A comparison of participation outcome measures and the International Classification of Functioning, Disability and Health Core Sets for traumatic brain injury.

PubMed

Chung, Pearl; Yun, Sarah Jin; Khan, Fary

2014-02-01

To compare the contents of participation outcome measures in traumatic brain injury with the International Classification of Functioning, Disability and Health (ICF) Core Sets for traumatic brain injury. A systematic search with an independent review process selected relevant articles to identify outcome measures in participation in traumatic brain injury. Instruments used in two or more studies were linked to the ICF categories, which identified categories in participation for comparison with the ICF Core Sets for traumatic brain injury. Selected articles (n = 101) identified participation instruments used in two or more studies (n = 9): Community Integration Questionnaire, Craig Handicap Assessment and Reporting Technique, Mayo-Portland Adaptability Inventory-4 Participation Index, Sydney Psychosocial Reintegration Scale Version-2, Participation Assessment with Recombined Tool-Objective, Community Integration Measure, Participation Objective Participation Subjective, Community Integration Questionnaire-2, and Quality of Community Integration Questionnaire. Each instrument was linked to 4-35 unique second-level ICF categories, of which 39-100% related to participation. Instruments addressed 86-100% and 50-100% of the participation categories in the Comprehensive and Brief ICF Core Sets for traumatic brain injury, respectively. Participation measures in traumatic brain injury were compared with the ICF Core Sets for traumatic brain injury. The ICF Core Sets for traumatic brain injury could contribute to the development and selection of participation measures.

Realistic modeling of neurons and networks: towards brain simulation.

PubMed

D'Angelo, Egidio; Solinas, Sergio; Garrido, Jesus; Casellato, Claudia; Pedrocchi, Alessandra; Mapelli, Jonathan; Gandolfi, Daniela; Prestori, Francesca

2013-01-01

Realistic modeling is a new advanced methodology for investigating brain functions. Realistic modeling is based on a detailed biophysical description of neurons and synapses, which can be integrated into microcircuits. The latter can, in turn, be further integrated to form large-scale brain networks and eventually to reconstruct complex brain systems. Here we provide a review of the realistic simulation strategy and use the cerebellar network as an example. This network has been carefully investigated at molecular and cellular level and has been the object of intense theoretical investigation. The cerebellum is thought to lie at the core of the forward controller operations of the brain and to implement timing and sensory prediction functions. The cerebellum is well described and provides a challenging field in which one of the most advanced realistic microcircuit models has been generated. We illustrate how these models can be elaborated and embedded into robotic control systems to gain insight into how the cellular properties of cerebellar neurons emerge in integrated behaviors. Realistic network modeling opens up new perspectives for the investigation of brain pathologies and for the neurorobotic field.

Realistic modeling of neurons and networks: towards brain simulation

PubMed Central

D’Angelo, Egidio; Solinas, Sergio; Garrido, Jesus; Casellato, Claudia; Pedrocchi, Alessandra; Mapelli, Jonathan; Gandolfi, Daniela; Prestori, Francesca

Summary Realistic modeling is a new advanced methodology for investigating brain functions. Realistic modeling is based on a detailed biophysical description of neurons and synapses, which can be integrated into microcircuits. The latter can, in turn, be further integrated to form large-scale brain networks and eventually to reconstruct complex brain systems. Here we provide a review of the realistic simulation strategy and use the cerebellar network as an example. This network has been carefully investigated at molecular and cellular level and has been the object of intense theoretical investigation. The cerebellum is thought to lie at the core of the forward controller operations of the brain and to implement timing and sensory prediction functions. The cerebellum is well described and provides a challenging field in which one of the most advanced realistic microcircuit models has been generated. We illustrate how these models can be elaborated and embedded into robotic control systems to gain insight into how the cellular properties of cerebellar neurons emerge in integrated behaviors. Realistic network modeling opens up new perspectives for the investigation of brain pathologies and for the neurorobotic field. PMID:24139652

Higher levels of trait emotional awareness are associated with more efficient global information integration throughout the brain: A graph-theoretic analysis of resting state functional connectivity.

PubMed

Smith, Ryan; Sanova, Anna; Alkozei, Anna; Lane, Richard D; Killgore, William D S

2018-06-21

Previous studies have suggested that trait differences in emotional awareness (tEA) are clinically relevant, and associated with differences in neural structure/function. While multiple leading theories suggest that conscious awareness requires widespread information integration across the brain, no study has yet tested the hypothesis that higher tEA corresponds to more efficient brain-wide information exchange. Twenty-six healthy volunteers (13 female) underwent a resting state functional magnetic resonance imaging scan, and completed the Levels of Emotional Awareness Scale (LEAS; a measure of tEA) and the Wechsler Abbreviated Scale of Intelligence (WASI-II; a measure of general intelligence [IQ]). Using a whole-brain (functionally defined) region-of-interest (ROI) atlas, we computed several graph theory metrics to assess the efficiency of brain-wide information exchange. After statistically controlling for differences in age, gender, and IQ, we first observed a significant relationship between higher LEAS scores and greater average degree (i.e., overall whole-brain network density). When controlling for average degree, we found that higher LEAS scores were also associated with shorter average path lengths across the collective network of all included ROIs. These results jointly suggest that individuals with higher tEA display more efficient global information exchange throughout the brain. This is consistent with the idea that conscious awareness requires global accessibility of represented information.

Participation in a social and recreational day programme increases community integration and reduces family burden of persons with acquired brain injury.

PubMed

Gerber, Gary J; Gargaro, Judith

2015-01-01

To describe and evaluate a new day programme for persons living with an acquired brain injury (ABI), including persons exhibiting challenging behaviours. Activities were designed to reduce participants' social isolation, increase participation in community activities and increase social and leisure skills. It was expected that community integration would increase and challenging behaviours and family burden would decrease for day programme participants. Pre-post convenience sample design. Sixty-one participants and family members completed questionnaires before starting the day programme and after 6-month participation. Community Integration Questionnaire, Overt Behaviour Scale, Burden Assessment Scale, Goal Attainment Scaling. Participants had increased community integration (p = 0.000) and decreased family burden (p = 0.006). There was a trend to decreased severity of challenging behaviour. Participants and family members were very satisfied. Results suggest that the programme was effective in reducing participants' social isolation and increasing appropriate interpersonal behaviours. Participation increased community integration and reduced burden on family caregivers. ABI day programmes help fill the void left after other rehabilitation services end and provide survivors with opportunities to engage in a variety of activities. Persons living with ABI have need for ongoing social, recreational and life skill coaching services after formal rehabilitation has been completed.

A prospective study to evaluate a new residential community reintegration programme for severe chronic brain injury: the Brain Integration Programme.

PubMed

Geurtsen, G J; Martina, J D; Van Heugten, C M; Geurts, A C H

2008-07-01

To assess the effectiveness of a residential community reintegration programme for participants with chronic sequelae of severe acquired brain injury that hamper community functioning. Prospective cohort study. Twenty-four participants with acquired brain injury (traumatic n = 18; stroke n = 3, tumour n = 2, encephalitis n = 1). Participants had impaired illness awareness, alcohol and drug problems and/or behavioural problems. A skills-oriented programme with modules related to independent living, work, social and emotional well-being. The Community Integration Questionnaire, CES-Depression, EuroQOL, Employability Rating Scale, living situation and work status were scored at the start (T0), end of treatment (T1) and 1-year follow-up (T2). Significant effects on the majority of outcome measures were present at T1. Employability significantly improved at T2 and living independently rose from 42% to over 70%. Participants working increased from 38% to 58% and the hours of work per week increased from 8 to 15. The Brain Integration Programme led to a sustained reduction in experienced problems and improved community integration. It is concluded that even participants with complex problems due to severe brain injury who got stuck in life could improve their social participation and emotional well-being through a residential community reintegration programme.

Simultaneous EEG and MEG source reconstruction in sparse electromagnetic source imaging.

PubMed

Ding, Lei; Yuan, Han

2013-04-01

Electroencephalography (EEG) and magnetoencephalography (MEG) have different sensitivities to differently configured brain activations, making them complimentary in providing independent information for better detection and inverse reconstruction of brain sources. In the present study, we developed an integrative approach, which integrates a novel sparse electromagnetic source imaging method, i.e., variation-based cortical current density (VB-SCCD), together with the combined use of EEG and MEG data in reconstructing complex brain activity. To perform simultaneous analysis of multimodal data, we proposed to normalize EEG and MEG signals according to their individual noise levels to create unit-free measures. Our Monte Carlo simulations demonstrated that this integrative approach is capable of reconstructing complex cortical brain activations (up to 10 simultaneously activated and randomly located sources). Results from experimental data showed that complex brain activations evoked in a face recognition task were successfully reconstructed using the integrative approach, which were consistent with other research findings and validated by independent data from functional magnetic resonance imaging using the same stimulus protocol. Reconstructed cortical brain activations from both simulations and experimental data provided precise source localizations as well as accurate spatial extents of localized sources. In comparison with studies using EEG or MEG alone, the performance of cortical source reconstructions using combined EEG and MEG was significantly improved. We demonstrated that this new sparse ESI methodology with integrated analysis of EEG and MEG data could accurately probe spatiotemporal processes of complex human brain activations. This is promising for noninvasively studying large-scale brain networks of high clinical and scientific significance. Copyright © 2011 Wiley Periodicals, Inc.

A regulatory toolbox of MiniPromoters to drive selective expression in the brain.

PubMed

Portales-Casamar, Elodie; Swanson, Douglas J; Liu, Li; de Leeuw, Charles N; Banks, Kathleen G; Ho Sui, Shannan J; Fulton, Debra L; Ali, Johar; Amirabbasi, Mahsa; Arenillas, David J; Babyak, Nazar; Black, Sonia F; Bonaguro, Russell J; Brauer, Erich; Candido, Tara R; Castellarin, Mauro; Chen, Jing; Chen, Ying; Cheng, Jason C Y; Chopra, Vik; Docking, T Roderick; Dreolini, Lisa; D'Souza, Cletus A; Flynn, Erin K; Glenn, Randy; Hatakka, Kristi; Hearty, Taryn G; Imanian, Behzad; Jiang, Steven; Khorasan-zadeh, Shadi; Komljenovic, Ivana; Laprise, Stéphanie; Liao, Nancy Y; Lim, Jonathan S; Lithwick, Stuart; Liu, Flora; Liu, Jun; Lu, Meifen; McConechy, Melissa; McLeod, Andrea J; Milisavljevic, Marko; Mis, Jacek; O'Connor, Katie; Palma, Betty; Palmquist, Diana L; Schmouth, Jean-François; Swanson, Magdalena I; Tam, Bonny; Ticoll, Amy; Turner, Jenna L; Varhol, Richard; Vermeulen, Jenny; Watkins, Russell F; Wilson, Gary; Wong, Bibiana K Y; Wong, Siaw H; Wong, Tony Y T; Yang, George S; Ypsilanti, Athena R; Jones, Steven J M; Holt, Robert A; Goldowitz, Daniel; Wasserman, Wyeth W; Simpson, Elizabeth M

2010-09-21

The Pleiades Promoter Project integrates genomewide bioinformatics with large-scale knockin mouse production and histological examination of expression patterns to develop MiniPromoters and related tools designed to study and treat the brain by directed gene expression. Genes with brain expression patterns of interest are subjected to bioinformatic analysis to delineate candidate regulatory regions, which are then incorporated into a panel of compact human MiniPromoters to drive expression to brain regions and cell types of interest. Using single-copy, homologous-recombination "knockins" in embryonic stem cells, each MiniPromoter reporter is integrated immediately 5' of the Hprt locus in the mouse genome. MiniPromoter expression profiles are characterized in differentiation assays of the transgenic cells or in mouse brains following transgenic mouse production. Histological examination of adult brains, eyes, and spinal cords for reporter gene activity is coupled to costaining with cell-type-specific markers to define expression. The publicly available Pleiades MiniPromoter Project is a key resource to facilitate research on brain development and therapies.

A Network Model of the Emotional Brain.

PubMed

Pessoa, Luiz

2017-05-01

Emotion is often understood in terms of a circumscribed set of cortical and subcortical brain regions. I propose, instead, that emotion should be understood in terms of large-scale network interactions spanning the entire neuroaxis. I describe multiple anatomical and functional principles of brain organization that lead to the concept of 'functionally integrated systems', cortical-subcortical systems that anchor the organization of emotion in the brain. The proposal is illustrated by describing the cortex-amygdala integrated system and how it intersects with systems involving the ventral striatum/accumbens, septum, hippocampus, hypothalamus, and brainstem. The important role of the thalamus is also highlighted. Overall, the model clarifies why the impact of emotion is wide-ranging, and how emotion is interlocked with perception, cognition, motivation, and action. Copyright © 2017 Elsevier Ltd. All rights reserved.

From Whole-Brain Data to Functional Circuit Models: The Zebrafish Optomotor Response.

PubMed

Naumann, Eva A; Fitzgerald, James E; Dunn, Timothy W; Rihel, Jason; Sompolinsky, Haim; Engert, Florian

2016-11-03

Detailed descriptions of brain-scale sensorimotor circuits underlying vertebrate behavior remain elusive. Recent advances in zebrafish neuroscience offer new opportunities to dissect such circuits via whole-brain imaging, behavioral analysis, functional perturbations, and network modeling. Here, we harness these tools to generate a brain-scale circuit model of the optomotor response, an orienting behavior evoked by visual motion. We show that such motion is processed by diverse neural response types distributed across multiple brain regions. To transform sensory input into action, these regions sequentially integrate eye- and direction-specific sensory streams, refine representations via interhemispheric inhibition, and demix locomotor instructions to independently drive turning and forward swimming. While experiments revealed many neural response types throughout the brain, modeling identified the dimensions of functional connectivity most critical for the behavior. We thus reveal how distributed neurons collaborate to generate behavior and illustrate a paradigm for distilling functional circuit models from whole-brain data. Copyright © 2016 Elsevier Inc. All rights reserved.

Multiscale modeling and simulation of brain blood flow

NASA Astrophysics Data System (ADS)

Perdikaris, Paris; Grinberg, Leopold; Karniadakis, George Em

2016-02-01

The aim of this work is to present an overview of recent advances in multi-scale modeling of brain blood flow. In particular, we present some approaches that enable the in silico study of multi-scale and multi-physics phenomena in the cerebral vasculature. We discuss the formulation of continuum and atomistic modeling approaches, present a consistent framework for their concurrent coupling, and list some of the challenges that one needs to overcome in achieving a seamless and scalable integration of heterogeneous numerical solvers. The effectiveness of the proposed framework is demonstrated in a realistic case involving modeling the thrombus formation process taking place on the wall of a patient-specific cerebral aneurysm. This highlights the ability of multi-scale algorithms to resolve important biophysical processes that span several spatial and temporal scales, potentially yielding new insight into the key aspects of brain blood flow in health and disease. Finally, we discuss open questions in multi-scale modeling and emerging topics of future research.

A new neuroinformatics approach to personalized medicine in neurology: The Virtual Brain

PubMed Central

Falcon, Maria I.; Jirsa, Viktor; Solodkin, Ana

2017-01-01

Purpose of review An exciting advance in the field of neuroimaging is the acquisition and processing of very large data sets (so called ‘big data’), permitting large-scale inferences that foster a greater understanding of brain function in health and disease. Yet what we are clearly lacking are quantitative integrative tools to translate this understanding to the individual level to lay the basis for personalized medicine. Recent findings Here we address this challenge through a review on how the relatively new field of neuroinformatics modeling has the capacity to track brain network function at different levels of inquiry, from microscopic to macroscopic and from the localized to the distributed. In this context, we introduce a new and unique multiscale approach, The Virtual Brain (TVB), that effectively models individualized brain activity, linking large-scale (macroscopic) brain dynamics with biophysical parameters at the microscopic level. We also show how TVB modeling provides unique biological interpretable data in epilepsy and stroke. Summary These results establish the basis for a deliberate integration of computational biology and neuroscience into clinical approaches for elucidating cellular mechanisms of disease. In the future, this can provide the means to create a collection of disease-specific models that can be applied on the individual level to personalize therapeutic interventions. Video abstract http://links.lww.com/CONR/A41 PMID:27224088

Motor and cortico-striatal-thalamic connectivity alterations in intrauterine growth restriction.

PubMed

Eixarch, Elisenda; Muñoz-Moreno, Emma; Bargallo, Nuria; Batalle, Dafnis; Gratacos, Eduard

2016-06-01

Intrauterine growth restriction is associated with short- and long-term neurodevelopmental problems. Structural brain changes underlying these alterations have been described with the use of different magnetic resonance-based methods that include changes in whole structural brain networks. However, evaluation of specific brain circuits and its correlation with related functions has not been investigated in intrauterine growth restriction. In this study, we aimed to investigate differences in tractography-related metrics in cortico-striatal-thalamic and motor networks in intrauterine growth restricted children and whether these parameters were related with their specific function in order to explore its potential use as an imaging biomarker of altered neurodevelopment. We included a group of 24 intrauterine growth restriction subjects and 27 control subjects that were scanned at 1 year old; we acquired T1-weighted and 30 directions diffusion magnetic resonance images. Each subject brain was segmented in 93 regions with the use of anatomical automatic labeling atlas, and deterministic tractography was performed. Brain regions included in motor and cortico-striatal-thalamic networks were defined based in functional and anatomic criteria. Within the streamlines that resulted from the whole brain tractography, those belonging to each specific circuit were selected and tractography-related metrics that included number of streamlines, fractional anisotropy, and integrity were calculated for each network. We evaluated differences between both groups and further explored the correlation of these parameters with the results of socioemotional, cognitive, and motor scales from Bayley Scale at 2 years of age. Reduced fractional anisotropy (cortico-striatal-thalamic, 0.319 ± 0.018 vs 0.315 ± 0.015; P = .010; motor, 0.322 ± 0.019 vs 0.319 ± 0.020; P = .019) and integrity cortico-striatal-thalamic (0.407 ± 0.040 vs 0.399 ± 0.034; P = .018; motor, 0.417 ± 0.044 vs 0.409 ± 0.046; P = .016) in both networks were observed in the intrauterine growth restriction group, with no differences in number of streamlines. More importantly, strong specific correlation was found between tractography-related metrics and its relative function in both networks in intrauterine growth restricted children. Motor network metrics were correlated specifically with motor scale results (fractional anisotropy: rho = 0.857; integrity: rho = 0.740); cortico-striatal-thalamic network metrics were correlated with cognitive (fractional anisotropy: rho = 0.793; integrity, rho = 0.762) and socioemotional scale (fractional anisotropy: rho = 0.850; integrity: rho = 0.877). These results support the existence of altered brain connectivity in intrauterine growth restriction demonstrated by altered connectivity in motor and cortico-striatal-thalamic networks, with reduced fractional anisotropy and integrity. The specific correlation between tractography-related metrics and neurodevelopmental outcomes in intrauterine growth restriction shows the potential to use this approach to develop imaging biomarkers to predict specific neurodevelopmental outcome in infants who are at risk because of intrauterine growth restriction and other prenatal diseases. Copyright © 2015 Elsevier Inc. All rights reserved.

Fine-Granularity Functional Interaction Signatures for Characterization of Brain Conditions

PubMed Central

Hu, Xintao; Zhu, Dajiang; Lv, Peili; Li, Kaiming; Han, Junwei; Wang, Lihong; Shen, Dinggang; Guo, Lei; Liu, Tianming

2014-01-01

In the human brain, functional activity occurs at multiple spatial scales. Current studies on functional brain networks and their alterations in brain diseases via resting-state functional magnetic resonance imaging (rs-fMRI) are generally either at local scale (regionally confined analysis and inter-regional functional connectivity analysis) or at global scale (graph theoretic analysis). In contrast, inferring functional interaction at fine-granularity sub-network scale has not been adequately explored yet. Here our hypothesis is that functional interaction measured at fine-granularity subnetwork scale can provide new insight into the neural mechanisms of neurological and psychological conditions, thus offering complementary information for healthy and diseased population classification. In this paper, we derived fine-granularity functional interaction (FGFI) signatures in subjects with Mild Cognitive Impairment (MCI) and Schizophrenia by diffusion tensor imaging (DTI) and rsfMRI, and used patient-control classification experiments to evaluate the distinctiveness of the derived FGFI features. Our experimental results have shown that the FGFI features alone can achieve comparable classification performance compared with the commonly used inter-regional connectivity features. However, the classification performance can be substantially improved when FGFI features and inter-regional connectivity features are integrated, suggesting the complementary information achieved from the FGFI signatures. PMID:23319242

Large-scale extraction of brain connectivity from the neuroscientific literature

PubMed Central

Richardet, Renaud; Chappelier, Jean-Cédric; Telefont, Martin; Hill, Sean

2015-01-01

Motivation: In neuroscience, as in many other scientific domains, the primary form of knowledge dissemination is through published articles. One challenge for modern neuroinformatics is finding methods to make the knowledge from the tremendous backlog of publications accessible for search, analysis and the integration of such data into computational models. A key example of this is metascale brain connectivity, where results are not reported in a normalized repository. Instead, these experimental results are published in natural language, scattered among individual scientific publications. This lack of normalization and centralization hinders the large-scale integration of brain connectivity results. In this article, we present text-mining models to extract and aggregate brain connectivity results from 13.2 million PubMed abstracts and 630 216 full-text publications related to neuroscience. The brain regions are identified with three different named entity recognizers (NERs) and then normalized against two atlases: the Allen Brain Atlas (ABA) and the atlas from the Brain Architecture Management System (BAMS). We then use three different extractors to assess inter-region connectivity. Results: NERs and connectivity extractors are evaluated against a manually annotated corpus. The complete in litero extraction models are also evaluated against in vivo connectivity data from ABA with an estimated precision of 78%. The resulting database contains over 4 million brain region mentions and over 100 000 (ABA) and 122 000 (BAMS) potential brain region connections. This database drastically accelerates connectivity literature review, by providing a centralized repository of connectivity data to neuroscientists. Availability and implementation: The resulting models are publicly available at github.com/BlueBrain/bluima. Contact: renaud.richardet@epfl.ch Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25609795

Exploring the brain on multiple scales with correlative two-photon and light sheet microscopy

NASA Astrophysics Data System (ADS)

Silvestri, Ludovico; Allegra Mascaro, Anna Letizia; Costantini, Irene; Sacconi, Leonardo; Pavone, Francesco S.

2014-02-01

One of the unique features of the brain is that its activity cannot be framed in a single spatio-temporal scale, but rather spans many orders of magnitude both in space and time. A single imaging technique can reveal only a small part of this complex machinery. To obtain a more comprehensive view of brain functionality, complementary approaches should be combined into a correlative framework. Here, we describe a method to integrate data from in vivo two-photon fluorescence imaging and ex vivo light sheet microscopy, taking advantage of blood vessels as reference chart. We show how the apical dendritic arbor of a single cortical pyramidal neuron imaged in living thy1-GFP-M mice can be found in the large-scale brain reconstruction obtained with light sheet microscopy. Starting from the apical portion, the whole pyramidal neuron can then be segmented. The correlative approach presented here allows contextualizing within a three-dimensional anatomic framework the neurons whose dynamics have been observed with high detail in vivo.

Simultaneous 11C-Methionine Positron Emission Tomography/Magnetic Resonance Imaging of Suspected Primary Brain Tumors

PubMed Central

Deuschl, Cornelius; Goericke, Sophia; Grueneisen, Johannes; Sawicki, Lino Morris; Goebel, Juliane; El Hindy, Nicolai; Wrede, Karsten; Binse, Ina; Poeppel, Thorsten; Quick, Harald; Forsting, Michael; Hense, Joerg; Umutlu, Lale; Schlamann, Marc

2016-01-01

Introduction The objective of this study was to assess the diagnostic value of integrated 11C- methionine PET/MRI for suspected primary brain tumors, in comparison to MRI alone. Material and Methods Forty-eight consecutive patients with suspected primary brain tumor were prospectively enrolled for an integrated 11C-methionine PET/MRI. Two neuro-radiologists separately evaluated the MRI alone and the integrated PET/MRI data sets regarding most likely diagnosis and diagnostic confidence on a 5-point scale. Reference standard was histopathology or follow-up imaging. Results Fifty-one suspicious lesions were detected: 16 high-grade glioma and 25 low-grade glioma. Ten non-malignant cerebral lesions were described by the reference standard. MRI alone and integrated PET/MRI each correctly classified 42 of the 51 lesions (82.4%) as neoplastic lesions (WHO grade II, III and IV) or non-malignant lesions (infectious and neoplastic lesions). Diagnostic confidence for all lesions, low-grade astrocytoma and high-grade astrocytoma (3.7 vs. 4.2, 3,1 vs. 3.8, 4.0 vs. 4,7) were significantly (p < 0.05) better with integrated PET/MRI than in MRI alone. Conclusions The present study demonstrates the high potential of integrated 11C-methionine-PET/MRI for the assessment of suspected primary brain tumors. Although integrated methionine PET/MRI does not lead to an improvement of correct diagnoses, diagnostic confidence is significantly improved. PMID:27907162

Effect of meditation on psychological distress and brain functioning: A randomized controlled study.

PubMed

Travis, Fred; Valosek, Laurent; Konrad, Arthur; Link, Janice; Salerno, John; Scheller, Ray; Nidich, Sanford

2018-06-21

Psychological stability and brain integration are important factors related to physical and mental health and organization effectiveness. This study tested whether a mind-body technique, the Transcendental Meditation (TM) program could increase EEG brain integration and positive affect, and decrease psychological distress in government employees. Ninety-six central office administrators and staff at the San Francisco Unified School District were randomly assigned to either immediate start of the TM program or to a wait-list control group. At baseline and four-month posttest, participants completed an online version of the Profile of Mood States questionnaire (POMS). In addition, a subset of this population (N = 79) had their EEG recorded at baseline and at four-month posttest to calculate Brain Integration Scale (BIS) scores. At posttest, TM participants significantly decreased on the POMS Total Mood Disturbance and anxiety, anger, depression, fatigue, and confusion subscales, and significantly increased in the POMS vigor subscale. TM participants in the EEG-subgroup also significantly increased in BIS scores. Compliance with meditation practice was high (93%). Findings indicate the feasibility and effectiveness of implementing the TM program to improve brain integration and positive affect and reduce psychological distress in government administrators and staff. Copyright © 2018. Published by Elsevier Inc.

Distributed XQuery-Based Integration and Visualization of Multimodality Brain Mapping Data

PubMed Central

Detwiler, Landon T.; Suciu, Dan; Franklin, Joshua D.; Moore, Eider B.; Poliakov, Andrew V.; Lee, Eunjung S.; Corina, David P.; Ojemann, George A.; Brinkley, James F.

2008-01-01

This paper addresses the need for relatively small groups of collaborating investigators to integrate distributed and heterogeneous data about the brain. Although various national efforts facilitate large-scale data sharing, these approaches are generally too “heavyweight” for individual or small groups of investigators, with the result that most data sharing among collaborators continues to be ad hoc. Our approach to this problem is to create a “lightweight” distributed query architecture, in which data sources are accessible via web services that accept arbitrary query languages but return XML results. A Distributed XQuery Processor (DXQP) accepts distributed XQueries in which subqueries are shipped to the remote data sources to be executed, with the resulting XML integrated by DXQP. A web-based application called DXBrain accesses DXQP, allowing a user to create, save and execute distributed XQueries, and to view the results in various formats including a 3-D brain visualization. Example results are presented using distributed brain mapping data sources obtained in studies of language organization in the brain, but any other XML source could be included. The advantage of this approach is that it is very easy to add and query a new source, the tradeoff being that the user needs to understand XQuery and the schemata of the underlying sources. For small numbers of known sources this burden is not onerous for a knowledgeable user, leading to the conclusion that the system helps to fill the gap between ad hoc local methods and large scale but complex national data sharing efforts. PMID:19198662

White matter tract integrity and intelligence in patients with mental retardation and healthy adults.

PubMed

Yu, Chunshui; Li, Jun; Liu, Yong; Qin, Wen; Li, Yonghui; Shu, Ni; Jiang, Tianzi; Li, Kuncheng

2008-05-01

It is well known that brain structures correlate with intelligence but the association between the integrity of brain white matter tracts and intelligence in patients with mental retardation (MR) and healthy adults remains unknown. The aims of this study are to investigate whether the integrity of corpus callosum (CC), cingulum, uncinate fasciculus (UF), optic radiation (OR) and corticospinal tract (CST) are damaged in patients with MR, and to determine the correlations between the integrity of these tracts and full scale intelligence quotient (FSIQ) in both patients and controls. Fifteen MR patients and 79 healthy controls underwent intelligence tests and diffusion tensor imaging examinations. According to the FSIQ, all healthy controls were divided into general intelligence (GI: FSIQ<120; n=42) and high intelligence (HI: FSIQ> or =120; n=37) groups. Intelligence was assessed by Chinese Revised Wechsler Adult Intelligence Scale, and white matter tract integrity was assessed by fractional anisotropy (FA). MR patients showed significantly lower FA than healthy controls in the CC, UF, OR and CST. However, GI subjects only demonstrated lower FA than HI subjects in the right UF. Partial correlation analysis controlling for age and sex showed that FSIQ scores were significantly correlated with the FA of the bilateral UF, genu and truncus of CC, bilateral OR and left CST. While FSIQ scores were only significantly correlated with the FA of the right UF when further controlling for group. This study indicate that MR patients show extensive damage in the integrity of the brain white matter tracts, and the right UF is an important neural basis of human intelligence.

PPAR-gamma agonist pioglitazone modifies craving intensity and brain white matter integrity in patients with primary cocaine use disorder: a double-blind randomized controlled pilot trial.

PubMed

Schmitz, Joy M; Green, Charles E; Hasan, Khader M; Vincent, Jessica; Suchting, Robert; Weaver, Michael F; Moeller, F Gerard; Narayana, Ponnada A; Cunningham, Kathryn A; Dineley, Kelly T; Lane, Scott D

2017-10-01

Pioglitazone (PIO), a potent agonist of PPAR-gamma, is a promising candidate treatment for cocaine use disorder (CUD). We tested the effects of PIO on targeted mechanisms relevant to CUD: cocaine craving and brain white matter (WM) integrity. Feasibility, medication compliance and tolerability were evaluated. Two-arm double-blind randomized controlled proof-of-concept pilot trial of PIO or placebo (PLC). Single-site out-patient treatment research clinic in Houston, TX, USA. Thirty treatment-seeking adults, 18 to 60 years old, with CUD. Eighteen participants (8 = PIO; 10 = PLC) completed diffusion tensor imaging (DTI) of WM integrity at pre-/post-treatment. Study medication was dispensed at thrice weekly visits along with once-weekly cognitive behavioral therapy for 12 weeks. Measures of target engagement mechanisms of interest included cocaine craving assessed by the Brief Substance Craving Scale (BSCS), the Obsessive Compulsive Drug Use Scale (OCDUS), a visual analog scale (VAS) and change in WM integrity. Feasibility measures included number completing treatment, medication compliance (riboflavin detection) and tolerability (side effects, serious adverse events). Target engagement change in mechanisms of interest, defined as a ≥ 0.75 Bayesian posterior probability of an interaction existing favoring PIO over PLC, was demonstrated on measures of craving (BSCS, VAS) and WM integrity indexed by fractional anisotropy (FA) values. Outcomes indicated greater decrease in craving and greater increase in FA values in the PIO group. Feasibility was demonstrated by high completion rates among those starting treatment (21/26 = 80%) and medication compliance (≥ 80%). There were no reported serious adverse events for PIO. Compared with placebo, patients receiving pioglitazone show a higher likelihood of reduced cocaine craving and improved brain white matter integrity as a function of time in treatment. Pioglitazone shows good feasibility as a treatment for cocaine use disorder. © 2017 Society for the Study of Addiction.

A regulatory toolbox of MiniPromoters to drive selective expression in the brain

PubMed Central

Portales-Casamar, Elodie; Swanson, Douglas J.; Liu, Li; de Leeuw, Charles N.; Banks, Kathleen G.; Ho Sui, Shannan J.; Fulton, Debra L.; Ali, Johar; Amirabbasi, Mahsa; Arenillas, David J.; Babyak, Nazar; Black, Sonia F.; Bonaguro, Russell J.; Brauer, Erich; Candido, Tara R.; Castellarin, Mauro; Chen, Jing; Chen, Ying; Cheng, Jason C. Y.; Chopra, Vik; Docking, T. Roderick; Dreolini, Lisa; D'Souza, Cletus A.; Flynn, Erin K.; Glenn, Randy; Hatakka, Kristi; Hearty, Taryn G.; Imanian, Behzad; Jiang, Steven; Khorasan-zadeh, Shadi; Komljenovic, Ivana; Laprise, Stéphanie; Liao, Nancy Y.; Lim, Jonathan S.; Lithwick, Stuart; Liu, Flora; Liu, Jun; Lu, Meifen; McConechy, Melissa; McLeod, Andrea J.; Milisavljevic, Marko; Mis, Jacek; O'Connor, Katie; Palma, Betty; Palmquist, Diana L.; Schmouth, Jean-François; Swanson, Magdalena I.; Tam, Bonny; Ticoll, Amy; Turner, Jenna L.; Varhol, Richard; Vermeulen, Jenny; Watkins, Russell F.; Wilson, Gary; Wong, Bibiana K. Y.; Wong, Siaw H.; Wong, Tony Y. T.; Yang, George S.; Ypsilanti, Athena R.; Jones, Steven J. M.; Holt, Robert A.; Goldowitz, Daniel; Wasserman, Wyeth W.; Simpson, Elizabeth M.

2010-01-01

The Pleiades Promoter Project integrates genomewide bioinformatics with large-scale knockin mouse production and histological examination of expression patterns to develop MiniPromoters and related tools designed to study and treat the brain by directed gene expression. Genes with brain expression patterns of interest are subjected to bioinformatic analysis to delineate candidate regulatory regions, which are then incorporated into a panel of compact human MiniPromoters to drive expression to brain regions and cell types of interest. Using single-copy, homologous-recombination “knockins” in embryonic stem cells, each MiniPromoter reporter is integrated immediately 5′ of the Hprt locus in the mouse genome. MiniPromoter expression profiles are characterized in differentiation assays of the transgenic cells or in mouse brains following transgenic mouse production. Histological examination of adult brains, eyes, and spinal cords for reporter gene activity is coupled to costaining with cell-type–specific markers to define expression. The publicly available Pleiades MiniPromoter Project is a key resource to facilitate research on brain development and therapies. PMID:20807748

The Virtual Mouse Brain: A Computational Neuroinformatics Platform to Study Whole Mouse Brain Dynamics.

PubMed

Melozzi, Francesca; Woodman, Marmaduke M; Jirsa, Viktor K; Bernard, Christophe

2017-01-01

Connectome-based modeling of large-scale brain network dynamics enables causal in silico interrogation of the brain's structure-function relationship, necessitating the close integration of diverse neuroinformatics fields. Here we extend the open-source simulation software The Virtual Brain (TVB) to whole mouse brain network modeling based on individual diffusion magnetic resonance imaging (dMRI)-based or tracer-based detailed mouse connectomes. We provide practical examples on how to use The Virtual Mouse Brain (TVMB) to simulate brain activity, such as seizure propagation and the switching behavior of the resting state dynamics in health and disease. TVMB enables theoretically driven experimental planning and ways to test predictions in the numerous strains of mice available to study brain function in normal and pathological conditions.

Segregated Systems of Human Brain Networks.

PubMed

Wig, Gagan S

2017-12-01

The organization of the brain network enables its function. Evaluation of this organization has revealed that large-scale brain networks consist of multiple segregated subnetworks of interacting brain areas. Descriptions of resting-state network architecture have provided clues for understanding the functional significance of these segregated subnetworks, many of which correspond to distinct brain systems. The present report synthesizes accumulating evidence to reveal how maintaining segregated brain systems renders the human brain network functionally specialized, adaptable to task demands, and largely resilient following focal brain damage. The organizational properties that support system segregation are harmonious with the properties that promote integration across the network, but confer unique and important features to the brain network that are central to its function and behavior. Copyright © 2017 Elsevier Ltd. All rights reserved.

Low frequency steady-state brain responses modulate large scale functional networks in a frequency-specific means.

PubMed

Wang, Yi-Feng; Long, Zhiliang; Cui, Qian; Liu, Feng; Jing, Xiu-Juan; Chen, Heng; Guo, Xiao-Nan; Yan, Jin H; Chen, Hua-Fu

2016-01-01

Neural oscillations are essential for brain functions. Research has suggested that the frequency of neural oscillations is lower for more integrative and remote communications. In this vein, some resting-state studies have suggested that large scale networks function in the very low frequency range (<1 Hz). However, it is difficult to determine the frequency characteristics of brain networks because both resting-state studies and conventional frequency tagging approaches cannot simultaneously capture multiple large scale networks in controllable cognitive activities. In this preliminary study, we aimed to examine whether large scale networks can be modulated by task-induced low frequency steady-state brain responses (lfSSBRs) in a frequency-specific pattern. In a revised attention network test, the lfSSBRs were evoked in the triple network system and sensory-motor system, indicating that large scale networks can be modulated in a frequency tagging way. Furthermore, the inter- and intranetwork synchronizations as well as coherence were increased at the fundamental frequency and the first harmonic rather than at other frequency bands, indicating a frequency-specific modulation of information communication. However, there was no difference among attention conditions, indicating that lfSSBRs modulate the general attention state much stronger than distinguishing attention conditions. This study provides insights into the advantage and mechanism of lfSSBRs. More importantly, it paves a new way to investigate frequency-specific large scale brain activities. © 2015 Wiley Periodicals, Inc.

The Metastable Brain

PubMed Central

Tognoli, Emmanuelle; Kelso, J. A. Scott

2014-01-01

Neural ensembles oscillate across a broad range of frequencies and are transiently coupled or “bound” together when people attend to a stimulus, perceive, think and act. This is a dynamic, self-assembling process, with parts of the brain engaging and disengaging in time. But how is it done? The theory of Coordination Dynamics proposes a mechanism called metastability, a subtle blend of integration and segregation. Tendencies for brain regions to express their individual autonomy and specialized functions (segregation, modularity) coexist with tendencies to couple and coordinate globally for multiple functions (integration). Although metastability has garnered increasing attention, it has yet to be demonstrated and treated within a fully spatiotemporal perspective. Here, we illustrate metastability in continuous neural and behavioral recordings, and we discuss theory and experiments at multiple scales suggesting that metastable dynamics underlie the real-time coordination necessary for the brain's dynamic cognitive, behavioral and social functions. PMID:24411730

The impact of unilateral brain damage on anticipatory grip force scaling when lifting everyday objects.

PubMed

Eidenmüller, S; Randerath, J; Goldenberg, G; Li, Y; Hermsdörfer, J

2014-08-01

The scaling of our finger forces according to the properties of manipulated objects is an elementary prerequisite of skilled motor behavior. Lesions of the motor-dominant left brain may impair several aspects of motor planning. For example, limb-apraxia, a tool-use disorder after left brain damage is thought to be caused by deficient recall or integration of tool-use knowledge into an action plan. The aim of the present study was to investigate whether left brain damage affects anticipatory force scaling when lifting everyday objects. We examined 26 stroke patients with unilateral brain damage (16 with left brain damage, ten with right brain damage) and 21 healthy control subjects. Limb apraxia was assessed by testing pantomime of familiar tool-use and imitation of meaningless hand postures. Participants grasped and lifted twelve randomly presented everyday objects. Grip force was measured with help of sensors fixed on thumb, index and middle-finger. The maximum rate of grip force was determined to quantify the precision of anticipation of object properties. Regression analysis yielded clear deficits of anticipation in the group of patients with left brain damage, while the comparison of patient with right brain damage with their respective control group did not reveal comparable deficits. Lesion-analyses indicate that brain structures typically associated with a tool-use network in the left hemisphere play an essential role for anticipatory grip force scaling, especially the left inferior frontal gyrus (IFG) and the premotor cortex (PMC). Furthermore, significant correlations of impaired anticipation with limb apraxia scores suggest shared representations. However, the presence of dissociations, implicates also independent processes. Overall, our findings suggest that the left hemisphere is engaged in anticipatory grip force scaling for lifting everyday objects. The underlying neural substrate is not restricted to a single region or stream; instead it may rely on the intact functioning of a left hemisphere network that may overlap with the left hemisphere dominant tool-use network. Copyright © 2014 Elsevier Ltd. All rights reserved.

Friends with social benefits: host-microbe interactions as a driver of brain evolution and development?

PubMed Central

Stilling, Roman M.; Bordenstein, Seth R.; Dinan, Timothy G.; Cryan, John F.

2014-01-01

The tight association of the human body with trillions of colonizing microbes that we observe today is the result of a long evolutionary history. Only very recently have we started to understand how this symbiosis also affects brain function and behavior. In this hypothesis and theory article, we propose how host-microbe associations potentially influenced mammalian brain evolution and development. In particular, we explore the integration of human brain development with evolution, symbiosis, and RNA biology, which together represent a “social triangle” that drives human social behavior and cognition. We argue that, in order to understand how inter-kingdom communication can affect brain adaptation and plasticity, it is inevitable to consider epigenetic mechanisms as important mediators of genome-microbiome interactions on an individual as well as a transgenerational time scale. Finally, we unite these interpretations with the hologenome theory of evolution. Taken together, we propose a tighter integration of neuroscience fields with host-associated microbiology by taking an evolutionary perspective. PMID:25401092

TVB-EduPack—An Interactive Learning and Scripting Platform for The Virtual Brain

PubMed Central

Matzke, Henrik; Schirner, Michael; Vollbrecht, Daniel; Rothmeier, Simon; Llarena, Adalberto; Rojas, Raúl; Triebkorn, Paul; Domide, Lia; Mersmann, Jochen; Solodkin, Ana; Jirsa, Viktor K.; McIntosh, Anthony Randal; Ritter, Petra

2015-01-01

The Virtual Brain (TVB; thevirtualbrain.org) is a neuroinformatics platform for full brain network simulation based on individual anatomical connectivity data. The framework addresses clinical and neuroscientific questions by simulating multi-scale neural dynamics that range from local population activity to large-scale brain function and related macroscopic signals like electroencephalography and functional magnetic resonance imaging. TVB is equipped with a graphical and a command-line interface to create models that capture the characteristic biological variability to predict the brain activity of individual subjects. To enable researchers from various backgrounds a quick start into TVB and brain network modeling in general, we developed an educational module: TVB-EduPack. EduPack offers two educational functionalities that seamlessly integrate into TVB's graphical user interface (GUI): (i) interactive tutorials introduce GUI elements, guide through the basic mechanics of software usage and develop complex use-case scenarios; animations, videos and textual descriptions transport essential principles of computational neuroscience and brain modeling; (ii) an automatic script generator records model parameters and produces input files for TVB's Python programming interface; thereby, simulation configurations can be exported as scripts that allow flexible customization of the modeling process and self-defined batch- and post-processing applications while benefitting from the full power of the Python language and its toolboxes. This article covers the implementation of TVB-EduPack and its integration into TVB architecture. Like TVB, EduPack is an open source community project that lives from the participation and contribution of its users. TVB-EduPack can be obtained as part of TVB from thevirtualbrain.org. PMID:26635597

Integrating neuroinformatics tools in TheVirtualBrain.

PubMed

Woodman, M Marmaduke; Pezard, Laurent; Domide, Lia; Knock, Stuart A; Sanz-Leon, Paula; Mersmann, Jochen; McIntosh, Anthony R; Jirsa, Viktor

2014-01-01

TheVirtualBrain (TVB) is a neuroinformatics Python package representing the convergence of clinical, systems, and theoretical neuroscience in the analysis, visualization and modeling of neural and neuroimaging dynamics. TVB is composed of a flexible simulator for neural dynamics measured across scales from local populations to large-scale dynamics measured by electroencephalography (EEG), magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI), and core analytic and visualization functions, all accessible through a web browser user interface. A datatype system modeling neuroscientific data ties together these pieces with persistent data storage, based on a combination of SQL and HDF5. These datatypes combine with adapters allowing TVB to integrate other algorithms or computational systems. TVB provides infrastructure for multiple projects and multiple users, possibly participating under multiple roles. For example, a clinician might import patient data to identify several potential lesion points in the patient's connectome. A modeler, working on the same project, tests these points for viability through whole brain simulation, based on the patient's connectome, and subsequent analysis of dynamical features. TVB also drives research forward: the simulator itself represents the culmination of several simulation frameworks in the modeling literature. The availability of the numerical methods, set of neural mass models and forward solutions allows for the construction of a wide range of brain-scale simulation scenarios. This paper briefly outlines the history and motivation for TVB, describing the framework and simulator, giving usage examples in the web UI and Python scripting.

Integrating neuroinformatics tools in TheVirtualBrain

PubMed Central

Woodman, M. Marmaduke; Pezard, Laurent; Domide, Lia; Knock, Stuart A.; Sanz-Leon, Paula; Mersmann, Jochen; McIntosh, Anthony R.; Jirsa, Viktor

2014-01-01

TheVirtualBrain (TVB) is a neuroinformatics Python package representing the convergence of clinical, systems, and theoretical neuroscience in the analysis, visualization and modeling of neural and neuroimaging dynamics. TVB is composed of a flexible simulator for neural dynamics measured across scales from local populations to large-scale dynamics measured by electroencephalography (EEG), magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI), and core analytic and visualization functions, all accessible through a web browser user interface. A datatype system modeling neuroscientific data ties together these pieces with persistent data storage, based on a combination of SQL and HDF5. These datatypes combine with adapters allowing TVB to integrate other algorithms or computational systems. TVB provides infrastructure for multiple projects and multiple users, possibly participating under multiple roles. For example, a clinician might import patient data to identify several potential lesion points in the patient's connectome. A modeler, working on the same project, tests these points for viability through whole brain simulation, based on the patient's connectome, and subsequent analysis of dynamical features. TVB also drives research forward: the simulator itself represents the culmination of several simulation frameworks in the modeling literature. The availability of the numerical methods, set of neural mass models and forward solutions allows for the construction of a wide range of brain-scale simulation scenarios. This paper briefly outlines the history and motivation for TVB, describing the framework and simulator, giving usage examples in the web UI and Python scripting. PMID:24795617

Large-Scale Brain Simulation and Disorders of Consciousness. Mapping Technical and Conceptual Issues.

PubMed

Farisco, Michele; Kotaleski, Jeanette H; Evers, Kathinka

2018-01-01

Modeling and simulations have gained a leading position in contemporary attempts to describe, explain, and quantitatively predict the human brain's operations. Computer models are highly sophisticated tools developed to achieve an integrated knowledge of the brain with the aim of overcoming the actual fragmentation resulting from different neuroscientific approaches. In this paper we investigate the plausibility of simulation technologies for emulation of consciousness and the potential clinical impact of large-scale brain simulation on the assessment and care of disorders of consciousness (DOCs), e.g., Coma, Vegetative State/Unresponsive Wakefulness Syndrome, Minimally Conscious State. Notwithstanding their technical limitations, we suggest that simulation technologies may offer new solutions to old practical problems, particularly in clinical contexts. We take DOCs as an illustrative case, arguing that the simulation of neural correlates of consciousness is potentially useful for improving treatments of patients with DOCs.

