2018-05-02

Recent advances in neuroscience and technology have made it possible to record from large assemblies of neurons and to decode their activity to extract information. At the same time, available methods to stimulate the brain and influence ongoing processing are also rapidly expanding. These developments pave the way for advanced neurotechnological applications that directly read from, and write to, the human brain. While such technologies are still primarily used in restricted therapeutic contexts, this may change in the future once their performance has improved and they become more widely applicable. Here, we provide an overview of methods to interface with the brain, speculate about potential applications, and discuss important issues associated with a neurotechnologically assisted future. Copyright © 2018 Elsevier Ltd. All rights reserved.

Multislice 1H magnetic resonance spectroscopic imaging: assessment of epilepsy, Alzheimer's disease, and amyotrophic lateral sclerosis

NASA Astrophysics Data System (ADS)

Weiner, Michael W.; Maudsley, Andrew A.; Schuff, Norbert; Soher, Brian J.; Vermathen, Peter P.; Fein, George; Laxer, Kenneth D.

1998-07-01

Proton magnetic resonance spectroscopic imaging (1H MRSI) with volume pre-selection (i.e. by PRESS) or multislice 1H MRSI was used to investigate changes in brain metabolites in Alzheimer's disease, epilepsy, and amyotrophic lateral sclerosis. Examples of results from several ongoing clinical studies are provided. Multislice 1H MRSI of the human brain, without volume pre-selection offers considerable advantages over previously available techniques. Furthermore, MRI tissue segmentation and completely automated spectra curve fitting greatly facilitate quantitative data analysis. Future efforts will be devoted to obtaining full brain coverage and data acquisition at short spin echo times (TE less than 30 ms) for the detection of metabolites with short T2 relaxation times.

Robotics, stem cells, and brain-computer interfaces in rehabilitation and recovery from stroke: updates and advances.

PubMed

Boninger, Michael L; Wechsler, Lawrence R; Stein, Joel

2014-11-01

The aim of this study was to describe the current state and latest advances in robotics, stem cells, and brain-computer interfaces in rehabilitation and recovery for stroke. The authors of this summary recently reviewed this work as part of a national presentation. The article represents the information included in each area. Each area has seen great advances and challenges as products move to market and experiments are ongoing. Robotics, stem cells, and brain-computer interfaces all have tremendous potential to reduce disability and lead to better outcomes for patients with stroke. Continued research and investment will be needed as the field moves forward. With this investment, the potential for recovery of function is likely substantial.

Robotics, Stem Cells and Brain Computer Interfaces in Rehabilitation and Recovery from Stroke; Updates and Advances

PubMed Central

Boninger, Michael L; Wechsler, Lawrence R.; Stein, Joel

2014-01-01

Objective To describe the current state and latest advances in robotics, stem cells, and brain computer interfaces in rehabilitation and recovery for stroke. Design The authors of this summary recently reviewed this work as part of a national presentation. The paper represents the information included in each area. Results Each area has seen great advances and challenges as products move to market and experiments are ongoing. Conclusion Robotics, stem cells, and brain computer interfaces all have tremendous potential to reduce disability and lead to better outcomes for patients with stroke. Continued research and investment will be needed as the field moves forward. With this investment, the potential for recovery of function is likely substantial PMID:25313662

Right or wrong? The brain's fast response to morally objectionable statements.

PubMed

Van Berkum, Jos J A; Holleman, Bregje; Nieuwland, Mante; Otten, Marte; Murre, Jaap

2009-09-01

How does the brain respond to statements that clash with a person's value system? We recorded event-related brain potentials while respondents from contrasting political-ethical backgrounds completed an attitude survey on drugs, medical ethics, social conduct, and other issues. Our results show that value-based disagreement is unlocked by language extremely rapidly, within 200 to 250 ms after the first word that indicates a clash with the reader's value system (e.g., "I think euthanasia is an acceptable/unacceptable..."). Furthermore, strong disagreement rapidly influences the ongoing analysis of meaning, which indicates that even very early processes in language comprehension are sensitive to a person's value system. Our results testify to rapid reciprocal links between neural systems for language and for valuation.

Brain Activity in Self- and Value-Related Regions in Response to Online Antismoking Messages Predicts Behavior Change

PubMed Central

Cooper, Nicole; Tompson, Steve; O’Donnell, Matthew Brook; Falk, Emily B.

2017-01-01

In this study, we combined approaches from media psychology and neuroscience to ask whether brain activity in response to online antismoking messages can predict smoking behavior change. In particular, we examined activity in subregions of the medial prefrontal cortex linked to self- and value-related processing, to test whether these neurocognitive processes play a role in message-consistent behavior change. We observed significant relationships between activity in both brain regions of interest and behavior change (such that higher activity predicted a larger reduction in smoking). Furthermore, activity in these brain regions predicted variance independent of traditional, theory-driven self-report metrics such as intention, self-efficacy, and risk perceptions. We propose that valuation is an additional cognitive process that should be investigated further as we search for a mechanistic explanation of the relationship between brain activity and media effects relevant to health behavior change. PMID:29057013

Dance and the brain: a review.

PubMed

Karpati, Falisha J; Giacosa, Chiara; Foster, Nicholas E V; Penhune, Virginia B; Hyde, Krista L

2015-03-01

Dance is a universal form of human expression that offers a rich source for scientific study. Dance provides a unique opportunity to investigate brain plasticity and its interaction with behavior. Several studies have investigated the behavioral correlates of dance, but less is known about the brain basis of dance. Studies on dance observation suggest that long- and short-term dance training affect brain activity in the action observation and simulation networks. Despite methodological challenges, the feasibility of conducting neuroimaging while dancing has been demonstrated, and several brain regions have been implicated in dance execution. Preliminary work from our laboratory suggests that long-term dance training changes both gray and white matter structure. This article provides a critical summary of work investigating the neural correlates of dance. It covers functional neuroimaging studies of dance observation and performance as well as structural neuroimaging studies of expert dancers. To stimulate ongoing dialogue between dance and science, future directions in dance and brain research as well as implications are discussed. Research on the neuroscience of dance will lead to a better understanding of brain-behavior relationships and brain plasticity in experts and nonexperts and can be applied to the development of dance-based therapy programs. © 2014 New York Academy of Sciences.

Inferring deep-brain activity from cortical activity using functional near-infrared spectroscopy

PubMed Central

Liu, Ning; Cui, Xu; Bryant, Daniel M.; Glover, Gary H.; Reiss, Allan L.

2015-01-01

Functional near-infrared spectroscopy (fNIRS) is an increasingly popular technology for studying brain function because it is non-invasive, non-irradiating and relatively inexpensive. Further, fNIRS potentially allows measurement of hemodynamic activity with high temporal resolution (milliseconds) and in naturalistic settings. However, in comparison with other imaging modalities, namely fMRI, fNIRS has a significant drawback: limited sensitivity to hemodynamic changes in deep-brain regions. To overcome this limitation, we developed a computational method to infer deep-brain activity using fNIRS measurements of cortical activity. Using simultaneous fNIRS and fMRI, we measured brain activity in 17 participants as they completed three cognitive tasks. A support vector regression (SVR) learning algorithm was used to predict activity in twelve deep-brain regions using information from surface fNIRS measurements. We compared these predictions against actual fMRI-measured activity using Pearson’s correlation to quantify prediction performance. To provide a benchmark for comparison, we also used fMRI measurements of cortical activity to infer deep-brain activity. When using fMRI-measured activity from the entire cortex, we were able to predict deep-brain activity in the fusiform cortex with an average correlation coefficient of 0.80 and in all deep-brain regions with an average correlation coefficient of 0.67. The top 15% of predictions using fNIRS signal achieved an accuracy of 0.7. To our knowledge, this study is the first to investigate the feasibility of using cortical activity to infer deep-brain activity. This new method has the potential to extend fNIRS applications in cognitive and clinical neuroscience research. PMID:25798327

Changes in event-related potential functional networks predict traumatic brain injury in piglets.

PubMed

Atlan, Lorre S; Lan, Ingrid S; Smith, Colin; Margulies, Susan S

2018-06-01

Traumatic brain injury is a leading cause of cognitive and behavioral deficits in children in the US each year. None of the current diagnostic tools, such as quantitative cognitive and balance tests, have been validated to identify mild traumatic brain injury in infants, adults and animals. In this preliminary study, we report a novel, quantitative tool that has the potential to quickly and reliably diagnose traumatic brain injury and which can track the state of the brain during recovery across multiple ages and species. Using 32 scalp electrodes, we recorded involuntary auditory event-related potentials from 22 awake four-week-old piglets one day before and one, four, and seven days after two different injury types (diffuse and focal) or sham. From these recordings, we generated event-related potential functional networks and assessed whether the patterns of the observed changes in these networks could distinguish brain-injured piglets from non-injured. Piglet brains exhibited significant changes after injury, as evaluated by five network metrics. The injury prediction algorithm developed from our analysis of the changes in the event-related potentials functional networks ultimately produced a tool with 82% predictive accuracy. This novel approach is the first application of auditory event-related potential functional networks to the prediction of traumatic brain injury. The resulting tool is a robust, objective and predictive method that offers promise for detecting mild traumatic brain injury, in particular because collecting event-related potentials data is noninvasive and inexpensive. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Top-Down Predictions in the Cognitive Brain

ERIC Educational Resources Information Center

Kveraga, Kestutis; Ghuman, Avniel S.; Bar, Moshe

2007-01-01

The human brain is not a passive organ simply waiting to be activated by external stimuli. Instead, we propose that the brain continuously employs memory of past experiences to interpret sensory information and predict the immediately relevant future. The basic elements of this proposal include analogical mapping, associative representations and…

Predicting Age Using Neuroimaging: Innovative Brain Ageing Biomarkers.

PubMed

Cole, James H; Franke, Katja

2017-12-01

The brain changes as we age and these changes are associated with functional deterioration and neurodegenerative disease. It is vital that we better understand individual differences in the brain ageing process; hence, techniques for making individualised predictions of brain ageing have been developed. We present evidence supporting the use of neuroimaging-based 'brain age' as a biomarker of an individual's brain health. Increasingly, research is showing how brain disease or poor physical health negatively impacts brain age. Importantly, recent evidence shows that having an 'older'-appearing brain relates to advanced physiological and cognitive ageing and the risk of mortality. We discuss controversies surrounding brain age and highlight emerging trends such as the use of multimodality neuroimaging and the employment of 'deep learning' methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Finding influential nodes for integration in brain networks using optimal percolation theory.

PubMed

Del Ferraro, Gino; Moreno, Andrea; Min, Byungjoon; Morone, Flaviano; Pérez-Ramírez, Úrsula; Pérez-Cervera, Laura; Parra, Lucas C; Holodny, Andrei; Canals, Santiago; Makse, Hernán A

2018-06-11

Global integration of information in the brain results from complex interactions of segregated brain networks. Identifying the most influential neuronal populations that efficiently bind these networks is a fundamental problem of systems neuroscience. Here, we apply optimal percolation theory and pharmacogenetic interventions in vivo to predict and subsequently target nodes that are essential for global integration of a memory network in rodents. The theory predicts that integration in the memory network is mediated by a set of low-degree nodes located in the nucleus accumbens. This result is confirmed with pharmacogenetic inactivation of the nucleus accumbens, which eliminates the formation of the memory network, while inactivations of other brain areas leave the network intact. Thus, optimal percolation theory predicts essential nodes in brain networks. This could be used to identify targets of interventions to modulate brain function.

Developing a clinical translational neuroscience taxonomy for anxiety and mood disorder: protocol for the baseline-follow up Research domain criteria Anxiety and Depression ("RAD") project.

PubMed

Williams, Leanne M; Goldstein-Piekarski, Andrea N; Chowdhry, Nowreen; Grisanzio, Katherine A; Haug, Nancy A; Samara, Zoe; Etkin, Amit; O'Hara, Ruth; Schatzberg, Alan F; Suppes, Trisha; Yesavage, Jerome

2016-03-15

Understanding how brain circuit dysfunctions relate to specific symptoms offers promise for developing a brain-based taxonomy for classifying psychopathology, identifying targets for mechanistic studies and ultimately for guiding treatment choice. The goal of the Research Domain Criteria (RDoC) initiative of the National Institute of Mental Health is to accelerate the development of such neurobiological models of mental disorder independent of traditional diagnostic criteria. In our RDoC Anxiety and Depression ("RAD") project we focus trans-diagnostically on the spectrum of depression and anxiety psychopathology. Our aims are a) to use brain imaging to define cohesive dimensions defined by dysfunction of circuits involved in reactivity to and regulation of negatively valenced emotional stimulation and in cognitive control, b) to assess the relationships between these dimension and specific symptoms, behavioral performance and the real world capacity to function socially and at work and c) to assess the stability of brain-symptom-behavior-function relationships over time. Here we present the protocol for the "RAD" project, one of the first RDoC studies to use brain circuit functioning to define new dimensions of psychopathology. The RAD project follows baseline-follow up design. In line with RDoC principles we use a strategy for recruiting all clients who "walk through the door" of a large community mental health clinic as well as the surrounding community. The clinic attends to a broad spectrum of anxiety and mood-related symptoms. Participants are unmedicated and studied at baseline using a standardized battery of functional brain imaging, structural brain imaging and behavioral probes that assay constructs of threat reactivity, threat regulation and cognitive control. The battery also includes self-report measures of anxiety and mood symptoms, and social and occupational functioning. After baseline assessments, therapists in the clinic apply treatment planning as usual. Follow-up assessments are undertaken at 3 months, to establish the reliability of brain-based subgroups over time and to assess whether these subgroups predict real-world functional capacity over time. First enrollment was August 2013, and is ongoing. This project is designed to advance knowledge toward a neural circuit taxonomy for mental disorder. Data will be shared via the RDoC database for dissemination to the scientific community. The clinical translational neuroscience goals of the project are to develop brain-behavior profile reports for each individual participant and to refine these reports with therapist feedback. Reporting of results is expected from December 2016 onward. ClinicalTrials.gov Identifier: NCT02220309 . Registered: August 13, 2014.

Neural substrates of updating the prediction through prediction error during decision making.

PubMed

Wang, Ying; Ma, Ning; He, Xiaosong; Li, Nan; Wei, Zhengde; Yang, Lizhuang; Zha, Rujing; Han, Long; Li, Xiaoming; Zhang, Daren; Liu, Ying; Zhang, Xiaochu

2017-08-15

Learning of prediction error (PE), including reward PE and risk PE, is crucial for updating the prediction in reinforcement learning (RL). Neurobiological and computational models of RL have reported extensive brain activations related to PE. However, the occurrence of PE does not necessarily predict updating the prediction, e.g., in a probability-known event. Therefore, the brain regions specifically engaged in updating the prediction remain unknown. Here, we conducted two functional magnetic resonance imaging (fMRI) experiments, the probability-unknown Iowa Gambling Task (IGT) and the probability-known risk decision task (RDT). Behavioral analyses confirmed that PEs occurred in both tasks but were only used for updating the prediction in the IGT. By comparing PE-related brain activations between the two tasks, we found that the rostral anterior cingulate cortex/ventral medial prefrontal cortex (rACC/vmPFC) and the posterior cingulate cortex (PCC) activated only during the IGT and were related to both reward and risk PE. Moreover, the responses in the rACC/vmPFC and the PCC were modulated by uncertainty and were associated with reward prediction-related brain regions. Electric brain stimulation over these regions lowered the performance in the IGT but not in the RDT. Our findings of a distributed neural circuit of PE processing suggest that the rACC/vmPFC and the PCC play a key role in updating the prediction through PE processing during decision making. Copyright © 2017 Elsevier Inc. All rights reserved.

Bridging from Cells to Cognition in Autism Pathophysiology: Biological Pathways to Defective Brain Function and Plasticity

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

Anderson, Matthew; Hooker, Brian S.; Herbert, Martha

We review evidence to support the model that autism may begin when a maternal environmental, infectious, or autoantibody insult causes inflammation which increases reactive oxygen species (ROS) production in the fetus, leading to fetal DNA damage (nuclear and mitochondrial), and that these inflammatory and oxidative stressors persist beyond early development (with potential further exacerbations), producing ongoing functional consequences. In organs with a high metabolic demand such as the central nervous system, the continued use of mitochondria with DNA damage may generate additional ROS which will activate the innate immune system leading to more ROS production. Such a mechanism would self-sustainmore » and possibly progressively worsen. The mitochondrial dysfunction and altered redox signal transduction pathways found in autism would conspire to activate both astroglia and microglia. These activated cells can then initiate a broad-spectrum proinflammatory gene response. Neurons may have acquired receptors for these inflammatory signals to inhibit neuronal signaling as a protection from excitotoxic damage during various pathologic insults (e.g., infection). In autism, over-zealous neuroinflammatory responses could not only influence neural developmental processes, but may more significantly impair neural signaling involved in cognition in an ongoing fashion. This model makes specific predictions in patients and experimental animal models and suggests a number of targets sites of intervention. Our model of potentially reversible pathophysiological mechanisms in autism motivates our hope that effective therapies may soon appear on the horizon.« less

Refining a measure of brain injury sequelae to predict postacute rehabilitation outcome: rating scale analysis of the Mayo-Portland Adaptability Inventory.

PubMed

Malec, J F; Moessner, A M; Kragness, M; Lezak, M D

2000-02-01

Evaluate the psychometric properties of the Mayo-Portland Adaptability Inventory (MPAI). Rating scale (Rasch) analysis of MPAI and principal component analysis of residuals; the predictive validity of the MPAI measures and raw scores was assessed in a sample from a day rehabilitation program. Outpatient brain injury rehabilitation. 305 persons with brain injury. A 22-item scale reflecting severity of sequelae of brain injury that contained a mix of indicators of impairment, activity, and participation was identified. Scores and measures for MPAI scales were strongly correlated and their predictive validities were comparable. Impairment, activity, and participation define a single dimension of brain injury sequelae. The MPAI shows promise as a measure of this construct.

Face-selective neurons maintain consistent visual responses across months

PubMed Central

McMahon, David B. T.; Jones, Adam P.; Bondar, Igor V.; Leopold, David A.

2014-01-01

Face perception in both humans and monkeys is thought to depend on neurons clustered in discrete, specialized brain regions. Because primates are frequently called upon to recognize and remember new individuals, the neuronal representation of faces in the brain might be expected to change over time. The functional properties of neurons in behaving animals are typically assessed over time periods ranging from minutes to hours, which amounts to a snapshot compared to a lifespan of a neuron. It therefore remains unclear how neuronal properties observed on a given day predict that same neuron's activity months or years later. Here we show that the macaque inferotemporal cortex contains face-selective cells that show virtually no change in their patterns of visual responses over time periods as long as one year. Using chronically implanted microwire electrodes guided by functional MRI targeting, we obtained distinct profiles of selectivity for face and nonface stimuli that served as fingerprints for individual neurons in the anterior fundus (AF) face patch within the superior temporal sulcus. Longitudinal tracking over a series of daily recording sessions revealed that face-selective neurons maintain consistent visual response profiles across months-long time spans despite the influence of ongoing daily experience. We propose that neurons in the AF face patch are specialized for aspects of face perception that demand stability as opposed to plasticity. PMID:24799679

Face-selective neurons maintain consistent visual responses across months.

PubMed

McMahon, David B T; Jones, Adam P; Bondar, Igor V; Leopold, David A

2014-06-03

Face perception in both humans and monkeys is thought to depend on neurons clustered in discrete, specialized brain regions. Because primates are frequently called upon to recognize and remember new individuals, the neuronal representation of faces in the brain might be expected to change over time. The functional properties of neurons in behaving animals are typically assessed over time periods ranging from minutes to hours, which amounts to a snapshot compared to a lifespan of a neuron. It therefore remains unclear how neuronal properties observed on a given day predict that same neuron's activity months or years later. Here we show that the macaque inferotemporal cortex contains face-selective cells that show virtually no change in their patterns of visual responses over time periods as long as one year. Using chronically implanted microwire electrodes guided by functional MRI targeting, we obtained distinct profiles of selectivity for face and nonface stimuli that served as fingerprints for individual neurons in the anterior fundus (AF) face patch within the superior temporal sulcus. Longitudinal tracking over a series of daily recording sessions revealed that face-selective neurons maintain consistent visual response profiles across months-long time spans despite the influence of ongoing daily experience. We propose that neurons in the AF face patch are specialized for aspects of face perception that demand stability as opposed to plasticity.

Interfacing to the brain’s motor decisions

PubMed Central

2017-01-01

It has been long known that neural activity, recorded with electrophysiological methods, contains rich information about a subject’s motor intentions, sensory experiences, allocation of attention, action planning, and even abstract thoughts. All these functions have been the subject of neurophysiological investigations, with the goal of understanding how neuronal activity represents behavioral parameters, sensory inputs, and cognitive functions. The field of brain-machine interfaces (BMIs) strives for a somewhat different goal: it endeavors to extract information from neural modulations to create a communication link between the brain and external devices. Although many remarkable successes have been already achieved in the BMI field, questions remain regarding the possibility of decoding high-order neural representations, such as decision making. Could BMIs be employed to decode the neural representations of decisions underlying goal-directed actions? In this review we lay out a framework that describes the computations underlying goal-directed actions as a multistep process performed by multiple cortical and subcortical areas. We then discuss how BMIs could connect to different decision-making steps and decode the neural processing ongoing before movements are initiated. Such decision-making BMIs could operate as a system with prediction that offers many advantages, such as shorter reaction time, better error processing, and improved unsupervised learning. To present the current state of the art, we review several recent BMIs incorporating decision-making components. PMID:28003406

Social dysfunction after pediatric traumatic brain injury: a translational perspective

PubMed Central

Ryan, Nicholas P.; Catroppa, Cathy; Godfrey, Celia; Noble-Haeusslein, Linda J.; Shultz, Sandy R.; O'Brien, Terence J.; Anderson, Vicki; Semple, Bridgette D.

2016-01-01

Social dysfunction is common after traumatic brain injury (TBI), contributing to reduced quality of life for survivors. Factors which influence the emergence, development or persistence of social deficits after injury remain poorly understood, particularly in the context of ongoing brain maturation during childhood. Aberrant social interactions have recently been modeled in adult and juvenile rodents after experimental TBI, providing an opportunity to gain new insights into the underlying neurobiology of these behaviors. Here, we review our current understanding of social dysfunction in both humans and rodent models of TBI, with a focus on brain injuries acquired during early development. Modulators of social outcomes are discussed, including injury-related and environmental risk and resilience factors. Disruption of social brain network connectivity and aberrant neuroendocrine function are identified as potential mechanisms of social impairments after pediatric TBI. Throughout, we highlight the overlap and disparities between outcome measures and findings from clinical and experimental approaches, and explore the translational potential of future research to prevent or ameliorate social dysfunction after childhood TBI. PMID:26949224

Pathogenesis of Alzheimer disease: role of oxidative stress, amyloid-β peptides, systemic ammonia and erythrocyte energy metabolism.

PubMed

Kosenko, Elena A; Solomadin, Iliya N; Tikhonova, Lyudmila A; Reddy, V Prakash; Aliev, Gjumrakch; Kaminsky, Yury G

2014-02-01

Aβ exerts prooxidant or antioxidant effects based on the metal ion concentrations that it sequesters from the cytosol; at low metal ion concentrations, it is an antioxidant, whereas at relatively higher concentration it is a prooxidant. Thus Alzheimer disease (AD) treatment strategies based solely on the amyloid-β clearance should be re-examined in light of the vast accumulating evidence that increased oxidative stress in the human brains is the key causative factor for AD. Accumulating evidence indicates that the reduced brain glucose availability and brain hypoxia, due to the relatively lower concentration of ATP and 2,3-diphosphoglycerate, may be associated with increased concentration of endogenous ammonia, a potential neurotoxin in the AD brains. In this review, we summarize the progress in this area, and present some of our ongoing research activities with regard to brain Amyloid-β, systemic ammonia, erythrocyte energy metabolism and the role of 2,3-diphosphoglycerate in AD pathogenesis.

NeuroGrid: recording action potentials from the surface of the brain.

PubMed

Khodagholy, Dion; Gelinas, Jennifer N; Thesen, Thomas; Doyle, Werner; Devinsky, Orrin; Malliaras, George G; Buzsáki, György

2015-02-01

Recording from neural networks at the resolution of action potentials is critical for understanding how information is processed in the brain. Here, we address this challenge by developing an organic material-based, ultraconformable, biocompatible and scalable neural interface array (the 'NeuroGrid') that can record both local field potentials(LFPs) and action potentials from superficial cortical neurons without penetrating the brain surface. Spikes with features of interneurons and pyramidal cells were simultaneously acquired by multiple neighboring electrodes of the NeuroGrid, allowing for the isolation of putative single neurons in rats. Spiking activity demonstrated consistent phase modulation by ongoing brain oscillations and was stable in recordings exceeding 1 week's duration. We also recorded LFP-modulated spiking activity intraoperatively in patients undergoing epilepsy surgery. The NeuroGrid constitutes an effective method for large-scale, stable recording of neuronal spikes in concert with local population synaptic activity, enhancing comprehension of neural processes across spatiotemporal scales and potentially facilitating diagnosis and therapy for brain disorders.

Functional neuroanatomy of disorders of consciousness.

PubMed

Di Perri, Carol; Stender, Johan; Laureys, Steven; Gosseries, Olivia

2014-01-01

Our understanding of the mechanisms of loss and recovery of consciousness, following severe brain injury or during anesthesia, is changing rapidly. Recent neuroimaging studies have shown that patients with chronic disorders of consciousness and subjects undergoing general anesthesia present a complex dysfunctionality in the architecture of brain connectivity. At present, the global hallmark of impaired consciousness appears to be a multifaceted dysfunctional connectivity pattern with both within-network loss of connectivity in a widespread frontoparietal network and between-network hyperconnectivity involving other regions such as the insula and ventral tegmental area. Despite ongoing efforts, the mechanisms underlying the emergence of consciousness after severe brain injury are not thoroughly understood. Important questions remain unanswered: What triggers the connectivity impairment leading to disorders of consciousness? Why do some patients recover from coma, while others with apparently similar brain injuries do not? Understanding these mechanisms could lead to a better comprehension of brain function and, hopefully, lead to new therapeutic strategies in this challenging patient population. © 2013.

Whole brain radiotherapy for brain metastasis

PubMed Central

McTyre, Emory; Scott, Jacob; Chinnaiyan, Prakash

2013-01-01

Whole brain radiotherapy (WBRT) is a mainstay of treatment in patients with both identifiable brain metastases and prophylaxis for microscopic disease. The use of WBRT has decreased somewhat in recent years due to both advances in radiation technology, allowing for a more localized delivery of radiation, and growing concerns regarding the late toxicity profile associated with WBRT. This has prompted the development of several recent and ongoing prospective studies designed to provide Level I evidence to guide optimal treatment approaches for patients with intracranial metastases. In addition to defining the role of WBRT in patients with brain metastases, identifying methods to improve WBRT is an active area of investigation, and can be classified into two general categories: Those designed to decrease the morbidity of WBRT, primarily by reducing late toxicity, and those designed to improve the efficacy of WBRT. Both of these areas of research show diversity and promise, and it seems feasible that in the near future, the efficacy/toxicity ratio may be improved, allowing for a more diverse clinical application of WBRT. PMID:23717795

The implications of brain connectivity in the neuropsychology of autism

PubMed Central

Maximo, Jose O.; Cadena, Elyse J.; Kana, Rajesh K.

2014-01-01

Autism is a neurodevelopmental disorder that has been associated with atypical brain functioning. Functional connectivity MRI (fcMRI) studies examining neural networks in autism have seen an exponential rise over the last decade. Such investigations have led to characterization of autism as a distributed neural systems disorder. Studies have found widespread cortical underconnectivity, local overconnectivity, and mixed results suggesting disrupted brain connectivity as a potential neural signature of autism. In this review, we summarize the findings of previous fcMRI studies in autism with a detailed examination of their methodology, in order to better understand its potential and to delineate the pitfalls. We also address how a multimodal neuroimaging approach (incorporating different measures of brain connectivity) may help characterize the complex neurobiology of autism at a global level. Finally, we also address the potential of neuroimaging-based markers in assisting neuropsychological assessment of autism. The quest for a biomarker for autism is still ongoing, yet new findings suggest that aberrant brain connectivity may be a promising candidate. PMID:24496901

Investigations of HPA Function and the Enduring Consequences of Stressors in Adolescence in Animal Models

ERIC Educational Resources Information Center

McCormick, Cheryl M.; Mathews, Iva Z.; Thomas, Catherine; Waters, Patti

2010-01-01

Developmental differences in hypothalamic-pituitary-adrenal (HPA) axis responsiveness to stressors and ongoing development of glucocorticoid-sensitive brain regions in adolescence suggest that similar to the neonatal period of ontogeny, adolescence may also be a sensitive period for programming effects of stressors on the central nervous system.…

Interactive Learning to Stimulate the Brain's Visual Center and to Enhance Memory Retention

ERIC Educational Resources Information Center

Yun, Yang H.; Allen, Philip A.; Chaumpanich, Kritsakorn; Xiao, Yingcai

2014-01-01

This short paper describes an ongoing NSF-funded project on enhancing science and engineering education using the latest technology. More specifically, the project aims at developing an interactive learning system with Microsoft Kinect™ and Unity3D game engine. This system promotes active, rather than passive, learning by employing embodied…

Baseline Cognition, Behavior, and Motor Skills in Children with New-Onset, Idiopathic Epilepsy

ERIC Educational Resources Information Center

Bhise, Vikram V.; Burack, Gail D.; Mandelbaum, David E.

2010-01-01

Aim: Epilepsy is associated with difficulties in cognition and behavior in children. These problems have been attributed to genetics, ongoing seizures, psychosocial issues, underlying abnormality of the brain, and/or antiepileptic drugs. In a previous study, we found baseline cognitive differences between children with partial versus generalized…

A Primer on Persistent Postconcussion Symptoms

ERIC Educational Resources Information Center

Jantz, Paul B.

2015-01-01

The existence of persistent postconcussion symptoms (PPCS) is controversial, and there is ongoing debate as to whether the etiology of PPCS is psychogenic or physiogenic. In addition, there is a lack of agreement on diagnostic definitions of mild traumatic brain injury (mTBI) and concussion and the terms are used interchangeably in the research…

Developing a Deep Brain Stimulation Neuromodulation Network for Parkinson Disease, Essential Tremor, and Dystonia: Report of a Quality Improvement Project

PubMed Central

O’Suilleabhain, Padraig E.; Sanghera, Manjit; Patel, Neepa; Khemani, Pravin; Lacritz, Laura H.; Chitnis, Shilpa; Whitworth, Louis A.; Dewey, Richard B.

2016-01-01

Objective To develop a process to improve patient outcomes from deep brain stimulation (DBS) surgery for Parkinson disease (PD), essential tremor (ET), and dystonia. Methods We employed standard quality improvement methodology using the Plan-Do-Study-Act process to improve patient selection, surgical DBS lead implantation, postoperative programming, and ongoing assessment of patient outcomes. Results The result of this quality improvement process was the development of a neuromodulation network. The key aspect of this program is rigorous patient assessment of both motor and non-motor outcomes tracked longitudinally using a REDCap database. We describe how this information is used to identify problems and to initiate Plan-Do-Study-Act cycles to address them. Preliminary outcomes data is presented for the cohort of PD and ET patients who have received surgery since the creation of the neuromodulation network. Conclusions Careful outcomes tracking is essential to ensure quality in a complex therapeutic endeavor like DBS surgery for movement disorders. The REDCap database system is well suited to store outcomes data for the purpose of ongoing quality assurance monitoring. PMID:27711133

Developing a Deep Brain Stimulation Neuromodulation Network for Parkinson Disease, Essential Tremor, and Dystonia: Report of a Quality Improvement Project.

PubMed

Dewey, Richard B; O'Suilleabhain, Padraig E; Sanghera, Manjit; Patel, Neepa; Khemani, Pravin; Lacritz, Laura H; Chitnis, Shilpa; Whitworth, Louis A; Dewey, Richard B

2016-01-01

To develop a process to improve patient outcomes from deep brain stimulation (DBS) surgery for Parkinson disease (PD), essential tremor (ET), and dystonia. We employed standard quality improvement methodology using the Plan-Do-Study-Act process to improve patient selection, surgical DBS lead implantation, postoperative programming, and ongoing assessment of patient outcomes. The result of this quality improvement process was the development of a neuromodulation network. The key aspect of this program is rigorous patient assessment of both motor and non-motor outcomes tracked longitudinally using a REDCap database. We describe how this information is used to identify problems and to initiate Plan-Do-Study-Act cycles to address them. Preliminary outcomes data is presented for the cohort of PD and ET patients who have received surgery since the creation of the neuromodulation network. Careful outcomes tracking is essential to ensure quality in a complex therapeutic endeavor like DBS surgery for movement disorders. The REDCap database system is well suited to store outcomes data for the purpose of ongoing quality assurance monitoring.

T-cell- and macrophage-mediated axon damage in the absence of a CNS-specific immune response: involvement of metalloproteinases.

PubMed

Newman, T A; Woolley, S T; Hughes, P M; Sibson, N R; Anthony, D C; Perry, V H

2001-11-01

Recent evidence has highlighted the fact that axon injury is an important component of multiple sclerosis pathology. The issue of whether a CNS antigen-specific immune response is required to produce axon injury remains unresolved. We investigated the extent and time course of axon injury in a rodent model of a delayed-type hypersensitivity (DTH) reaction directed against the mycobacterium bacille Calmette-Guérin (BCG). Using MRI, we determined whether the ongoing axon injury is restricted to the period during which the blood-brain barrier is compromised. DTH lesions were initiated in adult rats by intracerebral injection of heat-killed BCG followed by a peripheral challenge with BCG. Our findings demonstrate that a DTH reaction to a non-CNS antigen within a CNS white matter tract leads to axon injury. Ongoing axon injury persisted throughout the 3-month period studied and was not restricted to the period of blood-brain barrier breakdown, as detected by MRI enhancing lesions. We have previously demonstrated that matrix metalloproteinases (MMPs) are upregulated in multiple sclerosis plaques and DTH lesions. In this study we demonstrated that microinjection of activated MMPs into the cortical white matter results in axon injury. Our results show that axon injury, possibly mediated by MMPs, is immunologically non-specific and may continue behind an intact blood-brain barrier.

Differences between chronological and brain age are related to education and self-reported physical activity.

PubMed

Steffener, Jason; Habeck, Christian; O'Shea, Deirdre; Razlighi, Qolamreza; Bherer, Louis; Stern, Yaakov

2016-04-01

This study investigated the relationship between education and physical activity and the difference between a physiological prediction of age and chronological age (CA). Cortical and subcortical gray matter regional volumes were calculated from 331 healthy adults (range: 19-79 years). Multivariate analyses identified a covariance pattern of brain volumes best predicting CA (R(2) = 47%). Individual expression of this brain pattern served as a physiologic measure of brain age (BA). The difference between CA and BA was predicted by education and self-report measures of physical activity. Education and the daily number of flights of stairs climbed (FOSC) were the only 2 significant predictors of decreased BA. Effect sizes demonstrated that BA decreased by 0.95 years for each year of education and by 0.58 years for 1 additional FOSC daily. Effects of education and FOSC on regional brain volume were largely driven by temporal and subcortical volumes. These results demonstrate that higher levels of education and daily FOSC are related to larger brain volume than predicted by CA which supports the utility of regional gray matter volume as a biomarker of healthy brain aging. Copyright © 2016 Elsevier Inc. All rights reserved.

Development of a Physiologically-Based Pharmacokinetic Model of the Rat Central Nervous System

PubMed Central

Badhan, Raj K. Singh; Chenel, Marylore; Penny, Jeffrey I.

2014-01-01

Central nervous system (CNS) drug disposition is dictated by a drug’s physicochemical properties and its ability to permeate physiological barriers. The blood–brain barrier (BBB), blood-cerebrospinal fluid barrier and centrally located drug transporter proteins influence drug disposition within the central nervous system. Attainment of adequate brain-to-plasma and cerebrospinal fluid-to-plasma partitioning is important in determining the efficacy of centrally acting therapeutics. We have developed a physiologically-based pharmacokinetic model of the rat CNS which incorporates brain interstitial fluid (ISF), choroidal epithelial and total cerebrospinal fluid (CSF) compartments and accurately predicts CNS pharmacokinetics. The model yielded reasonable predictions of unbound brain-to-plasma partition ratio (Kpuu,brain) and CSF:plasma ratio (CSF:Plasmau) using a series of in vitro permeability and unbound fraction parameters. When using in vitro permeability data obtained from L-mdr1a cells to estimate rat in vivo permeability, the model successfully predicted, to within 4-fold, Kpuu,brain and CSF:Plasmau for 81.5% of compounds simulated. The model presented allows for simultaneous simulation and analysis of both brain biophase and CSF to accurately predict CNS pharmacokinetics from preclinical drug parameters routinely available during discovery and development pathways. PMID:24647103

Big data challenges in decoding cortical activity in a human with quadriplegia to inform a brain computer interface.

PubMed

Friedenberg, David A; Bouton, Chad E; Annetta, Nicholas V; Skomrock, Nicholas; Mingming Zhang; Schwemmer, Michael; Bockbrader, Marcia A; Mysiw, W Jerry; Rezai, Ali R; Bresler, Herbert S; Sharma, Gaurav

2016-08-01

Recent advances in Brain Computer Interfaces (BCIs) have created hope that one day paralyzed patients will be able to regain control of their paralyzed limbs. As part of an ongoing clinical study, we have implanted a 96-electrode Utah array in the motor cortex of a paralyzed human. The array generates almost 3 million data points from the brain every second. This presents several big data challenges towards developing algorithms that should not only process the data in real-time (for the BCI to be responsive) but are also robust to temporal variations and non-stationarities in the sensor data. We demonstrate an algorithmic approach to analyze such data and present a novel method to evaluate such algorithms. We present our methodology with examples of decoding human brain data in real-time to inform a BCI.

What cues do nurses use to predict aggression in people with acquired brain injury?

PubMed

Pryor, Julie

2005-04-01

There is a paucity of research on the frequent and repeated episodes of aggression and violence experienced by nurses when working with people who have an acquired brain injury. The purpose of this study was to bring this issue into focus by identifying the cues nurses use to predict aggression in people with acquired brain injury. Twenty-eight nurses from 10 different inpatient brain injury rehabilitation units in Australia participated in the study. Participants were interviewed using the Critical Decision Method on a one to one basis for up to one and one half hours on two consecutive days. Transcripts of the interviews were analysed using thematic analysis. Results revealed that nurses identified five groups of cues that predict aggression in a patient: (1) what a patient is saying; (2) changes in a patient's voice; (3) changes in a patient's face; (4) changes in a patient's behavior; and (5) a patient's emotions. Nurses reported using multiple cues to predict aggression and highlighted the importance of personal knowledge of the patient in conjunction with identified cues when predicting aggression. Nurses caring for patients with acquired brain injury can predict many episodes of aggression, though not all, by identifying cues from the patient.

Prediction of brain tissue temperature using near-infrared spectroscopy

PubMed Central

Holper, Lisa; Mitra, Subhabrata; Bale, Gemma; Robertson, Nicola; Tachtsidis, Ilias

2017-01-01

Abstract. Broadband near-infrared spectroscopy (NIRS) can provide an endogenous indicator of tissue temperature based on the temperature dependence of the water absorption spectrum. We describe a first evaluation of the calibration and prediction of brain tissue temperature obtained during hypothermia in newborn piglets (animal dataset) and rewarming in newborn infants (human dataset) based on measured body (rectal) temperature. The calibration using partial least squares regression proved to be a reliable method to predict brain tissue temperature with respect to core body temperature in the wavelength interval of 720 to 880 nm with a strong mean predictive power of R2=0.713±0.157 (animal dataset) and R2=0.798±0.087 (human dataset). In addition, we applied regression receiver operating characteristic curves for the first time to evaluate the temperature prediction, which provided an overall mean error bias between NIRS predicted brain temperature and body temperature of 0.436±0.283°C (animal dataset) and 0.162±0.149°C (human dataset). We discuss main methodological aspects, particularly the well-known aspect of over- versus underestimation between brain and body temperature, which is relevant for potential clinical applications. PMID:28630878

Brain Network Theory Can Predict Whether Neuropsychological Outcomes Will Differ from Clinical Expectations.

PubMed

Warren, David E; Denburg, Natalie L; Power, Jonathan D; Bruss, Joel; Waldron, Eric J; Sun, Haoxin; Petersen, Steve E; Tranel, Daniel

2017-02-01

Theories of brain-network organization based on neuroimaging data have burgeoned in recent years, but the predictive power of such theories for cognition and behavior has only rarely been examined. Here, predictions from clinical neuropsychologists about the cognitive profiles of patients with focal brain lesions were used to evaluate a brain-network theory (Warren et al., 2014). Neuropsychologists made predictions regarding the neuropsychological profiles of a neurological patient sample (N = 30) based on lesion location. The neuropsychologists then rated the congruence of their predictions with observed neuropsychological outcomes, in regard to the "severity" of neuropsychological deficits and the "focality" of neuropsychological deficits. Based on the network theory, two types of lesion locations were identified: "target" locations (putative hubs in a brain-wide network) and "control" locations (hypothesized to play limited roles in network function). We found that patients with lesions of target locations (N = 19) had deficits of greater than expected severity that were more widespread than expected, whereas patients with lesions of control locations (N = 11) showed milder, circumscribed deficits that were more congruent with expectations. The findings for the target brain locations suggest that prevailing views of brain-behavior relationships may be sharpened and refined by integrating recently proposed network-oriented perspectives. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Cerebral oxygenation in traumatic brain injury; Can a non-invasive frequency domain near-infrared spectroscopy device detect changes in brain tissue oxygen tension as well as the established invasive monitor?

PubMed

Davies, David James; Clancy, Michael; Dehghani, Hamid; Lucas, Samuel John Edwin; Forcione, Mario; Yakoub, Kamal Makram; Belli, Antonio

2018-06-07

The cost and highly invasive nature of brain monitoring modality in traumatic brain injury patients currently restrict its utility to specialist neurological intensive care settings. We aim to test the abilities of a frequency domain near-infrared spectroscopy (FD-NIRS) device in predicting changes in invasively measured brain tissue oxygen tension. Individuals admitted to a United Kingdom specialist major trauma centre were contemporaneously monitored with an FD-NIRS device and invasively measured brain tissue oxygen tension probe. Area under the curve receiver operating characteristic (AUROC) statistical analysis was utilised to assess the predictive power of FD-NIRS in detecting both moderate and severe hypoxia (20 and 10 mmHg, respectively), as measured invasively. 16 individuals were prospectively recruited to the investigation. Severe hypoxic episodes were detected in 9 of these individuals, with the NIRS demonstrating a broad range of predictive abilities (AUROC 0.68-0.88) from relatively poor to good. Moderate hypoxic episodes were detected in seven individuals with similar predictive performance (AUROC 0.576 - 0.905). A variable performance in the predictive powers of this FD-NIRS device to detect changes in brain tissue oxygen was demonstrated. Consequently, this enhanced NIRS technology has not demonstrated sufficient ability to replace the established invasive measurement.

Relative value of diverse brain MRI and blood-based biomarkers for predicting cognitive decline in the elderly

NASA Astrophysics Data System (ADS)

Madsen, Sarah K.; Ver Steeg, Greg; Daianu, Madelaine; Mezher, Adam; Jahanshad, Neda; Nir, Talia M.; Hua, Xue; Gutman, Boris A.; Galstyan, Aram; Thompson, Paul M.

2016-03-01

Cognitive decline accompanies many debilitating illnesses, including Alzheimer's disease (AD). In old age, brain tissue loss also occurs along with cognitive decline. Although blood tests are easier to perform than brain MRI, few studies compare brain scans to standard blood tests to see which kinds of information best predict future decline. In 504 older adults from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we first used linear regression to assess the relative value of different types of data to predict cognitive decline, including 196 blood panel biomarkers, 249 MRI biomarkers obtained from the FreeSurfer software, demographics, and the AD-risk gene APOE. A subset of MRI biomarkers was the strongest predictor. There was no specific blood marker that increased predictive accuracy on its own, we found that a novel unsupervised learning method, CorEx, captured weak correlations among blood markers, and the resulting clusters offered unique predictive power.

The possibility of application of spiral brain computed tomography to traumatic brain injury.

PubMed

Lim, Daesung; Lee, Soo Hoon; Kim, Dong Hoon; Choi, Dae Seub; Hong, Hoon Pyo; Kang, Changwoo; Jeong, Jin Hee; Kim, Seong Chun; Kang, Tae-Sin

2014-09-01

The spiral computed tomography (CT) with the advantage of low radiation dose, shorter test time required, and its multidimensional reconstruction is accepted as an essential diagnostic method for evaluating the degree of injury in severe trauma patients and establishment of therapeutic plans. However, conventional sequential CT is preferred for the evaluation of traumatic brain injury (TBI) over spiral CT due to image noise and artifact. We aimed to compare the diagnostic power of spiral facial CT for TBI to that of conventional sequential brain CT. We evaluated retrospectively the images of 315 traumatized patients who underwent both brain CT and facial CT simultaneously. The hemorrhagic traumatic brain injuries such as epidural hemorrhage, subdural hemorrhage, subarachnoid hemorrhage, and contusional hemorrhage were evaluated in both images. Statistics were performed using Cohen's κ to compare the agreement between 2 imaging modalities and sensitivity, specificity, positive predictive value, and negative predictive value of spiral facial CT to conventional sequential brain CT. Almost perfect agreement was noted regarding hemorrhagic traumatic brain injuries between spiral facial CT and conventional sequential brain CT (Cohen's κ coefficient, 0.912). To conventional sequential brain CT, sensitivity, specificity, positive predictive value, and negative predictive value of spiral facial CT were 92.2%, 98.1%, 95.9%, and 96.3%, respectively. In TBI, the diagnostic power of spiral facial CT was equal to that of conventional sequential brain CT. Therefore, expanded spiral facial CT covering whole frontal lobe can be applied to evaluate TBI in the future. Copyright © 2014 Elsevier Inc. All rights reserved.