Neural Signatures of Autism Spectrum Disorders: Insights into Brain Network Dynamics

PubMed Central

Hernandez, Leanna M; Rudie, Jeffrey D; Green, Shulamite A; Bookheimer, Susan; Dapretto, Mirella

2015-01-01

Neuroimaging investigations of autism spectrum disorders (ASDs) have advanced our understanding of atypical brain function and structure, and have recently converged on a model of altered network-level connectivity. Traditional task-based functional magnetic resonance imaging (MRI) and volume-based structural MRI studies have identified widespread atypicalities in brain regions involved in social behavior and other core ASD-related behavioral deficits. More recent advances in MR-neuroimaging methods allow for quantification of brain connectivity using diffusion tensor imaging, functional connectivity, and graph theoretic methods. These newer techniques have moved the field toward a systems-level understanding of ASD etiology, integrating functional and structural measures across distal brain regions. Neuroimaging findings in ASD as a whole have been mixed and at times contradictory, likely due to the vast genetic and phenotypic heterogeneity characteristic of the disorder. Future longitudinal studies of brain development will be crucial to yield insights into mechanisms of disease etiology in ASD sub-populations. Advances in neuroimaging methods and large-scale collaborations will also allow for an integrated approach linking neuroimaging, genetics, and phenotypic data. PMID:25011468

Flexible Organic Electronics for Use in Neural Sensing

PubMed Central

Bink, Hank; Lai, Yuming; Saudari, Sangameshwar R.; Helfer, Brian; Viventi, Jonathan; Van der Spiegel, Jan; Litt, Brian; Kagan, Cherie

2016-01-01

Recent research in brain-machine interfaces and devices to treat neurological disease indicate that important network activity exists at temporal and spatial scales beyond the resolution of existing implantable devices. High density, active electrode arrays hold great promise in enabling high-resolution interface with the brain to access and influence this network activity. Integrating flexible electronic devices directly at the neural interface can enable thousands of multiplexed electrodes to be connected using many fewer wires. Active electrode arrays have been demonstrated using flexible, inorganic silicon transistors. However, these approaches may be limited in their ability to be cost-effectively scaled to large array sizes (8×8 cm). Here we show amplifiers built using flexible organic transistors with sufficient performance for neural signal recording. We also demonstrate a pathway for a fully integrated, amplified and multiplexed electrode array built from these devices. PMID:22255558

Intraoperative virtual brain counseling

NASA Astrophysics Data System (ADS)

Jiang, Zhaowei; Grosky, William I.; Zamorano, Lucia J.; Muzik, Otto; Diaz, Fernando

1997-06-01

Our objective is to offer online real-tim e intelligent guidance to the neurosurgeon. Different from traditional image-guidance technologies that offer intra-operative visualization of medical images or atlas images, virtual brain counseling goes one step further. It can distinguish related brain structures and provide information about them intra-operatively. Virtual brain counseling is the foundation for surgical planing optimization and on-line surgical reference. It can provide a warning system that alerts the neurosurgeon if the chosen trajectory will pass through eloquent brain areas. In order to fulfill this objective, tracking techniques are involved for intra- operativity. Most importantly, a 3D virtual brian environment, different from traditional 3D digitized atlases, is an object-oriented model of the brain that stores information about different brain structures together with their elated information. An object-oriented hierarchical hyper-voxel space (HHVS) is introduced to integrate anatomical and functional structures. Spatial queries based on position of interest, line segment of interest, and volume of interest are introduced in this paper. The virtual brain environment is integrated with existing surgical pre-planning and intra-operative tracking systems to provide information for planning optimization and on-line surgical guidance. The neurosurgeon is alerted automatically if the planned treatment affects any critical structures. Architectures such as HHVS and algorithms, such as spatial querying, normalizing, and warping are presented in the paper. A prototype has shown that the virtual brain is intuitive in its hierarchical 3D appearance. It also showed that HHVS, as the key structure for virtual brain counseling, efficiently integrates multi-scale brain structures based on their spatial relationships.This is a promising development for optimization of treatment plans and online surgical intelligent guidance.

The circuit architecture of whole brains at the mesoscopic scale.

PubMed

Mitra, Partha P

2014-09-17

Vertebrate brains of even moderate size are composed of astronomically large numbers of neurons and show a great degree of individual variability at the microscopic scale. This variation is presumably the result of phenotypic plasticity and individual experience. At a larger scale, however, relatively stable species-typical spatial patterns are observed in neuronal architecture, e.g., the spatial distributions of somata and axonal projection patterns, probably the result of a genetically encoded developmental program. The mesoscopic scale of analysis of brain architecture is the transitional point between a microscopic scale where individual variation is prominent and the macroscopic level where a stable, species-typical neural architecture is observed. The empirical existence of this scale, implicit in neuroanatomical atlases, combined with advances in computational resources, makes studying the circuit architecture of entire brains a practical task. A methodology has previously been proposed that employs a shotgun-like grid-based approach to systematically cover entire brain volumes with injections of neuronal tracers. This methodology is being employed to obtain mesoscale circuit maps in mouse and should be applicable to other vertebrate taxa. The resulting large data sets raise issues of data representation, analysis, and interpretation, which must be resolved. Even for data representation the challenges are nontrivial: the conventional approach using regional connectivity matrices fails to capture the collateral branching patterns of projection neurons. Future success of this promising research enterprise depends on the integration of previous neuroanatomical knowledge, partly through the development of suitable computational tools that encapsulate such expertise. Copyright © 2014 Elsevier Inc. All rights reserved.

Quantifying Mesoscale Neuroanatomy Using X-Ray Microtomography

PubMed Central

Gray Roncal, William; Prasad, Judy A.; Fernandes, Hugo L.; Gürsoy, Doga; De Andrade, Vincent; Fezzaa, Kamel; Xiao, Xianghui; Vogelstein, Joshua T.; Jacobsen, Chris; Körding, Konrad P.

2017-01-01

Methods for resolving the three-dimensional (3D) microstructure of the brain typically start by thinly slicing and staining the brain, followed by imaging numerous individual sections with visible light photons or electrons. In contrast, X-rays can be used to image thick samples, providing a rapid approach for producing large 3D brain maps without sectioning. Here we demonstrate the use of synchrotron X-ray microtomography (µCT) for producing mesoscale (∼1 µm 3 resolution) brain maps from millimeter-scale volumes of mouse brain. We introduce a pipeline for µCT-based brain mapping that develops and integrates methods for sample preparation, imaging, and automated segmentation of cells, blood vessels, and myelinated axons, in addition to statistical analyses of these brain structures. Our results demonstrate that X-ray tomography achieves rapid quantification of large brain volumes, complementing other brain mapping and connectomics efforts. PMID:29085899

Normative brain size variation and brain shape diversity in humans.

PubMed

Reardon, P K; Seidlitz, Jakob; Vandekar, Simon; Liu, Siyuan; Patel, Raihaan; Park, Min Tae M; Alexander-Bloch, Aaron; Clasen, Liv S; Blumenthal, Jonathan D; Lalonde, Francois M; Giedd, Jay N; Gur, Ruben C; Gur, Raquel E; Lerch, Jason P; Chakravarty, M Mallar; Satterthwaite, Theodore D; Shinohara, Russell T; Raznahan, Armin

2018-06-15

Brain size variation over primate evolution and human development is associated with shifts in the proportions of different brain regions. Individual brain size can vary almost twofold among typically developing humans, but the consequences of this for brain organization remain poorly understood. Using in vivo neuroimaging data from more than 3000 individuals, we find that larger human brains show greater areal expansion in distributed frontoparietal cortical networks and related subcortical regions than in limbic, sensory, and motor systems. This areal redistribution recapitulates cortical remodeling across evolution, manifests by early childhood in humans, and is linked to multiple markers of heightened metabolic cost and neuronal connectivity. Thus, human brain shape is systematically coupled to naturally occurring variations in brain size through a scaling map that integrates spatiotemporally diverse aspects of neurobiology. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Dynamic functional connectivity: Promise, issues, and interpretations

PubMed Central

Hutchison, R. Matthew; Womelsdorf, Thilo; Allen, Elena A.; Bandettini, Peter A.; Calhoun, Vince D.; Corbetta, Maurizio; Penna, Stefania Della; Duyn, Jeff H.; Glover, Gary H.; Gonzalez-Castillo, Javier; Handwerker, Daniel A.; Keilholz, Shella; Kiviniemi, Vesa; Leopold, David A.; de Pasquale, Francesco; Sporns, Olaf; Walter, Martin; Chang, Catie

2013-01-01

The brain must dynamically integrate, coordinate, and respond to internal and external stimuli across multiple time scales. Non-invasive measurements of brain activity with fMRI have greatly advanced our understanding of the large-scale functional organization supporting these fundamental features of brain function. Conclusions from previous resting-state fMRI investigations were based upon static descriptions of functional connectivity (FC), and only recently studies have begun to capitalize on the wealth of information contained within the temporal features of spontaneous BOLD FC. Emerging evidence suggests that dynamic FC metrics may index changes in macroscopic neural activity patterns underlying critical aspects of cognition and behavior, though limitations with regard to analysis and interpretation remain. Here, we review recent findings, methodological considerations, neural and behavioral correlates, and future directions in the emerging field of dynamic FC investigations. PMID:23707587

The modulation of EEG variability between internally- and externally-driven cognitive states varies with maturation and task performance

PubMed Central

Willatt, Stephanie E.; Cortese, Filomeno; Protzner, Andrea B.

2017-01-01

Increasing evidence suggests that brain signal variability is an important measure of brain function reflecting information processing capacity and functional integrity. In this study, we examined how maturation from childhood to adulthood affects the magnitude and spatial extent of state-to-state transitions in brain signal variability, and how this relates to cognitive performance. We looked at variability changes between resting-state and task (a symbol-matching task with three levels of difficulty), and within trial (fixation, post-stimulus, and post-response). We calculated variability with multiscale entropy (MSE), and additionally examined spectral power density (SPD) from electroencephalography (EEG) in children aged 8–14, and in adults aged 18–33. Our results suggest that maturation is characterized by increased local information processing (higher MSE at fine temporal scales) and decreased long-range interactions with other neural populations (lower MSE at coarse temporal scales). Children show MSE changes that are similar in magnitude, but greater in spatial extent when transitioning between internally- and externally-driven brain states. Additionally, we found that in children, greater changes in task difficulty were associated with greater magnitude of modulation in MSE. Our results suggest that the interplay between maturational and state-to-state changes in brain signal variability manifest across different spatial and temporal scales, and influence information processing capacity in the brain. PMID:28750035

Challenges and Opportunities in Mining Neuroscience Data

PubMed Central

Akil, Huda; Martone, Maryann E.; Van Essen, David C.

2011-01-01

Understanding the brain requires a broad range of approaches and methods from the domains of biology, psychology, chemistry, physics, and mathematics. The fundamental challenge is to decipher the “neural choreography” associated with complex behaviors and functions, including thoughts, memories, actions, and emotions. This demands the acquisition and integration of vast amounts of data of many types, at multiple scales in time and in space. Here, we discuss the need for neuroinformatics approaches to accelerate progress, using several illustrative examples. The nascent field of ‘connectomics’ aims to comprehensively describe neuronal connectivity at either a macroscopic level (long-distance pathways for the entire brain) or a microscopic level (axons, dendrites, synapses in a small brain region). The Neuroscience Information Framework encompasses all of neuroscience and facilitates integration of existing knowledge and databases of many types. These examples illustrate the opportunities and challenges of data mining across multiple tiers of neuroscience information and underscore the need for cultural and infrastructure changes if neuroinformatics is to fulfill its potential to advance our understanding of the brain. PMID:21311009

Integrative Understanding of Emergent Brain Properties, Quantum Brain Hypotheses, and Connectome Alterations in Dementia are Key Challenges to Conquer Alzheimer's Disease.

PubMed

Kuljiš, Rodrigo O

2010-01-01

The biological substrate for cognition remains a challenge as much as defining this function of living beings. Here, we examine some of the difficulties to understand normal and disordered cognition in humans. We use aspects of Alzheimer's disease and related disorders to illustrate how the wealth of information at many conceptually separate, even intellectually decoupled, physical scales - in particular at the Molecular Neuroscience versus Systems Neuroscience/Neuropsychology levels - presents a challenge in terms of true interdisciplinary integration towards a coherent understanding. These unresolved dilemmas include critically the as yet untested quantum brain hypothesis, and the embryonic attempts to develop and define the so-called connectome in humans and in non-human models of disease. To mitigate these challenges, we propose a scheme incorporating the vast array of scales of the space and time (space-time) manifold from at least the subatomic through cognitive-behavioral dimensions of inquiry, to achieve a new understanding of both normal and disordered cognition, that is essential for a new era of progress in the Generative Sciences and its application to translational efforts for disease prevention and treatment.

Neurosurgical sapphire handheld probe for intraoperative optical diagnostics, laser coagulation and aspiration of malignant brain tissue

NASA Astrophysics Data System (ADS)

Shikunova, Irina A.; Zaytsev, Kirill I.; Stryukov, Dmitrii O.; Dubyanskaya, Evgenia N.; Kurlov, Vladimir N.

2017-07-01

In this paper, a handheld contact probe based on sapphire shaped crystal was developed for the intraoperative optical diagnosis and aspiration of malignant brain tissue combined with the laser hemostasis. Such a favorable combination of several functions in a single instrument significantly increases its clinical relevance. It makes possible highly-accurate real-time detection and removal of either large-scale malignancies or even separate invasive cancer cells. The proposed neuroprobe was integrated into the clinical neurosurgical workflow for the intraoperative fluorescence identification and removal of malignant tissues of the brain.

Co-activation patterns in resting-state fMRI signals.

PubMed

Liu, Xiao; Zhang, Nanyin; Chang, Catie; Duyn, Jeff H

2018-02-08

The brain is a complex system that integrates and processes information across multiple time scales by dynamically coordinating activities over brain regions and circuits. Correlations in resting-state functional magnetic resonance imaging (rsfMRI) signals have been widely used to infer functional connectivity of the brain, providing a metric of functional associations that reflects a temporal average over an entire scan (typically several minutes or longer). Not until recently was the study of dynamic brain interactions at much shorter time scales (seconds to minutes) considered for inference of functional connectivity. One method proposed for this objective seeks to identify and extract recurring co-activation patterns (CAPs) that represent instantaneous brain configurations at single time points. Here, we review the development and recent advancement of CAP methodology and other closely related approaches, as well as their applications and associated findings. We also discuss the potential neural origins and behavioral relevance of CAPs, along with methodological issues and future research directions in the analysis of fMRI co-activation patterns. Copyright © 2018 Elsevier Inc. All rights reserved.

To simulate or not to simulate: what are the questions?

PubMed

Dudai, Yadin; Evers, Kathinka

2014-10-22

Simulation is a powerful method in science and engineering. However, simulation is an umbrella term, and its meaning and goals differ among disciplines. Rapid advances in neuroscience and computing draw increasing attention to large-scale brain simulations. What is the meaning of simulation, and what should the method expect to achieve? We discuss the concept of simulation from an integrated scientific and philosophical vantage point and pinpoint selected issues that are specific to brain simulation.

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.

Topographic mapping of a hierarchy of temporal receptive windows using a narrated story

PubMed Central

Lerner, Y.; Honey, C.J.; Silbert, L.J.; Hasson, U.

2011-01-01

Real life activities, such as watching a movie or engaging in conversation, unfold over many minutes. In the course of such activities the brain has to integrate information over multiple time scales. We recently proposed that the brain uses similar strategies for integrating information across space and over time. Drawing a parallel with spatial receptive fields (SRF), we defined the temporal receptive window(TRW) of a cortical microcircuit as the length of time prior to a response during which sensory information may affect that response. Our previous findings in the visual system are consistent with the hypothesis that TRWs become larger when moving from low-level sensory to high-level perceptual and cognitive areas. In this study, we mapped TRWs in auditory and language areas by measuring fMRI activity in subjects listening to a real life story scrambled at the time scales of words, sentences and paragraphs. Our results revealed a hierarchical topography of TRWs. In early auditory cortices (A1+), brain responses were driven mainly by the momentary incoming input and were similarly reliable across all scrambling conditions. In areas with an intermediate TRW, coherent information at the sentence time scale or longer was necessary to evoke reliable responses. At the apex of the TRW hierarchy we found parietal and frontal areas which responded reliably only when intact paragraphs were heard in a meaningful sequence. These results suggest that the time scale of processing is a functional property that may provide a general organizing principle for the human cerebral cortex. PMID:21414912

A biased competition account of attention and memory in Alzheimer's disease

PubMed Central

Finke, Kathrin; Myers, Nicholas; Bublak, Peter; Sorg, Christian

2013-01-01

The common view of Alzheimer's disease (AD) is that of an age-related memory disorder, i.e. declarative memory deficits are the first signs of the disease and associated with progressive brain changes in the medial temporal lobes and the default mode network. However, two findings challenge this view. First, new model-based tools of attention research have revealed that impaired selective attention accompanies memory deficits from early pre-dementia AD stages on. Second, very early distributed lesions of lateral parietal networks may cause these attention deficits by disrupting brain mechanisms underlying attentional biased competition. We suggest that memory and attention impairments might indicate disturbances of a common underlying neurocognitive mechanism. We propose a unifying account of impaired neural interactions within and across brain networks involved in attention and memory inspired by the biased competition principle. We specify this account at two levels of analysis: at the computational level, the selective competition of representations during both perception and memory is biased by AD-induced lesions; at the large-scale brain level, integration within and across intrinsic brain networks, which overlap in parietal and temporal lobes, is disrupted. This account integrates a large amount of previously unrelated findings of changed behaviour and brain networks and favours a brain mechanism-centred view on AD. PMID:24018724

A biased competition account of attention and memory in Alzheimer's disease.

PubMed

Finke, Kathrin; Myers, Nicholas; Bublak, Peter; Sorg, Christian

2013-10-19

The common view of Alzheimer's disease (AD) is that of an age-related memory disorder, i.e. declarative memory deficits are the first signs of the disease and associated with progressive brain changes in the medial temporal lobes and the default mode network. However, two findings challenge this view. First, new model-based tools of attention research have revealed that impaired selective attention accompanies memory deficits from early pre-dementia AD stages on. Second, very early distributed lesions of lateral parietal networks may cause these attention deficits by disrupting brain mechanisms underlying attentional biased competition. We suggest that memory and attention impairments might indicate disturbances of a common underlying neurocognitive mechanism. We propose a unifying account of impaired neural interactions within and across brain networks involved in attention and memory inspired by the biased competition principle. We specify this account at two levels of analysis: at the computational level, the selective competition of representations during both perception and memory is biased by AD-induced lesions; at the large-scale brain level, integration within and across intrinsic brain networks, which overlap in parietal and temporal lobes, is disrupted. This account integrates a large amount of previously unrelated findings of changed behaviour and brain networks and favours a brain mechanism-centred view on AD.

Return to productive activity after traumatic brain injury: relationship with measures of disability, handicap, and community integration.

PubMed

Wagner, Amy K; Hammond, Flora M; Sasser, Howell C; Wiercisiewski, David

2002-01-01

To identify which factors are associated with successful return to productive activity (RTPA) 1 year after hospitalization with traumatic brain injury (TBI) and to examine the relations between successful RTPA and other measures of impairment, disability, handicap, and integration into the community. Prospective study with 1-year follow-up. Level I trauma center. One hundred five respondents from a cohort of 378 adults hospitalized with TBI admitted between September 1997 and May 1998. Not applicable. Return to productive work 1 year after injury; Disability Rating Scale (DRS); and Community Integration Scale (CIQ). Of the 105 participants, 72% achieved RTPA. Logistic regression showed an association between RPTA and the following factors: premorbid educational level, premorbid psychiatric history, violent mechanism of injury, discharge status after acute hospitalization, prior alcohol and drug use, and injury severity. Handicap and community integration at 1-year postinjury, as measured by subscales of the DRS and the CIQ, were also associated with RTPA. Premorbid and injury-related variables and measures of handicap and community integration were associated with RTPA at 1 year. To understand and effectively support vocational pursuits in the TBI population, future studies are needed to define further causality and origin of these relationships. Copyright 2002 by the American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and Rehabilitation

Highly Crumpled All-Carbon Transistors for Brain Activity Recording.

PubMed

Yang, Long; Zhao, Yan; Xu, Wenjing; Shi, Enzheng; Wei, Wenjing; Li, Xinming; Cao, Anyuan; Cao, Yanping; Fang, Ying

2017-01-11

Neural probes based on graphene field-effect transistors have been demonstrated. Yet, the minimum detectable signal of graphene transistor-based probes is inversely proportional to the square root of the active graphene area. This fundamentally limits the scaling of graphene transistor-based neural probes for improved spatial resolution in brain activity recording. Here, we address this challenge using highly crumpled all-carbon transistors formed by compressing down to 16% of its initial area. All-carbon transistors, chemically synthesized by seamless integration of graphene channels and hybrid graphene/carbon nanotube electrodes, maintained structural integrity and stable electronic properties under large mechanical deformation, whereas stress-induced cracking and junction failure occurred in conventional graphene/metal transistors. Flexible, highly crumpled all-carbon transistors were further verified for in vivo recording of brain activity in rats. These results highlight the importance of advanced material and device design concepts to make improvements in neuroelectronics.

Consciousness, cognition and brain networks: New perspectives.

PubMed

Aldana, E M; Valverde, J L; Fábregas, N

2016-10-01

A detailed analysis of the literature on consciousness and cognition mechanisms based on the neural networks theory is presented. The immune and inflammatory response to the anesthetic-surgical procedure induces modulation of neuronal plasticity by influencing higher cognitive functions. Anesthetic drugs can cause unconsciousness, producing a functional disruption of cortical and thalamic cortical integration complex. The external and internal perceptions are processed through an intricate network of neural connections, involving the higher nervous activity centers, especially the cerebral cortex. This requires an integrated model, formed by neural networks and their interactions with highly specialized regions, through large-scale networks, which are distributed throughout the brain collecting information flow of these perceptions. Functional and effective connectivity between large-scale networks, are essential for consciousness, unconsciousness and cognition. It is what is called the "human connectome" or map neural networks. Copyright © 2014 Sociedad Española de Anestesiología, Reanimación y Terapéutica del Dolor. Publicado por Elsevier España, S.L.U. All rights reserved.

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

Perdikaris, Paris, E-mail: parisp@mit.edu; Grinberg, Leopold, E-mail: leopoldgrinberg@us.ibm.com; Karniadakis, George Em, E-mail: george-karniadakis@brown.edu

The aim of this work is to present an overview of recent advances in multi-scale modeling of brain blood flow. In particular, we present some approaches that enable the in silico study of multi-scale and multi-physics phenomena in the cerebral vasculature. We discuss the formulation of continuum and atomistic modeling approaches, present a consistent framework for their concurrent coupling, and list some of the challenges that one needs to overcome in achieving a seamless and scalable integration of heterogeneous numerical solvers. The effectiveness of the proposed framework is demonstrated in a realistic case involving modeling the thrombus formation process takingmore » place on the wall of a patient-specific cerebral aneurysm. This highlights the ability of multi-scale algorithms to resolve important biophysical processes that span several spatial and temporal scales, potentially yielding new insight into the key aspects of brain blood flow in health and disease. Finally, we discuss open questions in multi-scale modeling and emerging topics of future research.« less

Large-Scale Brain Simulation and Disorders of Consciousness. Mapping Technical and Conceptual Issues

PubMed Central

Farisco, Michele; Kotaleski, Jeanette H.; Evers, Kathinka

2018-01-01

Modeling and simulations have gained a leading position in contemporary attempts to describe, explain, and quantitatively predict the human brain’s operations. Computer models are highly sophisticated tools developed to achieve an integrated knowledge of the brain with the aim of overcoming the actual fragmentation resulting from different neuroscientific approaches. In this paper we investigate the plausibility of simulation technologies for emulation of consciousness and the potential clinical impact of large-scale brain simulation on the assessment and care of disorders of consciousness (DOCs), e.g., Coma, Vegetative State/Unresponsive Wakefulness Syndrome, Minimally Conscious State. Notwithstanding their technical limitations, we suggest that simulation technologies may offer new solutions to old practical problems, particularly in clinical contexts. We take DOCs as an illustrative case, arguing that the simulation of neural correlates of consciousness is potentially useful for improving treatments of patients with DOCs. PMID:29740372

The Dynamic Brain: From Spiking Neurons to Neural Masses and Cortical Fields

PubMed Central

Deco, Gustavo; Jirsa, Viktor K.; Robinson, Peter A.; Breakspear, Michael; Friston, Karl

2008-01-01

The cortex is a complex system, characterized by its dynamics and architecture, which underlie many functions such as action, perception, learning, language, and cognition. Its structural architecture has been studied for more than a hundred years; however, its dynamics have been addressed much less thoroughly. In this paper, we review and integrate, in a unifying framework, a variety of computational approaches that have been used to characterize the dynamics of the cortex, as evidenced at different levels of measurement. Computational models at different space–time scales help us understand the fundamental mechanisms that underpin neural processes and relate these processes to neuroscience data. Modeling at the single neuron level is necessary because this is the level at which information is exchanged between the computing elements of the brain; the neurons. Mesoscopic models tell us how neural elements interact to yield emergent behavior at the level of microcolumns and cortical columns. Macroscopic models can inform us about whole brain dynamics and interactions between large-scale neural systems such as cortical regions, the thalamus, and brain stem. Each level of description relates uniquely to neuroscience data, from single-unit recordings, through local field potentials to functional magnetic resonance imaging (fMRI), electroencephalogram (EEG), and magnetoencephalogram (MEG). Models of the cortex can establish which types of large-scale neuronal networks can perform computations and characterize their emergent properties. Mean-field and related formulations of dynamics also play an essential and complementary role as forward models that can be inverted given empirical data. This makes dynamic models critical in integrating theory and experiments. We argue that elaborating principled and informed models is a prerequisite for grounding empirical neuroscience in a cogent theoretical framework, commensurate with the achievements in the physical sciences. PMID:18769680

An integrative architecture for general intelligence and executive function revealed by lesion mapping

PubMed Central

Colom, Roberto; Solomon, Jeffrey; Krueger, Frank; Forbes, Chad; Grafman, Jordan

2012-01-01

Although cognitive neuroscience has made remarkable progress in understanding the involvement of the prefrontal cortex in executive control, the broader functional networks that support high-level cognition and give rise to general intelligence remain to be well characterized. Here, we investigated the neural substrates of the general factor of intelligence (g) and executive function in 182 patients with focal brain damage using voxel-based lesion–symptom mapping. The Wechsler Adult Intelligence Scale and Delis–Kaplan Executive Function System were used to derive measures of g and executive function, respectively. Impaired performance on these measures was associated with damage to a distributed network of left lateralized brain areas, including regions of frontal and parietal cortex and white matter association tracts, which bind these areas into a coordinated system. The observed findings support an integrative framework for understanding the architecture of general intelligence and executive function, supporting their reliance upon a shared fronto-parietal network for the integration and control of cognitive representations and making specific recommendations for the application of the Wechsler Adult Intelligence Scale and Delis–Kaplan Executive Function System to the study of high-level cognition in health and disease. PMID:22396393

Scaling and intermittency of brain events as a manifestation of consciousness

NASA Astrophysics Data System (ADS)

Paradisi, P.; Allegrini, P.; Gemignani, A.; Laurino, M.; Menicucci, D.; Piarulli, A.

2013-01-01

We discuss the critical brain hypothesis and its relationship with intermittent renewal processes displaying power-law decay in the distribution of waiting times between two consecutive renewal events. In particular, studies on complex systems in a "critical" condition show that macroscopic variables, integrating the activities of many individual functional units, undergo fluctuations with an intermittent serial structure characterized by avalanches with inverse-power-law (scale-free) distribution densities of sizes and inter-event times. This condition, which is denoted as "fractal intermittency", was found in the electroencephalograms of subjects observed during a resting state wake condition. It remained unsolved whether fractal intermittency correlates with the stream of consciousness or with a non-task-driven default mode activity, also present in non-conscious states, like deep sleep. After reviewing a method of scaling analysis of intermittent systems based of eventdriven random walks, we show that during deep sleep fractal intermittency breaks down, and reestablishes during REM (Rapid Eye Movement) sleep, with essentially the same anomalous scaling of the pre-sleep wake condition. From the comparison of the pre-sleep wake, deep sleep and REM conditions we argue that the scaling features of intermittent brain events are related to the level of consciousness and, consequently, could be exploited as a possible indicator of consciousness in clinical applications.

Temporal integration and 1/f power scaling in a circuit model of cerebellar interneurons.

PubMed

Maex, Reinoud; Gutkin, Boris

2017-07-01

Inhibitory interneurons interconnected via electrical and chemical (GABA A receptor) synapses form extensive circuits in several brain regions. They are thought to be involved in timing and synchronization through fast feedforward control of principal neurons. Theoretical studies have shown, however, that whereas self-inhibition does indeed reduce response duration, lateral inhibition, in contrast, may generate slow response components through a process of gradual disinhibition. Here we simulated a circuit of interneurons (stellate and basket cells) of the molecular layer of the cerebellar cortex and observed circuit time constants that could rise, depending on parameter values, to >1 s. The integration time scaled both with the strength of inhibition, vanishing completely when inhibition was blocked, and with the average connection distance, which determined the balance between lateral and self-inhibition. Electrical synapses could further enhance the integration time by limiting heterogeneity among the interneurons and by introducing a slow capacitive current. The model can explain several observations, such as the slow time course of OFF-beam inhibition, the phase lag of interneurons during vestibular rotation, or the phase lead of Purkinje cells. Interestingly, the interneuron spike trains displayed power that scaled approximately as 1/ f at low frequencies. In conclusion, stellate and basket cells in cerebellar cortex, and interneuron circuits in general, may not only provide fast inhibition to principal cells but also act as temporal integrators that build a very short-term memory. NEW & NOTEWORTHY The most common function attributed to inhibitory interneurons is feedforward control of principal neurons. In many brain regions, however, the interneurons are densely interconnected via both chemical and electrical synapses but the function of this coupling is largely unknown. Based on large-scale simulations of an interneuron circuit of cerebellar cortex, we propose that this coupling enhances the integration time constant, and hence the memory trace, of the circuit. Copyright © 2017 the American Physiological Society.

Brain-CODE: A Secure Neuroinformatics Platform for Management, Federation, Sharing and Analysis of Multi-Dimensional Neuroscience Data.

PubMed

Vaccarino, Anthony L; Dharsee, Moyez; Strother, Stephen; Aldridge, Don; Arnott, Stephen R; Behan, Brendan; Dafnas, Costas; Dong, Fan; Edgecombe, Kenneth; El-Badrawi, Rachad; El-Emam, Khaled; Gee, Tom; Evans, Susan G; Javadi, Mojib; Jeanson, Francis; Lefaivre, Shannon; Lutz, Kristen; MacPhee, F Chris; Mikkelsen, Jordan; Mikkelsen, Tom; Mirotchnick, Nicholas; Schmah, Tanya; Studzinski, Christa M; Stuss, Donald T; Theriault, Elizabeth; Evans, Kenneth R

2018-01-01

Historically, research databases have existed in isolation with no practical avenue for sharing or pooling medical data into high dimensional datasets that can be efficiently compared across databases. To address this challenge, the Ontario Brain Institute's "Brain-CODE" is a large-scale neuroinformatics platform designed to support the collection, storage, federation, sharing and analysis of different data types across several brain disorders, as a means to understand common underlying causes of brain dysfunction and develop novel approaches to treatment. By providing researchers access to aggregated datasets that they otherwise could not obtain independently, Brain-CODE incentivizes data sharing and collaboration and facilitates analyses both within and across disorders and across a wide array of data types, including clinical, neuroimaging and molecular. The Brain-CODE system architecture provides the technical capabilities to support (1) consolidated data management to securely capture, monitor and curate data, (2) privacy and security best-practices, and (3) interoperable and extensible systems that support harmonization, integration, and query across diverse data modalities and linkages to external data sources. Brain-CODE currently supports collaborative research networks focused on various brain conditions, including neurodevelopmental disorders, cerebral palsy, neurodegenerative diseases, epilepsy and mood disorders. These programs are generating large volumes of data that are integrated within Brain-CODE to support scientific inquiry and analytics across multiple brain disorders and modalities. By providing access to very large datasets on patients with different brain disorders and enabling linkages to provincial, national and international databases, Brain-CODE will help to generate new hypotheses about the biological bases of brain disorders, and ultimately promote new discoveries to improve patient care.

Brain-CODE: A Secure Neuroinformatics Platform for Management, Federation, Sharing and Analysis of Multi-Dimensional Neuroscience Data

PubMed Central

Vaccarino, Anthony L.; Dharsee, Moyez; Strother, Stephen; Aldridge, Don; Arnott, Stephen R.; Behan, Brendan; Dafnas, Costas; Dong, Fan; Edgecombe, Kenneth; El-Badrawi, Rachad; El-Emam, Khaled; Gee, Tom; Evans, Susan G.; Javadi, Mojib; Jeanson, Francis; Lefaivre, Shannon; Lutz, Kristen; MacPhee, F. Chris; Mikkelsen, Jordan; Mikkelsen, Tom; Mirotchnick, Nicholas; Schmah, Tanya; Studzinski, Christa M.; Stuss, Donald T.; Theriault, Elizabeth; Evans, Kenneth R.

2018-01-01

Historically, research databases have existed in isolation with no practical avenue for sharing or pooling medical data into high dimensional datasets that can be efficiently compared across databases. To address this challenge, the Ontario Brain Institute’s “Brain-CODE” is a large-scale neuroinformatics platform designed to support the collection, storage, federation, sharing and analysis of different data types across several brain disorders, as a means to understand common underlying causes of brain dysfunction and develop novel approaches to treatment. By providing researchers access to aggregated datasets that they otherwise could not obtain independently, Brain-CODE incentivizes data sharing and collaboration and facilitates analyses both within and across disorders and across a wide array of data types, including clinical, neuroimaging and molecular. The Brain-CODE system architecture provides the technical capabilities to support (1) consolidated data management to securely capture, monitor and curate data, (2) privacy and security best-practices, and (3) interoperable and extensible systems that support harmonization, integration, and query across diverse data modalities and linkages to external data sources. Brain-CODE currently supports collaborative research networks focused on various brain conditions, including neurodevelopmental disorders, cerebral palsy, neurodegenerative diseases, epilepsy and mood disorders. These programs are generating large volumes of data that are integrated within Brain-CODE to support scientific inquiry and analytics across multiple brain disorders and modalities. By providing access to very large datasets on patients with different brain disorders and enabling linkages to provincial, national and international databases, Brain-CODE will help to generate new hypotheses about the biological bases of brain disorders, and ultimately promote new discoveries to improve patient care. PMID:29875648

A healthy heart is not a metronome: an integrative review of the heart's anatomy and heart rate variability.

PubMed

Shaffer, Fred; McCraty, Rollin; Zerr, Christopher L

2014-01-01

Heart rate variability (HRV), the change in the time intervals between adjacent heartbeats, is an emergent property of interdependent regulatory systems that operate on different time scales to adapt to challenges and achieve optimal performance. This article briefly reviews neural regulation of the heart, and its basic anatomy, the cardiac cycle, and the sinoatrial and atrioventricular pacemakers. The cardiovascular regulation center in the medulla integrates sensory information and input from higher brain centers, and afferent cardiovascular system inputs to adjust heart rate and blood pressure via sympathetic and parasympathetic efferent pathways. This article reviews sympathetic and parasympathetic influences on the heart, and examines the interpretation of HRV and the association between reduced HRV, risk of disease and mortality, and the loss of regulatory capacity. This article also discusses the intrinsic cardiac nervous system and the heart-brain connection, through which afferent information can influence activity in the subcortical and frontocortical areas, and motor cortex. It also considers new perspectives on the putative underlying physiological mechanisms and properties of the ultra-low-frequency (ULF), very-low-frequency (VLF), low-frequency (LF), and high-frequency (HF) bands. Additionally, it reviews the most common time and frequency domain measurements as well as standardized data collection protocols. In its final section, this article integrates Porges' polyvagal theory, Thayer and colleagues' neurovisceral integration model, Lehrer et al.'s resonance frequency model, and the Institute of HeartMath's coherence model. The authors conclude that a coherent heart is not a metronome because its rhythms are characterized by both complexity and stability over longer time scales. Future research should expand understanding of how the heart and its intrinsic nervous system influence the brain.

A healthy heart is not a metronome: an integrative review of the heart's anatomy and heart rate variability

PubMed Central

Shaffer, Fred; McCraty, Rollin; Zerr, Christopher L.

2014-01-01

Heart rate variability (HRV), the change in the time intervals between adjacent heartbeats, is an emergent property of interdependent regulatory systems that operate on different time scales to adapt to challenges and achieve optimal performance. This article briefly reviews neural regulation of the heart, and its basic anatomy, the cardiac cycle, and the sinoatrial and atrioventricular pacemakers. The cardiovascular regulation center in the medulla integrates sensory information and input from higher brain centers, and afferent cardiovascular system inputs to adjust heart rate and blood pressure via sympathetic and parasympathetic efferent pathways. This article reviews sympathetic and parasympathetic influences on the heart, and examines the interpretation of HRV and the association between reduced HRV, risk of disease and mortality, and the loss of regulatory capacity. This article also discusses the intrinsic cardiac nervous system and the heart-brain connection, through which afferent information can influence activity in the subcortical and frontocortical areas, and motor cortex. It also considers new perspectives on the putative underlying physiological mechanisms and properties of the ultra-low-frequency (ULF), very-low-frequency (VLF), low-frequency (LF), and high-frequency (HF) bands. Additionally, it reviews the most common time and frequency domain measurements as well as standardized data collection protocols. In its final section, this article integrates Porges' polyvagal theory, Thayer and colleagues' neurovisceral integration model, Lehrer et al.'s resonance frequency model, and the Institute of HeartMath's coherence model. The authors conclude that a coherent heart is not a metronome because its rhythms are characterized by both complexity and stability over longer time scales. Future research should expand understanding of how the heart and its intrinsic nervous system influence the brain. PMID:25324790

Genetic influences on schizophrenia and subcortical brain volumes: large-scale proof-of-concept and roadmap for future studies

PubMed Central

Anttila, Verneri; Hibar, Derrek P; van Hulzen, Kimm J E; Arias-Vasquez, Alejandro; Smoller, Jordan W; Nichols, Thomas E; Neale, Michael C; McIntosh, Andrew M; Lee, Phil; McMahon, Francis J; Meyer-Lindenberg, Andreas; Mattheisen, Manuel; Andreassen, Ole A; Gruber, Oliver; Sachdev, Perminder S; Roiz-Santiañez, Roberto; Saykin, Andrew J; Ehrlich, Stefan; Mather, Karen A; Turner, Jessica A; Schwarz, Emanuel; Thalamuthu, Anbupalam; Shugart, Yin Yao; Ho, Yvonne YW; Martin, Nicholas G; Wright, Margaret J

2016-01-01

Schizophrenia is a devastating psychiatric illness with high heritability. Brain structure and function differ, on average, between schizophrenia cases and healthy individuals. As common genetic associations are emerging for both schizophrenia and brain imaging phenotypes, we can now use genome-wide data to investigate genetic overlap. Here we integrated results from common variant studies of schizophrenia (33,636 cases, 43,008 controls) and volumes of several (mainly subcortical) brain structures (11,840 subjects). We did not find evidence of genetic overlap between schizophrenia risk and subcortical volume measures either at the level of common variant genetic architecture or for single genetic markers. The current study provides proof-of-concept (albeit based on a limited set of structural brain measures), and defines a roadmap for future studies investigating the genetic covariance between structural/functional brain phenotypes and risk for psychiatric disorders. PMID:26854805

Electrophysiological Source Imaging: A Noninvasive Window to Brain Dynamics.

PubMed

He, Bin; Sohrabpour, Abbas; Brown, Emery; Liu, Zhongming

2018-06-04

Brain activity and connectivity are distributed in the three-dimensional space and evolve in time. It is important to image brain dynamics with high spatial and temporal resolution. Electroencephalography (EEG) and magnetoencephalography (MEG) are noninvasive measurements associated with complex neural activations and interactions that encode brain functions. Electrophysiological source imaging estimates the underlying brain electrical sources from EEG and MEG measurements. It offers increasingly improved spatial resolution and intrinsically high temporal resolution for imaging large-scale brain activity and connectivity on a wide range of timescales. Integration of electrophysiological source imaging and functional magnetic resonance imaging could further enhance spatiotemporal resolution and specificity to an extent that is not attainable with either technique alone. We review methodological developments in electrophysiological source imaging over the past three decades and envision its future advancement into a powerful functional neuroimaging technology for basic and clinical neuroscience applications.

Genetic influences on schizophrenia and subcortical brain volumes: large-scale proof of concept.

PubMed

Franke, Barbara; Stein, Jason L; Ripke, Stephan; Anttila, Verneri; Hibar, Derrek P; van Hulzen, Kimm J E; Arias-Vasquez, Alejandro; Smoller, Jordan W; Nichols, Thomas E; Neale, Michael C; McIntosh, Andrew M; Lee, Phil; McMahon, Francis J; Meyer-Lindenberg, Andreas; Mattheisen, Manuel; Andreassen, Ole A; Gruber, Oliver; Sachdev, Perminder S; Roiz-Santiañez, Roberto; Saykin, Andrew J; Ehrlich, Stefan; Mather, Karen A; Turner, Jessica A; Schwarz, Emanuel; Thalamuthu, Anbupalam; Shugart, Yin Yao; Ho, Yvonne Yw; Martin, Nicholas G; Wright, Margaret J; O'Donovan, Michael C; Thompson, Paul M; Neale, Benjamin M; Medland, Sarah E; Sullivan, Patrick F

2016-03-01

Schizophrenia is a devastating psychiatric illness with high heritability. Brain structure and function differ, on average, between people with schizophrenia and healthy individuals. As common genetic associations are emerging for both schizophrenia and brain imaging phenotypes, we can now use genome-wide data to investigate genetic overlap. Here we integrated results from common variant studies of schizophrenia (33,636 cases, 43,008 controls) and volumes of several (mainly subcortical) brain structures (11,840 subjects). We did not find evidence of genetic overlap between schizophrenia risk and subcortical volume measures either at the level of common variant genetic architecture or for single genetic markers. These results provide a proof of concept (albeit based on a limited set of structural brain measures) and define a roadmap for future studies investigating the genetic covariance between structural or functional brain phenotypes and risk for psychiatric disorders.

Loss of corticospinal tract integrity in early MS disease stages

PubMed Central

Neumann, Jens; Kaufmann, Jörn; Heidel, Jan; Stadler, Erhard; Sweeney-Reed, Catherine; Sailer, Michael; Schreiber, Stefanie

2017-01-01

Objective: We investigated corticospinal tract (CST) integrity in the absence of white matter (WM) lesions using diffusion tensor imaging (DTI) in early MS disease stages. Methods: Our study comprised 19 patients with clinically isolated syndrome (CIS), 11 patients with relapsing-remitting MS (RRMS), and 32 age- and sex-matched healthy controls, for whom MRI measures of CST integrity (fractional anisotropy [FA], mean diffusivity [MD]), T1- and T2-based lesion load, and brain volumes were available. The mean (SD) disease duration was 3.5 (2.1) months, and disability score was low (median Expanded Disability Status Scale 1.5) at the time of the study. Results: Patients with CIS and RRMS had significantly lower CST FA and higher CST MD values compared with controls. These findings were present, irrespective of whether WM lesions affected the CST. However, no group differences in the overall gray or WM volume were identified. Conclusions: In early MS disease stages, CST integrity is already affected in the absence of WM lesions or brain atrophy. PMID:28959706

Problem-Based Teaching and Learning in Technology Education.

ERIC Educational Resources Information Center

Putnam, A. R.

Research on how the brain works has resulted in wider-scale adoption of the principles of problem-based learning (PBL) in many areas of education, including technology education. The PBL approach is attractive to curriculum developers because it is based on interdisciplinary learning, results in multiple outcomes, is integrated and…

Injectable, cellular-scale optoelectronics with applications for wireless optogenetics.

PubMed

Kim, Tae-il; McCall, Jordan G; Jung, Yei Hwan; Huang, Xian; Siuda, Edward R; Li, Yuhang; Song, Jizhou; Song, Young Min; Pao, Hsuan An; Kim, Rak-Hwan; Lu, Chaofeng; Lee, Sung Dan; Song, Il-Sun; Shin, Gunchul; Al-Hasani, Ream; Kim, Stanley; Tan, Meng Peun; Huang, Yonggang; Omenetto, Fiorenzo G; Rogers, John A; Bruchas, Michael R

2013-04-12

Successful integration of advanced semiconductor devices with biological systems will accelerate basic scientific discoveries and their translation into clinical technologies. In neuroscience generally, and in optogenetics in particular, the ability to insert light sources, detectors, sensors, and other components into precise locations of the deep brain yields versatile and important capabilities. Here, we introduce an injectable class of cellular-scale optoelectronics that offers such features, with examples of unmatched operational modes in optogenetics, including completely wireless and programmed complex behavioral control over freely moving animals. The ability of these ultrathin, mechanically compliant, biocompatible devices to afford minimally invasive operation in the soft tissues of the mammalian brain foreshadow applications in other organ systems, with potential for broad utility in biomedical science and engineering.

Controllability of structural brain networks

NASA Astrophysics Data System (ADS)

Gu, Shi; Pasqualetti, Fabio; Cieslak, Matthew; Telesford, Qawi K.; Yu, Alfred B.; Kahn, Ari E.; Medaglia, John D.; Vettel, Jean M.; Miller, Michael B.; Grafton, Scott T.; Bassett, Danielle S.

2015-10-01

Cognitive function is driven by dynamic interactions between large-scale neural circuits or networks, enabling behaviour. However, fundamental principles constraining these dynamic network processes have remained elusive. Here we use tools from control and network theories to offer a mechanistic explanation for how the brain moves between cognitive states drawn from the network organization of white matter microstructure. Our results suggest that densely connected areas, particularly in the default mode system, facilitate the movement of the brain to many easily reachable states. Weakly connected areas, particularly in cognitive control systems, facilitate the movement of the brain to difficult-to-reach states. Areas located on the boundary between network communities, particularly in attentional control systems, facilitate the integration or segregation of diverse cognitive systems. Our results suggest that structural network differences between cognitive circuits dictate their distinct roles in controlling trajectories of brain network function.

Hierarchical random cellular neural networks for system-level brain-like signal processing.

PubMed

Kozma, Robert; Puljic, Marko

2013-09-01

Sensory information processing and cognition in brains are modeled using dynamic systems theory. The brain's dynamic state is described by a trajectory evolving in a high-dimensional state space. We introduce a hierarchy of random cellular automata as the mathematical tools to describe the spatio-temporal dynamics of the cortex. The corresponding brain model is called neuropercolation which has distinct advantages compared to traditional models using differential equations, especially in describing spatio-temporal discontinuities in the form of phase transitions. Phase transitions demarcate singularities in brain operations at critical conditions, which are viewed as hallmarks of higher cognition and awareness experience. The introduced Monte-Carlo simulations obtained by parallel computing point to the importance of computer implementations using very large-scale integration (VLSI) and analog platforms. Copyright © 2013 Elsevier Ltd. All rights reserved.

A prospective study to evaluate a residential community reintegration program for patients with chronic acquired brain injury.