Expansion of Multipotent Stem Cells from the Adult Human Brain

PubMed Central

Murrell, Wayne; Palmero, Emily; Bianco, John; Stangeland, Biljana; Joel, Mrinal; Paulson, Linda; Thiede, Bernd; Grieg, Zanina; Ramsnes, Ingunn; Skjellegrind, Håvard K.; Nygård, Ståle; Brandal, Petter; Sandberg, Cecilie; Vik-Mo, Einar; Palmero, Sheryl; Langmoen, Iver A.

2013-01-01

The discovery of stem cells in the adult human brain has revealed new possible scenarios for treatment of the sick or injured brain. Both clinical use of and preclinical research on human adult neural stem cells have, however, been seriously hampered by the fact that it has been impossible to passage these cells more than a very few times and with little expansion of cell numbers. Having explored a number of alternative culturing conditions we here present an efficient method for the establishment and propagation of human brain stem cells from whatever brain tissue samples we have tried. We describe virtually unlimited expansion of an authentic stem cell phenotype. Pluripotency proteins Sox2 and Oct4 are expressed without artificial induction. For the first time multipotency of adult human brain-derived stem cells is demonstrated beyond tissue boundaries. We characterize these cells in detail in vitro including microarray and proteomic approaches. Whilst clarification of these cells’ behavior is ongoing, results so far portend well for the future repair of tissues by transplantation of an adult patient’s own-derived stem cells. PMID:23967194

The Case for Reasonable Accommodation of Conscientious Objections to Declarations of Brain Death.

PubMed

Johnson, L Syd M

2016-03-01

Since its inception in 1968, the concept of whole-brain death has been contentious, and four decades on, controversy concerning the validity and coherence of whole-brain death continues unabated. Although whole-brain death is legally recognized and medically entrenched in the United States and elsewhere, there is reasonable disagreement among physicians, philosophers, and the public concerning whether brain death is really equivalent to death as it has been traditionally understood. A handful of states have acknowledged this plurality of viewpoints and enacted "conscience clauses" that require "reasonable accommodation" of religious and moral objections to the determination of death by neurological criteria. This paper argues for the universal adoption of "reasonable accommodation" policies using the New Jersey statute as a model, in light of both the ongoing controversy and the recent case of Jahi McMath, a child whose family raised religious objections to a declaration of brain death. Public policies that accommodate reasonable, divergent viewpoints concerning death provide a practical and compassionate way to resolve those conflicts that are the most urgent, painful, and difficult to reconcile.

Novel delivery methods bypassing the blood-brain and blood-tumor barriers.

PubMed

Hendricks, Benjamin K; Cohen-Gadol, Aaron A; Miller, James C

2015-03-01

Glioblastoma (GBM) is the most common primary brain tumor and carries a grave prognosis. Despite years of research investigating potentially new therapies for GBM, the median survival rate of individuals with this disease has remained fairly stagnant. Delivery of drugs to the tumor site is hampered by various barriers posed by the GBM pathological process and by the complex physiology of the blood-brain and blood-cerebrospinal fluid barriers. These anatomical and physiological barriers serve as a natural protection for the brain and preserve brain homeostasis, but they also have significantly limited the reach of intraparenchymal treatments in patients with GBM. In this article, the authors review the functional capabilities of the physical and physiological barriers that impede chemotherapy for GBM, with a specific focus on the pathological alterations of the blood-brain barrier (BBB) in this disease. They also provide an overview of current and future methods for circumventing these barriers in therapeutic interventions. Although ongoing research has yielded some potential options for future GBM therapies, delivery of chemotherapy medications across the BBB remains elusive and has limited the efficacy of these medications.

Regulation of cerebrospinal fluid (CSF) flow in neurodegenerative, neurovascular and neuroinflammatory disease

PubMed Central

Simon, Matthew J.; Iliff, Jeffrey J.

2015-01-01

Cerebrospinal fluid (CSF) circulation and turnover provides a sink for the elimination of solutes from the brain interstitium, serving an important homeostatic role for the function of the central nervous system. Disruption of normal CSF circulation and turnover is believed to contribute to the development of many diseases, including neurodegenerative conditions such as Alzheimer’s disease, ischemic and traumatic brain injury, and neuroinflammatory conditions such as multiple sclerosis. Recent insights into CSF biology suggesting that CSF and interstitial fluid exchange along a brain-wide network of perivascular spaces termed the ‘glymphatic’ system suggest that CSF circulation may interact intimately with glial and vascular function to regulate basic aspects of brain function. Dysfunction within this glial vascular network, which is a feature of the aging and injured brain, is a potentially critical link between brain injury, neuroinflammation and the development of chronic neurodegeneration. Ongoing research within this field may provide a powerful new framework for understanding the common links between neurodegenerative, neurovascular and neuroinflammatory disease, in addition to providing potentially novel therapeutic targets for these conditions. PMID:26499397

Hitting a Moving Target: Basic Mechanisms of Recovery from Acquired Developmental Brain Injury

PubMed Central

Giza, Christopher C.; Kolb, Bryan; Harris, Neil G.; Asarnow, Robert F.; Prins, Mayumi L.

2009-01-01

Acquired brain injuries represent a major cause of disability in the pediatric population. Understanding responses to developmental acquired brain injuries requires knowledge of the neurobiology of normal development, age-at-injury effects and experience-dependent neuroplasticity. In the developing brain, full recovery cannot be considered as a return to the premorbid baseline, since ongoing maturation means that cerebral functioning in normal individuals will continue to advance. Thus, the recovering immature brain has to ‘hit a moving target’ to achieve full functional recovery, defined as parity with age-matched uninjured peers. This review will discuss the consequences of developmental injuries such as focal lesions, diffuse hypoxia and traumatic brain injury (TBI). Underlying cellular and physiological mechanisms relevant to age-at-injury effects will be described in considerable detail, including but not limited to alterations in neurotransmission, connectivity/network functioning, the extracellular matrix, response to oxidative stress and changes in cerebral metabolism. Finally, mechanisms of experience-dependent plasticity will be reviewed in conjunction with their effects on neural repair and recovery. PMID:19956795

Cadmium concentrations in the brains of Alzheimer cases

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

Spyrou, N.M.; Stedman, J.D.

1996-12-31

There is ongoing research in relating the concentration of elements in the brain with Alzheimer`s disease. The presence of particular elements, such as aluminum and vanadium, has been considered as a possible environmental factor, creating significant interest and controversy in the field. We have been analyzing brain tissue from the MRC Alzheimer`s Disease Brain Bank, Institute of Psychiatry, from a number of cortical regions of the brain, namely, the frontal, occipital, parietal, and temporal lobes, as well as from the left and right hemispheres of the same brain whenever possible. The techniques employed have been proton-induced X-ray emission (PIXE) analysis,more » proton-induced gamma-ray emission (PIGE) analysis, Rutherford backscattering (RBS), and instrumental neutron activation analysis. Neutron irradiations were carried out at the Imperial College Consort II reactor, whereas for PIXE, PIGE, and RBS, the University of Surrey Accelerator Laboratories were used employing a Van de Graaff accelerator. In this paper, we present the cadmium results from the frontal lobe of Alzheimer cases and controls determined by PIXE analysis.« less

Regional Differences in Brain Volume Predict the Acquisition of Skill in a Complex Real-Time Strategy Videogame

PubMed Central

Basak, Chandramallika; Voss, Michelle W.; Erickson, Kirk I.; Boot, Walter R.; Kramer, Arthur F.

2015-01-01

Previous studies have found that differences in brain volume among older adults predict performance in laboratory tasks of executive control, memory, and motor learning. In the present study we asked whether regional differences in brain volume as assessed by the application of a voxel-based morphometry technique on high resolution MRI would also be useful in predicting the acquisition of skill in complex tasks, such as strategy-based video games. Twenty older adults were trained for over 20 hours to play Rise of Nations, a complex real-time strategy game. These adults showed substantial improvements over the training period in game performance. MRI scans obtained prior to training revealed that the volume of a number of brain regions, which have been previously associated with subsets of the trained skills, predicted a substantial amount of variance in learning on the complex game. Thus, regional differences in brain volume can predict learning in complex tasks that entail the use of a variety of perceptual, cognitive and motor processes. PMID:21546146

Regional differences in brain volume predict the acquisition of skill in a complex real-time strategy videogame.

PubMed

Basak, Chandramallika; Voss, Michelle W; Erickson, Kirk I; Boot, Walter R; Kramer, Arthur F

2011-08-01

Previous studies have found that differences in brain volume among older adults predict performance in laboratory tasks of executive control, memory, and motor learning. In the present study we asked whether regional differences in brain volume as assessed by the application of a voxel-based morphometry technique on high resolution MRI would also be useful in predicting the acquisition of skill in complex tasks, such as strategy-based video games. Twenty older adults were trained for over 20 h to play Rise of Nations, a complex real-time strategy game. These adults showed substantial improvements over the training period in game performance. MRI scans obtained prior to training revealed that the volume of a number of brain regions, which have been previously associated with subsets of the trained skills, predicted a substantial amount of variance in learning on the complex game. Thus, regional differences in brain volume can predict learning in complex tasks that entail the use of a variety of perceptual, cognitive and motor processes. Copyright © 2011 Elsevier Inc. All rights reserved.

Outcome prediction in home- and community-based brain injury rehabilitation using the Mayo-Portland Adaptability Inventory.

PubMed

Malec, James F; Parrot, Devan; Altman, Irwin M; Swick, Shannon

2015-01-01

The objective of the study was to develop statistical formulas to predict levels of community participation on discharge from post-hospital brain injury rehabilitation using retrospective data analysis. Data were collected from seven geographically distinct programmes in a home- and community-based brain injury rehabilitation provider network. Participants were 642 individuals with post-traumatic brain injury. Interventions consisted of home- and community-based brain injury rehabilitation. The main outcome measure was the Mayo-Portland Adaptability Inventory (MPAI-4) Participation Index. Linear discriminant models using admission MPAI-4 Participation Index score and log chronicity correctly predicted excellent (no to minimal participation limitations), very good (very mild participation limitations), good (mild participation limitations), and limited (significant participation limitations) outcome levels at discharge. Predicting broad outcome categories for post-hospital rehabilitation programmes based on admission assessment data appears feasible and valid. Equations to provide patients and families with probability statements on admission about expected levels of outcome are provided. It is unknown to what degree these prediction equations can be reliably applied and valid in other settings.

Restoration of Function With Acupuncture Following Severe Traumatic Brain Injury: A Case Report.

PubMed

Wolf, Jacob; Sparks, Linda; Deng, Yong; Langland, Jeffrey

2015-11-01

This case report illustrates the improvement of an acupuncture-treated patient who incurred a severe traumatic brain injury (TBI) from a snowboarding accident. Over 4 years, the patient progressed from initially not being able to walk, having difficulty with speech, and suffering from poor eyesight to where he has now regained significant motor function, speech, and vision and has returned to snowboarding. A core acupuncture protocol plus specific points added to address the patient's ongoing concerns was used. This case adds to the medical literature by demonstrating the potential role of acupuncture in TBI treatment.

Harvard Aging Brain Study: Dataset and accessibility.

PubMed

Dagley, Alexander; LaPoint, Molly; Huijbers, Willem; Hedden, Trey; McLaren, Donald G; Chatwal, Jasmeer P; Papp, Kathryn V; Amariglio, Rebecca E; Blacker, Deborah; Rentz, Dorene M; Johnson, Keith A; Sperling, Reisa A; Schultz, Aaron P

2017-01-01

The Harvard Aging Brain Study is sharing its data with the global research community. The longitudinal dataset consists of a 284-subject cohort with the following modalities acquired: demographics, clinical assessment, comprehensive neuropsychological testing, clinical biomarkers, and neuroimaging. To promote more extensive analyses, imaging data was designed to be compatible with other publicly available datasets. A cloud-based system enables access to interested researchers with blinded data available contingent upon completion of a data usage agreement and administrative approval. Data collection is ongoing and currently in its fifth year. Copyright © 2015 Elsevier Inc. All rights reserved.

Gender differences in autobiographical memory for everyday events: retrieval elicited by SenseCam images versus verbal cues.

PubMed

St Jacques, Peggy L; Conway, Martin A; Cabeza, Roberto

2011-10-01

Gender differences are frequently observed in autobiographical memory (AM). However, few studies have investigated the neural basis of potential gender differences in AM. In the present functional MRI (fMRI) study we investigated gender differences in AMs elicited using dynamic visual images vs verbal cues. We used a novel technology called a SenseCam, a wearable device that automatically takes thousands of photographs. SenseCam differs considerably from other prospective methods of generating retrieval cues because it does not disrupt the ongoing experience. This allowed us to control for potential gender differences in emotional processing and elaborative rehearsal, while manipulating how the AMs were elicited. We predicted that males would retrieve more richly experienced AMs elicited by the SenseCam images vs the verbal cues, whereas females would show equal sensitivity to both cues. The behavioural results indicated that there were no gender differences in subjective ratings of reliving, importance, vividness, emotion, and uniqueness, suggesting that gender differences in brain activity were not due to differences in these measures of phenomenological experience. Consistent with our predictions, the fMRI results revealed that males showed a greater difference in functional activity associated with the rich experience of SenseCam vs verbal cues, than did females.

Testing theories of irony processing using eye-tracking and ERPs.

PubMed

Filik, Ruth; Leuthold, Hartmut; Wallington, Katie; Page, Jemma

2014-05-01

Not much is known about how people comprehend ironic utterances, and to date, most studies have simply compared processing of ironic versus non-ironic statements. A key aspect of the graded salience hypothesis, distinguishing it from other accounts (such as the standard pragmatic view and direct access view), is that it predicts differences between processing of familiar and unfamiliar ironies. Specifically, if an ironic utterance is familiar, then the ironic interpretation should be available without the need for extra inferential processes, whereas for unfamiliar ironies, the literal interpretation would be computed first, and a mismatch with context would lead to a re-interpretation of the statement as being ironic. We recorded participants' eye movements while they were reading (Experiment 1), and electrical brain activity while they were listening to (Experiment 2), familiar and unfamiliar ironies compared to non-ironic controls. Results show disruption to eye movements and an N400-like effect for unfamiliar ironies only, supporting the predictions of the graded salience hypothesis. In addition, in Experiment 2, a late positivity was found for both familiar and unfamiliar ironic materials, compared to non-ironic controls. We interpret this positivity as reflecting ongoing conflict between the literal and ironic interpretations of the utterance. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Birth weight interacts with a functional variant of the oxytocin receptor gene (OXTR) to predict executive functioning in children.

PubMed

Wade, Mark; Prime, Heather; Hoffmann, Thomas J; Schmidt, Louis A; O'Connor, Thomas G; Jenkins, Jennifer M

2018-02-01

Genetic variation in the oxytocin receptor gene (OXTR) is associated with several psychiatric conditions characterized by deficits in executive functioning (EF). A specific OXTR variant, rs2254298, has previously been associated with brain functioning in regions implicated in EF. Moreover, birth weight variation across the entire range is associated with individual differences in cortical structure and function that underlie EF. This is the first study to examine the main and interactive effect between rs2254298 and birth weight on EF in children. The sample consisted of 310 children from an ongoing longitudinal study. EF was measured at age 4.5 using observational tasks indexing working memory, cognitive flexibility, and inhibitory control. A family-based design that controlled for population admixture, stratification, and nongenomic confounds was employed. A significant genetic association between rs2254298 and EF was observed, with more copies of the major allele (G) associated with higher EF. There was also a significant interaction between rs2254298 and birth weight, such that more copies of the major allele in combination with higher birth weight predicted better EF. Findings suggest that OXTR may be associated with discrete neurocognitive abilities in childhood, and these effects may be modulated by intrauterine conditions related to fetal growth and development.

Dynamic Filtering Improves Attentional State Prediction with fNIRS

NASA Technical Reports Server (NTRS)

Harrivel, Angela R.; Weissman, Daniel H.; Noll, Douglas C.; Huppert, Theodore; Peltier, Scott J.

2016-01-01

Brain activity can predict a person's level of engagement in an attentional task. However, estimates of brain activity are often confounded by measurement artifacts and systemic physiological noise. The optimal method for filtering this noise - thereby increasing such state prediction accuracy - remains unclear. To investigate this, we asked study participants to perform an attentional task while we monitored their brain activity with functional near infrared spectroscopy (fNIRS). We observed higher state prediction accuracy when noise in the fNIRS hemoglobin [Hb] signals was filtered with a non-stationary (adaptive) model as compared to static regression (84% +/- 6% versus 72% +/- 15%).

A nomogram to predict brain metastasis as the first relapse in curatively resected non-small cell lung cancer patients.

PubMed

Won, Young-Woong; Joo, Jungnam; Yun, Tak; Lee, Geon-Kook; Han, Ji-Youn; Kim, Heung Tae; Lee, Jin Soo; Kim, Moon Soo; Lee, Jong Mog; Lee, Hyun-Sung; Zo, Jae Ill; Kim, Sohee

2015-05-01

Development of brain metastasis results in a significant reduction in overall survival. However, there is no an effective tool to predict brain metastasis in non-small cell lung cancer (NSCLC) patients. We conducted this study to develop a feasible nomogram that can predict metastasis to the brain as the first relapse site in patients with curatively resected NSCLC. A retrospective review of NSCLC patients who had received curative surgery at National Cancer Center (Goyang, South Korea) between 2001 and 2008 was performed. We chose metastasis to the brain as the first relapse site after curative surgery as the primary endpoint of the study. A nomogram was modeled using logistic regression. Among 1218 patients, brain metastasis as the first relapse developed in 87 patients (7.14%) during the median follow-up of 43.6 months. Occurrence rates of brain metastasis were higher in patients with adenocarcinoma or those with a high pT and pN stage. Younger age appeared to be associated with brain metastasis, but this result was not statistically significant. The final prediction model included histology, smoking status, pT stage, and the interaction between adenocarcinoma and pN stage. The model showed fairly good discriminatory ability with a C-statistic of 69.3% and 69.8% for predicting brain metastasis within 2 years and 5 years, respectively. Internal validation using 2000 bootstrap samples resulted in C-statistics of 67.0% and 67.4% which still indicated good discriminatory performances. The nomogram presented here provides the individual risk estimate of developing metastasis to the brain as the first relapse site in patients with NSCLC who have undergone curative surgery. Surveillance programs or preventive treatment strategies for brain metastasis could be established based on this nomogram. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Reduced hippocampal activation during episodic encoding in middle-aged individuals at genetic risk of Alzheimer's Disease: a cross-sectional study

PubMed Central

Trivedi, Mehul A; Schmitz, Taylor W; Ries, Michele L; Torgerson, Britta M; Sager, Mark A; Hermann, Bruce P; Asthana, Sanjay; Johnson, Sterling C

2006-01-01

Background The presence of the apolipoprotein E (APOE) ε4 allele is a major risk factor for the development of Alzheimer's disease (AD), and has been associated with metabolic brain changes several years before the onset of typical AD symptoms. Functional MRI (fMRI) is a brain imaging technique that has been used to demonstrate hippocampal activation during measurement of episodic encoding, but the effect of the ε4 allele on hippocampal activation has not been firmly established. Methods The present study examined the effects of APOE genotype on brain activation patterns in the medial temporal lobe (MTL) during an episodic encoding task using a well-characterized novel item versus familiar item contrast in cognitively normal, middle-aged (mean = 54 years) individuals who had at least one parent with AD. Results We found that ε3/4 heterozygotes displayed reduced activation in the hippocampus and MTL compared to ε3/3 homozygotes. There were no significant differences between the groups in age, education or neuropsychological functioning, suggesting that the altered brain activation seen in ε3/4 heterozygotes was not associated with impaired cognitive function. We also found that participants' ability to encode information on a neuropsychological measure of learning was associated with greater activation in the anterior MTL in the ε3/3 homozygotes, but not in the ε3/4 heterozygotes. Conclusion Together with previous studies reporting reduced glucose metabolism and AD-related neuropathology, this study provides convergent validity for the idea that the MTL exhibits functional decline associated with the APOE ε4 allele. Importantly, these changes were detected in the absence of meaningful neuropsychological differences between the groups. A focus of ongoing work in this laboratory is to determine if these findings are predictive of subsequent cognitive decline. PMID:16412236

Neural signal processing and closed-loop control algorithm design for an implanted neural recording and stimulation system.

PubMed

Hamilton, Lei; McConley, Marc; Angermueller, Kai; Goldberg, David; Corba, Massimiliano; Kim, Louis; Moran, James; Parks, Philip D; Sang Chin; Widge, Alik S; Dougherty, Darin D; Eskandar, Emad N

2015-08-01

A fully autonomous intracranial device is built to continually record neural activities in different parts of the brain, process these sampled signals, decode features that correlate to behaviors and neuropsychiatric states, and use these features to deliver brain stimulation in a closed-loop fashion. In this paper, we describe the sampling and stimulation aspects of such a device. We first describe the signal processing algorithms of two unsupervised spike sorting methods. Next, we describe the LFP time-frequency analysis and feature derivation from the two spike sorting methods. Spike sorting includes a novel approach to constructing a dictionary learning algorithm in a Compressed Sensing (CS) framework. We present a joint prediction scheme to determine the class of neural spikes in the dictionary learning framework; and, the second approach is a modified OSort algorithm which is implemented in a distributed system optimized for power efficiency. Furthermore, sorted spikes and time-frequency analysis of LFP signals can be used to generate derived features (including cross-frequency coupling, spike-field coupling). We then show how these derived features can be used in the design and development of novel decode and closed-loop control algorithms that are optimized to apply deep brain stimulation based on a patient's neuropsychiatric state. For the control algorithm, we define the state vector as representative of a patient's impulsivity, avoidance, inhibition, etc. Controller parameters are optimized to apply stimulation based on the state vector's current state as well as its historical values. The overall algorithm and software design for our implantable neural recording and stimulation system uses an innovative, adaptable, and reprogrammable architecture that enables advancement of the state-of-the-art in closed-loop neural control while also meeting the challenges of system power constraints and concurrent development with ongoing scientific research designed to define brain network connectivity and neural network dynamics that vary at the individual patient level and vary over time.

An Investigation of Individual Variability in Brain Activity During Episodic Encoding and Retrieval

DTIC Science & Technology

2008-12-01

variability in mnemonic strategy use is, at least in part, related to the extensive variability observed in brain activity patterns. While a number of...1 AN INVESTIGATION OF INDIVIDUAL VARIABILITY IN BRAIN ACTIVITY DURING EPISODIC ENCODING AND RETRIEVAL C.L. Donovan*, and M.B. Miller Department of...strategy measures for predicting differences in brain activity patterns during a learning and memory task and to compare their predictive value to other

Ocular morbidities of juvenile idiopathic arthritis-associated uveitis in adulthood: results from a tertiary center study.

PubMed

Oray, Merih; Khachatryan, Naira; Ebrahimiadib, Nazanin; Abu Samra, Khawla; Lee, Stacey; Foster, C Stephen

2016-09-01

To describe the clinical and visual outcomes of juvenile idiopathic arthritis (JIA)-associated uveitis in adults and to examine risk factors for ongoing inflammation in adulthood. Medical records were reviewed for patients with JIA-associated uveitis who were >16 years old at the final visit (the last visit prior to data collection). In total, 135 eyes of 77 patients (70 female, 7 male) were included. The mean age of patients at the final visit was 29.72 ± 11.27 years. The number of eyes with visual acuity of ≤20/50 and ≤20/200 at the final visit was 37 (28 %) and 20 (15 %), respectively; at least one ocular complication was present in 72 % of eyes. Band keratopathy was the most frequent complication (42 %), followed by cataract (25 %), posterior synechiae (22 %), maculopathy (22 %), ocular hypertension (13 %), and hypotony (5 %). At the final visit, patients who were >16 years of age at presentation to the Massachusetts Eye Research and Surgery Institution had more ocular complications and a greater degree of vision loss than patients who were ≤16 years of age. Ongoing inflammation at the final visit was noted in 40 patients (52 %). The presence of posterior synechiae, hypotony, cataract at presentation, and a history of cataract surgery prior to presentation were predictive of ongoing inflammation in adulthood in univariate analysis. The presence of hypotony and posterior synechiae at the initial visit were predictive factors in multivariate analysis. JIA-associated uveitis may be associated with ongoing inflammation, ocular complications, and severe visual impairment in adulthood. The presence of posterior synechiae and hypotony at the initial visit is predictive of ongoing inflammation.

Ongoing Voluntary Settlement and Independent Agency: Evidence from China

PubMed Central

Feng, Jing; Ren, Xiaopeng; Ma, Xinran

2017-01-01

Voluntary frontier settlement leads to independent agency. Since this type of research has not yet been implemented in ongoing voluntary settlement frontiers, we conducted several cultural tasks to investigate Shenzhen, known as China’s ongoing “South Frontier,” which is composed mostly of people that have emigrated from other Chinese provinces within the past 30 years. We hypothesized that residents of Shenzhen are more independent than those in other regions of Mainland China. As predicted, residents of Shenzhen scored higher than China inland residents in self-reported independent beliefs and scored lower in nepotism. The results indicate that, even in a short-term ongoing frontier, voluntary settlement is associated with independent agency. PMID:28798712

Ongoing compound field potentials from octopus brain are labile and vertebrate-like.

PubMed

Bullock, T H

1984-05-01

Ongoing electrical activity was recorded from the brain of the virtually intact, semirestrained, unanesthetized octopus by semimicroelectrodes thrust through the cartilage into the optic, vertical or basal lobe. With flexible lead-in wires such electrodes were carried by and moved with the head without causing movement artifacts. Controls suggest that the activity reported comes from the brain; it is reversibly flattened by doses of urethane that do not embarrass respiration. Muscle potentials are only troublesome on occasion. Seen through a wideband filter, neuronal spikes are usually small or below noise level under these conditions; slow waves (1-70 Hz) dominate, with a maximum less than 25 Hz, usually less than 10 Hz and no consistent sharp peaks. The fall in power above ca. 25 Hz is usually slower than in the typical vertebrate EEG but the average power spectrum is much more like those of vertebrate brains than of cerebral ganglia of other invertebrates (insect, crustacean, gastropod). Variance among sample epochs is large, e.g. short spells may have relatively much more low frequency (less than 25 Hz) or more 'hashy' high frequency (greater than 50 Hz) energy; there may be runs of spikes. Fluctuation in the composition of ongoing activity is graphically shown by writing out in parallel the outputs of several narrow band (one octave) filters; this shows irregular low frequency waxing and waning of the amplitude in each band. The envelopes were computed and their peak power is around 1 Hz or lower; the waxing and waning in the several bands is sometimes strongly correlated, especially when the envelope amplitude is large and slow. Optic lobe activity tends usually to be faster, with more small spikey hash than in the vertical lobe. The described electrical activity of the brain is strikingly episodic; it is recorded during seconds or minutes separated by long intervals of nearly electrical silence (10-40 dB lower power; the difference larger at frequencies greater than 20 Hz). Active and quiet periods are usually not correlated with differences in visible behavior. Under my conditions the animal is usually not moving except for quiet ventilation and occasional local writhing of an arm. Potentials evoked by single flashes of light (0.2-1/sec) are conspicuous in the optic but not in the vertical lobe. They form a sequence of large, slow waves; the first peak may be at about 40 msec, others up to at least 400 msec.(ABSTRACT TRUNCATED AT 400 WORDS)

Sustained Activity in Hierarchical Modular Neural Networks: Self-Organized Criticality and Oscillations

PubMed Central

Wang, Sheng-Jun; Hilgetag, Claus C.; Zhou, Changsong

2010-01-01

Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. In particular, they are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality (SOC). We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. Previously, it was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We found that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and SOC, which are not present in the respective random networks. The mechanism underlying the sustained activity is that each dense module cannot sustain activity on its own, but displays SOC in the presence of weak perturbations. Therefore, the hierarchical modular networks provide the coupling among subsystems with SOC. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivity of critical states and the predictability and timing of oscillations for efficient information processing. PMID:21852971

Dynamics of alpha control: Preparatory suppression of posterior alpha oscillations by frontal modulators revealed with combined EEG and event-related optical signal (EROS)

PubMed Central

Mathewson, Kyle E.; Beck, Diane M.; Ro, Tony; Maclin, Edward L.; Low, Kathy A.; Fabiani, Monica; Gratton, Gabriele

2015-01-01

We investigated the dynamics of brain processes facilitating conscious experience of external stimuli. Previously we proposed that alpha (8-12 Hz) oscillations, which fluctuate with both sustained and directed attention, represent a pulsed inhibition of ongoing sensory brain activity. Here we tested the prediction that inhibitory alpha oscillations in visual cortex are modulated by top-down signals from frontoparietal attention networks. We measured modulations in phase-coherent alpha oscillations from superficial frontal, parietal, and occipital cortices using the event-related optical signal (EROS), a measure of neuronal activity affording high spatiotemporal resolution, along with concurrently-recorded electroencephalogram (EEG), while subjects performed a visual target-detection task. The pre-target alpha oscillations measured with EEG and EROS from posterior areas were larger for subsequently undetected targets, supporting alpha's inhibitory role. Using EROS, we localized brain correlates of these awareness-related alpha oscillations measured at the scalp to the cuneus and precuneus. Crucially, EROS alpha suppression correlated with posterior EEG alpha power across subjects. Sorting the EROS data based on EEG alpha power quartiles to investigate alpha modulators revealed that suppression of posterior alpha was preceded by increased activity in regions of the dorsal attention network, and decreased activity in regions of the cingulo-opercular network. Cross-correlations revealed the temporal dynamics of activity within these preparatory networks prior to posterior alpha modulation. The novel combination of EEG and EROS afforded localization of the sources and correlates of alpha oscillations and their temporal relationships, supporting our proposal that top-down control from attention networks modulates both posterior alpha and awareness of visual stimuli. PMID:24702458

Task relevance modulates the behavioural and neural effects of sensory predictions

PubMed Central

Friston, Karl J.; Nobre, Anna C.

2017-01-01

The brain is thought to generate internal predictions to optimize behaviour. However, it is unclear whether predictions signalling is an automatic brain function or depends on task demands. Here, we manipulated the spatial/temporal predictability of visual targets, and the relevance of spatial/temporal information provided by auditory cues. We used magnetoencephalography (MEG) to measure participants’ brain activity during task performance. Task relevance modulated the influence of predictions on behaviour: spatial/temporal predictability improved spatial/temporal discrimination accuracy, but not vice versa. To explain these effects, we used behavioural responses to estimate subjective predictions under an ideal-observer model. Model-based time-series of predictions and prediction errors (PEs) were associated with dissociable neural responses: predictions correlated with cue-induced beta-band activity in auditory regions and alpha-band activity in visual regions, while stimulus-bound PEs correlated with gamma-band activity in posterior regions. Crucially, task relevance modulated these spectral correlates, suggesting that current goals influence PE and prediction signalling. PMID:29206225

Driving working memory with frequency-tuned noninvasive brain stimulation.

PubMed

Albouy, Philippe; Baillet, Sylvain; Zatorre, Robert J

2018-04-29

Frequency-tuned noninvasive brain stimulation is a recent approach in cognitive neuroscience that involves matching the frequency of transcranially applied electromagnetic fields to that of specific oscillatory components of the underlying neurophysiology. The objective of this method is to modulate ongoing/intrinsic brain oscillations, which correspond to rhythmic fluctuations of neural excitability, to causally change behavior. We review the impact of frequency-tuned noninvasive brain stimulation on the research field of human working memory. We argue that this is a powerful method to probe and understand the mechanisms of memory functions, targeting specifically task-related oscillatory dynamics, neuronal representations, and brain networks. We report the main behavioral and neurophysiological outcomes published to date, in particular, how functionally relevant oscillatory signatures in signal power and interregional connectivity yield causal changes of working memory abilities. We also present recent developments of the technique that aim to modulate cross-frequency coupling in polyrhythmic neural activity. Overall, the method has led to significant advances in our understanding of the mechanisms of systems neuroscience, and the role of brain oscillations in cognition and behavior. We also emphasize the translational impact of noninvasive brain stimulation techniques in the development of therapeutic approaches. © 2018 New York Academy of Sciences.

Autonomous Optimization of Targeted Stimulation of Neuronal Networks

PubMed Central

Kumar, Sreedhar S.; Wülfing, Jan; Okujeni, Samora; Boedecker, Joschka; Riedmiller, Martin

2016-01-01

Driven by clinical needs and progress in neurotechnology, targeted interaction with neuronal networks is of increasing importance. Yet, the dynamics of interaction between intrinsic ongoing activity in neuronal networks and their response to stimulation is unknown. Nonetheless, electrical stimulation of the brain is increasingly explored as a therapeutic strategy and as a means to artificially inject information into neural circuits. Strategies using regular or event-triggered fixed stimuli discount the influence of ongoing neuronal activity on the stimulation outcome and are therefore not optimal to induce specific responses reliably. Yet, without suitable mechanistic models, it is hardly possible to optimize such interactions, in particular when desired response features are network-dependent and are initially unknown. In this proof-of-principle study, we present an experimental paradigm using reinforcement-learning (RL) to optimize stimulus settings autonomously and evaluate the learned control strategy using phenomenological models. We asked how to (1) capture the interaction of ongoing network activity, electrical stimulation and evoked responses in a quantifiable ‘state’ to formulate a well-posed control problem, (2) find the optimal state for stimulation, and (3) evaluate the quality of the solution found. Electrical stimulation of generic neuronal networks grown from rat cortical tissue in vitro evoked bursts of action potentials (responses). We show that the dynamic interplay of their magnitudes and the probability to be intercepted by spontaneous events defines a trade-off scenario with a network-specific unique optimal latency maximizing stimulus efficacy. An RL controller was set to find this optimum autonomously. Across networks, stimulation efficacy increased in 90% of the sessions after learning and learned latencies strongly agreed with those predicted from open-loop experiments. Our results show that autonomous techniques can exploit quantitative relationships underlying activity-response interaction in biological neuronal networks to choose optimal actions. Simple phenomenological models can be useful to validate the quality of the resulting controllers. PMID:27509295

Autonomous Optimization of Targeted Stimulation of Neuronal Networks.

PubMed

Kumar, Sreedhar S; Wülfing, Jan; Okujeni, Samora; Boedecker, Joschka; Riedmiller, Martin; Egert, Ulrich

2016-08-01

Driven by clinical needs and progress in neurotechnology, targeted interaction with neuronal networks is of increasing importance. Yet, the dynamics of interaction between intrinsic ongoing activity in neuronal networks and their response to stimulation is unknown. Nonetheless, electrical stimulation of the brain is increasingly explored as a therapeutic strategy and as a means to artificially inject information into neural circuits. Strategies using regular or event-triggered fixed stimuli discount the influence of ongoing neuronal activity on the stimulation outcome and are therefore not optimal to induce specific responses reliably. Yet, without suitable mechanistic models, it is hardly possible to optimize such interactions, in particular when desired response features are network-dependent and are initially unknown. In this proof-of-principle study, we present an experimental paradigm using reinforcement-learning (RL) to optimize stimulus settings autonomously and evaluate the learned control strategy using phenomenological models. We asked how to (1) capture the interaction of ongoing network activity, electrical stimulation and evoked responses in a quantifiable 'state' to formulate a well-posed control problem, (2) find the optimal state for stimulation, and (3) evaluate the quality of the solution found. Electrical stimulation of generic neuronal networks grown from rat cortical tissue in vitro evoked bursts of action potentials (responses). We show that the dynamic interplay of their magnitudes and the probability to be intercepted by spontaneous events defines a trade-off scenario with a network-specific unique optimal latency maximizing stimulus efficacy. An RL controller was set to find this optimum autonomously. Across networks, stimulation efficacy increased in 90% of the sessions after learning and learned latencies strongly agreed with those predicted from open-loop experiments. Our results show that autonomous techniques can exploit quantitative relationships underlying activity-response interaction in biological neuronal networks to choose optimal actions. Simple phenomenological models can be useful to validate the quality of the resulting controllers.

Subcortical processing of speech regularities underlies reading and music aptitude in children

PubMed Central

2011-01-01

Background Neural sensitivity to acoustic regularities supports fundamental human behaviors such as hearing in noise and reading. Although the failure to encode acoustic regularities in ongoing speech has been associated with language and literacy deficits, how auditory expertise, such as the expertise that is associated with musical skill, relates to the brainstem processing of speech regularities is unknown. An association between musical skill and neural sensitivity to acoustic regularities would not be surprising given the importance of repetition and regularity in music. Here, we aimed to define relationships between the subcortical processing of speech regularities, music aptitude, and reading abilities in children with and without reading impairment. We hypothesized that, in combination with auditory cognitive abilities, neural sensitivity to regularities in ongoing speech provides a common biological mechanism underlying the development of music and reading abilities. Methods We assessed auditory working memory and attention, music aptitude, reading ability, and neural sensitivity to acoustic regularities in 42 school-aged children with a wide range of reading ability. Neural sensitivity to acoustic regularities was assessed by recording brainstem responses to the same speech sound presented in predictable and variable speech streams. Results Through correlation analyses and structural equation modeling, we reveal that music aptitude and literacy both relate to the extent of subcortical adaptation to regularities in ongoing speech as well as with auditory working memory and attention. Relationships between music and speech processing are specifically driven by performance on a musical rhythm task, underscoring the importance of rhythmic regularity for both language and music. Conclusions These data indicate common brain mechanisms underlying reading and music abilities that relate to how the nervous system responds to regularities in auditory input. Definition of common biological underpinnings for music and reading supports the usefulness of music for promoting child literacy, with the potential to improve reading remediation. PMID:22005291

Predicting Treatment Response in Social Anxiety Disorder From Functional Magnetic Resonance Imaging

PubMed Central

Doehrmann, Oliver; Ghosh, Satrajit S.; Polli, Frida E.; Reynolds, Gretchen O.; Horn, Franziska; Keshavan, Anisha; Triantafyllou, Christina; Saygin, Zeynep M.; Whitfield-Gabrieli, Susan; Hofmann, Stefan G.; Pollack, Mark; Gabrieli, John D.

2013-01-01

Context Current behavioral measures poorly predict treatment outcome in social anxiety disorder (SAD). To our knowledge, this is the first study to examine neuroimaging-based treatment prediction in SAD. Objective To measure brain activation in patients with SAD as a biomarker to predict subsequent response to cognitive behavioral therapy (CBT). Design Functional magnetic resonance imaging (fMRI) data were collected prior to CBT intervention. Changes in clinical status were regressed on brain responses and tested for selectivity for social stimuli. Setting Patients were treated with protocol-based CBT at anxiety disorder programs at Boston University or Massachusetts General Hospital and underwent neuroimaging data collection at Massachusetts Institute of Technology. Patients Thirty-nine medication-free patients meeting DSM-IV criteria for the generalized subtype of SAD. Interventions Brain responses to angry vs neutral faces or emotional vs neutral scenes were examined with fMRI prior to initiation of CBT. Main Outcome Measures Whole-brain regression analyses with differential fMRI responses for angry vs neutral faces and changes in Liebowitz Social Anxiety Scale score as the treatment outcome measure. Results Pretreatment responses significantly predicted subsequent treatment outcome of patients selectively for social stimuli and particularly in regions of higher-order visual cortex. Combining the brain measures with information on clinical severity accounted for more than 40% of the variance in treatment response and substantially exceeded predictions based on clinical measures at baseline. Prediction success was unaffected by testing for potential confounding factors such as depression severity at baseline. Conclusions The results suggest that brain imaging can provide biomarkers that substantially improve predictions for the success of cognitive behavioral interventions and more generally suggest that such biomarkers may offer evidence-based, personalized medicine approaches for optimally selecting among treatment options for a patient. PMID:22945462

Effects of ongoing task context and target typicality on prospective memory performance: the importance of associative cueing

NASA Technical Reports Server (NTRS)

Nowinski, Jessica Lang; Dismukes, Key R.

2005-01-01

Two experiments examined whether prospective memory performance is influenced by contextual cues. In our automatic activation model, any information available at encoding and retrieval should aid recall of the prospective task. The first experiment demonstrated an effect of the ongoing task context; performance was better when information about the ongoing task present at retrieval was available at encoding. Performance was also improved by a strong association between the prospective memory target as it was presented at retrieval and the intention as it was encoded. Experiment 2 demonstrated boundary conditions of the ongoing task context effect, which implicate the association between the ongoing and prospective tasks formed at encoding as the source of the context effect. The results of this study are consistent with predictions based on automatic activation of intentions.

Robust prediction of individual creative ability from brain functional connectivity.

PubMed

Beaty, Roger E; Kenett, Yoed N; Christensen, Alexander P; Rosenberg, Monica D; Benedek, Mathias; Chen, Qunlin; Fink, Andreas; Qiu, Jiang; Kwapil, Thomas R; Kane, Michael J; Silvia, Paul J

2018-01-30

People's ability to think creatively is a primary means of technological and cultural progress, yet the neural architecture of the highly creative brain remains largely undefined. Here, we employed a recently developed method in functional brain imaging analysis-connectome-based predictive modeling-to identify a brain network associated with high-creative ability, using functional magnetic resonance imaging (fMRI) data acquired from 163 participants engaged in a classic divergent thinking task. At the behavioral level, we found a strong correlation between creative thinking ability and self-reported creative behavior and accomplishment in the arts and sciences ( r = 0.54). At the neural level, we found a pattern of functional brain connectivity related to high-creative thinking ability consisting of frontal and parietal regions within default, salience, and executive brain systems. In a leave-one-out cross-validation analysis, we show that this neural model can reliably predict the creative quality of ideas generated by novel participants within the sample. Furthermore, in a series of external validation analyses using data from two independent task fMRI samples and a large task-free resting-state fMRI sample, we demonstrate robust prediction of individual creative thinking ability from the same pattern of brain connectivity. The findings thus reveal a whole-brain network associated with high-creative ability comprised of cortical hubs within default, salience, and executive systems-intrinsic functional networks that tend to work in opposition-suggesting that highly creative people are characterized by the ability to simultaneously engage these large-scale brain networks.

Utilizing multiple scale models to improve predictions of extra-axial hemorrhage in the immature piglet.

PubMed

Scott, Gregory G; Margulies, Susan S; Coats, Brittany

2016-10-01

Traumatic brain injury (TBI) is a leading cause of death and disability in the USA. To help understand and better predict TBI, researchers have developed complex finite element (FE) models of the head which incorporate many biological structures such as scalp, skull, meninges, brain (with gray/white matter differentiation), and vasculature. However, most models drastically simplify the membranes and substructures between the pia and arachnoid membranes. We hypothesize that substructures in the pia-arachnoid complex (PAC) contribute substantially to brain deformation following head rotation, and that when included in FE models accuracy of extra-axial hemorrhage prediction improves. To test these hypotheses, microscale FE models of the PAC were developed to span the variability of PAC substructure anatomy and regional density. The constitutive response of these models were then integrated into an existing macroscale FE model of the immature piglet brain to identify changes in cortical stress distribution and predictions of extra-axial hemorrhage (EAH). Incorporating regional variability of PAC substructures substantially altered the distribution of principal stress on the cortical surface of the brain compared to a uniform representation of the PAC. Simulations of 24 non-impact rapid head rotations in an immature piglet animal model resulted in improved accuracy of EAH prediction (to 94 % sensitivity, 100 % specificity), as well as a high accuracy in regional hemorrhage prediction (to 82-100 % sensitivity, 100 % specificity). We conclude that including a biofidelic PAC substructure variability in FE models of the head is essential for improved predictions of hemorrhage at the brain/skull interface.

Brain Injury in Neonates with Complex Congenital Heart Disease: What Is the Predictive Value of MRI in the Fetal Period?

PubMed

Brossard-Racine, M; du Plessis, A; Vezina, G; Robertson, R; Donofrio, M; Tworetzky, W; Limperopoulos, C

2016-07-01

Brain injury in neonates with congenital heart disease is an important predictor of adverse neurodevelopmental outcome. Impaired brain development in congenital heart disease may have a prenatal origin, but the sensitivity and specificity of fetal brain MR imaging for predicting neonatal brain lesions are currently unknown. We sought to determine the value of conventional fetal MR imaging for predicting abnormal findings on neonatal preoperative MR imaging in neonates with complex congenital heart disease. MR imaging studies were performed in 103 fetuses with confirmed congenital heart disease (mean gestational age, 31.57 ± 3.86 weeks) and were repeated postnatally before cardiac surgery (mean age, 6.8 ± 12.2 days). Each MR imaging study was read by a pediatric neuroradiologist. Brain abnormalities were detected in 17/103 (16%) fetuses by fetal MR imaging and in 33/103 (32%) neonates by neonatal MR imaging. Only 9/33 studies with abnormal neonatal findings were preceded by abnormal findings on fetal MR imaging. The sensitivity and specificity of conventional fetal brain MR imaging for predicting neonatal brain abnormalities were 27% and 89%, respectively. Brain abnormalities detected by in utero MR imaging in fetuses with congenital heart disease are associated with higher risk of postnatal preoperative brain injury. However, a substantial proportion of anomalies on postnatal MR imaging were not present on fetal MR imaging; this result is likely due to the limitations of conventional fetal MR imaging and the emergence of new lesions that occurred after the fetal studies. Postnatal brain MR imaging studies are needed to confirm the presence of injury before open heart surgery. © 2016 by American Journal of Neuroradiology.

Consciousness, brain, neuroplasticity

PubMed Central

Askenasy, Jean; Lehmann, Joseph

2013-01-01

Subjectivity, intentionality, self-awareness and will are major components of consciousness in human beings. Changes in consciousness and its content following different brain processes and malfunction have long been studied. Cognitive sciences assume that brain activities have an infrastructure, but there is also evidence that consciousness itself may change this infrastructure. The two-way influence between brain and consciousness has been at the center of philosophy and less so, of science. This so-called bottom-up and top-down interrelationship is controversial and is the subject of our article. We would like to ask: how does it happen that consciousness may provoke structural changes in the brain? The living brain means continuous changes at the synaptic level with every new experience, with every new process of learning, memorizing or mastering new and existing skills. Synapses are generated and dissolved, while others are preserved, in an ever-changing process of so-called neuroplasticity. Ongoing processes of synaptic reinforcements and decay occur during wakefulness when consciousness is present, but also during sleep when it is mostly absent. We suggest that consciousness influences brain neuroplasticity both during wakefulness as well as sleep in a top-down way. This means that consciousness really activates synaptic flow and changes brain structures and functional organization. The dynamic impact of consciousness on brain never stops despite the relative stationary structure of the brain. Such a process can be a target for medical intervention, e.g., by cognitive training. PMID:23847580

Spontaneous brain activity predicts learning ability of foreign sounds.

PubMed

Ventura-Campos, Noelia; Sanjuán, Ana; González, Julio; Palomar-García, María-Ángeles; Rodríguez-Pujadas, Aina; Sebastián-Gallés, Núria; Deco, Gustavo; Ávila, César

2013-05-29

Can learning capacity of the human brain be predicted from initial spontaneous functional connectivity (FC) between brain areas involved in a task? We combined task-related functional magnetic resonance imaging (fMRI) and resting-state fMRI (rs-fMRI) before and after training with a Hindi dental-retroflex nonnative contrast. Previous fMRI results were replicated, demonstrating that this learning recruited the left insula/frontal operculum and the left superior parietal lobe, among other areas of the brain. Crucially, resting-state FC (rs-FC) between these two areas at pretraining predicted individual differences in learning outcomes after distributed (Experiment 1) and intensive training (Experiment 2). Furthermore, this rs-FC was reduced at posttraining, a change that may also account for learning. Finally, resting-state network analyses showed that the mechanism underlying this reduction of rs-FC was mainly a transfer in intrinsic activity of the left frontal operculum/anterior insula from the left frontoparietal network to the salience network. Thus, rs-FC may contribute to predict learning ability and to understand how learning modifies the functioning of the brain. The discovery of this correspondence between initial spontaneous brain activity in task-related areas and posttraining performance opens new avenues to find predictors of learning capacities in the brain using task-related fMRI and rs-fMRI combined.

Renovating Alzheimer's: "Constructive" Reflections on the New Clinical and Research Diagnostic Guidelines

ERIC Educational Resources Information Center

George, Daniel R.; Qualls, Sara H.; Camp, Cameron J.; Whitehouse, Peter J.

2013-01-01

The development of disease concepts for conditions such as Alzheimer's disease (AD) is an ongoing social process that evolves over time. The biomedical paradigm about AD that has informed our culture's understanding of brain aging for the past several decades is currently undergoing a major and timely renovation in the early 21st century. This…

Brain games: toward a neuroecology of social behavior.

PubMed

Gariépy, Jean-François; Chang, Steve W C; Platt, Michael L

2013-08-01

In the target article, Schilbach et al. defend a "second-person neuroscience" perspective that focuses on the neural basis of social cognition during live, ongoing interactions between individuals. We argue that a second-person neuroscience would benefit from formal approaches borrowed from economics and behavioral ecology and that it should be extended to social interactions in nonhuman animals.

Enhanced detection of infectious prions by direct ELISA from the brains of asymptomatic animals using DRM2-118 monoclonal antibody and Gdn-HCl

USDA-ARS?s Scientific Manuscript database

In this report we describe improved methods for the detection of infectious prions by immunoassay for the diagnosis of transmissible spongiform encephalopathies (TSEs) from asymptomatic animals. Tissue samples obtained as part of ongoing TSE surveillance efforts are often unsuitable for histopathol...

The Emergent Coordination of Cognitive Function

ERIC Educational Resources Information Center

Kello, Christopher T.; Beltz, Brandon C.; Holden, John G.; Van Orden, Guy C.

2007-01-01

1/f scaling has been observed throughout human physiology and behavior, but its origins and meaning remain a matter of debate. Some argue that it is a byproduct of ongoing processes in the brain or body and therefore of limited relevance to psychological theory. Others argue that 1/f scaling reflects a fundamental aspect of all physiological and…

Persistent Angiogenesis in the Autism Brain: An Immunocytochemical Study of Postmortem Cortex, Brainstem and Cerebellum

ERIC Educational Resources Information Center

Azmitia, E. C.; Saccomano, Z. T.; Alzoobaee, M. F.; Boldrini, M.; Whitaker-Azmitia, P. M.

2016-01-01

In the current work, we conducted an immunocytochemical search for markers of ongoing neurogenesis (e.g. nestin) in auditory cortex from postmortem sections of autism spectrum disorder (ASD) and age-matched control donors. We found nestin labeling in cells of the vascular system, indicating blood vessels plasticity. Evidence of angiogenesis was…

Age-Related Differences in the Temporal Dynamics of Prospective Memory Retrieval: A Lifespan Approach

ERIC Educational Resources Information Center

Mattli, Florentina; Zollig, Jacqueline; West, Robert

2011-01-01

The efficiency of prospective memory (PM) typically increases from childhood to young adulthood and then decreases in later adulthood. The current study used event-related brain potentials (ERPs) to examine the development of the neural correlates of processes associated with the detection of a PM cue, switching from the ongoing activity to the…

Artistic understanding as embodied simulation.

PubMed

Gibbs, Raymond W

2013-04-01

Bullot & Reber (B&R) correctly include historical perspectives into the scientific study of art appreciation. But artistic understanding always emerges from embodied simulation processes that incorporate the ongoing dynamics of brains, bodies, and world interactions. There may not be separate modes of artistic understanding, but a continuum of processes that provide imaginative simulations of the artworks we see or hear.

Imaging of neural oscillations with embedded inferential and group prevalence statistics.

PubMed

Donhauser, Peter W; Florin, Esther; Baillet, Sylvain

2018-02-01

Magnetoencephalography and electroencephalography (MEG, EEG) are essential techniques for studying distributed signal dynamics in the human brain. In particular, the functional role of neural oscillations remains to be clarified. For that reason, imaging methods need to identify distinct brain regions that concurrently generate oscillatory activity, with adequate separation in space and time. Yet, spatial smearing and inhomogeneous signal-to-noise are challenging factors to source reconstruction from external sensor data. The detection of weak sources in the presence of stronger regional activity nearby is a typical complication of MEG/EEG source imaging. We propose a novel, hypothesis-driven source reconstruction approach to address these methodological challenges. The imaging with embedded statistics (iES) method is a subspace scanning technique that constrains the mapping problem to the actual experimental design. A major benefit is that, regardless of signal strength, the contributions from all oscillatory sources, which activity is consistent with the tested hypothesis, are equalized in the statistical maps produced. We present extensive evaluations of iES on group MEG data, for mapping 1) induced oscillations using experimental contrasts, 2) ongoing narrow-band oscillations in the resting-state, 3) co-modulation of brain-wide oscillatory power with a seed region, and 4) co-modulation of oscillatory power with peripheral signals (pupil dilation). Along the way, we demonstrate several advantages of iES over standard source imaging approaches. These include the detection of oscillatory coupling without rejection of zero-phase coupling, and detection of ongoing oscillations in deeper brain regions, where signal-to-noise conditions are unfavorable. We also show that iES provides a separate evaluation of oscillatory synchronization and desynchronization in experimental contrasts, which has important statistical advantages. The flexibility of iES allows it to be adjusted to many experimental questions in systems neuroscience.

Towards Development of a 3-State Self-Paced Brain-Computer Interface

PubMed Central

Bashashati, Ali; Ward, Rabab K.; Birch, Gary E.

2007-01-01

Most existing brain-computer interfaces (BCIs) detect specific mental activity in a so-called synchronous paradigm. Unlike synchronous systems which are operational at specific system-defined periods, self-paced (asynchronous) interfaces have the advantage of being operational at all times. The low-frequency asynchronous switch design (LF-ASD) is a 2-state self-paced BCI that detects the presence of a specific finger movement in the ongoing EEG. Recent evaluations of the 2-state LF-ASD show an average true positive rate of 41% at the fixed false positive rate of 1%. This paper proposes two designs for a 3-state self-paced BCI that is capable of handling idle brain state. The two proposed designs aim at detecting right- and left-hand extensions from the ongoing EEG. They are formed of two consecutive detectors. The first detects the presence of a right- or a left-hand movement and the second classifies the detected movement as a right or a left one. In an offline analysis of the EEG data collected from four able-bodied individuals, the 3-state brain-computer interface shows a comparable performance with a 2-state system and significant performance improvement if used as a 2-state BCI, that is, in detecting the presence of a right- or a left-hand movement (regardless of the type of movement). It has an average true positive rate of 37.5% and 42.8% (at false positives rate of 1%) in detecting right- and left-hand extensions, respectively, in the context of a 3-state self-paced BCI and average detection rate of 58.1% (at false positive rate of 1%) in the context of a 2-state self-paced BCI. PMID:18288260

Imaging of neural oscillations with embedded inferential and group prevalence statistics

PubMed Central

2018-01-01

Magnetoencephalography and electroencephalography (MEG, EEG) are essential techniques for studying distributed signal dynamics in the human brain. In particular, the functional role of neural oscillations remains to be clarified. For that reason, imaging methods need to identify distinct brain regions that concurrently generate oscillatory activity, with adequate separation in space and time. Yet, spatial smearing and inhomogeneous signal-to-noise are challenging factors to source reconstruction from external sensor data. The detection of weak sources in the presence of stronger regional activity nearby is a typical complication of MEG/EEG source imaging. We propose a novel, hypothesis-driven source reconstruction approach to address these methodological challenges. The imaging with embedded statistics (iES) method is a subspace scanning technique that constrains the mapping problem to the actual experimental design. A major benefit is that, regardless of signal strength, the contributions from all oscillatory sources, which activity is consistent with the tested hypothesis, are equalized in the statistical maps produced. We present extensive evaluations of iES on group MEG data, for mapping 1) induced oscillations using experimental contrasts, 2) ongoing narrow-band oscillations in the resting-state, 3) co-modulation of brain-wide oscillatory power with a seed region, and 4) co-modulation of oscillatory power with peripheral signals (pupil dilation). Along the way, we demonstrate several advantages of iES over standard source imaging approaches. These include the detection of oscillatory coupling without rejection of zero-phase coupling, and detection of ongoing oscillations in deeper brain regions, where signal-to-noise conditions are unfavorable. We also show that iES provides a separate evaluation of oscillatory synchronization and desynchronization in experimental contrasts, which has important statistical advantages. The flexibility of iES allows it to be adjusted to many experimental questions in systems neuroscience. PMID:29408902

The brain, self and society: a social-neuroscience model of predictive processing.

PubMed

Kelly, Michael P; Kriznik, Natasha M; Kinmonth, Ann Louise; Fletcher, Paul C

2018-05-10

This paper presents a hypothesis about how social interactions shape and influence predictive processing in the brain. The paper integrates concepts from neuroscience and sociology where a gulf presently exists between the ways that each describe the same phenomenon - how the social world is engaged with by thinking humans. We combine the concepts of predictive processing models (also called predictive coding models in the neuroscience literature) with ideal types, typifications and social practice - concepts from the sociological literature. This generates a unified hypothetical framework integrating the social world and hypothesised brain processes. The hypothesis combines aspects of neuroscience and psychology with social theory to show how social behaviors may be "mapped" onto brain processes. It outlines a conceptual framework that connects the two disciplines and that may enable creative dialogue and potential future research.

Dynamic filtering improves attentional state prediction with fNIRS

PubMed Central

Harrivel, Angela R.; Weissman, Daniel H.; Noll, Douglas C.; Huppert, Theodore; Peltier, Scott J.

2016-01-01

Brain activity can predict a person’s level of engagement in an attentional task. However, estimates of brain activity are often confounded by measurement artifacts and systemic physiological noise. The optimal method for filtering this noise – thereby increasing such state prediction accuracy – remains unclear. To investigate this, we asked study participants to perform an attentional task while we monitored their brain activity with functional near infrared spectroscopy (fNIRS). We observed higher state prediction accuracy when noise in the fNIRS hemoglobin [Hb] signals was filtered with a non-stationary (adaptive) model as compared to static regression (84% ± 6% versus 72% ± 15%). PMID:27231602

Multimodal neuroimaging of male and female brain structure in health and disease across the life span

PubMed Central

Thompson, Paul M.

2016-01-01

Sex differences in brain development and aging are important to identify, as they may help to understand risk factors and outcomes in brain disorders that are more prevalent in one sex compared with the other. Brain imaging techniques have advanced rapidly in recent years, yielding detailed structural and functional maps of the living brain. Even so, studies are often limited in sample size, and inconsistent findings emerge, one example being varying findings regarding sex differences in the size of the corpus callosum. More recently, large‐scale neuroimaging consortia such as the Enhancing Neuro Imaging Genetics through Meta Analysis Consortium have formed, pooling together expertise, data, and resources from hundreds of institutions around the world to ensure adequate power and reproducibility. These initiatives are helping us to better understand how brain structure is affected by development, disease, and potential modulators of these effects, including sex. This review highlights some established and disputed sex differences in brain structure across the life span, as well as pitfalls related to interpreting sex differences in health and disease. We also describe sex‐related findings from the ENIGMA consortium, and ongoing efforts to better understand sex differences in brain circuitry. © 2016 The Authors. Journal of Neuroscience Research Published by Wiley Periodicals, Inc. PMID:27870421

Predicting individualized clinical measures by a generalized prediction framework and multimodal fusion of MRI data

PubMed Central

Meng, Xing; Jiang, Rongtao; Lin, Dongdong; Bustillo, Juan; Jones, Thomas; Chen, Jiayu; Yu, Qingbao; Du, Yuhui; Zhang, Yu; Jiang, Tianzi; Sui, Jing; Calhoun, Vince D.

2016-01-01

Neuroimaging techniques have greatly enhanced the understanding of neurodiversity (human brain variation across individuals) in both health and disease. The ultimate goal of using brain imaging biomarkers is to perform individualized predictions. Here we proposed a generalized framework that can predict explicit values of the targeted measures by taking advantage of joint information from multiple modalities. This framework also enables whole brain voxel-wise searching by combining multivariate techniques such as ReliefF, clustering, correlation-based feature selection and multiple regression models, which is more flexible and can achieve better prediction performance than alternative atlas-based methods. For 50 healthy controls and 47 schizophrenia patients, three kinds of features derived from resting-state fMRI (fALFF), sMRI (gray matter) and DTI (fractional anisotropy) were extracted and fed into a regression model, achieving high prediction for both cognitive scores (MCCB composite r = 0.7033, MCCB social cognition r = 0.7084) and symptomatic scores (positive and negative syndrome scale [PANSS] positive r = 0.7785, PANSS negative r = 0.7804). Moreover, the brain areas likely responsible for cognitive deficits of schizophrenia, including middle temporal gyrus, dorsolateral prefrontal cortex, striatum, cuneus and cerebellum, were located with different weights, as well as regions predicting PANSS symptoms, including thalamus, striatum and inferior parietal lobule, pinpointing the potential neuromarkers. Finally, compared to a single modality, multimodal combination achieves higher prediction accuracy and enables individualized prediction on multiple clinical measures. There is more work to be done, but the current results highlight the potential utility of multimodal brain imaging biomarkers to eventually inform clinical decision-making. PMID:27177764

A Kenyan Cloud School. Massive Open Online & Ongoing Courses for Blended and Lifelong Learning

ERIC Educational Resources Information Center

Jobe, William

2013-01-01

This research describes the predicted outcomes of a Kenyan Cloud School (KCS), which is a MOOC that contains all courses taught at the secondary school level in Kenya. This MOOC will consist of online, ongoing subjects in both English and Kiswahili. The KCS subjects offer self-testing and peer assessment to maximize scalability, and digital badges…

Regional Differences in Brain Volume Predict the Acquisition of Skill in a Complex Real-Time Strategy Videogame

ERIC Educational Resources Information Center

Basak, Chandramallika; Voss, Michelle W.; Erickson, Kirk I.; Boot, Walter R.; Kramer, Arthur F.

2011-01-01

Previous studies have found that differences in brain volume among older adults predict performance in laboratory tasks of executive control, memory, and motor learning. In the present study we asked whether regional differences in brain volume as assessed by the application of a voxel-based morphometry technique on high resolution MRI would also…

Predicting Story Goodness Performance from Cognitive Measures Following Traumatic Brain Injury

ERIC Educational Resources Information Center

Le, Karen; Coelho, Carl; Mozeiko, Jennifer; Krueger, Frank; Grafman, Jordan

2012-01-01

Purpose: This study examined the prediction of performance on measures of the Story Goodness Index (SGI; Le, Coelho, Mozeiko, & Grafman, 2011) from executive function (EF) and memory measures following traumatic brain injury (TBI). It was hypothesized that EF and memory measures would significantly predict SGI outcomes. Method: One hundred…

Brain mechanisms in religion and spirituality: An integrative predictive processing framework.

PubMed

van Elk, Michiel; Aleman, André

2017-02-01

We present the theory of predictive processing as a unifying framework to account for the neurocognitive basis of religion and spirituality. Our model is substantiated by discussing four different brain mechanisms that play a key role in religion and spirituality: temporal brain areas are associated with religious visions and ecstatic experiences; multisensory brain areas and the default mode network are involved in self-transcendent experiences; the Theory of Mind-network is associated with prayer experiences and over attribution of intentionality; top-down mechanisms instantiated in the anterior cingulate cortex and the medial prefrontal cortex could be involved in acquiring and maintaining intuitive supernatural beliefs. We compare the predictive processing model with two-systems accounts of religion and spirituality, by highlighting the central role of prediction error monitoring. We conclude by presenting novel predictions for future research and by discussing the philosophical and theological implications of neuroscientific research on religion and spirituality. Copyright © 2016 Elsevier Ltd. All rights reserved.

A nomogram for predicting distant brain failure in patients treated with gamma knife stereotactic radiosurgery without whole brain radiotherapy

PubMed Central

Ayala-Peacock, Diandra N.; Peiffer, Ann M.; Lucas, John T.; Isom, Scott; Kuremsky, J. Griff; Urbanic, James J.; Bourland, J. Daniel; Laxton, Adrian W.; Tatter, Stephen B.; Shaw, Edward G.; Chan, Michael D.

2014-01-01

Background We review our single institution experience to determine predictive factors for early and delayed distant brain failure (DBF) after radiosurgery without whole brain radiotherapy (WBRT) for brain metastases. Materials and methods Between January 2000 and December 2010, a total of 464 patients were treated with Gamma Knife stereotactic radiosurgery (SRS) without WBRT for primary management of newly diagnosed brain metastases. Histology, systemic disease, RPA class, and number of metastases were evaluated as possible predictors of DBF rate. DBF rates were determined by serial MRI. Kaplan–Meier method was used to estimate rate of DBF. Multivariate analysis was performed using Cox Proportional Hazard regression. Results Median number of lesions treated was 1 (range 1–13). Median time to DBF was 4.9 months. Twenty-seven percent of patients ultimately required WBRT with median time to WBRT of 5.6 months. Progressive systemic disease (χ2= 16.748, P < .001), number of metastases at SRS (χ2 = 27.216, P < .001), discovery of new metastases at time of SRS (χ2 = 9.197, P < .01), and histology (χ2 = 12.819, P < .07) were factors that predicted for earlier time to distant failure. High risk histologic subtypes (melanoma, her2 negative breast, χ2 = 11.020, P < .001) and low risk subtypes (her2 + breast, χ2 = 11.343, P < .001) were identified. Progressive systemic disease (χ2 = 9.549, P < .01), number of brain metastases (χ2 = 16.953, P < .001), minimum SRS dose (χ2 = 21.609, P < .001), and widespread metastatic disease (χ2 = 29.396, P < .001) were predictive of shorter time to WBRT. Conclusion Systemic disease, number of metastases, and histology are factors that predict distant failure rate after primary radiosurgical management of brain metastases. PMID:24558022

Model of brain activation predicts the neural collective influence map of the brain

PubMed Central

Morone, Flaviano; Roth, Kevin; Min, Byungjoon; Makse, Hernán A.

2017-01-01

Efficient complex systems have a modular structure, but modularity does not guarantee robustness, because efficiency also requires an ingenious interplay of the interacting modular components. The human brain is the elemental paradigm of an efficient robust modular system interconnected as a network of networks (NoN). Understanding the emergence of robustness in such modular architectures from the interconnections of its parts is a longstanding challenge that has concerned many scientists. Current models of dependencies in NoN inspired by the power grid express interactions among modules with fragile couplings that amplify even small shocks, thus preventing functionality. Therefore, we introduce a model of NoN to shape the pattern of brain activations to form a modular environment that is robust. The model predicts the map of neural collective influencers (NCIs) in the brain, through the optimization of the influence of the minimal set of essential nodes responsible for broadcasting information to the whole-brain NoN. Our results suggest intervention protocols to control brain activity by targeting influential neural nodes predicted by network theory. PMID:28351973

Energetic and nutritional constraints on infant brain development: implications for brain expansion during human evolution.

PubMed

Cunnane, Stephen C; Crawford, Michael A

2014-12-01

The human brain confronts two major challenges during its development: (i) meeting a very high energy requirement, and (ii) reliably accessing an adequate dietary source of specific brain selective nutrients needed for its structure and function. Implicitly, these energetic and nutritional constraints to normal brain development today would also have been constraints on human brain evolution. The energetic constraint was solved in large measure by the evolution in hominins of a unique and significant layer of body fat on the fetus starting during the third trimester of gestation. By providing fatty acids for ketone production that are needed as brain fuel, this fat layer supports the brain's high energy needs well into childhood. This fat layer also contains an important reserve of the brain selective omega-3 fatty acid, docosahexaenoic acid (DHA), not available in other primates. Foremost amongst the brain selective minerals are iodine and iron, with zinc, copper and selenium also being important. A shore-based diet, i.e., fish, molluscs, crustaceans, frogs, bird's eggs and aquatic plants, provides the richest known dietary sources of brain selective nutrients. Regular access to these foods by the early hominin lineage that evolved into humans would therefore have helped free the nutritional constraint on primate brain development and function. Inadequate dietary supply of brain selective nutrients still has a deleterious impact on human brain development on a global scale today, demonstrating the brain's ongoing vulnerability. The core of the shore-based paradigm of human brain evolution proposes that sustained access by certain groups of early Homo to freshwater and marine food resources would have helped surmount both the nutritional as well as the energetic constraints on mammalian brain development. Copyright © 2014 Elsevier Ltd. All rights reserved.

Modeling Brain Dynamics in Brain Tumor Patients Using the Virtual Brain.

PubMed

Aerts, Hannelore; Schirner, Michael; Jeurissen, Ben; Van Roost, Dirk; Achten, Eric; Ritter, Petra; Marinazzo, Daniele

2018-01-01

Presurgical planning for brain tumor resection aims at delineating eloquent tissue in the vicinity of the lesion to spare during surgery. To this end, noninvasive neuroimaging techniques such as functional MRI and diffusion-weighted imaging fiber tracking are currently employed. However, taking into account this information is often still insufficient, as the complex nonlinear dynamics of the brain impede straightforward prediction of functional outcome after surgical intervention. Large-scale brain network modeling carries the potential to bridge this gap by integrating neuroimaging data with biophysically based models to predict collective brain dynamics. As a first step in this direction, an appropriate computational model has to be selected, after which suitable model parameter values have to be determined. To this end, we simulated large-scale brain dynamics in 25 human brain tumor patients and 11 human control participants using The Virtual Brain, an open-source neuroinformatics platform. Local and global model parameters of the Reduced Wong-Wang model were individually optimized and compared between brain tumor patients and control subjects. In addition, the relationship between model parameters and structural network topology and cognitive performance was assessed. Results showed (1) significantly improved prediction accuracy of individual functional connectivity when using individually optimized model parameters; (2) local model parameters that can differentiate between regions directly affected by a tumor, regions distant from a tumor, and regions in a healthy brain; and (3) interesting associations between individually optimized model parameters and structural network topology and cognitive performance.

Satellite Observations and Chemistry Climate Models - A Meandering Path Towards Better Predictions

NASA Technical Reports Server (NTRS)

Douglass, Anne R.

2011-01-01

Knowledge of the chemical and dynamical processes that control the stratospheric ozone layer has grown rapidly since the 1970s, when ideas that depletion of the ozone layer due to human activity were put forth. The concept of ozone depletion due to anthropogenic chlorine increase is simple; quantification of the effect is much more difficult. The future of stratospheric ozone is complicated because ozone is expected to increase for two reasons: the slow decrease in anthropogenic chlorine due to the Montreal Protocol and its amendments and stratospheric cooling caused by increases in carbon dioxide and other greenhouse gases. Prediction of future ozone levels requires three-dimensional models that represent physical, photochemical and radiative processes, i.e., chemistry climate models (CCMs). While laboratory kinetic and photochemical data are necessary inputs for a CCM, atmospheric measurements are needed both to reveal physical and chemical processes and for comparison with simulations to test the conceptual model that CCMs represent. Global measurements are available from various satellites including but not limited to the LIMS and TOMS instruments on Nimbus 7 (1979 - 1993), and various instruments on the Upper Atmosphere Research Satellite (1991 - 2005), Envisat (2002 - ongoing), Sci-Sat (2003 - ongoing) and Aura (2004 - ongoing). Every successful satellite instrument requires a physical concept for the measurement, knowledge of physical chemical properties of the molecules to be measured, and stellar engineering to design an instrument that will survive launch and operate for years with no opportunity for repair but providing enough information that trend information can be separated from any instrument change. The on-going challenge is to use observations to decrease uncertainty in prediction. This talk will focus on two applications. The first considers transport diagnostics and implications for prediction of the eventual demise of the Antarctic ozone hole. The second focuses on the upper stratosphere, where ozone is predicted to increase both due to chlorine decrease and due to temperature decrease expected as a result of increased concentrations Of CO2 and other greenhouse gases. Both applications show how diagnostics developed from global observations are being used to explain why the ozone response varies among CCM predictions for stratospheric ozone in the 21st century.

Estimation of brain network ictogenicity predicts outcome from epilepsy surgery

NASA Astrophysics Data System (ADS)

Goodfellow, M.; Rummel, C.; Abela, E.; Richardson, M. P.; Schindler, K.; Terry, J. R.

2016-07-01

Surgery is a valuable option for pharmacologically intractable epilepsy. However, significant post-operative improvements are not always attained. This is due in part to our incomplete understanding of the seizure generating (ictogenic) capabilities of brain networks. Here we introduce an in silico, model-based framework to study the effects of surgery within ictogenic brain networks. We find that factors conventionally determining the region of tissue to resect, such as the location of focal brain lesions or the presence of epileptiform rhythms, do not necessarily predict the best resection strategy. We validate our framework by analysing electrocorticogram (ECoG) recordings from patients who have undergone epilepsy surgery. We find that when post-operative outcome is good, model predictions for optimal strategies align better with the actual surgery undertaken than when post-operative outcome is poor. Crucially, this allows the prediction of optimal surgical strategies and the provision of quantitative prognoses for patients undergoing epilepsy surgery.

Prediction of clinical depression scores and detection of changes in whole-brain using resting-state functional MRI data with partial least squares regression

PubMed Central

Shimizu, Yu; Yoshimoto, Junichiro; Takamura, Masahiro; Okada, Go; Okamoto, Yasumasa; Yamawaki, Shigeto; Doya, Kenji

2017-01-01

In diagnostic applications of statistical machine learning methods to brain imaging data, common problems include data high-dimensionality and co-linearity, which often cause over-fitting and instability. To overcome these problems, we applied partial least squares (PLS) regression to resting-state functional magnetic resonance imaging (rs-fMRI) data, creating a low-dimensional representation that relates symptoms to brain activity and that predicts clinical measures. Our experimental results, based upon data from clinically depressed patients and healthy controls, demonstrated that PLS and its kernel variants provided significantly better prediction of clinical measures than ordinary linear regression. Subsequent classification using predicted clinical scores distinguished depressed patients from healthy controls with 80% accuracy. Moreover, loading vectors for latent variables enabled us to identify brain regions relevant to depression, including the default mode network, the right superior frontal gyrus, and the superior motor area. PMID:28700672

Spatial Attention, Motor Intention, and Bayesian Cue Predictability in the Human Brain.

PubMed

Kuhns, Anna B; Dombert, Pascasie L; Mengotti, Paola; Fink, Gereon R; Vossel, Simone

2017-05-24

Predictions about upcoming events influence how we perceive and respond to our environment. There is increasing evidence that predictions may be generated based upon previous observations following Bayesian principles, but little is known about the underlying cortical mechanisms and their specificity for different cognitive subsystems. The present study aimed at identifying common and distinct neural signatures of predictive processing in the spatial attentional and motor intentional system. Twenty-three female and male healthy human volunteers performed two probabilistic cueing tasks with either spatial or motor cues while lying in the fMRI scanner. In these tasks, the percentage of cue validity changed unpredictably over time. Trialwise estimates of cue predictability were derived from a Bayesian observer model of behavioral responses. These estimates were included as parametric regressors for analyzing the BOLD time series. Parametric effects of cue predictability in valid and invalid trials were considered to reflect belief updating by precision-weighted prediction errors. The brain areas exhibiting predictability-dependent effects dissociated between the spatial attention and motor intention task, with the right temporoparietal cortex being involved during spatial attention and the left angular gyrus and anterior cingulate cortex during motor intention. Connectivity analyses revealed that all three areas showed predictability-dependent coupling with the right hippocampus. These results suggest that precision-weighted prediction errors of stimulus locations and motor responses are encoded in distinct brain regions, but that crosstalk with the hippocampus may be necessary to integrate new trialwise outcomes in both cognitive systems. SIGNIFICANCE STATEMENT The brain is able to infer the environments' statistical structure and responds strongly to expectancy violations. In the spatial attentional domain, it has been shown that parts of the attentional networks are sensitive to the predictability of stimuli. It remains unknown, however, whether these effects are ubiquitous or if they are specific for different cognitive systems. The present study compared the influence of model-derived cue predictability on brain activity in the spatial attentional and motor intentional system. We identified areas with distinct predictability-dependent activation for spatial attention and motor intention, but also common connectivity changes of these regions with the hippocampus. These findings provide novel insights into the generality and specificity of predictive processing signatures in the human brain. Copyright © 2017 the authors 0270-6474/17/375334-11$15.00/0.

Wnt/Notum spatial feedback inhibition controls neoblast differentiation to regulate reversible growth of the planarian brain

PubMed Central

Hill, Eric M.; Petersen, Christian P.

2015-01-01

Mechanisms determining final organ size are poorly understood. Animals undergoing regeneration or ongoing adult growth are likely to require sustained and robust mechanisms to achieve and maintain appropriate sizes. Planarians, well known for their ability to undergo whole-body regeneration using pluripotent adult stem cells of the neoblast population, can reversibly scale body size over an order of magnitude by controlling cell number. Using quantitative analysis, we showed that after injury planarians perfectly restored brain:body proportion by increasing brain cell number through epimorphosis or decreasing brain cell number through tissue remodeling (morphallaxis), as appropriate. We identified a pathway controlling a brain size set-point that involves feedback inhibition between wnt11-6/wntA/wnt4a and notum, encoding conserved antagonistic signaling factors expressed at opposite brain poles. wnt11-6/wntA/wnt4a undergoes feedback inhibition through canonical Wnt signaling but is likely to regulate brain size in a non-canonical pathway independently of beta-catenin-1 and APC. Wnt/Notum signaling tunes numbers of differentiated brain cells in regenerative growth and tissue remodeling by influencing the abundance of brain progenitors descended from pluripotent stem cells, as opposed to regulating cell death. These results suggest that the attainment of final organ size might be accomplished by achieving a balance of positional signaling inputs that regulate the rates of tissue production. PMID:26525673

Is our brain hardwired to produce God, or is our brain hardwired to perceive God? A systematic review on the role of the brain in mediating religious experience.

PubMed

Fingelkurts, Alexander A; Fingelkurts, Andrew A

2009-11-01

To figure out whether the main empirical question "Is our brain hardwired to believe in and produce God, or is our brain hardwired to perceive and experience God?" is answered, this paper presents systematic critical review of the positions, arguments and controversies of each side of the neuroscientific-theological debate and puts forward an integral view where the human is seen as a psycho-somatic entity consisting of the multiple levels and dimensions of human existence (physical, biological, psychological, and spiritual reality), allowing consciousness/mind/spirit and brain/body/matter to be seen as different sides of the same phenomenon, neither reducible to each other. The emergence of a form of causation distinctive from physics where mental/conscious agency (a) is neither identical with nor reducible to brain processes and (b) does exert "downward" causal influence on brain plasticity and the various levels of brain functioning is discussed. This manuscript also discusses the role of cognitive processes in religious experience and outlines what can neuroscience offer for study of religious experience and what is the significance of this study for neuroscience, clinicians, theology and philosophy. A methodological shift from "explanation" to "description" of religious experience is suggested. This paper contributes to the ongoing discussion between theologians, cognitive psychologists and neuroscientists.

The ketogenic diet: metabolic influences on brain excitability and epilepsy

PubMed Central

Lutas, Andrew; Yellen, Gary

2012-01-01

A dietary therapy for pediatric epilepsy known as the ketogenic diet has seen a revival in its clinical use in the past decade. Though the diet’s underlying mechanism remains unknown, modern scientific approaches like genetic disruption of glucose metabolism are allowing for more detailed questions to be addressed. Recent work indicates that several mechanisms may exist for the ketogenic diet including disruption of glutamatergic synaptic transmission, inhibition of glycolysis, and activation of ATP-sensitive potassium channels. Here we describe on-going work in these areas that is providing a better understanding of metabolic influences on brain excitability and epilepsy. PMID:23228828

HYPERGLYCOSYLATED HUMAN CHORIONIC GONADOTROPIN AS AN EARLY PREDICTOR OF PREGNANCY OUTCOMES AFTER IN VITRO FERTILIZATION

PubMed Central

Chuan, Sandy; Homer, Michael; Pandian, Raj; Conway, Deirdre; Garzo, Gabriel; Yeo, Lisa; Su, H. Irene

2014-01-01

Objective To determine if hyperglycosylated hCG (hhCG), produced by invasive trophoblasts, measured as early as 9 days after egg retrieval can predict ongoing pregnancies (OP) after in vitro fertilization and fresh embryo transfer (IVF-ET). Design Cohort Setting Academic ART center Patients Consecutive patients undergoing IVF-ET Interventions Serum hhCG and hCG levels measured 9 (D9) and 16 (D16) days after egg retrieval Outcome Ongoing pregnancy (OP) beyond 9 weeks of gestation Results OP (62 of 112 participants) was associated with higher D9 levels of hhCG and hCG However, hhCG was detectable in all D9 OP samples, while hCG was detectable in only 22%. D9 hhCG levels >110 pg/mL was 96% specific for OP, yielding a positive predictive value of 95%. Compared to D9 hCG levels, hhCG was more sensitive and had a larger area under the curve (0.87 vs. 0.67). Diagnostic test characteristics were similar between D16 hhCG and hCG levels. Conclusions In patients undergoing assisted reproduction, a test to detect pregnancy early and predict outcomes is highly desirable. HhCG is detectable in serum 9 days after egg retrieval IVF-ET cycles. At this early assessment, hhCG is superior to traditional hCG and highly predictive of ongoing pregnancies. PMID:24355054

Engineers have more sons, nurses have more daughters: an evolutionary psychological extension of Baron-Cohen's extreme male brain theory of autism.

PubMed

Kanazawa, Satoshi; Vandermassen, Griet

2005-04-21

In his extreme male brain theory of autism, Baron-Cohen postulates that having a typically male brain was adaptive for ancestral men and having a typically female brain was adaptive for ancestral women. He also suggests that brain types are substantially heritable. These postulates, combined with the insight from the Trivers-Willard hypothesis regarding parental ability to vary offspring sex ratio, lead to the prediction that people who have strong male brains should have more sons than daughters, and people who have strong female brains should have more daughters than sons. The analysis of the 1994 US General Social Survey data provides support for this prediction. Our results suggest potentially fruitful extensions of both Baron-Cohen's theory and the Trivers-Willard hypothesis.

Neurobiological signatures associated with alcohol and drug use in the human adolescent brain

PubMed Central

Silveri, Marisa M.; Dager, Alecia D.; Cohen-Gilbert, Julia E.; Sneider, Jennifer T.

2017-01-01

Magnetic resonance (MR) techniques provide opportunities to non-invasively characterize neurobiological milestones of adolescent brain development. Juxtaposed to the critical finalization of brain development is initiation of alcohol and substance use, and increased frequency and quantity of use, patterns that can lead to abuse and addiction. This review provides a comprehensive overview of existing MR studies of adolescent alcohol and drug users. The most common alteration reported across substance used and MR modalities is in the frontal lobe (63% of published studies). This is not surprising, given that this is the last region to reach neurobiological adulthood. Comparatively, evidence is less consistent regarding alterations in regions that mature earlier (e.g., amygdala, hippocampus), however newer techniques now permit investigations beyond regional approaches that are uncovering network-level vulnerabilities. Regardless of whether neurobiological signatures exist prior to the initiation of use, this body of work provides important direction for ongoing prospective investigations of adolescent brain development, and the significant impact of alcohol and substance use on the brain during the second decade of life. PMID:27377691

Neurolinguistics: Structure, Function, and Connectivity in the Bilingual Brain

PubMed Central

Wong, Becky; Yin, Bin; O'Brien, Beth

2016-01-01

Advances in neuroimaging techniques and analytic methods have led to a proliferation of studies investigating the impact of bilingualism on the cognitive and brain systems in humans. Lately, these findings have attracted much interest and debate in the field, leading to a number of recent commentaries and reviews. Here, we contribute to the ongoing discussion by compiling and interpreting the plethora of findings that relate to the structural, functional, and connective changes in the brain that ensue from bilingualism. In doing so, we integrate theoretical models and empirical findings from linguistics, cognitive/developmental psychology, and neuroscience to examine the following issues: (1) whether the language neural network is different for first (dominant) versus second (nondominant) language processing; (2) the effects of bilinguals' executive functioning on the structure and function of the “universal” language neural network; (3) the differential effects of bilingualism on phonological, lexical-semantic, and syntactic aspects of language processing on the brain; and (4) the effects of age of acquisition and proficiency of the user's second language in the bilingual brain, and how these have implications for future research in neurolinguistics. PMID:26881224

Neurobiological signatures associated with alcohol and drug use in the human adolescent brain.

PubMed

Silveri, Marisa M; Dager, Alecia D; Cohen-Gilbert, Julia E; Sneider, Jennifer T

2016-11-01

Magnetic resonance (MR) techniques provide opportunities to non-invasively characterize neurobiological milestones of adolescent brain development. Juxtaposed to the critical finalization of brain development is initiation of alcohol and substance use, and increased frequency and quantity of use, patterns that can lead to abuse and addiction. This review provides a comprehensive overview of existing MR studies of adolescent alcohol and drug users. The most common alterations reported across substance used and MR modalities are in the frontal lobe (63% of published studies). This is not surprising, given that this is the last region to reach neurobiological adulthood. Comparatively, evidence is less consistent regarding alterations in regions that mature earlier (e.g., amygdala, hippocampus), however newer techniques now permit investigations beyond regional approaches that are uncovering network-level vulnerabilities. Regardless of whether neurobiological signatures exist prior to the initiation of use, this body of work provides important direction for ongoing prospective investigations of adolescent brain development, and the significant impact of alcohol and substance use on the brain during the second decade of life. Copyright © 2016 Elsevier Ltd. All rights reserved.

Found in translation: understanding the biology and behavior of experimental traumatic brain injury

PubMed Central

Bondi, Corina O.; Semple, Bridgette D.; Noble-Haeusslein, Linda J.; Osier, Nicole D.; Carlson, Shaun W.; Dixon, C. Edward; Giza, Christopher C.; Kline, Anthony E.

2014-01-01

BONDI, C.O., B.D. Semple, L.J. Noble-Haeusslein, N.D. Osier, S.W. Carlson, C.E. Dixon, C.C. Giza and A.E. Kline. Found in translation: understanding the biology and behavior of experimental traumatic brain injury. NEUROSCI BIOBEHAV REV. The aim of this review is to discuss in greater detail the topics covered in the recent symposium entitled “Traumatic brain injury: laboratory and clinical perspectives,” presented at the 2014 International Behavioral Neuroscience Society annual meeting. Herein we review contemporary laboratory models of traumatic brain injury (TBI) including common assays for sensorimotor and cognitive behavior. New modalities to evaluate social behavior after injury to the developing brain, as well as the attentional set-shifting test (AST) as a measure of executive function in TBI, will be highlighted. Environmental enrichment (EE) will be discussed as a preclinical model of neurorehabilitation, and finally, an evidence-based approach to sports-related concussion will be considered. The review consists predominantly of published data, but some discussion of ongoing or future directions is provided. PMID:25496906

Cerebral cartography and connectomics

PubMed Central

Sporns, Olaf

2015-01-01

Cerebral cartography and connectomics pursue similar goals in attempting to create maps that can inform our understanding of the structural and functional organization of the cortex. Connectome maps explicitly aim at representing the brain as a complex network, a collection of nodes and their interconnecting edges. This article reflects on some of the challenges that currently arise in the intersection of cerebral cartography and connectomics. Principal challenges concern the temporal dynamics of functional brain connectivity, the definition of areal parcellations and their hierarchical organization into large-scale networks, the extension of whole-brain connectivity to cellular-scale networks, and the mapping of structure/function relations in empirical recordings and computational models. Successfully addressing these challenges will require extensions of methods and tools from network science to the mapping and analysis of human brain connectivity data. The emerging view that the brain is more than a collection of areas, but is fundamentally operating as a complex networked system, will continue to drive the creation of ever more detailed and multi-modal network maps as tools for on-going exploration and discovery in human connectomics. PMID:25823870

Brain Structural Integrity and Intrinsic Functional Connectivity Forecast 6 Year Longitudinal Growth in Children's Numerical Abilities.

PubMed

Evans, Tanya M; Kochalka, John; Ngoon, Tricia J; Wu, Sarah S; Qin, Shaozheng; Battista, Christian; Menon, Vinod

2015-08-19

Early numerical proficiency lays the foundation for acquiring quantitative skills essential in today's technological society. Identification of cognitive and brain markers associated with long-term growth of children's basic numerical computation abilities is therefore of utmost importance. Previous attempts to relate brain structure and function to numerical competency have focused on behavioral measures from a single time point. Thus, little is known about the brain predictors of individual differences in growth trajectories of numerical abilities. Using a longitudinal design, with multimodal imaging and machine-learning algorithms, we investigated whether brain structure and intrinsic connectivity in early childhood are predictive of 6 year outcomes in numerical abilities spanning childhood and adolescence. Gray matter volume at age 8 in distributed brain regions, including the ventrotemporal occipital cortex (VTOC), the posterior parietal cortex, and the prefrontal cortex, predicted longitudinal gains in numerical, but not reading, abilities. Remarkably, intrinsic connectivity analysis revealed that the strength of functional coupling among these regions also predicted gains in numerical abilities, providing novel evidence for a network of brain regions that works in concert to promote numerical skill acquisition. VTOC connectivity with posterior parietal, anterior temporal, and dorsolateral prefrontal cortices emerged as the most extensive network predicting individual gains in numerical abilities. Crucially, behavioral measures of mathematics, IQ, working memory, and reading did not predict children's gains in numerical abilities. Our study identifies, for the first time, functional circuits in the human brain that scaffold the development of numerical skills, and highlights potential biomarkers for identifying children at risk for learning difficulties. Children show substantial individual differences in math abilities and ease of math learning. Early numerical abilities provide the foundation for future academic and professional success in an increasingly technological society. Understanding the early identification of poor math skills has therefore taken on great significance. This work provides important new insights into brain structure and connectivity measures that can predict longitudinal growth of children's math skills over a 6 year period, and may eventually aid in the early identification of children who might benefit from targeted interventions. Copyright © 2015 the authors 0270-6474/15/3511743-08$15.00/0.