PubMed

Geurtsen, Gert J; van Heugten, Caroline M; Martina, Juan D; Rietveld, Antonius C; Meijer, Ron; Geurts, Alexander C

2011-05-01

To examine the effects of a residential community reintegration program on independent living, societal participation, emotional well-being, and quality of life in patients with chronic acquired brain injury and psychosocial problems hampering societal participation. A prospective cohort study with a 3-month waiting list control period and 1-year follow up. A tertiary rehabilitation center for acquired brain injury. Patients (N=70) with acquired brain injury (46 men; mean age, 25.1y; mean time post-onset, 5.2y; at follow up n=67). A structured residential treatment program was offered directed at improving independence in domestic life, work, leisure time, and social interactions. Community Integration Questionnaire (CIQ), Employability Rating Scale, living situation, school, work situation, work hours, Center for Epidemiological Studies Depression Scale, EuroQOL quality of life scale (2 scales), World Health Organization Quality of Life Scale Abbreviated (WHOQOL-BREF; 5 scales), and the Global Assessment of Functioning (GAF) scale. There was an overall significant time effect for all outcome measures (multiple analysis of variance T(2)=26.16; F(36,557) 134.9; P=.000). There was no spontaneous recovery during the waiting-list period. The effect sizes for the CIQ, Employability Rating Scale, work hours, and GAF were large (partial η(2)=0.25, 0.35, 0.22, and 0.72, respectively). The effect sizes were moderate for 7 of the 8 emotional well-being and quality of life (sub)scales (partial η(2)=0.11-0.20). The WHOQOL-BREF environment subscale showed a small effect size (partial η(2)=0.05). Living independently rose from 25.4% before treatment to 72.4% after treatment and was still 65.7% at follow up. This study shows that a residential community reintegration program leads to significant and relevant improvements of independent living, societal participation, emotional well-being, and quality of life in patients with chronic acquired brain injury and psychosocial problems hampering societal participation. Copyright © 2011 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Influence of anesthesia on cerebral blood flow, cerebral metabolic rate, and brain functional connectivity.

PubMed

Bonhomme, Vincent; Boveroux, Pierre; Hans, Pol; Brichant, Jean François; Vanhaudenhuyse, Audrey; Boly, Melanie; Laureys, Steven

2011-10-01

To describe recent studies exploring brain function under the influence of hypnotic anesthetic agents, and their implications on the understanding of consciousness physiology and anesthesia-induced alteration of consciousness. Cerebral cortex is the primary target of the hypnotic effect of anesthetic agents, and higher-order association areas are more sensitive to this effect than lower-order processing regions. Increasing concentration of anesthetic agents progressively attenuates connectivity in the consciousness networks, while connectivity in lower-order sensory and motor networks is preserved. Alteration of thalamic sub-cortical regulation could compromise the cortical integration of information despite preserved thalamic activation by external stimuli. At concentrations producing unresponsiveness, the activity of consciousness networks becomes anticorrelated with thalamic activity, while connectivity in lower-order sensory networks persists, although with cross-modal interaction alterations. Accumulating evidence suggests that hypnotic anesthetic agents disrupt large-scale cerebral connectivity. This would result in an inability of the brain to generate and integrate information, while external sensory information is still processed at a lower order of complexity.

Toward an integrative science of the developing human mind and brain: Focus on the developing cortex☆

PubMed Central

Jernigan, Terry L.; Brown, Timothy T.; Bartsch, Hauke; Dale, Anders M.

2015-01-01

Based on the Huttenlocher lecture, this article describes the need for a more integrative scientific paradigm for addressing important questions raised by key observations made over 2 decades ago. Among these are the early descriptions by Huttenlocher of variability in synaptic density in cortex of postmortem brains of children of different ages and the almost simultaneous reports of cortical volume reductions on MR imaging in children and adolescents. In spite of much progress in developmental neurobiology, developmental cognitive neuroscience, and behavioral and imaging genetics, we still do not know how these early observations relate to each other. It is argued that large scale, collaborative research programs are needed to establish the associations between behavioral differences among children and imaging biomarkers, and to link the latter to cellular changes in the developing brain. Examples of progress and challenges remaining are illustrated with data from the Pediatric Imaging, Neurocognition, and Genetics Project (PING). PMID:26347228

Artificial brains. A million spiking-neuron integrated circuit with a scalable communication network and interface.

PubMed

Merolla, Paul A; Arthur, John V; Alvarez-Icaza, Rodrigo; Cassidy, Andrew S; Sawada, Jun; Akopyan, Filipp; Jackson, Bryan L; Imam, Nabil; Guo, Chen; Nakamura, Yutaka; Brezzo, Bernard; Vo, Ivan; Esser, Steven K; Appuswamy, Rathinakumar; Taba, Brian; Amir, Arnon; Flickner, Myron D; Risk, William P; Manohar, Rajit; Modha, Dharmendra S

2014-08-08

Inspired by the brain's structure, we have developed an efficient, scalable, and flexible non-von Neumann architecture that leverages contemporary silicon technology. To demonstrate, we built a 5.4-billion-transistor chip with 4096 neurosynaptic cores interconnected via an intrachip network that integrates 1 million programmable spiking neurons and 256 million configurable synapses. Chips can be tiled in two dimensions via an interchip communication interface, seamlessly scaling the architecture to a cortexlike sheet of arbitrary size. The architecture is well suited to many applications that use complex neural networks in real time, for example, multiobject detection and classification. With 400-pixel-by-240-pixel video input at 30 frames per second, the chip consumes 63 milliwatts. Copyright © 2014, American Association for the Advancement of Science.

Interactionist Neuroscience.

PubMed

Badre, David; Frank, Michael J; Moore, Christopher I

2015-12-02

We argue that bidirectional interaction between animal and human studies is essential for understanding the human brain. The revolution in meso-scale study of circuits in non-human species provides a historical opportunity. However, to fully realize its potential requires integration with human neuroscience. We describe three strategies for successful interactionist neuroscience. Copyright © 2015 Elsevier Inc. All rights reserved.

Quantifying white matter structural integrity with high-definition fiber tracking in traumatic brain injury.

PubMed

Presson, Nora; Krishnaswamy, Deepa; Wagener, Lauren; Bird, William; Jarbo, Kevin; Pathak, Sudhir; Puccio, Ava M; Borasso, Allison; Benso, Steven; Okonkwo, David O; Schneider, Walter

2015-03-01

There is an urgent, unmet demand for definitive biological diagnosis of traumatic brain injury (TBI) to pinpoint the location and extent of damage. We have developed High-Definition Fiber Tracking, a 3 T magnetic resonance imaging-based diffusion spectrum imaging and tractography analysis protocol, to quantify axonal injury in military and civilian TBI patients. A novel analytical methodology quantified white matter integrity in patients with TBI and healthy controls. Forty-one subjects (23 TBI, 18 controls) were scanned with the High-Definition Fiber Tracking diffusion spectrum imaging protocol. After reconstruction, segmentation was used to isolate bilateral hemisphere homologues of eight major tracts. Integrity of segmented tracts was estimated by calculating homologue correlation and tract coverage. Both groups showed high correlations for all tracts. TBI patients showed reduced homologue correlation and tract spread and increased outlier count (correlations>2.32 SD below control mean). On average, 6.5% of tracts in the TBI group were outliers with substantial variability among patients. Number and summed deviation of outlying tracts correlated with initial Glasgow Coma Scale score and 6-month Glasgow Outcome Scale-Extended score. The correlation metric used here can detect heterogeneous damage affecting a low proportion of tracts, presenting a potential mechanism for advancing TBI diagnosis. Reprint & Copyright © 2015 Association of Military Surgeons of the U.S.

ELUCIDATING BRAIN CONNECTIVITY NETWORKS IN MAJOR DEPRESSIVE DISORDER USING CLASSIFICATION-BASED SCORING.

PubMed

Sacchet, Matthew D; Prasad, Gautam; Foland-Ross, Lara C; Thompson, Paul M; Gotlib, Ian H

2014-04-01

Graph theory is increasingly used in the field of neuroscience to understand the large-scale network structure of the human brain. There is also considerable interest in applying machine learning techniques in clinical settings, for example, to make diagnoses or predict treatment outcomes. Here we used support-vector machines (SVMs), in conjunction with whole-brain tractography, to identify graph metrics that best differentiate individuals with Major Depressive Disorder (MDD) from nondepressed controls. To do this, we applied a novel feature-scoring procedure that incorporates iterative classifier performance to assess feature robustness. We found that small-worldness , a measure of the balance between global integration and local specialization, most reliably differentiated MDD from nondepressed individuals. Post-hoc regional analyses suggested that heightened connectivity of the subcallosal cingulate gyrus (SCG) in MDDs contributes to these differences. The current study provides a novel way to assess the robustness of classification features and reveals anomalies in large-scale neural networks in MDD.

3D pre- versus post-season comparisons of surface and relative pose of the corpus callosum in contact sport athletes

NASA Astrophysics Data System (ADS)

Lao, Yi; Gajawelli, Niharika; Haas, Lauren; Wilkins, Bryce; Hwang, Darryl; Tsao, Sinchai; Wang, Yalin; Law, Meng; Leporé, Natasha

2014-03-01

Mild traumatic brain injury (MTBI) or concussive injury affects 1.7 million Americans annually, of which 300,000 are due to recreational activities and contact sports, such as football, rugby, and boxing[1]. Finding the neuroanatomical correlates of brain TBI non-invasively and precisely is crucial for diagnosis and prognosis. Several studies have shown the in influence of traumatic brain injury (TBI) on the integrity of brain WM [2-4]. The vast majority of these works focus on athletes with diagnosed concussions. However, in contact sports, athletes are subjected to repeated hits to the head throughout the season, and we hypothesize that these have an influence on white matter integrity. In particular, the corpus callosum (CC), as a small structure connecting the brain hemispheres, may be particularly affected by torques generated by collisions, even in the absence of full blown concussions. Here, we use a combined surface-based morphometry and relative pose analyses, applying on the point distribution model (PDM) of the CC, to investigate TBI related brain structural changes between 9 pre-season and 9 post-season contact sport athlete MRIs. All the data are fed into surface based morphometry analysis and relative pose analysis. The former looks at surface area and thickness changes between the two groups, while the latter consists of detecting the relative translation, rotation and scale between them.

An Adaptive Complex Network Model for Brain Functional Networks

PubMed Central

Gomez Portillo, Ignacio J.; Gleiser, Pablo M.

2009-01-01

Brain functional networks are graph representations of activity in the brain, where the vertices represent anatomical regions and the edges their functional connectivity. These networks present a robust small world topological structure, characterized by highly integrated modules connected sparsely by long range links. Recent studies showed that other topological properties such as the degree distribution and the presence (or absence) of a hierarchical structure are not robust, and show different intriguing behaviors. In order to understand the basic ingredients necessary for the emergence of these complex network structures we present an adaptive complex network model for human brain functional networks. The microscopic units of the model are dynamical nodes that represent active regions of the brain, whose interaction gives rise to complex network structures. The links between the nodes are chosen following an adaptive algorithm that establishes connections between dynamical elements with similar internal states. We show that the model is able to describe topological characteristics of human brain networks obtained from functional magnetic resonance imaging studies. In particular, when the dynamical rules of the model allow for integrated processing over the entire network scale-free non-hierarchical networks with well defined communities emerge. On the other hand, when the dynamical rules restrict the information to a local neighborhood, communities cluster together into larger ones, giving rise to a hierarchical structure, with a truncated power law degree distribution. PMID:19738902

Altered Integration of Structural Covariance Networks in Young Children With Type 1 Diabetes.

PubMed

Hosseini, S M Hadi; Mazaika, Paul; Mauras, Nelly; Buckingham, Bruce; Weinzimer, Stuart A; Tsalikian, Eva; White, Neil H; Reiss, Allan L

2016-11-01

Type 1 diabetes mellitus (T1D), one of the most frequent chronic diseases in children, is associated with glucose dysregulation that contributes to an increased risk for neurocognitive deficits. While there is a bulk of evidence regarding neurocognitive deficits in adults with T1D, little is known about how early-onset T1D affects neural networks in young children. Recent data demonstrated widespread alterations in regional gray matter and white matter associated with T1D in young children. These widespread neuroanatomical changes might impact the organization of large-scale brain networks. In the present study, we applied graph-theoretical analysis to test whether the organization of structural covariance networks in the brain for a cohort of young children with T1D (N = 141) is altered compared to healthy controls (HC; N = 69). While the networks in both groups followed a small world organization-an architecture that is simultaneously highly segregated and integrated-the T1D network showed significantly longer path length compared with HC, suggesting reduced global integration of brain networks in young children with T1D. In addition, network robustness analysis revealed that the T1D network model showed more vulnerability to neural insult compared with HC. These results suggest that early-onset T1D negatively impacts the global organization of structural covariance networks and influences the trajectory of brain development in childhood. This is the first study to examine structural covariance networks in young children with T1D. Improving glycemic control for young children with T1D might help prevent alterations in brain networks in this population. Hum Brain Mapp 37:4034-4046, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Brain Gym To Increase Academic Performance Of Children Aged 10-12 Years Old ( Experimental Study in Tembalang Elementary School and Pedalangan Elementary School Semarang)

NASA Astrophysics Data System (ADS)

Marpaung, M. G.; Sareharto, T. P.; Purwanti, A.; Hermawati, D.

2017-02-01

Academic performance becomes an important determinant of individual quality. it is determined by the function of affective, cognitive, psychomotor, and intelligence. Brain gym can improve learning processes and integrate all areas that related to the learning process. To prove the effect of brain gym towards academic performance of children aged 10-12 years. This study was a quasy experiment study with one group pre and post test design. Samples (n=18 male=7 and female=11) were taken from five and six grader and conducted in Tembalang and Pedalangan Elementary School, Semarang. Pretest were administered, followed by brain gym, and post test administered in the end of study. The measurement of Intelligence Quotient pre and post test using Culture Fair Intelligence Test Scale 2. Among the 18 subjects (male=7 and female=11) the average of academic performance and IQ score after brain gym showed improvement. The Improvement of IQ score with Culture Fair Test Scale 2 was analyzed by Dependent T test showed significant results (p=0,000). The improvement of Bahasa score was analyzed by Wilcoxon test showed significant results (p=0,001), an unsignificant result were shown in Mathematics p=0,079 and natural sciences p=0,306. Brain gym can increase academic performance of children aged 10-12 years old.

Reduced hemispheric asymmetry of brain anatomical networks in attention deficit hyperactivity disorder.

PubMed

Li, Dandan; Li, Ting; Niu, Yan; Xiang, Jie; Cao, Rui; Liu, Bo; Zhang, Hui; Wang, Bin

2018-05-11

Despite many studies reporting a variety of alterations in brain networks in patients with attention deficit hyperactivity disorder (ADHD), alterations in hemispheric anatomical networks are still unclear. In this study, we investigated topology alterations in hemispheric white matter in patients with ADHD and the relationship between these alterations and clinical features of the illness. Weighted hemispheric brain anatomical networks were first constructed for each of 40 right-handed patients with ADHD and 53 matched normal controls. Then, graph theoretical approaches were utilized to compute hemispheric topological properties. The small-world property was preserved in the hemispheric network. Furthermore, a significant group-by-hemisphere interaction was revealed in global efficiency, local efficiency and characteristic path length, attributed to the significantly reduced hemispheric asymmetry of global and local integration in patients with ADHD compared with normal controls. Specifically, reduced asymmetric regional efficiency was found in three regions. Finally, we found that the abnormal asymmetry of hemispheric brain anatomical network topology and regional efficiency were both associated with clinical features (the Adult ADHD Self-Report Scale and Wechsler Adult Intelligence Scale) in patients. Our findings provide new insights into the lateralized nature of hemispheric dysconnectivity and highlight the potential for using brain network measures of hemispheric asymmetry as neural biomarkers for ADHD and its clinical features.

A pairwise maximum entropy model accurately describes resting-state human brain networks

PubMed Central

Watanabe, Takamitsu; Hirose, Satoshi; Wada, Hiroyuki; Imai, Yoshio; Machida, Toru; Shirouzu, Ichiro; Konishi, Seiki; Miyashita, Yasushi; Masuda, Naoki

2013-01-01

The resting-state human brain networks underlie fundamental cognitive functions and consist of complex interactions among brain regions. However, the level of complexity of the resting-state networks has not been quantified, which has prevented comprehensive descriptions of the brain activity as an integrative system. Here, we address this issue by demonstrating that a pairwise maximum entropy model, which takes into account region-specific activity rates and pairwise interactions, can be robustly and accurately fitted to resting-state human brain activities obtained by functional magnetic resonance imaging. Furthermore, to validate the approximation of the resting-state networks by the pairwise maximum entropy model, we show that the functional interactions estimated by the pairwise maximum entropy model reflect anatomical connexions more accurately than the conventional functional connectivity method. These findings indicate that a relatively simple statistical model not only captures the structure of the resting-state networks but also provides a possible method to derive physiological information about various large-scale brain networks. PMID:23340410

Dynamic reconfiguration of frontal brain networks during executive cognition in humans

PubMed Central

Braun, Urs; Schäfer, Axel; Walter, Henrik; Erk, Susanne; Romanczuk-Seiferth, Nina; Haddad, Leila; Schweiger, Janina I.; Grimm, Oliver; Heinz, Andreas; Tost, Heike; Meyer-Lindenberg, Andreas; Bassett, Danielle S.

2015-01-01

The brain is an inherently dynamic system, and executive cognition requires dynamically reconfiguring, highly evolving networks of brain regions that interact in complex and transient communication patterns. However, a precise characterization of these reconfiguration processes during cognitive function in humans remains elusive. Here, we use a series of techniques developed in the field of “dynamic network neuroscience” to investigate the dynamics of functional brain networks in 344 healthy subjects during a working-memory challenge (the “n-back” task). In contrast to a control condition, in which dynamic changes in cortical networks were spread evenly across systems, the effortful working-memory condition was characterized by a reconfiguration of frontoparietal and frontotemporal networks. This reconfiguration, which characterizes “network flexibility,” employs transient and heterogeneous connectivity between frontal systems, which we refer to as “integration.” Frontal integration predicted neuropsychological measures requiring working memory and executive cognition, suggesting that dynamic network reconfiguration between frontal systems supports those functions. Our results characterize dynamic reconfiguration of large-scale distributed neural circuits during executive cognition in humans and have implications for understanding impaired cognitive function in disorders affecting connectivity, such as schizophrenia or dementia. PMID:26324898

Space, self, and the theater of consciousness.

PubMed

Trehub, Arnold

2007-06-01

Over a decade ago, I introduced a large-scale theory of the cognitive brain which explained for the first time how the human brain is able to create internal models of its intimate world and invent models of a wider universe. An essential part of the theoretical model is an organization of neuronal mechanisms which I have named the Retinoid Model [Trehub, A. (1977). Neuronal models for cognitive processes: Networks for learning, perception and imagination. Journal of Theoretical Biology, 65, 141-169; Trehub, A. (1991). The Cognitive Brain: MIT Press]. This hypothesized brain system has structural and dynamic properties enabling it to register and appropriately integrate disparate foveal stimuli into a perspectival, egocentric representation of an extended 3D world scene including a neuronally tokened locus of the self which, in this theory, is the neuronal origin of retinoid space. As an integral part of the larger neuro-cognitive model, the retinoid system is able to perform many other useful perceptual and higher cognitive functions. In this paper, I draw on the hypothesized properties of this system to argue that neuronal activity within the retinoid structure constitutes the phenomenal content of consciousness and the unique sense of self that each of us experiences.

Integration of miRNA and Protein Profiling Reveals Coordinated Neuroadaptations in the Alcohol-Dependent Mouse Brain

PubMed Central

Gorini, Giorgio; Nunez, Yury O.; Mayfield, R. Dayne

2013-01-01

The molecular mechanisms underlying alcohol dependence involve different neurochemical systems and are brain region-dependent. Chronic Intermittent Ethanol (CIE) procedure, combined with a Two-Bottle Choice voluntary drinking paradigm, represents one of the best available animal models for alcohol dependence and relapse drinking. MicroRNAs, master regulators of the cellular transcriptome and proteome, can regulate their targets in a cooperative, combinatorial fashion, ensuring fine tuning and control over a large number of cellular functions. We analyzed cortex and midbrain microRNA expression levels using an integrative approach to combine and relate data to previous protein profiling from the same CIE-subjected samples, and examined the significance of the data in terms of relative contribution to alcohol consumption and dependence. MicroRNA levels were significantly altered in CIE-exposed dependent mice compared with their non-dependent controls. More importantly, our integrative analysis identified modules of coexpressed microRNAs that were highly correlated with CIE effects and predicted target genes encoding differentially expressed proteins. Coexpressed CIE-relevant proteins, in turn, were often negatively correlated with specific microRNA modules. Our results provide evidence that microRNA-orchestrated translational imbalances are driving the behavioral transition from alcohol consumption to dependence. This study represents the first attempt to combine ex vivo microRNA and protein expression on a global scale from the same mammalian brain samples. The integrative systems approach used here will improve our understanding of brain adaptive changes in response to drug abuse and suggests the potential therapeutic use of microRNAs as tools to prevent or compensate multiple neuroadaptations underlying addictive behavior. PMID:24358208

Allometric Analysis Detects Brain Size-Independent Effects of Sex and Sex Chromosome Complement on Human Cerebellar Organization

PubMed Central

Mankiw, Catherine; Park, Min Tae M.; Reardon, P.K.; Fish, Ari M.; Clasen, Liv S.; Greenstein, Deanna; Blumenthal, Jonathan D.; Lerch, Jason P.; Chakravarty, M. Mallar

2017-01-01

The cerebellum is a large hindbrain structure that is increasingly recognized for its contribution to diverse domains of cognitive and affective processing in human health and disease. Although several of these domains are sex biased, our fundamental understanding of cerebellar sex differences—including their spatial distribution, potential biological determinants, and independence from brain volume variation—lags far behind that for the cerebrum. Here, we harness automated neuroimaging methods for cerebellar morphometrics in 417 individuals to (1) localize normative male–female differences in raw cerebellar volume, (2) compare these to sex chromosome effects estimated across five rare sex (X/Y) chromosome aneuploidy (SCA) syndromes, and (3) clarify brain size-independent effects of sex and SCA on cerebellar anatomy using a generalizable allometric approach that considers scaling relationships between regional cerebellar volume and brain volume in health. The integration of these approaches shows that (1) sex and SCA effects on raw cerebellar volume are large and distributed, but regionally heterogeneous, (2) human cerebellar volume scales with brain volume in a highly nonlinear and regionally heterogeneous fashion that departs from documented patterns of cerebellar scaling in phylogeny, and (3) cerebellar organization is modified in a brain size-independent manner by sex (relative expansion of total cerebellum, flocculus, and Crus II-lobule VIIIB volumes in males) and SCA (contraction of total cerebellar, lobule IV, and Crus I volumes with additional X- or Y-chromosomes; X-specific contraction of Crus II-lobule VIIIB). Our methods and results clarify the shifts in human cerebellar organization that accompany interwoven variations in sex, sex chromosome complement, and brain size. SIGNIFICANCE STATEMENT Cerebellar systems are implicated in diverse domains of sex-biased behavior and pathology, but we lack a basic understanding of how sex differences in the human cerebellum are distributed and determined. We leverage a rare neuroimaging dataset to deconvolve the interwoven effects of sex, sex chromosome complement, and brain size on human cerebellar organization. We reveal topographically variegated scaling relationships between regional cerebellar volume and brain size in humans, which (1) are distinct from those observed in phylogeny, (2) invalidate a traditional neuroimaging method for brain volume correction, and (3) allow more valid and accurate resolution of which cerebellar subcomponents are sensitive to sex and sex chromosome complement. These findings advance understanding of cerebellar organization in health and sex chromosome aneuploidy. PMID:28314818

Large scale digital atlases in neuroscience

NASA Astrophysics Data System (ADS)

Hawrylycz, M.; Feng, D.; Lau, C.; Kuan, C.; Miller, J.; Dang, C.; Ng, L.

2014-03-01

Imaging in neuroscience has revolutionized our current understanding of brain structure, architecture and increasingly its function. Many characteristics of morphology, cell type, and neuronal circuitry have been elucidated through methods of neuroimaging. Combining this data in a meaningful, standardized, and accessible manner is the scope and goal of the digital brain atlas. Digital brain atlases are used today in neuroscience to characterize the spatial organization of neuronal structures, for planning and guidance during neurosurgery, and as a reference for interpreting other data modalities such as gene expression and connectivity data. The field of digital atlases is extensive and in addition to atlases of the human includes high quality brain atlases of the mouse, rat, rhesus macaque, and other model organisms. Using techniques based on histology, structural and functional magnetic resonance imaging as well as gene expression data, modern digital atlases use probabilistic and multimodal techniques, as well as sophisticated visualization software to form an integrated product. Toward this goal, brain atlases form a common coordinate framework for summarizing, accessing, and organizing this knowledge and will undoubtedly remain a key technology in neuroscience in the future. Since the development of its flagship project of a genome wide image-based atlas of the mouse brain, the Allen Institute for Brain Science has used imaging as a primary data modality for many of its large scale atlas projects. We present an overview of Allen Institute digital atlases in neuroscience, with a focus on the challenges and opportunities for image processing and computation.

Salience network integrity predicts default mode network function after traumatic brain injury

PubMed Central

Bonnelle, Valerie; Ham, Timothy E.; Leech, Robert; Kinnunen, Kirsi M.; Mehta, Mitul A.; Greenwood, Richard J.; Sharp, David J.

2012-01-01

Efficient behavior involves the coordinated activity of large-scale brain networks, but the way in which these networks interact is uncertain. One theory is that the salience network (SN)—which includes the anterior cingulate cortex, presupplementary motor area, and anterior insulae—regulates dynamic changes in other networks. If this is the case, then damage to the structural connectivity of the SN should disrupt the regulation of associated networks. To investigate this hypothesis, we studied a group of 57 patients with cognitive impairments following traumatic brain injury (TBI) and 25 control subjects using the stop-signal task. The pattern of brain activity associated with stop-signal task performance was studied by using functional MRI, and the structural integrity of network connections was quantified by using diffusion tensor imaging. Efficient inhibitory control was associated with rapid deactivation within parts of the default mode network (DMN), including the precuneus and posterior cingulate cortex. TBI patients showed a failure of DMN deactivation, which was associated with an impairment of inhibitory control. TBI frequently results in traumatic axonal injury, which can disconnect brain networks by damaging white matter tracts. The abnormality of DMN function was specifically predicted by the amount of white matter damage in the SN tract connecting the right anterior insulae to the presupplementary motor area and dorsal anterior cingulate cortex. The results provide evidence that structural integrity of the SN is necessary for the efficient regulation of activity in the DMN, and that a failure of this regulation leads to inefficient cognitive control. PMID:22393019

Disrupted Topological Patterns of Large-Scale Network in Conduct Disorder

PubMed Central

Jiang, Yali; Liu, Weixiang; Ming, Qingsen; Gao, Yidian; Ma, Ren; Zhang, Xiaocui; Situ, Weijun; Wang, Xiang; Yao, Shuqiao; Huang, Bingsheng

2016-01-01

Regional abnormalities in brain structure and function, as well as disrupted connectivity, have been found repeatedly in adolescents with conduct disorder (CD). Yet, the large-scale brain topology associated with CD is not well characterized, and little is known about the systematic neural mechanisms of CD. We employed graphic theory to investigate systematically the structural connectivity derived from cortical thickness correlation in a group of patients with CD (N = 43) and healthy controls (HCs, N = 73). Nonparametric permutation tests were applied for between-group comparisons of graphical metrics. Compared with HCs, network measures including global/local efficiency and modularity all pointed to hypo-functioning in CD, despite of preserved small-world organization in both groups. The hubs distribution is only partially overlapped with each other. These results indicate that CD is accompanied by both impaired integration and segregation patterns of brain networks, and the distribution of highly connected neural network ‘hubs’ is also distinct between groups. Such misconfiguration extends our understanding regarding how structural neural network disruptions may underlie behavioral disturbances in adolescents with CD, and potentially, implicates an aberrant cytoarchitectonic profiles in the brain of CD patients. PMID:27841320

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.

Breakdown of long-range temporal correlations in brain oscillations during general anesthesia.

PubMed

Krzemiński, Dominik; Kamiński, Maciej; Marchewka, Artur; Bola, Michał

2017-10-01

Consciousness has been hypothesized to emerge from complex neuronal dynamics, which prevails when brain operates in a critical state. Evidence supporting this hypothesis comes mainly from studies investigating neuronal activity on a short time-scale of seconds. However, a key aspect of criticality is presence of scale-free temporal dependencies occurring across a wide range of time-scales. Indeed, robust long-range temporal correlations (LRTCs) are found in neuronal oscillations during conscious states, but it is not known how LRTCs are affected by loss of consciousness. To further test a relation between critical dynamics and consciousness, we investigated LRTCs in electrocorticography signals recorded from four macaque monkeys during resting wakefulness and general anesthesia induced by various anesthetics (ketamine, medetomidine, or propofol). Detrended Fluctuation Analysis was used to estimate LRTCs in amplitude fluctuations (envelopes) of band-pass filtered signals. We demonstrate two main findings. First, during conscious states all lateral cortical regions are characterized by significant LRTCs of alpha-band activity (7-14 Hz). LRTCs are stronger in the eyes-open than eyes-closed state, but in both states they form a spatial gradient, with anterior brain regions exhibiting stronger LRTCs than posterior regions. Second, we observed a substantial decrease of LRTCs during loss of consciousness, the magnitude of which was associated with the baseline (i.e. pre-anesthesia) state of the brain. Specifically, brain regions characterized by strongest LRTCs during a wakeful baseline exhibited greatest decreases during anesthesia (i.e. "the rich got poorer"), which consequently disturbed the posterior-anterior gradient. Therefore, our results suggest that general anesthesia affects mainly brain areas characterized by strongest LRTCs during wakefulness, which might account for lack of capacities for extensive temporal integration during loss of consciousness. Copyright © 2017 Elsevier Inc. All rights reserved.

An examination of the psychometric properties of the community integration questionnaire (CIQ) in spinal cord injury.

PubMed

Kratz, Anna L; Chadd, Edmund; Jensen, Mark P; Kehn, Matthew; Kroll, Thilo

2015-07-01

To examine the psychometric properties of the Community Integration Questionnaire (CIQ) in large samples of individuals with spinal cord injury (SCI). Longitudinal 12-month survey study. Nation-wide, community dwelling. Adults with SCI: 627 at Time 1, 494 at Time 2. Not applicable. The CIQ is a 15-item measure developed to measure three domains of community integration in individuals with traumatic brain injury: home integration, social integration, and productive activity. SCI consumer input suggested the need for two additional items assessing socializing at home and internet/email activity. Exploratory factor analyses at Time 1 indicated three factors. Time 2 confirmatory factor analysis did not show a good fit of the 3-factor model. CIQ scores were normally distributed and only the Productive subscale demonstrated problems with high (25%) ceiling effects. Internal reliability was acceptable for the Total and Home scales, but low for the Social and Productive activity scales. Validity of the CIQ is suggested by significant differences by sex, age, and wheelchair use. The factor structure of the CIQ was not stable over time. The CIQ may be most useful for assessing home integration, as this is the subscale with the most scale stability and internal reliability. The CIQ may be improved for use in SCI by including items that reflect higher levels of productive functioning, integration across the life span, and home- and internet-based social functioning.

Imaging functional and structural brain connectomics in attention-deficit/hyperactivity disorder.

PubMed

Cao, Miao; Shu, Ni; Cao, Qingjiu; Wang, Yufeng; He, Yong

2014-12-01

Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopment disorders in childhood. Clinically, the core symptoms of this disorder include inattention, hyperactivity, and impulsivity. Previous studies have documented that these behavior deficits in ADHD children are associated with not only regional brain abnormalities but also changes in functional and structural connectivity among regions. In the past several years, our understanding of how ADHD affects the brain's connectivity has been greatly advanced by mapping topological alterations of large-scale brain networks (i.e., connectomes) using noninvasive neurophysiological and neuroimaging techniques (e.g., electroencephalograph, functional MRI, and diffusion MRI) in combination with graph theoretical approaches. In this review, we summarize the recent progresses of functional and structural brain connectomics in ADHD, focusing on graphic analysis of large-scale brain systems. Convergent evidence suggests that children with ADHD had abnormal small-world properties in both functional and structural brain networks characterized by higher local clustering and lower global integrity, suggesting a disorder-related shift of network topology toward regular configurations. Moreover, ADHD children showed the redistribution of regional nodes and connectivity involving the default-mode, attention, and sensorimotor systems. Importantly, these ADHD-associated alterations significantly correlated with behavior disturbances (e.g., inattention and hyperactivity/impulsivity symptoms) and exhibited differential patterns between clinical subtypes. Together, these connectome-based studies highlight brain network dysfunction in ADHD, thus opening up a new window into our understanding of the pathophysiological mechanisms of this disorder. These works might also have important implications on the development of imaging-based biomarkers for clinical diagnosis and treatment evaluation in ADHD.

Identifying factors associated with perceived success in the transition from hospital to home after brain injury.

PubMed

Nalder, Emily; Fleming, Jennifer; Foster, Michele; Cornwell, Petrea; Shields, Cassandra; Khan, Asad

2012-01-01

: To identify the factors associated with perceived success of the transition from hospital to home after traumatic brain injury (TBI). : Prospective longitudinal cohort design with data collection at discharge and 1, 3, and 6 months postdischarge. : A total of 127 individuals with TBI discharged to the community and 83 significant others. : An analog scale (0-100) of perceived success of the transition from hospital to home rated by individuals and significant others; Sentinel Events Questionnaire; EuroQol Group Quality-of-Life measure visual analog scale; Sydney Psychosocial Reintegration Scale; Mayo-Portland Adaptability Inventory-4; short form of the Depression, Anxiety, Stress Scales; Craig Hospital Inventory of Environmental Factors; and Caregiver Strain Index. : Greater perceived success of transition for individuals with a TBI was associated with higher levels of health-related quality of life, level of community integration, and more severe injury. Among survivors, sentinel events such as returning to work and independent community access and changing living situation were associated with greater perceived success; financial strain and difficulty accessing therapy services were associated with less success. Among significant others, lower ratings of transition success were associated with higher significant other stress levels as well as lower levels of community integration and changes in the living situation of the individual with TBI. : A combination of sentinel events and personal and environmental factors influences the perceptions of individuals and their families regarding the success of the transition from hospital to home.

Plasticity of brain wave network interactions and evolution across physiologic states

PubMed Central

Liu, Kang K. L.; Bartsch, Ronny P.; Lin, Aijing; Mantegna, Rosario N.; Ivanov, Plamen Ch.

2015-01-01

Neural plasticity transcends a range of spatio-temporal scales and serves as the basis of various brain activities and physiologic functions. At the microscopic level, it enables the emergence of brain waves with complex temporal dynamics. At the macroscopic level, presence and dominance of specific brain waves is associated with important brain functions. The role of neural plasticity at different levels in generating distinct brain rhythms and how brain rhythms communicate with each other across brain areas to generate physiologic states and functions remains not understood. Here we perform an empirical exploration of neural plasticity at the level of brain wave network interactions representing dynamical communications within and between different brain areas in the frequency domain. We introduce the concept of time delay stability (TDS) to quantify coordinated bursts in the activity of brain waves, and we employ a system-wide Network Physiology integrative approach to probe the network of coordinated brain wave activations and its evolution across physiologic states. We find an association between network structure and physiologic states. We uncover a hierarchical reorganization in the brain wave networks in response to changes in physiologic state, indicating new aspects of neural plasticity at the integrated level. Globally, we find that the entire brain network undergoes a pronounced transition from low connectivity in Deep Sleep and REM to high connectivity in Light Sleep and Wake. In contrast, we find that locally, different brain areas exhibit different network dynamics of brain wave interactions to achieve differentiation in function during different sleep stages. Moreover, our analyses indicate that plasticity also emerges in frequency-specific networks, which represent interactions across brain locations mediated through a specific frequency band. Comparing frequency-specific networks within the same physiologic state we find very different degree of network connectivity and link strength, while at the same time each frequency-specific network is characterized by a different signature pattern of sleep-stage stratification, reflecting a remarkable flexibility in response to change in physiologic state. These new aspects of neural plasticity demonstrate that in addition to dominant brain waves, the network of brain wave interactions is a previously unrecognized hallmark of physiologic state and function. PMID:26578891

3D Reconstructed Cyto-, Muscarinic M2 Receptor, and Fiber Architecture of the Rat Brain Registered to the Waxholm Space Atlas

PubMed Central

Schubert, Nicole; Axer, Markus; Schober, Martin; Huynh, Anh-Minh; Huysegoms, Marcel; Palomero-Gallagher, Nicola; Bjaalie, Jan G.; Leergaard, Trygve B.; Kirlangic, Mehmet E.; Amunts, Katrin; Zilles, Karl

2016-01-01

High-resolution multiscale and multimodal 3D models of the brain are essential tools to understand its complex structural and functional organization. Neuroimaging techniques addressing different aspects of brain organization should be integrated in a reference space to enable topographically correct alignment and subsequent analysis of the various datasets and their modalities. The Waxholm Space (http://software.incf.org/software/waxholm-space) is a publicly available 3D coordinate-based standard reference space for the mapping and registration of neuroanatomical data in rodent brains. This paper provides a newly developed pipeline combining imaging and reconstruction steps with a novel registration strategy to integrate new neuroimaging modalities into the Waxholm Space atlas. As a proof of principle, we incorporated large scale high-resolution cyto-, muscarinic M2 receptor, and fiber architectonic images of rat brains into the 3D digital MRI based atlas of the Sprague Dawley rat in Waxholm Space. We describe the whole workflow, from image acquisition to reconstruction and registration of these three modalities into the Waxholm Space rat atlas. The registration of the brain sections into the atlas is performed by using both linear and non-linear transformations. The validity of the procedure is qualitatively demonstrated by visual inspection, and a quantitative evaluation is performed by measurement of the concordance between representative atlas-delineated regions and the same regions based on receptor or fiber architectonic data. This novel approach enables for the first time the generation of 3D reconstructed volumes of nerve fibers and fiber tracts, or of muscarinic M2 receptor density distributions, in an entire rat brain. Additionally, our pipeline facilitates the inclusion of further neuroimaging datasets, e.g., 3D reconstructed volumes of histochemical stainings or of the regional distributions of multiple other receptor types, into the Waxholm Space. Thereby, a multiscale and multimodal rat brain model was created in the Waxholm Space atlas of the rat brain. Since the registration of these multimodal high-resolution datasets into the same coordinate system is an indispensable requisite for multi-parameter analyses, this approach enables combined studies on receptor and cell distributions as well as fiber densities in the same anatomical structures at microscopic scales for the first time. PMID:27199682

3D Reconstructed Cyto-, Muscarinic M2 Receptor, and Fiber Architecture of the Rat Brain Registered to the Waxholm Space Atlas.

PubMed

Schubert, Nicole; Axer, Markus; Schober, Martin; Huynh, Anh-Minh; Huysegoms, Marcel; Palomero-Gallagher, Nicola; Bjaalie, Jan G; Leergaard, Trygve B; Kirlangic, Mehmet E; Amunts, Katrin; Zilles, Karl

2016-01-01

High-resolution multiscale and multimodal 3D models of the brain are essential tools to understand its complex structural and functional organization. Neuroimaging techniques addressing different aspects of brain organization should be integrated in a reference space to enable topographically correct alignment and subsequent analysis of the various datasets and their modalities. The Waxholm Space (http://software.incf.org/software/waxholm-space) is a publicly available 3D coordinate-based standard reference space for the mapping and registration of neuroanatomical data in rodent brains. This paper provides a newly developed pipeline combining imaging and reconstruction steps with a novel registration strategy to integrate new neuroimaging modalities into the Waxholm Space atlas. As a proof of principle, we incorporated large scale high-resolution cyto-, muscarinic M2 receptor, and fiber architectonic images of rat brains into the 3D digital MRI based atlas of the Sprague Dawley rat in Waxholm Space. We describe the whole workflow, from image acquisition to reconstruction and registration of these three modalities into the Waxholm Space rat atlas. The registration of the brain sections into the atlas is performed by using both linear and non-linear transformations. The validity of the procedure is qualitatively demonstrated by visual inspection, and a quantitative evaluation is performed by measurement of the concordance between representative atlas-delineated regions and the same regions based on receptor or fiber architectonic data. This novel approach enables for the first time the generation of 3D reconstructed volumes of nerve fibers and fiber tracts, or of muscarinic M2 receptor density distributions, in an entire rat brain. Additionally, our pipeline facilitates the inclusion of further neuroimaging datasets, e.g., 3D reconstructed volumes of histochemical stainings or of the regional distributions of multiple other receptor types, into the Waxholm Space. Thereby, a multiscale and multimodal rat brain model was created in the Waxholm Space atlas of the rat brain. Since the registration of these multimodal high-resolution datasets into the same coordinate system is an indispensable requisite for multi-parameter analyses, this approach enables combined studies on receptor and cell distributions as well as fiber densities in the same anatomical structures at microscopic scales for the first time.

Three-year follow-up results of a residential community reintegration program for patients with chronic acquired brain injury.

PubMed

Geurtsen, Gert J; van Heugten, Caroline M; Martina, Juan D; Rietveld, Antonius C; Meijer, Ron; Geurts, Alexander C

2012-05-01

To evaluate outcomes of a residential community reintegration program 3 years after treatment on independent living, societal participation, emotional well-being, and quality of life in patients with chronic acquired brain injury and psychosocial problems hampering societal participation. A follow-up assessment 3 years after treatment was compared with the 1-year follow-up assessment in a prospective cohort study. A tertiary rehabilitation center for acquired brain injury. Of the 67 patients assessed at the 1-year follow-up, 63 subjects (94%; 42 men; mean age at admission to treatment 24.7y; mean time postonset 5.1y) were available at the 3-year follow-up and taken into account in the analyses. A structured residential treatment program directed at improving independence in domestic life, work, leisure time, and social interactions. Community Integration Questionnaire, Employability Rating Scale, living situation, school, work situation, work hours, Center for Epidemiological Studies-Depression scale, and the World Health Organization Quality of Life Scale Abbreviated (5 scales). There were no significant differences for any of the outcome measures between the 1-year and 3-year follow-up assessment. These results indicate that the established significant and clinically relevant improvements after a residential community reintegration program remain stable in the long term. Copyright © 2012 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Sound symbolism scaffolds language development in preverbal infants.

PubMed

Asano, Michiko; Imai, Mutsumi; Kita, Sotaro; Kitajo, Keiichi; Okada, Hiroyuki; Thierry, Guillaume

2015-02-01

A fundamental question in language development is how infants start to assign meaning to words. Here, using three Electroencephalogram (EEG)-based measures of brain activity, we establish that preverbal 11-month-old infants are sensitive to the non-arbitrary correspondences between language sounds and concepts, that is, to sound symbolism. In each trial, infant participants were presented with a visual stimulus (e.g., a round shape) followed by a novel spoken word that either sound-symbolically matched ("moma") or mismatched ("kipi") the shape. Amplitude increase in the gamma band showed perceptual integration of visual and auditory stimuli in the match condition within 300 msec of word onset. Furthermore, phase synchronization between electrodes at around 400 msec revealed intensified large-scale, left-hemispheric communication between brain regions in the mismatch condition as compared to the match condition, indicating heightened processing effort when integration was more demanding. Finally, event-related brain potentials showed an increased adult-like N400 response - an index of semantic integration difficulty - in the mismatch as compared to the match condition. Together, these findings suggest that 11-month-old infants spontaneously map auditory language onto visual experience by recruiting a cross-modal perceptual processing system and a nascent semantic network within the first year of life. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Brain noise is task dependent and region specific.

PubMed

Misić, Bratislav; Mills, Travis; Taylor, Margot J; McIntosh, Anthony R

2010-11-01

The emerging organization of anatomical and functional connections during human brain development is thought to facilitate global integration of information. Recent empirical and computational studies have shown that this enhanced capacity for information processing enables a diversified dynamic repertoire that manifests in neural activity as irregularity and noise. However, transient functional networks unfold over multiple time, scales and the embedding of a particular region depends not only on development, but also on the manner in which sensory and cognitive systems are engaged. Here we show that noise is a facet of neural activity that is also sensitive to the task context and is highly region specific. Children (6-16 yr) and adults (20-41 yr) performed a one-back face recognition task with inverted and upright faces. Neuromagnetic activity was estimated at several hundred sources in the brain by applying a beamforming technique to the magnetoencephalogram (MEG). During development, neural activity became more variable across the whole brain, with most robust increases in medial parietal regions, such as the precuneus and posterior cingulate cortex. For young children and adults, activity evoked by upright faces was more variable and noisy compared with inverted faces, and this effect was reliable only in the right fusiform gyrus. These results are consistent with the notion that upright faces engender a variety of integrative neural computations, such as the relations among facial features and their holistic constitution. This study shows that transient changes in functional integration modulated by task demand are evident in the variability of regional neural activity.

Amplitude-integrated EEG in newborns with critical congenital heart disease predicts preoperative brain magnetic resonance imaging findings.

PubMed

Mulkey, Sarah B; Yap, Vivien L; Bai, Shasha; Ramakrishnaiah, Raghu H; Glasier, Charles M; Bornemeier, Renee A; Schmitz, Michael L; Bhutta, Adnan T

2015-06-01

The study aims are to evaluate cerebral background patterns using amplitude-integrated electroencephalography in newborns with critical congenital heart disease, determine if amplitude-integrated electroencephalography is predictive of preoperative brain injury, and assess the incidence of preoperative seizures. We hypothesize that amplitude-integrated electroencephalography will show abnormal background patterns in the early preoperative period in infants with congenital heart disease that have preoperative brain injury on magnetic resonance imaging. Twenty-four newborns with congenital heart disease requiring surgery at younger than 30 days of age were prospectively enrolled within the first 3 days of age at a tertiary care pediatric hospital. Infants had amplitude-integrated electroencephalography for 24 hours beginning close to birth and preoperative brain magnetic resonance imaging. The amplitude-integrated electroencephalographies were read to determine if the background pattern was normal, mildly abnormal, or severely abnormal. The presence of seizures and sleep-wake cycling were noted. The preoperative brain magnetic resonance imaging scans were used for brain injury and brain atrophy assessment. Fifteen of 24 infants had abnormal amplitude-integrated electroencephalography at 0.71 (0-2) (mean [range]) days of age. In five infants, the background pattern was severely abnormal. (burst suppression and/or continuous low voltage). Of the 15 infants with abnormal amplitude-integrated electroencephalography, 9 (60%) had brain injury. One infant with brain injury had a seizure on amplitude-integrated electroencephalography. A severely abnormal background pattern on amplitude-integrated electroencephalography was associated with brain atrophy (P = 0.03) and absent sleep-wake cycling (P = 0.022). Background cerebral activity is abnormal on amplitude-integrated electroencephalography following birth in newborns with congenital heart disease who have findings of brain injury and/or brain atrophy on preoperative brain magnetic resonance imaging. Copyright © 2015 Elsevier Inc. All rights reserved.

A cellular perspective on brain energy metabolism and functional imaging.

PubMed

Magistretti, Pierre J; Allaman, Igor

2015-05-20

The energy demands of the brain are high: they account for at least 20% of the body's energy consumption. Evolutionary studies indicate that the emergence of higher cognitive functions in humans is associated with an increased glucose utilization and expression of energy metabolism genes. Functional brain imaging techniques such as fMRI and PET, which are widely used in human neuroscience studies, detect signals that monitor energy delivery and use in register with neuronal activity. Recent technological advances in metabolic studies with cellular resolution have afforded decisive insights into the understanding of the cellular and molecular bases of the coupling between neuronal activity and energy metabolism and point at a key role of neuron-astrocyte metabolic interactions. This article reviews some of the most salient features emerging from recent studies and aims at providing an integration of brain energy metabolism across resolution scales. Copyright © 2015 Elsevier Inc. All rights reserved.

Fundamental challenges of contemporary "personality" research. Comment on "Personality from a cognitive-biological perspective" by Y. Neuman

NASA Astrophysics Data System (ADS)

Uher, Jana

2014-12-01

The growing interest in "personality" from scientists of ever more diverse fields demands conceptual integrations-and reveals fundamental challenges. For what is "personality" given that "it" is explored in humans and nonhuman species, that people encode "it" in their everyday language, scientists seek "it" in the brain and study "it" primarily with rating scales?