Altered predictive capability of the brain network EEG model in schizophrenia during cognition.

PubMed

Gomez-Pilar, Javier; Poza, Jesús; Gómez, Carlos; Northoff, Georg; Lubeiro, Alba; Cea-Cañas, Benjamín B; Molina, Vicente; Hornero, Roberto

2018-05-12

The study of the mechanisms involved in cognition is of paramount importance for the understanding of the neurobiological substrates in psychiatric disorders. Hence, this research is aimed at exploring the brain network dynamics during a cognitive task. Specifically, we analyze the predictive capability of the pre-stimulus theta activity to ascertain the functional brain dynamics during cognition in both healthy and schizophrenia subjects. Firstly, EEG recordings were acquired during a three-tone oddball task from fifty-one healthy subjects and thirty-five schizophrenia patients. Secondly, phase-based coupling measures were used to generate the time-varying functional network for each subject. Finally, pre-stimulus network connections were iteratively modified according to different models of network reorganization. This adjustment was applied by minimizing the prediction error through recurrent iterations, following the predictive coding approach. Both controls and schizophrenia patients follow a reinforcement of the secondary neural pathways (i.e., pathways between cortical brain regions weakly connected during pre-stimulus) for most of the subjects, though the ratio of controls that exhibited this behavior was statistically significant higher than for patients. These findings suggest that schizophrenia is associated with an impaired ability to modify brain network configuration during cognition. Furthermore, we provide direct evidence that the changes in phase-based brain network parameters from pre-stimulus to cognitive response in the theta band are closely related to the performance in important cognitive domains. Our findings not only contribute to the understanding of healthy brain dynamics, but also shed light on the altered predictive neuronal substrates in schizophrenia. Copyright © 2018 Elsevier B.V. All rights reserved.

Automated detection of brain atrophy patterns based on MRI for the prediction of Alzheimer's disease

PubMed Central

Plant, Claudia; Teipel, Stefan J.; Oswald, Annahita; Böhm, Christian; Meindl, Thomas; Mourao-Miranda, Janaina; Bokde, Arun W.; Hampel, Harald; Ewers, Michael

2010-01-01

Subjects with mild cognitive impairment (MCI) have an increased risk to develop Alzheimer's disease (AD). Voxel-based MRI studies have demonstrated that widely distributed cortical and subcortical brain areas show atrophic changes in MCI, preceding the onset of AD-type dementia. Here we developed a novel data mining framework in combination with three different classifiers including support vector machine (SVM), Bayes statistics, and voting feature intervals (VFI) to derive a quantitative index of pattern matching for the prediction of the conversion from MCI to AD. MRI was collected in 32 AD patients, 24 MCI subjects and 18 healthy controls (HC). Nine out of 24 MCI subjects converted to AD after an average follow-up interval of 2.5 years. Using feature selection algorithms, brain regions showing the highest accuracy for the discrimination between AD and HC were identified, reaching a classification accuracy of up to 92%. The extracted AD clusters were used as a search region to extract those brain areas that are predictive of conversion to AD within MCI subjects. The most predictive brain areas included the anterior cingulate gyrus and orbitofrontal cortex. The best prediction accuracy, which was cross-validated via train-and-test, was 75% for the prediction of the conversion from MCI to AD. The present results suggest that novel multivariate methods of pattern matching reach a clinically relevant accuracy for the a priori prediction of the progression from MCI to AD. PMID:19961938

Assessment of MRI-Based Automated Fetal Cerebral Cortical Folding Measures in Prediction of Gestational Age in the Third Trimester.

PubMed

Wu, J; Awate, S P; Licht, D J; Clouchoux, C; du Plessis, A J; Avants, B B; Vossough, A; Gee, J C; Limperopoulos, C

2015-07-01

Traditional methods of dating a pregnancy based on history or sonographic assessment have a large variation in the third trimester. We aimed to assess the ability of various quantitative measures of brain cortical folding on MR imaging in determining fetal gestational age in the third trimester. We evaluated 8 different quantitative cortical folding measures to predict gestational age in 33 healthy fetuses by using T2-weighted fetal MR imaging. We compared the accuracy of the prediction of gestational age by these cortical folding measures with the accuracy of prediction by brain volume measurement and by a previously reported semiquantitative visual scale of brain maturity. Regression models were constructed, and measurement biases and variances were determined via a cross-validation procedure. The cortical folding measures are accurate in the estimation and prediction of gestational age (mean of the absolute error, 0.43 ± 0.45 weeks) and perform better than (P = .024) brain volume (mean of the absolute error, 0.72 ± 0.61 weeks) or sonography measures (SDs approximately 1.5 weeks, as reported in literature). Prediction accuracy is comparable with that of the semiquantitative visual assessment score (mean, 0.57 ± 0.41 weeks). Quantitative cortical folding measures such as global average curvedness can be an accurate and reliable estimator of gestational age and brain maturity for healthy fetuses in the third trimester and have the potential to be an indicator of brain-growth delays for at-risk fetuses and preterm neonates. © 2015 by American Journal of Neuroradiology.

Magnetic resonance spectroscopy metabolite profiles predict survival in paediatric brain tumours.

PubMed

Wilson, Martin; Cummins, Carole L; Macpherson, Lesley; Sun, Yu; Natarajan, Kal; Grundy, Richard G; Arvanitis, Theodoros N; Kauppinen, Risto A; Peet, Andrew C

2013-01-01

Brain tumours cause the highest mortality and morbidity rate of all childhood tumour groups and new methods are required to improve clinical management. (1)H magnetic resonance spectroscopy (MRS) allows non-invasive concentration measurements of small molecules present in tumour tissue, providing clinically useful imaging biomarkers. The primary aim of this study was to investigate whether MRS detectable molecules can predict the survival of paediatric brain tumour patients. Short echo time (30ms) single voxel (1)H MRS was performed on children attending Birmingham Children's Hospital with a suspected brain tumour and 115 patients were included in the survival analysis. Patients were followed-up for a median period of 35 months and Cox-Regression was used to establish the prognostic value of individual MRS detectable molecules. A multivariate model of survival was also investigated to improve prognostic power. Lipids and scyllo-inositol predicted poor survival whilst glutamine and N-acetyl aspartate predicted improved survival (p<0.05). A multivariate model of survival based on three MRS biomarkers predicted survival with a similar accuracy to histologic grading (p<5e-5). A negative correlation between lipids and glutamine was found, suggesting a functional link between these molecules. MRS detectable biomolecules have been identified that predict survival of paediatric brain tumour patients across a range of tumour types. The evaluation of these biomarkers in large prospective studies of specific tumour types should be undertaken. The correlation between lipids and glutamine provides new insight into paediatric brain tumour metabolism that may present novel targets for therapy. Copyright © 2012 Elsevier Ltd. All rights reserved.

Brain metabolism in health, aging, and neurodegeneration.

PubMed

Camandola, Simonetta; Mattson, Mark P

2017-06-01

Brain cells normally respond adaptively to bioenergetic challenges resulting from ongoing activity in neuronal circuits, and from environmental energetic stressors such as food deprivation and physical exertion. At the cellular level, such adaptive responses include the "strengthening" of existing synapses, the formation of new synapses, and the production of new neurons from stem cells. At the molecular level, bioenergetic challenges result in the activation of transcription factors that induce the expression of proteins that bolster the resistance of neurons to the kinds of metabolic, oxidative, excitotoxic, and proteotoxic stresses involved in the pathogenesis of brain disorders including stroke, and Alzheimer's and Parkinson's diseases. Emerging findings suggest that lifestyles that include intermittent bioenergetic challenges, most notably exercise and dietary energy restriction, can increase the likelihood that the brain will function optimally and in the absence of disease throughout life. Here, we provide an overview of cellular and molecular mechanisms that regulate brain energy metabolism, how such mechanisms are altered during aging and in neurodegenerative disorders, and the potential applications to brain health and disease of interventions that engage pathways involved in neuronal adaptations to metabolic stress. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Regulation of cerebrospinal fluid (CSF) flow in neurodegenerative, neurovascular and neuroinflammatory disease.

PubMed

Simon, Matthew J; Iliff, Jeffrey J

2016-03-01

Cerebrospinal fluid (CSF) circulation and turnover provides a sink for the elimination of solutes from the brain interstitium, serving an important homeostatic role for the function of the central nervous system. Disruption of normal CSF circulation and turnover is believed to contribute to the development of many diseases, including neurodegenerative conditions such as Alzheimer's disease, ischemic and traumatic brain injury, and neuroinflammatory conditions such as multiple sclerosis. Recent insights into CSF biology suggesting that CSF and interstitial fluid exchange along a brain-wide network of perivascular spaces termed the 'glymphatic' system suggest that CSF circulation may interact intimately with glial and vascular function to regulate basic aspects of brain function. Dysfunction within this glial vascular network, which is a feature of the aging and injured brain, is a potentially critical link between brain injury, neuroinflammation and the development of chronic neurodegeneration. Ongoing research within this field may provide a powerful new framework for understanding the common links between neurodegenerative, neurovascular and neuroinflammatory disease, in addition to providing potentially novel therapeutic targets for these conditions. This article is part of a Special Issue entitled: Neuro Inflammation edited by Helga E. de Vries and Markus Schwaninger. Copyright © 2015 Elsevier B.V. All rights reserved.

Diffusion-weighted imaging score of the brain stem: A predictor of outcome in acute basilar artery occlusion treated with the Solitaire FR device.

PubMed

Mourand, I; Machi, P; Nogué, E; Arquizan, C; Costalat, V; Picot, M-C; Bonafé, A; Milhaud, D

2014-06-01

The prognosis for ischemic stroke due to acute basilar artery occlusion is very poor: Early recanalization remains the main factor that can improve outcomes. The baseline extent of brain stem ischemic damage can also influence outcomes. We evaluated the validity of an easy-to-use DWI score to predict clinical outcome in patients with acute basilar artery occlusion treated by mechanical thrombectomy. We analyzed the baseline clinical and DWI parameters of 31 patients with acute basilar artery occlusion, treated within 24 hours of symptom onset by using a Solitaire FR device. The DWI score of the brain stem was assessed with a 12-point semiquantitative score that separately considered each side of the medulla, pons, and midbrain. Clinical outcome was assessed at 180 days by using the mRS. According to receiver operating characteristic analyses, the cutoff score determined the optimal positive predictive value for outcome. The Spearman rank correlation coefficient assessed the correlation between the DWI brain stem score and baseline characteristics. Successful recanalization (Thrombolysis in Cerebral Infarction 3-2b) was achieved in 23 patients (74%). A favorable outcome (mRS ≤ 2) was observed in 11 patients (35%). An optimal DWI brain stem score of <3 predicted a favorable outcome. The probability of a very poor outcome (mRS ≥ 5) if the DWI brain stem score was ≥5 reached 80% (positive predictive value) and 100% if this score was ≥6. Interobserver reliability of the DWI brain stem score was excellent, with an intraclass correlation coefficient of 0.97 (95% CI, 0.96-0.99). The DWI brain stem score was significantly associated with baseline tetraplegia (P = .001) and coma (P = .005). In patients with acute basilar artery occlusion treated by mechanical thrombectomy, the baseline DWI brain lesion score seems to predict clinical outcome. © 2014 by American Journal of Neuroradiology.

Model development, testing and experimentation in a CyberWorkstation for Brain-Machine Interface research.

PubMed

Rattanatamrong, Prapaporn; Matsunaga, Andrea; Raiturkar, Pooja; Mesa, Diego; Zhao, Ming; Mahmoudi, Babak; Digiovanna, Jack; Principe, Jose; Figueiredo, Renato; Sanchez, Justin; Fortes, Jose

2010-01-01

The CyberWorkstation (CW) is an advanced cyber-infrastructure for Brain-Machine Interface (BMI) research. It allows the development, configuration and execution of BMI computational models using high-performance computing resources. The CW's concept is implemented using a software structure in which an "experiment engine" is used to coordinate all software modules needed to capture, communicate and process brain signals and motor-control commands. A generic BMI-model template, which specifies a common interface to the CW's experiment engine, and a common communication protocol enable easy addition, removal or replacement of models without disrupting system operation. This paper reviews the essential components of the CW and shows how templates can facilitate the processes of BMI model development, testing and incorporation into the CW. It also discusses the ongoing work towards making this process infrastructure independent.

The Berlin Brain-Computer Interface: Progress Beyond Communication and Control

PubMed Central

Blankertz, Benjamin; Acqualagna, Laura; Dähne, Sven; Haufe, Stefan; Schultze-Kraft, Matthias; Sturm, Irene; Ušćumlic, Marija; Wenzel, Markus A.; Curio, Gabriel; Müller, Klaus-Robert

2016-01-01

The combined effect of fundamental results about neurocognitive processes and advancements in decoding mental states from ongoing brain signals has brought forth a whole range of potential neurotechnological applications. In this article, we review our developments in this area and put them into perspective. These examples cover a wide range of maturity levels with respect to their applicability. While we assume we are still a long way away from integrating Brain-Computer Interface (BCI) technology in general interaction with computers, or from implementing neurotechnological measures in safety-critical workplaces, results have already now been obtained involving a BCI as research tool. In this article, we discuss the reasons why, in some of the prospective application domains, considerable effort is still required to make the systems ready to deal with the full complexity of the real world. PMID:27917107

The Berlin Brain-Computer Interface: Progress Beyond Communication and Control.

PubMed

Blankertz, Benjamin; Acqualagna, Laura; Dähne, Sven; Haufe, Stefan; Schultze-Kraft, Matthias; Sturm, Irene; Ušćumlic, Marija; Wenzel, Markus A; Curio, Gabriel; Müller, Klaus-Robert

2016-01-01

The combined effect of fundamental results about neurocognitive processes and advancements in decoding mental states from ongoing brain signals has brought forth a whole range of potential neurotechnological applications. In this article, we review our developments in this area and put them into perspective. These examples cover a wide range of maturity levels with respect to their applicability. While we assume we are still a long way away from integrating Brain-Computer Interface (BCI) technology in general interaction with computers, or from implementing neurotechnological measures in safety-critical workplaces, results have already now been obtained involving a BCI as research tool. In this article, we discuss the reasons why, in some of the prospective application domains, considerable effort is still required to make the systems ready to deal with the full complexity of the real world.

A square root ensemble Kalman filter application to a motor-imagery brain-computer interface.

PubMed

Kamrunnahar, M; Schiff, S J

2011-01-01

We here investigated a non-linear ensemble Kalman filter (SPKF) application to a motor imagery brain computer interface (BCI). A square root central difference Kalman filter (SR-CDKF) was used as an approach for brain state estimation in motor imagery task performance, using scalp electroencephalography (EEG) signals. Healthy human subjects imagined left vs. right hand movements and tongue vs. bilateral toe movements while scalp EEG signals were recorded. Offline data analysis was conducted for training the model as well as for decoding the imagery movements. Preliminary results indicate the feasibility of this approach with a decoding accuracy of 78%-90% for the hand movements and 70%-90% for the tongue-toes movements. Ongoing research includes online BCI applications of this approach as well as combined state and parameter estimation using this algorithm with different system dynamic models.

Periodicity of high-order neural functions

NASA Technical Reports Server (NTRS)

Kellaway, P.; Borda, R. P.; Frost, J. D.; Carrie, J. R. G.; Coats, A. C.

1973-01-01

The results of recent studies on higher order, integrative processes in the central nervous system are reported. Attempts were made to determine whether these processes exhibit any ongoing rhythmicity which might manifest itself in alterations of attention and alertness. Experiments were also designed to determine if a periodicity approximating that of the REM could be detected in various parameters of brain electrical activity.

Controlling Working Memory Operations by Selective Gating: The Roles of Oscillations and Synchrony

PubMed Central

Dipoppa, Mario; Szwed, Marcin; Gutkin, Boris S.

2016-01-01

Working memory (WM) is a primary cognitive function that corresponds to the ability to update, stably maintain, and manipulate short-term memory (ST M) rapidly to perform ongoing cognitive tasks. A prevalent neural substrate of WM coding is persistent neural activity, the property of neurons to remain active after having been activated by a transient sensory stimulus. This persistent activity allows for online maintenance of memory as well as its active manipulation necessary for task performance. WM is tightly capacity limited. Therefore, selective gating of sensory and internally generated information is crucial for WM function. While the exact neural substrate of selective gating remains unclear, increasing evidence suggests that it might be controlled by modulating ongoing oscillatory brain activity. Here, we review experiments and models that linked selective gating, persistent activity, and brain oscillations, putting them in the more general mechanistic context of WM. We do so by defining several operations necessary for successful WM function and then discussing how such operations may be carried out by mechanisms suggested by computational models. We specifically show how oscillatory mechanisms may provide a rapid and flexible active gating mechanism for WM operations. PMID:28154616

Tenure Track Investigator | Center for Cancer Research

Cancer.gov

The Neuro-Oncology Branch (NOB), Center for Cancer Research (CCR) of the National Cancer Institute (NCI), National Institutes of Health (NIH), Department of Health and Human Services (HHS), Bethesda, MD, is actively recruiting for a tenure-track principal investigator to work in the area of immunology and/or immunotherapy.  The NOB Immunology/Immunotherapy Investigator will be tasked with forming and leading an independent research program.  This position will build the basic immunology program in the NOB and complement ongoing and planned translational research and clinical trials evaluating the effects of immunotherapy in patients with primary brain tumors.  This program will be able to access biospecimens generated from ongoing and planned immunotherapy protocols within the NOB, thus creating an opportunity to perform correlative studies to interrogate the complex biology of immunologic response, toxicity, and treatment resistance.  Demonstrated expertise in scientific inquiries in immunotherapy and/or immunology are essential, but prior work in brain tumors is not required.  This is an exciting opportunity to join a growing trans-institutional research team that promotes and supports collaborations across the basic, translational, and clinical research spectrum to develop novel therapeutics for individuals with primary central nervous system malignancies that will globally influence the field.

[Intensive care treatment of traumatic brain injury in multiple trauma patients : Decision making for complex pathophysiology].

PubMed

Trimmel, H; Herzer, G; Schöchl, H; Voelckel, W G

2017-09-01

Traumatic brain injury (TBI) and hemorrhagic shock due to uncontrolled bleeding are the major causes of death after severe trauma. Mortality rates are threefold higher in patients suffering from multiple injuries and additionally TBI. Factors known to impair outcome after TBI, namely hypotension, hypoxia, hypercapnia, acidosis, coagulopathy and hypothermia are aggravated by the extent and severity of extracerebral injuries. The mainstays of TBI intensive care may be, at least temporarily, contradictory to the trauma care concept for multiple trauma patients. In particular, achieving normotension in uncontrolled bleeding situations, maintenance of normocapnia in traumatic lung injury and thromboembolic prophylaxis are prone to discussion. Due to an ongoing uncertainty about the definition of normotensive blood pressure values, a cerebral perfusion pressure-guided cardiovascular management is of key importance. In contrast, there is no doubt that early goal directed coagulation management improves outcome in patients with TBI and multiple trauma. The timing of subsequent surgical interventions must be based on the development of TBI pathology; therefore, intensive care of multiple trauma patients with TBI requires an ongoing and close cooperation between intensivists and trauma surgeons in order to individualize patient care.

Controlling Working Memory Operations by Selective Gating: The Roles of Oscillations and Synchrony.

PubMed

Dipoppa, Mario; Szwed, Marcin; Gutkin, Boris S

2016-01-01

Working memory (WM) is a primary cognitive function that corresponds to the ability to update, stably maintain, and manipulate short-term memory (ST M) rapidly to perform ongoing cognitive tasks. A prevalent neural substrate of WM coding is persistent neural activity , the property of neurons to remain active after having been activated by a transient sensory stimulus. This persistent activity allows for online maintenance of memory as well as its active manipulation necessary for task performance. WM is tightly capacity limited. Therefore, selective gating of sensory and internally generated information is crucial for WM function. While the exact neural substrate of selective gating remains unclear, increasing evidence suggests that it might be controlled by modulating ongoing oscillatory brain activity. Here, we review experiments and models that linked selective gating, persistent activity, and brain oscillations, putting them in the more general mechanistic context of WM. We do so by defining several operations necessary for successful WM function and then discussing how such operations may be carried out by mechanisms suggested by computational models. We specifically show how oscillatory mechanisms may provide a rapid and flexible active gating mechanism for WM operations.

Ongoing daytime behavioural problems in university students following childhood mild traumatic brain injury.

PubMed

Albicini, Michelle S; Lee, James; McKinlay, Audrey

2016-03-01

Sleep is often disrupted in traumatic brain injury (TBI) and may be related to persistent behaviour problems; however, little is known about this relationship in young adults. This study explored associations between TBI, behavioural problems and sleep disturbances in 247 university students (197 non-TBI, 47 mild TBI, two moderate TBI, one severe TBI) aged 18-25 years, who completed validated measures for behaviour, sleep quality and history of TBI. Because of small group numbers, participants reporting moderate to severe TBI were excluded from the analyses. Results indicated that students with mild TBI reported higher levels of daytime dysfunction, somatic complaints, withdrawal, other behavioural complaints and internalizing behaviours compared with students with no TBI history. A correlational analysis indicated a moderate relationship between the above significant variables. Our results suggest that university students with a history of mild TBI are more likely to experience certain ongoing daytime behavioural problems, which are likely to negatively influence their academic functioning in tertiary education. This study highlights the importance of research on long-term problems following mild TBI in young adults aged 18-25 years--an age group often overlooked within the literature.

The US Navy Coastal Surge and Inundation Prediction System (CSIPS): Making Forecasts Easier

DTIC Science & Technology

2013-02-14

produced the best results Peak Water Level Percent Error CD Formulation LAWMA , Amerada Pass Freshwater Canal Locks Calcasieu Pass Sabine Pass...Conclusions Ongoing Work 16 Baseline Simulation Results Peak Water Level Percent Error LAWMA , Amerada Pass Freshwater Canal Locks Calcasieu Pass...Conclusions Ongoing Work 20 Sensitivity Studies Waves Run Water Level – Percent Error of Peak HWM MAPE Lawma , Armeda Pass Freshwater

Does tooth wear status predict ongoing sleep bruxism in 30-year-old Japanese subjects?

PubMed

Baba, Kazuyoshi; Haketa, Tadasu; Clark, Glenn T; Ohyama, Takashi

2004-01-01

This study investigated whether tooth wear status can predict bruxism level. Sixteen Japanese subjects (eight bruxers and eight age- and gender-matched controls; mean age 30 years) participated in this study. From dental casts of these subjects, the tooth wear was scored by Murphy's method. Bruxism level in these subjects was also recorded for 5 consecutive nights in the subject's home environment using a force-based bruxism detecting system. The relationship between the tooth wear score and bruxism data was evaluated statistically. Correlation analysis between the Murphy's scores of maxillary and mandibular dental arch and bruxism event duration score revealed no significant relationship between tooth wear and current bruxism. Tooth wear status is not predictive of ongoing bruxism level as measured by the force-based bruxism detection system in 30-year-old Japanese subjects.

Temporal lobe interictal epileptic discharges affect cerebral activity in “default mode” brain regions

PubMed Central

Laufs, Helmut; Hamandi, Khalid; Salek-Haddadi, Afraim; Kleinschmidt, Andreas K; Duncan, John S; Lemieux, Louis

2007-01-01

A cerebral network comprising precuneus, medial frontal, and temporoparietal cortices is less active both during goal-directed behavior and states of reduced consciousness than during conscious rest. We tested the hypothesis that the interictal epileptic discharges affect activity in these brain regions in patients with temporal lobe epilepsy who have complex partial seizures. At the group level, using electroencephalography-correlated functional magnetic resonance imaging in 19 consecutive patients with focal epilepsy, we found common decreases of resting state activity in 9 patients with temporal lobe epilepsy (TLE) but not in 10 patients with extra-TLE. We infer that the functional consequences of TLE interictal epileptic discharges are different from those in extra-TLE and affect ongoing brain function. Activity increases were detected in the ipsilateral hippocampus in patients with TLE, and in subthalamic, bilateral superior temporal and medial frontal brain regions in patients with extra-TLE, possibly indicating effects of different interictal epileptic discharge propagation. PMID:17133385

Rostro-caudal and dorso-ventral gradients in medial and lateral prefrontal cortex during cognitive control of affective and cognitive interference.

PubMed

Rahm, Christoffer; Liberg, Benny; Wiberg-Kristoffersen, Maria; Aspelin, Peter; Msghina, Mussie

2013-04-01

Characterizing the anatomical substrates of major brain functions such as cognition and emotion is of utmost importance to the ongoing efforts of understanding the nature of psychiatric ailments and their potential treatment. The aim of our study was to investigate how the brain handles affective and cognitive interferences on cognitive processes. Functional magnetic resonance imaging investigation was performed on healthy individuals, comparing the brain oxygenation level dependent activation patterns during affective and cognitive counting Stroop tasks. The affective Stroop task activated rostral parts of medial prefrontal cortex (PFC) and rostral and ventral parts of lateral PFC, while cognitive Stroop activated caudal parts of medial PFC and caudal and dorsal parts of lateral PFC. Our findings suggest that the brain may handle affective and cognitive interference on cognitive processes differentially, with affective interference preferentially activating rostral and ventral PFC networks and cognitive interference activating caudal and dorsal PFC networks. © 2013 The Authors. Scandinavian Journal of Psychology © 2013 The Scandinavian Psychological Associations.

Acetylcholine as a neuromodulator: cholinergic signaling shapes nervous system function and behavior

PubMed Central

Picciotto, Marina R.; Higley, Michael J.; Mineur, Yann S.

2012-01-01

Acetylcholine in the brain alters neuronal excitability, influences synaptic transmission, induces synaptic plasticity and coordinates the firing of groups of neurons. As a result, it changes the state of neuronal networks throughout the brain and modifies their response to internal and external inputs: the classical role of a neuromodulator. Here we identify actions of cholinergic signaling on cellular and synaptic properties of neurons in several brain areas and discuss the consequences of this signaling on behaviors related to drug abuse, attention, food intake, and affect. The diverse effects of acetylcholine depend on the site of release, the receptor subtypes, and the target neuronal population, however, a common theme is that acetylcholine potentiates behaviors that are adaptive to environmental stimuli and decreases responses to ongoing stimuli that do not require immediate action. The ability of acetylcholine to coordinate the response of neuronal networks in many brain areas makes cholinergic modulation an essential mechanism underlying complex behaviors. PMID:23040810

Management of sport-related concussion in young athletes.

PubMed

Patel, Dilip R; Shivdasani, Vandana; Baker, Robert J

2005-01-01

Sport-related head injuries are a common clinical problem. Most head injuries in young athletes are mild traumatic brain injuries or concussions. The highest number of sport-related concussions has been reported in American football. In addition to the well described physical and psychosocial growth, there is ongoing neurocognitive development of the brain during childhood and through adolescence. This developmental process has direct implications in the assessment and management of head injuries in young athletes. Research on the management and long-term outcome following brain injuries in young athletes is limited. Traditionally, the assessment of concussion has been based on clinical history and physical and neurological examination. Increasingly, neuropsychological testing, especially computerised testing, is providing objective measures for the initial assessment and follow-up of young athletes following brain injuries. Numerous guidelines have been published for grading and return to play criteria following concussion; however, none of these have been prospectively validated by research and none are specifically applicable to children and adolescents.

Tracking ongoing cognition in individuals using brief, whole-brain functional connectivity patterns

PubMed Central

Gonzalez-Castillo, Javier; Hoy, Colin W.; Handwerker, Daniel A.; Robinson, Meghan E.; Buchanan, Laura C.; Saad, Ziad S.; Bandettini, Peter A.

2015-01-01

Functional connectivity (FC) patterns in functional MRI exhibit dynamic behavior on the scale of seconds, with rich spatiotemporal structure and limited sets of whole-brain, quasi-stable FC configurations (FC states) recurring across time and subjects. Based on previous evidence linking various aspects of cognition to group-level, minute-to-minute FC changes in localized connections, we hypothesized that whole-brain FC states may reflect the global, orchestrated dynamics of cognitive processing on the scale of seconds. To test this hypothesis, subjects were continuously scanned as they engaged in and transitioned between mental states dictated by tasks. FC states computed within windows as short as 22.5 s permitted robust tracking of cognition in single subjects with near perfect accuracy. Accuracy dropped markedly for subjects with the lowest task performance. Spatially restricting FC information decreased accuracy at short time scales, emphasizing the distributed nature of whole-brain FC dynamics, beyond univariate magnitude changes, as valuable markers of cognition. PMID:26124112

Insular dwarfism in hippos and a model for brain size reduction in Homo floresiensis.

PubMed

Weston, Eleanor M; Lister, Adrian M

2009-05-07

Body size reduction in mammals is usually associated with only moderate brain size reduction, because the brain and sensory organs complete their growth before the rest of the body during ontogeny. On this basis, 'phyletic dwarfs' are predicted to have a greater relative brain size than 'phyletic giants'. However, this trend has been questioned in the special case of dwarfism of mammals on islands. Here we show that the endocranial capacities of extinct dwarf species of hippopotamus from Madagascar are up to 30% smaller than those of a mainland African ancestor scaled to equivalent body mass. These results show that brain size reduction is much greater than predicted from an intraspecific 'late ontogenetic' model of dwarfism in which brain size scales to body size with an exponent of 0.35. The nature of the proportional change or grade shift observed here indicates that selective pressures on brain size are potentially independent of those on body size. This study demonstrates empirically that it is mechanistically possible for dwarf mammals on islands to evolve significantly smaller brains than would be predicted from a model of dwarfing based on the intraspecific scaling of the mainland ancestor. Our findings challenge current understanding of brain-body allometric relationships in mammals and suggest that the process of dwarfism could in principle explain small brain size, a factor relevant to the interpretation of the small-brained hominin found on the Island of Flores, Indonesia.

Insular dwarfism in hippos and a model for brain size reduction in Homo floresiensis

PubMed Central

Weston, Eleanor M.; Lister, Adrian M.

2009-01-01

Body size reduction in mammals is usually associated with only moderate brain size reduction as the brain and sensory organs complete their growth before the rest of the body during ontogeny1,2. On this basis “phyletic dwarfs” are predicted to have a higher relative brain size than “phyletic giants”1,3. This trend has been questioned, however, in the special case of dwarfism of mammals on islands4. Here we show that the endocranial capacities of extinct dwarf species of hippopotamus from Madagascar are up to 30% smaller than those of a mainland African ancestor scaled to equivalent body mass. These results show brain size reduction is much greater than predicted from an intraspecific ‘late ontogenetic’ model of dwarfism where brain size scales to body size with an exponent of 0.35. The nature of the proportional change or grade shift2,5 observed here indicates that selective pressures upon brain size are potentially independent from those on body size. This study demonstrates empirically that it is mechanistically possible for dwarf mammals on islands to evolve significantly smaller brains than would be predicted from a model of dwarfing based on the intraspecific scaling of the mainland ancestor. Our findings challenge our understanding of brain-body allometric relationships in mammals and suggest that the process of dwarfism could in principle explain small brain size, a factor relevant to the interpretation of the small-brained hominin found on the Island of Flores, Indonesia6. PMID:19424156

Brain shift computation using a fully nonlinear biomechanical model.

PubMed

Wittek, Adam; Kikinis, Ron; Warfield, Simon K; Miller, Karol

2005-01-01

In the present study, fully nonlinear (i.e. accounting for both geometric and material nonlinearities) patient specific finite element brain model was applied to predict deformation field within the brain during the craniotomy-induced brain shift. Deformation of brain surface was used as displacement boundary conditions. Application of the computed deformation field to align (i.e. register) the preoperative images with the intraoperative ones indicated that the model very accurately predicts the displacements of gravity centers of the lateral ventricles and tumor even for very limited information about the brain surface deformation. These results are sufficient to suggest that nonlinear biomechanical models can be regarded as one possible way of complementing medical image processing techniques when conducting nonrigid registration. Important advantage of such models over the linear ones is that they do not require unrealistic assumptions that brain deformations are infinitesimally small and brain tissue stress-strain relationship is linear.

Longitudinal Dynamics of 3-Dimensional Components of Selfhood After Severe Traumatic Brain Injury: A qEEG Case Study.

PubMed

Fingelkurts, Andrew A; Fingelkurts, Alexander A

2017-09-01

In this report, we describe the case of a patient who sustained extremely severe traumatic brain damage with diffuse axonal injury in a traffic accident and whose recovery was monitored during 6 years. Specifically, we were interested in the recovery dynamics of 3-dimensional components of selfhood (a 3-dimensional construct model for the complex experiential selfhood has been recently proposed based on the empirical findings on the functional-topographical specialization of 3 operational modules of brain functional network responsible for the self-consciousness processing) derived from the electroencephalographic (EEG) signal. The analysis revealed progressive (though not monotonous) restoration of EEG functional connectivity of 3 modules of brain functional network responsible for the self-consciousness processing, which was also paralleled by the clinically significant functional recovery. We propose that restoration of normal integrity of the operational modules of the self-referential brain network may underlie the positive dynamics of 3 aspects of selfhood and provide a neurobiological mechanism for their recovery. The results are discussed in the context of recent experimental studies that support this inference. Studies of ongoing recovery after severe brain injury utilizing knowledge about each separate aspect of complex selfhood will likely help to develop more efficient and targeted rehabilitation programs for patients with brain trauma.

Stereotactic radiosurgery of brain metastases.

PubMed

Specht, Hanno M; Combs, Stephanie E

2016-09-01

Brain metastases are a common problem in solid malignancies and still represent a major cause of morbidity and mortality. With the ongoing improvement in systemic therapies, the expectations on the efficacy of brain metastases directed treatment options are growing. As local therapies against brain metastases continue to evolve, treatment patterns have shifted from a palliative "one-treatment-fits-all" towards an individualized, patient adapted approach. In this article we review the evidence for stereotactic radiation treatment based on the current literature. Stereotactic radiosurgery (SRS) as a local high precision approach for the primary treatment of asymptomatic brain metastases has gained wide acceptance. It leads to lasting tumor control with only minor side effects compared to whole brain radiotherapy, since there is only little dose delivered to the healthy brain. The same holds true for hypofractionated stereotactic radiotherapy (HFSRT) for large metastases or for lesions close to organs at risk (e.g. the brainstem). New treatment indications such as neoadjuvant SRS followed by surgical resection or postoperative local therapy to the resection cavity show promising data and are also highlighted in this manuscript. With the evolution of local treatment options, optimal patient selection becomes more and more crucial. This article aims to aid decision making by outlining prognostic factors, treatment techniques and indications and common dose prescriptions.

Brain size and visual environment predict species differences in paper wasp sensory processing brain regions (hymenoptera: vespidae, polistinae).

PubMed

O'Donnell, Sean; Clifford, Marie R; DeLeon, Sara; Papa, Christopher; Zahedi, Nazaneen; Bulova, Susan J

2013-01-01

The mosaic brain evolution hypothesis predicts that the relative volumes of functionally distinct brain regions will vary independently and correlate with species' ecology. Paper wasp species (Hymenoptera: Vespidae, Polistinae) differ in light exposure: they construct open versus enclosed nests and one genus (Apoica) is nocturnal. We asked whether light environments were related to species differences in the size of antennal and optic processing brain tissues. Paper wasp brains have anatomically distinct peripheral and central regions that process antennal and optic sensory inputs. We measured the volumes of 4 sensory processing brain regions in paper wasp species from 13 Neotropical genera including open and enclosed nesters, and diurnal and nocturnal species. Species differed in sensory region volumes, but there was no evidence for trade-offs among sensory modalities. All sensory region volumes correlated with brain size. However, peripheral optic processing investment increased with brain size at a higher rate than peripheral antennal processing investment. Our data suggest that mosaic and concerted (size-constrained) brain evolution are not exclusive alternatives. When brain regions increase with brain size at different rates, these distinct allometries can allow for differential investment among sensory modalities. As predicted by mosaic evolution, species ecology was associated with some aspects of brain region investment. Nest architecture variation was not associated with brain investment differences, but the nocturnal genus Apoica had the largest antennal:optic volume ratio in its peripheral sensory lobes. Investment in central processing tissues was not related to nocturnality, a pattern also noted in mammals. The plasticity of neural connections in central regions may accommodate evolutionary shifts in input from the periphery with relatively minor changes in volume. © 2013 S. Karger AG, Basel.

Perceptually relevant speech tracking in auditory and motor cortex reflects distinct linguistic features

PubMed Central

Gross, Joachim; Kayser, Christoph

2018-01-01

During online speech processing, our brain tracks the acoustic fluctuations in speech at different timescales. Previous research has focused on generic timescales (for example, delta or theta bands) that are assumed to map onto linguistic features such as prosody or syllables. However, given the high intersubject variability in speaking patterns, such a generic association between the timescales of brain activity and speech properties can be ambiguous. Here, we analyse speech tracking in source-localised magnetoencephalographic data by directly focusing on timescales extracted from statistical regularities in our speech material. This revealed widespread significant tracking at the timescales of phrases (0.6–1.3 Hz), words (1.8–3 Hz), syllables (2.8–4.8 Hz), and phonemes (8–12.4 Hz). Importantly, when examining its perceptual relevance, we found stronger tracking for correctly comprehended trials in the left premotor (PM) cortex at the phrasal scale as well as in left middle temporal cortex at the word scale. Control analyses using generic bands confirmed that these effects were specific to the speech regularities in our stimuli. Furthermore, we found that the phase at the phrasal timescale coupled to power at beta frequency (13–30 Hz) in motor areas. This cross-frequency coupling presumably reflects top-down temporal prediction in ongoing speech perception. Together, our results reveal specific functional and perceptually relevant roles of distinct tracking and cross-frequency processes along the auditory–motor pathway. PMID:29529019

Increase in posterior alpha activity during rehearsal predicts successful long-term memory formation of word sequences.

PubMed

Meeuwissen, Esther B; Takashima, Atsuko; Fernández, Guillén; Jensen, Ole

2011-12-01

It is becoming increasingly clear that demanding cognitive tasks rely on an extended network engaging task-relevant areas and, importantly, disengaging task-irrelevant areas. Given that alpha activity (8-12 Hz) has been shown to reflect the disengagement of task-irrelevant regions in attention and working memory tasks, we here ask if alpha activity plays a related role for long-term memory formation. Subjects were instructed to encode and maintain the order of word sequences while the ongoing brain activity was recorded using magnetoencephalography (MEG). In each trial, three words were presented followed by a 3.4 s rehearsal interval. Considering the good temporal resolution of MEG this allowed us to investigate the word presentation and rehearsal interval separately. The sequences were grouped in trials where word order either could be tested immediately (working memory trials; WM) or later (LTM trials) according to instructions. Subjects were tested on their ability to retrieve the order of the three words. The data revealed that alpha power in parieto-occipital regions was lower during word presentation compared to rehearsal. Our key finding was that parieto-occipital alpha power during the rehearsal period was markedly stronger for successfully than unsuccessfully encoded LTM sequences. This subsequent memory effect demonstrates that high posterior alpha activity creates an optimal brain state for successful LTM formation possibly by actively reducing parieto-occipital activity that might interfere with sequence encoding. Copyright © 2010 Wiley Periodicals, Inc.

Targeting Brain Tumors with Nanomedicines: Overcoming Challenges of Blood Brain Barrier.

PubMed

Ningaraj, Nagendra S; Reddy, Polluru L; Khaitan, Divya

2018-04-12

This review elucidates ongoing research, which show improved delivery of anticancer drugs alone and/ or enclosed in carriers collectively called nanomedicines to cross the Blood brain barrier (BBB) / blood-brain tumor barrier (BTB) to kill tumor cells and impact patient survival. We highlighted various advances in understanding the mechanism of BTB function that impact on anticancer therapeutics delivery. We discussed latest breakthroughs in developing pharmaceutical strategies, including nanomedicines and delivering them across BTB for brain tumor management and treatment. We highlight various studies on regulation of BTB permeability regulation with respect to nanotech-based nanomedicines for targeted treatment of brain tumors. We have reviewed latest literature on development of specialized molecules and nanospheres for carrying pay load of anticancer agents to brain tumor cells across the BBB/ BTB and avoid drug efflux systems. We discuss identification and development of distinctive BTB biomarkers for targeted anti-cancer drug delivery to brain tumors. In addition, we discussed nanomedicines and multimeric molecular therapeutics that were encapsulated in nanospheres for treatment and monitoring of brain tumors. In this context, we highlight our research on calcium-activated potassium channels (KCa) and ATP-sensitive potassium channels (KATP) as portals of enhanced antineoplastic drugs delivery. This review might interest both academic and drug company scientists involved in drug delivery to brain tumors. We further seek to present evidence that BTB modulators can be clinically developed as combination drug or/ and as stand-alone anticancer drugs. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Comprehension of Idioms in Turkish Aphasic Participants.

PubMed

Aydin, Burcu; Barin, Muzaffer; Yagiz, Oktay

2017-12-01

Brain damaged participants offer an opportunity to evaluate the cognitive and linguistic processes and make assumptions about how the brain works. Cognitive linguists have been investigating the underlying mechanisms of idiom comprehension to unravel the ongoing debate on hemispheric specialization in figurative language comprehension. The aim of this study is to evaluate and compare the comprehension of idiomatic expressions in left brain damaged (LBD) aphasic, right brain damaged (RBD) and healthy control participants. Idiom comprehension in eleven LBD aphasic participants, ten RBD participants and eleven healthy control participants were assessed with three tasks: String to Picture Matching Task, Literal Sentence Comprehension Task and Oral Idiom Definition Task. The results of the tasks showed that in overall idiom comprehension category, the left brain-damaged aphasic participants interpret idioms more literally compared to right brain-damaged participants. What is more, there is a significant difference in opaque idiom comprehension implying that left brain-damaged aphasic participants perform worse compared to right brain-damaged participants. On the other hand, there is no statistically significant difference in scores of transparent idiom comprehension between the left brain-damaged aphasic and right brain-damaged participants. This result also contribute to the idea that while figurative processing system is damaged in LBD aphasics, the literal comprehension mechanism is spared to some extent. The results of this study support the view that idiom comprehension sites are mainly left lateralized. Furthermore, the results of this study are in consistence with the Giora's Graded Salience Hypothesis.

Prevalence of Brain Injuries among Children with Special Healthcare Needs.

PubMed

Lebrun-Harris, Lydie A; Parasuraman, Sarika Rane; Desrocher, Rebecca

2018-06-06

To investigate differences in brain injury prevalence among US children by special healthcare needs status, accounting for sociodemographic and family characteristics, and to examine correlated health conditions among children with special healthcare needs (CSHCN). We conducted cross-sectional analyses using parent/caregiver responses to the 2016 National Survey of Children's Health (n = 50 212 children). CSHCN status was based on responses to a 5-item tool designed to identify children through assessment of functional limitations, prescription medication use, elevated service use or need, use of specialized therapies, and ongoing emotional, developmental, or behavioral conditions. Brain injury history was reported by parents/caregivers based on healthcare provider diagnosis. Bivariate and multivariable analyses were conducted. Lifetime history of brain injury was significantly higher among CSHCN than non-CSHCN (6.7% vs 2.3%, P < .001). CSHCN make up 19% of the total US child population but comprise 42% of children with lifetime brain injuries. In addition, the prevalence of a number of comorbid conditions and functional limitations was significantly higher among CSHCN with lifetime brain injury vs those without brain injury. The prevalence of lifetime history of brain injury is nearly 3 times greater among CSHCN than among non-CSHCN. Several comorbid conditions among CSHCN are significantly associated with lifetime history of brain injury. Further studies are needed to examine the extent to which brain injury in CSHCN may exacerbate or be misdiagnosed as other comorbid conditions. Published by Elsevier Inc.

Label-free imaging of brain and brain tumor specimens with combined two-photon excited fluorescence and second harmonic generation microscopy

NASA Astrophysics Data System (ADS)

Jiang, Liwei; Wang, Xingfu; Wu, Zanyi; Du, Huiping; Wang, Shu; Li, Lianhuang; Fang, Na; Lin, Peihua; Chen, Jianxin; Kang, Dezhi; Zhuo, Shuangmu

2017-10-01

Label-free imaging techniques are gaining acceptance within the medical imaging field, including brain imaging, because they have the potential to be applied to intraoperative in situ identifications of pathological conditions. In this paper, we describe the use of two-photon excited fluorescence (TPEF) and second harmonic generation (SHG) microscopy in combination for the label-free detection of brain and brain tumor specimens; gliomas. Two independently detecting channels were chosen to subsequently collect TPEF/SHG signals from the specimen to increase TPEF/SHG image contrasts. Our results indicate that the combined TPEF/SHG microscopic techniques can provide similar rat brain structural information and produce a similar resolution like conventional H&E staining in neuropathology; including meninges, cerebral cortex, white-matter structure corpus callosum, choroid plexus, hippocampus, striatum, and cerebellar cortex. It can simultaneously detect infiltrating human brain tumor cells, the extracellular matrix collagen fiber of connective stroma within brain vessels and collagen depostion in tumor microenvironments. The nuclear-to-cytoplasmic ratio and collagen content can be extracted as quantitative indicators for differentiating brain gliomas from healthy brain tissues. With the development of two-photon fiberscopes and microendoscope probes and their clinical applications, the combined TPEF and SHG microcopy may become an important multimodal, nonlinear optical imaging approach for real-time intraoperative histological diagnostics of residual brain tumors. These occur in various brain regions during ongoing surgeries through the method of simultaneously identifying tumor cells, and the change of tumor microenvironments, without the need for the removal biopsies and without the need for tissue labelling or fluorescent markers.

Neural Correlates of Semantic Prediction and Resolution in Sentence Processing.

PubMed

Grisoni, Luigi; Miller, Tally McCormick; Pulvermüller, Friedemann

2017-05-03

Most brain-imaging studies of language comprehension focus on activity following meaningful stimuli. Testing adult human participants with high-density EEG, we show that, already before the presentation of a critical word, context-induced semantic predictions are reflected by a neurophysiological index, which we therefore call the semantic readiness potential (SRP). The SRP precedes critical words if a previous sentence context constrains the upcoming semantic content (high-constraint contexts), but not in unpredictable (low-constraint) contexts. Specific semantic predictions were indexed by SRP sources within the motor system-in dorsolateral hand motor areas for expected hand-related words (e.g., "write"), but in ventral motor cortex for face-related words ("talk"). Compared with affirmative sentences, negated ones led to medial prefrontal and more widespread motor source activation, the latter being consistent with predictive semantic computation of alternatives to the negated expected concept. Predictive processing of semantic alternatives in negated sentences is further supported by a negative-going event-related potential at ∼400 ms (N400), which showed the typical enhancement to semantically incongruent sentence endings only in high-constraint affirmative contexts, but not to high-constraint negated ones. These brain dynamics reveal the interplay between semantic prediction and resolution (match vs error) processing in sentence understanding. SIGNIFICANCE STATEMENT Most neuroscientists agree on the eminent importance of predictive mechanisms for understanding basic as well as higher brain functions. This contrasts with a sparseness of brain measures that directly reflects specific aspects of prediction, as they are relevant in the processing of language and thought. Here we show that when critical words are strongly expected in their sentence context, a predictive brain response reflects meaning features of these anticipated symbols already before they appear. The granularity of the semantic predictions was so fine grained that the cortical sources in sensorimotor and medial prefrontal cortex even distinguished between predicted face- or hand-related action words (e.g., the words "lick" or "pick") and between affirmative and negated sentence meanings. Copyright © 2017 Grisoni et al.

Neural Correlates of Semantic Prediction and Resolution in Sentence Processing

PubMed Central

2017-01-01

Most brain-imaging studies of language comprehension focus on activity following meaningful stimuli. Testing adult human participants with high-density EEG, we show that, already before the presentation of a critical word, context-induced semantic predictions are reflected by a neurophysiological index, which we therefore call the semantic readiness potential (SRP). The SRP precedes critical words if a previous sentence context constrains the upcoming semantic content (high-constraint contexts), but not in unpredictable (low-constraint) contexts. Specific semantic predictions were indexed by SRP sources within the motor system—in dorsolateral hand motor areas for expected hand-related words (e.g., “write”), but in ventral motor cortex for face-related words (“talk”). Compared with affirmative sentences, negated ones led to medial prefrontal and more widespread motor source activation, the latter being consistent with predictive semantic computation of alternatives to the negated expected concept. Predictive processing of semantic alternatives in negated sentences is further supported by a negative-going event-related potential at ∼400 ms (N400), which showed the typical enhancement to semantically incongruent sentence endings only in high-constraint affirmative contexts, but not to high-constraint negated ones. These brain dynamics reveal the interplay between semantic prediction and resolution (match vs error) processing in sentence understanding. SIGNIFICANCE STATEMENT Most neuroscientists agree on the eminent importance of predictive mechanisms for understanding basic as well as higher brain functions. This contrasts with a sparseness of brain measures that directly reflects specific aspects of prediction, as they are relevant in the processing of language and thought. Here we show that when critical words are strongly expected in their sentence context, a predictive brain response reflects meaning features of these anticipated symbols already before they appear. The granularity of the semantic predictions was so fine grained that the cortical sources in sensorimotor and medial prefrontal cortex even distinguished between predicted face- or hand-related action words (e.g., the words “lick” or “pick”) and between affirmative and negated sentence meanings. PMID:28411271

Neural underpinnings of music: the polyrhythmic brain.

PubMed

Vuust, Peter; Gebauer, Line K; Witek, Maria A G

2014-01-01

Musical rhythm, consisting of apparently abstract intervals of accented temporal events, has the remarkable ability to move our minds and bodies. Why do certain rhythms make us want to tap our feet, bop our heads or even get up and dance? And how does the brain process rhythmically complex rhythms during our experiences of music? In this chapter, we describe some common forms of rhythmic complexity in music and propose that the theory of predictive coding can explain how rhythm and rhythmic complexity are processed in the brain. We also consider how this theory may reveal why we feel so compelled by rhythmic tension in music. First, musical-theoretical and neuroscientific frameworks of rhythm are presented, in which rhythm perception is conceptualized as an interaction between what is heard ('rhythm') and the brain's anticipatory structuring of music ('the meter'). Second, three different examples of tension between rhythm and meter in music are described: syncopation, polyrhythm and groove. Third, we present the theory of predictive coding of music, which posits a hierarchical organization of brain responses reflecting fundamental, survival-related mechanisms associated with predicting future events. According to this theory, perception and learning is manifested through the brain's Bayesian minimization of the error between the input to the brain and the brain's prior expectations. Fourth, empirical studies of neural and behavioral effects of syncopation, polyrhythm and groove will be reported, and we propose how these studies can be seen as special cases of the predictive coding theory. Finally, we argue that musical rhythm exploits the brain's general principles of anticipation and propose that pleasure from musical rhythm may be a result of such anticipatory mechanisms.

Serum neurofilament as a predictor of disease worsening and brain and spinal cord atrophy in multiple sclerosis.

PubMed

Barro, Christian; Benkert, Pascal; Disanto, Giulio; Tsagkas, Charidimos; Amann, Michael; Naegelin, Yvonne; Leppert, David; Gobbi, Claudio; Granziera, Cristina; Yaldizli, Özgür; Michalak, Zuzanna; Wuerfel, Jens; Kappos, Ludwig; Parmar, Katrin; Kuhle, Jens

2018-05-30

Neuro-axonal injury is a key factor in the development of permanent disability in multiple sclerosis. Neurofilament light chain in peripheral blood has recently emerged as a biofluid marker reflecting neuro-axonal damage in this disease. We aimed at comparing serum neurofilament light chain levels in multiple sclerosis and healthy controls, to determine their association with measures of disease activity and their ability to predict future clinical worsening as well as brain and spinal cord volume loss. Neurofilament light chain was measured by single molecule array assay in 2183 serum samples collected as part of an ongoing cohort study from 259 patients with multiple sclerosis (189 relapsing and 70 progressive) and 259 healthy control subjects. Clinical assessment, serum sampling and MRI were done annually; median follow-up time was 6.5 years. Brain volumes were quantified by structural image evaluation using normalization of atrophy, and structural image evaluation using normalization of atrophy, cross-sectional, cervical spinal cord volumes using spinal cord image analyser (cordial). Results were analysed using ordinary linear regression models and generalized estimating equation modelling. Serum neurofilament light chain was higher in patients with a clinically isolated syndrome or relapsing remitting multiple sclerosis as well as in patients with secondary or primary progressive multiple sclerosis than in healthy controls (age adjusted P < 0.001 for both). Serum neurofilament light chain above the 90th percentile of healthy controls values was an independent predictor of Expanded Disability Status Scale worsening in the subsequent year (P < 0.001). The probability of Expanded Disability Status Scale worsening gradually increased by higher serum neurofilament light chain percentile category. Contrast enhancing and new/enlarging lesions were independently associated with increased serum neurofilament light chain (17.8% and 4.9% increase per lesion respectively; P < 0.001). The higher the serum neurofilament light chain percentile level, the more pronounced was future brain and cervical spinal volume loss: serum neurofilament light chain above the 97.5th percentile was associated with an additional average loss in brain volume of 1.5% (P < 0.001) and spinal cord volume of 2.5% over 5 years (P = 0.009). Serum neurofilament light chain correlated with concurrent and future clinical and MRI measures of disease activity and severity. High serum neurofilament light chain levels were associated with both brain and spinal cord volume loss. Neurofilament light chain levels are a real-time, easy to measure marker of neuro-axonal injury that is conceptually more comprehensive than brain MRI.

Milieu matters: Evidence that ongoing lifestyle activities influence health behaviors

PubMed Central

Lowe, Rob; Norman, Paul

2017-01-01

Health behaviors occur within a milieu of lifestyle activities that could conflict with health actions. We examined whether cognitions about, and performance of, other lifestyle activities augment the prediction of health behaviors, and whether these lifestyle factors are especially influential among individuals with low health behavior engagement. Participants (N = 211) completed measures of past behavior and cognitions relating to five health behaviors (e.g., smoking, getting drunk) and 23 lifestyle activities (e.g., reading, socializing), as well as personality variables. All behaviors were measured again at two weeks. Data were analyzed using neural network and cluster analyses. The neural network accurately predicted health behaviors at follow-up (R2 = .71). As hypothesized, lifestyle cognitions and activities independently predicted health behaviors over and above behavior-specific cognitions and previous behavior. Additionally, lifestyle activities and poor self-regulatory capability were more influential among people exhibiting unhealthy behaviors. Considering ongoing lifestyle activities can enhance prediction and understanding of health behaviors and offer new targets for health behavior interventions. PMID:28662120

Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion.

PubMed

Zafar, Raheel; Dass, Sarat C; Malik, Aamir Saeed

2017-01-01

Electroencephalogram (EEG)-based decoding human brain activity is challenging, owing to the low spatial resolution of EEG. However, EEG is an important technique, especially for brain-computer interface applications. In this study, a novel algorithm is proposed to decode brain activity associated with different types of images. In this hybrid algorithm, convolutional neural network is modified for the extraction of features, a t-test is used for the selection of significant features and likelihood ratio-based score fusion is used for the prediction of brain activity. The proposed algorithm takes input data from multichannel EEG time-series, which is also known as multivariate pattern analysis. Comprehensive analysis was conducted using data from 30 participants. The results from the proposed method are compared with current recognized feature extraction and classification/prediction techniques. The wavelet transform-support vector machine method is the most popular currently used feature extraction and prediction method. This method showed an accuracy of 65.7%. However, the proposed method predicts the novel data with improved accuracy of 79.9%. In conclusion, the proposed algorithm outperformed the current feature extraction and prediction method.

Radiation-induced brain structural and functional abnormalities in presymptomatic phase and outcome prediction.

PubMed

Ding, Zhongxiang; Zhang, Han; Lv, Xiao-Fei; Xie, Fei; Liu, Lizhi; Qiu, Shijun; Li, Li; Shen, Dinggang

2018-01-01

Radiation therapy, a major method of treatment for brain cancer, may cause severe brain injuries after many years. We used a rare and unique cohort of nasopharyngeal carcinoma patients with normal-appearing brains to study possible early irradiation injury in its presymptomatic phase before severe, irreversible necrosis happens. The aim is to detect any structural or functional imaging biomarker that is sensitive to early irradiation injury, and to understand the recovery and progression of irradiation injury that can shed light on outcome prediction for early clinical intervention. We found an acute increase in local brain activity that is followed by extensive reductions in such activity in the temporal lobe and significant loss of functional connectivity in a distributed, large-scale, high-level cognitive function-related brain network. Intriguingly, these radiosensitive functional alterations were found to be fully or partially recoverable. In contrast, progressive late disruptions to the integrity of the related far-end white matter structure began to be significant after one year. Importantly, early increased local brain functional activity was predictive of severe later temporal lobe necrosis. Based on these findings, we proposed a dynamic, multifactorial model for radiation injury and another preventive model for timely clinical intervention. Hum Brain Mapp 39:407-427, 2018. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Sparse network-based models for patient classification using fMRI

PubMed Central

Rosa, Maria J.; Portugal, Liana; Hahn, Tim; Fallgatter, Andreas J.; Garrido, Marta I.; Shawe-Taylor, John; Mourao-Miranda, Janaina

2015-01-01

Pattern recognition applied to whole-brain neuroimaging data, such as functional Magnetic Resonance Imaging (fMRI), has proved successful at discriminating psychiatric patients from healthy participants. However, predictive patterns obtained from whole-brain voxel-based features are difficult to interpret in terms of the underlying neurobiology. Many psychiatric disorders, such as depression and schizophrenia, are thought to be brain connectivity disorders. Therefore, pattern recognition based on network models might provide deeper insights and potentially more powerful predictions than whole-brain voxel-based approaches. Here, we build a novel sparse network-based discriminative modeling framework, based on Gaussian graphical models and L1-norm regularized linear Support Vector Machines (SVM). In addition, the proposed framework is optimized in terms of both predictive power and reproducibility/stability of the patterns. Our approach aims to provide better pattern interpretation than voxel-based whole-brain approaches by yielding stable brain connectivity patterns that underlie discriminative changes in brain function between the groups. We illustrate our technique by classifying patients with major depressive disorder (MDD) and healthy participants, in two (event- and block-related) fMRI datasets acquired while participants performed a gender discrimination and emotional task, respectively, during the visualization of emotional valent faces. PMID:25463459

A scalable population code for time in the striatum.

PubMed

Mello, Gustavo B M; Soares, Sofia; Paton, Joseph J

2015-05-04

To guide behavior and learn from its consequences, the brain must represent time over many scales. Yet, the neural signals used to encode time in the seconds-to-minute range are not known. The striatum is a major input area of the basal ganglia associated with learning and motor function. Previous studies have also shown that the striatum is necessary for normal timing behavior. To address how striatal signals might be involved in timing, we recorded from striatal neurons in rats performing an interval timing task. We found that neurons fired at delays spanning tens of seconds and that this pattern of responding reflected the interaction between time and the animals' ongoing sensorimotor state. Surprisingly, cells rescaled responses in time when intervals changed, indicating that striatal populations encoded relative time. Moreover, time estimates decoded from activity predicted timing behavior as animals adjusted to new intervals, and disrupting striatal function led to a decrease in timing performance. These results suggest that striatal activity forms a scalable population code for time, providing timing signals that animals use to guide their actions. Copyright © 2015 Elsevier Ltd. All rights reserved.

Progranulin as a therapeutic target for dementia.

PubMed

Galimberti, Daniela; Fenoglio, Chiara; Scarpini, Elio

2018-06-22

Progranulin (PGRN) is an acrosomal glycoprotein that is synthesized during spermatogenesis. It is overexpressed in tumors and has anti-inflammatory properties. The protein may be cleaved into granulins which display pro-inflammatory properties. In 2006, mutations in progranulin gene (GRN) that cause haploinsufficiency were found in familial cases of frontotemporal dementia (FTD). Patients with null mutations in GRN display very low-plasma PGRN levels; this analysis is useful for identifying mutation carriers, independent of the clinical presentation, and in those before the appearance of symptoms. Areas covered: Here, we review the current knowledge of PGRN physiological functions and GRN mutations associated with FTD; we also summarize state of the art clinical trials and those compounds able to replace PGRN loss in preclinical models. Expert opinion: PGRN represents a promising therapeutic target for FTD. Cohorts suitable for treatment, ideally at the preclinical stage, where pathogenic mechanisms ongoing in the brain are targeted, are available. However, PGRN may have side effects, such as the risk of tumorigenesis, and the risk/benefit ratio of any intervention cannot be predicted. Furthermore, at present, the situation is complicated by the absence of adequate outcome measures.

The sensory side of post-stroke motor rehabilitation.

PubMed

Bolognini, Nadia; Russo, Cristina; Edwards, Dylan J

2016-04-11

Contemporary strategies to promote motor recovery following stroke focus on repetitive voluntary movements. Although successful movement relies on efficient sensorimotor integration, functional outcomes often bias motor therapy toward motor-related impairments such as weakness, spasticity and synergies; sensory therapy and reintegration is implied, but seldom targeted. However, the planning and execution of voluntary movement requires that the brain extracts sensory information regarding body position and predicts future positions, by integrating a variety of sensory inputs with ongoing and planned motor activity. Neurological patients who have lost one or more of their senses may show profoundly affected motor functions, even if muscle strength remains unaffected. Following stroke, motor recovery can be dictated by the degree of sensory disruption. Consequently, a thorough account of sensory function might be both prognostic and prescriptive in neurorehabilitation. This review outlines the key sensory components of human voluntary movement, describes how sensory disruption can influence prognosis and expected outcomes in stroke patients, reports on current sensory-based approaches in post-stroke motor rehabilitation, and makes recommendations for optimizing rehabilitation programs based on sensory stimulation.

The sensory side of post-stroke motor rehabilitation

PubMed Central

Bolognini, Nadia; Russo, Cristina; Edwards, Dylan J.

2017-01-01

Contemporary strategies to promote motor recovery following stroke focus on repetitive voluntary movements. Although successful movement relies on efficient sensorimotor integration, functional outcomes often bias motor therapy toward motor-related impairments such as weakness, spasticity and synergies; sensory therapy and reintegration is implied, but seldom targeted. However, the planning and execution of voluntary movement requires that the brain extracts sensory information regarding body position and predicts future positions, by integrating a variety of sensory inputs with ongoing and planned motor activity. Neurological patients who have lost one or more of their senses may show profoundly affected motor functions, even if muscle strength remains unaffected. Following stroke, motor recovery can be dictated by the degree of sensory disruption. Consequently, a thorough account of sensory function might be both prognostic and prescriptive in neurorehabilitation. This review outlines the key sensory components of human voluntary movement, describes how sensory disruption can influence prognosis and expected outcomes in stroke patients, reports on current sensory-based approaches in post-stroke motor rehabilitation, and makes recommendations for optimizing rehabilitation programs based on sensory stimulation. PMID:27080070

Global Neuromagnetic Cortical Fields Have Non-Zero Velocity

PubMed Central

Alexander, David M.; Nikolaev, Andrey R.; Jurica, Peter; Zvyagintsev, Mikhail; Mathiak, Klaus; van Leeuwen, Cees

2016-01-01

Globally coherent patterns of phase can be obscured by analysis techniques that aggregate brain activity measures across-trials, whether prior to source localization or for estimating inter-areal coherence. We analyzed, at single-trial level, whole head MEG recorded during an observer-triggered apparent motion task. Episodes of globally coherent activity occurred in the delta, theta, alpha and beta bands of the signal in the form of large-scale waves, which propagated with a variety of velocities. Their mean speed at each frequency band was proportional to temporal frequency, giving a range of 0.06 to 4.0 m/s, from delta to beta. The wave peaks moved over the entire measurement array, during both ongoing activity and task-relevant intervals; direction of motion was more predictable during the latter. A large proportion of the cortical signal, measurable at the scalp, exists as large-scale coherent motion. We argue that the distribution of observable phase velocities in MEG is dominated by spatial filtering considerations in combination with group velocity of cortical activity. Traveling waves may index processes involved in global coordination of cortical activity. PMID:26953886

Prediction of brain maturity based on cortical thickness at different spatial resolutions.

PubMed

Khundrakpam, Budhachandra S; Tohka, Jussi; Evans, Alan C

2015-05-01

Several studies using magnetic resonance imaging (MRI) scans have shown developmental trajectories of cortical thickness. Cognitive milestones happen concurrently with these structural changes, and a delay in such changes has been implicated in developmental disorders such as attention-deficit/hyperactivity disorder (ADHD). Accurate estimation of individuals' brain maturity, therefore, is critical in establishing a baseline for normal brain development against which neurodevelopmental disorders can be assessed. In this study, cortical thickness derived from structural magnetic resonance imaging (MRI) scans of a large longitudinal dataset of normally growing children and adolescents (n=308), were used to build a highly accurate predictive model for estimating chronological age (cross-validated correlation up to R=0.84). Unlike previous studies which used kernelized approach in building prediction models, we used an elastic net penalized linear regression model capable of producing a spatially sparse, yet accurate predictive model of chronological age. Upon investigating different scales of cortical parcellation from 78 to 10,240 brain parcels, we observed that the accuracy in estimated age improved with increased spatial scale of brain parcellation, with the best estimations obtained for spatial resolutions consisting of 2560 and 10,240 brain parcels. The top predictors of brain maturity were found in highly localized sensorimotor and association areas. The results of our study demonstrate that cortical thickness can be used to estimate individuals' brain maturity with high accuracy, and the estimated ages relate to functional and behavioural measures, underscoring the relevance and scope of the study in the understanding of biological maturity. Copyright © 2015 Elsevier Inc. All rights reserved.

Multimodal neuroimaging of male and female brain structure in health and disease across the life span.

PubMed

Jahanshad, Neda; Thompson, Paul M

2017-01-02

Sex differences in brain development and aging are important to identify, as they may help to understand risk factors and outcomes in brain disorders that are more prevalent in one sex compared with the other. Brain imaging techniques have advanced rapidly in recent years, yielding detailed structural and functional maps of the living brain. Even so, studies are often limited in sample size, and inconsistent findings emerge, one example being varying findings regarding sex differences in the size of the corpus callosum. More recently, large-scale neuroimaging consortia such as the Enhancing Neuro Imaging Genetics through Meta Analysis Consortium have formed, pooling together expertise, data, and resources from hundreds of institutions around the world to ensure adequate power and reproducibility. These initiatives are helping us to better understand how brain structure is affected by development, disease, and potential modulators of these effects, including sex. This review highlights some established and disputed sex differences in brain structure across the life span, as well as pitfalls related to interpreting sex differences in health and disease. We also describe sex-related findings from the ENIGMA consortium, and ongoing efforts to better understand sex differences in brain circuitry. © 2016 The Authors. Journal of Neuroscience Research Published by Wiley Periodicals, Inc. © 2016 The Authors. Journal of Neuroscience Research Published by Wiley Periodicals, Inc.

Short-Term Memory: The "Storage" Component of Human Brain Responses Predicts Recall.

ERIC Educational Resources Information Center

Chapman, Robert M.; And Others

1978-01-01

Presents electrophysiological and behavioral evidence for a neural process related to storage in short-term memory. Predicting recall performance on the basis of the storage component of brain responses is presented. A list of references is also included. (HM)

Learning Temporal Statistics for Sensory Predictions in Aging.

PubMed

Luft, Caroline Di Bernardi; Baker, Rosalind; Goldstone, Aimee; Zhang, Yang; Kourtzi, Zoe

2016-03-01

Predicting future events based on previous knowledge about the environment is critical for successful everyday interactions. Here, we ask which brain regions support our ability to predict the future based on implicit knowledge about the past in young and older age. Combining behavioral and fMRI measurements, we test whether training on structured temporal sequences improves the ability to predict upcoming sensory events; we then compare brain regions involved in learning predictive structures between young and older adults. Our behavioral results demonstrate that exposure to temporal sequences without feedback facilitates the ability of young and older adults to predict the orientation of an upcoming stimulus. Our fMRI results provide evidence for the involvement of corticostriatal regions in learning predictive structures in both young and older learners. In particular, we showed learning-dependent fMRI responses for structured sequences in frontoparietal regions and the striatum (putamen) for young adults. However, for older adults, learning-dependent activations were observed mainly in subcortical (putamen, thalamus) regions but were weaker in frontoparietal regions. Significant correlations of learning-dependent behavioral and fMRI changes in these regions suggest a strong link between brain activations and behavioral improvement rather than general overactivation. Thus, our findings suggest that predicting future events based on knowledge of temporal statistics engages brain regions involved in implicit learning in both young and older adults.

Predictive probability methods for interim monitoring in clinical trials with longitudinal outcomes.

PubMed

Zhou, Ming; Tang, Qi; Lang, Lixin; Xing, Jun; Tatsuoka, Kay

2018-04-17

In clinical research and development, interim monitoring is critical for better decision-making and minimizing the risk of exposing patients to possible ineffective therapies. For interim futility or efficacy monitoring, predictive probability methods are widely adopted in practice. Those methods have been well studied for univariate variables. However, for longitudinal studies, predictive probability methods using univariate information from only completers may not be most efficient, and data from on-going subjects can be utilized to improve efficiency. On the other hand, leveraging information from on-going subjects could allow an interim analysis to be potentially conducted once a sufficient number of subjects reach an earlier time point. For longitudinal outcomes, we derive closed-form formulas for predictive probabilities, including Bayesian predictive probability, predictive power, and conditional power and also give closed-form solutions for predictive probability of success in a future trial and the predictive probability of success of the best dose. When predictive probabilities are used for interim monitoring, we study their distributions and discuss their analytical cutoff values or stopping boundaries that have desired operating characteristics. We show that predictive probabilities utilizing all longitudinal information are more efficient for interim monitoring than that using information from completers only. To illustrate their practical application for longitudinal data, we analyze 2 real data examples from clinical trials. Copyright © 2018 John Wiley & Sons, Ltd.

Association of Elevated Reward Prediction Error Response With Weight Gain in Adolescent Anorexia Nervosa.

PubMed

DeGuzman, Marisa; Shott, Megan E; Yang, Tony T; Riederer, Justin; Frank, Guido K W

2017-06-01

Anorexia nervosa is a psychiatric disorder of unknown etiology. Understanding associations between behavior and neurobiology is important in treatment development. Using a novel monetary reward task during functional magnetic resonance brain imaging, the authors tested how brain reward learning in adolescent anorexia nervosa changes with weight restoration. Female adolescents with anorexia nervosa (N=21; mean age, 16.4 years [SD=1.9]) underwent functional MRI (fMRI) before and after treatment; similarly, healthy female control adolescents (N=21; mean age, 15.2 years [SD=2.4]) underwent fMRI on two occasions. Brain function was tested using the reward prediction error construct, a computational model for reward receipt and omission related to motivation and neural dopamine responsiveness. Compared with the control group, the anorexia nervosa group exhibited greater brain response 1) for prediction error regression within the caudate, ventral caudate/nucleus accumbens, and anterior and posterior insula, 2) to unexpected reward receipt in the anterior and posterior insula, and 3) to unexpected reward omission in the caudate body. Prediction error and unexpected reward omission response tended to normalize with treatment, while unexpected reward receipt response remained significantly elevated. Greater caudate prediction error response when underweight was associated with lower weight gain during treatment. Punishment sensitivity correlated positively with ventral caudate prediction error response. Reward system responsiveness is elevated in adolescent anorexia nervosa when underweight and after weight restoration. Heightened prediction error activity in brain reward regions may represent a phenotype of adolescent anorexia nervosa that does not respond well to treatment. Prediction error response could be a neurobiological marker of illness severity that can indicate individual treatment needs.

Association of Elevated Reward Prediction Error Response With Weight Gain in Adolescent Anorexia Nervosa

PubMed Central

DeGuzman, Marisa; Shott, Megan E.; Yang, Tony T.; Riederer, Justin; Frank, Guido K.W.

2017-01-01

Objective Anorexia nervosa is a psychiatric disorder of unknown etiology. Understanding associations between behavior and neurobiology is important in treatment development. Using a novel monetary reward task during functional magnetic resonance brain imaging, the authors tested how brain reward learning in adolescent anorexia nervosa changes with weight restoration. Method Female adolescents with anorexia nervosa (N=21; mean age, 15.2 years [SD=2.4]) underwent functional MRI (fMRI) before and after treatment; similarly, healthy female control adolescents (N=21; mean age, 16.4 years [SD=1.9]) underwent fMRI on two occasions. Brain function was tested using the reward prediction error construct, a computational model for reward receipt and omission related to motivation and neural dopamine responsiveness. Results Compared with the control group, the anorexia nervosa group exhibited greater brain response 1) for prediction error regression within the caudate, ventral caudate/nucleus accumbens, and anterior and posterior insula, 2) to unexpected reward receipt in the anterior and posterior insula, and 3) to unexpected reward omission in the caudate body. Prediction error and unexpected reward omission response tended to normalize with treatment, while unexpected reward receipt response remained significantly elevated. Greater caudate prediction error response when underweight was associated with lower weight gain during treatment. Punishment sensitivity correlated positively with ventral caudate prediction error response. Conclusions Reward system responsiveness is elevated in adolescent anorexia nervosa when underweight and after weight restoration. Heightened prediction error activity in brain reward regions may represent a phenotype of adolescent anorexia nervosa that does not respond well to treatment. Prediction error response could be a neurobiological marker of illness severity that can indicate individual treatment needs. PMID:28231717

Initial Validation for the Estimation of Resting-State fMRI Effective Connectivity by a Generalization of the Correlation Approach.

PubMed

Xu, Nan; Spreng, R Nathan; Doerschuk, Peter C

2017-01-01

Resting-state functional MRI (rs-fMRI) is widely used to noninvasively study human brain networks. Network functional connectivity is often estimated by calculating the timeseries correlation between blood-oxygen-level dependent (BOLD) signal from different regions of interest (ROIs). However, standard correlation cannot characterize the direction of information flow between regions. In this paper, we introduce and test a new concept, prediction correlation, to estimate effective connectivity in functional brain networks from rs-fMRI. In this approach, the correlation between two BOLD signals is replaced by a correlation between one BOLD signal and a prediction of this signal via a causal system driven by another BOLD signal. Three validations are described: (1) Prediction correlation performed well on simulated data where the ground truth was known, and outperformed four other methods. (2) On simulated data designed to display the "common driver" problem, prediction correlation did not introduce false connections between non-interacting driven ROIs. (3) On experimental data, prediction correlation recovered the previously identified network organization of human brain. Prediction correlation scales well to work with hundreds of ROIs, enabling it to assess whole brain interregional connectivity at the single subject level. These results provide an initial validation that prediction correlation can capture the direction of information flow and estimate the duration of extended temporal delays in information flow between regions of interest ROIs based on BOLD signal. This approach not only maintains the high sensitivity to network connectivity provided by the correlation analysis, but also performs well in the estimation of causal information flow in the brain.

Gray Matter-White Matter De-Differentiation on Brain Computed Tomography Predicts Brain Death Occurrence.

PubMed

Vigneron, C; Labeye, V; Cour, M; Hannoun, S; Grember, A; Rampon, F; Cotton, F

2016-01-01

Previous studies have shown that a loss of distinction between gray matter (GM) and white matter (WM) on unenhanced CT scans was predictive of poor outcome after cardiac arrest. The aim of this study was to identify a marker/predictor of imminent brain death. In this retrospective study, 15 brain-dead patients after anoxia and cardiac arrest were included. Patients were paired (1:1) with normal control subjects. Only patients' unenhanced CT scans performed before brain death and during the 24 hours after initial signs were analyzed. WM and GM densities were measured in predefined regions of interest (basal ganglia level, centrum semi-ovale level, high convexity level, brainstem level). At each level, GM and WM density and GM/WM ratio for brain-dead patients and normal control subjects were compared using the Wilcoxon signed-rank test. At each level, a lower GM/WM ratio and decreased GM and WM densities were observed in brain-dead patients' CT scans when compared with normal control subject CT scans. A cut-off value of 1.21 at the basal ganglia level was identified, below which brain death systematically occurred. GM/WM dedifferentiation on unenhanced CT scan is measurable before the occurrence of brain death, highlighting its importance in brain death prediction. The mechanism of GM/WM differentiation loss could be explained by the lack of oxygen caused by ischemia initially affecting the mitochondrial system. Copyright © 2016 Elsevier Inc. All rights reserved.

Can Bayesian Theories of Autism Spectrum Disorder Help Improve Clinical Practice?

PubMed

Haker, Helene; Schneebeli, Maya; Stephan, Klaas Enno

2016-01-01

Diagnosis and individualized treatment of autism spectrum disorder (ASD) represent major problems for contemporary psychiatry. Tackling these problems requires guidance by a pathophysiological theory. In this paper, we consider recent theories that re-conceptualize ASD from a "Bayesian brain" perspective, which posit that the core abnormality of ASD resides in perceptual aberrations due to a disbalance in the precision of prediction errors (sensory noise) relative to the precision of predictions (prior beliefs). This results in percepts that are dominated by sensory inputs and less guided by top-down regularization and shifts the perceptual focus to detailed aspects of the environment with difficulties in extracting meaning. While these Bayesian theories have inspired ongoing empirical studies, their clinical implications have not yet been carved out. Here, we consider how this Bayesian perspective on disease mechanisms in ASD might contribute to improving clinical care for affected individuals. Specifically, we describe a computational strategy, based on generative (e.g., hierarchical Bayesian) models of behavioral and functional neuroimaging data, for establishing diagnostic tests. These tests could provide estimates of specific cognitive processes underlying ASD and delineate pathophysiological mechanisms with concrete treatment targets. Written with a clinical audience in mind, this article outlines how the development of computational diagnostics applicable to behavioral and functional neuroimaging data in routine clinical practice could not only fundamentally alter our concept of ASD but eventually also transform the clinical management of this disorder.

A simple brain atrophy measure improves the prediction of malignant middle cerebral artery infarction by acute DWI lesion volume.

PubMed

Beck, Christoph; Kruetzelmann, Anna; Forkert, Nils D; Juettler, Eric; Singer, Oliver C; Köhrmann, Martin; Kersten, Jan F; Sobesky, Jan; Gerloff, Christian; Fiehler, Jens; Schellinger, Peter D; Röther, Joachim; Thomalla, Götz

2014-06-01

In patients with malignant middle cerebral artery infarction (MMI) decompressive surgery within 48 h improves functional outcome. In this respect, early identification of patients at risk of developing MMI is crucial. While the acute diffusion weighted imaging (DWI) lesion volume was found to predict MMI with high predictive values, the potential impact of preexisting brain atrophy on the course of space-occupying middle cerebral artery (MCA) infarction and the development of MMI remains unclear. We tested the hypothesis that the combination of the acute DWI lesion volume with simple measures of brain atrophy improves the early prediction of MMI. Data from a prospective, multicenter, observational study, which included patients with acute middle cerebral artery main stem occlusion studied by MRI within 6 h of symptom onset, was analyzed retrospectively. The development of MMI was defined according to the European randomized controlled trials of decompressive surgery. Acute DWI lesion volume, as well as brain and cerebrospinal fluid volume (CSF) were delineated. The intercaudate distance (ICD) was assessed as a linear brain atrophy marker by measuring the hemi-ICD of the intact hemisphere to account for local brain swelling. Binary logistic regression analysis was used to identify significant predictors of MMI. Cut-off values were determined by Classification and Regression Trees analysis. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the resulting models were calculated. Twenty-one (18 %) of 116 patients developed a MMI. Malignant middle cerebral artery infarctions patients had higher National Institutes of Health Stroke Scale scores on admission and presented more often with combined occlusion of the internal carotid artery and MCA. There were no differences in brain and CSF volume between the two groups. Diffusion weighted imaging lesion volume was larger (p < 0.001), while hemi-ICD was smaller (p = 0.029) in MMI patients. Inclusion of hemi-ICD improved the prediction of MMI. Best cut-off values to predict the development of MMI were DWI lesion volume > 87 ml and hemi-ICD ≤ 9.4 mm. The addition of hemi-ICD to the decision tree strongly increased PPV (0.93 vs. 0.70) resulting in a reduction of false positive findings from 7/23 (30 %) to 1/15 (7 %), while there were only slight changes in specificity, sensitivity and NPV. The absolute number of correct classifications increased by 4 (3.4 %). The integration of hemi-ICD as a linear marker of brain atrophy, that can easily be assessed in an emergency setting, may improve the prediction of MMI by lesion volume based predictive models.

Using Vision and Speech Features for Automated Prediction of Performance Metrics in Multimodal Dialogs. Research Report. ETS RR-17-20

ERIC Educational Resources Information Center

Ramanarayanan, Vikram; Lange, Patrick; Evanini, Keelan; Molloy, Hillary; Tsuprun, Eugene; Qian, Yao; Suendermann-Oeft, David

2017-01-01

Predicting and analyzing multimodal dialog user experience (UX) metrics, such as overall call experience, caller engagement, and latency, among other metrics, in an ongoing manner is important for evaluating such systems. We investigate automated prediction of multiple such metrics collected from crowdsourced interactions with an open-source,…

Metastatic brain cancer: prediction of response to whole-brain helical tomotherapy with simultaneous intralesional boost for metastatic disease using quantitative MR imaging features

NASA Astrophysics Data System (ADS)

Sharma, Harish; Bauman, Glenn; Rodrigues, George; Bartha, Robert; Ward, Aaron

2014-03-01

The sequential application of whole brain radiotherapy (WBRT) and more targeted stereotactic radiosurgery (SRS) is frequently used to treat metastatic brain tumors. However, SRS has side effects related to necrosis and edema, and requires separate and relatively invasive localization procedures. Helical tomotherapy (HT) allows for a SRS-type simultaneous infield boost (SIB) of multiple brain metastases, synchronously with WBRT and without separate stereotactic procedures. However, some patients' tumors may not respond to HT+SIB, and would be more appropriately treated with radiosurgery or conventional surgery despite the additional risks and side effects. As a first step toward a broader objective of developing a means for response prediction to HT+SIB, the goal of this study was to investigate whether quantitative measurements of tumor size and appearance (including first- and second-order texture features) on a magnetic resonance imaging (MRI) scan acquired prior to treatment could be used to differentiate responder and nonresponder patient groups after HT+SIB treatment of metastatic disease of the brain. Our results demonstrated that smaller lesions may respond better to this form of therapy; measures of appearance provided limited added value over measures of size for response prediction. With further validation on a larger data set, this approach may lead to a means for prediction of individual patient response based on pre-treatment MRI, supporting appropriate therapy selection for patients with metastatic brain cancer.

Flowering in grassland predicted by CO2 and resource effects on species aboveground biomass

USDA-ARS?s Scientific Manuscript database

Ongoing enrichment of atmospheric CO2 concentration may increase plant community productivity by changing plant community composition through direct and indirect effects on light, water, or nutrient availability. CO2 enrichment has been predicted to reduce plant reproductive allocation in herbaceou...

Intellectual enrichment lessens the effect of brain atrophy on learning and memory in multiple sclerosis.

PubMed

Sumowski, James F; Wylie, Glenn R; Chiaravalloti, Nancy; DeLuca, John

2010-06-15

Learning and memory impairments are prevalent among persons with multiple sclerosis (MS); however, such deficits are only weakly associated with MS disease severity (brain atrophy). The cognitive reserve hypothesis states that greater lifetime intellectual enrichment lessens the negative impact of brain disease on cognition, thereby helping to explain the incomplete relationship between brain disease and cognitive status in neurologic populations. The literature on cognitive reserve has focused mainly on Alzheimer disease. The current research examines whether greater intellectual enrichment lessens the negative effect of brain atrophy on learning and memory in patients with MS. Forty-four persons with MS completed neuropsychological measures of verbal learning and memory, and a vocabulary-based estimate of lifetime intellectual enrichment. Brain atrophy was estimated with third ventricle width measured from 3-T magnetization-prepared rapid gradient echo MRIs. Hierarchical regression was used to predict learning and memory with brain atrophy, intellectual enrichment, and the interaction between brain atrophy and intellectual enrichment. Brain atrophy predicted worse learning and memory, and intellectual enrichment predicted better learning; however, these effects were moderated by interactions between brain atrophy and intellectual enrichment. Specifically, higher intellectual enrichment lessened the negative impact of brain atrophy on both learning and memory. These findings help to explain the incomplete relationship between multiple sclerosis disease severity and cognition, as the effect of disease on cognition is attenuated among patients with higher intellectual enrichment. As such, intellectual enrichment is supported as a protective factor against disease-related cognitive impairment in persons with multiple sclerosis.

Intrusive effects of semantic information on visual selective attention.

PubMed

Malcolm, George L; Rattinger, Michelle; Shomstein, Sarah

2016-10-01

Every object is represented by semantic information in extension to its low-level properties. It is well documented that such information biases attention when it is necessary for an ongoing task. However, whether semantic relationships influence attentional selection when they are irrelevant to the ongoing task remains an open question. The ubiquitous nature of semantic information suggests that it could bias attention even when these properties are irrelevant. In the present study, three objects appeared on screen, two of which were semantically related. After a varying time interval, a target or distractor appeared on top of each object. The objects' semantic relationships never predicted the target location. Despite this, a semantic bias on attentional allocation was observed, with an initial, transient bias to semantically related objects. Further experiments demonstrated that this effect was contingent on the objects being attended: if an object never contained the target, it no longer exerted a semantic influence. In a final set of experiments, we demonstrated that the semantic bias is robust and appears even in the presence of more predictive cues (spatial probability). These results suggest that as long as an object is attended, its semantic properties bias attention, even if it is irrelevant to an ongoing task and if more predictive factors are available.

Microbial Endocrinology: An Ongoing Personal Journey.

PubMed

Lyte, Mark

2016-01-01

The development of microbial endocrinology is covered from a decidedly personal perspective. Specific focus is given to the role of microbial endocrinology in the evolutionary symbiosis between man and microbe as it relates to both health and disease. Since the first edition of this book series 5 years ago, the role of microbial endocrinology in the microbiota-gut-brain axis is additionally discussed. Future avenues of research are suggested.

Preclinical Comparison of Osimertinib with Other EGFR-TKIs in EGFR-Mutant NSCLC Brain Metastases Models, and Early Evidence of Clinical Brain Metastases Activity.

PubMed

Ballard, Peter; Yates, James W T; Yang, Zhenfan; Kim, Dong-Wan; Yang, James Chih-Hsin; Cantarini, Mireille; Pickup, Kathryn; Jordan, Angela; Hickey, Mike; Grist, Matthew; Box, Matthew; Johnström, Peter; Varnäs, Katarina; Malmquist, Jonas; Thress, Kenneth S; Jänne, Pasi A; Cross, Darren

2016-10-15

Approximately one-third of patients with non-small cell lung cancer (NSCLC) harboring tumors with EGFR-tyrosine kinase inhibitor (TKI)-sensitizing mutations (EGFRm) experience disease progression during treatment due to brain metastases. Despite anecdotal reports of EGFR-TKIs providing benefit in some patients with EGFRm NSCLC brain metastases, there is a clinical need for novel EGFR-TKIs with improved efficacy against brain lesions. We performed preclinical assessments of brain penetration and activity of osimertinib (AZD9291), an oral, potent, irreversible EGFR-TKI selective for EGFRm and T790M resistance mutations, and other EGFR-TKIs in various animal models of EGFR-mutant NSCLC brain metastases. We also present case reports of previously treated patients with EGFRm-advanced NSCLC and brain metastases who received osimertinib in the phase I/II AURA study (NCT01802632). Osimertinib demonstrated greater penetration of the mouse blood-brain barrier than gefitinib, rociletinib (CO-1686), or afatinib, and at clinically relevant doses induced sustained tumor regression in an EGFRm PC9 mouse brain metastases model; rociletinib did not achieve tumor regression. Under positron emission tomography micro-dosing conditions, [ 11 C]osimertinib showed markedly greater exposure in the cynomolgus monkey brain than [ 11 C]rociletinib and [ 11 C]gefitinib. Early clinical evidence of osimertinib activity in previously treated patients with EGFRm-advanced NSCLC and brain metastases is also reported. Osimertinib may represent a clinically significant treatment option for patients with EGFRm NSCLC and brain metastases. Further investigation of osimertinib in this patient population is ongoing. Clin Cancer Res; 22(20); 5130-40. ©2016 AACR. ©2016 American Association for Cancer Research.

Hearing through the noise: Biologically inspired noise reduction

NASA Astrophysics Data System (ADS)

Lee, Tyler Paul

Vocal communication in the natural world demands that a listener perform a remarkably complicated task in real-time. Vocalizations mix with all other sounds in the environment as they travel to the listener, arriving as a jumbled low-dimensional signal. A listener must then use this signal to extract the structure corresponding to individual sound sources. How this computation is implemented in the brain remains poorly understood, yet an accurate description of such mechanisms would impact a variety of medical and technological applications of sound processing. In this thesis, I describe initial work on how neurons in the secondary auditory cortex of the Zebra Finch extract song from naturalistic background noise. I then build on our understanding of the function of these neurons by creating an algorithm that extracts speech from natural background noise using spectrotemporal modulations. The algorithm, implemented as an artificial neural network, can be flexibly applied to any class of signal or noise and performs better than an optimal frequency-based noise reduction algorithm for a variety of background noises and signal-to-noise ratios. One potential drawback to using spectrotemporal modulations for noise reduction, though, is that analyzing the modulations present in an ongoing sound requires a latency set by the slowest temporal modulation computed. The algorithm avoids this problem by reducing noise predictively, taking advantage of the large amount of temporal structure present in natural sounds. This predictive denoising has ties to recent work suggesting that the auditory system uses attention to focus on predicted regions of spectrotemporal space when performing auditory scene analysis.

GABAergic modulation of visual gamma and alpha oscillations and its consequences for working memory performance.