The Virtual Brain: a simulator of primate brain network dynamics.

PubMed

Sanz Leon, Paula; Knock, Stuart A; Woodman, M Marmaduke; Domide, Lia; Mersmann, Jochen; McIntosh, Anthony R; Jirsa, Viktor

2013-01-01

We present The Virtual Brain (TVB), a neuroinformatics platform for full brain network simulations using biologically realistic connectivity. This simulation environment enables the model-based inference of neurophysiological mechanisms across different brain scales that underlie the generation of macroscopic neuroimaging signals including functional MRI (fMRI), EEG and MEG. Researchers from different backgrounds can benefit from an integrative software platform including a supporting framework for data management (generation, organization, storage, integration and sharing) and a simulation core written in Python. TVB allows the reproduction and evaluation of personalized configurations of the brain by using individual subject data. This personalization facilitates an exploration of the consequences of pathological changes in the system, permitting to investigate potential ways to counteract such unfavorable processes. The architecture of TVB supports interaction with MATLAB packages, for example, the well known Brain Connectivity Toolbox. TVB can be used in a client-server configuration, such that it can be remotely accessed through the Internet thanks to its web-based HTML5, JS, and WebGL graphical user interface. TVB is also accessible as a standalone cross-platform Python library and application, and users can interact with the scientific core through the scripting interface IDLE, enabling easy modeling, development and debugging of the scientific kernel. This second interface makes TVB extensible by combining it with other libraries and modules developed by the Python scientific community. In this article, we describe the theoretical background and foundations that led to the development of TVB, the architecture and features of its major software components as well as potential neuroscience applications.

The Virtual Brain: a simulator of primate brain network dynamics

PubMed Central

Sanz Leon, Paula; Knock, Stuart A.; Woodman, M. Marmaduke; Domide, Lia; Mersmann, Jochen; McIntosh, Anthony R.; Jirsa, Viktor

2013-01-01

We present The Virtual Brain (TVB), a neuroinformatics platform for full brain network simulations using biologically realistic connectivity. This simulation environment enables the model-based inference of neurophysiological mechanisms across different brain scales that underlie the generation of macroscopic neuroimaging signals including functional MRI (fMRI), EEG and MEG. Researchers from different backgrounds can benefit from an integrative software platform including a supporting framework for data management (generation, organization, storage, integration and sharing) and a simulation core written in Python. TVB allows the reproduction and evaluation of personalized configurations of the brain by using individual subject data. This personalization facilitates an exploration of the consequences of pathological changes in the system, permitting to investigate potential ways to counteract such unfavorable processes. The architecture of TVB supports interaction with MATLAB packages, for example, the well known Brain Connectivity Toolbox. TVB can be used in a client-server configuration, such that it can be remotely accessed through the Internet thanks to its web-based HTML5, JS, and WebGL graphical user interface. TVB is also accessible as a standalone cross-platform Python library and application, and users can interact with the scientific core through the scripting interface IDLE, enabling easy modeling, development and debugging of the scientific kernel. This second interface makes TVB extensible by combining it with other libraries and modules developed by the Python scientific community. In this article, we describe the theoretical background and foundations that led to the development of TVB, the architecture and features of its major software components as well as potential neuroscience applications. PMID:23781198

Multimodal integration of fMRI and EEG data for high spatial and temporal resolution analysis of brain networks

PubMed Central

Mantini, D.; Marzetti, L.; Corbetta, M.; Romani, G.L.; Del Gratta, C.

2017-01-01

Two major non-invasive brain mapping techniques, electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), have complementary advantages with regard to their spatial and temporal resolution. We propose an approach based on the integration of EEG and fMRI, enabling the EEG temporal dynamics of information processing to be characterized within spatially well-defined fMRI large-scale networks. First, the fMRI data are decomposed into networks by means of spatial independent component analysis (sICA), and those associated with intrinsic activity and/or responding to task performance are selected using information from the related time-courses. Next, the EEG data over all sensors are averaged with respect to event timing, thus calculating event-related potentials (ERPs). The ERPs are subjected to temporal ICA (tICA), and the resulting components are localized with the weighted minimum norm (WMNLS) algorithm using the task-related fMRI networks as priors. Finally, the temporal contribution of each ERP component in the areas belonging to the fMRI large-scale networks is estimated. The proposed approach has been evaluated on visual target detection data. Our results confirm that two different components, commonly observed in EEG when presenting novel and salient stimuli respectively, are related to the neuronal activation in large-scale networks, operating at different latencies and associated with different functional processes. PMID:20052528

Computing Arm Movements with a Monkey Brainet.

PubMed

Ramakrishnan, Arjun; Ifft, Peter J; Pais-Vieira, Miguel; Byun, Yoon Woo; Zhuang, Katie Z; Lebedev, Mikhail A; Nicolelis, Miguel A L

2015-07-09

Traditionally, brain-machine interfaces (BMIs) extract motor commands from a single brain to control the movements of artificial devices. Here, we introduce a Brainet that utilizes very-large-scale brain activity (VLSBA) from two (B2) or three (B3) nonhuman primates to engage in a common motor behaviour. A B2 generated 2D movements of an avatar arm where each monkey contributed equally to X and Y coordinates; or one monkey fully controlled the X-coordinate and the other controlled the Y-coordinate. A B3 produced arm movements in 3D space, while each monkey generated movements in 2D subspaces (X-Y, Y-Z, or X-Z). With long-term training we observed increased coordination of behavior, increased correlations in neuronal activity between different brains, and modifications to neuronal representation of the motor plan. Overall, performance of the Brainet improved owing to collective monkey behaviour. These results suggest that primate brains can be integrated into a Brainet, which self-adapts to achieve a common motor goal.

Computing Arm Movements with a Monkey Brainet

PubMed Central

Ramakrishnan, Arjun; Ifft, Peter J.; Pais-Vieira, Miguel; Woo Byun, Yoon; Zhuang, Katie Z.; Lebedev, Mikhail A.; Nicolelis, Miguel A.L.

2015-01-01

Traditionally, brain-machine interfaces (BMIs) extract motor commands from a single brain to control the movements of artificial devices. Here, we introduce a Brainet that utilizes very-large-scale brain activity (VLSBA) from two (B2) or three (B3) nonhuman primates to engage in a common motor behaviour. A B2 generated 2D movements of an avatar arm where each monkey contributed equally to X and Y coordinates; or one monkey fully controlled the X-coordinate and the other controlled the Y-coordinate. A B3 produced arm movements in 3D space, while each monkey generated movements in 2D subspaces (X-Y, Y-Z, or X-Z). With long-term training we observed increased coordination of behavior, increased correlations in neuronal activity between different brains, and modifications to neuronal representation of the motor plan. Overall, performance of the Brainet improved owing to collective monkey behaviour. These results suggest that primate brains can be integrated into a Brainet, which self-adapts to achieve a common motor goal. PMID:26158523

Individual differences and time-varying features of modular brain architecture.

PubMed

Liao, Xuhong; Cao, Miao; Xia, Mingrui; He, Yong

2017-05-15

Recent studies have suggested that human brain functional networks are topologically organized into functionally specialized but inter-connected modules to facilitate efficient information processing and highly flexible cognitive function. However, these studies have mainly focused on group-level network modularity analyses using "static" functional connectivity approaches. How these extraordinary modular brain structures vary across individuals and spontaneously reconfigure over time remain largely unknown. Here, we employed multiband resting-state functional MRI data (N=105) from the Human Connectome Project and a graph-based modularity analysis to systematically investigate individual variability and dynamic properties in modular brain networks. We showed that the modular structures of brain networks dramatically vary across individuals, with higher modular variability primarily in the association cortex (e.g., fronto-parietal and attention systems) and lower variability in the primary systems. Moreover, brain regions spontaneously changed their module affiliations on a temporal scale of seconds, which cannot be simply attributable to head motion and sampling error. Interestingly, the spatial pattern of intra-subject dynamic modular variability largely overlapped with that of inter-subject modular variability, both of which were highly reproducible across repeated scanning sessions. Finally, the regions with remarkable individual/temporal modular variability were closely associated with network connectors and the number of cognitive components, suggesting a potential contribution to information integration and flexible cognitive function. Collectively, our findings highlight individual modular variability and the notable dynamic characteristics in large-scale brain networks, which enhance our understanding of the neural substrates underlying individual differences in a variety of cognition and behaviors. Copyright © 2017 Elsevier Inc. All rights reserved.

Angular default mode network connectivity across working memory load.

PubMed

Vatansever, D; Manktelow, A E; Sahakian, B J; Menon, D K; Stamatakis, E A

2017-01-01

Initially identified during no-task, baseline conditions, it has now been suggested that the default mode network (DMN) engages during a variety of working memory paradigms through its flexible interactions with other large-scale brain networks. Nevertheless, its contribution to whole-brain connectivity dynamics across increasing working memory load has not been explicitly assessed. The aim of our study was to determine which DMN hubs relate to working memory task performance during an fMRI-based n-back paradigm with parametric increases in difficulty. Using a voxel-wise metric, termed the intrinsic connectivity contrast (ICC), we found that the bilateral angular gyri (core DMN hubs) displayed the greatest change in global connectivity across three levels of n-back task load. Subsequent seed-based functional connectivity analysis revealed that the angular DMN regions robustly interact with other large-scale brain networks, suggesting a potential involvement in the global integration of information. Further support for this hypothesis comes from the significant correlations we found between angular gyri connectivity and reaction times to correct responses. The implication from our study is that the DMN is actively involved during the n-back task and thus plays an important role related to working memory, with its core angular regions contributing to the changes in global brain connectivity in response to increasing environmental demands. Hum Brain Mapp 38:41-52, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

The integrate model of emotion, thinking and self regulation: an application to the "paradox of aging".

PubMed

Williams, Leanne M; Gatt, Justine M; Hatch, Ainslie; Palmer, Donna M; Nagy, Marie; Rennie, Christopher; Cooper, Nicholas J; Morris, Charlotte; Grieve, Stuart; Dobson-Stone, Carol; Schofield, Peter; Clark, C Richard; Gordon, Evian; Arns, Martijn; Paul, Robert H

2008-09-01

This study was undertaken using the INTEGRATE Model of brain organization, which is based on a temporal continuum of emotion, thinking and self regulation. In this model, the key organizing principle of self adaption is the motivation to minimize danger and maximize reward. This principle drives brain organization across a temporal continuum spanning milliseconds to seconds, minutes and hours. The INTEGRATE Model comprises three distinct processes across this continuum. Emotion is defined by automatic action tendencies triggered by signals that are significant due to their relevance to minimizing danger-maximizing reward (such as abrupt, high contrast stimuli). Thinking represents cognitive functions and feelings that rely on brain and body feedback emerging from around 200 ms post-stimulus onwards. Self regulation is the modulation of emotion, thinking and feeling over time, according to more abstract adaptions to minimize danger-maximize reward. Here, we examined the impact of dispositional factors, age and genetic variation, on this temporal continuum. Brain Resource methodology provided a standardized platform for acquiring genetic, brain and behavioral data in the same 1000 healthy subjects. Results showed a "paradox" of declining function in the "thinking" time scale over the lifespan (6 to 80+ years), but a corresponding preservation or even increase in automatic functions of "emotion" and "self regulation". This paradox was paralleled by a greater loss of grey matter in cortical association areas (assessed using MRI) over age, but a relative preservation of subcortical grey matter. Genetic polymorphisms associated with both healthy function and susceptibility to disorder (including the BDNFVal(66)Met, COMTVal(158/108)Met, MAOA and DRD4 tandem repeat and 5HTT-LPR polymorphisms) made specific contributions to emotion, thinking and self regulatory functions, which also varied according to age.

75 FR 76994 - Center for Scientific Review; Notice of Closed Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-10

... Committee: Brain Disorders and Clinical Neuroscience Integrated Review Group Developmental Brain Disorders....gov . Name of Committee: Brain Disorders and Clinical Neuroscience Integrated Review Group, Cell [email protected] . Name of Committee: Brain Disorders and Clinical Neuroscience Integrated Review Group...

Development and construct validation of the Client-Centredness of Goal Setting (C-COGS) scale.

PubMed

Doig, Emmah; Prescott, Sarah; Fleming, Jennifer; Cornwell, Petrea; Kuipers, Pim

2015-07-01

Client-centred philosophy is integral to occupational therapy practice and client-centred goal planning is considered fundamental to rehabilitation. Evaluation of whether goal-planning practices are client-centred requires an understanding of the client's perspective about goal-planning processes and practices. The Client-Centredness of Goal Setting (C-COGS) was developed for use by practitioners who seek to be more client-centred and who require a scale to guide and evaluate individually orientated practice, especially with adults with cognitive impairment related to acquired brain injury. To describe development of the C-COGS scale and examine its construct validity. The C-COGS was administered to 42 participants with acquired brain injury after multidisciplinary goal planning. C-COGS scores were correlated with the Canadian Occupational Performance Measure (COPM) importance scores, and measures of therapeutic alliance, motivation, and global functioning to establish construct validity. The C-COGS scale has three subscales evaluating goal alignment, goal planning participation, and client-centredness of goals. The C-COGS subscale items demonstrated moderately significant correlations with scales measuring similar constructs. Findings provide preliminary evidence to support the construct validity of the C-COGS scale, which is intended to be used to evaluate and reflect on client-centred goal planning in clinical practice, and to highlight factors contributing to best practice rehabilitation.

Neurokernel: An Open Source Platform for Emulating the Fruit Fly Brain

PubMed Central

2016-01-01

We have developed an open software platform called Neurokernel for collaborative development of comprehensive models of the brain of the fruit fly Drosophila melanogaster and their execution and testing on multiple Graphics Processing Units (GPUs). Neurokernel provides a programming model that capitalizes upon the structural organization of the fly brain into a fixed number of functional modules to distinguish between these modules’ local information processing capabilities and the connectivity patterns that link them. By defining mandatory communication interfaces that specify how data is transmitted between models of each of these modules regardless of their internal design, Neurokernel explicitly enables multiple researchers to collaboratively model the fruit fly’s entire brain by integration of their independently developed models of its constituent processing units. We demonstrate the power of Neurokernel’s model integration by combining independently developed models of the retina and lamina neuropils in the fly’s visual system and by demonstrating their neuroinformation processing capability. We also illustrate Neurokernel’s ability to take advantage of direct GPU-to-GPU data transfers with benchmarks that demonstrate scaling of Neurokernel’s communication performance both over the number of interface ports exposed by an emulation’s constituent modules and the total number of modules comprised by an emulation. PMID:26751378

Large-scale, high-density (up to 512 channels) recording of local circuits in behaving animals

PubMed Central

Berényi, Antal; Somogyvári, Zoltán; Nagy, Anett J.; Roux, Lisa; Long, John D.; Fujisawa, Shigeyoshi; Stark, Eran; Leonardo, Anthony; Harris, Timothy D.

2013-01-01

Monitoring representative fractions of neurons from multiple brain circuits in behaving animals is necessary for understanding neuronal computation. Here, we describe a system that allows high-channel-count recordings from a small volume of neuronal tissue using a lightweight signal multiplexing headstage that permits free behavior of small rodents. The system integrates multishank, high-density recording silicon probes, ultraflexible interconnects, and a miniaturized microdrive. These improvements allowed for simultaneous recordings of local field potentials and unit activity from hundreds of sites without confining free movements of the animal. The advantages of large-scale recordings are illustrated by determining the electroanatomic boundaries of layers and regions in the hippocampus and neocortex and constructing a circuit diagram of functional connections among neurons in real anatomic space. These methods will allow the investigation of circuit operations and behavior-dependent interregional interactions for testing hypotheses of neural networks and brain function. PMID:24353300

Allometric Analysis Detects Brain Size-Independent Effects of Sex and Sex Chromosome Complement on Human Cerebellar Organization.

PubMed

Mankiw, Catherine; Park, Min Tae M; Reardon, P K; Fish, Ari M; Clasen, Liv S; Greenstein, Deanna; Giedd, Jay N; Blumenthal, Jonathan D; Lerch, Jason P; Chakravarty, M Mallar; Raznahan, Armin

2017-05-24

The cerebellum is a large hindbrain structure that is increasingly recognized for its contribution to diverse domains of cognitive and affective processing in human health and disease. Although several of these domains are sex biased, our fundamental understanding of cerebellar sex differences-including their spatial distribution, potential biological determinants, and independence from brain volume variation-lags far behind that for the cerebrum. Here, we harness automated neuroimaging methods for cerebellar morphometrics in 417 individuals to (1) localize normative male-female differences in raw cerebellar volume, (2) compare these to sex chromosome effects estimated across five rare sex (X/Y) chromosome aneuploidy (SCA) syndromes, and (3) clarify brain size-independent effects of sex and SCA on cerebellar anatomy using a generalizable allometric approach that considers scaling relationships between regional cerebellar volume and brain volume in health. The integration of these approaches shows that (1) sex and SCA effects on raw cerebellar volume are large and distributed, but regionally heterogeneous, (2) human cerebellar volume scales with brain volume in a highly nonlinear and regionally heterogeneous fashion that departs from documented patterns of cerebellar scaling in phylogeny, and (3) cerebellar organization is modified in a brain size-independent manner by sex (relative expansion of total cerebellum, flocculus, and Crus II-lobule VIIIB volumes in males) and SCA (contraction of total cerebellar, lobule IV, and Crus I volumes with additional X- or Y-chromosomes; X-specific contraction of Crus II-lobule VIIIB). Our methods and results clarify the shifts in human cerebellar organization that accompany interwoven variations in sex, sex chromosome complement, and brain size. SIGNIFICANCE STATEMENT Cerebellar systems are implicated in diverse domains of sex-biased behavior and pathology, but we lack a basic understanding of how sex differences in the human cerebellum are distributed and determined. We leverage a rare neuroimaging dataset to deconvolve the interwoven effects of sex, sex chromosome complement, and brain size on human cerebellar organization. We reveal topographically variegated scaling relationships between regional cerebellar volume and brain size in humans, which (1) are distinct from those observed in phylogeny, (2) invalidate a traditional neuroimaging method for brain volume correction, and (3) allow more valid and accurate resolution of which cerebellar subcomponents are sensitive to sex and sex chromosome complement. These findings advance understanding of cerebellar organization in health and sex chromosome aneuploidy. Copyright © 2017 the authors 0270-6474/17/375222-11$15.00/0.

Dynamics of brain activity in motor and frontal cortical areas during music listening: a magnetoencephalographic study.

PubMed

Popescu, Mihai; Otsuka, Asuka; Ioannides, Andreas A

2004-04-01

There are formidable problems in studying how 'real' music engages the brain over wide ranges of temporal scales extending from milliseconds to a lifetime. In this work, we recorded the magnetoencephalographic signal while subjects listened to music as it unfolded over long periods of time (seconds), and we developed and applied methods to correlate the time course of the regional brain activations with the dynamic aspects of the musical sound. We showed that frontal areas generally respond with slow time constants to the music, reflecting their more integrative mode; motor-related areas showed transient-mode responses to fine temporal scale structures of the sound. The study combined novel analysis techniques designed to capture and quantify fine temporal sequencing from the authentic musical piece (characterized by a clearly defined rhythm and melodic structure) with the extraction of relevant features from the dynamics of the regional brain activations. The results demonstrated that activity in motor-related structures, specifically in lateral premotor areas, supplementary motor areas, and somatomotor areas, correlated with measures of rhythmicity derived from the music. These correlations showed distinct laterality depending on how the musical performance deviated from the strict tempo of the music score, that is, depending on the musical expression.

Congenital blindness is associated with large-scale reorganization of anatomical networks.

PubMed

Hasson, Uri; Andric, Michael; Atilgan, Hicret; Collignon, Olivier

2016-03-01

Blindness is a unique model for understanding the role of experience in the development of the brain's functional and anatomical architecture. Documenting changes in the structure of anatomical networks for this population would substantiate the notion that the brain's core network-level organization may undergo neuroplasticity as a result of life-long experience. To examine this issue, we compared whole-brain networks of regional cortical-thickness covariance in early blind and matched sighted individuals. This covariance is thought to reflect signatures of integration between systems involved in similar perceptual/cognitive functions. Using graph-theoretic metrics, we identified a unique mode of anatomical reorganization in the blind that differed from that found for sighted. This was seen in that network partition structures derived from subgroups of blind were more similar to each other than they were to partitions derived from sighted. Notably, after deriving network partitions, we found that language and visual regions tended to reside within separate modules in sighted but showed a pattern of merging into shared modules in the blind. Our study demonstrates that early visual deprivation triggers a systematic large-scale reorganization of whole-brain cortical-thickness networks, suggesting changes in how occipital regions interface with other functional networks in the congenitally blind. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

The Maryland Large-Scale Integrated Neurocognitive Architecture

DTIC Science & Technology

2008-03-01

Visual input enters the network through the lateral geniculate nucleus (LGN) and is passed forward through visual brain regions (V1, V2, and V4...University of Maryland Sponsored by Defense Advanced Research Projects Agency DARPA Order No. V029 APPROVED FOR PUBLIC RELEASE...interpreted as necessarily representing the official policies, either expressed or implied, of the Defense Advanced Research Projects Agency or the U.S

Integrative, multimodal analysis of glioblastoma using TCGA molecular data, pathology images, and clinical outcomes.

PubMed

Kong, Jun; Cooper, Lee A D; Wang, Fusheng; Gutman, David A; Gao, Jingjing; Chisolm, Candace; Sharma, Ashish; Pan, Tony; Van Meir, Erwin G; Kurc, Tahsin M; Moreno, Carlos S; Saltz, Joel H; Brat, Daniel J

2011-12-01

Multimodal, multiscale data synthesis is becoming increasingly critical for successful translational biomedical research. In this letter, we present a large-scale investigative initiative on glioblastoma, a high-grade brain tumor, with complementary data types using in silico approaches. We integrate and analyze data from The Cancer Genome Atlas Project on glioblastoma that includes novel nuclear phenotypic data derived from microscopic slides, genotypic signatures described by transcriptional class and genetic alterations, and clinical outcomes defined by response to therapy and patient survival. Our preliminary results demonstrate numerous clinically and biologically significant correlations across multiple data types, revealing the power of in silico multimodal data integration for cancer research.

Korea Brain Initiative: Integration and Control of Brain Functions.

PubMed

Jeong, Sung-Jin; Lee, Haejin; Hur, Eun-Mi; Choe, Youngshik; Koo, Ja Wook; Rah, Jong-Cheol; Lee, Kea Joo; Lim, Hyun-Ho; Sun, Woong; Moon, Cheil; Kim, Kyungjin

2016-11-02

This article introduces the history and the long-term goals of the Korea Brain Initiative, which is centered on deciphering the brain functions and mechanisms that mediate the integration and control of brain functions that underlie decision-making. The goal of this initiative is the mapping of a functional connectome with searchable, multi-dimensional, and information-integrated features. The project also includes the development of novel technologies and neuro-tools for integrated brain mapping. Beyond the scientific goals this grand endeavor will ultimately have socioeconomic ramifications that not only facilitate global collaboration in the neuroscience community, but also develop various brain science-related industrial and medical innovations. Copyright © 2016. Published by Elsevier Inc.

Integrating the Allen Brain Institute Cell Types Database into Automated Neuroscience Workflow.

PubMed

Stockton, David B; Santamaria, Fidel

2017-10-01

We developed software tools to download, extract features, and organize the Cell Types Database from the Allen Brain Institute (ABI) in order to integrate its whole cell patch clamp characterization data into the automated modeling/data analysis cycle. To expand the potential user base we employed both Python and MATLAB. The basic set of tools downloads selected raw data and extracts cell, sweep, and spike features, using ABI's feature extraction code. To facilitate data manipulation we added a tool to build a local specialized database of raw data plus extracted features. Finally, to maximize automation, we extended our NeuroManager workflow automation suite to include these tools plus a separate investigation database. The extended suite allows the user to integrate ABI experimental and modeling data into an automated workflow deployed on heterogeneous computer infrastructures, from local servers, to high performance computing environments, to the cloud. Since our approach is focused on workflow procedures our tools can be modified to interact with the increasing number of neuroscience databases being developed to cover all scales and properties of the nervous system.

Brain Dynamics of Aging: Multiscale Variability of EEG Signals at Rest and during an Auditory Oddball Task1,2,3

PubMed Central

Perdikis, Dionysios; Müller, Viktor; Blanc, Jean-Luc; Huys, Raoul; Temprado, Jean-Jacques

2015-01-01

Abstract The present work focused on the study of fluctuations of cortical activity across time scales in young and older healthy adults. The main objective was to offer a comprehensive characterization of the changes of brain (cortical) signal variability during aging, and to make the link with known underlying structural, neurophysiological, and functional modifications, as well as aging theories. We analyzed electroencephalogram (EEG) data of young and elderly adults, which were collected at resting state and during an auditory oddball task. We used a wide battery of metrics that typically are separately applied in the literature, and we compared them with more specific ones that address their limits. Our procedure aimed to overcome some of the methodological limitations of earlier studies and verify whether previous findings can be reproduced and extended to different experimental conditions. In both rest and task conditions, our results mainly revealed that EEG signals presented systematic age-related changes that were time-scale-dependent with regard to the structure of fluctuations (complexity) but not with regard to their magnitude. Namely, compared with young adults, the cortical fluctuations of the elderly were more complex at shorter time scales, but less complex at longer scales, although always showing a lower variance. Additionally, the elderly showed signs of spatial, as well as between, experimental conditions dedifferentiation. By integrating these so far isolated findings across time scales, metrics, and conditions, the present study offers an overview of age-related changes in the fluctuation electrocortical activity while making the link with underlying brain dynamics. PMID:26464983

From behavior to neural dynamics: An integrated theory of attention

PubMed Central

Buschman, Timothy J.; Kastner, Sabine

2015-01-01

The brain has a limited capacity and therefore needs mechanisms to selectively enhance the information most relevant to one’s current behavior. We refer to these mechanisms as ‘attention’. Attention acts by increasing the strength of selected neural representations and preferentially routing them through the brain’s large-scale network. This is a critical component of cognition and therefore has been a central topic in cognitive neuroscience. Here we review a diverse literature that has studied attention at the level of behavior, networks, circuits and neurons. We then integrate these disparate results into a unified theory of attention. PMID:26447577

Parsing the Behavioral and Brain Mechanisms of Third-Party Punishment

PubMed Central

Bonnie, Richard J.; Hoffman, Morris B.; Shen, Francis X.; Simons, Kenneth W.

2016-01-01

The evolved capacity for third-party punishment is considered crucial to the emergence and maintenance of elaborate human social organization and is central to the modern provision of fairness and justice within society. Although it is well established that the mental state of the offender and the severity of the harm he caused are the two primary predictors of punishment decisions, the precise cognitive and brain mechanisms by which these distinct components are evaluated and integrated into a punishment decision are poorly understood. Using fMRI, here we implement a novel experimental design to functionally dissociate the mechanisms underlying evaluation, integration, and decision that were conflated in previous studies of third-party punishment. Behaviorally, the punishment decision is primarily defined by a superadditive interaction between harm and mental state, with subjects weighing the interaction factor more than the single factors of harm and mental state. On a neural level, evaluation of harms engaged brain areas associated with affective and somatosensory processing, whereas mental state evaluation primarily recruited circuitry involved in mentalization. Harm and mental state evaluations are integrated in medial prefrontal and posterior cingulate structures, with the amygdala acting as a pivotal hub of the interaction between harm and mental state. This integrated information is used by the right dorsolateral prefrontal cortex at the time of the decision to assign an appropriate punishment through a distributed coding system. Together, these findings provide a blueprint of the brain mechanisms by which neutral third parties render punishment decisions. SIGNIFICANCE STATEMENT Punishment undergirds large-scale cooperation and helps dispense criminal justice. Yet it is currently unknown precisely how people assess the mental states of offenders, evaluate the harms they caused, and integrate those two components into a single punishment decision. Using a new design, we isolated these three processes, identifying the distinct brain systems and activities that enable each. Additional findings suggest that the amygdala plays a crucial role in mediating the interaction of mental state and harm information, whereas the dorsolateral prefrontal cortex plays a crucial, final-stage role, both in integrating mental state and harm information and in selecting a suitable punishment amount. These findings deepen our understanding of how punishment decisions are made, which may someday help to improve them. PMID:27605616

Parsing the Behavioral and Brain Mechanisms of Third-Party Punishment.

PubMed

Ginther, Matthew R; Bonnie, Richard J; Hoffman, Morris B; Shen, Francis X; Simons, Kenneth W; Jones, Owen D; Marois, René

2016-09-07

The evolved capacity for third-party punishment is considered crucial to the emergence and maintenance of elaborate human social organization and is central to the modern provision of fairness and justice within society. Although it is well established that the mental state of the offender and the severity of the harm he caused are the two primary predictors of punishment decisions, the precise cognitive and brain mechanisms by which these distinct components are evaluated and integrated into a punishment decision are poorly understood. Using fMRI, here we implement a novel experimental design to functionally dissociate the mechanisms underlying evaluation, integration, and decision that were conflated in previous studies of third-party punishment. Behaviorally, the punishment decision is primarily defined by a superadditive interaction between harm and mental state, with subjects weighing the interaction factor more than the single factors of harm and mental state. On a neural level, evaluation of harms engaged brain areas associated with affective and somatosensory processing, whereas mental state evaluation primarily recruited circuitry involved in mentalization. Harm and mental state evaluations are integrated in medial prefrontal and posterior cingulate structures, with the amygdala acting as a pivotal hub of the interaction between harm and mental state. This integrated information is used by the right dorsolateral prefrontal cortex at the time of the decision to assign an appropriate punishment through a distributed coding system. Together, these findings provide a blueprint of the brain mechanisms by which neutral third parties render punishment decisions. Punishment undergirds large-scale cooperation and helps dispense criminal justice. Yet it is currently unknown precisely how people assess the mental states of offenders, evaluate the harms they caused, and integrate those two components into a single punishment decision. Using a new design, we isolated these three processes, identifying the distinct brain systems and activities that enable each. Additional findings suggest that the amygdala plays a crucial role in mediating the interaction of mental state and harm information, whereas the dorsolateral prefrontal cortex plays a crucial, final-stage role, both in integrating mental state and harm information and in selecting a suitable punishment amount. These findings deepen our understanding of how punishment decisions are made, which may someday help to improve them. Copyright © 2016 Ginther et al.

HIV scale-up in Mozambique: Exceptionalism, normalisation and global health

PubMed Central

Høg, Erling

2014-01-01

The large-scale introduction of HIV and AIDS services in Mozambique from 2000 onwards occurred in the context of deep political commitment to sovereign nation-building and an important transition in the nation's health system. Simultaneously, the international community encountered a willing state partner that recognised the need to take action against the HIV epidemic. This article examines two critical policy shifts: sustained international funding and public health system integration (the move from parallel to integrated HIV services). The Mozambican government struggles to support its national health system against privatisation, NGO competition and internal brain drain. This is a sovereignty issue. However, the dominant discourse on self-determination shows a contradictory twist: it is part of the political rhetoric to keep the sovereignty discourse alive, while the real challenge is coordination, not partnerships. Nevertheless, we need more anthropological studies to understand the political implications of global health funding and governance. Other studies need to examine the consequences of public health system integration for the quality of access to health care. PMID:24499102

HIV scale-up in Mozambique: exceptionalism, normalisation and global health.

PubMed

Høg, Erling

2014-01-01

The large-scale introduction of HIV and AIDS services in Mozambique from 2000 onwards occurred in the context of deep political commitment to sovereign nation-building and an important transition in the nation's health system. Simultaneously, the international community encountered a willing state partner that recognised the need to take action against the HIV epidemic. This article examines two critical policy shifts: sustained international funding and public health system integration (the move from parallel to integrated HIV services). The Mozambican government struggles to support its national health system against privatisation, NGO competition and internal brain drain. This is a sovereignty issue. However, the dominant discourse on self-determination shows a contradictory twist: it is part of the political rhetoric to keep the sovereignty discourse alive, while the real challenge is coordination, not partnerships. Nevertheless, we need more anthropological studies to understand the political implications of global health funding and governance. Other studies need to examine the consequences of public health system integration for the quality of access to health care.

Long-term disability progression in primary progressive multiple sclerosis: a 15-year study.

PubMed

Rocca, Maria A; Sormani, Maria Pia; Rovaris, Marco; Caputo, Domenico; Ghezzi, Angelo; Montanari, Enrico; Bertolotto, Antonio; Laroni, Alice; Bergamaschi, Roberto; Martinelli, Vittorio; Comi, Giancarlo; Filippi, Massimo

2017-11-01

Prognostic markers of primary progressive multiple sclerosis evolution are needed. We investigated the added value of magnetic resonance imaging measures of brain and cervical cord damage in predicting long-term clinical worsening of primary progressive multiple sclerosis compared to simple clinical assessment. In 54 patients, conventional and diffusion tensor brain scans and cervical cord T1-weighted scans were acquired at baseline and after 15 months. Clinical evaluation was performed after 5 and 15 years in 49 patients. Lesion load, brain and cord atrophy, mean diffusivity and fractional anisotropy values from the brain normal-appearing white matter and grey matter were obtained. Using linear regression models, we screened the clinical and imaging variables as independent predictors of 15-year disability change (measured on the expanded disability status scale). At 15 years, 90% of the patients had disability progression. Integrating clinical and imaging variables at 15 months predicted disability changes at 15 years better than clinical factors at 5 years (R2 = 61% versus R2 = 57%). The model predicted long-term disability change with a precision within one point in 38 of 49 patients (77.6%). Integration of clinical and imaging measures allows identification of primary progressive multiple sclerosis patients at risk of long-term disease progression 4 years earlier than when using clinical assessment alone. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Non-invasive biomarkers of fetal brain development reflecting prenatal stress: An integrative multi-scale multi-species perspective on data collection and analysis.

PubMed

Frasch, Martin G; Lobmaier, Silvia M; Stampalija, Tamara; Desplats, Paula; Pallarés, María Eugenia; Pastor, Verónica; Brocco, Marcela A; Wu, Hau-Tieng; Schulkin, Jay; Herry, Christophe L; Seely, Andrew J E; Metz, Gerlinde A S; Louzoun, Yoram; Antonelli, Marta C

2018-05-30

Prenatal stress (PS) impacts early postnatal behavioural and cognitive development. This process of 'fetal programming' is mediated by the effects of the prenatal experience on the developing hypothalamic-pituitary-adrenal (HPA) axis and autonomic nervous system (ANS). We derive a multi-scale multi-species approach to devising preclinical and clinical studies to identify early non-invasively available pre- and postnatal biomarkers of PS. The multiple scales include brain epigenome, metabolome, microbiome and the ANS activity gauged via an array of advanced non-invasively obtainable properties of fetal heart rate fluctuations. The proposed framework has the potential to reveal mechanistic links between maternal stress during pregnancy and changes across these physiological scales. Such biomarkers may hence be useful as early and non-invasive predictors of neurodevelopmental trajectories influenced by the PS as well as follow-up indicators of success of therapeutic interventions to correct such altered neurodevelopmental trajectories. PS studies must be conducted on multiple scales derived from concerted observations in multiple animal models and human cohorts performed in an interactive and iterative manner and deploying machine learning for data synthesis, identification and validation of the best non-invasive detection and follow-up biomarkers, a prerequisite for designing effective therapeutic interventions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Oral choline decreases brain purine levels in lithium-treated subjects with rapid-cycling bipolar disorder: a double-blind trial using proton and lithium magnetic resonance spectroscopy.

PubMed

Lyoo, In Kyoon; Demopulos, Christina M; Hirashima, Fuyuki; Ahn, Kyung Heup; Renshaw, Perry F

2003-08-01

Oral choline administration has been reported to increase brain phosphatidylcholine levels. As phospholipid synthesis for maintaining membrane integrity in mammalian brain cells consumes approximately 10-15% of the total adenosine triphosphate (ATP) pool, an increased availability of brain choline may lead to an increase in ATP consumption. Given reports of genetic studies, which suggest mitochondrial dysfunction, and phosphorus (31P) magnetic resonance spectroscopy (MRS) studies, which report dysfunction in high-energy phosphate metabolism in patients with bipolar disorder, the current study is designed to evaluate the role of oral choline supplementation in modifying high-energy phosphate metabolism in subjects with bipolar disorder. Eight lithium-treated patients with DSM-IV bipolar disorder, rapid cycling type were randomly assigned to 50 mg/kg/day of choline bitartrate or placebo for 12 weeks. Brain purine, choline and lithium levels were assessed using 1H- and 7Li-MRS. Patients received four to six MRS scans, at baseline and weeks 2, 3, 5, 8, 10 and 12 of treatment (n = 40 scans). Patients were assessed using the Clinical Global Impression Scale (CGIS), the Young Mania Rating Scale (YRMS) and the Hamilton Depression Rating Scale (HDRS) at each MRS scan. There were no significant differences in change-from-baseline measures of CGIS, YMRS, and HDRS, brain choline/creatine ratios, and brain lithium levels over a 12-week assessment period between the choline and placebo groups or within each group. However, the choline treatment group showed a significant decrease in purine metabolite ratios from baseline (purine/n-acetyl aspartate: coef = -0.08, z = -2.17, df = 22, p = 0.030; purine/choline: coef = -0.12, z = -1.97, df = 22, p = 0.049) compared to the placebo group, controlling for brain lithium level changes. Brain lithium level change was not a significant predictor of purine ratios. The current study reports that oral choline supplementation resulted in a significant decrease in brain purine levels over a 12-week treatment period in lithium-treated patients with DSM-IV bipolar disorder, rapid-cycling type, which may be related to the anti-manic effects of adjuvant choline. This result is consistent with mitochondrial dysfunction in bipolar disorder inadequately meeting the demand for increased ATP production as exogenous oral choline administration increases membrane phospholipid synthesis.

Association of Severe Traumatic Brain Injury Patient Outcomes With Duration of Cerebrovascular Autoregulation Impairment Events.

PubMed

Preiksaitis, Aidanas; Krakauskaite, Solventa; Petkus, Vytautas; Rocka, Saulius; Chomskis, Romanas; Dagi, Teodoro Forcht; Ragauskas, Arminas

2016-07-01

Cerebrovascular autoregulation (CA) is an important hemodynamic mechanism that protects the brain against inappropriate fluctuations in cerebral blood flow in the face of changing cerebral perfusion pressure. Temporal CA failure is associated with worse outcomes in various acute neurological diseases. An integrative approach is presently used according to the existing paradigm for the association of series of temporal CA impairments with the outcomes of patients with traumatic brain injury (TBI). To explore the influence of the duration of CA impairment events on severe TBI patient outcomes. Patient age was also included in the analysis of the prospectively collected clinical data. CA monitoring included 33 prospective severe TBI patients. The pressure reactivity index [PRx(t)] was continuously monitored to collect information on the dynamics of CA status and to analyze associations between the duration of the longest CA impairment event and patient outcomes. The Glasgow outcome scale and the duration of the longest CA impairment were negatively correlated. The duration of autoregulation impairment significantly correlated with worse outcomes. Multidimensional representation of Glasgow outcome scale plots showed that better outcomes were obtained for younger patients (age < 47 years) and those whose longest CA impairment event was shorter than 40 minutes if PRx(t) was above 0.7 in the CA impairment event. Unfavorable outcomes for TBI patients are more significantly associated with the duration of the single longest CA impairment episode at a high PRx(t) value, rather than with averaged PRx(t) values or the average time of all CA impairment episodes. ABP, arterial blood pressureABP(t), continuous reference arterial blood pressureCA, cerebrovascular autoregulationCBF, cerebral blood flowCPP, cerebral perfusion pressureGOS, Glasgow outcome scaleGOSHD, Glasgow outcome scale after hospital dischargeGOS6M, Glasgow outcome scale at 6 months after dischargeICP, intracranial pressureICP(t), continuously monitored intracranial pressureLCAI, longest CA impairmentoptCPP, optimal cerebral perfusion pressurePRx(t), pressure reactivity indexTBI, traumatic brain injury.

Role of character strengths in outcome after mild complicated to severe traumatic brain injury: a positive psychology study.

PubMed

Hanks, Robin A; Rapport, Lisa J; Waldron-Perrine, Brigid; Millis, Scott R

2014-11-01

To examine the effects of character strengths on psychosocial outcomes after mild complicated to severe traumatic brain injury (TBI). Prospective study with consecutive enrollment. A Midwestern rehabilitation hospital. Persons with mild complicated to severe TBI (N=65). Not applicable. Community Integration Measure, Disability Rating Scale, Modified Cumulative Illness Rating Scale, Positive and Negative Affect Schedule, Satisfaction with Life Scale, Values in Action Inventory of Strengths, and Wechsler Test of Adult Reading. Character virtues and strengths were moderately associated with subjective outcomes, such that there were fewer and less strong associations between character virtues/strengths and objective outcomes than subjective outcomes. Specifically, positive attributes were associated with greater life satisfaction and perceived community integration. Fewer and less strong associations were observed for objective well-being; however, character strengths and virtues showed unique value in predicting physical health and disability. Positive affectivity was not meaningfully related to objective outcomes, but it was significantly related to subjective outcomes. In contrast, negative affectivity was related to objective but not subjective outcomes. Given the strength of the associations between positive aspects of character or ways of perceiving the world and positive feelings about one's current life situation, treatments focused on facilitating these virtues and strengths in persons who have experienced TBI may result in better perceived outcomes and potentially subsequently lower comorbidities. Copyright © 2014 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

relationship between diffusion tensor imaging findings and cognitive outcomes following adult traumatic brain injury: A meta-analysis.

PubMed

Wallace, E J; Mathias, J L; Ward, L

2018-05-24

Cognitive impairments are common following a traumatic brain injury (TBI) and frequently result from white matter (WM) damage. This damage can be quantified using diffusion tensor imaging (DTI), which measures the directionality (fractional anisotropy: FA) and amount (mean diffusivity/apparent diffusion coefficient: MD/ADC) of water diffusion in WM, with high FA and low MD/ADC thought to indicate greater WM integrity. However, the relationship between DTI and cognitive outcomes is currently unclear. The data from 20 studies that examined the relationship between WM integrity (measured using DTI) and cognition (categorised into seven domains) following mild-severe adult TBI were meta-analysed. Overall, high FA and low MD/ADC in most brain regions was associated with better cognitive performance, with memory and attention most strongly related to DTI findings. Specifically, memory and/or attention were very strongly related to DTI findings in the corpus callosum, fornix, internal capsule, arcuate and uncinate fasciculi. However, most findings were based on single studies and therefore await replication. Larger-scale, longitudinal studies are now needed to determine the predictive utility of DTI. Copyright © 2018. Published by Elsevier Ltd.

Hemispheric Asymmetry of Human Brain Anatomical Network Revealed by Diffusion Tensor Tractography

PubMed Central

Liu, Yaou; Duan, Yunyun; Li, Kuncheng

2015-01-01

The topological architecture of the cerebral anatomical network reflects the structural organization of the human brain. Recently, topological measures based on graph theory have provided new approaches for quantifying large-scale anatomical networks. However, few studies have investigated the hemispheric asymmetries of the human brain from the perspective of the network model, and little is known about the asymmetries of the connection patterns of brain regions, which may reflect the functional integration and interaction between different regions. Here, we utilized diffusion tensor imaging to construct binary anatomical networks for 72 right-handed healthy adult subjects. We established the existence of structural connections between any pair of the 90 cortical and subcortical regions using deterministic tractography. To investigate the hemispheric asymmetries of the brain, statistical analyses were performed to reveal the brain regions with significant differences between bilateral topological properties, such as degree of connectivity, characteristic path length, and betweenness centrality. Furthermore, local structural connections were also investigated to examine the local asymmetries of some specific white matter tracts. From the perspective of both the global and local connection patterns, we identified the brain regions with hemispheric asymmetries. Combined with the previous studies, we suggested that the topological asymmetries in the anatomical network may reflect the functional lateralization of the human brain. PMID:26539535

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.

Default mode network as a potential biomarker of chemotherapy-related brain injury

PubMed Central

Kesler, Shelli R.

2014-01-01

Chronic medical conditions and/or their treatments may interact with aging to alter or even accelerate brain senescence. Adult onset cancer, for example, is a disease associated with advanced aging and emerging evidence suggests a profile of subtle but diffuse brain injury following cancer chemotherapy. Breast cancer is currently the primary model for studying these “chemobrain” effects. Given the widespread changes to brain structure and function as well as the common impairment of integrated cognitive skills observed following breast cancer chemotherapy, it is likely that large-scale brain networks are involved. Default mode network (DMN) is a strong candidate considering its preferential vulnerability to aging and sensitivity to toxicity and disease states. Additionally, chemotherapy is associated with several physiologic effects including increased inflammation and oxidative stress that are believed to elevate toxicity in the DMN. Biomarkers of DMN connectivity could aid in the development of treatments for chemotherapy-related cognitive decline. For example, certain nutritional interventions could potentially reduce the metabolic changes (e.g. amyloid beta toxicity) associated with DMN disruption. PMID:24913897

Age-related reduction of adaptive brain response during semantic integration is associated with gray matter reduction.

PubMed

Zhu, Zude; Yang, Fengjun; Li, Dongning; Zhou, Lianjun; Liu, Ying; Zhang, Ying; Chen, Xuezhi

2017-01-01

While aging is associated with increased knowledge, it is also associated with decreased semantic integration. To investigate brain activation changes during semantic integration, a sample of forty-eight 25-75 year-old adults read sentences with high cloze (HC) and low cloze (LC) probability while functional magnetic resonance imaging was conducted. Significant age-related reduction of cloze effect (LC vs. HC) was found in several regions, especially the left middle frontal gyrus (MFG) and right inferior frontal gyrus (IFG), which play an important role in semantic integration. Moreover, when accounting for global gray matter volume reduction, the age-cloze correlation in the left MFG and right IFG was absent. The results suggest that brain structural atrophy may disrupt brain response in aging brains, which then show less brain engagement in semantic integration.

A Novel Audiovisual Brain-Computer Interface and Its Application in Awareness Detection.

PubMed

Wang, Fei; He, Yanbin; Pan, Jiahui; Xie, Qiuyou; Yu, Ronghao; Zhang, Rui; Li, Yuanqing

2015-06-30

Currently, detecting awareness in patients with disorders of consciousness (DOC) is a challenging task, which is commonly addressed through behavioral observation scales such as the JFK Coma Recovery Scale-Revised. Brain-computer interfaces (BCIs) provide an alternative approach to detect awareness in patients with DOC. However, these patients have a much lower capability of using BCIs compared to healthy individuals. This study proposed a novel BCI using temporally, spatially, and semantically congruent audiovisual stimuli involving numbers (i.e., visual and spoken numbers). Subjects were instructed to selectively attend to the target stimuli cued by instruction. Ten healthy subjects first participated in the experiment to evaluate the system. The results indicated that the audiovisual BCI system outperformed auditory-only and visual-only systems. Through event-related potential analysis, we observed audiovisual integration effects for target stimuli, which enhanced the discriminability between brain responses for target and nontarget stimuli and thus improved the performance of the audiovisual BCI. This system was then applied to detect the awareness of seven DOC patients, five of whom exhibited command following as well as number recognition. Thus, this audiovisual BCI system may be used as a supportive bedside tool for awareness detection in patients with DOC.

A Novel Audiovisual Brain-Computer Interface and Its Application in Awareness Detection

PubMed Central

Wang, Fei; He, Yanbin; Pan, Jiahui; Xie, Qiuyou; Yu, Ronghao; Zhang, Rui; Li, Yuanqing

2015-01-01

Currently, detecting awareness in patients with disorders of consciousness (DOC) is a challenging task, which is commonly addressed through behavioral observation scales such as the JFK Coma Recovery Scale-Revised. Brain-computer interfaces (BCIs) provide an alternative approach to detect awareness in patients with DOC. However, these patients have a much lower capability of using BCIs compared to healthy individuals. This study proposed a novel BCI using temporally, spatially, and semantically congruent audiovisual stimuli involving numbers (i.e., visual and spoken numbers). Subjects were instructed to selectively attend to the target stimuli cued by instruction. Ten healthy subjects first participated in the experiment to evaluate the system. The results indicated that the audiovisual BCI system outperformed auditory-only and visual-only systems. Through event-related potential analysis, we observed audiovisual integration effects for target stimuli, which enhanced the discriminability between brain responses for target and nontarget stimuli and thus improved the performance of the audiovisual BCI. This system was then applied to detect the awareness of seven DOC patients, five of whom exhibited command following as well as number recognition. Thus, this audiovisual BCI system may be used as a supportive bedside tool for awareness detection in patients with DOC. PMID:26123281

Synaptic Scaling Enables Dynamically Distinct Short- and Long-Term Memory Formation

PubMed Central

Tetzlaff, Christian; Kolodziejski, Christoph; Timme, Marc; Tsodyks, Misha; Wörgötter, Florentin

2013-01-01

Memory storage in the brain relies on mechanisms acting on time scales from minutes, for long-term synaptic potentiation, to days, for memory consolidation. During such processes, neural circuits distinguish synapses relevant for forming a long-term storage, which are consolidated, from synapses of short-term storage, which fade. How time scale integration and synaptic differentiation is simultaneously achieved remains unclear. Here we show that synaptic scaling – a slow process usually associated with the maintenance of activity homeostasis – combined with synaptic plasticity may simultaneously achieve both, thereby providing a natural separation of short- from long-term storage. The interaction between plasticity and scaling provides also an explanation for an established paradox where memory consolidation critically depends on the exact order of learning and recall. These results indicate that scaling may be fundamental for stabilizing memories, providing a dynamic link between early and late memory formation processes. PMID:24204240

Synaptic scaling enables dynamically distinct short- and long-term memory formation.

PubMed

Tetzlaff, Christian; Kolodziejski, Christoph; Timme, Marc; Tsodyks, Misha; Wörgötter, Florentin

2013-10-01

Memory storage in the brain relies on mechanisms acting on time scales from minutes, for long-term synaptic potentiation, to days, for memory consolidation. During such processes, neural circuits distinguish synapses relevant for forming a long-term storage, which are consolidated, from synapses of short-term storage, which fade. How time scale integration and synaptic differentiation is simultaneously achieved remains unclear. Here we show that synaptic scaling - a slow process usually associated with the maintenance of activity homeostasis - combined with synaptic plasticity may simultaneously achieve both, thereby providing a natural separation of short- from long-term storage. The interaction between plasticity and scaling provides also an explanation for an established paradox where memory consolidation critically depends on the exact order of learning and recall. These results indicate that scaling may be fundamental for stabilizing memories, providing a dynamic link between early and late memory formation processes.

An integrated modelling framework for neural circuits with multiple neuromodulators.

PubMed

Joshi, Alok; Youssofzadeh, Vahab; Vemana, Vinith; McGinnity, T M; Prasad, Girijesh; Wong-Lin, KongFatt

2017-01-01

Neuromodulators are endogenous neurochemicals that regulate biophysical and biochemical processes, which control brain function and behaviour, and are often the targets of neuropharmacological drugs. Neuromodulator effects are generally complex partly owing to the involvement of broad innervation, co-release of neuromodulators, complex intra- and extrasynaptic mechanism, existence of multiple receptor subtypes and high interconnectivity within the brain. In this work, we propose an efficient yet sufficiently realistic computational neural modelling framework to study some of these complex behaviours. Specifically, we propose a novel dynamical neural circuit model that integrates the effective neuromodulator-induced currents based on various experimental data (e.g. electrophysiology, neuropharmacology and voltammetry). The model can incorporate multiple interacting brain regions, including neuromodulator sources, simulate efficiently and easily extendable to large-scale brain models, e.g. for neuroimaging purposes. As an example, we model a network of mutually interacting neural populations in the lateral hypothalamus, dorsal raphe nucleus and locus coeruleus, which are major sources of neuromodulator orexin/hypocretin, serotonin and norepinephrine/noradrenaline, respectively, and which play significant roles in regulating many physiological functions. We demonstrate that such a model can provide predictions of systemic drug effects of the popular antidepressants (e.g. reuptake inhibitors), neuromodulator antagonists or their combinations. Finally, we developed user-friendly graphical user interface software for model simulation and visualization for both fundamental sciences and pharmacological studies. © 2017 The Authors.

An integrated modelling framework for neural circuits with multiple neuromodulators

PubMed Central

Vemana, Vinith

2017-01-01

Neuromodulators are endogenous neurochemicals that regulate biophysical and biochemical processes, which control brain function and behaviour, and are often the targets of neuropharmacological drugs. Neuromodulator effects are generally complex partly owing to the involvement of broad innervation, co-release of neuromodulators, complex intra- and extrasynaptic mechanism, existence of multiple receptor subtypes and high interconnectivity within the brain. In this work, we propose an efficient yet sufficiently realistic computational neural modelling framework to study some of these complex behaviours. Specifically, we propose a novel dynamical neural circuit model that integrates the effective neuromodulator-induced currents based on various experimental data (e.g. electrophysiology, neuropharmacology and voltammetry). The model can incorporate multiple interacting brain regions, including neuromodulator sources, simulate efficiently and easily extendable to large-scale brain models, e.g. for neuroimaging purposes. As an example, we model a network of mutually interacting neural populations in the lateral hypothalamus, dorsal raphe nucleus and locus coeruleus, which are major sources of neuromodulator orexin/hypocretin, serotonin and norepinephrine/noradrenaline, respectively, and which play significant roles in regulating many physiological functions. We demonstrate that such a model can provide predictions of systemic drug effects of the popular antidepressants (e.g. reuptake inhibitors), neuromodulator antagonists or their combinations. Finally, we developed user-friendly graphical user interface software for model simulation and visualization for both fundamental sciences and pharmacological studies. PMID:28100828

Through the Immune Looking Glass: A Model for Brain Memory Strategies

PubMed Central

Sánchez-Ramón, Silvia; Faure, Florence

2016-01-01

The immune system (IS) and the central nervous system (CNS) are complex cognitive networks involved in defining the identity (self) of the individual through recognition and memory processes that enable one to anticipate responses to stimuli. Brain memory has traditionally been classified as either implicit or explicit on psychological and anatomical grounds, with reminiscences of the evolutionarily-based innate-adaptive IS responses. Beyond the multineuronal networks of the CNS, we propose a theoretical model of brain memory integrating the CNS as a whole. This is achieved by analogical reasoning between the operational rules of recognition and memory processes in both systems, coupled to an evolutionary analysis. In this new model, the hippocampus is no longer specifically ascribed to explicit memory but rather it both becomes part of the innate (implicit) memory system and tightly controls the explicit memory system. Alike the antigen presenting cells for the IS, the hippocampus would integrate transient and pseudo-specific (i.e., danger-fear) memories and would drive the formation of long-term and highly specific or explicit memories (i.e., the taste of the Proust’s madeleine cake) by the more complex and recent, evolutionarily speaking, neocortex. Experimental and clinical evidence is provided to support the model. We believe that the singularity of this model’s approximation could help to gain a better understanding of the mechanisms operating in brain memory strategies from a large-scale network perspective. PMID:26869886

A mesoscale connectome of the mouse brain

PubMed Central

Oh, Seung Wook; Harris, Julie A.; Ng, Lydia; Winslow, Brent; Cain, Nicholas; Mihalas, Stefan; Wang, Quanxin; Lau, Chris; Kuan, Leonard; Henry, Alex M.; Mortrud, Marty T.; Ouellette, Benjamin; Nguyen, Thuc Nghi; Sorensen, Staci A.; Slaughterbeck, Clifford R.; Wakeman, Wayne; Li, Yang; Feng, David; Ho, Anh; Nicholas, Eric; Hirokawa, Karla E.; Bohn, Phillip; Joines, Kevin M.; Peng, Hanchuan; Hawrylycz, Michael J.; Phillips, John W.; Hohmann, John G.; Wohnoutka, Paul; Gerfen, Charles R.; Koch, Christof; Bernard, Amy; Dang, Chinh; Jones, Allan R.; Zeng, Hongkui

2016-01-01

Comprehensive knowledge of the brain’s wiring diagram is fundamental for understanding how the nervous system processes information at both local and global scales. However, with the singular exception of the C. elegans microscale connectome, there are no complete connectivity data sets in other species. Here we report a brain-wide, cellular-level, mesoscale connectome for the mouse. The Allen Mouse Brain Connectivity Atlas uses enhanced green fluorescent protein (EGFP)-expressing adeno-associated viral vectors to trace axonal projections from defined regions and cell types, and high-throughput serial two-photon tomography to image the EGFP-labelled axons throughout the brain. This systematic and standardized approach allows spatial registration of individual experiments into a common three dimensional (3D) reference space, resulting in a whole-brain connectivity matrix. A computational model yields insights into connectional strength distribution, symmetry and other network properties. Virtual tractography illustrates 3D topography among interconnected regions. Cortico-thalamic pathway analysis demonstrates segregation and integration of parallel pathways. The Allen Mouse Brain Connectivity Atlas is a freely available, foundational resource for structural and functional investigations into the neural circuits that support behavioural and cognitive processes in health and disease. PMID:24695228

The evolution of self-control

PubMed Central

MacLean, Evan L.; Hare, Brian; Nunn, Charles L.; Addessi, Elsa; Amici, Federica; Anderson, Rindy C.; Aureli, Filippo; Baker, Joseph M.; Bania, Amanda E.; Barnard, Allison M.; Boogert, Neeltje J.; Brannon, Elizabeth M.; Bray, Emily E.; Bray, Joel; Brent, Lauren J. N.; Burkart, Judith M.; Call, Josep; Cantlon, Jessica F.; Cheke, Lucy G.; Clayton, Nicola S.; Delgado, Mikel M.; DiVincenti, Louis J.; Fujita, Kazuo; Herrmann, Esther; Hiramatsu, Chihiro; Jacobs, Lucia F.; Jordan, Kerry E.; Laude, Jennifer R.; Leimgruber, Kristin L.; Messer, Emily J. E.; de A. Moura, Antonio C.; Ostojić, Ljerka; Picard, Alejandra; Platt, Michael L.; Plotnik, Joshua M.; Range, Friederike; Reader, Simon M.; Reddy, Rachna B.; Sandel, Aaron A.; Santos, Laurie R.; Schumann, Katrin; Seed, Amanda M.; Sewall, Kendra B.; Shaw, Rachael C.; Slocombe, Katie E.; Su, Yanjie; Takimoto, Ayaka; Tan, Jingzhi; Tao, Ruoting; van Schaik, Carel P.; Virányi, Zsófia; Visalberghi, Elisabetta; Wade, Jordan C.; Watanabe, Arii; Widness, Jane; Young, Julie K.; Zentall, Thomas R.; Zhao, Yini

2014-01-01

Cognition presents evolutionary research with one of its greatest challenges. Cognitive evolution has been explained at the proximate level by shifts in absolute and relative brain volume and at the ultimate level by differences in social and dietary complexity. However, no study has integrated the experimental and phylogenetic approach at the scale required to rigorously test these explanations. Instead, previous research has largely relied on various measures of brain size as proxies for cognitive abilities. We experimentally evaluated these major evolutionary explanations by quantitatively comparing the cognitive performance of 567 individuals representing 36 species on two problem-solving tasks measuring self-control. Phylogenetic analysis revealed that absolute brain volume best predicted performance across species and accounted for considerably more variance than brain volume controlling for body mass. This result corroborates recent advances in evolutionary neurobiology and illustrates the cognitive consequences of cortical reorganization through increases in brain volume. Within primates, dietary breadth but not social group size was a strong predictor of species differences in self-control. Our results implicate robust evolutionary relationships between dietary breadth, absolute brain volume, and self-control. These findings provide a significant first step toward quantifying the primate cognitive phenome and explaining the process of cognitive evolution. PMID:24753565

Enhancing the Temporal Complexity of Distributed Brain Networks with Patterned Cerebellar Stimulation

PubMed Central

Farzan, Faranak; Pascual-Leone, Alvaro; Schmahmann, Jeremy D.; Halko, Mark

2016-01-01

Growing evidence suggests that sensory, motor, cognitive and affective processes map onto specific, distributed neural networks. Cerebellar subregions are part of these networks, but how the cerebellum is involved in this wide range of brain functions remains poorly understood. It is postulated that the cerebellum contributes a basic role in brain functions, helping to shape the complexity of brain temporal dynamics. We therefore hypothesized that stimulating cerebellar nodes integrated in different networks should have the same impact on the temporal complexity of cortical signals. In healthy humans, we applied intermittent theta burst stimulation (iTBS) to the vermis lobule VII or right lateral cerebellar Crus I/II, subregions that prominently couple to the dorsal-attention/fronto-parietal and default-mode networks, respectively. Cerebellar iTBS increased the complexity of brain signals across multiple time scales in a network-specific manner identified through electroencephalography (EEG). We also demonstrated a region-specific shift in power of cortical oscillations towards higher frequencies consistent with the natural frequencies of targeted cortical areas. Our findings provide a novel mechanism and evidence by which the cerebellum contributes to multiple brain functions: specific cerebellar subregions control the temporal dynamics of the networks they are engaged in. PMID:27009405

Videogame-based group therapy to improve self-awareness and social skills after traumatic brain injury.

PubMed

Llorens, Roberto; Noé, Enrique; Ferri, Joan; Alcañiz, Mariano

2015-04-11

This study determines the feasibility of different approaches to integrative videogame-based group therapy for improving self-awareness, social skills, and behaviors among traumatic brain injury (TBI) victims and retrieves participant feedback. Forty-two adult TBI survivors were included in a longitudinal study with a pre- and post-assessments. The experimental intervention involved weekly one-hour sessions conducted over six months. Participants were assessed using the Self-Awareness Deficits Interview (SADI), Patient Competency Rating Scale (PCRS), the Social Skills Scale (SSS), the Frontal Systems Behavior Scale (FrSBe), the System Usability Scale (SUS). Pearson's chi-squared test (χ (2)) was applied to determine the percentage of participants who had changed their clinical classification in these tests. Feedback of the intervention was collected through the Intrinsic Motivation Inventory (IMI). SADI results showed an improvement in participant perceptions of deficits (χ (2) = 5.25, p < 0.05), of their implications (χ (2) = 4.71, p < 0.05), and of long-term planning (χ (2) = 7.86, p < 0.01). PCRS results confirm these findings (χ (2) = 5.79, p < 0.05). SSS results were also positive with respect to social skills outcomes (χ (2) = 17.52, p < 0.01), and FrSBe results showed behavioral improvements (χ (2) = 34.12, p < 0.01). Participants deemed the system accessible (80.43 ± 8.01 out of 100) and regarded the intervention as interesting and useful (5.74 ± 0.69 out of 7). Integrative videogame-based group therapy can improve self-awareness, social skills, and behaviors among individuals with chronic TBI, and the approach is considered effective and motivating.

A Hybrid CMOS-Memristor Neuromorphic Synapse.

PubMed

Azghadi, Mostafa Rahimi; Linares-Barranco, Bernabe; Abbott, Derek; Leong, Philip H W

2017-04-01

Although data processing technology continues to advance at an astonishing rate, computers with brain-like processing capabilities still elude us. It is envisioned that such computers may be achieved by the fusion of neuroscience and nano-electronics to realize a brain-inspired platform. This paper proposes a high-performance nano-scale Complementary Metal Oxide Semiconductor (CMOS)-memristive circuit, which mimics a number of essential learning properties of biological synapses. The proposed synaptic circuit that is composed of memristors and CMOS transistors, alters its memristance in response to timing differences among its pre- and post-synaptic action potentials, giving rise to a family of Spike Timing Dependent Plasticity (STDP). The presented design advances preceding memristive synapse designs with regards to the ability to replicate essential behaviours characterised in a number of electrophysiological experiments performed in the animal brain, which involve higher order spike interactions. Furthermore, the proposed hybrid device CMOS area is estimated as [Formula: see text] in a [Formula: see text] process-this represents a factor of ten reduction in area with respect to prior CMOS art. The new design is integrated with silicon neurons in a crossbar array structure amenable to large-scale neuromorphic architectures and may pave the way for future neuromorphic systems with spike timing-dependent learning features. These systems are emerging for deployment in various applications ranging from basic neuroscience research, to pattern recognition, to Brain-Machine-Interfaces.

Cerebral energy metabolism and the brain's functional network architecture: an integrative review.

PubMed

Lord, Louis-David; Expert, Paul; Huckins, Jeremy F; Turkheimer, Federico E

2013-09-01

Recent functional magnetic resonance imaging (fMRI) studies have emphasized the contributions of synchronized activity in distributed brain networks to cognitive processes in both health and disease. The brain's 'functional connectivity' is typically estimated from correlations in the activity time series of anatomically remote areas, and postulated to reflect information flow between neuronal populations. Although the topological properties of functional brain networks have been studied extensively, considerably less is known regarding the neurophysiological and biochemical factors underlying the temporal coordination of large neuronal ensembles. In this review, we highlight the critical contributions of high-frequency electrical oscillations in the γ-band (30 to 100 Hz) to the emergence of functional brain networks. After describing the neurobiological substrates of γ-band dynamics, we specifically discuss the elevated energy requirements of high-frequency neural oscillations, which represent a mechanistic link between the functional connectivity of brain regions and their respective metabolic demands. Experimental evidence is presented for the high oxygen and glucose consumption, and strong mitochondrial performance required to support rhythmic cortical activity in the γ-band. Finally, the implications of mitochondrial impairments and deficits in glucose metabolism for cognition and behavior are discussed in the context of neuropsychiatric and neurodegenerative syndromes characterized by large-scale changes in the organization of functional brain networks.

Automated voxel classification used with atlas-guided diffuse optical tomography for assessment of functional brain networks in young and older adults.

PubMed

Li, Lin; Cazzell, Mary; Babawale, Olajide; Liu, Hanli

2016-10-01

Atlas-guided diffuse optical tomography (atlas-DOT) is a computational means to image changes in cortical hemodynamic signals during human brain activities. Graph theory analysis (GTA) is a network analysis tool commonly used in functional neuroimaging to study brain networks. Atlas-DOT has not been analyzed with GTA to derive large-scale brain connectivity/networks based on near-infrared spectroscopy (NIRS) measurements. We introduced an automated voxel classification (AVC) method that facilitated the use of GTA with atlas-DOT images by grouping unequal-sized finite element voxels into anatomically meaningful regions of interest within the human brain. The overall approach included volume segmentation, AVC, and cross-correlation. To demonstrate the usefulness of AVC, we applied reproducibility analysis to resting-state functional connectivity measurements conducted from 15 young adults in a two-week period. We also quantified and compared changes in several brain network metrics between young and older adults, which were in agreement with those reported by a previous positron emission tomography study. Overall, this study demonstrated that AVC is a useful means for facilitating integration or combination of atlas-DOT with GTA and thus for quantifying NIRS-based, voxel-wise resting-state functional brain networks.

Smart integrated microsystems: the energy efficiency challenge (Conference Presentation) (Plenary Presentation)

NASA Astrophysics Data System (ADS)

Benini, Luca

2017-06-01

The "internet of everything" envisions trillions of connected objects loaded with high-bandwidth sensors requiring massive amounts of local signal processing, fusion, pattern extraction and classification. From the computational viewpoint, the challenge is formidable and can be addressed only by pushing computing fabrics toward massive parallelism and brain-like energy efficiency levels. CMOS technology can still take us a long way toward this goal, but technology scaling is losing steam. Energy efficiency improvement will increasingly hinge on architecture, circuits, design techniques such as heterogeneous 3D integration, mixed-signal preprocessing, event-based approximate computing and non-Von-Neumann architectures for scalable acceleration.

Transforming Research and Clinical Knowledge in Traumatic Brain Injury

DTIC Science & Technology

2016-12-01

Szuflita, N., Orman, J., and Schwab, K. (2010). Advancing integrated research in psychological health and traumatic brain injury: common data ele- ments...Szuflita N, Orman J, et al. Advancing Integrated Research in Psychological Health and Traumatic Brain Injury: Common Data Elements. Arch Phys Med Rehabil...R, Gleason T, et al. Advancing integrated research in psychological health and traumatic brain injury: common data elements. Arch Phys Med Rehabil

Effect of ischemic cerebral volume changes on behavior.

PubMed

Lyden, P D; Lonzo, L M; Nunez, S Y; Dockstader, T; Mathieu-Costello, O; Zivin, J A

1997-08-01

Ischemia causes long-term effects on brain volume and neurologic function but the relationship between the two is poorly characterized. We studied the relationships between brain volume and three measures of rodent behavior after cerebral ischemia was induced by injecting several thousand microspheres into the internal carotid arteries of rats. Forty eight hours later, each subject was rated using a global neurologic rating scale. Several weeks later, the subjects were tested for open field activity and visual spatial learning. Post-mortem we measured the volume of the cerebral hemispheres and estimated the volume densities of cortex, white matter, hippocampus, basal ganglia, thalamus, ventricle, and visible infarction. Ischemia caused significant impairment, as measured by the global rating scale; the probability of an abnormal rating was correlated with the number of microspheres trapped in the brains. Visual spatial learning was significantly impaired by ischemia, but this deficit was independent of the count of microspheres, whether the subject was abnormal at 48 h, and whether the left or right hemisphere was embolized. Cerebral hemisphere volume was reduced from 430 mm3 to 376 mm3 (P < 0.05). The cortex was reduced from 22 to 19% of cerebrum (P < 0.05) and the white matter compartment was reduced to similar degree. The lesion volume was 6% of cerebrum, comparable to that seen with other ischemia methods. The global outcome rating was significantly related to total cerebral volume, but not to volume changes in any single compartment. On the other hand, visual spatial learning was significantly influenced by volume changes in the cortex and white matter, but not by the topography of the visible infarctions. Open field activity was not altered by infarction. Our data suggests that the total volume of brain tissue lost to infarction may partially determine global neurological rating independently of the topography of the volume loss. Integrative functions such as learning may depend more on the integrity of specific compartments and less on the total volume of intact brain. The volume of visible cystic infarction was not related to long term behavioral outcome. These results should be confirmed using another method of inducing ischemia.

77 FR 297 - Center for Scientific Review; Notice of Closed Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2012-01-04

... of Committee: Brain Disorders and Clinical Neuroscience Integrated Review Group, Developmental Brain...- 9866, [email protected] . Name of Committee: Brain Disorders and Clinical Neuroscience Integrated...

Speech networks at rest and in action: interactions between functional brain networks controlling speech production.

PubMed

Simonyan, Kristina; Fuertinger, Stefan

2015-04-01

Speech production is one of the most complex human behaviors. Although brain activation during speaking has been well investigated, our understanding of interactions between the brain regions and neural networks remains scarce. We combined seed-based interregional correlation analysis with graph theoretical analysis of functional MRI data during the resting state and sentence production in healthy subjects to investigate the interface and topology of functional networks originating from the key brain regions controlling speech, i.e., the laryngeal/orofacial motor cortex, inferior frontal and superior temporal gyri, supplementary motor area, cingulate cortex, putamen, and thalamus. During both resting and speaking, the interactions between these networks were bilaterally distributed and centered on the sensorimotor brain regions. However, speech production preferentially recruited the inferior parietal lobule (IPL) and cerebellum into the large-scale network, suggesting the importance of these regions in facilitation of the transition from the resting state to speaking. Furthermore, the cerebellum (lobule VI) was the most prominent region showing functional influences on speech-network integration and segregation. Although networks were bilaterally distributed, interregional connectivity during speaking was stronger in the left vs. right hemisphere, which may have underlined a more homogeneous overlap between the examined networks in the left hemisphere. Among these, the laryngeal motor cortex (LMC) established a core network that fully overlapped with all other speech-related networks, determining the extent of network interactions. Our data demonstrate complex interactions of large-scale brain networks controlling speech production and point to the critical role of the LMC, IPL, and cerebellum in the formation of speech production network. Copyright © 2015 the American Physiological Society.

Multilayer network modeling of integrated biological systems. Comment on "Network science of biological systems at different scales: A review" by Gosak et al.

NASA Astrophysics Data System (ADS)

De Domenico, Manlio

2018-03-01

Biological systems, from a cell to the human brain, are inherently complex. A powerful representation of such systems, described by an intricate web of relationships across multiple scales, is provided by complex networks. Recently, several studies are highlighting how simple networks - obtained by aggregating or neglecting temporal or categorical description of biological data - are not able to account for the richness of information characterizing biological systems. More complex models, namely multilayer networks, are needed to account for interdependencies, often varying across time, of biological interacting units within a cell, a tissue or parts of an organism.

How a (sub)Cellular Coincidence Detection Mechanism Featuring Layer-5 Pyramidal Cells May Help Produce Various Visual Phenomena.

PubMed

Bachmann, Talis

2015-01-01

Perceptual phenomena such as spatio-temporal illusions and masking are typically explained by psychological (cognitive) processing theories or large-scale neural theories involving inter-areal connectivity and neural circuits comprising of hundreds or more interconnected single cells. Subcellular mechanisms are hardly used for such purpose. Here, a mechanistic theoretical view is presented on how a subcellular brain mechanism of integration of presynaptic signals that arrive at different compartments of layer-5 pyramidal neurons could explain a couple of spatiotemporal visual-phenomenal effects unfolding along very brief time intervals within the range of the sub-second temporal scale.

A model for integrating elementary neural functions into delayed-response behavior.

PubMed

Gisiger, Thomas; Kerszberg, Michel

2006-04-01

It is well established that various cortical regions can implement a wide array of neural processes, yet the mechanisms which integrate these processes into behavior-producing, brain-scale activity remain elusive. We propose that an important role in this respect might be played by executive structures controlling the traffic of information between the cortical regions involved. To illustrate this hypothesis, we present a neural network model comprising a set of interconnected structures harboring stimulus-related activity (visual representation, working memory, and planning), and a group of executive units with task-related activity patterns that manage the information flowing between them. The resulting dynamics allows the network to perform the dual task of either retaining an image during a delay (delayed-matching to sample task), or recalling from this image another one that has been associated with it during training (delayed-pair association task). The model reproduces behavioral and electrophysiological data gathered on the inferior temporal and prefrontal cortices of primates performing these same tasks. It also makes predictions on how neural activity coding for the recall of the image associated with the sample emerges and becomes prospective during the training phase. The network dynamics proves to be very stable against perturbations, and it exhibits signs of scale-invariant organization and cooperativity. The present network represents a possible neural implementation for active, top-down, prospective memory retrieval in primates. The model suggests that brain activity leading to performance of cognitive tasks might be organized in modular fashion, simple neural functions becoming integrated into more complex behavior by executive structures harbored in prefrontal cortex and/or basal ganglia.

Is functional integration of resting state brain networks an unspecific biomarker for working memory performance?

PubMed

Alavash, Mohsen; Doebler, Philipp; Holling, Heinz; Thiel, Christiane M; Gießing, Carsten

2015-03-01

Is there one optimal topology of functional brain networks at rest from which our cognitive performance would profit? Previous studies suggest that functional integration of resting state brain networks is an important biomarker for cognitive performance. However, it is still unknown whether higher network integration is an unspecific predictor for good cognitive performance or, alternatively, whether specific network organization during rest predicts only specific cognitive abilities. Here, we investigated the relationship between network integration at rest and cognitive performance using two tasks that measured different aspects of working memory; one task assessed visual-spatial and the other numerical working memory. Network clustering, modularity and efficiency were computed to capture network integration on different levels of network organization, and to statistically compare their correlations with the performance in each working memory test. The results revealed that each working memory aspect profits from a different resting state topology, and the tests showed significantly different correlations with each of the measures of network integration. While higher global network integration and modularity predicted significantly better performance in visual-spatial working memory, both measures showed no significant correlation with numerical working memory performance. In contrast, numerical working memory was superior in subjects with highly clustered brain networks, predominantly in the intraparietal sulcus, a core brain region of the working memory network. Our findings suggest that a specific balance between local and global functional integration of resting state brain networks facilitates special aspects of cognitive performance. In the context of working memory, while visual-spatial performance is facilitated by globally integrated functional resting state brain networks, numerical working memory profits from increased capacities for local processing, especially in brain regions involved in working memory performance. Copyright © 2014 Elsevier Inc. All rights reserved.

Novel Intrinsic Ignition Method Measuring Local-Global Integration Characterizes Wakefulness and Deep Sleep

PubMed Central

Tagliazucchi, Enzo; Sanjuán, Ana

2017-01-01

Abstract A precise definition of a brain state has proven elusive. Here, we introduce the novel local-global concept of intrinsic ignition characterizing the dynamical complexity of different brain states. Naturally occurring intrinsic ignition events reflect the capability of a given brain area to propagate neuronal activity to other regions, giving rise to different levels of integration. The ignitory capability of brain regions is computed by the elicited level of integration for each intrinsic ignition event in each brain region, averaged over all events. This intrinsic ignition method is shown to clearly distinguish human neuroimaging data of two fundamental brain states (wakefulness and deep sleep). Importantly, whole-brain computational modelling of this data shows that at the optimal working point is found where there is maximal variability of the intrinsic ignition across brain regions. Thus, combining whole brain models with intrinsic ignition can provide novel insights into underlying mechanisms of brain states. PMID:28966977

Novel Intrinsic Ignition Method Measuring Local-Global Integration Characterizes Wakefulness and Deep Sleep.

PubMed

Deco, Gustavo; Tagliazucchi, Enzo; Laufs, Helmut; Sanjuán, Ana; Kringelbach, Morten L

2017-01-01

A precise definition of a brain state has proven elusive. Here, we introduce the novel local-global concept of intrinsic ignition characterizing the dynamical complexity of different brain states. Naturally occurring intrinsic ignition events reflect the capability of a given brain area to propagate neuronal activity to other regions, giving rise to different levels of integration. The ignitory capability of brain regions is computed by the elicited level of integration for each intrinsic ignition event in each brain region, averaged over all events. This intrinsic ignition method is shown to clearly distinguish human neuroimaging data of two fundamental brain states (wakefulness and deep sleep). Importantly, whole-brain computational modelling of this data shows that at the optimal working point is found where there is maximal variability of the intrinsic ignition across brain regions. Thus, combining whole brain models with intrinsic ignition can provide novel insights into underlying mechanisms of brain states.

Quantitative Tractography and Volumetric MRI in Blast and Blunt Force TBI: Predictors of Neurocognitive and Behavioral Outcome

DTIC Science & Technology

2016-10-01

are related to mechanism of injury as well as white matter integrity using diffusion tensor imaging (DTI). We are also collecting and analyzing...APOE ε4] and brain-derived neurotrophic factor [BDNF]) to brain integrity , neuropsychological functioning, and neurobehavioral outcome. 15. SUBJECT...contribution of genetic factors (Apolipoprotein-E ε-4 [APOE ε4] and brain-derived neurotrophic factor [BDNF]) to brain integrity , neuropsychological

Normalization of similarity-based individual brain networks from gray matter MRI and its association with neurodevelopment in infants with intrauterine growth restriction.

PubMed

Batalle, Dafnis; Muñoz-Moreno, Emma; Figueras, Francesc; Bargallo, Nuria; Eixarch, Elisenda; Gratacos, Eduard

2013-12-01

Obtaining individual biomarkers for the prediction of altered neurological outcome is a challenge of modern medicine and neuroscience. Connectomics based on magnetic resonance imaging (MRI) stands as a good candidate to exhaustively extract information from MRI by integrating the information obtained in a few network features that can be used as individual biomarkers of neurological outcome. However, this approach typically requires the use of diffusion and/or functional MRI to extract individual brain networks, which require high acquisition times and present an extreme sensitivity to motion artifacts, critical problems when scanning fetuses and infants. Extraction of individual networks based on morphological similarity from gray matter is a new approach that benefits from the power of graph theory analysis to describe gray matter morphology as a large-scale morphological network from a typical clinical anatomic acquisition such as T1-weighted MRI. In the present paper we propose a methodology to normalize these large-scale morphological networks to a brain network with standardized size based on a parcellation scheme. The proposed methodology was applied to reconstruct individual brain networks of 63 one-year-old infants, 41 infants with intrauterine growth restriction (IUGR) and 22 controls, showing altered network features in the IUGR group, and their association with neurodevelopmental outcome at two years of age by means of ordinal regression analysis of the network features obtained with Bayley Scale for Infant and Toddler Development, third edition. Although it must be more widely assessed, this methodology stands as a good candidate for the development of biomarkers for altered neurodevelopment in the pediatric population. © 2013 Elsevier Inc. All rights reserved.

Selective Audiovisual Semantic Integration Enabled by Feature-Selective Attention.

PubMed

Li, Yuanqing; Long, Jinyi; Huang, Biao; Yu, Tianyou; Wu, Wei; Li, Peijun; Fang, Fang; Sun, Pei

2016-01-13

An audiovisual object may contain multiple semantic features, such as the gender and emotional features of the speaker. Feature-selective attention and audiovisual semantic integration are two brain functions involved in the recognition of audiovisual objects. Humans often selectively attend to one or several features while ignoring the other features of an audiovisual object. Meanwhile, the human brain integrates semantic information from the visual and auditory modalities. However, how these two brain functions correlate with each other remains to be elucidated. In this functional magnetic resonance imaging (fMRI) study, we explored the neural mechanism by which feature-selective attention modulates audiovisual semantic integration. During the fMRI experiment, the subjects were presented with visual-only, auditory-only, or audiovisual dynamical facial stimuli and performed several feature-selective attention tasks. Our results revealed that a distribution of areas, including heteromodal areas and brain areas encoding attended features, may be involved in audiovisual semantic integration. Through feature-selective attention, the human brain may selectively integrate audiovisual semantic information from attended features by enhancing functional connectivity and thus regulating information flows from heteromodal areas to brain areas encoding the attended features.

AAV-PHP.B-Mediated Global-Scale Expression in the Mouse Nervous System Enables GBA1 Gene Therapy for Wide Protection from Synucleinopathy.

PubMed

Morabito, Giuseppe; Giannelli, Serena G; Ordazzo, Gabriele; Bido, Simone; Castoldi, Valerio; Indrigo, Marzia; Cabassi, Tommaso; Cattaneo, Stefano; Luoni, Mirko; Cancellieri, Cinzia; Sessa, Alessandro; Bacigaluppi, Marco; Taverna, Stefano; Leocani, Letizia; Lanciego, José L; Broccoli, Vania

2017-12-06

The lack of technology for direct global-scale targeting of the adult mouse nervous system has hindered research on brain processing and dysfunctions. Currently, gene transfer is normally achieved by intraparenchymal viral injections, but these injections target a restricted brain area. Herein, we demonstrated that intravenous delivery of adeno-associated virus (AAV)-PHP.B viral particles permeated and diffused throughout the neural parenchyma, targeting both the central and the peripheral nervous system in a global pattern. We then established multiple procedures of viral transduction to control gene expression or inactivate gene function exclusively in the adult nervous system and assessed the underlying behavioral effects. Building on these results, we established an effective gene therapy strategy to counteract the widespread accumulation of α-synuclein deposits throughout the forebrain in a mouse model of synucleinopathy. Transduction of A53T-SCNA transgenic mice with AAV-PHP.B-GBA1 restored physiological levels of the enzyme, reduced α-synuclein pathology, and produced significant behavioral recovery. Finally, we provided evidence that AAV-PHP.B brain penetration does not lead to evident dysfunctions in blood-brain barrier integrity or permeability. Altogether, the AAV-PHP.B viral platform enables non-invasive, widespread, and long-lasting global neural expression of therapeutic genes, such as GBA1, providing an invaluable approach to treat neurodegenerative diseases with diffuse brain pathology such as synucleinopathies. Copyright © 2017 The American Society of Gene and Cell Therapy. Published by Elsevier Inc. All rights reserved.

Quantification of brain macrostates using dynamical nonstationarity of physiological time series.

PubMed

Latchoumane, Charles-Francois Vincent; Jeong, Jaeseung

2011-04-01

The brain shows complex, nonstationarity temporal dynamics, with abrupt micro- and macrostate transitions during its information processing. Detecting and characterizing these transitions in dynamical states of the brain is a critical issue in the field of neuroscience and psychiatry. In the current study, a novel method is proposed to quantify brain macrostates (e.g., sleep stages or cognitive states) from shifts of dynamical microstates or dynamical nonstationarity. A ``dynamical microstate'' is a temporal unit of the information processing in the brain with fixed dynamical parameters and specific spatial distribution. In this proposed approach, a phase-space-based dynamical dissimilarity map (DDM) is used to detect transitions between dynamically stationary microstates in the time series, and Tsallis time-dependent entropy is applied to quantify dynamical patterns of transitions in the DDM. We demonstrate that the DDM successfully detects transitions between microstates of different temporal dynamics in the simulated physiological time series against high levels of noise. Based on the assumption of nonlinear, deterministic brain dynamics, we also demonstrate that dynamical nonstationarity analysis is useful to quantify brain macrostates (sleep stages I, II, III, IV, and rapid eye movement (REM) sleep) from sleep EEGs with an overall accuracy of 77%. We suggest that dynamical nonstationarity is a useful tool to quantify macroscopic mental states (statistical integration) of the brain using dynamical transitions at the microscopic scale in physiological data.

Spectral fingerprints of large-scale cortical dynamics during ambiguous motion perception.

PubMed

Helfrich, Randolph F; Knepper, Hannah; Nolte, Guido; Sengelmann, Malte; König, Peter; Schneider, Till R; Engel, Andreas K

2016-11-01

Ambiguous stimuli have been widely used to study the neuronal correlates of consciousness. Recently, it has been suggested that conscious perception might arise from the dynamic interplay of functionally specialized but widely distributed cortical areas. While previous research mainly focused on phase coupling as a correlate of cortical communication, more recent findings indicated that additional coupling modes might coexist and possibly subserve distinct cortical functions. Here, we studied two coupling modes, namely phase and envelope coupling, which might differ in their origins, putative functions and dynamics. Therefore, we recorded 128-channel EEG while participants performed a bistable motion task and utilized state-of-the-art source-space connectivity analysis techniques to study the functional relevance of different coupling modes for cortical communication. Our results indicate that gamma-band phase coupling in extrastriate visual cortex might mediate the integration of visual tokens into a moving stimulus during ambiguous visual stimulation. Furthermore, our results suggest that long-range fronto-occipital gamma-band envelope coupling sustains the horizontal percept during ambiguous motion perception. Additionally, our results support the idea that local parieto-occipital alpha-band phase coupling controls the inter-hemispheric information transfer. These findings provide correlative evidence for the notion that synchronized oscillatory brain activity reflects the processing of sensory input as well as the information integration across several spatiotemporal scales. The results indicate that distinct coupling modes are involved in different cortical computations and that the rich spatiotemporal correlation structure of the brain might constitute the functional architecture for cortical processing and specific multi-site communication. Hum Brain Mapp 37:4099-4111, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

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.

An animal-to-human scaling law for blast-induced traumatic brain injury risk assessment.

PubMed

Jean, Aurélie; Nyein, Michelle K; Zheng, James Q; Moore, David F; Joannopoulos, John D; Radovitzky, Raúl

2014-10-28

Despite recent efforts to understand blast effects on the human brain, there are still no widely accepted injury criteria for humans. Recent animal studies have resulted in important advances in the understanding of brain injury due to intense dynamic loads. However, the applicability of animal brain injury results to humans remains uncertain. Here, we use advanced computational models to derive a scaling law relating blast wave intensity to the mechanical response of brain tissue across species. Detailed simulations of blast effects on the brain are conducted for different mammals using image-based biofidelic models. The intensity of the stress waves computed for different external blast conditions is compared across species. It is found that mass scaling, which successfully estimates blast tolerance of the thorax, fails to capture the brain mechanical response to blast across mammals. Instead, we show that an appropriate scaling variable must account for the mass of protective tissues relative to the brain, as well as their acoustic impedance. Peak stresses transmitted to the brain tissue by the blast are then shown to be a power function of the scaling parameter for a range of blast conditions relevant to TBI. In particular, it is found that human brain vulnerability to blast is higher than for any other mammalian species, which is in distinct contrast to previously proposed scaling laws based on body or brain mass. An application of the scaling law to recent experiments on rabbits furnishes the first physics-based injury estimate for blast-induced TBI in humans.

Answering Schrödinger's question: A free-energy formulation

NASA Astrophysics Data System (ADS)

Ramstead, Maxwell James Désormeau; Badcock, Paul Benjamin; Friston, Karl John

2018-03-01

The free-energy principle (FEP) is a formal model of neuronal processes that is widely recognised in neuroscience as a unifying theory of the brain and biobehaviour. More recently, however, it has been extended beyond the brain to explain the dynamics of living systems, and their unique capacity to avoid decay. The aim of this review is to synthesise these advances with a meta-theoretical ontology of biological systems called variational neuroethology, which integrates the FEP with Tinbergen's four research questions to explain biological systems across spatial and temporal scales. We exemplify this framework by applying it to Homo sapiens, before translating variational neuroethology into a systematic research heuristic that supplies the biological, cognitive, and social sciences with a computationally tractable guide to discovery.

Direction of information flow in large-scale resting-state networks is frequency-dependent.

PubMed

Hillebrand, Arjan; Tewarie, Prejaas; van Dellen, Edwin; Yu, Meichen; Carbo, Ellen W S; Douw, Linda; Gouw, Alida A; van Straaten, Elisabeth C W; Stam, Cornelis J

2016-04-05

Normal brain function requires interactions between spatially separated, and functionally specialized, macroscopic regions, yet the directionality of these interactions in large-scale functional networks is unknown. Magnetoencephalography was used to determine the directionality of these interactions, where directionality was inferred from time series of beamformer-reconstructed estimates of neuronal activation, using a recently proposed measure of phase transfer entropy. We observed well-organized posterior-to-anterior patterns of information flow in the higher-frequency bands (alpha1, alpha2, and beta band), dominated by regions in the visual cortex and posterior default mode network. Opposite patterns of anterior-to-posterior flow were found in the theta band, involving mainly regions in the frontal lobe that were sending information to a more distributed network. Many strong information senders in the theta band were also frequent receivers in the alpha2 band, and vice versa. Our results provide evidence that large-scale resting-state patterns of information flow in the human brain form frequency-dependent reentry loops that are dominated by flow from parieto-occipital cortex to integrative frontal areas in the higher-frequency bands, which is mirrored by a theta band anterior-to-posterior flow.

Scaling theory for information networks.

PubMed

Moses, Melanie E; Forrest, Stephanie; Davis, Alan L; Lodder, Mike A; Brown, James H

2008-12-06

Networks distribute energy, materials and information to the components of a variety of natural and human-engineered systems, including organisms, brains, the Internet and microprocessors. Distribution networks enable the integrated and coordinated functioning of these systems, and they also constrain their design. The similar hierarchical branching networks observed in organisms and microprocessors are striking, given that the structure of organisms has evolved via natural selection, while microprocessors are designed by engineers. Metabolic scaling theory (MST) shows that the rate at which networks deliver energy to an organism is proportional to its mass raised to the 3/4 power. We show that computational systems are also characterized by nonlinear network scaling and use MST principles to characterize how information networks scale, focusing on how MST predicts properties of clock distribution networks in microprocessors. The MST equations are modified to account for variation in the size and density of transistors and terminal wires in microprocessors. Based on the scaling of the clock distribution network, we predict a set of trade-offs and performance properties that scale with chip size and the number of transistors. However, there are systematic deviations between power requirements on microprocessors and predictions derived directly from MST. These deviations are addressed by augmenting the model to account for decentralized flow in some microprocessor networks (e.g. in logic networks). More generally, we hypothesize a set of constraints between the size, power and performance of networked information systems including transistors on chips, hosts on the Internet and neurons in the brain.

Intra-opeartive OCT imaging and sensing devices for clinical translation (Conference Presentation)

NASA Astrophysics Data System (ADS)

Chen, Yu

2017-02-01

Stereotactic procedures that require insertion of needle-based instruments into the brain serve important roles in a variety of neurosurgical interventions, such as biopsy, catheterization, and electrode placement. A fundamental limitation of these stereotactic procedures is that they are blind procedures in that the operator does not have real-time feedback as to what lies immediately ahead of the advancing needle. Therefore, there is a great clinical need to navigate the instrument safely and accurately to the targets. Towards that end, we developed a forwarding-imaging needle-type optical coherence tomography (OCT) probe for avoiding the hemorrhage and guiding neurosurgical interventions. The needle probe has a thin diameter of 0.7 mm. The feasibility of vessel detection and neurosurgical guidance were demonstrated on sheep brain in vivo and human brain ex vivo. In addition, we further reduced the probe size to 0.3 mm using an optical Doppler sensing (ODS) fiber probe that can integrate with microelectrode recording (MER) to detect the blood vessels lying ahead to improve the safety of this procedure. Furthermore, to overcome the field-of-view limitation of OCT probe, we developed an MRI-compatible OCT imaging probe for neurosurgery. MRI/OCT multi-scale imaging integrates micro-resolution optical imaging with wide-field MRI imaging, and has potential to further improve the targeting accuracy.

Gorilla and Orangutan Brains Conform to the Primate Cellular Scaling Rules: Implications for Human Evolution

PubMed Central

Herculano-Houzel, Suzana; Kaas, Jon H.

2011-01-01

Gorillas and orangutans are primates at least as large as humans, but their brains amount to about one third of the size of the human brain. This discrepancy has been used as evidence that the human brain is about 3 times larger than it should be for a primate species of its body size. In contrast to the view that the human brain is special in its size, we have suggested that it is the great apes that might have evolved bodies that are unusually large, on the basis of our recent finding that the cellular composition of the human brain matches that expected for a primate brain of its size, making the human brain a linearly scaled-up primate brain in its number of cells. To investigate whether the brain of great apes also conforms to the primate cellular scaling rules identified previously, we determine the numbers of neuronal and other cells that compose the orangutan and gorilla cerebella, use these numbers to calculate the size of the brain and of the cerebral cortex expected for these species, and show that these match the sizes described in the literature. Our results suggest that the brains of great apes also scale linearly in their numbers of neurons like other primate brains, including humans. The conformity of great apes and humans to the linear cellular scaling rules that apply to other primates that diverged earlier in primate evolution indicates that prehistoric Homo species as well as other hominins must have had brains that conformed to the same scaling rules, irrespective of their body size. We then used those scaling rules and published estimated brain volumes for various hominin species to predict the numbers of neurons that composed their brains. We predict that Homo heidelbergensis and Homo neanderthalensis had brains with approximately 80 billion neurons, within the range of variation found in modern Homo sapiens. We propose that while the cellular scaling rules that apply to the primate brain have remained stable in hominin evolution (since they apply to simians, great apes and modern humans alike), the Colobinae and Pongidae lineages favored marked increases in body size rather than brain size from the common ancestor with the Homo lineage, while the Homo lineage seems to have favored a large brain instead of a large body, possibly due to the metabolic limitations to having both. PMID:21228547

Gorilla and orangutan brains conform to the primate cellular scaling rules: implications for human evolution.