PubMed

Lozano-Soldevilla, Diego; ter Huurne, Niels; Cools, Roshan; Jensen, Ole

2014-12-15

Impressive in vitro research in rodents and computational modeling has uncovered the core mechanisms responsible for generating neuronal oscillations. In particular, GABAergic interneurons play a crucial role for synchronizing neural populations. Do these mechanistic principles apply to human oscillations associated with function? To address this, we recorded ongoing brain activity using magnetoencephalography (MEG) in healthy human subjects participating in a double-blind pharmacological study receiving placebo, 0.5 mg and 1.5 mg of lorazepam (LZP; a benzodiazepine upregulating GABAergic conductance). Participants performed a demanding visuospatial working memory (WM) task. We found that occipital gamma power associated with WM recognition increased with LZP dosage. Importantly, the frequency of the gamma activity decreased with dosage, as predicted by models derived from the rat hippocampus. A regionally specific gamma increase correlated with the drug-related performance decrease. Despite the system-wide pharmacological intervention, gamma power drug modulations were specific to visual cortex: sensorimotor gamma power and frequency during button presses remained unaffected. In contrast, occipital alpha power modulations during the delay interval decreased parametrically with drug dosage, predicting performance impairment. Consistent with alpha oscillations reflecting functional inhibition, LZP affected alpha power strongly in early visual regions not required for the task demonstrating a regional specific occipital impairment. GABAergic interneurons are strongly implicated in the generation of gamma and alpha oscillations in human occipital cortex where drug-induced power modulations predicted WM performance. Our findings bring us an important step closer to linking neuronal dynamics to behavior by embracing established animal models. Copyright © 2014 Elsevier Ltd. All rights reserved.

Prediction of human errors by maladaptive changes in event-related brain networks.

PubMed

Eichele, Tom; Debener, Stefan; Calhoun, Vince D; Specht, Karsten; Engel, Andreas K; Hugdahl, Kenneth; von Cramon, D Yves; Ullsperger, Markus

2008-04-22

Humans engaged in monotonous tasks are susceptible to occasional errors that may lead to serious consequences, but little is known about brain activity patterns preceding errors. Using functional MRI and applying independent component analysis followed by deconvolution of hemodynamic responses, we studied error preceding brain activity on a trial-by-trial basis. We found a set of brain regions in which the temporal evolution of activation predicted performance errors. These maladaptive brain activity changes started to evolve approximately 30 sec before the error. In particular, a coincident decrease of deactivation in default mode regions of the brain, together with a decline of activation in regions associated with maintaining task effort, raised the probability of future errors. Our findings provide insights into the brain network dynamics preceding human performance errors and suggest that monitoring of the identified precursor states may help in avoiding human errors in critical real-world situations.

Prediction of human errors by maladaptive changes in event-related brain networks

PubMed Central

Eichele, Tom; Debener, Stefan; Calhoun, Vince D.; Specht, Karsten; Engel, Andreas K.; Hugdahl, Kenneth; von Cramon, D. Yves; Ullsperger, Markus

2008-01-01

Humans engaged in monotonous tasks are susceptible to occasional errors that may lead to serious consequences, but little is known about brain activity patterns preceding errors. Using functional MRI and applying independent component analysis followed by deconvolution of hemodynamic responses, we studied error preceding brain activity on a trial-by-trial basis. We found a set of brain regions in which the temporal evolution of activation predicted performance errors. These maladaptive brain activity changes started to evolve ≈30 sec before the error. In particular, a coincident decrease of deactivation in default mode regions of the brain, together with a decline of activation in regions associated with maintaining task effort, raised the probability of future errors. Our findings provide insights into the brain network dynamics preceding human performance errors and suggest that monitoring of the identified precursor states may help in avoiding human errors in critical real-world situations. PMID:18427123

Insulin Resistance as a Link between Amyloid-Beta and Tau Pathologies in Alzheimer’s Disease

PubMed Central

Mullins, Roger J.; Diehl, Thomas C.; Chia, Chee W.; Kapogiannis, Dimitrios

2017-01-01

Current hypotheses and theories regarding the pathogenesis of Alzheimer’s disease (AD) heavily implicate brain insulin resistance (IR) as a key factor. Despite the many well-validated metrics for systemic IR, the absence of biomarkers for brain-specific IR represents a translational gap that has hindered its study in living humans. In our lab, we have been working to develop biomarkers that reflect the common mechanisms of brain IR and AD that may be used to follow their engagement by experimental treatments. We present two promising biomarkers for brain IR in AD: insulin cascade mediators probed in extracellular vesicles (EVs) enriched for neuronal origin, and two-dimensional magnetic resonance spectroscopy (MRS) measures of brain glucose. As further evidence for a fundamental link between brain IR and AD, we provide a novel analysis demonstrating the close spatial correlation between brain expression of genes implicated in IR (using Allen Human Brain Atlas data) and tau and beta-amyloid pathologies. We proceed to propose the bold hypotheses that baseline differences in the metabolic reliance on glycolysis, and the expression of glucose transporters (GLUT) and insulin signaling genes determine the vulnerability of different brain regions to Tau and/or Amyloid beta (Aβ) pathology, and that IR is a critical link between these two pathologies that define AD. Lastly, we provide an overview of ongoing clinical trials that target IR as an angle to treat AD, and suggest how biomarkers may be used to evaluate treatment efficacy and target engagement. PMID:28515688

Tuning pathological brain oscillations with neurofeedback: a systems neuroscience framework

PubMed Central

Ros, Tomas; J. Baars, Bernard; Lanius, Ruth A.; Vuilleumier, Patrik

2014-01-01

Neurofeedback (NFB) is emerging as a promising technique that enables self-regulation of ongoing brain oscillations. However, despite a rise in empirical evidence attesting to its clinical benefits, a solid theoretical basis is still lacking on the manner in which NFB is able to achieve these outcomes. The present work attempts to bring together various concepts from neurobiology, engineering, and dynamical systems so as to propose a contemporary theoretical framework for the mechanistic effects of NFB. The objective is to provide a firmly neurophysiological account of NFB, which goes beyond traditional behaviorist interpretations that attempt to explain psychological processes solely from a descriptive standpoint whilst treating the brain as a “black box”. To this end, we interlink evidence from experimental findings that encompass a broad range of intrinsic brain phenomena: starting from “bottom-up” mechanisms of neural synchronization, followed by “top-down” regulation of internal brain states, moving to dynamical systems plus control-theoretic principles, and concluding with activity-dependent as well as homeostatic forms of brain plasticity. In support of our framework, we examine the effects of NFB in several brain disorders, including attention-deficit hyperactivity (ADHD) and post-traumatic stress disorder (PTSD). In sum, it is argued that pathological oscillations emerge from an abnormal formation of brain-state attractor landscape(s). The central thesis put forward is that NFB tunes brain oscillations toward a homeostatic set-point which affords an optimal balance between network flexibility and stability (i.e., self-organised criticality (SOC)). PMID:25566028

The neurology of mTOR.

PubMed

Lipton, Jonathan O; Sahin, Mustafa

2014-10-22

The mechanistic target of rapamycin (mTOR) signaling pathway is a crucial cellular signaling hub that, like the nervous system itself, integrates internal and external cues to elicit critical outputs including growth control, protein synthesis, gene expression, and metabolic balance. The importance of mTOR signaling to brain function is underscored by the myriad disorders in which mTOR pathway dysfunction is implicated, such as autism, epilepsy, and neurodegenerative disorders. Pharmacological manipulation of mTOR signaling holds therapeutic promise and has entered clinical trials for several disorders. Here, we review the functions of mTOR signaling in the normal and pathological brain, highlighting ongoing efforts to translate our understanding of cellular physiology into direct medical benefit for neurological disorders.

Did some 18th and 19th century treatments for mental disorders act on the brain?

PubMed

Leonard, Edward C

2004-01-01

Review of 18th and 19th century psychiatric therapies raises the possibility that several may have altered the activity of vasopressin or Na-K-ATPase. Bleeding, whirling, nausea created by medicines, and vagus nerve stimulation by application of electricity through the skin all perturb the hypothalamic hormone, arginine vasopressin, while helleborus and digitalis inhibit the sodium pump enzyme, Na-K-ATPase. These approaches were used with reported benefit many years ago, acting on the brain in ways ongoing research suggests may play a role in affective disorders. Study of long-abandoned treatments may clarify their mechanisms of action and the characteristics of responsive patients.

Brain atrophy and lesion load measures over 1 year relate to clinical status after 6 years in patients with clinically isolated syndromes.

PubMed

Di Filippo, M; Anderson, V M; Altmann, D R; Swanton, J K; Plant, G T; Thompson, A J; Miller, D H

2010-02-01

Conventional MRI lesion measures modestly predict long term disability in some clinically isolated syndrome (CIS) studies. Brain atrophy suggests neuroaxonal loss in multiple sclerosis (MS) with the potential to reflect disease progression to a greater extent than lesion measures. To investigate whether brain atrophy and lesion load, during the first year in patients presenting with CIS, independently predict clinical outcome (development of MS and disability at 6 years). 99 patients presenting with CIS were included in the study. T1 gadolinium enhanced and T2 weighted brain MRI was acquired at baseline and approximately 1 year later. Percentage brain atrophy rate between baseline and follow-up scans was analysed using SIENA. Mean annual brain atrophy rates were -0.38% for all patients, -0.50% in patients who had developed MS at 6 years and -0.26% in those who had not. Brain atrophy rate (p = 0.005) and baseline T2 lesion load (p<0.001) were independent predictors of clinically definite MS. While brain atrophy rate was a predictor of Expanded Disability Status Scale (EDSS) score in a univariate analysis, only 1 year T2 lesion load change (p = 0.007) and baseline gadolinium enhancing lesion number (p = 0.03) were independent predictors of EDSS score at the 6 year follow-up. T1 lesion load was the only MRI parameter which predicted Multiple Sclerosis Functional Composite score at the 6 year follow-up. The findings confirm that brain atrophy occurs during the earliest phases of MS and suggest that 1 year longitudinal measures of MRI change, if considered together with baseline MRI variables, might help to predict clinical status 6 years after the first demyelinating event in CIS patients, better than measurements such as lesion or brain volumes on baseline MRI alone.

Identification of brain regions predicting epileptogenesis by serial [18F]GE-180 positron emission tomography imaging of neuroinflammation in a rat model of temporal lobe epilepsy.

PubMed

Russmann, Vera; Brendel, Matthias; Mille, Erik; Helm-Vicidomini, Angela; Beck, Roswitha; Günther, Lisa; Lindner, Simon; Rominger, Axel; Keck, Michael; Salvamoser, Josephine D; Albert, Nathalie L; Bartenstein, Peter; Potschka, Heidrun

2017-01-01

Excessive activation of inflammatory signaling pathways seems to be a hallmark of epileptogenesis. Positron emission tomography (PET) allows in vivo detection of brain inflammation with spatial information and opportunities for longitudinal follow-up scanning protocols. Here, we assessed whether molecular imaging of the 18 kDa translocator protein (TSPO) can serve as a biomarker for the development of epilepsy. Therefore, brain uptake of [ 18 F]GE-180, a highly selective radioligand of TSPO, was investigated in a longitudinal PET study in a chronic rat model of temporal lobe epilepsy. Analyses revealed that the influence of the epileptogenic insult on [ 18 F]GE-180 brain uptake was most pronounced in the earlier phase of epileptogenesis. Differences were evident in various brain regions during earlier phases of epileptogenesis with [ 18 F]GE-180 standardized uptake value enhanced by 2.1 to 2.7fold. In contrast, brain regions exhibiting differences seemed to be more restricted with less pronounced increases of tracer uptake by 1.8-2.5fold four weeks following status epilepticus and by 1.5-1.8fold in the chronic phase. Based on correlation analysis, we were able to identify regions with a predictive value showing a correlation with seizure development. These regions include the amygdala as well as a cluster of brain areas. This cluster comprises parts of different brain regions, e.g. the hippocampus, parietal cortex, thalamus, and somatosensory cortex. In conclusion, the data provide evidence that [ 18 F]GE-180 PET brain imaging can serve as a biomarker of epileptogenesis. The identification of brain regions with predictive value might facilitate the development of preventive concepts as well as the early assessment of the interventional success. Future studies are necessary to further confirm the predictivity of the approach.

Allostasis and the human brain: Integrating models of stress from the social and life sciences

PubMed Central

Ganzel, Barbara L.; Morris, Pamela A.; Wethington, Elaine

2009-01-01

We draw on the theory of allostasis to develop an integrative model of the current stress process that highlights the brain as a dynamically adapting interface between the changing environment and the biological self. We review evidence that the core emotional regions of the brain constitute the primary mediator of the well-established association between stress and health, as well as the neural focus of “wear and tear” due to ongoing adaptation. This mediation, in turn, allows us to model the interplay over time between context, current stressor exposure, internal regulation of bodily processes, and health outcomes. We illustrate how this approach facilitates the integration of current findings in human neuroscience and genetics with key constructs from stress models from the social and life sciences, with implications for future research and the design of interventions targeting individuals at risk. PMID:20063966

Impaired cerebral autoregulation and brain injury in newborns with hypoxic-ischemic encephalopathy treated with hypothermia.

PubMed

Massaro, An N; Govindan, R B; Vezina, Gilbert; Chang, Taeun; Andescavage, Nickie N; Wang, Yunfei; Al-Shargabi, Tareq; Metzler, Marina; Harris, Kari; du Plessis, Adre J

2015-08-01

Impaired cerebral autoregulation may contribute to secondary injury in newborns with hypoxic-ischemic encephalopathy (HIE). Continuous, noninvasive assessment of cerebral pressure autoregulation can be achieved with bedside near-infrared spectroscopy (NIRS) and systemic mean arterial blood pressure (MAP) monitoring. This study aimed to evaluate whether impaired cerebral autoregulation measured by NIRS-MAP monitoring during therapeutic hypothermia and rewarming relates to outcome in 36 newborns with HIE. Spectral coherence analysis between NIRS and MAP was used to quantify changes in the duration [pressure passivity index (PPI)] and magnitude (gain) of cerebral autoregulatory impairment. Higher PPI in both cerebral hemispheres and gain in the right hemisphere were associated with neonatal adverse outcomes [death or detectable brain injury by magnetic resonance imaging (MRI), P < 0.001]. NIRS-MAP monitoring of cerebral autoregulation can provide an ongoing physiological biomarker that may help direct care in perinatal brain injury. Copyright © 2015 the American Physiological Society.

L1 retrotransposons and somatic mosaicism in the brain.

PubMed

Richardson, Sandra R; Morell, Santiago; Faulkner, Geoffrey J

2014-01-01

Long interspersed element 1 (LINE-1 or L1) retrotransposons have generated one-third of the human genome, and their ongoing mobility is a source of inter- and intraindividual genetic diversity. Although retrotransposition in metazoans has long been considered a germline phenomenon, recent experiments using cultured cells, animal models, and human tissues have revealed extensive L1 mobilization in rodent and human neurons, as well as mobile element activity in the Drosophila brain. In this review, we evaluate the available evidence for L1 retrotransposition in the brain and discuss mechanisms that may regulate neuronal retrotransposition in vivo. We compare experimental strategies used to map de novo somatic retrotransposition events and present the optimal criteria to identify a somatic L1 insertion. Finally, we discuss the unresolved impact of L1-mediated somatic mosaicism upon normal neurobiology, as well as its potential to drive neurological disease.

Mild Traumatic Brain Injury and Post-concussion Syndrome: Treatment and Related Sequela for Persistent Symptomatic Disease.

PubMed

Bramley, Harry; Hong, Justin; Zacko, Christopher; Royer, Christopher; Silvis, Matthew

2016-09-01

Sport-related concussion typically resolves within a few weeks of the injury; however, persistent symptoms have been reported to occur in 10% to 15% of concussions. These ongoing symptoms can cause significant disability and be frustrating for the patient and family. In addition, factors other than brain injury can cause complications for these patients, such as adjustment disorder or exacerbation of preexisting conditions such as depression or migraine. Individuals with prolonged symptoms of concussion may be classified as having post-concussion syndrome. A careful and thoughtful evaluation is important, as the clinician must determine whether these prolonged symptoms reflect brain injury pathophysiology versus another process. Although there have been numerous studies on the acute management of concussion, much less is available on the treatment of persistent disease. This review will provide an evaluation approach for the patient with prolonged concussion symptoms and review recent literature on treatment strategies.

Adolescent rationality.

PubMed

Moshman, David

2013-01-01

Adolescents are commonly seen as irrational, a position supported to varying degrees by many developmentalists, who often appeal to recent research on adolescent brains. Careful review of relevant evidence, however, shows that (1) adults are less rational than is generally assumed, (2) adolescents (and adults) are categorically different from children with respect to the attainment of advanced levels of rationality and psychological functioning, and (3) adolescents and adults do not differ categorically from each other with respect to any rational competencies, irrational tendencies, brain structures, or neurological functioning. Development often continues in adolescence and beyond but categorical claims about adolescents as distinct from adults cannot be justified. A review of U.S. Supreme Court decisions concerning intellectual freedom, reproductive freedom, and criminal responsibility shows ongoing ambivalence and confusion about the rationality of adolescents. Developmental theory and research suggest that adolescents should be conceptualized as young adults, not immature brains, with important implications for their roles, rights, and responsibilities.

Advances in Light Microscopy for Neuroscience

PubMed Central

Wilt, Brian A.; Burns, Laurie D.; Ho, Eric Tatt Wei; Ghosh, Kunal K.; Mukamel, Eran A.

2010-01-01

Since the work of Golgi and Cajal, light microscopy has remained a key tool for neuroscientists to observe cellular properties. Ongoing advances have enabled new experimental capabilities using light to inspect the nervous system across multiple spatial scales, including ultrastructural scales finer than the optical diffraction limit. Other progress permits functional imaging at faster speeds, at greater depths in brain tissue, and over larger tissue volumes than previously possible. Portable, miniaturized fluorescence microscopes now allow brain imaging in freely behaving mice. Complementary progress on animal preparations has enabled imaging in head-restrained behaving animals, as well as time-lapse microscopy studies in the brains of live subjects. Mouse genetic approaches permit mosaic and inducible fluorescence-labeling strategies, whereas intrinsic contrast mechanisms allow in vivo imaging of animals and humans without use of exogenous markers. This review surveys such advances and highlights emerging capabilities of particular interest to neuroscientists. PMID:19555292

A square root ensemble Kalman filter application to a motor-imagery brain-computer interface

PubMed Central

Kamrunnahar, M.; Schiff, S. J.

2017-01-01

We here investigated a non-linear ensemble Kalman filter (SPKF) application to a motor imagery brain computer interface (BCI). A square root central difference Kalman filter (SR-CDKF) was used as an approach for brain state estimation in motor imagery task performance, using scalp electroencephalography (EEG) signals. Healthy human subjects imagined left vs. right hand movements and tongue vs. bilateral toe movements while scalp EEG signals were recorded. Offline data analysis was conducted for training the model as well as for decoding the imagery movements. Preliminary results indicate the feasibility of this approach with a decoding accuracy of 78%–90% for the hand movements and 70%–90% for the tongue-toes movements. Ongoing research includes online BCI applications of this approach as well as combined state and parameter estimation using this algorithm with different system dynamic models. PMID:22255799

Longitudinal Changes in Total Brain Volume in Schizophrenia: Relation to Symptom Severity, Cognition and Antipsychotic Medication

PubMed Central

Veijola, Juha; Guo, Joyce Y.; Moilanen, Jani S.; Jääskeläinen, Erika; Miettunen, Jouko; Kyllönen, Merja; Haapea, Marianne; Huhtaniska, Sanna; Alaräisänen, Antti; Mäki, Pirjo; Kiviniemi, Vesa; Nikkinen, Juha; Starck, Tuomo; Remes, Jukka J.; Tanskanen, Päivikki; Tervonen, Osmo; Wink, Alle-Meije; Kehagia, Angie; Suckling, John; Kobayashi, Hiroyuki; Barnett, Jennifer H.; Barnes, Anna; Koponen, Hannu J.; Jones, Peter B.; Isohanni, Matti; Murray, Graham K.

2014-01-01

Studies show evidence of longitudinal brain volume decreases in schizophrenia. We studied brain volume changes and their relation to symptom severity, level of function, cognition, and antipsychotic medication in participants with schizophrenia and control participants from a general population based birth cohort sample in a relatively long follow-up period of almost a decade. All members of the Northern Finland Birth Cohort 1966 with any psychotic disorder and a random sample not having psychosis were invited for a MRI brain scan, and clinical and cognitive assessment during 1999–2001 at the age of 33–35 years. A follow-up was conducted 9 years later during 2008–2010. Brain scans at both time points were obtained from 33 participants with schizophrenia and 71 control participants. Regression models were used to examine whether brain volume changes predicted clinical and cognitive changes over time, and whether antipsychotic medication predicted brain volume changes. The mean annual whole brain volume reduction was 0.69% in schizophrenia, and 0.49% in controls (p = 0.003, adjusted for gender, educational level, alcohol use and weight gain). The brain volume reduction in schizophrenia patients was found especially in the temporal lobe and periventricular area. Symptom severity, functioning level, and decline in cognition were not associated with brain volume reduction in schizophrenia. The amount of antipsychotic medication (dose years of equivalent to 100 mg daily chlorpromazine) over the follow-up period predicted brain volume loss (p = 0.003 adjusted for symptom level, alcohol use and weight gain). In this population based sample, brain volume reduction continues in schizophrenia patients after the onset of illness, and antipsychotic medications may contribute to these reductions. PMID:25036617

Apparent diffusion coefficient mapping in medulloblastoma predicts non-infiltrative surgical planes.

PubMed

Marupudi, Neena I; Altinok, Deniz; Goncalves, Luis; Ham, Steven D; Sood, Sandeep

2016-11-01

An appropriate surgical approach for posterior fossa lesions is to start tumor removal from areas with a defined plane to where tumor is infiltrating the brainstem or peduncles. This surgical approach minimizes risk of damage to eloquent areas. Although magnetic resonance imaging (MRI) is the current standard preoperative imaging obtained for diagnosis and surgical planning of pediatric posterior fossa tumors, it offers limited information on the infiltrative planes between tumor and normal structures in patients with medulloblastomas. Because medulloblastomas demonstrate diffusion restriction on apparent diffusion coefficient map (ADC map) sequences, we investigated the role of ADC map in predicting infiltrative and non-infiltrative planes along the brain stem and/or cerebellar peduncles by medulloblastomas prior to surgery. Thirty-four pediatric patients with pathologically confirmed medulloblastomas underwent surgical resection at our facility from 2004 to 2012. An experienced pediatric neuroradiologist reviewed the brain MRIs/ADC map, assessing the planes between the tumor and cerebellar peduncles/brain stem. An independent evaluator documented surgical findings from operative reports for comparison to the radiographic findings. The radiographic findings were statistically compared to the documented intraoperative findings to determine predictive value of the test in identifying tumor infiltration of the brain stem cerebellar peduncles. Twenty-six patients had preoperative ADC mapping completed and thereby, met inclusion criteria. Mean age at time of surgery was 8.3 ± 4.6 years. Positive predictive value of ADC maps to predict tumor invasion of the brain stem and cerebellar peduncles ranged from 69 to 88 %; negative predictive values ranged from 70 to 89 %. Sensitivity approached 93 % while specificity approached 78 %. ADC maps are valuable in predicting the infiltrative and non-infiltrative planes along the tumor and brain stem interface in medulloblastomas. Inclusion and evaluation of ADC maps in preoperative evaluation can assist in surgical resection planning in patients with medulloblastoma.

The proactive brain: memory for predictions

PubMed Central

Bar, Moshe

2009-01-01

It is proposed that the human brain is proactive in that it continuously generates predictions that anticipate the relevant future. In this proposal, analogies are derived from elementary information that is extracted rapidly from the input, to link that input with the representations that exist in memory. Finding an analogical link results in the generation of focused predictions via associative activation of representations that are relevant to this analogy, in the given context. Predictions in complex circumstances, such as social interactions, combine multiple analogies. Such predictions need not be created afresh in new situations, but rather rely on existing scripts in memory, which are the result of real as well as of previously imagined experiences. This cognitive neuroscience framework provides a new hypothesis with which to consider the purpose of memory, and can help explain a variety of phenomena, ranging from recognition to first impressions, and from the brain's ‘default mode’ to a host of mental disorders. PMID:19528004

Can blood and semen presepsin levels in males predict pregnancy in couples undergoing intra-cytoplasmic sperm injection?

PubMed

Ovayolu, Ali; Arslanbuğa, Cansev Yilmaz; Gun, Ismet; Devranoglu, Belgin; Ozdemir, Arman; Cakar, Sule Eren

2016-01-01

To determine whether semen and plasma presepsin values measured in men with normozoospermia and oligoasthenospermia undergoing invitro-fertilization would be helpful in predicting ongoing pregnancy and live birth. Group-I was defined as patients who had pregnancy after treatment and Group-II comprised those with no pregnancy. Semen and blood presepsin values were subsequently compared between the groups. Parametric comparisons were performed using Student's t-test, and non-parametric comparisons were conducted using the Mann-Whitney U test. There were 42 patients in Group-I and 72 in Group-II. In the context of successful pregnancy and live birth, semen presepsin values were statistically significantly higher in Group-I than in Group-II (p= 0.004 and p= 0.037, respectively). The most appropriate semen presepsin cut-off value for predicting both ongoing pregnancy and live birth was calculated as 199 pg/mL. Accordingly, their sensitivity was 64.5% to 59.3%, their specificity was 57.0% to 54.2%, and their positive predictive value was 37.0% to 29.6%, respectively; their negative predictive value was 80.4% in both instances. Semen presepsin values could be a new marker that may enable the prediction of successful pregnancy and/or live birth. Its negative predictive values are especially high.

Multiparametric MRI changes persist beyond recovery in concussed adolescent hockey players

PubMed Central

Manning, Kathryn Y.; Schranz, Amy; Bartha, Robert; Dekaban, Gregory A.; Barreira, Christy; Brown, Arthur; Fischer, Lisa; Asem, Kevin; Doherty, Timothy J.; Fraser, Douglas D.; Holmes, Jeff

2017-01-01

Objective: To determine whether multiparametric MRI data can provide insight into the acute and long-lasting neuronal sequelae after a concussion in adolescent athletes. Methods: Players were recruited from Bantam hockey leagues in which body checking is first introduced (male, age 11–14 years). Clinical measures, diffusion metrics, resting-state network and region-to-region functional connectivity patterns, and magnetic resonance spectroscopy absolute metabolite concentrations were analyzed from an independent, age-matched control group of hockey players (n = 26) and longitudinally in concussed athletes within 24 to 72 hours (n = 17) and 3 months (n = 14) after a diagnosed concussion. Results: There were diffusion abnormalities within multiple white matter tracts, functional hyperconnectivity, and decreases in choline 3 months after concussion. Tract-specific spatial statistics revealed a large region along the superior longitudinal fasciculus with the largest decreases in diffusivity measures, which significantly correlated with clinical deficits. This region also spatially intersected with probabilistic tracts connecting cortical regions where we found acute functional connectivity changes. Hyperconnectivity patterns at 3 months after concussion were present only in players with relatively less severe clinical outcomes, higher choline concentrations, and diffusivity indicative of relatively less axonal disruption. Conclusions: Changes persisted well after players' clinical scores had returned to normal and they had been cleared to return to play. Ongoing white matter maturation may make adolescent athletes particularly vulnerable to brain injury, and they may require extended recovery periods. The consequences of early brain injury for ongoing brain development and risk of more serious conditions such as second impact syndrome or neural degenerative processes need to be elucidated. PMID:29070666

Prediction of Composition and Emission Characteristics of Articles in Support of Exposure Assessment

EPA Science Inventory

The risk to humans from chemicals in consumer products is dependent on both hazard and exposure. The prediction and quantification of near-field (i.e., indoor) chemical exposure from household articles such as furniture and building materials is an ongoing effort. As opposed to (...

Characteristics of voxel prediction power in full-brain Granger causality analysis of fMRI data

NASA Astrophysics Data System (ADS)

Garg, Rahul; Cecchi, Guillermo A.; Rao, A. Ravishankar

2011-03-01

Functional neuroimaging research is moving from the study of "activations" to the study of "interactions" among brain regions. Granger causality analysis provides a powerful technique to model spatio-temporal interactions among brain regions. We apply this technique to full-brain fMRI data without aggregating any voxel data into regions of interest (ROIs). We circumvent the problem of dimensionality using sparse regression from machine learning. On a simple finger-tapping experiment we found that (1) a small number of voxels in the brain have very high prediction power, explaining the future time course of other voxels in the brain; (2) these voxels occur in small sized clusters (of size 1-4 voxels) distributed throughout the brain; (3) albeit small, these clusters overlap with most of the clusters identified with the non-temporal General Linear Model (GLM); and (4) the method identifies clusters which, while not determined by the task and not detectable by GLM, still influence brain activity.

Structure Shapes Dynamics and Directionality in Diverse Brain Networks: Mathematical Principles and Empirical Confirmation in Three Species

NASA Astrophysics Data System (ADS)

Moon, Joon-Young; Kim, Junhyeok; Ko, Tae-Wook; Kim, Minkyung; Iturria-Medina, Yasser; Choi, Jee-Hyun; Lee, Joseph; Mashour, George A.; Lee, Uncheol

2017-04-01

Identifying how spatially distributed information becomes integrated in the brain is essential to understanding higher cognitive functions. Previous computational and empirical studies suggest a significant influence of brain network structure on brain network function. However, there have been few analytical approaches to explain the role of network structure in shaping regional activities and directionality patterns. In this study, analytical methods are applied to a coupled oscillator model implemented in inhomogeneous networks. We first derive a mathematical principle that explains the emergence of directionality from the underlying brain network structure. We then apply the analytical methods to the anatomical brain networks of human, macaque, and mouse, successfully predicting simulation and empirical electroencephalographic data. The results demonstrate that the global directionality patterns in resting state brain networks can be predicted solely by their unique network structures. This study forms a foundation for a more comprehensive understanding of how neural information is directed and integrated in complex brain networks.

Relating resting-state fMRI and EEG whole-brain connectomes across frequency bands.

PubMed

Deligianni, Fani; Centeno, Maria; Carmichael, David W; Clayden, Jonathan D

2014-01-01

Whole brain functional connectomes hold promise for understanding human brain activity across a range of cognitive, developmental and pathological states. So called resting-state (rs) functional MRI studies have contributed to the brain being considered at a macroscopic scale as a set of interacting regions. Interactions are defined as correlation-based signal measurements driven by blood oxygenation level dependent (BOLD) contrast. Understanding the neurophysiological basis of these measurements is important in conveying useful information about brain function. Local coupling between BOLD fMRI and neurophysiological measurements is relatively well defined, with evidence that gamma (range) frequency EEG signals are the closest correlate of BOLD fMRI changes during cognitive processing. However, it is less clear how whole-brain network interactions relate during rest where lower frequency signals have been suggested to play a key role. Simultaneous EEG-fMRI offers the opportunity to observe brain network dynamics with high spatio-temporal resolution. We utilize these measurements to compare the connectomes derived from rs-fMRI and EEG band limited power (BLP). Merging this multi-modal information requires the development of an appropriate statistical framework. We relate the covariance matrices of the Hilbert envelope of the source localized EEG signal across bands to the covariance matrices derived from rs-fMRI with the means of statistical prediction based on sparse Canonical Correlation Analysis (sCCA). Subsequently, we identify the most prominent connections that contribute to this relationship. We compare whole-brain functional connectomes based on their geodesic distance to reliably estimate the performance of the prediction. The performance of predicting fMRI from EEG connectomes is considerably better than predicting EEG from fMRI across all bands, whereas the connectomes derived in low frequency EEG bands resemble best rs-fMRI connectivity.

Relating resting-state fMRI and EEG whole-brain connectomes across frequency bands

PubMed Central

Deligianni, Fani; Centeno, Maria; Carmichael, David W.; Clayden, Jonathan D.

2014-01-01

Whole brain functional connectomes hold promise for understanding human brain activity across a range of cognitive, developmental and pathological states. So called resting-state (rs) functional MRI studies have contributed to the brain being considered at a macroscopic scale as a set of interacting regions. Interactions are defined as correlation-based signal measurements driven by blood oxygenation level dependent (BOLD) contrast. Understanding the neurophysiological basis of these measurements is important in conveying useful information about brain function. Local coupling between BOLD fMRI and neurophysiological measurements is relatively well defined, with evidence that gamma (range) frequency EEG signals are the closest correlate of BOLD fMRI changes during cognitive processing. However, it is less clear how whole-brain network interactions relate during rest where lower frequency signals have been suggested to play a key role. Simultaneous EEG-fMRI offers the opportunity to observe brain network dynamics with high spatio-temporal resolution. We utilize these measurements to compare the connectomes derived from rs-fMRI and EEG band limited power (BLP). Merging this multi-modal information requires the development of an appropriate statistical framework. We relate the covariance matrices of the Hilbert envelope of the source localized EEG signal across bands to the covariance matrices derived from rs-fMRI with the means of statistical prediction based on sparse Canonical Correlation Analysis (sCCA). Subsequently, we identify the most prominent connections that contribute to this relationship. We compare whole-brain functional connectomes based on their geodesic distance to reliably estimate the performance of the prediction. The performance of predicting fMRI from EEG connectomes is considerably better than predicting EEG from fMRI across all bands, whereas the connectomes derived in low frequency EEG bands resemble best rs-fMRI connectivity. PMID:25221467

The problem with brain GUTs: conflation of different senses of "prediction" threatens metaphysical disaster.

PubMed

Anderson, Michael L; Chemero, Tony

2013-06-01

Clark appears to be moving toward epistemic internalism, which he once rightly rejected. This results from a double over-interpretation of predictive coding's significance. First, Clark argues that predictive coding offers a Grand Unified Theory (GUT) of brain function. Second, he over-reads its epistemic import, perhaps even conflating causal and epistemic mediators. We argue instead for a plurality of neurofunctional principles.

Attention and prediction in human audition: a lesson from cognitive psychophysiology

PubMed Central

Schröger, Erich; Marzecová, Anna; SanMiguel, Iria

2015-01-01

Attention is a hypothetical mechanism in the service of perception that facilitates the processing of relevant information and inhibits the processing of irrelevant information. Prediction is a hypothetical mechanism in the service of perception that considers prior information when interpreting the sensorial input. Although both (attention and prediction) aid perception, they are rarely considered together. Auditory attention typically yields enhanced brain activity, whereas auditory prediction often results in attenuated brain responses. However, when strongly predicted sounds are omitted, brain responses to silence resemble those elicited by sounds. Studies jointly investigating attention and prediction revealed that these different mechanisms may interact, e.g. attention may magnify the processing differences between predicted and unpredicted sounds. Following the predictive coding theory, we suggest that prediction relates to predictions sent down from predictive models housed in higher levels of the processing hierarchy to lower levels and attention refers to gain modulation of the prediction error signal sent up to the higher level. As predictions encode contents and confidence in the sensory data, and as gain can be modulated by the intention of the listener and by the predictability of the input, various possibilities for interactions between attention and prediction can be unfolded. From this perspective, the traditional distinction between bottom-up/exogenous and top-down/endogenous driven attention can be revisited and the classic concepts of attentional gain and attentional trace can be integrated. PMID:25728182

Dynamic causal modelling of brain-behaviour relationships.

PubMed

Rigoux, L; Daunizeau, J

2015-08-15

In this work, we expose a mathematical treatment of brain-behaviour relationships, which we coin behavioural Dynamic Causal Modelling or bDCM. This approach aims at decomposing the brain's transformation of stimuli into behavioural outcomes, in terms of the relative contribution of brain regions and their connections. In brief, bDCM places the brain at the interplay between stimulus and behaviour: behavioural outcomes arise from coordinated activity in (hidden) neural networks, whose dynamics are driven by experimental inputs. Estimating neural parameters that control network connectivity and plasticity effectively performs a neurobiologically-constrained approximation to the brain's input-outcome transform. In other words, neuroimaging data essentially serves to enforce the realism of bDCM's decomposition of input-output relationships. In addition, post-hoc artificial lesions analyses allow us to predict induced behavioural deficits and quantify the importance of network features for funnelling input-output relationships. This is important, because this enables one to bridge the gap with neuropsychological studies of brain-damaged patients. We demonstrate the face validity of the approach using Monte-Carlo simulations, and its predictive validity using empirical fMRI/behavioural data from an inhibitory control task. Lastly, we discuss promising applications of this work, including the assessment of functional degeneracy (in the healthy brain) and the prediction of functional recovery after lesions (in neurological patients). Copyright © 2015 Elsevier Inc. All rights reserved.

Brain entropy and human intelligence: A resting-state fMRI study

PubMed Central

Calderone, Daniel; Morales, Leah J.

2018-01-01

Human intelligence comprises comprehension of and reasoning about an infinitely variable external environment. A brain capable of large variability in neural configurations, or states, will more easily understand and predict variable external events. Entropy measures the variety of configurations possible within a system, and recently the concept of brain entropy has been defined as the number of neural states a given brain can access. This study investigates the relationship between human intelligence and brain entropy, to determine whether neural variability as reflected in neuroimaging signals carries information about intellectual ability. We hypothesize that intelligence will be positively associated with entropy in a sample of 892 healthy adults, using resting-state fMRI. Intelligence is measured with the Shipley Vocabulary and WASI Matrix Reasoning tests. Brain entropy was positively associated with intelligence. This relation was most strongly observed in the prefrontal cortex, inferior temporal lobes, and cerebellum. This relationship between high brain entropy and high intelligence indicates an essential role for entropy in brain functioning. It demonstrates that access to variable neural states predicts complex behavioral performance, and specifically shows that entropy derived from neuroimaging signals at rest carries information about intellectual capacity. Future work in this area may elucidate the links between brain entropy in both resting and active states and various forms of intelligence. This insight has the potential to provide predictive information about adaptive behavior and to delineate the subdivisions and nature of intelligence based on entropic patterns. PMID:29432427

Brain entropy and human intelligence: A resting-state fMRI study.

PubMed

Saxe, Glenn N; Calderone, Daniel; Morales, Leah J

2018-01-01

Human intelligence comprises comprehension of and reasoning about an infinitely variable external environment. A brain capable of large variability in neural configurations, or states, will more easily understand and predict variable external events. Entropy measures the variety of configurations possible within a system, and recently the concept of brain entropy has been defined as the number of neural states a given brain can access. This study investigates the relationship between human intelligence and brain entropy, to determine whether neural variability as reflected in neuroimaging signals carries information about intellectual ability. We hypothesize that intelligence will be positively associated with entropy in a sample of 892 healthy adults, using resting-state fMRI. Intelligence is measured with the Shipley Vocabulary and WASI Matrix Reasoning tests. Brain entropy was positively associated with intelligence. This relation was most strongly observed in the prefrontal cortex, inferior temporal lobes, and cerebellum. This relationship between high brain entropy and high intelligence indicates an essential role for entropy in brain functioning. It demonstrates that access to variable neural states predicts complex behavioral performance, and specifically shows that entropy derived from neuroimaging signals at rest carries information about intellectual capacity. Future work in this area may elucidate the links between brain entropy in both resting and active states and various forms of intelligence. This insight has the potential to provide predictive information about adaptive behavior and to delineate the subdivisions and nature of intelligence based on entropic patterns.

Neurotherapy of Traumatic Brain Injury/Post-Traumatic Stress Symptoms in Vietnam Veterans.

PubMed

Nelson, David V; Esty, Mary Lee

2015-10-01

Previous report suggested the beneficial effects of an adaptation of the Flexyx Neurotherapy System (FNS) for the amelioration of mixed traumatic brain injury/post-traumatic stress symptoms in veterans of the Afghanistan and Iraq wars. As a novel variant of electroencephalograph biofeedback, FNS falls within the bioenergy domain of complementary and alternative medicine. Rather than learning voluntary control over the production/inhibition of brain wave patterns, FNS involves offsetting stimulation of brain wave activity by means of an external energy source, specifically, the conduction of electromagnetic energy stimulation via the connecting electroencephalograph cables. Essentially, these procedures subliminally induce strategic distortion of ongoing brain wave activity to presumably facilitate resetting of more adaptive patterns of activity. Reported herein are two cases of Vietnam veterans with mixed traumatic brain injury/post-traumatic stress symptoms, each treated with FNS for 25 sessions. Comparisons of pre- and post-treatment questionnaire assessments revealed notable decreases for all symptoms, suggesting improvements across the broad domains of cognition, pain, sleep, fatigue, and mood/emotion, including post-traumatic stress symptoms, as well as for overall activity levels. Findings suggest FNS treatment may be of potential benefit for the partial amelioration of symptoms, even in some individuals for whom symptoms have been present for decades. Reprint & Copyright © 2015 Association of Military Surgeons of the U.S.

Hypopituitarism after acute brain injury.

PubMed

Urban, Randall J

2006-07-01

Acute brain injury has many causes, but the most common is trauma. There are 1.5-2.0 million traumatic brain injuries (TBI) in the United States yearly, with an associated cost exceeding 10 billion dollars. TBI is the most common cause of death and disability in young adults less than 35 years of age. The consequences of TBI can be severe, including disability in motor function, speech, cognition, and psychosocial and emotional skills. Recently, clinical studies have documented the occurrence of pituitary dysfunction after TBI and another cause of acute brain injury, subarachnoid hemorrhage (SAH). These studies have consistently demonstrated a 30-40% occurrence of pituitary dysfunction involving at least one anterior pituitary hormone following a moderate to severe TBI or SAH. Growth hormone (GH) deficiency is the most common pituitary hormone disorder, occurring in approximately 20% of patients when multiple tests of GH deficiency are used. Within 7-21 days of acute brain injury, adrenal insufficiency is the primary concern. Pituitary function can fluctuate over the first year after TBI, but it is well established by 1 year. Studies are ongoing to assess the effects of hormone replacement on motor function and cognition in TBI patients. Any subject with a moderate to severe acute brain injury should be screened for pituitary dysfunction.

Subtle volume differences in brain parenchyma of children surviving medulloblastoma

NASA Astrophysics Data System (ADS)

Reddick, Wilburn E.; Mulhern, Raymond K.; Elkin, T. David; Glass, John O.; Langston, James W.

1998-07-01

The overriding incentive for accurate quantification of the functional status of children treated for brain tumors emerges from the clinician's desire to balance the efficacy and chronic toxicity of therapies used for the developing child. A hybrid combination of the Kohonen self-organizing map (SOM) for segmentation and a multilayer backpropagation (MLBP) neural network for classification removes observer variances to yield a reproducible and accurate identification of tissues. A group of 17 volunteers and 77 patients from a larger ongoing study of pediatric patients with brain tumors were used to investigate the sensitivity of segmented volumes to determine atrophy as measured by two radiologists. The atrophy study revealed a significant relationship for brain parenchyma, CSF and white matter volumes with atrophy while gray matter had no significant relationship. Brain parenchyma and subsequently white matter were found to be inversely proportional to increasing grades of atrophy. An additional study compared fifteen age-matched patients treated with irradiation and surgery with patients treated with surgery alone. The age-matched study of patients demonstrated that brain volumes in the irradiated patients were significantly decreased compared to those treated with surgery alone. Further investigation of this difference revealed that white matter was significantly reduced while gray matter was relatively unchanged.

Brain Stimulation and the Role of the Right Hemisphere in Aphasia Recovery.

PubMed

Turkeltaub, Peter E

2015-11-01

Aphasia is a common consequence of left hemisphere stroke and causes a disabling loss of language and communication ability. Current treatments for aphasia are inadequate, leaving a majority of aphasia sufferers with ongoing communication difficulties for the rest of their lives. In the past decade, two forms of noninvasive brain stimulation, repetitive transcranial magnetic stimulation and transcranial direct current stimulation, have emerged as promising new treatments for aphasia. The most common brain stimulation protocols attempt to inhibit the intact right hemisphere based on the hypothesis that maladaptive activity in the right hemisphere limits language recovery in the left. There is now sufficient evidence to demonstrate that this approach, at least for repetitive transcranial magnetic stimulation, improves specific language abilities in aphasia. However, the biological mechanisms that produce these behavioral improvements remain poorly understood. Taken in the context of the larger neurobiological literature on aphasia recovery, the role of the right hemisphere in aphasia recovery remains unclear. Additional research is needed to understand biological mechanisms of recovery, in order to optimize brain stimulation treatments for aphasia. This article summarizes the current evidence on noninvasive brain stimulation methods for aphasia and the neuroscientific considerations surrounding treatments using right hemisphere inhibition. Suggestions are provided for further investigation and for clinicians whose patients ask about brain stimulation treatments for aphasia.

Prefrontal Brain Activity Predicts Temporally Extended Decision-Making Behavior

ERIC Educational Resources Information Center

Yarkoni, Tal; Braver, Todd S.; Gray, Jeremy R.; Green, Leonard

2005-01-01

Although functional neuroimaging studies of human decision-making processes are increasingly common, most of the research in this area has relied on passive tasks that generate little individual variability. Relatively little attention has been paid to the ability of brain activity to predict overt behavior. Using functional magnetic resonance…

Predicting homeowners' approval of fuel management at the wild-urban interface using the theory of reasoned action.

Treesearch

Christine A. Vogt; Greg Winter; Jeremy S. Fried

2005-01-01

Social science models are increasingly needed as a framework for explaining and predicting how members of the public respond to the natural environment and their communities. The theory of reasoned action is widely used in human dimensions research on natural resource problems and work is ongoing to increase the predictive power of models based on this theory. This...

Trends and Challenges in Neuroengineering: Toward "Intelligent" Neuroprostheses through Brain-"Brain Inspired Systems" Communication.

PubMed

Vassanelli, Stefano; Mahmud, Mufti

2016-01-01

Future technologies aiming at restoring and enhancing organs function will intimately rely on near-physiological and energy-efficient communication between living and artificial biomimetic systems. Interfacing brain-inspired devices with the real brain is at the forefront of such emerging field, with the term "neurobiohybrids" indicating all those systems where such interaction is established. We argue that achieving a "high-level" communication and functional synergy between natural and artificial neuronal networks in vivo , will allow the development of a heterogeneous world of neurobiohybrids, which will include "living robots" but will also embrace "intelligent" neuroprostheses for augmentation of brain function. The societal and economical impact of intelligent neuroprostheses is likely to be potentially strong, as they will offer novel therapeutic perspectives for a number of diseases, and going beyond classical pharmaceutical schemes. However, they will unavoidably raise fundamental ethical questions on the intermingling between man and machine and more specifically, on how deeply it should be allowed that brain processing is affected by implanted "intelligent" artificial systems. Following this perspective, we provide the reader with insights on ongoing developments and trends in the field of neurobiohybrids. We address the topic also from a "community building" perspective, showing through a quantitative bibliographic analysis, how scientists working on the engineering of brain-inspired devices and brain-machine interfaces are increasing their interactions. We foresee that such trend preludes to a formidable technological and scientific revolution in brain-machine communication and to the opening of new avenues for restoring or even augmenting brain function for therapeutic purposes.

Trends and Challenges in Neuroengineering: Toward “Intelligent” Neuroprostheses through Brain-“Brain Inspired Systems” Communication

PubMed Central

Vassanelli, Stefano; Mahmud, Mufti

2016-01-01

Future technologies aiming at restoring and enhancing organs function will intimately rely on near-physiological and energy-efficient communication between living and artificial biomimetic systems. Interfacing brain-inspired devices with the real brain is at the forefront of such emerging field, with the term “neurobiohybrids” indicating all those systems where such interaction is established. We argue that achieving a “high-level” communication and functional synergy between natural and artificial neuronal networks in vivo, will allow the development of a heterogeneous world of neurobiohybrids, which will include “living robots” but will also embrace “intelligent” neuroprostheses for augmentation of brain function. The societal and economical impact of intelligent neuroprostheses is likely to be potentially strong, as they will offer novel therapeutic perspectives for a number of diseases, and going beyond classical pharmaceutical schemes. However, they will unavoidably raise fundamental ethical questions on the intermingling between man and machine and more specifically, on how deeply it should be allowed that brain processing is affected by implanted “intelligent” artificial systems. Following this perspective, we provide the reader with insights on ongoing developments and trends in the field of neurobiohybrids. We address the topic also from a “community building” perspective, showing through a quantitative bibliographic analysis, how scientists working on the engineering of brain-inspired devices and brain-machine interfaces are increasing their interactions. We foresee that such trend preludes to a formidable technological and scientific revolution in brain-machine communication and to the opening of new avenues for restoring or even augmenting brain function for therapeutic purposes. PMID:27721741

A brain imaging repository of normal structural MRI across the life course: Brain Images of Normal Subjects (BRAINS).

PubMed

Job, Dominic E; Dickie, David Alexander; Rodriguez, David; Robson, Andrew; Danso, Sammy; Pernet, Cyril; Bastin, Mark E; Boardman, James P; Murray, Alison D; Ahearn, Trevor; Waiter, Gordon D; Staff, Roger T; Deary, Ian J; Shenkin, Susan D; Wardlaw, Joanna M

2017-01-01

The Brain Images of Normal Subjects (BRAINS) Imagebank (http://www.brainsimagebank.ac.uk) is an integrated repository project hosted by the University of Edinburgh and sponsored by the Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) collaborators. BRAINS provide sharing and archiving of detailed normal human brain imaging and relevant phenotypic data already collected in studies of healthy volunteers across the life-course. It particularly focusses on the extremes of age (currently older age, and in future perinatal) where variability is largest, and which are under-represented in existing databanks. BRAINS is a living imagebank where new data will be added when available. Currently BRAINS contains data from 808 healthy volunteers, from 15 to 81years of age, from 7 projects in 3 centres. Additional completed and ongoing studies of normal individuals from 1st to 10th decades are in preparation and will be included as they become available. BRAINS holds several MRI structural sequences, including T1, T2, T2* and fluid attenuated inversion recovery (FLAIR), available in DICOM (http://dicom.nema.org/); in future Diffusion Tensor Imaging (DTI) will be added where available. Images are linked to a wide range of 'textual data', such as age, medical history, physiological measures (e.g. blood pressure), medication use, cognitive ability, and perinatal information for pre/post-natal subjects. The imagebank can be searched to include or exclude ranges of these variables to create better estimates of 'what is normal' at different ages. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Brain age and other bodily 'ages': implications for neuropsychiatry.

PubMed

Cole, James H; Marioni, Riccardo E; Harris, Sarah E; Deary, Ian J

2018-06-11

As our brains age, we tend to experience cognitive decline and are at greater risk of neurodegenerative disease and dementia. Symptoms of chronic neuropsychiatric diseases are also exacerbated during ageing. However, the ageing process does not affect people uniformly; nor, in fact, does the ageing process appear to be uniform even within an individual. Here, we outline recent neuroimaging research into brain ageing and the use of other bodily ageing biomarkers, including telomere length, the epigenetic clock, and grip strength. Some of these techniques, using statistical approaches, have the ability to predict chronological age in healthy people. Moreover, they are now being applied to neurological and psychiatric disease groups to provide insights into how these diseases interact with the ageing process and to deliver individualised predictions about future brain and body health. We discuss the importance of integrating different types of biological measurements, from both the brain and the rest of the body, to build more comprehensive models of the biological ageing process. Finally, we propose seven steps for the field of brain-ageing research to take in coming years. This will help us reach the long-term goal of developing clinically applicable statistical models of biological processes to measure, track and predict brain and body health in ageing and disease.

Cortical oscillations and sensory predictions.

PubMed

Arnal, Luc H; Giraud, Anne-Lise

2012-07-01

Many theories of perception are anchored in the central notion that the brain continuously updates an internal model of the world to infer the probable causes of sensory events. In this framework, the brain needs not only to predict the causes of sensory input, but also when they are most likely to happen. In this article, we review the neurophysiological bases of sensory predictions of "what' (predictive coding) and 'when' (predictive timing), with an emphasis on low-level oscillatory mechanisms. We argue that neural rhythms offer distinct and adapted computational solutions to predicting 'what' is going to happen in the sensory environment and 'when'. Copyright © 2012 Elsevier Ltd. All rights reserved.

Resting-State fMRI Functional Connectivity Is Associated with Sleepiness, Imagery, and Discontinuity of Mind

PubMed Central

Chen, Gang; den Braber, Anouk; van ‘t Ent, Dennis; Boomsma, Dorret I.; Mansvelder, Huibert D.; de Geus, Eco; Van Someren, Eus J. W.; Linkenkaer-Hansen, Klaus

2015-01-01

Resting-state functional magnetic resonance imaging (rs-fMRI) is widely used to investigate the functional architecture of the healthy human brain and how it is affected by learning, lifelong development, brain disorders or pharmacological intervention. Non-sensory experiences are prevalent during rest and must arise from ongoing brain activity, yet little is known about this relationship. Here, we used two runs of rs-fMRI both immediately followed by the Amsterdam Resting-State Questionnaire (ARSQ) to investigate the relationship between functional connectivity within ten large-scale functional brain networks and ten dimensions of thoughts and feelings experienced during the scan in 106 healthy participants. We identified 11 positive associations between brain-network functional connectivity and ARSQ dimensions. ‘Sleepiness’ exhibited significant associations with functional connectivity within Visual, Sensorimotor and Default Mode networks. Similar associations were observed for ‘Visual Thought’ and ‘Discontinuity of Mind’, which may relate to variation in imagery and thought control mediated by arousal fluctuations. Our findings show that self-reports of thoughts and feelings experienced during a rs-fMRI scan help understand the functional significance of variations in functional connectivity, which should be of special relevance to clinical studies. PMID:26540239

Head or brain injuries and Alzheimer's disease: A nested case-control register study.

PubMed

Tolppanen, Anna-Maija; Taipale, Heidi; Hartikainen, Sirpa

2017-12-01

Many previous studies have been limited by self- or proxy-reported injury or short follow-up. We investigated whether head or brain injuries are associated with Alzheimer's disease (AD), possible modifying factors and dose-response relationship. Nested register-based case-control study of all community dwellers who received clinically verified AD diagnosis in Finland in 2005 to 2011 (n = 70,719) and one to four matched controls for each case (n of controls = 282,862). The magnitude of association between hospital-treated head and/or brain injuries was strongly dependent on the lag time between exposure and outcome. With a 5-year lag time, head injury (adjusted odds ratio; 95% confidence interval 1.19; 1.15-1.23) or brain injury (1.23; 1.18-1.29) was associated with higher risk of AD. Dose-response relationship with number and severity of injuries was observed. Associations were stronger in those with earlier onset of AD. Stronger associations with shorter lag times indicate that head and/or brain injuries may also reflect the ongoing AD disease process. Copyright © 2017 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Neuroimaging of the Injured Pediatric Brain: Methods and New Lessons.

PubMed

Dennis, Emily L; Babikian, Talin; Giza, Christopher C; Thompson, Paul M; Asarnow, Robert F

2018-02-01

Traumatic brain injury (TBI) is a significant public health problem in the United States, especially for children and adolescents. Current epidemiological data estimate over 600,000 patients younger than 20 years are treated for TBI in emergency rooms annually. While many patients experience a full recovery, for others there can be long-lasting cognitive, neurological, psychological, and behavioral disruptions. TBI in youth can disrupt ongoing brain development and create added family stress during a formative period. The neuroimaging methods used to assess brain injury improve each year, providing researchers a more detailed characterization of the injury and recovery process. In this review, we cover current imaging methods used to quantify brain disruption post-injury, including structural magnetic resonance imaging (MRI), diffusion MRI, functional MRI, resting state fMRI, and magnetic resonance spectroscopy (MRS), with brief coverage of other methods, including electroencephalography (EEG), single-photon emission computed tomography (SPECT), and positron emission tomography (PET). We include studies focusing on pediatric moderate-severe TBI from 2 months post-injury and beyond. While the morbidity of pediatric TBI is considerable, continuing advances in imaging methods have the potential to identify new treatment targets that can lead to significant improvements in outcome.

Convection-enhanced delivery for the treatment of glioblastoma

PubMed Central

Vogelbaum, Michael A.; Aghi, Manish K.

2015-01-01

Effective treatment of glioblastoma (GBM) remains a formidable challenge. Survival rates remain poor despite decades of clinical trials of conventional and novel, biologically targeted therapeutics. There is considerable evidence that most of these therapeutics do not reach their targets in the brain when administered via conventional routes (intravenous or oral). Hence, direct delivery of therapeutics to the brain and to brain tumors is an active area of investigation. One of these techniques, convection-enhanced delivery (CED), involves the implantation of catheters through which conventional and novel therapeutic formulations can be delivered using continuous, low–positive-pressure bulk flow. Investigation in preclinical and clinical settings has demonstrated that CED can produce effective delivery of therapeutics to substantial volumes of brain and brain tumor. However, limitations in catheter technology and imaging of delivery have prevented this technique from being reliable and reproducible, and the only completed phase III study in GBM did not show a survival benefit for patients treated with an investigational therapeutic delivered via CED. Further development of CED is ongoing, with novel catheter designs and imaging approaches that may allow CED to become a more effective therapeutic delivery technique. PMID:25746090

Effects of Anesthetics on Brain Circuit Formation

PubMed Central

Wagner, Meredith; Ryu, Yun Kyoung; Smith, Sarah C.; Mintz, C. David

2014-01-01

The results of several retrospective clinical studies suggest that exposure to anesthetic agents early in life is correlated with subsequent learning and behavioral disorders. While ongoing prospective clinical trials may help to clarify this association, they remain confounded by numerous factors. Thus, some of the most compelling data supporting the hypothesis that a relatively short anesthetic exposure can lead to a long-lasting change in brain function are derived from animal models. The mechanism by which such changes could occur remains incompletely understood. Early studies identified anesthetic-induced neuronal apoptosis as a possible mechanism of injury, and more recent work suggests that anesthetics may interfere with several critical processes in brain development. The function of the mature brain requires the presence of circuits, established during development, that perform the computations underlying learning and cognition. In this review we examine the mechanisms by which anesthetics could disrupt brain circuit formation, including effects on neuronal survival and neurogenesis, neurite growth and guidance, formation of synapses, and function of supporting cells. There is evidence that anesthetics can disrupt aspects of all of these processes, and further research is required to elucidate which are most relevant to pediatric anesthetic neurotoxicity. PMID:25144504

Variability of perceptual multistability: from brain state to individual trait

PubMed Central

Kleinschmidt, Andreas; Sterzer, Philipp; Rees, Geraint

2012-01-01

Few phenomena are as suitable as perceptual multistability to demonstrate that the brain constructively interprets sensory input. Several studies have outlined the neural circuitry involved in generating perceptual inference but only more recently has the individual variability of this inferential process been appreciated. Studies of the interaction of evoked and ongoing neural activity show that inference itself is not merely a stimulus-triggered process but is related to the context of the current brain state into which the processing of external stimulation is embedded. As brain states fluctuate, so does perception of a given sensory input. In multistability, perceptual fluctuation rates are consistent for a given individual but vary considerably between individuals. There has been some evidence for a genetic basis for these individual differences and recent morphometric studies of parietal lobe regions have identified neuroanatomical substrates for individual variability in spontaneous switching behaviour. Moreover, disrupting the function of these latter regions by transcranial magnetic stimulation yields systematic interference effects on switching behaviour, further arguing for a causal role of these regions in perceptual inference. Together, these studies have advanced our understanding of the biological mechanisms by which the brain constructs the contents of consciousness from sensory input. PMID:22371620

Study the efficacy of neuroprotective drugs on brain physiological properties during focal head injury using optical spectroscopy data analysis

NASA Astrophysics Data System (ADS)

Abookasis, David; Shochat, Ariel

2016-03-01

We present a comparative evaluation of five different neuroprotective drugs in the early phase following focal traumatic brain injury (TBI) in mouse intact head. The effectiveness of these drugs in terms of changes in brain tissue morphology and hemodynamic properties was experimentally evaluated through analysis of the optical absorption coefficient and spectral reduced scattering parameters in the range of 650-1000 nm. Anesthetized male mice (n=50 and n=10 control) were subjected to weight drop model mimics real life focal head trauma. Monitoring the effect of injury and neuroprotective drugs was obtained by using a diffuse reflectance spectroscopy system utilizing independent source-detector separation and location. Result indicates that administration of minocycline improve hemodynamic and reduced the level of tissue injury at an early phase post-injury while hypertonic saline treatment decrease brain water content. These findings highlight the heterogeneity between neuroprotective drugs and the ongoing controversy among researchers regarding which drug therapy is preferred for treatment of TBI. On the other hand, our results show the capability of optical spectroscopy technique to noninvasively study brain function following injury and drug therapy.

Cerebral cartography and connectomics.

PubMed

Sporns, Olaf

2015-05-19

Cerebral cartography and connectomics pursue similar goals in attempting to create maps that can inform our understanding of the structural and functional organization of the cortex. Connectome maps explicitly aim at representing the brain as a complex network, a collection of nodes and their interconnecting edges. This article reflects on some of the challenges that currently arise in the intersection of cerebral cartography and connectomics. Principal challenges concern the temporal dynamics of functional brain connectivity, the definition of areal parcellations and their hierarchical organization into large-scale networks, the extension of whole-brain connectivity to cellular-scale networks, and the mapping of structure/function relations in empirical recordings and computational models. Successfully addressing these challenges will require extensions of methods and tools from network science to the mapping and analysis of human brain connectivity data. The emerging view that the brain is more than a collection of areas, but is fundamentally operating as a complex networked system, will continue to drive the creation of ever more detailed and multi-modal network maps as tools for on-going exploration and discovery in human connectomics. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Childhood Brain Insult: Can Age at Insult Help Us Predict Outcome?

ERIC Educational Resources Information Center

Anderson, Vicki; Spencer-Smith, Megan; Leventer, Rick; Coleman, Lee; Anderson, Peter; Williams, Jackie; Greenham, Mardee; Jacobs, Rani

2009-01-01

Until recently, the impact of early brain insult (EBI) has been considered to be less significant than for later brain injuries, consistent with the notion that the young brain is more flexible and able to reorganize in the context of brain insult. This study aimed to evaluate this notion by comparing cognitive and behavioural outcomes for…

Initial Validation for the Estimation of Resting-State fMRI Effective Connectivity by a Generalization of the Correlation Approach

PubMed Central

Xu, Nan; Spreng, R. Nathan; Doerschuk, Peter C.

2017-01-01

Resting-state functional MRI (rs-fMRI) is widely used to noninvasively study human brain networks. Network functional connectivity is often estimated by calculating the timeseries correlation between blood-oxygen-level dependent (BOLD) signal from different regions of interest (ROIs). However, standard correlation cannot characterize the direction of information flow between regions. In this paper, we introduce and test a new concept, prediction correlation, to estimate effective connectivity in functional brain networks from rs-fMRI. In this approach, the correlation between two BOLD signals is replaced by a correlation between one BOLD signal and a prediction of this signal via a causal system driven by another BOLD signal. Three validations are described: (1) Prediction correlation performed well on simulated data where the ground truth was known, and outperformed four other methods. (2) On simulated data designed to display the “common driver” problem, prediction correlation did not introduce false connections between non-interacting driven ROIs. (3) On experimental data, prediction correlation recovered the previously identified network organization of human brain. Prediction correlation scales well to work with hundreds of ROIs, enabling it to assess whole brain interregional connectivity at the single subject level. These results provide an initial validation that prediction correlation can capture the direction of information flow and estimate the duration of extended temporal delays in information flow between regions of interest ROIs based on BOLD signal. This approach not only maintains the high sensitivity to network connectivity provided by the correlation analysis, but also performs well in the estimation of causal information flow in the brain. PMID:28559793

Improved Prediction of Blood-Brain Barrier Permeability Through Machine Learning with Combined Use of Molecular Property-Based Descriptors and Fingerprints.

PubMed

Yuan, Yaxia; Zheng, Fang; Zhan, Chang-Guo

2018-03-21

Blood-brain barrier (BBB) permeability of a compound determines whether the compound can effectively enter the brain. It is an essential property which must be accounted for in drug discovery with a target in the brain. Several computational methods have been used to predict the BBB permeability. In particular, support vector machine (SVM), which is a kernel-based machine learning method, has been used popularly in this field. For SVM training and prediction, the compounds are characterized by molecular descriptors. Some SVM models were based on the use of molecular property-based descriptors (including 1D, 2D, and 3D descriptors) or fragment-based descriptors (known as the fingerprints of a molecule). The selection of descriptors is critical for the performance of a SVM model. In this study, we aimed to develop a generally applicable new SVM model by combining all of the features of the molecular property-based descriptors and fingerprints to improve the accuracy for the BBB permeability prediction. The results indicate that our SVM model has improved accuracy compared to the currently available models of the BBB permeability prediction.

Innate immunity and cellular senescence: The good and the bad in the developmental and aged brain.

PubMed

Santoro, Antonietta; Spinelli, Chiara Carmela; Martucciello, Stefania; Nori, Stefania Lucia; Capunzo, Mario; Puca, Annibale Alessandro; Ciaglia, Elena

2018-03-01

Ongoing studies evidence cellular senescence in undifferentiated and specialized cells from tissues of all ages. Although it is believed that senescence plays a wider role in several stress responses in the mature age, its participation in certain physiological and pathological processes throughout life is coming to light. The "senescence machinery" has been observed in all brain cell populations, including components of innate immunity (e.g., microglia and astrocytes). As the beneficial versus detrimental implications of senescence is an open question, we aimed to analyze the contribution of immune responses in regulatory mechanisms governing its distinct functions in healthy (development, organogenesis, danger patrolling events) and diseased brain (glioma, neuroinflammation, neurodeneration), and the putative connection between cellular and molecular events governing the 2 states. Particularly this review offers new insights into the complex roles of senescence both as a chronological event as age advances, and as a molecular mechanism of brain homeostasis through the important contribution of innate immune responses and their crosstalk with neighboring cells in brain parenchyma. We also highlight the impact of the recently described glymphatic system and brain lymphatic vasculature in the interplay between peripheral and central immune surveillance and its potential implication during aging. This will open new ways to understand brain development, its deterioration during aging, and the occurrence of several oncological and neurodegenerative diseases. ©2018 Society for Leukocyte Biology.

Electrical stimulation of rhesus monkey nucleus reticularis gigantocellularis. II. Effects on metrics and kinematics of ongoing gaze shifts to visual targets.

PubMed

Freedman, Edward G; Quessy, Stephan

2004-06-01

Saccade kinematics are altered by ongoing head movements. The hypothesis that a head movement command signal, proportional to head velocity, transiently reduces the gain of the saccadic burst generator (Freedman 2001, Biol Cybern 84:453-462) can account for this observation. Using electrical stimulation of the rhesus monkey nucleus reticularis gigantocellularis (NRG) to alter the head contribution to ongoing gaze shifts, two critical predictions of this gaze control hypothesis were tested. First, this hypothesis predicts that activation of the head command pathway will cause a transient reduction in the gain of the saccadic burst generator. This should alter saccade kinematics by initially reducing velocity without altering saccade amplitude. Second, because this hypothesis does not assume that gaze amplitude is controlled via feedback, the added head contribution (produced by NRG stimulation on the side ipsilateral to the direction of an ongoing gaze shift) should lead to hypermetric gaze shifts. At every stimulation site tested, saccade kinematics were systematically altered in a way that was consistent with transient reduction of the gain of the saccadic burst generator. In addition, gaze shifts produced during NRG stimulation were hypermetric compared with control movements. For example, when targets were briefly flashed 30 degrees from an initial fixation location, gaze shifts during NRG stimulation were on average 140% larger than control movements. These data are consistent with the predictions of the tested hypothesis, and may be problematic for gaze control models that rely on feedback control of gaze amplitude, as well as for models that do not posit an interaction between head commands and the saccade burst generator.

Hippocampal Dosimetry Predicts Neurocognitive Function Impairment After Fractionated Stereotactic Radiotherapy for Benign or Low-Grade Adult Brain Tumors

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

Gondi, Vinai; Hermann, Bruce P.; Mehta, Minesh P.

2012-07-15

Purpose: To prospectively evaluate the association between hippocampal dose and long-term neurocognitive function (NCF) impairment for benign or low-grade adult brain tumors treated with fractionated stereotactic radiotherapy (FSRT). Methods and Materials: Adult patients with benign or low-grade adult brain tumors were treated with FSRT per institutional practice. No attempt was made to spare the hippocampus. NCF testing was conducted at baseline and 18 months follow-up, on a prospective clinical trial. Regression-based standardized z scores were calculated by using similar healthy control individuals evaluated at the same test-retest interval. NCF impairment was defined as a z score {<=}-1.5. After delineation ofmore » the bilateral hippocampi according to the Radiation Therapy Oncology Group contouring atlas, dose-volume histograms were generated for the left and right hippocampi and for the composite pair. Biologically equivalent doses in 2-Gy fractions (EQD{sub 2}) assuming an {alpha}/{beta} ratio of 2 Gy were computed. Fisher's exact test and binary logistic regression were used for univariate and multivariate analyses, respectively. Dose-response data were fit to a nonlinear model. Results: Of 29 patients enrolled in this trial, 18 completed both baseline and 18-month NCF testing. An EQD{sub 2} to 40% of the bilateral hippocampi >7.3 Gy was associated with impairment in Wechsler Memory Scale-III Word List (WMS-WL) delayed recall (odds ratio [OR] 19.3; p = 0.043). The association between WMS-WL delayed recall and EQD{sub 2} to 100% of the bilateral hippocampi >0.0 Gy trended to significance (OR 14.8; p = 0.068). Conclusion: EQD{sub 2} to 40% of the bilateral hippocampi greater than 7.3 Gy is associated with long-term impairment in list-learning delayed recall after FSRT for benign or low-grade adult brain tumors. Given that modern intensity-modulated radiotherapy techniques can reduce the dose to the bilateral hippocampi below this dosimetric threshold, patients should be enrolled in ongoing prospective trials of hippocampal sparing during cranial irradiation to confirm these preliminary results.« less

Hippocampal Dosimetry Predicts Neurocognitive Function Impairment After Fractionated Stereotactic Radiotherapy for Benign or Low-Grade Adult Brain Tumors

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

Gondi, Vinai; Hermann, Bruce P.; Mehta, Minesh P.

2013-02-01

Purpose: To prospectively evaluate the association between hippocampal dose and long-term neurocognitive function (NCF) impairment for benign or low-grade adult brain tumors treated with fractionated stereotactic radiotherapy (FSRT). Methods and Materials: Adult patients with benign or low-grade adult brain tumors were treated with FSRT per institutional practice. No attempt was made to spare the hippocampus. NCF testing was conducted at baseline and 18 months follow-up, on a prospective clinical trial. Regression-based standardized z scores were calculated by using similar healthy control individuals evaluated at the same test-retest interval. NCF impairment was defined as a z score {<=}-1.5. After delineation ofmore » the bilateral hippocampi according to the Radiation Therapy Oncology Group contouring atlas, dose-volume histograms were generated for the left and right hippocampi and for the composite pair. Biologically equivalent doses in 2-Gy fractions (EQD{sub 2}) assuming an {alpha}/{beta} ratio of 2 Gy were computed. Fisher's exact test and binary logistic regression were used for univariate and multivariate analyses, respectively. Dose-response data were fit to a nonlinear model. Results: Of 29 patients enrolled in this trial, 18 completed both baseline and 18-month NCF testing. An EQD{sub 2} to 40% of the bilateral hippocampi >7.3 Gy was associated with impairment in Wechsler Memory Scale-III Word List (WMS-WL) delayed recall (odds ratio [OR] 19.3; p = 0.043). The association between WMS-WL delayed recall and EQD{sub 2} to 100% of the bilateral hippocampi >0.0 Gy trended to significance (OR 14.8; p = 0.068). Conclusion: EQD{sub 2} to 40% of the bilateral hippocampi greater than 7.3 Gy is associated with long-term impairment in list-learning delayed recall after FSRT for benign or low-grade adult brain tumors. Given that modern intensity-modulated radiotherapy techniques can reduce the dose to the bilateral hippocampi below this dosimetric threshold, patients should be enrolled in ongoing prospective trials of hippocampal sparing during cranial irradiation to confirm these preliminary results.« less

Multivariate Brain Prediction of Heart Rate and Skin Conductance Responses to Social Threat.

PubMed

Eisenbarth, Hedwig; Chang, Luke J; Wager, Tor D

2016-11-23

Psychosocial stressors induce autonomic nervous system (ANS) responses in multiple body systems that are linked to health risks. Much work has focused on the common effects of stress, but ANS responses in different body systems are dissociable and may result from distinct patterns of cortical-subcortical interactions. Here, we used machine learning to develop multivariate patterns of fMRI activity predictive of heart rate (HR) and skin conductance level (SCL) responses during social threat in humans (N = 18). Overall, brain patterns predicted both HR and SCL in cross-validated analyses successfully (r HR = 0.54, r SCL = 0.58, both p < 0.0001). These patterns partly reflected central stress mechanisms common to both responses because each pattern predicted the other signal to some degree (r HR→SCL = 0.21 and r SCL→HR = 0.22, both p < 0.01), but they were largely physiological response specific. Both patterns included positive predictive weights in dorsal anterior cingulate and cerebellum and negative weights in ventromedial PFC and local pattern similarity analyses within these regions suggested that they encode common central stress mechanisms. However, the predictive maps and searchlight analysis suggested that the patterns predictive of HR and SCL were substantially different across most of the brain, including significant differences in ventromedial PFC, insula, lateral PFC, pre-SMA, and dmPFC. Overall, the results indicate that specific patterns of cerebral activity track threat-induced autonomic responses in specific body systems. Physiological measures of threat are not interchangeable, but rather reflect specific interactions among brain systems. We show that threat-induced increases in heart rate and skin conductance share some common representations in the brain, located mainly in the vmPFC, temporal and parahippocampal cortices, thalamus, and brainstem. However, despite these similarities, the brain patterns that predict these two autonomic responses are largely distinct. This evidence for largely output-measure-specific regulation of autonomic responses argues against a common system hypothesis and provides evidence that different autonomic measures reflect distinct, measurable patterns of cortical-subcortical interactions. Copyright © 2016 the authors 0270-6474/16/3611987-12$15.00/0.

Intellectual enrichment lessens the effect of brain atrophy on learning and memory in multiple sclerosis

PubMed Central

Sumowski, James F.; Wylie, Glenn R.; Chiaravalloti, Nancy; DeLuca, John

2010-01-01

Objective: Learning and memory impairments are prevalent among persons with multiple sclerosis (MS); however, such deficits are only weakly associated with MS disease severity (brain atrophy). The cognitive reserve hypothesis states that greater lifetime intellectual enrichment lessens the negative impact of brain disease on cognition, thereby helping to explain the incomplete relationship between brain disease and cognitive status in neurologic populations. The literature on cognitive reserve has focused mainly on Alzheimer disease. The current research examines whether greater intellectual enrichment lessens the negative effect of brain atrophy on learning and memory in patients with MS. Methods: Forty-four persons with MS completed neuropsychological measures of verbal learning and memory, and a vocabulary-based estimate of lifetime intellectual enrichment. Brain atrophy was estimated with third ventricle width measured from 3-T magnetization-prepared rapid gradient echo MRIs. Hierarchical regression was used to predict learning and memory with brain atrophy, intellectual enrichment, and the interaction between brain atrophy and intellectual enrichment. Results: Brain atrophy predicted worse learning and memory, and intellectual enrichment predicted better learning; however, these effects were moderated by interactions between brain atrophy and intellectual enrichment. Specifically, higher intellectual enrichment lessened the negative impact of brain atrophy on both learning and memory. Conclusion: These findings help to explain the incomplete relationship between multiple sclerosis disease severity and cognition, as the effect of disease on cognition is attenuated among patients with higher intellectual enrichment. As such, intellectual enrichment is supported as a protective factor against disease-related cognitive impairment in persons with multiple sclerosis. GLOSSARY AD = Alzheimer disease; ANOVA = analysis of variance; MPRAGE = magnetization-prepared rapid gradient echo; MS = multiple sclerosis; SRT = Selective Reminding Test; TVW = third ventricle width; WASI = Wechsler Abbreviated Scale of Intelligence. PMID:20548040

Application of brain cholinesterase reactivation to differentiate between organophosphorus and carbamate pesticide exposure in wild birds

USGS Publications Warehouse

Smith, M.R.; Thomas, N.J.; Hulse, C.

1995-01-01

Brain cholinesterase activity was measured to evaluate pesticide exposure in wild birds. Thermal reactivation of brain cholinesterase was used to differentiate between carbamate and organophosphorus pesticide exposure. Brain cholinesterase activity was compared with gas chromatography and mass spectrometry of stomach contents. Pesticides were identified and confirmed in 86 of 102 incidents of mortality from 29 states within the USA from 1986 through 1991. Thermal reactivation of cholinesterase activity was used to correctly predict carbamates in 22 incidents and organophosphates in 59 incidents. Agreement (P < 0.001) between predictions based on cholinesterase activities and GC/MS results was significant.

Longitudinal connectome-based predictive modeling for REM sleep behavior disorder from structural brain connectivity

NASA Astrophysics Data System (ADS)

Giancardo, Luca; Ellmore, Timothy M.; Suescun, Jessika; Ocasio, Laura; Kamali, Arash; Riascos-Castaneda, Roy; Schiess, Mya C.

2018-02-01

Methods to identify neuroplasticity patterns in human brains are of the utmost importance in understanding and potentially treating neurodegenerative diseases. Parkinson disease (PD) research will greatly benefit and advance from the discovery of biomarkers to quantify brain changes in the early stages of the disease, a prodromal period when subjects show no obvious clinical symptoms. Diffusion tensor imaging (DTI) allows for an in-vivo estimation of the structural connectome inside the brain and may serve to quantify the degenerative process before the appearance of clinical symptoms. In this work, we introduce a novel strategy to compute longitudinal structural connectomes in the context of a whole-brain data-driven pipeline. In these initial tests, we show that our predictive models are able to distinguish controls from asymptomatic subjects at high risk of developing PD (REM sleep behavior disorder, RBD) with an area under the receiving operating characteristic curve of 0.90 (p<0.001) and a longitudinal dataset of 46 subjects part of the Parkinson's Progression Markers Initiative. By analyzing the brain connections most relevant for the predictive ability of the best performing model, we find connections that are biologically relevant to the disease.

Structural brain MRI trait polygenic score prediction of cognitive abilities

PubMed Central

Luciano, Michelle; Marioni, Riccardo E; Hernández, Maria Valdés; Maniega, Susana Munoz; Hamilton, Iona F; Royle, Natalie A.; Scotland, Generation; Chauhan, Ganesh; Bis, Joshua C.; Debette, Stephanie; DeCarli, Charles; Fornage, Myriam; Schmidt, Reinhold; Ikram, M. Arfan; Launer, Lenore J.; Seshadri, Sudha; Bastin, Mark E.; Porteous, David J.; Wardlaw, Joanna; Deary, Ian J

2016-01-01

Structural brain magnetic resonance imaging (MRI) traits share part of their genetic variance with cognitive traits. Here, we use genetic association results from large meta-analytic studies of genome-wide association for brain infarcts, white matter hyperintensities, intracranial, hippocampal and total brain volumes to estimate polygenic scores for these traits in three Scottish samples: Generation Scotland: Scottish Family Health Study (GS:SFHS), and the Lothian Birth Cohorts of 1936 (LBC1936) and 1921 (LBC1921). These five brain MRI trait polygenic scores were then used to 1) predict corresponding MRI traits in the LBC1936 (numbers ranged 573 to 630 across traits) and 2) predict cognitive traits in all three cohorts (in 8,115 to 8,250 persons). In the LBC1936, all MRI phenotypic traits were correlated with at least one cognitive measure; and polygenic prediction of MRI traits was observed for intracranial volume. Meta-analysis of the correlations between MRI polygenic scores and cognitive traits revealed a significant negative correlation (maximal r=0.08) between the hippocampal volume polygenic score and measures of global cognitive ability collected in childhood and in old age in the Lothian Birth Cohorts. The lack of association to a related general cognitive measure when including the GS:SFHS points to either type 1 error or the importance of using prediction samples that closely match the demographics of the genome-wide association samples from which prediction is based. Ideally, these analyses should be repeated in larger samples with data on both MRI and cognition, and using MRI GWA results from even larger meta-analysis studies. PMID:26427786

A Natural Language Processing-based Model to Automate MRI Brain Protocol Selection and Prioritization.

PubMed

Brown, Andrew D; Marotta, Thomas R

2017-02-01

Incorrect imaging protocol selection can contribute to increased healthcare cost and waste. To help healthcare providers improve the quality and safety of medical imaging services, we developed and evaluated three natural language processing (NLP) models to determine whether NLP techniques could be employed to aid in clinical decision support for protocoling and prioritization of magnetic resonance imaging (MRI) brain examinations. To test the feasibility of using an NLP model to support clinical decision making for MRI brain examinations, we designed three different medical imaging prediction tasks, each with a unique outcome: selecting an examination protocol, evaluating the need for contrast administration, and determining priority. We created three models for each prediction task, each using a different classification algorithm-random forest, support vector machine, or k-nearest neighbor-to predict outcomes based on the narrative clinical indications and demographic data associated with 13,982 MRI brain examinations performed from January 1, 2013 to June 30, 2015. Test datasets were used to calculate the accuracy, sensitivity and specificity, predictive values, and the area under the curve. Our optimal results show an accuracy of 82.9%, 83.0%, and 88.2% for the protocol selection, contrast administration, and prioritization tasks, respectively, demonstrating that predictive algorithms can be used to aid in clinical decision support for examination protocoling. NLP models developed from the narrative clinical information provided by referring clinicians and demographic data are feasible methods to predict the protocol and priority of MRI brain examinations. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

First steps in using machine learning on fMRI data to predict intrusive memories of traumatic film footage

PubMed Central

Clark, Ian A.; Niehaus, Katherine E.; Duff, Eugene P.; Di Simplicio, Martina C.; Clifford, Gari D.; Smith, Stephen M.; Mackay, Clare E.; Woolrich, Mark W.; Holmes, Emily A.

2014-01-01

After psychological trauma, why do some only some parts of the traumatic event return as intrusive memories while others do not? Intrusive memories are key to cognitive behavioural treatment for post-traumatic stress disorder, and an aetiological understanding is warranted. We present here analyses using multivariate pattern analysis (MVPA) and a machine learning classifier to investigate whether peri-traumatic brain activation was able to predict later intrusive memories (i.e. before they had happened). To provide a methodological basis for understanding the context of the current results, we first show how functional magnetic resonance imaging (fMRI) during an experimental analogue of trauma (a trauma film) via a prospective event-related design was able to capture an individual's later intrusive memories. Results showed widespread increases in brain activation at encoding when viewing a scene in the scanner that would later return as an intrusive memory in the real world. These fMRI results were replicated in a second study. While traditional mass univariate regression analysis highlighted an association between brain processing and symptomatology, this is not the same as prediction. Using MVPA and a machine learning classifier, it was possible to predict later intrusive memories across participants with 68% accuracy, and within a participant with 97% accuracy; i.e. the classifier could identify out of multiple scenes those that would later return as an intrusive memory. We also report here brain networks key in intrusive memory prediction. MVPA opens the possibility of decoding brain activity to reconstruct idiosyncratic cognitive events with relevance to understanding and predicting mental health symptoms. PMID:25151915

Learning during processing Word learning doesn’t wait for word recognition to finish

PubMed Central

Apfelbaum, Keith S.; McMurray, Bob

2017-01-01

Previous research on associative learning has uncovered detailed aspects of the process, including what types of things are learned, how they are learned, and where in the brain such learning occurs. However, perceptual processes, such as stimulus recognition and identification, take time to unfold. Previous studies of learning have not addressed when, during the course of these dynamic recognition processes, learned representations are formed and updated. If learned representations are formed and updated while recognition is ongoing, the result of learning may incorporate spurious, partial information. For example, during word recognition, words take time to be identified, and competing words are often active in parallel. If learning proceeds before this competition resolves, representations may be influenced by the preliminary activations present at the time of learning. In three experiments using word learning as a model domain, we provide evidence that learning reflects the ongoing dynamics of auditory and visual processing during a learning event. These results show that learning can occur before stimulus recognition processes are complete; learning does not wait for ongoing perceptual processing to complete. PMID:27471082

Microglial migration and interactions with dendrimer nanoparticles are altered in the presence of neuroinflammation.

PubMed

Zhang, Fan; Nance, Elizabeth; Alnasser, Yossef; Kannan, Rangaramanujam; Kannan, Sujatha

2016-03-22

Microglial cells have been implicated in neuroinflammation-mediated injury in the brain, including neurodevelopmental disorders such as cerebral palsy (CP) and autism. Pro-inflammatory activation of microglial cells results in the impairment of their neuroprotective functions, leading to an exaggerated, ongoing immune dysregulation that can persist long after the initial insult. We have previously shown that dendrimer-mediated delivery of an anti-inflammatory agent can attenuate inflammation in a rabbit model of maternal inflammation-induced CP and significantly improve the motor phenotype, due to the ability of the dendrimer to selectively localize in activated microglia. To elucidate the interactions between dendrimers and microglia, we created an organotypic whole-hemisphere brain slice culture model from newborn rabbits with and without exposure to inflammation in utero. We then used this model to analyze the dynamics of microglial migration and their interactions with dendrimers in the presence of neuroinflammation. Microglial cells in animals with CP had an amoeboid morphology and impaired cell migration, demonstrated by decreased migration distance and velocity when compared to cells in healthy, age-matched controls. However, this decreased migration was associated with a greater, more rapid dendrimer uptake compared to microglial cells from healthy controls. This study demonstrates that maternal intrauterine inflammation is associated with impaired microglial function and movement in the newborn brain. This microglial impairment may play a role in the development of ongoing brain injury and CP in the offspring. Increased uptake of dendrimers by the "impaired" microglia can be exploited to deliver drugs specifically to these cells and modulate their functions. Host tissue and target cell characteristics are important aspects to be considered in the design and evaluation of targeted dendrimer-based nanotherapeutics for improved and sustained efficacy. This ex vivo model also provides a rapid screening tool for evaluation of the effects of various therapies on microglial function.

The PD-1 pathway as a therapeutic target to overcome immune escape mechanisms in cancer.

PubMed

Henick, Brian S; Herbst, Roy S; Goldberg, Sarah B

2014-12-01

Immunotherapy is emerging as a powerful approach in cancer treatment. Preclinical data predicted the antineoplastic effects seen in clinical trials of programmed death-1 (PD-1) pathway inhibitors, as well as their observed toxicities. The results of early clinical trials are extraordinarily promising in several cancer types and have shaped the direction of ongoing and future studies. This review describes the biological rationale for targeting the PD-1 pathway with monoclonal antibodies for the treatment of cancer as a context for examining the results of early clinical trials. It also surveys the landscape of ongoing clinical trials and discusses their anticipated strengths and limitations. PD-1 pathway inhibition represents a new frontier in cancer immunotherapy, which shows clear evidence of activity in various tumor types including NSCLC and melanoma. Ongoing and upcoming trials will examine optimal combinations of these agents, which should further define their role across tumor types. Current limitations include the absence of a reliable companion diagnostic to predict likely responders, as well as lack of data in early-stage cancer when treatment has the potential to increase cure rates.

A comparison of transfer-appropriate processing and multi-process frameworks for prospective memory performance.

PubMed

McBride, Dawn M; Abney, Drew H

2012-01-01

We examined multi-process (MP) and transfer-appropriate processing descriptions of prospective memory (PM). Three conditions were compared that varied the overlap in processing type (perceptual/conceptual) between the ongoing and PM tasks such that two conditions involved a match of perceptual processing and one condition involved a mismatch in processing (conceptual ongoing task/perceptual PM task). One of the matched processing conditions also created a focal PM task, whereas the other two conditions were considered non-focal (Einstein & McDaniel, 2005). PM task accuracy and ongoing task completion speed in baseline and PM task conditions were measured. Accuracy results indicated a higher PM task completion rate for the focal condition than the non-focal conditions, a finding that is consistent with predictions made by the MP view. However, reaction time (RT) analyses indicated that PM task cost did not differ across conditions when practice effects are considered. Thus, the PM accuracy results are consistent with a MP description of PM, but RT results did not support the MP view predictions regarding PM cost.

Remote Associates Test and Alpha Brain Waves

ERIC Educational Resources Information Center

Haarmann, Henk J.; George, Timothy; Smaliy, Alexei; Dien, Joseph

2012-01-01

Previous studies found that performance on the remote associates test (RAT) improves after a period of incubation and that increased alpha brain waves over the right posterior brain predict the emergence of RAT insight solutions. We report an experiment that tested whether increased alpha brain waves during incubation improve RAT performance.…

Pre-stimulus EEG oscillations correlate with perceptual alternation of speech forms.

PubMed

Barraza, Paulo; Jaume-Guazzini, Francisco; Rodríguez, Eugenio

2016-05-27

Speech perception is often seen as a passive process guided by physical stimulus properties. However, ongoing brain dynamics could influence the subsequent perceptual organization of the speech, to an as yet unknown extent. To elucidate this issue, we analyzed EEG oscillatory activity before and immediately after the repetitive auditory presentation of words inducing the so-called verbal transformation effect (VTE), or spontaneous alternation of meanings due to its rapid repetition. Subjects indicated whether the meaning of the bistable word changed or not. For the Reversal more than for the Stable condition, results show a pre-stimulus local alpha desynchronization (300-50ms), followed by an early post-stimulus increase of local beta synchrony (0-80ms), and then a late increase and decrease of local alpha (200-340ms) and beta (360-440ms) synchrony respectively. Additionally, the ERPs showed that reversal positivity (RP) and reversal negativity components (RN), along with a late positivity complex (LPC) correlate with switching between verbal forms. Our results show how the ongoing dynamics brain is actively involved in the perceptual organization of the speech, destabilizing verbal perceptual states, and facilitating the perceptual regrouping of the elements composing the linguistic auditory stimulus. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Invasive Cortical Stimulation to Promote Recovery of Function After Stroke

PubMed Central

Plow, Ela B.; Carey, James R.; Nudo, Randolph J.; Pascual-Leone, Alvaro

2011-01-01

Background and Purpose Residual motor deficits frequently linger after stroke. Search for newer effective strategies to promote functional recovery is ongoing. Brain stimulation, as a means of directing adaptive plasticity, is appealing. Animal studies and Phase I and II trials in humans have indicated safety, feasibility, and efficacy of combining rehabilitation and concurrent invasive cortical stimulation. However, a recent Phase III trial showed no advantage of the combination. We critically review results of various trials and discuss the factors that contributed to the distinctive result. Summary of Review Regarding cortical stimulation, it is important to determine the (1) location of peri-infarct representations by integrating multiple neuroanatomical and physiological techniques; (2) role of other mechanisms of stroke recovery; (3) viability of peri-infarct tissue and descending pathways; (4) lesion geometry to ensure no alteration/displacement of current density; and (5) applicability of lessons generated from noninvasive brain stimulation studies in humans. In terms of combining stimulation with rehabilitation, we should understand (1) the principle of homeostatic plasticity; (2) the effect of ongoing cortical activity and phases of learning; and (3) that subject-specific intervention may be necessary. Conclusions Future cortical stimulation trials should consider the factors that may have contributed to the peculiar results of the Phase III trial and address those in future study designs. PMID:19359643

Implementing a Primary Healthcare Framework: The Importance of Nursing Leadership in Developing and Maintaining a Brain Tumor Support Group.