PubMed

Herculano-Houzel, Suzana; Kaas, Jon H

2011-01-01

Gorillas and orangutans are primates at least as large as humans, but their brains amount to about one third of the size of the human brain. This discrepancy has been used as evidence that the human brain is about 3 times larger than it should be for a primate species of its body size. In contrast to the view that the human brain is special in its size, we have suggested that it is the great apes that might have evolved bodies that are unusually large, on the basis of our recent finding that the cellular composition of the human brain matches that expected for a primate brain of its size, making the human brain a linearly scaled-up primate brain in its number of cells. To investigate whether the brain of great apes also conforms to the primate cellular scaling rules identified previously, we determine the numbers of neuronal and other cells that compose the orangutan and gorilla cerebella, use these numbers to calculate the size of the brain and of the cerebral cortex expected for these species, and show that these match the sizes described in the literature. Our results suggest that the brains of great apes also scale linearly in their numbers of neurons like other primate brains, including humans. The conformity of great apes and humans to the linear cellular scaling rules that apply to other primates that diverged earlier in primate evolution indicates that prehistoric Homo species as well as other hominins must have had brains that conformed to the same scaling rules, irrespective of their body size. We then used those scaling rules and published estimated brain volumes for various hominin species to predict the numbers of neurons that composed their brains. We predict that Homo heidelbergensis and Homo neanderthalensis had brains with approximately 80 billion neurons, within the range of variation found in modern Homo sapiens. We propose that while the cellular scaling rules that apply to the primate brain have remained stable in hominin evolution (since they apply to simians, great apes and modern humans alike), the Colobinae and Pongidae lineages favored marked increases in body size rather than brain size from the common ancestor with the Homo lineage, while the Homo lineage seems to have favored a large brain instead of a large body, possibly due to the metabolic limitations to having both. Copyright © 2011 S. Karger AG, Basel.

Impaired development of intrinsic connectivity networks in children with medically intractable localization-related epilepsy.

PubMed

Ibrahim, George M; Morgan, Benjamin R; Lee, Wayne; Smith, Mary Lou; Donner, Elizabeth J; Wang, Frank; Beers, Craig A; Federico, Paolo; Taylor, Margot J; Doesburg, Sam M; Rutka, James T; Snead, O Carter

2014-11-01

Typical childhood development is characterized by the emergence of intrinsic connectivity networks (ICNs) by way of internetwork segregation and intranetwork integration. The impact of childhood epilepsy on the maturation of ICNs is, however, poorly understood. The developmental trajectory of ICNs in 26 children (8-17 years) with localization-related epilepsy and 28 propensity-score matched controls was evaluated using graph theoretical analysis of whole brain connectomes from resting-state functional magnetic resonance imaging (fMRI) data. Children with epilepsy demonstrated impaired development of regional hubs in nodes of the salience and default mode networks (DMN). Seed-based connectivity and hierarchical clustering analysis revealed significantly decreased intranetwork connections, and greater internetwork connectivity in children with epilepsy compared to controls. Significant interactions were identified between epilepsy duration and the expected developmental trajectory of ICNs, indicating that prolonged epilepsy may cause progressive alternations in large-scale networks throughout childhood. DMN integration was also associated with better working memory, whereas internetwork segregation was associated with higher full-scale intelligence quotient scores. Furthermore, subgroup analyses revealed the thalamus, hippocampus, and caudate were weaker hubs in children with secondarily generalized seizures, relative to other patient subgroups. Our findings underscore that epilepsy interferes with the developmental trajectory of brain networks underlying cognition, providing evidence supporting the early treatment of affected children. Copyright © 2014 Wiley Periodicals, Inc.

Decentralized Multisensory Information Integration in Neural Systems.

PubMed

Zhang, Wen-Hao; Chen, Aihua; Rasch, Malte J; Wu, Si

2016-01-13

How multiple sensory cues are integrated in neural circuitry remains a challenge. The common hypothesis is that information integration might be accomplished in a dedicated multisensory integration area receiving feedforward inputs from the modalities. However, recent experimental evidence suggests that it is not a single multisensory brain area, but rather many multisensory brain areas that are simultaneously involved in the integration of information. Why many mutually connected areas should be needed for information integration is puzzling. Here, we investigated theoretically how information integration could be achieved in a distributed fashion within a network of interconnected multisensory areas. Using biologically realistic neural network models, we developed a decentralized information integration system that comprises multiple interconnected integration areas. Studying an example of combining visual and vestibular cues to infer heading direction, we show that such a decentralized system is in good agreement with anatomical evidence and experimental observations. In particular, we show that this decentralized system can integrate information optimally. The decentralized system predicts that optimally integrated information should emerge locally from the dynamics of the communication between brain areas and sheds new light on the interpretation of the connectivity between multisensory brain areas. To extract information reliably from ambiguous environments, the brain integrates multiple sensory cues, which provide different aspects of information about the same entity of interest. Here, we propose a decentralized architecture for multisensory integration. In such a system, no processor is in the center of the network topology and information integration is achieved in a distributed manner through reciprocally connected local processors. Through studying the inference of heading direction with visual and vestibular cues, we show that the decentralized system can integrate information optimally, with the reciprocal connections between processers determining the extent of cue integration. Our model reproduces known multisensory integration behaviors observed in experiments and sheds new light on our understanding of how information is integrated in the brain. Copyright © 2016 Zhang et al.

Decentralized Multisensory Information Integration in Neural Systems

PubMed Central

Zhang, Wen-hao; Chen, Aihua

2016-01-01

How multiple sensory cues are integrated in neural circuitry remains a challenge. The common hypothesis is that information integration might be accomplished in a dedicated multisensory integration area receiving feedforward inputs from the modalities. However, recent experimental evidence suggests that it is not a single multisensory brain area, but rather many multisensory brain areas that are simultaneously involved in the integration of information. Why many mutually connected areas should be needed for information integration is puzzling. Here, we investigated theoretically how information integration could be achieved in a distributed fashion within a network of interconnected multisensory areas. Using biologically realistic neural network models, we developed a decentralized information integration system that comprises multiple interconnected integration areas. Studying an example of combining visual and vestibular cues to infer heading direction, we show that such a decentralized system is in good agreement with anatomical evidence and experimental observations. In particular, we show that this decentralized system can integrate information optimally. The decentralized system predicts that optimally integrated information should emerge locally from the dynamics of the communication between brain areas and sheds new light on the interpretation of the connectivity between multisensory brain areas. SIGNIFICANCE STATEMENT To extract information reliably from ambiguous environments, the brain integrates multiple sensory cues, which provide different aspects of information about the same entity of interest. Here, we propose a decentralized architecture for multisensory integration. In such a system, no processor is in the center of the network topology and information integration is achieved in a distributed manner through reciprocally connected local processors. Through studying the inference of heading direction with visual and vestibular cues, we show that the decentralized system can integrate information optimally, with the reciprocal connections between processers determining the extent of cue integration. Our model reproduces known multisensory integration behaviors observed in experiments and sheds new light on our understanding of how information is integrated in the brain. PMID:26758843

The effect of souvenaid on functional brain network organisation in patients with mild Alzheimer's disease: a randomised controlled study.

PubMed

de Waal, Hanneke; Stam, Cornelis J; Lansbergen, Marieke M; Wieggers, Rico L; Kamphuis, Patrick J G H; Scheltens, Philip; Maestú, Fernando; van Straaten, Elisabeth C W

2014-01-01

Synaptic loss is a major hallmark of Alzheimer's disease (AD). Disturbed organisation of large-scale functional brain networks in AD might reflect synaptic loss and disrupted neuronal communication. The medical food Souvenaid, containing the specific nutrient combination Fortasyn Connect, is designed to enhance synapse formation and function and has been shown to improve memory performance in patients with mild AD in two randomised controlled trials. To explore the effect of Souvenaid compared to control product on brain activity-based networks, as a derivative of underlying synaptic function, in patients with mild AD. A 24-week randomised, controlled, double-blind, parallel-group, multi-country study. 179 drug-naïve mild AD patients who participated in the Souvenir II study. Patients were randomised 1∶1 to receive Souvenaid or an iso-caloric control product once daily for 24 weeks. In a secondary analysis of the Souvenir II study, electroencephalography (EEG) brain networks were constructed and graph theory was used to quantify complex brain structure. Local brain network connectivity (normalised clustering coefficient gamma) and global network integration (normalised characteristic path length lambda) were compared between study groups, and related to memory performance. THE NETWORK MEASURES IN THE BETA BAND WERE SIGNIFICANTLY DIFFERENT BETWEEN GROUPS: they decreased in the control group, but remained relatively unchanged in the active group. No consistent relationship was found between these network measures and memory performance. The current results suggest that Souvenaid preserves the organisation of brain networks in patients with mild AD within 24 weeks, hypothetically counteracting the progressive network disruption over time in AD. The results strengthen the hypothesis that Souvenaid affects synaptic integrity and function. Secondly, we conclude that advanced EEG analysis, using the mathematical framework of graph theory, is useful and feasible for assessing the effects of interventions. Dutch Trial Register NTR1975.

The Effect of Souvenaid on Functional Brain Network Organisation in Patients with Mild Alzheimer’s Disease: A Randomised Controlled Study

PubMed Central

de Waal, Hanneke; Stam, Cornelis J.; Lansbergen, Marieke M.; Wieggers, Rico L.; Kamphuis, Patrick J. G. H.; Scheltens, Philip; Maestú, Fernando; van Straaten, Elisabeth C. W.

2014-01-01

Background Synaptic loss is a major hallmark of Alzheimer’s disease (AD). Disturbed organisation of large-scale functional brain networks in AD might reflect synaptic loss and disrupted neuronal communication. The medical food Souvenaid, containing the specific nutrient combination Fortasyn Connect, is designed to enhance synapse formation and function and has been shown to improve memory performance in patients with mild AD in two randomised controlled trials. Objective To explore the effect of Souvenaid compared to control product on brain activity-based networks, as a derivative of underlying synaptic function, in patients with mild AD. Design A 24-week randomised, controlled, double-blind, parallel-group, multi-country study. Participants 179 drug-naïve mild AD patients who participated in the Souvenir II study. Intervention Patients were randomised 1∶1 to receive Souvenaid or an iso-caloric control product once daily for 24 weeks. Outcome In a secondary analysis of the Souvenir II study, electroencephalography (EEG) brain networks were constructed and graph theory was used to quantify complex brain structure. Local brain network connectivity (normalised clustering coefficient gamma) and global network integration (normalised characteristic path length lambda) were compared between study groups, and related to memory performance. Results The network measures in the beta band were significantly different between groups: they decreased in the control group, but remained relatively unchanged in the active group. No consistent relationship was found between these network measures and memory performance. Conclusions The current results suggest that Souvenaid preserves the organisation of brain networks in patients with mild AD within 24 weeks, hypothetically counteracting the progressive network disruption over time in AD. The results strengthen the hypothesis that Souvenaid affects synaptic integrity and function. Secondly, we conclude that advanced EEG analysis, using the mathematical framework of graph theory, is useful and feasible for assessing the effects of interventions. Trial registration Dutch Trial Register NTR1975. PMID:24475144

Regional homogeneity of the resting-state brain activity correlates with individual intelligence.

PubMed

Wang, Leiqiong; Song, Ming; Jiang, Tianzi; Zhang, Yunting; Yu, Chunshui

2011-01-25

Resting-state functional magnetic resonance imaging has confirmed that the strengths of the long distance functional connectivity between different brain areas are correlated with individual differences in intelligence. However, the association between the local connectivity within a specific brain region and intelligence during rest remains largely unknown. The aim of this study is to investigate the relationship between local connectivity and intelligence. Fifty-nine right-handed healthy adults participated in the study. The regional homogeneity (ReHo) was used to assess the strength of local connectivity. The associations between ReHo and full-scale intelligence quotient (FSIQ) scores were studied in a voxel-wise manner using partial correlation analysis controlling for age and sex. We found that the FSIQ scores were positively correlated with the ReHo values of the bilateral inferior parietal lobules, middle frontal, parahippocampal and inferior temporal gyri, the right thalamus, superior frontal and fusiform gyri, and the left superior parietal lobule. The main findings are consistent with the parieto-frontal integration theory (P-FIT) of intelligence, supporting the view that general intelligence involves multiple brain regions throughout the brain. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Brain mitochondrial bioenergetics change with rapid and prolonged shifts in aggression in the honey bee, Apis mellifera.

PubMed

Rittschof, Clare C; Vekaria, Hemendra J; Palmer, Joseph H; Sullivan, Patrick G

2018-04-25

Neuronal function demands high-level energy production, and as such, a decline in mitochondrial respiration characterizes brain injury and disease. A growing number of studies, however, link brain mitochondrial function to behavioral modulation in non-diseased contexts. In the honey bee, we show for the first time that an acute social interaction, which invokes an aggressive response, may also cause a rapid decline in brain mitochondrial bioenergetics. The degree and speed of this decline has only been previously observed in the context of brain injury. Furthermore, in the honey bee, age-related increases in aggressive tendency are associated with increased baseline brain mitochondrial respiration, as well as increased plasticity in response to metabolic fuel type in vitro Similarly, diet restriction and ketone body feeding, which commonly enhance mammalian brain mitochondrial function in vivo , cause increased aggression. Thus, even in normal behavioral contexts, brain mitochondria show a surprising degree of variation in function over both rapid and prolonged time scales, with age predicting both baseline function and plasticity in function. These results suggest that mitochondrial function is integral to modulating aggression-related neuronal signaling. We hypothesize that variation in function reflects mitochondrial calcium buffering activity, and that shifts in mitochondrial function signal to the neuronal soma to regulate gene expression and neural energetic state. Modulating brain energetic state is emerging as a critical component of the regulation of behavior in non-diseased contexts. © 2018. Published by The Company of Biologists Ltd.

Rough-Fuzzy Clustering and Unsupervised Feature Selection for Wavelet Based MR Image Segmentation

PubMed Central

Maji, Pradipta; Roy, Shaswati

2015-01-01

Image segmentation is an indispensable process in the visualization of human tissues, particularly during clinical analysis of brain magnetic resonance (MR) images. For many human experts, manual segmentation is a difficult and time consuming task, which makes an automated brain MR image segmentation method desirable. In this regard, this paper presents a new segmentation method for brain MR images, integrating judiciously the merits of rough-fuzzy computing and multiresolution image analysis technique. The proposed method assumes that the major brain tissues, namely, gray matter, white matter, and cerebrospinal fluid from the MR images are considered to have different textural properties. The dyadic wavelet analysis is used to extract the scale-space feature vector for each pixel, while the rough-fuzzy clustering is used to address the uncertainty problem of brain MR image segmentation. An unsupervised feature selection method is introduced, based on maximum relevance-maximum significance criterion, to select relevant and significant textural features for segmentation problem, while the mathematical morphology based skull stripping preprocessing step is proposed to remove the non-cerebral tissues like skull. The performance of the proposed method, along with a comparison with related approaches, is demonstrated on a set of synthetic and real brain MR images using standard validity indices. PMID:25848961

Callosal Function in Pediatric Traumatic Brain Injury Linked to Disrupted White Matter Integrity

PubMed Central

Dennis, Emily L.; Ellis, Monica U.; Marion, Sarah D.; Jin, Yan; Moran, Lisa; Olsen, Alexander; Kernan, Claudia; Babikian, Talin; Mink, Richard; Babbitt, Christopher; Johnson, Jeffrey; Giza, Christopher C.; Asarnow, Robert F.

2015-01-01

Traumatic brain injury (TBI) often results in traumatic axonal injury and white matter (WM) damage, particularly to the corpus callosum (CC). Damage to the CC can lead to impaired performance on neurocognitive tasks, but there is a high degree of heterogeneity in impairment following TBI. Here we examined the relation between CC microstructure and function in pediatric TBI. We used high angular resolution diffusion-weighted imaging (DWI) to evaluate the structural integrity of the CC in humans following brain injury in a sample of 32 children (23 males and 9 females) with moderate-to-severe TBI (msTBI) at 1–5 months postinjury, compared with well matched healthy control children. We assessed CC function through interhemispheric transfer time (IHTT) as measured using event-related potentials (ERPs), and related this to DWI measures of WM integrity. Finally, the relation between DWI and IHTT results was supported by additional results of neurocognitive performance assessed using a single composite performance scale. Half of the msTBI participants (16 participants) had significantly slower IHTTs than the control group. This slow IHTT group demonstrated lower CC integrity (lower fractional anisotropy and higher mean diffusivity) and poorer neurocognitive functioning than both the control group and the msTBI group with normal IHTTs. Lower fractional anisotropy—a common sign of impaired WM—and slower IHTTs also predicted poor neurocognitive function. This study reveals that there is a subset of pediatric msTBI patients during the post-acute phase of injury who have markedly impaired CC functioning and structural integrity that is associated with poor neurocognitive functioning. SIGNIFICANCE STATEMENT Traumatic brain injury (TBI) is the primary cause of death and disability in children and adolescents. There is considerable heterogeneity in postinjury outcome, which is only partially explained by injury severity. Imaging biomarkers may help explain some of this variance, as diffusion weighted imaging is sensitive to the white matter disruption that is common after injury. The corpus callosum (CC) is one of the most commonly reported areas of disruption. In this multimodal study, we discovered a divergence within our pediatric moderate-to-severe TBI sample 1–5 months postinjury. A subset of the TBI sample showed significant impairment in CC function, which is supported by additional results showing deficits in CC structural integrity. This subset also had poorer neurocognitive functioning. Our research sheds light on postinjury heterogeneity. PMID:26180196

Analysis of Electronic Densities and Integrated Doses in Multiform Glioblastomas Stereotactic Radiotherapy

NASA Astrophysics Data System (ADS)

Barón-Aznar, C.; Moreno-Jiménez, S.; Celis, M. A.; Lárraga-Gutiérrez, J. M.; Ballesteros-Zebadúa, P.

2008-08-01

Integrated dose is the total energy delivered in a radiotherapy target. This physical parameter could be a predictor for complications such as brain edema and radionecrosis after stereotactic radiotherapy treatments for brain tumors. Integrated Dose depends on the tissue density and volume. Using CT patients images from the National Institute of Neurology and Neurosurgery and BrainScansoftware, this work presents the mean density of 21 multiform glioblastomas, comparative results for normal tissue and estimated integrated dose for each case. The relationship between integrated dose and the probability of complications is discussed.

Overlap and Differences in Brain Networks Underlying the Processing of Complex Sentence Structures in Second Language Users Compared with Native Speakers.

PubMed

Weber, Kirsten; Luther, Lisa; Indefrey, Peter; Hagoort, Peter

2016-05-01

When we learn a second language later in life, do we integrate it with the established neural networks in place for the first language or is at least a partially new network recruited? While there is evidence that simple grammatical structures in a second language share a system with the native language, the story becomes more multifaceted for complex sentence structures. In this study, we investigated the underlying brain networks in native speakers compared with proficient second language users while processing complex sentences. As hypothesized, complex structures were processed by the same large-scale inferior frontal and middle temporal language networks of the brain in the second language, as seen in native speakers. These effects were seen both in activations and task-related connectivity patterns. Furthermore, the second language users showed increased task-related connectivity from inferior frontal to inferior parietal regions of the brain, regions related to attention and cognitive control, suggesting less automatic processing for these structures in a second language.

Selective Audiovisual Semantic Integration Enabled by Feature-Selective Attention

PubMed Central

Li, Yuanqing; Long, Jinyi; Huang, Biao; Yu, Tianyou; Wu, Wei; Li, Peijun; Fang, Fang; Sun, Pei

2016-01-01

An audiovisual object may contain multiple semantic features, such as the gender and emotional features of the speaker. Feature-selective attention and audiovisual semantic integration are two brain functions involved in the recognition of audiovisual objects. Humans often selectively attend to one or several features while ignoring the other features of an audiovisual object. Meanwhile, the human brain integrates semantic information from the visual and auditory modalities. However, how these two brain functions correlate with each other remains to be elucidated. In this functional magnetic resonance imaging (fMRI) study, we explored the neural mechanism by which feature-selective attention modulates audiovisual semantic integration. During the fMRI experiment, the subjects were presented with visual-only, auditory-only, or audiovisual dynamical facial stimuli and performed several feature-selective attention tasks. Our results revealed that a distribution of areas, including heteromodal areas and brain areas encoding attended features, may be involved in audiovisual semantic integration. Through feature-selective attention, the human brain may selectively integrate audiovisual semantic information from attended features by enhancing functional connectivity and thus regulating information flows from heteromodal areas to brain areas encoding the attended features. PMID:26759193

Cognitive Flexibility through Metastable Neural Dynamics Is Disrupted by Damage to the Structural Connectome.

PubMed

Hellyer, Peter J; Scott, Gregory; Shanahan, Murray; Sharp, David J; Leech, Robert

2015-06-17

Current theory proposes that healthy neural dynamics operate in a metastable regime, where brain regions interact to simultaneously maximize integration and segregation. Metastability may confer important behavioral properties, such as cognitive flexibility. It is increasingly recognized that neural dynamics are constrained by the underlying structural connections between brain regions. An important challenge is, therefore, to relate structural connectivity, neural dynamics, and behavior. Traumatic brain injury (TBI) is a pre-eminent structural disconnection disorder whereby traumatic axonal injury damages large-scale connectivity, producing characteristic cognitive impairments, including slowed information processing speed and reduced cognitive flexibility, that may be a result of disrupted metastable dynamics. Therefore, TBI provides an experimental and theoretical model to examine how metastable dynamics relate to structural connectivity and cognition. Here, we use complementary empirical and computational approaches to investigate how metastability arises from the healthy structural connectome and relates to cognitive performance. We found reduced metastability in large-scale neural dynamics after TBI, measured with resting-state functional MRI. This reduction in metastability was associated with damage to the connectome, measured using diffusion MRI. Furthermore, decreased metastability was associated with reduced cognitive flexibility and information processing. A computational model, defined by empirically derived connectivity data, demonstrates how behaviorally relevant changes in neural dynamics result from structural disconnection. Our findings suggest how metastable dynamics are important for normal brain function and contingent on the structure of the human connectome. Copyright © 2015 the authors 0270-6474/15/359050-14$15.00/0.

Youthful Brains in Older Adults: Preserved Neuroanatomy in the Default Mode and Salience Networks Contributes to Youthful Memory in Superaging.

PubMed

Sun, Felicia W; Stepanovic, Michael R; Andreano, Joseph; Barrett, Lisa Feldman; Touroutoglou, Alexandra; Dickerson, Bradford C

2016-09-14

Decline in cognitive skills, especially in memory, is often viewed as part of "normal" aging. Yet some individuals "age better" than others. Building on prior research showing that cortical thickness in one brain region, the anterior midcingulate cortex, is preserved in older adults with memory performance abilities equal to or better than those of people 20-30 years younger (i.e., "superagers"), we examined the structural integrity of two large-scale intrinsic brain networks in superaging: the default mode network, typically engaged during memory encoding and retrieval tasks, and the salience network, typically engaged during attention, motivation, and executive function tasks. We predicted that superagers would have preserved cortical thickness in critical nodes in these networks. We defined superagers (60-80 years old) based on their performance compared to young adults (18-32 years old) on the California Verbal Learning Test Long Delay Free Recall test. We found regions within the networks of interest where the cerebral cortex of superagers was thicker than that of typical older adults, and where superagers were anatomically indistinguishable from young adults; hippocampal volume was also preserved in superagers. Within the full group of older adults, thickness of a number of regions, including the anterior temporal cortex, rostral medial prefrontal cortex, and anterior midcingulate cortex, correlated with memory performance, as did the volume of the hippocampus. These results indicate older adults with youthful memory abilities have youthful brain regions in key paralimbic and limbic nodes of the default mode and salience networks that support attentional, executive, and mnemonic processes subserving memory function. Memory performance typically declines with age, as does cortical structural integrity, yet some older adults maintain youthful memory. We tested the hypothesis that superagers (older individuals with youthful memory performance) would exhibit preserved neuroanatomy in key brain networks subserving memory. We found that superagers not only perform similarly to young adults on memory testing, they also do not show the typical patterns of brain atrophy in certain regions. These regions are contained largely within two major intrinsic brain networks: the default mode network, implicated in memory encoding, storage, and retrieval, and the salience network, associated with attention and executive processes involved in encoding and retrieval. Preserved neuroanatomical integrity in these networks is associated with better memory performance among older adults. Copyright © 2016 Sun, Stepanovic et al.

Relationship of caregiver and family functioning to participation outcomes after postacute rehabilitation for traumatic brain injury: a multicenter investigation.

PubMed

Sander, Angelle M; Maestas, Kacey Little; Sherer, Mark; Malec, James F; Nakase-Richardson, Risa

2012-05-01

To investigate the contribution of caregiver emotional functioning and family functioning to participation outcomes after postacute rehabilitation for traumatic brain injury (TBI). Prospective cohort study. Three postacute comprehensive-integrated postacute rehabilitation programs associated with National Institute on Disability and Rehabilitation Research-funded TBI Model Systems Centers. Persons with medically documented TBI (N=136; 57% with severe TBI, 12% moderate, 31% mild), primarily men and 69% white. Not applicable. Community Integration Questionnaire and Craig Handicap Assessment and Reporting Technique (CHART). After accounting for age, education, sex, and race/ethnicity, there was a significant interaction between caregiver emotional functioning and time since injury for CHART Occupation and Social Integration Scale scores. Better emotional functioning in caregivers was associated with greater occupation and social integration outcomes for persons who entered the postacute rehabilitation program within 6 months of injury, but not for those >6 months postinjury. There was no relationship of family functioning to participation outcomes, and no interaction between family functioning and time since injury. Caregiver distress should be accounted for in studies investigating the effectiveness of postacute rehabilitation after TBI. Screening of caregivers early during postacute rehabilitation can target those who need assistance to improve their support of the person with TBI. Copyright © 2012 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Theta-Modulated Gamma-Band Synchronization Among Activated Regions During a Verb Generation Task

PubMed Central

Doesburg, Sam M.; Vinette, Sarah A.; Cheung, Michael J.; Pang, Elizabeth W.

2012-01-01

Expressive language is complex and involves processing within a distributed network of cortical regions. Functional MRI and magnetoencephalography (MEG) have identified brain areas critical for expressive language, but how these regions communicate across the network remains poorly understood. It is thought that synchronization of oscillations between neural populations, particularly at a gamma rate (>30 Hz), underlies functional integration within cortical networks. Modulation of gamma rhythms by theta-band oscillations (4–8 Hz) has been proposed as a mechanism for the integration of local cell coalitions into large-scale networks underlying cognition and perception. The present study tested the hypothesis that these oscillatory mechanisms of functional integration were present within the expressive language network. We recorded MEG while subjects performed a covert verb generation task. We localized activated cortical regions using beamformer analysis, calculated inter-regional phase locking between activated areas, and measured modulation of inter-regional gamma synchronization by theta phase. The results show task-dependent gamma-band synchronization among regions activated during the performance of the verb generation task, and we provide evidence that these transient and periodic instances of high-frequency connectivity were modulated by the phase of cortical theta oscillations. These findings suggest that oscillatory synchronization and cross-frequency interactions are mechanisms for functional integration among distributed brain areas supporting expressive language processing. PMID:22707946

Building brains for bodies

NASA Technical Reports Server (NTRS)

Brooks, Rodney Allen; Stein, Lynn Andrea

1994-01-01

We describe a project to capitalize on newly available levels of computational resources in order to understand human cognition. We will build an integrated physical system including vision, sound input and output, and dextrous manipulation, all controlled by a continuously operating large scale parallel MIMD computer. The resulting system will learn to 'think' by building on its bodily experiences to accomplish progressively more abstract tasks. Past experience suggests that in attempting to build such an integrated system we will have to fundamentally change the way artificial intelligence, cognitive science, linguistics, and philosophy think about the organization of intelligence. We expect to be able to better reconcile the theories that will be developed with current work in neuroscience.

Re-emergence of modular brain networks in stroke recovery.

PubMed

Siegel, Joshua S; Seitzman, Benjamin A; Ramsey, Lenny E; Ortega, Mario; Gordon, Evan M; Dosenbach, Nico U F; Petersen, Steven E; Shulman, Gordon L; Corbetta, Maurizio

2018-04-01

Studies of stroke have identified local reorganization in perilesional tissue. However, because the brain is highly networked, strokes also broadly alter the brain's global network organization. Here, we assess brain network structure longitudinally in adult stroke patients using resting state fMRI. The topology and boundaries of cortical regions remain grossly unchanged across recovery. In contrast, the modularity of brain systems i.e. the degree of integration within and segregation between networks, was significantly reduced sub-acutely (n = 107), but partially recovered by 3 months (n = 85), and 1 year (n = 67). Importantly, network recovery correlated with recovery from language, spatial memory, and attention deficits, but not motor or visual deficits. Finally, in-depth single subject analyses were conducted using tools for visualization of changes in brain networks over time. This exploration indicated that changes in modularity during successful recovery reflect specific alterations in the relationships between different networks. For example, in a patient with left temporo-parietal stroke and severe aphasia, sub-acute loss of modularity reflected loss of association between frontal and temporo-parietal regions bi-hemispherically across multiple modules. These long-distance connections then returned over time, paralleling aphasia recovery. This work establishes the potential importance of normalization of large-scale modular brain systems in stroke recovery. Copyright © 2017. Published by Elsevier Ltd.

Advancing multiscale structural mapping of the brain through fluorescence imaging and analysis across length scales

PubMed Central

Hogstrom, L. J.; Guo, S. M.; Murugadoss, K.; Bathe, M.

2016-01-01

Brain function emerges from hierarchical neuronal structure that spans orders of magnitude in length scale, from the nanometre-scale organization of synaptic proteins to the macroscopic wiring of neuronal circuits. Because the synaptic electrochemical signal transmission that drives brain function ultimately relies on the organization of neuronal circuits, understanding brain function requires an understanding of the principles that determine hierarchical neuronal structure in living or intact organisms. Recent advances in fluorescence imaging now enable quantitative characterization of neuronal structure across length scales, ranging from single-molecule localization using super-resolution imaging to whole-brain imaging using light-sheet microscopy on cleared samples. These tools, together with correlative electron microscopy and magnetic resonance imaging at the nanoscopic and macroscopic scales, respectively, now facilitate our ability to probe brain structure across its full range of length scales with cellular and molecular specificity. As these imaging datasets become increasingly accessible to researchers, novel statistical and computational frameworks will play an increasing role in efforts to relate hierarchical brain structure to its function. In this perspective, we discuss several prominent experimental advances that are ushering in a new era of quantitative fluorescence-based imaging in neuroscience along with novel computational and statistical strategies that are helping to distil our understanding of complex brain structure. PMID:26855758

Functional atlas of the awake rat brain: A neuroimaging study of rat brain specialization and integration.

PubMed

Ma, Zhiwei; Perez, Pablo; Ma, Zilu; Liu, Yikang; Hamilton, Christina; Liang, Zhifeng; Zhang, Nanyin

2018-04-15

Connectivity-based parcellation approaches present an innovative method to segregate the brain into functionally specialized regions. These approaches have significantly advanced our understanding of the human brain organization. However, parallel progress in animal research is sparse. Using resting-state fMRI data and a novel, data-driven parcellation method, we have obtained robust functional parcellations of the rat brain. These functional parcellations reveal the regional specialization of the rat brain, which exhibited high within-parcel homogeneity and high reproducibility across animals. Graph analysis of the whole-brain network constructed based on these functional parcels indicates that the rat brain has a topological organization similar to humans, characterized by both segregation and integration. Our study also provides compelling evidence that the cingulate cortex is a functional hub region conserved from rodents to humans. Together, this study has characterized the rat brain specialization and integration, and has significantly advanced our understanding of the rat brain organization. In addition, it is valuable for studies of comparative functional neuroanatomy in mammalian brains. Copyright © 2016 Elsevier Inc. All rights reserved.

Understanding principles of integration and segregation using whole-brain computational connectomics: implications for neuropsychiatric disorders

PubMed Central

Lord, Louis-David; Stevner, Angus B.; Kringelbach, Morten L.

2017-01-01

To survive in an ever-changing environment, the brain must seamlessly integrate a rich stream of incoming information into coherent internal representations that can then be used to efficiently plan for action. The brain must, however, balance its ability to integrate information from various sources with a complementary capacity to segregate information into modules which perform specialized computations in local circuits. Importantly, evidence suggests that imbalances in the brain's ability to bind together and/or segregate information over both space and time is a common feature of several neuropsychiatric disorders. Most studies have, however, until recently strictly attempted to characterize the principles of integration and segregation in static (i.e. time-invariant) representations of human brain networks, hence disregarding the complex spatio-temporal nature of these processes. In the present Review, we describe how the emerging discipline of whole-brain computational connectomics may be used to study the causal mechanisms of the integration and segregation of information on behaviourally relevant timescales. We emphasize how novel methods from network science and whole-brain computational modelling can expand beyond traditional neuroimaging paradigms and help to uncover the neurobiological determinants of the abnormal integration and segregation of information in neuropsychiatric disorders. This article is part of the themed issue ‘Mathematical methods in medicine: neuroscience, cardiology and pathology’. PMID:28507228

Multiscale agent-based cancer modeling.

PubMed

Zhang, Le; Wang, Zhihui; Sagotsky, Jonathan A; Deisboeck, Thomas S

2009-04-01

Agent-based modeling (ABM) is an in silico technique that is being used in a variety of research areas such as in social sciences, economics and increasingly in biomedicine as an interdisciplinary tool to study the dynamics of complex systems. Here, we describe its applicability to integrative tumor biology research by introducing a multi-scale tumor modeling platform that understands brain cancer as a complex dynamic biosystem. We summarize significant findings of this work, and discuss both challenges and future directions for ABM in the field of cancer research.

View from Silicon Valley: Maximizing the Scientific Impact of Global Brain Initiatives through Entrepreneurship.

PubMed

Joshi, Pushkar S; Ghosh, Kunal K

2016-11-02

In this era of technology-driven global neuroscience initiatives, the role of the neurotechnology industry remains woefully ambiguous. Here, we explain why industry is essential to the success of these global initiatives, and how it can maximize the scientific impact of these efforts by (1) scaling and ultimately democratizing access to breakthrough neurotechnologies, and (2) commercializing technologies as part of integrated, end-to-end solutions that accelerate neuroscientific discovery. Copyright © 2016 Elsevier Inc. All rights reserved.

Analysis of Electronic Densities and Integrated Doses in Multiform Glioblastomas Stereotactic Radiotherapy

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

Baron-Aznar, C.; Moreno-Jimenez, S.; Celis, M. A.

2008-08-11

Integrated dose is the total energy delivered in a radiotherapy target. This physical parameter could be a predictor for complications such as brain edema and radionecrosis after stereotactic radiotherapy treatments for brain tumors. Integrated Dose depends on the tissue density and volume. Using CT patients images from the National Institute of Neurology and Neurosurgery and BrainScan(c) software, this work presents the mean density of 21 multiform glioblastomas, comparative results for normal tissue and estimated integrated dose for each case. The relationship between integrated dose and the probability of complications is discussed.

The temporal structures and functional significance of scale-free brain activity

PubMed Central

He, Biyu J.; Zempel, John M.; Snyder, Abraham Z.; Raichle, Marcus E.

2010-01-01

SUMMARY Scale-free dynamics, with a power spectrum following P ∝ f-β, are an intrinsic feature of many complex processes in nature. In neural systems, scale-free activity is often neglected in electrophysiological research. Here, we investigate scale-free dynamics in human brain and show that it contains extensive nested frequencies, with the phase of lower frequencies modulating the amplitude of higher frequencies in an upward progression across the frequency spectrum. The functional significance of scale-free brain activity is indicated by task performance modulation and regional variation, with β being larger in default network and visual cortex and smaller in hippocampus and cerebellum. The precise patterns of nested frequencies in the brain differ from other scale-free dynamics in nature, such as earth seismic waves and stock market fluctuations, suggesting system-specific generative mechanisms. Our findings reveal robust temporal structures and behavioral significance of scale-free brain activity and should motivate future study on its physiological mechanisms and cognitive implications. PMID:20471349

Functional split brain in a driving/listening paradigm.

PubMed

Sasai, Shuntaro; Boly, Melanie; Mensen, Armand; Tononi, Giulio

2016-12-13

We often engage in two concurrent but unrelated activities, such as driving on a quiet road while listening to the radio. When we do so, does our brain split into functionally distinct entities? To address this question, we imaged brain activity with fMRI in experienced drivers engaged in a driving simulator while listening either to global positioning system instructions (integrated task) or to a radio show (split task). We found that, compared with the integrated task, the split task was characterized by reduced multivariate functional connectivity between the driving and listening networks. Furthermore, the integrated information content of the two networks, predicting their joint dynamics above and beyond their independent dynamics, was high in the integrated task and zero in the split task. Finally, individual subjects' ability to switch between high and low information integration predicted their driving performance across integrated and split tasks. This study raises the possibility that under certain conditions of daily life, a single brain may support two independent functional streams, a "functional split brain" similar to what is observed in patients with an anatomical split.

Dose-volume metrics and their relation to memory performance in pediatric brain tumor patients: A preliminary study.

PubMed

Raghubar, Kimberly P; Lamba, Michael; Cecil, Kim M; Yeates, Keith Owen; Mahone, E Mark; Limke, Christina; Grosshans, David; Beckwith, Travis J; Ris, M Douglas

2018-06-01

Advances in radiation treatment (RT), specifically volumetric planning with detailed dose and volumetric data for specific brain structures, have provided new opportunities to study neurobehavioral outcomes of RT in children treated for brain tumor. The present study examined the relationship between biophysical and physical dose metrics and neurocognitive ability, namely learning and memory, 2 years post-RT in pediatric brain tumor patients. The sample consisted of 26 pediatric patients with brain tumor, 14 of whom completed neuropsychological evaluations on average 24 months post-RT. Prescribed dose and dose-volume metrics for specific brain regions were calculated including physical metrics (i.e., mean dose and maximum dose) and biophysical metrics (i.e., integral biological effective dose and generalized equivalent uniform dose). We examined the associations between dose-volume metrics (whole brain, right and left hippocampus), and performance on measures of learning and memory (Children's Memory Scale). Biophysical dose metrics were highly correlated with the physical metric of mean dose but not with prescribed dose. Biophysical metrics and mean dose, but not prescribed dose, correlated with measures of learning and memory. These preliminary findings call into question the value of prescribed dose for characterizing treatment intensity; they also suggest that biophysical dose has only a limited advantage compared to physical dose when calculated for specific regions of the brain. We discuss the implications of the findings for evaluating and understanding the relation between RT and neurocognitive functioning. © 2018 Wiley Periodicals, Inc.

The Neurona at Home project: Simulating a large-scale cellular automata brain in a distributed computing environment

NASA Astrophysics Data System (ADS)

Acedo, L.; Villanueva-Oller, J.; Moraño, J. A.; Villanueva, R.-J.

2013-01-01

The Berkeley Open Infrastructure for Network Computing (BOINC) has become the standard open source solution for grid computing in the Internet. Volunteers use their computers to complete an small part of the task assigned by a dedicated server. We have developed a BOINC project called Neurona@Home whose objective is to simulate a cellular automata random network with, at least, one million neurons. We consider a cellular automata version of the integrate-and-fire model in which excitatory and inhibitory nodes can activate or deactivate neighbor nodes according to a set of probabilistic rules. Our aim is to determine the phase diagram of the model and its behaviour and to compare it with the electroencephalographic signals measured in real brains.

Modeling brain circuitry over a wide range of scales.

PubMed

Fua, Pascal; Knott, Graham W

2015-01-01

If we are ever to unravel the mysteries of brain function at its most fundamental level, we will need a precise understanding of how its component neurons connect to each other. Electron Microscopes (EM) can now provide the nanometer resolution that is needed to image synapses, and therefore connections, while Light Microscopes (LM) see at the micrometer resolution required to model the 3D structure of the dendritic network. Since both the topology and the connection strength are integral parts of the brain's wiring diagram, being able to combine these two modalities is critically important. In fact, these microscopes now routinely produce high-resolution imagery in such large quantities that the bottleneck becomes automated processing and interpretation, which is needed for such data to be exploited to its full potential. In this paper, we briefly review the Computer Vision techniques we have developed at EPFL to address this need. They include delineating dendritic arbors from LM imagery, segmenting organelles from EM, and combining the two into a consistent representation.

Modeling brain circuitry over a wide range of scales

PubMed Central

Fua, Pascal; Knott, Graham W.

2015-01-01

If we are ever to unravel the mysteries of brain function at its most fundamental level, we will need a precise understanding of how its component neurons connect to each other. Electron Microscopes (EM) can now provide the nanometer resolution that is needed to image synapses, and therefore connections, while Light Microscopes (LM) see at the micrometer resolution required to model the 3D structure of the dendritic network. Since both the topology and the connection strength are integral parts of the brain's wiring diagram, being able to combine these two modalities is critically important. In fact, these microscopes now routinely produce high-resolution imagery in such large quantities that the bottleneck becomes automated processing and interpretation, which is needed for such data to be exploited to its full potential. In this paper, we briefly review the Computer Vision techniques we have developed at EPFL to address this need. They include delineating dendritic arbors from LM imagery, segmenting organelles from EM, and combining the two into a consistent representation. PMID:25904852

Dependence of normal brain integral dose and normal tissue complication probability on the prescription isodose values for γ-knife radiosurgery

NASA Astrophysics Data System (ADS)

Ma, Lijun

2001-11-01

A recent multi-institutional clinical study suggested possible benefits of lowering the prescription isodose lines for stereotactic radiosurgery procedures. In this study, we investigate the dependence of the normal brain integral dose and the normal tissue complication probability (NTCP) on the prescription isodose values for γ-knife radiosurgery. An analytical dose model was developed for γ-knife treatment planning. The dose model was commissioned by fitting the measured dose profiles for each helmet size. The dose model was validated by comparing its results with the Leksell gamma plan (LGP, version 5.30) calculations. The normal brain integral dose and the NTCP were computed and analysed for an ensemble of treatment cases. The functional dependence of the normal brain integral dose and the NCTP versus the prescribing isodose values was studied for these cases. We found that the normal brain integral dose and the NTCP increase significantly when lowering the prescription isodose lines from 50% to 35% of the maximum tumour dose. Alternatively, the normal brain integral dose and the NTCP decrease significantly when raising the prescribing isodose lines from 50% to 65% of the maximum tumour dose. The results may be used as a guideline for designing future dose escalation studies for γ-knife applications.

Seizure Control and Memory Impairment Are Related to Disrupted Brain Functional Integration in Temporal Lobe Epilepsy.

PubMed

Park, Chang-Hyun; Choi, Yun Seo; Jung, A-Reum; Chung, Hwa-Kyoung; Kim, Hyeon Jin; Yoo, Jeong Hyun; Lee, Hyang Woon

2017-01-01

Brain functional integration can be disrupted in patients with temporal lobe epilepsy (TLE), but the clinical relevance of this disruption is not completely understood. The authors hypothesized that disrupted functional integration over brain regions remote from, as well as adjacent to, the seizure focus could be related to clinical severity in terms of seizure control and memory impairment. Using resting-state functional MRI data acquired from 48 TLE patients and 45 healthy controls, the authors mapped functional brain networks and assessed changes in a network parameter of brain functional integration, efficiency, to examine the distribution of disrupted functional integration within and between brain regions. The authors assessed whether the extent of altered efficiency was influenced by seizure control status and whether the degree of altered efficiency was associated with the severity of memory impairment. Alterations in the efficiency were observed primarily near the subcortical region ipsilateral to the seizure focus in TLE patients. The extent of regional involvement was greater in patients with poor seizure control: it reached the frontal, temporal, occipital, and insular cortices in TLE patients with poor seizure control, whereas it was limited to the limbic and parietal cortices in TLE patients with good seizure control. Furthermore, TLE patients with poor seizure control experienced more severe memory impairment, and this was associated with lower efficiency in the brain regions with altered efficiency. These findings indicate that the distribution of disrupted brain functional integration is clinically relevant, as it is associated with seizure control status and comorbid memory impairment.

Fifth dimension of life and the 4/5 allometric scaling law for human brain.

PubMed

He, Ji-Huan; Zhang, Juan

2004-01-01

Brain cells are not spherical. The basal metabolic rate (B) of a spherical cell scales as B approximately r2, where r is the radius of the cell; that of a brain cell scales as B approximately r(d), where r is the characteristic radius of the cell and d is the fractal dimensionality of its contour. The fractal geometry of the cell leads to a 4/5 allometric scaling law for human brain, uniquely endowing humans with a 5th dimension and successfully explains why the scaling exponent varies during rest and exercise. A striking analogy between Kleiber's 3/4 law and Newton's second law is heuristically illustrated. A physical explanation is given for the 4th dimension of life for three-dimensional organisms and the 5th dimension for human brain.

Integrating Traumatic Brain Injury Model Systems Data into the Federal Interagency Traumatic Brain Injury Research Informatics Systems

DTIC Science & Technology

2016-10-01

Traumatic Brain Injury Research Informatics Systems 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-14-1-0564 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S...AWARD NUMBER: W81XWH-14-1-0564 TITLE: Integrating Traumatic Brain Injury Model Systems Data into the Federal Interagency Traumatic Brain Injury...Research Informatics Systems PRINCIPAL INVESTIGATOR: Cynthia Harrison-Felix, PhD CONTRACTING ORGANIZATION: Craig Hospital Englewood, CO 80113

A Query Integrator and Manager for the Query Web

PubMed Central

Brinkley, James F.; Detwiler, Landon T.

2012-01-01

We introduce two concepts: the Query Web as a layer of interconnected queries over the document web and the semantic web, and a Query Web Integrator and Manager (QI) that enables the Query Web to evolve. QI permits users to write, save and reuse queries over any web accessible source, including other queries saved in other installations of QI. The saved queries may be in any language (e.g. SPARQL, XQuery); the only condition for interconnection is that the queries return their results in some form of XML. This condition allows queries to chain off each other, and to be written in whatever language is appropriate for the task. We illustrate the potential use of QI for several biomedical use cases, including ontology view generation using a combination of graph-based and logical approaches, value set generation for clinical data management, image annotation using terminology obtained from an ontology web service, ontology-driven brain imaging data integration, small-scale clinical data integration, and wider-scale clinical data integration. Such use cases illustrate the current range of applications of QI and lead us to speculate about the potential evolution from smaller groups of interconnected queries into a larger query network that layers over the document and semantic web. The resulting Query Web could greatly aid researchers and others who now have to manually navigate through multiple information sources in order to answer specific questions. PMID:22531831

The Dynamical Balance of the Brain at Rest

PubMed Central

Deco, Gustavo; Corbetta, Maurizio

2014-01-01

We review evidence that spontaneous, i.e. not stimulus- or task-driven, activity in the brain is not noise, but orderly organized at the level of large scale systems in a series of functional networks that maintain at all times a high level of coherence. These networks of spontaneous activity correlation or resting state networks (RSN) are closely related to the underlying anatomical connectivity, but their topography is also gated by the history of prior task activation. Network coherence does not depend on covert cognitive activity, but its strength and integrity relates to behavioral performance. Some RSN are functionally organized as dynamically competing systems both at rest and during tasks. Computational studies show that one of such dynamics, the anti-correlation between networks, depends on noise driven transitions between different multi-stable cluster synchronization states. These multi-stable states emerge because of transmission delays between regions that are modeled as coupled oscillators systems. Large-scale systems dynamics are useful for keeping different functional sub-networks in a state of heightened competition, which can be stabilized and fired by even small modulations of either sensory or internal signals. PMID:21196530

A large-scale circuit mechanism for hierarchical dynamical processing in the primate cortex

PubMed Central

Chaudhuri, Rishidev; Knoblauch, Kenneth; Gariel, Marie-Alice; Kennedy, Henry; Wang, Xiao-Jing

2015-01-01

We developed a large-scale dynamical model of the macaque neocortex, which is based on recently acquired directed- and weighted-connectivity data from tract-tracing experiments, and which incorporates heterogeneity across areas. A hierarchy of timescales naturally emerges from this system: sensory areas show brief, transient responses to input (appropriate for sensory processing), whereas association areas integrate inputs over time and exhibit persistent activity (suitable for decision-making and working memory). The model displays multiple temporal hierarchies, as evidenced by contrasting responses to visual versus somatosensory stimulation. Moreover, slower prefrontal and temporal areas have a disproportionate impact on global brain dynamics. These findings establish a circuit mechanism for “temporal receptive windows” that are progressively enlarged along the cortical hierarchy, suggest an extension of time integration in decision-making from local to large circuits, and should prompt a re-evaluation of the analysis of functional connectivity (measured by fMRI or EEG/MEG) by taking into account inter-areal heterogeneity. PMID:26439530

Multiple-scale neuroendocrine signals connect brain and pituitary hormone rhythms

PubMed Central

Romanò, Nicola; Guillou, Anne; Martin, Agnès O; Mollard, Patrice

2017-01-01

Small assemblies of hypothalamic “parvocellular” neurons release their neuroendocrine signals at the median eminence (ME) to control long-lasting pituitary hormone rhythms essential for homeostasis. How such rapid hypothalamic neurotransmission leads to slowly evolving hormonal signals remains unknown. Here, we show that the temporal organization of dopamine (DA) release events in freely behaving animals relies on a set of characteristic features that are adapted to the dynamic dopaminergic control of pituitary prolactin secretion, a key reproductive hormone. First, locally generated DA release signals are organized over more than four orders of magnitude (0.001 Hz–10 Hz). Second, these DA events are finely tuned within and between frequency domains as building blocks that recur over days to weeks. Third, an integration time window is detected across the ME and consists of high-frequency DA discharges that are coordinated within the minutes range. Thus, a hierarchical combination of time-scaled neuroendocrine signals displays local–global integration to connect brain–pituitary rhythms and pace hormone secretion. PMID:28193889

Validation of the Early Functional Abilities scale: An assessment of four dimensions in early recovery after traumatic brain injury.

PubMed

Poulsen, Ingrid; Kreiner, Svend; Engberg, Aase W

2018-02-13

The Early Functional Abilities scale assesses the restoration of brain function after brain injury, based on 4 dimensions. The primary objective of this study was to evaluate the validity, objectivity, reliability and measurement precision of the Early Functional Abilities scale by Rasch model item analysis. A secondary objective was to examine the relationship between the Early Functional Abilities scale and the Functional Independence Measurement™, in order to establish the criterion validity of the Early Functional Abilities scale and to compare the sensitivity of measurements using the 2 instruments. The Rasch analysis was based on the assessment of 408 adult patients at admission to sub-acute rehabilitation in Copenhagen, Denmark after traumatic brain injury. The Early Functional Abilities scale provides valid and objective measurement of vegetative (autonomic), facio-oral, sensorimotor and communicative/cognitive functions. Removal of one item from the sensorimotor scale confirmed unidimensionality for each of the 4 subscales, but not for the entire scale. The Early Functional Abilities subscales are sensitive to differences between patients in ranges in which the Functional Independence Measurement™ has a floor effect. The Early Functional Abilities scale assesses the early recovery of important aspects of brain function after traumatic brain injury, but is not unidimensional. We recommend removal of the "standing" item and calculation of summary subscales for the separate dimensions.

Organizational topology of brain and its relationship to ADHD in adolescents with d-transposition of the great arteries.

PubMed

Schmithorst, Vincent J; Panigrahy, Ashok; Gaynor, J William; Watson, Christopher G; Lee, Vince; Bellinger, David C; Rivkin, Michael J; Newburger, Jane W

2016-08-01

Little is currently known about the impact of congenital heart disease (CHD) on the organization of large-scale brain networks in relation to neurobehavioral outcome. We investigated whether CHD might impact ADHD symptoms via changes in brain structural network topology in a cohort of adolescents with d-transposition of the great arteries (d-TGA) repaired with the arterial switch operation in early infancy and referent subjects. We also explored whether these effects might be modified by apolipoprotein E (APOE) genotype, as the APOE ε2 allele has been associated with worse neurodevelopmental outcomes after repair of d-TGA in infancy. We applied graph analysis techniques to diffusion tensor imaging (DTI) data obtained from 47 d-TGA adolescents and 29 healthy referents to construct measures of structural topology at the global and regional levels. We developed statistical mediation models revealing the respective contributions of d-TGA, APOE genotype, and structural network topology on ADHD outcome as measured by the Connors ADHD/DSM-IV Scales (CADS). Changes in overall network connectivity, integration, and segregation mediated worse ADHD outcomes in d-TGA patients compared to healthy referents; these changes were predominantly in the left and right intrahemispheric regional subnetworks. Exploratory analysis revealed that network topology also mediated detrimental effects of the APOE ε4 allele but improved neurobehavioral outcomes for the APOE ε2 allele. Our results suggest that disruption of organization of large-scale networks may contribute to neurobehavioral dysfunction in adolescents with CHD and that this effect may interact with APOE genotype.

BrainFrame: a node-level heterogeneous accelerator platform for neuron simulations

NASA Astrophysics Data System (ADS)

Smaragdos, Georgios; Chatzikonstantis, Georgios; Kukreja, Rahul; Sidiropoulos, Harry; Rodopoulos, Dimitrios; Sourdis, Ioannis; Al-Ars, Zaid; Kachris, Christoforos; Soudris, Dimitrios; De Zeeuw, Chris I.; Strydis, Christos

2017-12-01

Objective. The advent of high-performance computing (HPC) in recent years has led to its increasing use in brain studies through computational models. The scale and complexity of such models are constantly increasing, leading to challenging computational requirements. Even though modern HPC platforms can often deal with such challenges, the vast diversity of the modeling field does not permit for a homogeneous acceleration platform to effectively address the complete array of modeling requirements. Approach. In this paper we propose and build BrainFrame, a heterogeneous acceleration platform that incorporates three distinct acceleration technologies, an Intel Xeon-Phi CPU, a NVidia GP-GPU and a Maxeler Dataflow Engine. The PyNN software framework is also integrated into the platform. As a challenging proof of concept, we analyze the performance of BrainFrame on different experiment instances of a state-of-the-art neuron model, representing the inferior-olivary nucleus using a biophysically-meaningful, extended Hodgkin-Huxley representation. The model instances take into account not only the neuronal-network dimensions but also different network-connectivity densities, which can drastically affect the workload’s performance characteristics. Main results. The combined use of different HPC technologies demonstrates that BrainFrame is better able to cope with the modeling diversity encountered in realistic experiments while at the same time running on significantly lower energy budgets. Our performance analysis clearly shows that the model directly affects performance and all three technologies are required to cope with all the model use cases. Significance. The BrainFrame framework is designed to transparently configure and select the appropriate back-end accelerator technology for use per simulation run. The PyNN integration provides a familiar bridge to the vast number of models already available. Additionally, it gives a clear roadmap for extending the platform support beyond the proof of concept, with improved usability and directly useful features to the computational-neuroscience community, paving the way for wider adoption.

BrainFrame: a node-level heterogeneous accelerator platform for neuron simulations.

PubMed

Smaragdos, Georgios; Chatzikonstantis, Georgios; Kukreja, Rahul; Sidiropoulos, Harry; Rodopoulos, Dimitrios; Sourdis, Ioannis; Al-Ars, Zaid; Kachris, Christoforos; Soudris, Dimitrios; De Zeeuw, Chris I; Strydis, Christos

2017-12-01

The advent of high-performance computing (HPC) in recent years has led to its increasing use in brain studies through computational models. The scale and complexity of such models are constantly increasing, leading to challenging computational requirements. Even though modern HPC platforms can often deal with such challenges, the vast diversity of the modeling field does not permit for a homogeneous acceleration platform to effectively address the complete array of modeling requirements. In this paper we propose and build BrainFrame, a heterogeneous acceleration platform that incorporates three distinct acceleration technologies, an Intel Xeon-Phi CPU, a NVidia GP-GPU and a Maxeler Dataflow Engine. The PyNN software framework is also integrated into the platform. As a challenging proof of concept, we analyze the performance of BrainFrame on different experiment instances of a state-of-the-art neuron model, representing the inferior-olivary nucleus using a biophysically-meaningful, extended Hodgkin-Huxley representation. The model instances take into account not only the neuronal-network dimensions but also different network-connectivity densities, which can drastically affect the workload's performance characteristics. The combined use of different HPC technologies demonstrates that BrainFrame is better able to cope with the modeling diversity encountered in realistic experiments while at the same time running on significantly lower energy budgets. Our performance analysis clearly shows that the model directly affects performance and all three technologies are required to cope with all the model use cases. The BrainFrame framework is designed to transparently configure and select the appropriate back-end accelerator technology for use per simulation run. The PyNN integration provides a familiar bridge to the vast number of models already available. Additionally, it gives a clear roadmap for extending the platform support beyond the proof of concept, with improved usability and directly useful features to the computational-neuroscience community, paving the way for wider adoption.

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.

Disrupted topological properties of brain white matter networks in left temporal lobe epilepsy: a diffusion tensor imaging study.

PubMed

Xu, Y; Qiu, S; Wang, J; Liu, Z; Zhang, R; Li, S; Cheng, L; Liu, Z; Wang, W; Huang, R

2014-10-24

Mesial temporal lobe epilepsy (mTLE) is the most common drug-refractory focal epilepsy in adults. Although previous functional and morphological studies have revealed abnormalities in the brain networks of mTLE, the topological organization of the brain white matter (WM) networks in mTLE patients is still ambiguous. In this study, we constructed brain WM networks for 14 left mTLE patients and 22 age- and gender-matched normal controls using diffusion tensor tractography and estimated the alterations of network properties in the mTLE brain networks using graph theoretical analysis. We found that networks for both the mTLE patients and the controls exhibited prominent small-world properties, suggesting a balanced topology of integration and segregation. However, the brain WM networks of mTLE patients showed a significant increased characteristic path length but significant decreased global efficiency, which indicate a disruption in the organization of the brain WM networks in mTLE patients. Moreover, we found significant between-group differences in the nodal properties in several brain regions, such as the left superior temporal gyrus, left hippocampus, the right occipital and right temporal cortices. The robustness analysis showed that the results were likely to be consistent for the networks constructed with different definitions of node and edge weight. Taken together, our findings may suggest an adverse effect of epileptic seizures on the organization of large-scale brain WM networks in mTLE patients. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

Large-Scale Functional Brain Network Reorganization During Taoist Meditation.

PubMed

Jao, Tun; Li, Chia-Wei; Vértes, Petra E; Wu, Changwei Wesley; Achard, Sophie; Hsieh, Chao-Hsien; Liou, Chien-Hui; Chen, Jyh-Horng; Bullmore, Edward T

2016-02-01

Meditation induces a distinct and reversible mental state that provides insights into brain correlates of consciousness. We explored brain network changes related to meditation by graph theoretical analysis of resting-state functional magnetic resonance imaging data. Eighteen Taoist meditators with varying levels of expertise were scanned using a within-subjects counterbalanced design during resting and meditation states. State-related differences in network topology were measured globally and at the level of individual nodes and edges. Although measures of global network topology, such as small-worldness, were unchanged, meditation was characterized by an extensive and expertise-dependent reorganization of the hubs (highly connected nodes) and edges (functional connections). Areas of sensory cortex, especially the bilateral primary visual and auditory cortices, and the bilateral temporopolar areas, which had the highest degree (or connectivity) during the resting state, showed the biggest decrease during meditation. Conversely, bilateral thalamus and components of the default mode network, mainly the bilateral precuneus and posterior cingulate cortex, had low degree in the resting state but increased degree during meditation. Additionally, these changes in nodal degree were accompanied by reorganization of anatomical orientation of the edges. During meditation, long-distance longitudinal (antero-posterior) edges increased proportionally, whereas orthogonal long-distance transverse (right-left) edges connecting bilaterally homologous cortices decreased. Our findings suggest that transient changes in consciousness associated with meditation introduce convergent changes in the topological and spatial properties of brain functional networks, and the anatomical pattern of integration might be as important as the global level of integration when considering the network basis for human consciousness.

Altered gray matter organization in children and adolescents with ADHD: a structural covariance connectome study

PubMed Central

Griffiths, K R; Grieve, S M; Kohn, M R; Clarke, S; Williams, L M; Korgaonkar, M S

2016-01-01

Although multiple studies have reported structural deficits in multiple brain regions in attention-deficit hyperactivity disorder (ADHD), we do not yet know if these deficits reflect a more systematic disruption to the anatomical organization of large-scale brain networks. Here we used a graph theoretical approach to quantify anatomical organization in children and adolescents with ADHD. We generated anatomical networks based on covariance of gray matter volumes from 92 regions across the brain in children and adolescents with ADHD (n=34) and age- and sex-matched healthy controls (n=28). Using graph theory, we computed metrics that characterize both the global organization of anatomical networks (interconnectivity (clustering), integration (path length) and balance of global integration and localized segregation (small-worldness)) and their local nodal measures (participation (degree) and interaction (betweenness) within a network). Relative to Controls, ADHD participants exhibited altered global organization reflected in more clustering or network segregation. Locally, nodal degree and betweenness were increased in the subcortical amygdalae in ADHD, but reduced in cortical nodes in the anterior cingulate, posterior cingulate, mid temporal pole and rolandic operculum. In ADHD, anatomical networks were disrupted and reflected an emphasis on subcortical local connections centered around the amygdala, at the expense of cortical organization. Brains of children and adolescents with ADHD may be anatomically configured to respond impulsively to the automatic significance of stimulus input without having the neural organization to regulate and inhibit these responses. These findings provide a novel addition to our current understanding of the ADHD connectome. PMID:27824356

An Integrated Neuroscience and Engineering Approach to Classifying Human Brain-States

DTIC Science & Technology

2015-12-22

AFRL-AFOSR-VA-TR-2016-0037 An Integrated Neuroscience and Engineering Approach to Classifying Human Brain-States Adrian Lee UNIVERSITY OF WASHINGTON...to 14-09-2015 4. TITLE AND SUBTITLE An Integrated Neuroscience and Engineering Approach to Classifying Human Brain- States 5a.  CONTRACT NUMBER 5b...specific cognitive states remains elusive, owing perhaps to limited crosstalk between the fields of neuroscience and engineering. Here, we report a

Differences between brain mass and body weight scaling to height: potential mechanism of reduced mass-specific resting energy expenditure of taller adults.

PubMed

Heymsfield, Steven B; Chirachariyavej, Thamrong; Rhyu, Im Joo; Roongpisuthipong, Chulaporn; Heo, Moonseong; Pietrobelli, Angelo

2009-01-01

Adult resting energy expenditure (REE) scales as height( approximately 1.5), whereas body weight (BW) scales as height( approximately 2). Mass-specific REE (i.e., REE/BW) is thus lower in tall subjects compared with their shorter counterparts, the mechanism of which is unknown. We evaluated the hypothesis that high-metabolic-rate brain mass scales to height with a power significantly less than that of BW, a theory that if valid would provide a potential mechanism for height-related REE effects. The hypothesis was tested by measuring brain mass on a large (n = 372) postmortem sample of Thai men. Since brain mass-body size relations may be influenced by age, the hypothesis was secondarily explored in Thai men age < or =45 yr (n = 299) and with brain magnetic resonance imaging (MRI) studies in Korean men (n = 30) age > or =20<30 yr. The scaling of large body compartments was examined in a third group of Asian men living in New York (NY, n = 28) with MRI and dual-energy X-ray absorptiometry. Brain mass scaled to height with a power (mean +/- SEE; 0.46 +/- 0.13) significantly smaller (P < 0.001) than that of BW scaled to height (2.36 +/- 0.19) in the whole group of Thai men; brain mass/BW scaled negatively to height (-1.94 +/- 0.20, P < 0.001). Similar results were observed in younger Thai men, and results for brain mass/BW vs. height were directionally the same (P = 0.09) in Korean men. Skeletal muscle and bone scaled to height with powers similar to that of BW (i.e., approximately 2-3) in the NY Asian men. Models developed using REE estimates in Thai men suggest that brain accounts for most of the REE/BW height dependency. Tall and short men thus differ in relative brain mass, but the proportions of BW as large compartments appear independent of height, observations that provide a potential mechanistic basis for related differences in REE and that have implications for the study of adult energy requirements.

Abnormal white matter integrity in chronic users of codeine-containing cough syrups: a tract-based spatial statistics study.

PubMed

Qiu, Y-W; Su, H-H; Lv, X-F; Jiang, G-H

2015-01-01

Codeine-containing cough syrups have become one of the most popular drugs of abuse in young people in the world. Chronic codeine-containing cough syrup abuse is related to impairments in a broad range of cognitive functions. However, the potential brain white matter impairment caused by chronic codeine-containing cough syrup abuse has not been reported previously. Our aim was to investigate abnormalities in the microstructure of brain white matter in chronic users of codeine-containing syrups and to determine whether these WM abnormalities are related to the duration of the use these syrups and clinical impulsivity. Thirty chronic codeine-containing syrup users and 30 matched controls were evaluated. Diffusion tensor imaging was performed by using a single-shot spin-echo-planar sequence. Whole-brain voxelwise analysis of fractional anisotropy was performed by using tract-based spatial statistics to localize abnormal WM regions. The Barratt Impulsiveness Scale 11 was surveyed to assess participants' impulsivity. Volume-of-interest analysis was used to detect changes of diffusivity indices in regions with fractional anisotropy abnormalities. Abnormal fractional anisotropy was extracted and correlated with clinical impulsivity and the duration of codeine-containing syrup use. Chronic codeine-containing syrup users had significantly lower fractional anisotropy in the inferior fronto-occipital fasciculus of the bilateral temporo-occipital regions, right frontal region, and the right corona radiata WM than controls. There were significant negative correlations among fractional anisotropy values of the right frontal region of the inferior fronto-occipital fasciculus and the right superior corona radiata WM and Barratt Impulsiveness Scale total scores, and between the right frontal region of the inferior fronto-occipital fasciculus and nonplan impulsivity scores in chronic codeine-containing syrup users. There was also a significant negative correlation between fractional anisotropy values of the right frontal region of the inferior fronto-occipital fasciculus and the duration of codeine-containing syrup use in chronic users. Chronic codeine-containing syrup abuse may be associated with disruptions in brain WM integrity. These WM microstructural deficits may be linked to higher impulsivity in chronic codeine-containing syrup users. © 2015 by American Journal of Neuroradiology.

Capture of fixation by rotational flow; a deterministic hypothesis regarding scaling and stochasticity in fixational eye movements

PubMed Central

Wilkinson, Nicholas M.; Metta, Giorgio

2014-01-01

Visual scan paths exhibit complex, stochastic dynamics. Even during visual fixation, the eye is in constant motion. Fixational drift and tremor are thought to reflect fluctuations in the persistent neural activity of neural integrators in the oculomotor brainstem, which integrate sequences of transient saccadic velocity signals into a short term memory of eye position. Despite intensive research and much progress, the precise mechanisms by which oculomotor posture is maintained remain elusive. Drift exhibits a stochastic statistical profile which has been modeled using random walk formalisms. Tremor is widely dismissed as noise. Here we focus on the dynamical profile of fixational tremor, and argue that tremor may be a signal which usefully reflects the workings of oculomotor postural control. We identify signatures reminiscent of a certain flavor of transient neurodynamics; toric traveling waves which rotate around a central phase singularity. Spiral waves play an organizational role in dynamical systems at many scales throughout nature, though their potential functional role in brain activity remains a matter of educated speculation. Spiral waves have a repertoire of functionally interesting dynamical properties, including persistence, which suggest that they could in theory contribute to persistent neural activity in the oculomotor postural control system. Whilst speculative, the singularity hypothesis of oculomotor postural control implies testable predictions, and could provide the beginnings of an integrated dynamical framework for eye movements across scales. PMID:24616670

3D Data Mapping and Real-Time Experiment Control and Visualization in Brain Slices.

PubMed

Navarro, Marco A; Hibbard, Jaime V K; Miller, Michael E; Nivin, Tyler W; Milescu, Lorin S

2015-10-20

Here, we propose two basic concepts that can streamline electrophysiology and imaging experiments in brain slices and enhance data collection and analysis. The first idea is to interface the experiment with a software environment that provides a 3D scene viewer in which the experimental rig, the brain slice, and the recorded data are represented to scale. Within the 3D scene viewer, the user can visualize a live image of the sample and 3D renderings of the recording electrodes with real-time position feedback. Furthermore, the user can control the instruments and visualize their status in real time. The second idea is to integrate multiple types of experimental data into a spatial and temporal map of the brain slice. These data may include low-magnification maps of the entire brain slice, for spatial context, or any other type of high-resolution structural and functional image, together with time-resolved electrical and optical signals. The entire data collection can be visualized within the 3D scene viewer. These concepts can be applied to any other type of experiment in which high-resolution data are recorded within a larger sample at different spatial and temporal coordinates. Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Accurate and robust brain image alignment using boundary-based registration.

PubMed

Greve, Douglas N; Fischl, Bruce

2009-10-15

The fine spatial scales of the structures in the human brain represent an enormous challenge to the successful integration of information from different images for both within- and between-subject analysis. While many algorithms to register image pairs from the same subject exist, visual inspection shows that their accuracy and robustness to be suspect, particularly when there are strong intensity gradients and/or only part of the brain is imaged. This paper introduces a new algorithm called Boundary-Based Registration, or BBR. The novelty of BBR is that it treats the two images very differently. The reference image must be of sufficient resolution and quality to extract surfaces that separate tissue types. The input image is then aligned to the reference by maximizing the intensity gradient across tissue boundaries. Several lower quality images can be aligned through their alignment with the reference. Visual inspection and fMRI results show that BBR is more accurate than correlation ratio or normalized mutual information and is considerably more robust to even strong intensity inhomogeneities. BBR also excels at aligning partial-brain images to whole-brain images, a domain in which existing registration algorithms frequently fail. Even in the limit of registering a single slice, we show the BBR results to be robust and accurate.

A review and empirical study of the composite scales of the Das-Naglieri cognitive assessment system.

PubMed

McCrea, Simon M

2009-01-01

Alexander Luria's model of the working brain consisting of three functional units was formulated through the examination of hundreds of focal brain-injury patients. Several psychometric instruments based on Luria's syndrome analysis and accompanying qualitative tasks have been developed since the 1970s. In the mid-1970s, JP Das and colleagues defined a specific cognitive processes model based directly on Luria's two coding units termed simultaneous and successive by studying diverse cross-cultural, ability, and socioeconomic strata. The cognitive assessment system is based on the PASS model of cognitive processes and consists of four composite scales of Planning-Attention-Simultaneous-Successive (PASS) devised by Naglieri and Das in 1997. Das and colleagues developed the two new scales of planning and attention to more closely model Luria's theory of higher cortical functions. In this paper a theoretical review of Luria's theory, Das and colleagues elaboration of Luria's model, and the neural correlates of PASS composite scales based on extant studies is summarized. A brief empirical study of the neuropsychological specificity of the PASS composite scales in a sample of 33 focal cortical stroke patients using cluster analysis is then discussed. Planning and simultaneous were sensitive to right hemisphere lesions. These findings were integrated with recent functional neuroimaging studies of PASS scales. In sum it was found that simultaneous is strongly dependent on dual bilateral occipitoparietal interhemispheric coordination whereas successive demonstrated left frontotemporal specificity with some evidence of interhemispheric coordination across the prefrontal cortex. Hence, support for the validity of the PASS composite scales was found as well as for the axiom of the independence of code content from code type originally specified in 1994 by Das, Naglieri, and Kirby.

A review and empirical study of the composite scales of the Das–Naglieri cognitive assessment system

PubMed Central

McCrea, Simon M

2009-01-01

Alexander Luria’s model of the working brain consisting of three functional units was formulated through the examination of hundreds of focal brain-injury patients. Several psychometric instruments based on Luria’s syndrome analysis and accompanying qualitative tasks have been developed since the 1970s. In the mid-1970s, JP Das and colleagues defined a specific cognitive processes model based directly on Luria’s two coding units termed simultaneous and successive by studying diverse cross-cultural, ability, and socioeconomic strata. The cognitive assessment system is based on the PASS model of cognitive processes and consists of four composite scales of Planning–Attention–Simultaneous–Successive (PASS) devised by Naglieri and Das in 1997. Das and colleagues developed the two new scales of planning and attention to more closely model Luria’s theory of higher cortical functions. In this paper a theoretical review of Luria’s theory, Das and colleagues elaboration of Luria’s model, and the neural correlates of PASS composite scales based on extant studies is summarized. A brief empirical study of the neuropsychological specificity of the PASS composite scales in a sample of 33 focal cortical stroke patients using cluster analysis is then discussed. Planning and simultaneous were sensitive to right hemisphere lesions. These findings were integrated with recent functional neuroimaging studies of PASS scales. In sum it was found that simultaneous is strongly dependent on dual bilateral occipitoparietal interhemispheric coordination whereas successive demonstrated left frontotemporal specificity with some evidence of interhemispheric coordination across the prefrontal cortex. Hence, support for the validity of the PASS composite scales was found as well as for the axiom of the independence of code content from code type originally specified in 1994 by Das, Naglieri, and Kirby. PMID:22110322

Whole brain diffeomorphic metric mapping via integration of sulcal and gyral curves, cortical surfaces, and images

PubMed Central

Du, Jia; Younes, Laurent; Qiu, Anqi

2011-01-01

This paper introduces a novel large deformation diffeomorphic metric mapping algorithm for whole brain registration where sulcal and gyral curves, cortical surfaces, and intensity images are simultaneously carried from one subject to another through a flow of diffeomorphisms. To the best of our knowledge, this is the first time that the diffeomorphic metric from one brain to another is derived in a shape space of intensity images and point sets (such as curves and surfaces) in a unified manner. We describe the Euler–Lagrange equation associated with this algorithm with respect to momentum, a linear transformation of the velocity vector field of the diffeomorphic flow. The numerical implementation for solving this variational problem, which involves large-scale kernel convolution in an irregular grid, is made feasible by introducing a class of computationally friendly kernels. We apply this algorithm to align magnetic resonance brain data. Our whole brain mapping results show that our algorithm outperforms the image-based LDDMM algorithm in terms of the mapping accuracy of gyral/sulcal curves, sulcal regions, and cortical and subcortical segmentation. Moreover, our algorithm provides better whole brain alignment than combined volumetric and surface registration (Postelnicu et al., 2009) and hierarchical attribute matching mechanism for elastic registration (HAMMER) (Shen and Davatzikos, 2002) in terms of cortical and subcortical volume segmentation. PMID:21281722

Poor Brain Growth in Extremely Preterm Neonates Long Before the Onset of Autism Spectrum Disorder Symptoms.

PubMed

Padilla, Nelly; Eklöf, Eva; Mårtensson, Gustaf E; Bölte, Sven; Lagercrantz, Hugo; Ådén, Ulrika

2017-02-01

Preterm infants face an increased risk of autism spectrum disorder (ASD). The relationship between autism during childhood and early brain development remains unexplored. We studied 84 preterm children born at <27 weeks of gestation, who underwent neonatal magnetic resonance imaging (MRI) at term and were screened for ASD at 6.5 years. Full-scale intelligence quotient was measured and neonatal morbidities were recorded. Structural brain morphometric studies were performed in 33 infants with high-quality MRI and no evidence of focal brain lesions. Twenty-three (27.4%) of the children tested ASD positive and 61 (72.6%) tested ASD negative. The ASD-positive group had a significantly higher frequency of neonatal complications than the ASD-negative group. In the subgroup of 33 children, the ASD infants had reduced volumes in the temporal, occipital, insular, and limbic regions and in the brain areas involved in social/behavior and salience integration. This study shows that the neonatal MRI scans of extremely preterm children, subsequently diagnosed with ASD at 6.5 years, showed brain structural alterations, localized in the regions that play a key role in the core features of autism. Early detection of these structural alterations may allow the early identification and intervention of children at risk of ASD. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The moon illusion and size-distance scaling--evidence for shared neural patterns.

PubMed

Weidner, Ralph; Plewan, Thorsten; Chen, Qi; Buchner, Axel; Weiss, Peter H; Fink, Gereon R

2014-08-01

A moon near to the horizon is perceived larger than a moon at the zenith, although--obviously--the moon does not change its size. In this study, the neural mechanisms underlying the "moon illusion" were investigated using a virtual 3-D environment and fMRI. Illusory perception of an increased moon size was associated with increased neural activity in ventral visual pathway areas including the lingual and fusiform gyri. The functional role of these areas was further explored in a second experiment. Left V3v was found to be involved in integrating retinal size and distance information, thus indicating that the brain regions that dynamically integrate retinal size and distance play a key role in generating the moon illusion.

The application of integrated knowledge-based systems for the Biomedical Risk Assessment Intelligent Network (BRAIN)

NASA Technical Reports Server (NTRS)

Loftin, Karin C.; Ly, Bebe; Webster, Laurie; Verlander, James; Taylor, Gerald R.; Riley, Gary; Culbert, Chris

1992-01-01

One of NASA's goals for long duration space flight is to maintain acceptable levels of crew health, safety, and performance. One way of meeting this goal is through BRAIN, an integrated network of both human and computer elements. BRAIN will function as an advisor to mission managers by assessing the risk of inflight biomedical problems and recommending appropriate countermeasures. Described here is a joint effort among various NASA elements to develop BRAIN and the Infectious Disease Risk Assessment (IDRA) prototype. The implementation of this effort addresses the technological aspects of knowledge acquisition, integration of IDRA components, the use of expert systems to automate the biomedical prediction process, development of a user friendly interface, and integration of IDRA and ExerCISys systems. Because C language, CLIPS and the X-Window System are portable and easily integrated, they were chosen ss the tools for the initial IDRA prototype.

Analysis of the characteristics of the synchronous clusters in the adaptive Kuramoto network and neural network of the epileptic brain

NASA Astrophysics Data System (ADS)

Hramov, Alexander E.; Kharchenko, Alexander A.; Makarov, Vladimir V.; Khramova, Marina V.; Koronovskii, Alexey A.; Pavlov, Alexey N.; Dana, Syamal K.

2016-04-01

In the paper we study the mechanisms of phase synchronization in the adaptive model network of Kuramoto oscillators and the neural network of brain by consideration of the integral characteristics of the observed networks signals. As the integral characteristics of the model network we consider the summary signal produced by the oscillators. Similar to the model situation we study the ECoG signal as the integral characteristic of neural network of the brain. We show that the establishment of the phase synchronization results in the increase of the peak, corresponding to synchronized oscillators, on the wavelet energy spectrum of the integral signals. The observed correlation between the phase relations of the elements and the integral characteristics of the whole network open the way to detect the size of synchronous clusters in the neural networks of the epileptic brain before and during seizure.

Losing protein in the brain: the case of progranulin.

PubMed

Ghidoni, Roberta; Paterlini, Anna; Albertini, Valentina; Binetti, Giuliano; Benussi, Luisa

2012-10-02

It is well known that progranulin protein is involved in wound repair, inflammation, and tumor formation. The wedding between progranulin and brain was celebrated in 2006 with the involvement of progranulin gene (GRN) in Frontotemporal lobar degeneration (FTLD), the most common form of early-onset dementia: up to date, 75 mutations have been detected in FTLD patients as well as in patients with widely variable clinical phenotypes. All pathogenic GRN mutations identified thus far cause the disease through a uniform mechanism, i.e. loss of functional progranulin or haploinsufficiency. Studies on GRN knockout mice suggest that progranulin-related neurodegenerative diseases may result from lifetime depletion of neurotrophic support together with cumulative damage in association with dysregulated inflammation, thus highlighting possible new molecular targets for GRN-related FTLD treatment. Recently, the dosage of plasma progranulin has been proposed as a useful tool for a quick and inexpensive large-scale screening of affected and unaffected carriers of GRN mutations. Before it is systematically translated into clinical practice and, more importantly, included into diagnostic criteria for dementias, further standardization of plasma progranulin test and harmonization of its use are required. Once a specific treatment becomes available for these pathologies, this test - being applicable on large scale - will represent an important step towards personalized healthcare. This article is part of a Special Issue entitled: Brain Integration. Copyright © 2012 Elsevier B.V. All rights reserved.

Connectivity and functional profiling of abnormal brain structures in pedophilia

PubMed Central

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

2015-01-01

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

Connectivity and functional profiling of abnormal brain structures in pedophilia.

PubMed

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

2015-06-01

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

Differences in MMPI-2 FBS and RBS scores in brain injury, probable malingering, and conversion disorder groups: a preliminary study.

PubMed

Peck, C P; Schroeder, R W; Heinrichs, R J; Vondran, E J; Brockman, C J; Webster, B K; Baade, L E

2013-01-01

This study examined differences in raw scores on the Symptom Validity Scale and Response Bias Scale (RBS) from the Minnesota Multiphasic Personality Inventory-2 in three criterion groups: (i) valid traumatic brain injured, (ii) invalid traumatic brain injured, and (iii) psychogenic non-epileptic seizure disorders. Results indicate that a >30 raw score cutoff for the Symptom Validity Scale accurately identified 50% of the invalid traumatic brain injured group, while misclassifying none of the valid traumatic brain injured group and 6% of the psychogenic non-epileptic seizure disorder group. Using a >15 RBS raw cutoff score accurately classified 50% of the invalid traumatic brain injured group and misclassified fewer than 10% of the valid traumatic brain injured and psychogenic non-epileptic seizure disorder groups. These cutoff scores used conjunctively did not misclassify any members of the psychogenic non-epileptic seizure disorder or valid traumatic brain injured groups, while accurately classifying 44% of the invalid traumatic brain injured individuals. Findings from this preliminary study suggest that the conjunctive use of the Symptom Validity Scale and the RBS from the Minnesota Multiphasic Personality Inventory-2 may be useful in differentiating probable malingering from individuals with brain injuries and conversion disorders.

Effects of amyloid and small vessel disease on white matter network disruption.

PubMed

Kim, Hee Jin; Im, Kiho; Kwon, Hunki; Lee, Jong Min; Ye, Byoung Seok; Kim, Yeo Jin; Cho, Hanna; Choe, Yearn Seong; Lee, Kyung Han; Kim, Sung Tae; Kim, Jae Seung; Lee, Jae Hong; Na, Duk L; Seo, Sang Won

2015-01-01

There is growing evidence that the human brain is a large scale complex network. The structural network is reported to be disrupted in cognitively impaired patients. However, there have been few studies evaluating the effects of amyloid and small vessel disease (SVD) markers, the common causes of cognitive impairment, on structural networks. Thus, we evaluated the association between amyloid and SVD burdens and structural networks using diffusion tensor imaging (DTI). Furthermore, we determined if network parameters predict cognitive impairments. Graph theoretical analysis was applied to DTI data from 232 cognitively impaired patients with varying degrees of amyloid and SVD burdens. All patients underwent Pittsburgh compound-B (PiB) PET to detect amyloid burden, MRI to detect markers of SVD, including the volume of white matter hyperintensities and the number of lacunes, and detailed neuropsychological testing. The whole-brain network was assessed by network parameters of integration (shortest path length, global efficiency) and segregation (clustering coefficient, transitivity, modularity). PiB retention ratio was not associated with any white matter network parameters. Greater white matter hyperintensity volumes or lacunae numbers were significantly associated with decreased network integration (increased shortest path length, decreased global efficiency) and increased network segregation (increased clustering coefficient, increased transitivity, increased modularity). Decreased network integration or increased network segregation were associated with poor performances in attention, language, visuospatial, memory, and frontal-executive functions. Our results suggest that SVD alters white matter network integration and segregation, which further predicts cognitive dysfunction.

Brain/MINDS: brain-mapping project in Japan

PubMed Central

Okano, Hideyuki; Miyawaki, Atsushi; Kasai, Kiyoto

2015-01-01

There is an emerging interest in brain-mapping projects in countries across the world, including the USA, Europe, Australia and China. In 2014, Japan started a brain-mapping project called Brain Mapping by Integrated Neurotechnologies for Disease Studies (Brain/MINDS). Brain/MINDS aims to map the structure and function of neuronal circuits to ultimately understand the vast complexity of the human brain, and takes advantage of a unique non-human primate animal model, the common marmoset (Callithrix jacchus). In Brain/MINDS, the RIKEN Brain Science Institute acts as a central institute. The objectives of Brain/MINDS can be categorized into the following three major subject areas: (i) structure and functional mapping of a non-human primate brain (the marmoset brain); (ii) development of innovative neurotechnologies for brain mapping; and (iii) human brain mapping; and clinical research. Brain/MINDS researchers are highly motivated to identify the neuronal circuits responsible for the phenotype of neurological and psychiatric disorders, and to understand the development of these devastating disorders through the integration of these three subject areas. PMID:25823872

Community integration 2 years after moderate and severe traumatic brain injury.

PubMed

Sandhaug, Maria; Andelic, Nada; Langhammer, Birgitta; Mygland, Aase

2015-01-01

The aim of this study was to examine community integration by the Community Integration Questionnaire (CIQ) 2 years after injury in a divided TBI sample of moderately and severely injured patients. The second aim was to identify social-demographic, injury-related and rehabilitation associated predictors of CIQ. A cohort study. Outpatient follow-up. Fifty-seven patients with moderate (n = 21) or severe (n = 36) TBI were examined with the Community Integration Questionnaire (CIQ) at 2 years after injury. Possible predictors were analysed in a regression model using CIQ total score at 2 years as the outcome measure. The Community Integration Questionnaire. At 2 years follow-up, there was significant difference between the moderately and severely injured patients in the productivity scores (p < 0.003), while difference in the total CIQ scores approached the significance level (p = 0.074). Significant predictors of a higher CIQ score were living with a spouse, higher Glasgow Coma Scale (GCS) in the acute phase, shorter Post-Traumatic Amnesia (PTA), longer rehabilitation stay (LOS) and use of rehabilitation service. Use of rehabilitation service (B = 7.766) and living with a spouse (B = 4.251) had the largest influence. This means that living with a spouse, better score on the GCS scale, shorter PTA, longer LOS and use of rehabilitation service after discharge equated to better community integration 2 years after TBI Conclusions: Two years after TBI the moderately injured patients have a higher productivity level than the severely injured patients. Marital status, injury severity and rehabilitation after injury were associated with community integration 2 years after TBI.

Updated Neuronal Scaling Rules for the Brains of Glires (Rodents/Lagomorphs)

PubMed Central

Herculano-Houzel, Suzana; Ribeiro, Pedro; Campos, Leandro; Valotta da Silva, Alexandre; Torres, Laila B.; Catania, Kenneth C.; Kaas, Jon H.

2011-01-01

Brain size scales as different functions of its number of neurons across mammalian orders such as rodents, primates, and insectivores. In rodents, we have previously shown that, across a sample of 6 species, from mouse to capybara, the cerebral cortex, cerebellum and the remaining brain structures increase in size faster than they gain neurons, with an accompanying decrease in neuronal density in these structures [Herculano-Houzel et al.: Proc Natl Acad Sci USA 2006;103:12138–12143]. Important remaining questions are whether such neuronal scaling rules within an order apply equally to all pertaining species, and whether they extend to closely related taxa. Here, we examine whether 4 other species of Rodentia, as well as the closely related rabbit (Lagomorpha), conform to the scaling rules identified previously for rodents. We report the updated neuronal scaling rules obtained for the average values of each species in a way that is directly comparable to the scaling rules that apply to primates [Gabi et al.: Brain Behav Evol 2010;76:32–44], and examine whether the scaling relationships are affected when phylogenetic relatedness in the dataset is accounted for. We have found that the brains of the spiny rat, squirrel, prairie dog and rabbit conform to the neuronal scaling rules that apply to the previous sample of rodents. The conformity to the previous rules of the new set of species, which includes the rabbit, suggests that the cellular scaling rules we have identified apply to rodents in general, and probably to Glires as a whole (rodents/lagomorphs), with one notable exception: the naked mole-rat brain is apparently an outlier, with only about half of the neurons expected from its brain size in its cerebral cortex and cerebellum. PMID:21985803

Preoperative three-dimensional model creation of magnetic resonance brain images as a tool to assist neurosurgical planning.

PubMed

Spottiswoode, B S; van den Heever, D J; Chang, Y; Engelhardt, S; Du Plessis, S; Nicolls, F; Hartzenberg, H B; Gretschel, A

2013-01-01

Neurosurgeons regularly plan their surgery using magnetic resonance imaging (MRI) images, which may show a clear distinction between the area to be resected and the surrounding healthy brain tissue depending on the nature of the pathology. However, this distinction is often unclear with the naked eye during the surgical intervention, and it may be difficult to infer depth and an accurate volumetric interpretation from a series of MRI image slices. In this work, MRI data are used to create affordable patient-specific 3-dimensional (3D) scale models of the brain which clearly indicate the location and extent of a tumour relative to brain surface features and important adjacent structures. This is achieved using custom software and rapid prototyping. In addition, functionally eloquent areas identified using functional MRI are integrated into the 3D models. Preliminary in vivo results are presented for 2 patients. The accuracy of the technique was estimated both theoretically and by printing a geometrical phantom, with mean dimensional errors of less than 0.5 mm observed. This may provide a practical and cost-effective tool which can be used for training, and during neurosurgical planning and intervention. Copyright © 2013 S. Karger AG, Basel.

Role of local network oscillations in resting-state functional connectivity.

PubMed

Cabral, Joana; Hugues, Etienne; Sporns, Olaf; Deco, Gustavo

2011-07-01

Spatio-temporally organized low-frequency fluctuations (<0.1 Hz), observed in BOLD fMRI signal during rest, suggest the existence of underlying network dynamics that emerge spontaneously from intrinsic brain processes. Furthermore, significant correlations between distinct anatomical regions-or functional connectivity (FC)-have led to the identification of several widely distributed resting-state networks (RSNs). This slow dynamics seems to be highly structured by anatomical connectivity but the mechanism behind it and its relationship with neural activity, particularly in the gamma frequency range, remains largely unknown. Indeed, direct measurements of neuronal activity have revealed similar large-scale correlations, particularly in slow power fluctuations of local field potential gamma frequency range oscillations. To address these questions, we investigated neural dynamics in a large-scale model of the human brain's neural activity. A key ingredient of the model was a structural brain network defined by empirically derived long-range brain connectivity together with the corresponding conduction delays. A neural population, assumed to spontaneously oscillate in the gamma frequency range, was placed at each network node. When these oscillatory units are integrated in the network, they behave as weakly coupled oscillators. The time-delayed interaction between nodes is described by the Kuramoto model of phase oscillators, a biologically-based model of coupled oscillatory systems. For a realistic setting of axonal conduction speed, we show that time-delayed network interaction leads to the emergence of slow neural activity fluctuations, whose patterns correlate significantly with the empirically measured FC. The best agreement of the simulated FC with the empirically measured FC is found for a set of parameters where subsets of nodes tend to synchronize although the network is not globally synchronized. Inside such clusters, the simulated BOLD signal between nodes is found to be correlated, instantiating the empirically observed RSNs. Between clusters, patterns of positive and negative correlations are observed, as described in experimental studies. These results are found to be robust with respect to a biologically plausible range of model parameters. In conclusion, our model suggests how resting-state neural activity can originate from the interplay between the local neural dynamics and the large-scale structure of the brain. Copyright © 2011 Elsevier Inc. All rights reserved.

Reconfiguration of Brain Network Architectures between Resting-State and Complexity-Dependent Cognitive Reasoning.

PubMed

Hearne, Luke J; Cocchi, Luca; Zalesky, Andrew; Mattingley, Jason B

2017-08-30

Our capacity for higher cognitive reasoning has a measurable limit. This limit is thought to arise from the brain's capacity to flexibly reconfigure interactions between spatially distributed networks. Recent work, however, has suggested that reconfigurations of task-related networks are modest when compared with intrinsic "resting-state" network architecture. Here we combined resting-state and task-driven functional magnetic resonance imaging to examine how flexible, task-specific reconfigurations associated with increasing reasoning demands are integrated within a stable intrinsic brain topology. Human participants (21 males and 28 females) underwent an initial resting-state scan, followed by a cognitive reasoning task involving different levels of complexity, followed by a second resting-state scan. The reasoning task required participants to deduce the identity of a missing element in a 4 × 4 matrix, and item difficulty was scaled parametrically as determined by relational complexity theory. Analyses revealed that external task engagement was characterized by a significant change in functional brain modules. Specifically, resting-state and null-task demand conditions were associated with more segregated brain-network topology, whereas increases in reasoning complexity resulted in merging of resting-state modules. Further increments in task complexity did not change the established modular architecture, but affected selective patterns of connectivity between frontoparietal, subcortical, cingulo-opercular, and default-mode networks. Larger increases in network efficiency within the newly established task modules were associated with higher reasoning accuracy. Our results shed light on the network architectures that underlie external task engagement, and highlight selective changes in brain connectivity supporting increases in task complexity. SIGNIFICANCE STATEMENT Humans have clear limits in their ability to solve complex reasoning problems. It is thought that such limitations arise from flexible, moment-to-moment reconfigurations of functional brain networks. It is less clear how such task-driven adaptive changes in connectivity relate to stable, intrinsic networks of the brain and behavioral performance. We found that increased reasoning demands rely on selective patterns of connectivity within cortical networks that emerged in addition to a more general, task-induced modular architecture. This task-driven architecture reverted to a more segregated resting-state architecture both immediately before and after the task. These findings reveal how flexibility in human brain networks is integral to achieving successful reasoning performance across different levels of cognitive demand. Copyright © 2017 the authors 0270-6474/17/378399-13$15.00/0.

Comparison of seven optical clearing methods for mouse brain

NASA Astrophysics Data System (ADS)

Wan, Peng; Zhu, Jingtan; Yu, Tingting; Zhu, Dan

2018-02-01

Recently, a variety of tissue optical clearing techniques have been developed to reduce light scattering for imaging deeper and three-dimensional reconstruction of tissue structures. Combined with optical imaging techniques and diverse labeling methods, these clearing methods have significantly promoted the development of neuroscience. However, most of the protocols were proposed aiming for specific tissue type. Though there are some comparison results, the clearing methods covered are limited and the evaluation indices are lack of uniformity, which made it difficult to select a best-fit protocol for clearing in practical applications. Hence, it is necessary to systematically assess and compare these clearing methods. In this work, we evaluated the performance of seven typical clearing methods, including 3DISCO, uDISCO, SeeDB, ScaleS, ClearT2, CUBIC and PACT, on mouse brain samples. First, we compared the clearing capability on both brain slices and whole-brains by observing brain transparency. Further, we evaluated the fluorescence preservation and the increase of imaging depth. The results showed that 3DISCO, uDISCO and PACT posed excellent clearing capability on mouse brains, ScaleS and SeeDB rendered moderate transparency, while ClearT2 was the worst. Among those methods, ScaleS was the best on fluorescence preservation, and PACT achieved the highest increase of imaging depth. This study is expected to provide important reference for users in choosing most suitable brain optical clearing method.

Executive functioning in TBI from rehabilitation to social reintegration: COMPASS (goal,) a randomized controlled trial (grant: 1I01RX000637-01A3 by the VA ORD RR&D, 2013-2016).