PubMed

Nichols, Linda J; Wright, Kylie M

2015-08-01

Although brain tumor support groups have been available internationally for many years, Liverpool Hospital in Australia has not traditionally provided this service. As a leadership initiative, the development of a brain tumor support group that incorporates a primary healthcare framework is a sustainable approach that showcases the role of nursing leaders in changing attitudes and improving outcomes. The purpose of this review of the literature and reflection of clinical experience is to explore nursing leadership within brain tumor-specific support groups. This article will showcase a nurse-led group that incorporated a coordinated approach to delivering patient-centered care. The initiation of activities and interventions that reflected the five tenets of primary health care resulted in improved outcomes for individuals and their family caregivers throughout the trajectory of their illness. Vital to the success of this project was moving from a standalone leader to building collective and collaborative leadership more conducive to facilitating change. The support group successfully demonstrated that individuals and family caregivers may see ongoing and long-term improvements during and following treatment.

Imagine All the People: How the Brain Creates and Uses Personality Models to Predict Behavior

PubMed Central

Hassabis, Demis; Spreng, R. Nathan; Rusu, Andrei A.; Robbins, Clifford A.; Mar, Raymond A.; Schacter, Daniel L.

2014-01-01

The behaviors of other people are often central to envisioning the future. The ability to accurately predict the thoughts and actions of others is essential for successful social interactions, with far-reaching consequences. Despite its importance, little is known about how the brain represents people in order to predict behavior. In this functional magnetic resonance imaging study, participants learned the unique personality of 4 protagonists and imagined how each would behave in different scenarios. The protagonists' personalities were composed of 2 traits: Agreeableness and Extraversion. Which protagonist was being imagined was accurately inferred based solely on activity patterns in the medial prefrontal cortex using multivariate pattern classification, providing novel evidence that brain activity can reveal whom someone is thinking about. Lateral temporal and posterior cingulate cortex discriminated between different degrees of agreeableness and extraversion, respectively. Functional connectivity analysis confirmed that regions associated with trait-processing and individual identities were functionally coupled. Activity during the imagination task, and revealed by functional connectivity, was consistent with the default network. Our results suggest that distinct regions code for personality traits, and that the brain combines these traits to represent individuals. The brain then uses this “personality model” to predict the behavior of others in novel situations. PMID:23463340

Work environment stressors, social support, anxiety, and depression among secondary school teachers.

PubMed

Mahan, Pamela L; Mahan, Michael P; Park, Na-Jin; Shelton, Christie; Brown, Kathleen C; Weaver, Michael T

2010-05-01

Work environment stress, a salient health and safety issue for secondary school teachers, school administrators, parents, and students, was examined in 168 teachers from two urban and five suburban high schools. The purpose of this study was to examine relationships between ongoing and episodic stressors and anxiety and depression, as well as the extent to which anxiety and depression may be predicted by stressors and coworker and supervisor support. The Ongoing Stressor Scale (OSS) and the Episodic Stressor Scale (ESS), the Coworker and Supervisor Contents of Communication Scales (COCS), the State Anxiety inventory (S-Anxiety), and the Center for Epidemiological Studies Depression Scale (CES-D) were used to measure the variables. Ongoing and episodic stressors were significantly and positively associated with anxiety and depression. Ongoing stressors and coworker support were significant in explaining anxiety and depression among secondary school teachers. Coworker support had an inverse relationship to anxiety and depression.

The Role of Feedback in the Assimilation of Information in Prediction Markets

ERIC Educational Resources Information Center

Jolly, Richard Donald

2011-01-01

Leveraging the knowledge of an organization is an ongoing challenge that has given rise to the field of knowledge management. Yet, despite spending enormous sums of organizational resources on Information Technology (IT) systems, executives recognize there is much more knowledge to harvest. Prediction markets are emerging as one tool to help…

c-Fos expression predicts long-term social memory retrieval in mice.

PubMed

Lüscher Dias, Thomaz; Fernandes Golino, Hudson; Moura de Oliveira, Vinícius Elias; Dutra Moraes, Márcio Flávio; Schenatto Pereira, Grace

2016-10-15

The way the rodent brain generally processes socially relevant information is rather well understood. How social information is stored into long-term social memory, however, is still under debate. Here, brain c-Fos expression was measured after adult mice were exposed to familiar or novel juveniles and expression was compared in several memory and socially relevant brain areas. Machine Learning algorithm Random Forest was then used to predict the social interaction category of adult mice based on c-Fos expression in these areas. Interaction with a familiar co-specific altered brain activation in the olfactory bulb, amygdala, hippocampus, lateral septum and medial prefrontal cortex. Remarkably, Random Forest was able to predict interaction with a familiar juvenile with 100% accuracy. Activity in the olfactory bulb, amygdala, hippocampus and the medial prefrontal cortex were crucial to this prediction. From our results, we suggest long-term social memory depends on initial social olfactory processing in the medial amygdala and its output connections synergistically with non-social contextual integration by the hippocampus and medial prefrontal cortex top-down modulation of primary olfactory structures. Copyright © 2016 Elsevier B.V. All rights reserved.

Accelerated Changes in Cortical Thickness Measurements with Age in Military Service Members with Traumatic Brain Injury.

PubMed

Savjani, Ricky R; Taylor, Brian A; Acion, Laura; Wilde, Elisabeth A; Jorge, Ricardo E

2017-11-15

Finding objective and quantifiable imaging markers of mild traumatic brain injury (TBI) has proven challenging, especially in the military population. Changes in cortical thickness after injury have been reported in animals and in humans, but it is unclear how these alterations manifest in the chronic phase, and it is difficult to characterize accurately with imaging. We used cortical thickness measures derived from Advanced Normalization Tools (ANTs) to predict a continuous demographic variable: age. We trained four different regression models (linear regression, support vector regression, Gaussian process regression, and random forests) to predict age from healthy control brains from publicly available datasets (n = 762). We then used these models to predict brain age in military Service Members with TBI (n = 92) and military Service Members without TBI (n = 34). Our results show that all four models overpredicted age in Service Members with TBI, and the predicted age difference was significantly greater compared with military controls. These data extend previous civilian findings and show that cortical thickness measures may reveal an association of accelerated changes over time with military TBI.

Individual differences in intrinsic brain connectivity predict decision strategy.

PubMed

Barnes, Kelly Anne; Anderson, Kevin M; Plitt, Mark; Martin, Alex

2014-10-15

When humans are provided with ample time to make a decision, individual differences in strategy emerge. Using an adaptation of a well-studied decision making paradigm, motion direction discrimination, we probed the neural basis of individual differences in strategy. We tested whether strategies emerged from moment-to-moment reconfiguration of functional brain networks involved in decision making with task-evoked functional MRI (fMRI) and whether intrinsic properties of functional brain networks, measured at rest with functional connectivity MRI (fcMRI), were associated with strategy use. We found that human participants reliably selected one of two strategies across 2 days of task performance, either continuously accumulating evidence or waiting for task difficulty to decrease. Individual differences in decision strategy were predicted both by the degree of task-evoked activation of decision-related brain regions and by the strength of pretask correlated spontaneous brain activity. These results suggest that spontaneous brain activity constrains strategy selection on perceptual decisions.

Two Dimensional Finite Element Analysis for the Effect of a Pressure Wave in the Human Brain

NASA Astrophysics Data System (ADS)

Ponce L., Ernesto; Ponce S., Daniel

2008-11-01

Brain injuries in people of all ages is a serious, world-wide health problem, with consequences as varied as attention or memory deficits, difficulties in problem-solving, aggressive social behavior, and neuro degenerative diseases such as Alzheimer's and Parkinson's. Brain injuries can be the result of a direct impact, but also pressure waves and direct impulses. The aim of this work is to develop a predictive method to calculate the stress generated in the human brain by pressure waves such as high power sounds. The finite element method is used, combined with elastic wave theory. The predictions of the generated stress levels are compared with the resistance of the arterioles that pervade the brain. The problem was focused to the Chilean mining where there are some accidents happen by detonations and high sound level. There are not formal medical investigation, however these pressure waves could produce human brain damage.

T2 Relaxometry MRI Predicts Cerebral Palsy in Preterm Infants.

PubMed

Chen, L-W; Wang, S-T; Huang, C-C; Tu, Y-F; Tsai, Y-S

2018-01-18

T2-relaxometry brain MR imaging enables objective measurement of brain maturation based on the water-macromolecule ratio in white matter, but the outcome correlation is not established in preterm infants. Our study aimed to predict neurodevelopment with T2-relaxation values of brain MR imaging among preterm infants. From January 1, 2012, to May 31, 2015, preterm infants who underwent both T2-relaxometry brain MR imaging and neurodevelopmental follow-up were retrospectively reviewed. T2-relaxation values were measured over the periventricular white matter, including sections through the frontal horns, midbody of the lateral ventricles, and centrum semiovale. Periventricular T2 relaxometry in relation to corrected age was analyzed with restricted cubic spline regression. Prediction of cerebral palsy was examined with the receiver operating characteristic curve. Thirty-eight preterm infants were enrolled for analysis. Twenty patients (52.6%) had neurodevelopmental abnormalities, including 8 (21%) with developmental delay without cerebral palsy and 12 (31.6%) with cerebral palsy. The periventricular T2-relaxation values in relation to age were curvilinear in preterm infants with normal development, linear in those with developmental delay without cerebral palsy, and flat in those with cerebral palsy. When MR imaging was performed at >1 month corrected age, cerebral palsy could be predicted with T2 relaxometry of the periventricular white matter on sections through the midbody of the lateral ventricles (area under the receiver operating characteristic curve = 0.738; cutoff value of >217.4 with 63.6% sensitivity and 100.0% specificity). T2-relaxometry brain MR imaging could provide prognostic prediction of neurodevelopmental outcomes in premature infants. Age-dependent and area-selective interpretation in preterm brains should be emphasized. © 2018 by American Journal of Neuroradiology.

Brain Regional Blood Flow and Working Memory Performance Predict Change in Blood Pressure Over 2 Years.

PubMed

Jennings, J Richard; Heim, Alicia F; Sheu, Lei K; Muldoon, Matthew F; Ryan, Christopher; Gach, H Michael; Schirda, Claudiu; Gianaros, Peter J

2017-12-01

Hypertension is a presumptive risk factor for premature cognitive decline. However, lowering blood pressure (BP) does not uniformly reverse cognitive decline, suggesting that high BP per se may not cause cognitive decline. We hypothesized that essential hypertension has initial effects on the brain that, over time, manifest as cognitive dysfunction in conjunction with both brain vascular abnormalities and systemic BP elevation. Accordingly, we tested whether neuropsychological function and brain blood flow responses to cognitive challenges among prehypertensive individuals would predict subsequent progression of BP. Midlife adults (n=154; mean age, 49; 45% men) with prehypertensive BP underwent neuropsychological testing and assessment of regional cerebral blood flow (rCBF) response to cognitive challenges. Neuropsychological performance measures were derived for verbal and logical memory (memory), executive function, working memory, mental efficiency, and attention. A pseudo-continuous arterial spin labeling magnetic resonance imaging sequence compared rCBF responses with control and active phases of cognitive challenges. Brain areas previously associated with BP were grouped into composites for frontoparietal, frontostriatal, and insular-subcortical rCBF areas. Multiple regression models tested whether BP after 2 years was predicted by initial BP, initial neuropsychological scores, and initial rCBF responses to cognitive challenge. The neuropsychological composite of working memory (standardized beta, -0.276; se=0.116; P =0.02) and the frontostriatal rCBF response to cognitive challenge (standardized beta, 0.234; se=0.108; P =0.03) significantly predicted follow-up BP. Initial BP failed to significantly predict subsequent cognitive performance or rCBF. Changes in brain function may precede or co-occur with progression of BP toward hypertensive levels in midlife. © 2017 American Heart Association, Inc.

Predicting human age using regional morphometry and inter-regional morphological similarity

NASA Astrophysics Data System (ADS)

Wang, Xun-Heng; Li, Lihua

2016-03-01

The goal of this study is predicting human age using neuro-metrics derived from structural MRI, as well as investigating the relationships between age and predictive neuro-metrics. To this end, a cohort of healthy subjects were recruited from 1000 Functional Connectomes Project. The ages of the participations were ranging from 7 to 83 (36.17+/-20.46). The structural MRI for each subject was preprocessed using FreeSurfer, resulting in regional cortical thickness, mean curvature, regional volume and regional surface area for 148 anatomical parcellations. The individual age was predicted from the combination of regional and inter-regional neuro-metrics. The prediction accuracy is r = 0.835, p < 0.00001, evaluated by Pearson correlation coefficient between predicted ages and actual ages. Moreover, the LASSO linear regression also found certain predictive features, most of which were inter-regional features. The turning-point of the developmental trajectories in human brain was around 40 years old based on regional cortical thickness. In conclusion, structural MRI could be potential biomarkers for the aging in human brain. The human age could be successfully predicted from the combination of regional morphometry and inter-regional morphological similarity. The inter-regional measures could be beneficial to investigating human brain connectome.

Inferencing Processes After Right Hemisphere Brain Damage: Effects of Contextual Bias

PubMed Central

Blake, Margaret Lehman

2009-01-01

Purpose Comprehension deficits associated with right hemisphere brain damage (RHD) have been attributed to an inability to use context, but there is little direct evidence to support the claim. This study evaluated the effect of varying contextual bias on predictive inferencing by adults with RHD. Method Fourteen adults with no brain damage (NBD) and 14 with RHD read stories constructed with either high predictability or low predictability of a specific outcome. Reading time for a sentence that disconfirmed the target outcome was measured and compared with a control story context. Results Adults with RHD evidenced activation of predictive inferences only for highly predictive conditions, whereas NBD adults generated inferences in both high- and low-predictability stories. Adults with RHD were more likely than those with NBD to require additional time to integrate inferences in high-predictability conditions. The latter finding was related to working memory for the RHD group. Results are interpreted in light of previous findings obtained using the same stimuli. Conclusions RHD does not abolish the ability to use context. Evidence of predictive inferencing is influenced by task and strength of inference activation. Treatment considerations and cautions regarding interpreting results from one methodology are discussed. PMID:19252126

Predictions interact with missing sensory evidence in semantic processing areas.

PubMed

Scharinger, Mathias; Bendixen, Alexandra; Herrmann, Björn; Henry, Molly J; Mildner, Toralf; Obleser, Jonas

2016-02-01

Human brain function draws on predictive mechanisms that exploit higher-level context during lower-level perception. These mechanisms are particularly relevant for situations in which sensory information is compromised or incomplete, as for example in natural speech where speech segments may be omitted due to sluggish articulation. Here, we investigate which brain areas support the processing of incomplete words that were predictable from semantic context, compared with incomplete words that were unpredictable. During functional magnetic resonance imaging (fMRI), participants heard sentences that orthogonally varied in predictability (semantically predictable vs. unpredictable) and completeness (complete vs. incomplete, i.e. missing their final consonant cluster). The effects of predictability and completeness interacted in heteromodal semantic processing areas, including left angular gyrus and left precuneus, where activity did not differ between complete and incomplete words when they were predictable. The same regions showed stronger activity for incomplete than for complete words when they were unpredictable. The interaction pattern suggests that for highly predictable words, the speech signal does not need to be complete for neural processing in semantic processing areas. Hum Brain Mapp 37:704-716, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Decoding Spontaneous Emotional States in the Human Brain

PubMed Central

Kragel, Philip A.; Knodt, Annchen R.; Hariri, Ahmad R.; LaBar, Kevin S.

2016-01-01

Pattern classification of human brain activity provides unique insight into the neural underpinnings of diverse mental states. These multivariate tools have recently been used within the field of affective neuroscience to classify distributed patterns of brain activation evoked during emotion induction procedures. Here we assess whether neural models developed to discriminate among distinct emotion categories exhibit predictive validity in the absence of exteroceptive emotional stimulation. In two experiments, we show that spontaneous fluctuations in human resting-state brain activity can be decoded into categories of experience delineating unique emotional states that exhibit spatiotemporal coherence, covary with individual differences in mood and personality traits, and predict on-line, self-reported feelings. These findings validate objective, brain-based models of emotion and show how emotional states dynamically emerge from the activity of separable neural systems. PMID:27627738

Neural predictors of chocolate intake following chocolate exposure.

PubMed

Frankort, Astrid; Roefs, Anne; Siep, Nicolette; Roebroeck, Alard; Havermans, Remco; Jansen, Anita

2015-04-01

Previous studies have shown that one's brain response to high-calorie food cues can predict long-term weight gain or weight loss. The neural correlates that predict food intake in the short term have, however, hardly been investigated. This study examined which brain regions' activation predicts chocolate intake after participants had been either exposed to real chocolate or to control stimuli during approximately one hour, with interruptions for fMRI measurements. Further we investigated whether the variance in chocolate intake could be better explained by activated brain regions than by self-reported craving. In total, five brain regions correlated with subsequent chocolate intake. The activation of two reward regions (the right caudate and the left frontopolar cortex) correlated positively with intake in the exposure group. The activation of two regions associated with cognitive control (the left dorsolateral and left mid-dorsolateral PFC) correlated negatively with intake in the control group. When the regression analysis was conducted with the exposure and the control group together, an additional region's activation (the right anterior PFC) correlated positively with chocolate intake. In all analyses, the intake variance explained by neural correlates was above and beyond the variance explained by self-reported craving. These results are in line with neuroimaging research showing that brain responses are a better predictor of subsequent intake than self-reported craving. Therefore, our findings might provide for a missing link by associating brain activation, previously shown to predict weight change, with short-term intake. Copyright © 2014 Elsevier Ltd. All rights reserved.

Disruption to functional networks in neonates with perinatal brain injury predicts motor skills at 8 months.

PubMed

Linke, Annika C; Wild, Conor; Zubiaurre-Elorza, Leire; Herzmann, Charlotte; Duffy, Hester; Han, Victor K; Lee, David S C; Cusack, Rhodri

2018-01-01

Functional connectivity magnetic resonance imaging (fcMRI) of neonates with perinatal brain injury could improve prediction of motor impairment before symptoms manifest, and establish how early brain organization relates to subsequent development. This cohort study is the first to describe and quantitatively assess functional brain networks and their relation to later motor skills in neonates with a diverse range of perinatal brain injuries. Infants ( n  = 65, included in final analyses: n  = 53) were recruited from the neonatal intensive care unit (NICU) and were stratified based on their age at birth (premature vs. term), and on whether neuropathology was diagnosed from structural MRI. Functional brain networks and a measure of disruption to functional connectivity were obtained from 14 min of fcMRI acquired during natural sleep at term-equivalent age. Disruption to connectivity of the somatomotor and frontoparietal executive networks predicted motor impairment at 4 and 8 months. This disruption in functional connectivity was not found to be driven by differences between clinical groups, or by any of the specific measures we captured to describe the clinical course. fcMRI was predictive over and above other clinical measures available at discharge from the NICU, including structural MRI. Motor learning was affected by disruption to somatomotor networks, but also frontoparietal executive networks, which supports the functional importance of these networks in early development. Disruption to these two networks might be best addressed by distinct intervention strategies.

[CT scans in children with head/brain injury: five years after the revision of the guideline on "mild traumatic head/brain injury"].

PubMed

Hageman, G Gerard

2015-01-01

In 2010 the guideline on mild traumatic head/ brain injury for both adults and children was revised under the supervision of the Dutch Neurology Society. The revised guideline endorsed rules for decisions on whether to carry out diagnostic imaging investigations (brain CT scanning) and formulates indications for admission. Unfortunately, 5 years after its introduction, it is clear that the guideline rules result in excessive brain CT scanning, in which no more serious head injury is diagnosed. Brain injury may be present in (small) children even if symptoms are absent at first presentation. Also, clinical signs do not predict intracranial complications. This was nicely demonstrated in a study by Tilma, Bekhof and Brand of 410 children with mTBI: no clinical symptom or sign reliably predicted the risk of intracranial bleeding. They advise hospitalisation for observation instead of brain CT scanning. It may be necessary to review part of the Dutch guideline on mTBI.

Virtual reality and consciousness inference in dreaming.

PubMed

Hobson, J Allan; Hong, Charles C-H; Friston, Karl J

2014-01-01

This article explores the notion that the brain is genetically endowed with an innate virtual reality generator that - through experience-dependent plasticity - becomes a generative or predictive model of the world. This model, which is most clearly revealed in rapid eye movement (REM) sleep dreaming, may provide the theater for conscious experience. Functional neuroimaging evidence for brain activations that are time-locked to rapid eye movements (REMs) endorses the view that waking consciousness emerges from REM sleep - and dreaming lays the foundations for waking perception. In this view, the brain is equipped with a virtual model of the world that generates predictions of its sensations. This model is continually updated and entrained by sensory prediction errors in wakefulness to ensure veridical perception, but not in dreaming. In contrast, dreaming plays an essential role in maintaining and enhancing the capacity to model the world by minimizing model complexity and thereby maximizing both statistical and thermodynamic efficiency. This perspective suggests that consciousness corresponds to the embodied process of inference, realized through the generation of virtual realities (in both sleep and wakefulness). In short, our premise or hypothesis is that the waking brain engages with the world to predict the causes of sensations, while in sleep the brain's generative model is actively refined so that it generates more efficient predictions during waking. We review the evidence in support of this hypothesis - evidence that grounds consciousness in biophysical computations whose neuronal and neurochemical infrastructure has been disclosed by sleep research.

Spatial analysis and high resolution mapping of the human whole-brain transcriptome for integrative analysis in neuroimaging.

PubMed

Gryglewski, Gregor; Seiger, René; James, Gregory Miles; Godbersen, Godber Mathis; Komorowski, Arkadiusz; Unterholzner, Jakob; Michenthaler, Paul; Hahn, Andreas; Wadsak, Wolfgang; Mitterhauser, Markus; Kasper, Siegfried; Lanzenberger, Rupert

2018-08-01

The quantification of big pools of diverse molecules provides important insights on brain function, but is often restricted to a limited number of observations, which impairs integration with other modalities. To resolve this issue, a method allowing for the prediction of mRNA expression in the entire brain based on microarray data provided in the Allen Human Brain Atlas was developed. Microarray data of 3702 samples from 6 brain donors was registered to MNI and cortical surface space using FreeSurfer. For each of 18,686 genes, spatial dependence of transcription was assessed using variogram modelling. Variogram models were employed in Gaussian process regression to calculate best linear unbiased predictions for gene expression at all locations represented in well-established imaging atlases for cortex, subcortical structures and cerebellum. For validation, predicted whole-brain transcription of the HTR1A gene was correlated with [carbonyl- 11 C]WAY-100635 positron emission tomography data collected from 30 healthy subjects. Prediction results showed minimal bias ranging within ±0.016 (cortical surface), ±0.12 (subcortical regions) and ±0.14 (cerebellum) in units of log2 expression intensity for all genes. Across genes, the correlation of predicted and observed mRNA expression in leave-one-out cross-validation correlated with the strength of spatial dependence (cortical surface: r = 0.91, subcortical regions: r = 0.85, cerebellum: r = 0.84). 816 out of 18,686 genes exhibited a high spatial dependence accounting for more than 50% of variance in the difference of gene expression on the cortical surface. In subcortical regions and cerebellum, different sets of genes were implicated by high spatially structured variability. For the serotonin 1A receptor, correlation between PET binding potentials and predicted comprehensive mRNA expression was markedly higher (Spearman ρ = 0.72 for cortical surface, ρ = 0.84 for subcortical regions) than correlation of PET and discrete samples only (ρ = 0.55 and ρ = 0.63, respectively). Prediction of mRNA expression in the entire human brain allows for intuitive visualization of gene transcription and seamless integration in multimodal analysis without bias arising from non-uniform distribution of available samples. Extension of this methodology promises to facilitate translation of omics research and enable investigation of human brain function at a systems level. Copyright © 2018 Elsevier Inc. All rights reserved.

Investigation of blast-induced traumatic brain injury.

PubMed

Taylor, Paul A; Ludwigsen, John S; Ford, Corey C

2014-01-01

Many troops deployed in Iraq and Afghanistan have sustained blast-related, closed-head injuries from being within non-lethal distance of detonated explosive devices. Little is known, however, about the mechanisms associated with blast exposure that give rise to traumatic brain injury (TBI). This study attempts to identify the precise conditions of focused stress wave energy within the brain, resulting from blast exposure, which will correlate with a threshold for persistent brain injury. This study developed and validated a set of modelling tools to simulate blast loading to the human head. Using these tools, the blast-induced, early-time intracranial wave motions that lead to focal brain damage were simulated. The simulations predict the deposition of three distinct wave energy components, two of which can be related to injury-inducing mechanisms, namely cavitation and shear. Furthermore, the results suggest that the spatial distributions of these damaging energy components are independent of blast direction. The predictions reported herein will simplify efforts to correlate simulation predictions with clinical measures of TBI and aid in the development of protective headwear.

Investigation of blast-induced traumatic brain injury

PubMed Central

Ludwigsen, John S.; Ford, Corey C.

2014-01-01

Objective Many troops deployed in Iraq and Afghanistan have sustained blast-related, closed-head injuries from being within non-lethal distance of detonated explosive devices. Little is known, however, about the mechanisms associated with blast exposure that give rise to traumatic brain injury (TBI). This study attempts to identify the precise conditions of focused stress wave energy within the brain, resulting from blast exposure, which will correlate with a threshold for persistent brain injury. Methods This study developed and validated a set of modelling tools to simulate blast loading to the human head. Using these tools, the blast-induced, early-time intracranial wave motions that lead to focal brain damage were simulated. Results The simulations predict the deposition of three distinct wave energy components, two of which can be related to injury-inducing mechanisms, namely cavitation and shear. Furthermore, the results suggest that the spatial distributions of these damaging energy components are independent of blast direction. Conclusions The predictions reported herein will simplify efforts to correlate simulation predictions with clinical measures of TBI and aid in the development of protective headwear. PMID:24766453

Prospective Design of Anti‐Transferrin Receptor Bispecific Antibodies for Optimal Delivery into the Human Brain

PubMed Central

Kanodia, JS; Gadkar, K; Bumbaca, D; Zhang, Y; Tong, RK; Luk, W; Hoyte, K; Lu, Y; Wildsmith, KR; Couch, JA; Watts, RJ; Dennis, MS; Ernst, JA; Scearce‐Levie, K; Atwal, JK; Joseph, S

2016-01-01

Anti‐transferrin receptor (TfR)‐based bispecific antibodies have shown promise for boosting antibody uptake in the brain. Nevertheless, there are limited data on the molecular properties, including affinity required for successful development of TfR‐based therapeutics. A complex nonmonotonic relationship exists between affinity of the anti‐TfR arm and brain uptake at therapeutically relevant doses. However, the quantitative nature of this relationship and its translatability to humans is heretofore unexplored. Therefore, we developed a mechanistic pharmacokinetic‐pharmacodynamic (PK‐PD) model for bispecific anti‐TfR/BACE1 antibodies that accounts for antibody‐TfR interactions at the blood‐brain barrier (BBB) as well as the pharmacodynamic (PD) effect of anti‐BACE1 arm. The calibrated model correctly predicted the optimal anti‐TfR affinity required to maximize brain exposure of therapeutic antibodies in the cynomolgus monkey and was scaled to predict the optimal affinity of anti‐TfR bispecifics in humans. Thus, this model provides a framework for testing critical translational predictions for anti‐TfR bispecific antibodies, including choice of candidate molecule for clinical development. PMID:27299941

From Vivaldi to Beatles and back: predicting lateralized brain responses to music.

PubMed

Alluri, Vinoo; Toiviainen, Petri; Lund, Torben E; Wallentin, Mikkel; Vuust, Peter; Nandi, Asoke K; Ristaniemi, Tapani; Brattico, Elvira

2013-12-01

We aimed at predicting the temporal evolution of brain activity in naturalistic music listening conditions using a combination of neuroimaging and acoustic feature extraction. Participants were scanned using functional Magnetic Resonance Imaging (fMRI) while listening to two musical medleys, including pieces from various genres with and without lyrics. Regression models were built to predict voxel-wise brain activations which were then tested in a cross-validation setting in order to evaluate the robustness of the hence created models across stimuli. To further assess the generalizability of the models we extended the cross-validation procedure by including another dataset, which comprised continuous fMRI responses of musically trained participants to an Argentinean tango. Individual models for the two musical medleys revealed that activations in several areas in the brain belonging to the auditory, limbic, and motor regions could be predicted. Notably, activations in the medial orbitofrontal region and the anterior cingulate cortex, relevant for self-referential appraisal and aesthetic judgments, could be predicted successfully. Cross-validation across musical stimuli and participant pools helped identify a region of the right superior temporal gyrus, encompassing the planum polare and the Heschl's gyrus, as the core structure that processed complex acoustic features of musical pieces from various genres, with or without lyrics. Models based on purely instrumental music were able to predict activation in the bilateral auditory cortices, parietal, somatosensory, and left hemispheric primary and supplementary motor areas. The presence of lyrics on the other hand weakened the prediction of activations in the left superior temporal gyrus. Our results suggest spontaneous emotion-related processing during naturalistic listening to music and provide supportive evidence for the hemispheric specialization for categorical sounds with realistic stimuli. We herewith introduce a powerful means to predict brain responses to music, speech, or soundscapes across a large variety of contexts. © 2013.

Stimulation of the nervous system for the management of seizures: current and future developments.

PubMed

Murphy, Jerome V; Patil, Arunangelo

2003-01-01

Vagal nerve stimulation (VNS) for the treatment of refractory epilepsy appears to have started from the theory that since VNS can alter the EEG, it may influence epilepsy. It proved effective in several models of epilepsy and was then tried in short-term, open-label and double-blind trials, leading to approval in Canada, Europe and the US. Follow-up observations in these patients demonstrated continued improvement in seizure control for up to 2 years. Close to 50% of treated patients have achieved at least a 50% reduction in seizure frequency. This therapy was also useful as rescue therapy for ongoing seizures in some patients; many patients are more alert. The initial trials were completed in patients >/=12 years of age with refractory partial seizures. Subsequently, similar benefits were shown in patients with tuberous sclerosis complex, Lennox-Gastaut syndrome, hypothalamic hamartomas and primary generalised seizures. Implanting the generator and leads is technically easy, and complications are few. The method of action is largely unknown, although VNS appears to alter metabolic activity in specific brain nuclei. Considering that improvement in mood is frequently found in patients using VNS, it has undergone trials in patients with depression. Other illnesses deserving exploration with this unusual therapy are Alzheimer's disease and autism. Some aspects of VNS have proven disappointing. Although patients have fewer seizures, the number of antiepileptic drugs they take is not significantly reduced. In addition, there is no way to accurately predict the end of life of the generator. Optimal stimulation parameters, if they exist, are unknown. Deep brain stimulation is a new method for controlling medically refractory seizures. It is based on the observation that thalamic stimulation can influence the EEG over a wide area. Several thalamic nuclei have been the object of stimulation in different groups of patients. Intraoperative brain imaging is essential for electrode placement. The procedure is done under local anaesthesia. Experience with this therapy is currently limited, but growing.

Single Subject Prediction of Brain Disorders in Neuroimaging: Promises and Pitfalls

PubMed Central

Arbabshirani, Mohammad R.; Plis, Sergey; Sui, Jing; Calhoun, Vince D.

2016-01-01

Neuroimaging-based single subject prediction of brain disorders has gained increasing attention in recent years. Using a variety of neuroimaging modalities such as structural, functional and diffusion MRI, along with machine learning techniques, hundreds of studies have been carried out for accurate classification of patients with heterogeneous mental and neurodegenerative disorders such as schizophrenia and Alzheimer's disease. More than 500 studies have been published during the past quarter century on single subject prediction focused on a multiple brain disorders. In the first part of this study, we provide a survey of more than 200 reports in this field with a focus on schizophrenia, mild cognitive impairment (MCI), Alzheimer's disease (AD), depressive disorders, autism spectrum disease (ASD) and attention-deficit hyperactivity disorder (ADHD). Detailed information about those studies such as sample size, type and number of extracted features and reported accuracy are summarized and discussed. To our knowledge, this is by far the most comprehensive review of neuroimaging-based single subject prediction of brain disorders. In the second part, we present our opinion on major pitfalls of those studies from a machine learning point of view. Common biases are discussed and suggestions are provided. Moreover, emerging trends such as decentralized data sharing, multimodal brain imaging, differential diagnosis, disease subtype classification and deep learning are also discussed. Based on this survey, there are extensive evidences showing the great potential of neuroimaging data for single subject prediction of various disorders. However, the main bottleneck of this exciting field is still the limited sample size, which could be potentially addressed by modern data sharing models such as the ones discussed in this paper. Emerging big data technologies and advanced data-intensive machine learning methodologies such as deep learning have coincided with an increasing need for accurate, robust and generalizable single subject prediction of brain disorders during an exciting time. In this report, we survey the past and offer some opinions regarding the road ahead. PMID:27012503

Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls.

PubMed

Arbabshirani, Mohammad R; Plis, Sergey; Sui, Jing; Calhoun, Vince D

2017-01-15

Neuroimaging-based single subject prediction of brain disorders has gained increasing attention in recent years. Using a variety of neuroimaging modalities such as structural, functional and diffusion MRI, along with machine learning techniques, hundreds of studies have been carried out for accurate classification of patients with heterogeneous mental and neurodegenerative disorders such as schizophrenia and Alzheimer's disease. More than 500 studies have been published during the past quarter century on single subject prediction focused on a multiple brain disorders. In the first part of this study, we provide a survey of more than 200 reports in this field with a focus on schizophrenia, mild cognitive impairment (MCI), Alzheimer's disease (AD), depressive disorders, autism spectrum disease (ASD) and attention-deficit hyperactivity disorder (ADHD). Detailed information about those studies such as sample size, type and number of extracted features and reported accuracy are summarized and discussed. To our knowledge, this is by far the most comprehensive review of neuroimaging-based single subject prediction of brain disorders. In the second part, we present our opinion on major pitfalls of those studies from a machine learning point of view. Common biases are discussed and suggestions are provided. Moreover, emerging trends such as decentralized data sharing, multimodal brain imaging, differential diagnosis, disease subtype classification and deep learning are also discussed. Based on this survey, there is extensive evidence showing the great potential of neuroimaging data for single subject prediction of various disorders. However, the main bottleneck of this exciting field is still the limited sample size, which could be potentially addressed by modern data sharing models such as the ones discussed in this paper. Emerging big data technologies and advanced data-intensive machine learning methodologies such as deep learning have coincided with an increasing need for accurate, robust and generalizable single subject prediction of brain disorders during an exciting time. In this report, we survey the past and offer some opinions regarding the road ahead. Copyright © 2016 Elsevier Inc. All rights reserved.

Joint Prediction of Longitudinal Development of Cortical Surfaces and White Matter Fibers from Neonatal MRI

PubMed Central

Rekik, Islem; Li, Gang; Yap, Pew-Thian; Chen, Geng; Lin, Weili; Shen, Dinggang

2017-01-01

The human brain can be modeled as multiple interrelated shapes (or a multishape), each for characterizing one aspect of the brain, such as the cortex and white matter pathways. Predicting the developing multishape is a very challenging task due to the contrasting nature of the developmental trajectories of the constituent shapes: smooth for the cortical surface and non-smooth for white matter tracts due to changes such as bifurcation. We recently addressed this problem and proposed an approach for predicting the multishape developmental spatiotemporal trajectories of infant brains based only on neonatal MRI data using a set of geometric, dynamic, and fiber-to-surface connectivity features. In this paper, we propose two key innovations to further improve the prediction of multishape evolution. First, for a more accurate cortical surface prediction, instead of simply relying on one neonatal atlas to guide the prediction of the multishape, we propose to use multiple neonatal atlases to build a spatially heterogeneous atlas using the multidirectional varifold representation. This individualizes the atlas by locally maximizing its similarity to the testing baseline cortical shape for each cortical region, thereby better representing the baseline testing cortical surface, which founds the multishape prediction process. Second, for temporally consistent fiber prediction, we propose to reliably estimate spatiotemporal connectivity features using low-rank tensor completion, thereby capturing the variability and richness of the temporal development of fibers. Experimental results confirm that the proposed variants significantly improve the prediction performance of our original multishape prediction framework for both cortical surfaces and fiber tracts shape at 3, 6, and 9 months of age. Our pioneering model will pave the way for learning how to predict the evolution of anatomical shapes with abnormal changes. Ultimately, devising accurate shape evolution prediction models that can help quantify and predict the severity of a brain disorder as it progresses will be of great aid in individualized treatment planning. PMID:28284800

Joint prediction of longitudinal development of cortical surfaces and white matter fibers from neonatal MRI.

PubMed

Rekik, Islem; Li, Gang; Yap, Pew-Thian; Chen, Geng; Lin, Weili; Shen, Dinggang

2017-05-15

The human brain can be modeled as multiple interrelated shapes (or a multishape), each for characterizing one aspect of the brain, such as the cortex and white matter pathways. Predicting the developing multishape is a very challenging task due to the contrasting nature of the developmental trajectories of the constituent shapes: smooth for the cortical surface and non-smooth for white matter tracts due to changes such as bifurcation. We recently addressed this problem and proposed an approach for predicting the multishape developmental spatiotemporal trajectories of infant brains based only on neonatal MRI data using a set of geometric, dynamic, and fiber-to-surface connectivity features. In this paper, we propose two key innovations to further improve the prediction of multishape evolution. First, for a more accurate cortical surface prediction, instead of simply relying on one neonatal atlas to guide the prediction of the multishape, we propose to use multiple neonatal atlases to build a spatially heterogeneous atlas using the multidirectional varifold representation. This individualizes the atlas by locally maximizing its similarity to the testing baseline cortical shape for each cortical region, thereby better representing the baseline testing cortical surface, which founds the multishape prediction process. Second, for temporally consistent fiber prediction, we propose to reliably estimate spatiotemporal connectivity features using low-rank tensor completion, thereby capturing the variability and richness of the temporal development of fibers. Experimental results confirm that the proposed variants significantly improve the prediction performance of our original multishape prediction framework for both cortical surfaces and fiber tracts shape at 3, 6, and 9 months of age. Our pioneering model will pave the way for learning how to predict the evolution of anatomical shapes with abnormal changes. Ultimately, devising accurate shape evolution prediction models that can help quantify and predict the severity of a brain disorder as it progresses will be of great aid in individualized treatment planning. Copyright © 2017 Elsevier Inc. All rights reserved.

How the brain attunes to sentence processing: Relating behavior, structure, and function

PubMed Central

Fengler, Anja; Meyer, Lars; Friederici, Angela D.

2016-01-01

Unlike other aspects of language comprehension, the ability to process complex sentences develops rather late in life. Brain maturation as well as verbal working memory (vWM) expansion have been discussed as possible reasons. To determine the factors contributing to this functional development, we assessed three aspects in different age-groups (5–6 years, 7–8 years, and adults): first, functional brain activity during the processing of increasingly complex sentences; second, brain structure in language-related ROIs; and third, the behavioral comprehension performance on complex sentences and the performance on an independent vWM test. At the whole-brain level, brain functional data revealed a qualitatively similar neural network in children and adults including the left pars opercularis (PO), the left inferior parietal lobe together with the posterior superior temporal gyrus (IPL/pSTG), the supplementary motor area, and the cerebellum. While functional activation of the language-related ROIs PO and IPL/pSTG predicted sentence comprehension performance for all age-groups, only adults showed a functional selectivity in these brain regions with increased activation for more complex sentences. The attunement of both the PO and IPL/pSTG toward a functional selectivity for complex sentences is predicted by region-specific gray matter reduction while that of the IPL/pSTG is additionally predicted by vWM span. Thus, both structural brain maturation and vWM expansion provide the basis for the emergence of functional selectivity in language-related brain regions leading to more efficient sentence processing during development. PMID:26777477

Effect of bulk modulus on deformation of the brain under rotational accelerations

NASA Astrophysics Data System (ADS)

Ganpule, S.; Daphalapurkar, N. P.; Cetingul, M. P.; Ramesh, K. T.

2018-01-01

Traumatic brain injury such as that developed as a consequence of blast is a complex injury with a broad range of symptoms and disabilities. Computational models of brain biomechanics hold promise for illuminating the mechanics of traumatic brain injury and for developing preventive devices. However, reliable material parameters are needed for models to be predictive. Unfortunately, the properties of human brain tissue are difficult to measure, and the bulk modulus of brain tissue in particular is not well characterized. Thus, a wide range of bulk modulus values are used in computational models of brain biomechanics, spanning up to three orders of magnitude in the differences between values. However, the sensitivity of these variations on computational predictions is not known. In this work, we study the sensitivity of a 3D computational human head model to various bulk modulus values. A subject-specific human head model was constructed from T1-weighted MRI images at 2-mm3 voxel resolution. Diffusion tensor imaging provided data on spatial distribution and orientation of axonal fiber bundles for modeling white matter anisotropy. Non-injurious, full-field brain deformations in a human volunteer were used to assess the simulated predictions. The comparison suggests that a bulk modulus value on the order of GPa gives the best agreement with experimentally measured in vivo deformations in the human brain. Further, simulations of injurious loading suggest that bulk modulus values on the order of GPa provide the closest match with the clinical findings in terms of predicated injured regions and extent of injury.

Magnetic resonance spectroscopy and brain volumetry in mild cognitive impairment. A prospective study.

PubMed

Fayed, Nicolás; Modrego, Pedro J; García-Martí, Gracián; Sanz-Requena, Roberto; Marti-Bonmatí, Luis

2017-05-01

To assess the accuracy of magnetic resonance spectroscopy (1H-MRS) and brain volumetry in mild cognitive impairment (MCI) to predict conversion to probable Alzheimer's disease (AD). Forty-eight patients fulfilling the criteria of amnestic MCI who underwent a conventional magnetic resonance imaging (MRI) followed by MRS, and T1-3D on 1.5 Tesla MR unit. At baseline the patients underwent neuropsychological examination. 1H-MRS of the brain was carried out by exploring the left medial occipital lobe and ventral posterior cingulated cortex (vPCC) using the LCModel software. A high resolution T1-3D sequence was acquired to carry out the volumetric measurement. A cortical and subcortical parcellation strategy was used to obtain the volumes of each area within the brain. The patients were followed up to detect conversion to probable AD. After a 3-year follow-up, 15 (31.2%) patients converted to AD. The myo-inositol in the occipital cortex and glutamate+glutamine (Glx) in the posterior cingulate cortex predicted conversion to probable AD at 46.1% sensitivity and 90.6% specificity. The positive predictive value was 66.7%, and the negative predictive value was 80.6%, with an overall cross-validated classification accuracy of 77.8%. The volume of the third ventricle, the total white matter and entorhinal cortex predict conversion to probable AD at 46.7% sensitivity and 90.9% specificity. The positive predictive value was 70%, and the negative predictive value was 78.9%, with an overall cross-validated classification accuracy of 77.1%. Combining volumetric measures in addition to the MRS measures the prediction to probable AD has a 38.5% sensitivity and 87.5% specificity, with a positive predictive value of 55.6%, a negative predictive value of 77.8% and an overall accuracy of 73.3%. Either MRS or brain volumetric measures are markers separately of cognitive decline and may serve as a noninvasive tool to monitor cognitive changes and progression to dementia in patients with amnestic MCI, but the results do not support the routine use in the clinical settings. Copyright © 2016 Elsevier Inc. All rights reserved.

Trait positive affect is associated with hippocampal volume and change in caudate volume across adolescence.

PubMed

Dennison, Meg; Whittle, Sarah; Yücel, Murat; Byrne, Michelle L; Schwartz, Orli; Simmons, Julian G; Allen, Nicholas B

2015-03-01

Trait positive affect (PA) in childhood confers both risk and resilience to psychological and behavioral difficulties in adolescence, although explanations for this association are lacking. Neurodevelopment in key areas associated with positive affect is ongoing throughout adolescence, and is likely to be related to the increased incidence of disorders of positive affect during this period of development. The aim of this study was to prospectively explore the relationship between trait indices of PA and brain development in subcortical reward regions during early to mid-adolescence in a community sample of adolescents. A total of 89 (46 male, 43 female) adolescents participated in magnetic resonance imaging assessments during both early and mid-adolescence (mean age at baseline = 12.6 years, SD = 0.45; mean follow-up period = 3.78 years, SD = 0.21) and also completed self-report measures of trait positive and negative affect (at baseline). To examine the specificity of these effects, the relation between negative affect and brain development was also examined. The degree of volume reduction in the right caudate over time was predicted by PA. Independent of time, larger hippocampal volumes were associated with higher PA, and negative affect was associated with smaller left amygdala volume. The moderating effect of negative affect on the development of the left caudate varied as a function of lifetime psychiatric history. These findings suggest that early to mid-adolescence is an important period whereby neurodevelopmental processes may underlie key phenotypes conferring both risk and resilience for emotional and behavioral difficulties later in life.