PubMed

Libin, Alexander V; Scholten, Joel; Schladen, Manon Maitland; Danford, Ellen; Shara, Nawar; Penk, Walter; Grafman, Jordan; Resnik, Linda; Bruner, Dwan; Cichon, Samantha; Philmon, Miriam; Tsai, Brenda; Blackman, Marc; Dromerick, Alexander

2015-01-01

Traumatic brain injury is a major health problem that frequently leads to deficits in executive function. Self-regulation processes, such as goal-setting, may become disordered after traumatic brain injury, particularly when the frontal regions of the brain and their connections are involved. Such impairments reduce injured veterans' ability to return to work or school and to regain satisfactory personal lives. Understanding the neurologically disabling effects of brain injury on executive function is necessary for both the accurate diagnosis of impairment and the individual tailoring of rehabilitation processes to help returning service members recover independent function. The COMPASS(goal) (Community Participation through Self-Efficacy Skills Development) program develops and tests a novel patient-centered intervention framework for community re-integration psychosocial research in veterans with mild traumatic brain injury. COMPASS(goal) integrates the principles and best practices of goal self-management. Goal setting is a core skill in self-management training by which persons with chronic health conditions learn to improve their status and decrease symptom effects. Over a three-year period, COMPASS(goal) will recruit 110 participants with residual executive dysfunction three months or more post-injury. Inclusion criteria combine both clinical diagnosis and standardized scores that are >1 SD from the normative score on the Frontal Systems Rating Scale. Participants are randomized into two groups: goal-management (intervention) and supported discharge (control). The intervention is administered in eight consecutive, weekly sessions. Assessments occur at enrollment, post-intervention/supported discharge, and three months post-treatment follow-up. Goal management is part of the "natural language" of rehabilitation. However, collaborative goal-setting between clinicians/case managers and clients can be hindered by the cognitive deficits that follow brain injury. Re-training returning veterans with brain injury in goal management, with appropriate help and support, would essentially treat deficits in executive function. A structured approach to goal self-management may foster greater independence and self-efficacy, help veterans gain insight into goals that are realistic for them at a given time, and help clinicians and veterans to work more effectively as true collaborators.

Integration of Brain and Skull in Prenatal Mouse Models of Apert and Crouzon Syndromes

PubMed Central

Motch Perrine, Susan M.; Stecko, Tim; Neuberger, Thomas; Jabs, Ethylin W.; Ryan, Timothy M.; Richtsmeier, Joan T.

2017-01-01

The brain and skull represent a complex arrangement of integrated anatomical structures composed of various cell and tissue types that maintain structural and functional association throughout development. Morphological integration, a concept developed in vertebrate morphology and evolutionary biology, describes the coordinated variation of functionally and developmentally related traits of organisms. Syndromic craniosynostosis is characterized by distinctive changes in skull morphology and perceptible, though less well studied, changes in brain structure and morphology. Using mouse models for craniosynostosis conditions, our group has precisely defined how unique craniosynostosis causing mutations in fibroblast growth factor receptors affect brain and skull morphology and dysgenesis involving coordinated tissue-specific effects of these mutations. Here we examine integration of brain and skull in two mouse models for craniosynostosis: one carrying the FGFR2c C342Y mutation associated with Pfeiffer and Crouzon syndromes and a mouse model carrying the FGFR2 S252W mutation, one of two mutations responsible for two-thirds of Apert syndrome cases. Using linear distances estimated from three-dimensional coordinates of landmarks acquired from dual modality imaging of skull (high resolution micro-computed tomography and magnetic resonance microscopy) of mice at embryonic day 17.5, we confirm variation in brain and skull morphology in Fgfr2cC342Y/+ mice, Fgfr2+/S252W mice, and their unaffected littermates. Mutation-specific variation in neural and cranial tissue notwithstanding, patterns of integration of brain and skull differed only subtly between mice carrying either the FGFR2c C342Y or the FGFR2 S252W mutation and their unaffected littermates. However, statistically significant and substantial differences in morphological integration of brain and skull were revealed between the two mutant mouse models, each maintained on a different strain. Relative to the effects of disease-associated mutations, our results reveal a stronger influence of the background genome on patterns of brain-skull integration and suggest robust genetic, developmental, and evolutionary relationships between neural and skeletal tissues of the head. PMID:28790902

An allometric scaling relationship in the brain of preterm infants

PubMed Central

Paul, Rachel A; Smyser, Christopher D; Rogers, Cynthia E; English, Ian; Wallendorf, Michael; Alexopoulos, Dimitrios; Meyer, Erin J; Van Essen, David C; Neil, Jeffrey J; Inder, Terrie E

2014-01-01

Allometry has been used to demonstrate a power–law scaling relationship in the brain of premature born infants. Forty-nine preterm infants underwent neonatal MRI scans and neurodevelopmental testing at age 2. Measures of cortical surface area and total cerebral volume demonstrated a power–law scaling relationship (α = 1.27). No associations were identified between these measures and investigated clinical variables. Term equivalent cortical surface area and total cerebral volume measures and scaling exponents were not related to outcome. These findings confirm a previously reported allometric scaling relationship in the preterm brain, and suggest that scaling is not a sensitive indicator of aberrant cortical maturation. PMID:25540808

Oculometric Screening for Traumatic Brain Injury in Veterans

DTIC Science & Technology

2017-06-01

Durso, F., & Lee, J. (2015). APA handbook of human systems integration . Washington, DC: The American Psychological Association. Brain Injury Association...Submitted in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE IN HUMAN SYSTEMS INTEGRATION from the NAVAL POSTGRADUATE...PURPOSE ...................................................................................................3 C. HUMAN SYSTEMS INTEGRATION CONSIDERATIONS

What Brain Sciences Reveal about Integrating Theory and Practice

ERIC Educational Resources Information Center

Patton, Michael Quinn

2014-01-01

Theory and practice are integrated in the human brain. Situation recognition and response are key to this integration. Scholars of decision making and expertise have found that people with great expertise are more adept at situational recognition and intentional about their decision-making processes. Several interdisciplinary fields of inquiry…

Performance and Power Optimization for Cognitive Processor Design Using Deep-Submicron Very Large Scale Integration (VLSI) Technology

DTIC Science & Technology

2010-03-01

DATES COVERED (From - To) October 2008 – October 2009 4 . TITLE AND SUBTITLE PERFORMANCE AND POWER OPTIMIZATION FOR COGNITIVE PROCESSOR DESIGN USING...Computations 2  2.2  Cognitive Models and Algorithms for Intelligent Text Recognition 4   2.2.1 Brain-State-in-a-Box Neural Network Model. 4   2.2.2...The ASIC-style design and synthesis flow for FPU 8  Figure 4 : Screen shots of the final layouts 10  Figure 5: Projected performance and power roadmap

Features of spatial and functional segregation and integration of the primate connectome revealed by trade-off between wiring cost and efficiency

PubMed Central

Chen, Yuhan; Wang, Shengjun

2017-01-01

The primate connectome, possessing a characteristic global topology and specific regional connectivity profiles, is well organized to support both segregated and integrated brain function. However, the organization mechanisms shaping the characteristic connectivity and its relationship to functional requirements remain unclear. The primate brain connectome is shaped by metabolic economy as well as functional values. Here, we explored the influence of two competing factors and additional advanced functional requirements on the primate connectome employing an optimal trade-off model between neural wiring cost and the representative functional requirement of processing efficiency. Moreover, we compared this model with a generative model combining spatial distance and topological similarity, with the objective of statistically reproducing multiple topological features of the network. The primate connectome indeed displays a cost-efficiency trade-off and that up to 67% of the connections were recovered by optimal combination of the two basic factors of wiring economy and processing efficiency, clearly higher than the proportion of connections (56%) explained by the generative model. While not explicitly aimed for, the trade-off model captured several key topological features of the real connectome as the generative model, yet better explained the connectivity of most regions. The majority of the remaining 33% of connections unexplained by the best trade-off model were long-distance links, which are concentrated on few cortical areas, termed long-distance connectors (LDCs). The LDCs are mainly non-hubs, but form a densely connected group overlapping on spatially segregated functional modalities. LDCs are crucial for both functional segregation and integration across different scales. These organization features revealed by the optimization analysis provide evidence that the demands of advanced functional segregation and integration among spatially distributed regions may play a significant role in shaping the cortical connectome, in addition to the basic cost-efficiency trade-off. These findings also shed light on inherent vulnerabilities of brain networks in diseases. PMID:28961235

Features of spatial and functional segregation and integration of the primate connectome revealed by trade-off between wiring cost and efficiency.

PubMed

Chen, Yuhan; Wang, Shengjun; Hilgetag, Claus C; Zhou, Changsong

2017-09-01

The primate connectome, possessing a characteristic global topology and specific regional connectivity profiles, is well organized to support both segregated and integrated brain function. However, the organization mechanisms shaping the characteristic connectivity and its relationship to functional requirements remain unclear. The primate brain connectome is shaped by metabolic economy as well as functional values. Here, we explored the influence of two competing factors and additional advanced functional requirements on the primate connectome employing an optimal trade-off model between neural wiring cost and the representative functional requirement of processing efficiency. Moreover, we compared this model with a generative model combining spatial distance and topological similarity, with the objective of statistically reproducing multiple topological features of the network. The primate connectome indeed displays a cost-efficiency trade-off and that up to 67% of the connections were recovered by optimal combination of the two basic factors of wiring economy and processing efficiency, clearly higher than the proportion of connections (56%) explained by the generative model. While not explicitly aimed for, the trade-off model captured several key topological features of the real connectome as the generative model, yet better explained the connectivity of most regions. The majority of the remaining 33% of connections unexplained by the best trade-off model were long-distance links, which are concentrated on few cortical areas, termed long-distance connectors (LDCs). The LDCs are mainly non-hubs, but form a densely connected group overlapping on spatially segregated functional modalities. LDCs are crucial for both functional segregation and integration across different scales. These organization features revealed by the optimization analysis provide evidence that the demands of advanced functional segregation and integration among spatially distributed regions may play a significant role in shaping the cortical connectome, in addition to the basic cost-efficiency trade-off. These findings also shed light on inherent vulnerabilities of brain networks in diseases.

Dendritic integration: 60 years of progress.

PubMed

Stuart, Greg J; Spruston, Nelson

2015-12-01

Understanding how individual neurons integrate the thousands of synaptic inputs they receive is critical to understanding how the brain works. Modeling studies in silico and experimental work in vitro, dating back more than half a century, have revealed that neurons can perform a variety of different passive and active forms of synaptic integration on their inputs. But how are synaptic inputs integrated in the intact brain? With the development of new techniques, this question has recently received substantial attention, with new findings suggesting that many of the forms of synaptic integration observed in vitro also occur in vivo, including in awake animals. Here we review six decades of progress, which collectively highlights the complex ways that single neurons integrate their inputs, emphasizing the critical role of dendrites in information processing in the brain.

Ontology-based approach for in vivo human connectomics: the medial Brodmann area 6 case study

PubMed Central

Moreau, Tristan; Gibaud, Bernard

2015-01-01

Different non-invasive neuroimaging modalities and multi-level analysis of human connectomics datasets yield a great amount of heterogeneous data which are hard to integrate into an unified representation. Biomedical ontologies can provide a suitable integrative framework for domain knowledge as well as a tool to facilitate information retrieval, data sharing and data comparisons across scales, modalities and species. Especially, it is urgently needed to fill the gap between neurobiology and in vivo human connectomics in order to better take into account the reality highlighted in Magnetic Resonance Imaging (MRI) and relate it to existing brain knowledge. The aim of this study was to create a neuroanatomical ontology, called “Human Connectomics Ontology” (HCO), in order to represent macroscopic gray matter regions connected with fiber bundles assessed by diffusion tractography and to annotate MRI connectomics datasets acquired in the living human brain. First a neuroanatomical “view” called NEURO-DL-FMA was extracted from the reference ontology Foundational Model of Anatomy (FMA) in order to construct a gross anatomy ontology of the brain. HCO extends NEURO-DL-FMA by introducing entities (such as “MR_Node” and “MR_Route”) and object properties (such as “tracto_connects”) pertaining to MR connectivity. The Web Ontology Language Description Logics (OWL DL) formalism was used in order to enable reasoning with common reasoning engines. Moreover, an experimental work was achieved in order to demonstrate how the HCO could be effectively used to address complex queries concerning in vivo MRI connectomics datasets. Indeed, neuroimaging datasets of five healthy subjects were annotated with terms of the HCO and a multi-level analysis of the connectivity patterns assessed by diffusion tractography of the right medial Brodmann Area 6 was achieved using a set of queries. This approach can facilitate comparison of data across scales, modalities and species. PMID:25914640

From a meso- to micro-scale connectome: array tomography and mGRASP

PubMed Central

Rah, Jong-Cheol; Feng, Linqing; Druckmann, Shaul; Lee, Hojin; Kim, Jinhyun

2015-01-01

Mapping mammalian synaptic connectivity has long been an important goal of neuroscience because knowing how neurons and brain areas are connected underpins an understanding of brain function. Meeting this goal requires advanced techniques with single synapse resolution and large-scale capacity, especially at multiple scales tethering the meso- and micro-scale connectome. Among several advanced LM-based connectome technologies, Array Tomography (AT) and mammalian GFP-Reconstitution Across Synaptic Partners (mGRASP) can provide relatively high-throughput mapping synaptic connectivity at multiple scales. AT- and mGRASP-assisted circuit mapping (ATing and mGRASPing), combined with techniques such as retrograde virus, brain clearing techniques, and activity indicators will help unlock the secrets of complex neural circuits. Here, we discuss these useful new tools to enable mapping of brain circuits at multiple scales, some functional implications of spatial synaptic distribution, and future challenges and directions of these endeavors. PMID:26089781

[Prognosis in pediatric traumatic brain injury. A dynamic cohort study].

PubMed

Vázquez-Solís, María G; Villa-Manzano, Alberto I; Sánchez-Mosco, Dalia I; Vargas-Lares, José de Jesús; Plascencia-Fernández, Irma

2013-01-01

traumatic brain injury is a main cause of hospital admission and death in children. Our objective was to identify prognostic factors of pediatric traumatic brain injury. this was a dynamic cohort study of traumatic brain injury with 6 months follow-up. The exposition was: mild or moderate/severe traumatic brain injury, searching for prognosis (morbidity-mortality and decreased Glasgow scale). Relative risk and logistic regression was estimated for prognostic factors. we evaluated 440 patients with mild traumatic brain injury and 98 with moderate/severe traumatic brain injury. Morbidity for mild traumatic brain injury was 1 %; for moderate/severe traumatic brain injury, 5 %. There were no deaths. Prognostic factors for moderate/severe traumatic brain injury were associated injuries (RR = 133), fractures (RR = 60), street accidents (RR = 17), night time accidents (RR = 2.3) and weekend accidents (RR = 2). Decreased Glasgow scale was found in 9 %, having as prognostic factors: visible injuries (RR = 3), grown-up supervision (RR = 2.5) and time of progress (RR = 1.6). there should be a prognosis established based on kinetic energy of the injury and not only with Glasgow Scale.

Investigating large-scale brain dynamics using field potential recordings: analysis and interpretation.

PubMed

Pesaran, Bijan; Vinck, Martin; Einevoll, Gaute T; Sirota, Anton; Fries, Pascal; Siegel, Markus; Truccolo, Wilson; Schroeder, Charles E; Srinivasan, Ramesh

2018-06-25

New technologies to record electrical activity from the brain on a massive scale offer tremendous opportunities for discovery. Electrical measurements of large-scale brain dynamics, termed field potentials, are especially important to understanding and treating the human brain. Here, our goal is to provide best practices on how field potential recordings (electroencephalograms, magnetoencephalograms, electrocorticograms and local field potentials) can be analyzed to identify large-scale brain dynamics, and to highlight critical issues and limitations of interpretation in current work. We focus our discussion of analyses around the broad themes of activation, correlation, communication and coding. We provide recommendations for interpreting the data using forward and inverse models. The forward model describes how field potentials are generated by the activity of populations of neurons. The inverse model describes how to infer the activity of populations of neurons from field potential recordings. A recurring theme is the challenge of understanding how field potentials reflect neuronal population activity given the complexity of the underlying brain systems.

Sleep Variability in Adolescence is Associated with Altered Brain Development

PubMed Central

Telzer, Eva H.; Goldenberg, Diane; Fuligni, Andrew J.; Lieberman, Matthew D.; Galvan, Adriana

2015-01-01

Despite the known importance of sleep for brain development, and the sharp increase in poor sleep during adolescence, we know relatively little about how sleep impacts the developing brain. We present the first longitudinal study to examine how sleep during adolescence is associated with white matter integrity. We find that greater variability in sleep duration one year prior to a DTI scan is associated with lower white matter integrity above and beyond the effects of sleep duration, and variability in bedtime, whereas sleep variability a few months prior to the scan is not associated with white matter integrity. Thus, variability in sleep duration during adolescence may have long-term impairments on the developing brain. White matter integrity should be increasing during adolescence, and so sleep variability is directly at odds with normative developmental trends. PMID:26093368

Basic difference between brain and computer: integration of asynchronous processes implemented as hardware model of the retina.

PubMed

Przybyszewski, Andrzej W; Linsay, Paul S; Gaudiano, Paolo; Wilson, Christopher M

2007-01-01

There exists a common view that the brain acts like a Turing machine: The machine reads information from an infinite tape (sensory data) and, on the basis of the machine's state and information from the tape, an action (decision) is made. The main problem with this model lies in how to synchronize a large number of tapes in an adaptive way so that the machine is able to accomplish tasks such as object classification. We propose that such mechanisms exist already in the eye. A popular view is that the retina, typically associated with high gain and adaptation for light processing, is actually performing local preprocessing by means of its center-surround receptive field. We would like to show another property of the retina: The ability to integrate many independent processes. We believe that this integration is implemented by synchronization of neuronal oscillations. In this paper, we present a model of the retina consisting of a series of coupled oscillators which can synchronize on several scales. Synchronization is an analog process which is converted into a digital spike train in the output of the retina. We have developed a hardware implementation of this model, which enables us to carry out rapid simulation of multineuron oscillatory dynamics. We show that the properties of the spike trains in our model are similar to those found in vivo in the cat retina.

A multi-tissue type genome-scale metabolic network for analysis of whole-body systems physiology

PubMed Central

2011-01-01

Background Genome-scale metabolic reconstructions provide a biologically meaningful mechanistic basis for the genotype-phenotype relationship. The global human metabolic network, termed Recon 1, has recently been reconstructed allowing the systems analysis of human metabolic physiology and pathology. Utilizing high-throughput data, Recon 1 has recently been tailored to different cells and tissues, including the liver, kidney, brain, and alveolar macrophage. These models have shown utility in the study of systems medicine. However, no integrated analysis between human tissues has been done. Results To describe tissue-specific functions, Recon 1 was tailored to describe metabolism in three human cells: adipocytes, hepatocytes, and myocytes. These cell-specific networks were manually curated and validated based on known cellular metabolic functions. To study intercellular interactions, a novel multi-tissue type modeling approach was developed to integrate the metabolic functions for the three cell types, and subsequently used to simulate known integrated metabolic cycles. In addition, the multi-tissue model was used to study diabetes: a pathology with systemic properties. High-throughput data was integrated with the network to determine differential metabolic activity between obese and type II obese gastric bypass patients in a whole-body context. Conclusion The multi-tissue type modeling approach presented provides a platform to study integrated metabolic states. As more cell and tissue-specific models are released, it is critical to develop a framework in which to study their interdependencies. PMID:22041191

Identification of alterations associated with age in the clustering structure of functional brain networks.

PubMed

Guzman, Grover E C; Sato, Joao R; Vidal, Maciel C; Fujita, Andre

2018-01-01

Initial studies using resting-state functional magnetic resonance imaging on the trajectories of the brain network from childhood to adulthood found evidence of functional integration and segregation over time. The comprehension of how healthy individuals' functional integration and segregation occur is crucial to enhance our understanding of possible deviations that may lead to brain disorders. Recent approaches have focused on the framework wherein the functional brain network is organized into spatially distributed modules that have been associated with specific cognitive functions. Here, we tested the hypothesis that the clustering structure of brain networks evolves during development. To address this hypothesis, we defined a measure of how well a brain region is clustered (network fitness index), and developed a method to evaluate its association with age. Then, we applied this method to a functional magnetic resonance imaging data set composed of 397 males under 31 years of age collected as part of the Autism Brain Imaging Data Exchange Consortium. As results, we identified two brain regions for which the clustering change over time, namely, the left middle temporal gyrus and the left putamen. Since the network fitness index is associated with both integration and segregation, our finding suggests that the identified brain region plays a role in the development of brain systems.

Another Look at the PART-O Using the Traumatic Brain Injury Model Systems National Database: Scoring to Optimize Psychometrics.

PubMed

Malec, James F; Whiteneck, Gale G; Bogner, Jennifer A

2016-02-01

To integrate previous approaches to scoring the Participation Assessment with Recombined Tools-Objective (PART-O) in a unidimensional scale. Retrospective analysis of PART-O data from the Traumatic Brain Injury Model Systems. Community. Data from individuals (N=469) selected randomly from participants who completed 1-year follow-up in the Traumatic Brain Injury Model Systems were used in Rasch model development. The model was subsequently tested on data from additional random samples of similar size at 1-, 2-, 5-, 10-, and >15-year follow-ups. Not applicable. PART-O. After combining items for productivity and social interaction, the initial analysis at 1-year follow-up indicated relatively good fit to the Rasch model (person reliability=.80) but also suggested item misfit and that the 0-to-5 scale used for most items did not consistently show clear separation between rating levels. Reducing item rating scales to 3 levels (except combined and dichotomous items) resolved these issues and demonstrated good item level discrimination, fit, and person reliability (.81), with no evidence of multidimensionality. These results replicated in analyses at each additional follow-up period. Modifications to item scoring for the PART-O resulted in a unidimensional parametric equivalent measure that addresses previous concerns about competing item relations, and it fit the Rasch model consistently across follow-up periods. The person-item map shows a progression toward greater community participation from solitary and dyadic activities, such as leaving the house and having a friend through social and productivity activities, to group activities with others who share interests or beliefs. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

The BRAIN Initiative Provides a Unifying Context for Integrating Core STEM Competencies into a Neurobiology Course.

PubMed

Schaefer, Jennifer E

2016-01-01

The Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative introduced by the Obama Administration in 2013 presents a context for integrating many STEM competencies into undergraduate neuroscience coursework. The BRAIN Initiative core principles overlap with core STEM competencies identified by the AAAS Vision and Change report and other entities. This neurobiology course utilizes the BRAIN Initiative to serve as the unifying theme that facilitates a primary emphasis on student competencies such as scientific process, scientific communication, and societal relevance while teaching foundational neurobiological content such as brain anatomy, cellular neurophysiology, and activity modulation. Student feedback indicates that the BRAIN Initiative is an engaging and instructional context for this course. Course module organization, suitable BRAIN Initiative commentary literature, sample primary literature, and important assignments are presented.

A Study of the Effectiveness of Sensory Integration Therapy on Neuro-Physiological Development

ERIC Educational Resources Information Center

Reynolds, Christopher; Reynolds, Kathleen Sheena

2010-01-01

Background: Sensory integration theory proposes that because there is plasticity within the central nervous system (the brain is moldable) and because the brain consists of systems that are hierarchically organised, it is possible to stimulate and improve neuro-physiological processing and integration and thereby increase learning capacity.…

Functional split brain in a driving/listening paradigm

PubMed Central

Boly, Melanie; Mensen, Armand; Tononi, Giulio

2016-01-01

We often engage in two concurrent but unrelated activities, such as driving on a quiet road while listening to the radio. When we do so, does our brain split into functionally distinct entities? To address this question, we imaged brain activity with fMRI in experienced drivers engaged in a driving simulator while listening either to global positioning system instructions (integrated task) or to a radio show (split task). We found that, compared with the integrated task, the split task was characterized by reduced multivariate functional connectivity between the driving and listening networks. Furthermore, the integrated information content of the two networks, predicting their joint dynamics above and beyond their independent dynamics, was high in the integrated task and zero in the split task. Finally, individual subjects’ ability to switch between high and low information integration predicted their driving performance across integrated and split tasks. This study raises the possibility that under certain conditions of daily life, a single brain may support two independent functional streams, a “functional split brain” similar to what is observed in patients with an anatomical split. PMID:27911805

Leukoencephalopathy After Stereotactic Radiosurgery for Brain Metastases

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

Trifiletti, Daniel M., E-mail: daniel.trifiletti@gmail.com; Lee, Cheng-Chia; Schlesinger, David

Purpose: Although the use of stereotactic radiosurgery (SRS) in the treatment of multiple brain metastases has increased dramatically during the past decade to avoid the neurocognitive dysfunction induced by whole brain radiation therapy (WBRT), the cumulative neurocognitive effect of numerous SRS sessions remains unknown. Because leukoencephalopathy is a sensitive marker for radiation-induced central nervous system damage, we studied the clinical and dosimetric predictors of SRS-induced leukoencephalopathy. Methods and Materials: Patients treated at our institution with at least 2 sessions of SRS for brain metastases from 2007 to 2013 were reviewed. The pre- and post-SRS magnetic resonance imaging sequences were reviewedmore » and graded for white matter changes associated with radiation leukoencephalopathy using a previously validated scale. Patient characteristics and SRS dosimetric parameters were reviewed for factors that contributed to leukoencephalopathy using Cox proportional hazards modeling. Results: A total of 103 patients meeting the inclusion criteria were identified. The overall incidence of leukoencephalopathy was 29% at year 1, 38% at year 2, and 53% at year 3. Three factors were associated with radiation-induced leukoencephalopathy: (1) the use of WBRT (P=.019); (2) a higher SRS integral dose to the cranium (P=.036); and (3) the total number of intracranial metastases (P=.003). Conclusions: Our results have established that WBRT plus SRS produces leukoencephalopathy at a much higher rate than SRS alone. In addition, for patients who did not undergo WBRT before SRS, the integral dose was associated with the development of leukoencephalopathy. As the survival of patients with central nervous system metastases increases and as the neurotoxicity of chemotherapeutic and targeted agents becomes established, these 3 potential risk factors will be important to consider.« less

On the role of the amygdala for experiencing fatigue in patients with multiple sclerosis.

PubMed

Hanken, Katrin; Francis, Yoselin; Kastrup, Andreas; Eling, Paul; Klein, Jan; Hildebrandt, Helmut

2018-02-01

Recently, we proposed a model explaining the origin of fatigue in multiple sclerosis (MS) patients. This model assumes that the feeling of fatigue results from inflammation-induced information processing within interoceptive brain areas. To investigate the association between self-reported cognitive fatigue and structural integrity of interoceptive brain areas in MS patients. 95 MS patients and 28 healthy controls participated in this study. All participants underwent diffusion tensor MRI and fractional anisotropy data were calculated for the amygdala, the stria terminalis and the corpus callosum, a non-interoceptive brain area. Based on the cognitive fatigue score of the Fatigue Scale for Motor and Cognition, patients were divided into moderately cognitively fatigued (cognitive fatigue score ≥ 28) and cognitively non-fatigued (cognitive fatigue score < 28) MS patients. Healthy controls were recruited as a third group. Repeated measures analyses of covariance, controlling for age, depression and brain atrophy, were performed to investigate whether the factor Group had a significant effect on the fractional anisotropy data. A significant effect of Group was observed for the amygdala (F = 3.389, p = 0.037). MS patients without cognitive fatigue presented lower values of the amygdala than MS patients with cognitive fatigue and healthy controls. For the stria terminalis and the corpus callosum, no main effect of Group was observed. The structural integrity of the amygdala in non-fatigued MS patients appears to be reduced. According to our model this might indicate that the absence of fatigue in non-fatigued MS patients might result from disturbed inflammation-induced information processing in the amygdala. Copyright © 2017 Elsevier B.V. All rights reserved.

Diffusion Tensor Imaging in Relation to Cognitive and Functional Outcome of Traumatic Brain Injury in Children

PubMed Central

Levin, Harvey S.; Wilde, Elisabeth A.; Chu, Zili; Yallampalli, Ragini; Hanten, Gerri R.; Li, Xiaoqi; Chia, Jon; Vasquez, Carmen; Hunter, Jill V.

2008-01-01

Objective To investigate the relation of white matter integrity using diffusion tensor imaging (DTI) to cognitive and functional outcome of moderate to severe traumatic brain injury (TBI) in children. Design Prospective observational study of children who had sustained moderate to severe TBI and a comparison group of children who had sustained orthopedic injury (OI). Participants Thirty-two children who had sustained moderate to severe TBI and 36 children with OI were studied. Methods Fiber tracking analysis of DTI acquired at 3-month postinjury and assessment of global outcome and cognitive function within 2 weeks of brain imaging. Global outcome was assessed using the Glasgow Outcome Scale and the Flanker task was used to measure cognitive processing speed and resistance to interference. Results Fractional anisotropy and apparent diffusion coefficient values differentiated the groups and both cognitive and functional outcome measures were related to the DTI findings. Dissociations were present wherein the relation of Fractional anisotropy to cognitive performance differed between the TBI and OI groups. A DTI composite measure of white matter integrity was related to global outcome in the children with TBI. Conclusions DTI is sensitive to white matter injury at 3 months following moderate to severe TBI in children, including brain regions that appear normal on conventional magnetic resonance imaging. DTI measures reflecting diffusion of water parallel and perpendicular to white matter tracts as calculated by fiber tracking analysis are related to global outcome, cognitive processing speed, and speed of resolving interference in children with moderate to severe TBI. Longitudinal data are needed to determine whether these relations between DTI and neurobehavioral outcome of TBI in children persist at longer follow-up intervals. PMID:18650764

Genetic influences on functional connectivity associated with feedback processing and prediction error: Phase coupling of theta-band oscillations in twins.

PubMed

Demiral, Şükrü Barış; Golosheykin, Simon; Anokhin, Andrey P

2017-05-01

Detection and evaluation of the mismatch between the intended and actually obtained result of an action (reward prediction error) is an integral component of adaptive self-regulation of behavior. Extensive human and animal research has shown that evaluation of action outcome is supported by a distributed network of brain regions in which the anterior cingulate cortex (ACC) plays a central role, and the integration of distant brain regions into a unified feedback-processing network is enabled by long-range phase synchronization of cortical oscillations in the theta band. Neural correlates of feedback processing are associated with individual differences in normal and abnormal behavior, however, little is known about the role of genetic factors in the cerebral mechanisms of feedback processing. Here we examined genetic influences on functional cortical connectivity related to prediction error in young adult twins (age 18, n=399) using event-related EEG phase coherence analysis in a monetary gambling task. To identify prediction error-specific connectivity pattern, we compared responses to loss and gain feedback. Monetary loss produced a significant increase of theta-band synchronization between the frontal midline region and widespread areas of the scalp, particularly parietal areas, whereas gain resulted in increased synchrony primarily within the posterior regions. Genetic analyses showed significant heritability of frontoparietal theta phase synchronization (24 to 46%), suggesting that individual differences in large-scale network dynamics are under substantial genetic control. We conclude that theta-band synchronization of brain oscillations related to negative feedback reflects genetically transmitted differences in the neural mechanisms of feedback processing. To our knowledge, this is the first evidence for genetic influences on task-related functional brain connectivity assessed using direct real-time measures of neuronal synchronization. Copyright © 2016 Elsevier B.V. All rights reserved.

Towards a comprehensive atlas of cortical connections in a primate brain: Mapping tracer injection studies of the common marmoset into a reference digital template.

PubMed

Majka, Piotr; Chaplin, Tristan A; Yu, Hsin-Hao; Tolpygo, Alexander; Mitra, Partha P; Wójcik, Daniel K; Rosa, Marcello G P

2016-08-01

The marmoset is an emerging animal model for large-scale attempts to understand primate brain connectivity, but achieving this aim requires the development and validation of procedures for normalization and integration of results from many neuroanatomical experiments. Here we describe a computational pipeline for coregistration of retrograde tracing data on connections of cortical areas into a 3D marmoset brain template, generated from Nissl-stained sections. The procedure results in a series of spatial transformations that are applied to the coordinates of labeled neurons in the different cases, bringing them into common stereotaxic space. We applied this procedure to 17 injections, placed in the frontal lobe of nine marmosets as part of earlier studies. Visualizations of cortical patterns of connections revealed by these injections are supplied as Supplementary Materials. Comparison between the results of the automated and human-based processing of these cases reveals that the centers of injection sites can be reconstructed, on average, to within 0.6 mm of coordinates estimated by an experienced neuroanatomist. Moreover, cell counts obtained in different areas by the automated approach are highly correlated (r = 0.83) with those obtained by an expert, who examined in detail histological sections for each individual. The present procedure enables comparison and visualization of large datasets, which in turn opens the way for integration and analysis of results from many animals. Its versatility, including applicability to archival materials, may reduce the number of additional experiments required to produce the first detailed cortical connectome of a primate brain. J. Comp. Neurol. 524:2161-2181, 2016. © 2016 The Authors The Journal of Comparative Neurology Published by Wiley Periodicals, Inc. © 2016 The Authors The Journal of Comparative Neurology Published by Wiley Periodicals, Inc.

Allostasis and the Human Brain: Integrating Models of Stress from the Social and Life Sciences

ERIC Educational Resources Information Center

Ganzel, Barbara L.; Morris, Pamela A.; Wethington, Elaine

2010-01-01

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…

GABA regulates synaptic integration of newly generated neurons in the adult brain

NASA Astrophysics Data System (ADS)

Ge, Shaoyu; Goh, Eyleen L. K.; Sailor, Kurt A.; Kitabatake, Yasuji; Ming, Guo-Li; Song, Hongjun

2006-02-01

Adult neurogenesis, the birth and integration of new neurons from adult neural stem cells, is a striking form of structural plasticity and highlights the regenerative capacity of the adult mammalian brain. Accumulating evidence suggests that neuronal activity regulates adult neurogenesis and that new neurons contribute to specific brain functions. The mechanism that regulates the integration of newly generated neurons into the pre-existing functional circuitry in the adult brain is unknown. Here we show that newborn granule cells in the dentate gyrus of the adult hippocampus are tonically activated by ambient GABA (γ-aminobutyric acid) before being sequentially innervated by GABA- and glutamate-mediated synaptic inputs. GABA, the major inhibitory neurotransmitter in the adult brain, initially exerts an excitatory action on newborn neurons owing to their high cytoplasmic chloride ion content. Conversion of GABA-induced depolarization (excitation) into hyperpolarization (inhibition) in newborn neurons leads to marked defects in their synapse formation and dendritic development in vivo. Our study identifies an essential role for GABA in the synaptic integration of newly generated neurons in the adult brain, and suggests an unexpected mechanism for activity-dependent regulation of adult neurogenesis, in which newborn neurons may sense neuronal network activity through tonic and phasic GABA activation.

Abnormal rich club organization and functional brain dynamics in schizophrenia.

PubMed

van den Heuvel, Martijn P; Sporns, Olaf; Collin, Guusje; Scheewe, Thomas; Mandl, René C W; Cahn, Wiepke; Goñi, Joaquín; Hulshoff Pol, Hilleke E; Kahn, René S

2013-08-01

The human brain forms a large-scale structural network of regions and interregional pathways. Recent studies have reported the existence of a selective set of highly central and interconnected hub regions that may play a crucial role in the brain's integrative processes, together forming a central backbone for global brain communication. Abnormal brain connectivity may have a key role in the pathophysiology of schizophrenia. To examine the structure of the rich club in schizophrenia and its role in global functional brain dynamics. Structural diffusion tensor imaging and resting-state functional magnetic resonance imaging were performed in patients with schizophrenia and matched healthy controls. Department of Psychiatry, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, the Netherlands. Forty-eight patients and 45 healthy controls participated in the study. An independent replication data set of 41 patients and 51 healthy controls was included to replicate and validate significant findings. MAIN OUTCOME(S) AND MEASURES: Measures of rich club organization, connectivity density of rich club connections and connections linking peripheral regions to brain hubs, measures of global brain network efficiency, and measures of coupling between brain structure and functional dynamics. Rich club organization between high-degree hub nodes was significantly affected in patients, together with a reduced density of rich club connections predominantly comprising the white matter pathways that link the midline frontal, parietal, and insular hub regions. This reduction in rich club density was found to be associated with lower levels of global communication capacity, a relationship that was absent for other white matter pathways. In addition, patients had an increase in the strength of structural connectivity-functional connectivity coupling. Our findings provide novel biological evidence that schizophrenia is characterized by a selective disruption of brain connectivity among central hub regions of the brain, potentially leading to reduced communication capacity and altered functional brain dynamics.

Improvement of Blood-Brain Barrier Integrity in Traumatic Brain Injury and Hemorrhagic Shock Following Treatment With Valproic Acid and Fresh Frozen Plasma.

PubMed

Nikolian, Vahagn C; Dekker, Simone E; Bambakidis, Ted; Higgins, Gerald A; Dennahy, Isabel S; Georgoff, Patrick E; Williams, Aaron M; Andjelkovic, Anuska V; Alam, Hasan B

2018-01-01

Combined traumatic brain injury and hemorrhagic shock are highly lethal. Following injuries, the integrity of the blood-brain barrier can be impaired, contributing to secondary brain insults. The status of the blood-brain barrier represents a potential factor impacting long-term neurologic outcomes in combined injuries. Treatment strategies involving plasma-based resuscitation and valproic acid therapy have shown efficacy in this setting. We hypothesize that a component of this beneficial effect is related to blood-brain barrier preservation. Following controlled traumatic brain injury, hemorrhagic shock, various resuscitation and treatment strategies were evaluated for their association with blood-brain barrier integrity. Analysis of gene expression profiles was performed using Porcine Gene ST 1.1 microarray. Pathway analysis was completed using network analysis tools (Gene Ontology, Ingenuity Pathway Analysis, and Parametric Gene Set Enrichment Analysis). Female Yorkshire swine were subjected to controlled traumatic brain injury and 2 hours of hemorrhagic shock (40% blood volume, mean arterial pressure 30-35 mmHg). Subjects were resuscitated with 1) normal saline, 2) fresh frozen plasma, 3) hetastarch, 4) fresh frozen plasma + valproic acid, or 5) hetastarch + valproic acid (n = 5 per group). After 6 hours of observation, brains were harvested for evaluation. Immunofluoroscopic evaluation of the traumatic brain injury site revealed significantly increased expression of tight-junction associated proteins (zona occludin-1, claudin-5) following combination therapy (fresh frozen plasma + valproic acid and hetastarch + valproic acid). The extracellular matrix protein laminin was found to have significantly improved expression with combination therapies. Pathway analysis indicated that valproic acid significantly modulated pathways involved in endothelial barrier function and cell signaling. Resuscitation with fresh frozen plasma results in improved expression of proteins essential for blood-brain barrier integrity. The addition of valproic acid provides significant improvement to these protein expression profiles. This is likely secondary to activation of key pathways related to endothelial functions.

Early rehabilitation for severe acquired brain injury in intensive care unit: multicenter observational study.

PubMed

Bartolo, Michelangelo; Bargellesi, Stefano; Castioni, Carlo A; Bonaiuti, Donatella; Antenucci, Roberto; Benedetti, Angelo; Capuzzo, Valeria; Gamna, Federica; Radeschi, Giulio; Citerio, Giuseppe; Colombo, Carolina; Del Casale, Laura; Recubini, Elena; Toska, Saimir; Zanello, Marco; D'Aurizio, Carlo; Spina, Tullio; Del Gaudio, Alredo; Di Rienzo, Filomena; Intiso, Domenico; Dallocchio, Giulia; Felisatti, Giovanna; Lavezzi, Susanna; Zoppellari, Roberto; Gariboldi, Valentina; Lorini, Luca; Melizza, Giovanni; Molinero, Guido; Mandalà, Giorgio; Pignataro, Amedeo; Montis, Andrea; Napoleone, Alessandro; Pilia, Felicita; Pisu, Marina; Semerjian, Monica; Pagliaro, Giuseppina; Nardin, Lorella; Scarponi, Federico; Zampolini, Mauro; Zava, Raffaele; Massetti, Maria A; Piccolini, Carlo; Aloj, Fulvio; Antonelli, Sergio; Zucchella, Chiara

2016-02-01

The increased survival after a severe acquired brain injury (sABI) raise the problem of making most effective the treatments in Intensive Care Unit (ICU)/Neurointensive Care Unit (NICU), also integrating rehabilitation care. Despite previous studies reported that early mobilization in ICU was effective in preventing complications and reducing hospital stay, few studies addressed the rehabilitative management of sABI patients in ICU/NICU. To collect clinical and functional data about the early rehabilitative management of sABI patients during ICU/NICU stay. Prospective, observational, multicenter study. Fourteen facilities supplied by intensive neurorehabilitation units and ICU/NICUs. Consecutive sABI patients admitted to ICU/NICU. Patients were evaluated at admission and then every 3-5 days. Clinical, functional and rehabilitative data, including Glasgow Coma Scale (GCS), Disability Rating Scale (DRS), The Rancho Los Amigos Levels of Cognitive Functioning Scale (LCF), Early Rehabilitation Barthel Index (ERBI), Glasgow Outcome scale (GOS) and Functional Independence Measure (FIM) were collected. One hundred and two patients (F/M 44/58) were enrolled. The mean duration of ICU stay was 24.7±13.9 days and the first rehabilitative evaluation occurred after 8.7±8.8 days. Regular postural changes and multijoint mobilization were prescribed in 63.7% and 64.7% cases, respectively. The mean session duration was 38±11.5 minutes. Swallowing evaluation was performed in 14.7% patients, psychological support was provided to 12.7% of patients' caregivers, while 17.6% received a psycho-educational intervention, and 28.4% were involved in interdisciplinary team meetings. The main discharge destinations were Severe Acquired Brain Injury rehabilitation units for 43.7%, intensive neurorehabilitation units for 20.7%. Data showed that early rehabilitation was not diffusely performed in sABI subjects in ICU/NICU and rehabilitative interventions were variable; one-third of subjects were not referred to dedicated rehabilitation unit at discharge. The study stresses the need to spread and implement a rehabilitative culture also for critical ill patients due to neurological diseases.

Gait and Glasgow Coma Scale scores can predict functional recovery in patients with traumatic brain injury☆

PubMed Central

Bilgin, Sevil; Guclu-Gunduz, Arzu; Oruckaptan, Hakan; Kose, Nezire; Celik, Bülent

2012-01-01

Fifty-one patients with mild (n = 14), moderate (n = 10) and severe traumatic brain injury (n = 27) received early rehabilitation. Level of consciousness was evaluated using the Glasgow Coma Score. Functional level was determined using the Glasgow Outcome Score, whilst mobility was evaluated using the Mobility Scale for Acute Stroke. Activities of daily living were assessed using the Barthel Index. Following Bobath neurodevelopmental therapy, the level of consciousness was significantly improved in patients with moderate and severe traumatic brain injury, but was not greatly influenced in patients with mild traumatic brain injury. Mobility and functional level were significantly improved in patients with mild, moderate and severe traumatic brain injury. Gait recovery was more obvious in patients with mild traumatic brain injury than in patients with moderate and severe traumatic brain injury. Activities of daily living showed an improvement but this was insignificant except for patients with severe traumatic brain injury. Nevertheless, complete recovery was not acquired at discharge. Multiple regression analysis showed that gait and Glasgow Coma Scale scores can be considered predictors of functional outcomes following traumatic brain injury. PMID:25624828

Functional connectivity and graph theory in preclinical Alzheimer's disease.

PubMed

Brier, Matthew R; Thomas, Jewell B; Fagan, Anne M; Hassenstab, Jason; Holtzman, David M; Benzinger, Tammie L; Morris, John C; Ances, Beau M

2014-04-01

Alzheimer's disease (AD) has a long preclinical phase in which amyloid and tau cerebral pathology accumulate without producing cognitive symptoms. Resting state functional connectivity magnetic resonance imaging has demonstrated that brain networks degrade during symptomatic AD. It is unclear to what extent these degradations exist before symptomatic onset. In this study, we investigated graph theory metrics of functional integration (path length), functional segregation (clustering coefficient), and functional distinctness (modularity) as a function of disease severity. Further, we assessed whether these graph metrics were affected in cognitively normal participants with cerebrospinal fluid evidence of preclinical AD. Clustering coefficient and modularity, but not path length, were reduced in AD. Cognitively normal participants who harbored AD biomarker pathology also showed reduced values in these graph measures, demonstrating brain changes similar to, but smaller than, symptomatic AD. Only modularity was significantly affected by age. We also demonstrate that AD has a particular effect on hub-like regions in the brain. We conclude that AD causes large-scale disconnection that is present before onset of symptoms. Copyright © 2014 Elsevier Inc. All rights reserved.

Complexity of low-frequency blood oxygen level-dependent fluctuations covaries with local connectivity.

PubMed

Anderson, Jeffrey S; Zielinski, Brandon A; Nielsen, Jared A; Ferguson, Michael A

2014-04-01

Very low-frequency blood oxygen level-dependent (BOLD) fluctuations have emerged as a valuable tool for describing brain anatomy, neuropathology, and development. Such fluctuations exhibit power law frequency dynamics, with largest amplitude at lowest frequencies. The biophysical mechanisms generating such fluctuations are poorly understood. Using publicly available data from 1,019 subjects of age 7-30, we show that BOLD fluctuations exhibit temporal complexity that is linearly related to local connectivity (regional homogeneity), consistently and significantly covarying across subjects and across gray matter regions. This relationship persisted independently of covariance with gray matter density or standard deviation of BOLD signal. During late neurodevelopment, BOLD fluctuations were unchanged with age in association cortex while becoming more random throughout the rest of the brain. These data suggest that local interconnectivity may play a key role in establishing the complexity of low-frequency BOLD fluctuations underlying functional magnetic resonance imaging connectivity. Stable low-frequency power dynamics may emerge through segmentation and integration of connectivity during development of distributed large-scale brain networks. Copyright © 2013 Wiley Periodicals, Inc.

Dissociable meta-analytic brain networks contribute to coordinated emotional processing.

PubMed

Riedel, Michael C; Yanes, Julio A; Ray, Kimberly L; Eickhoff, Simon B; Fox, Peter T; Sutherland, Matthew T; Laird, Angela R

2018-06-01

Meta-analytic techniques for mining the neuroimaging literature continue to exert an impact on our conceptualization of functional brain networks contributing to human emotion and cognition. Traditional theories regarding the neurobiological substrates contributing to affective processing are shifting from regional- towards more network-based heuristic frameworks. To elucidate differential brain network involvement linked to distinct aspects of emotion processing, we applied an emergent meta-analytic clustering approach to the extensive body of affective neuroimaging results archived in the BrainMap database. Specifically, we performed hierarchical clustering on the modeled activation maps from 1,747 experiments in the affective processing domain, resulting in five meta-analytic groupings of experiments demonstrating whole-brain recruitment. Behavioral inference analyses conducted for each of these groupings suggested dissociable networks supporting: (1) visual perception within primary and associative visual cortices, (2) auditory perception within primary auditory cortices, (3) attention to emotionally salient information within insular, anterior cingulate, and subcortical regions, (4) appraisal and prediction of emotional events within medial prefrontal and posterior cingulate cortices, and (5) induction of emotional responses within amygdala and fusiform gyri. These meta-analytic outcomes are consistent with a contemporary psychological model of affective processing in which emotionally salient information from perceived stimuli are integrated with previous experiences to engender a subjective affective response. This study highlights the utility of using emergent meta-analytic methods to inform and extend psychological theories and suggests that emotions are manifest as the eventual consequence of interactions between large-scale brain networks. © 2018 Wiley Periodicals, Inc.

Cyber-workstation for computational neuroscience.

PubMed

Digiovanna, Jack; Rattanatamrong, Prapaporn; Zhao, Ming; Mahmoudi, Babak; Hermer, Linda; Figueiredo, Renato; Principe, Jose C; Fortes, Jose; Sanchez, Justin C

2010-01-01

A Cyber-Workstation (CW) to study in vivo, real-time interactions between computational models and large-scale brain subsystems during behavioral experiments has been designed and implemented. The design philosophy seeks to directly link the in vivo neurophysiology laboratory with scalable computing resources to enable more sophisticated computational neuroscience investigation. The architecture designed here allows scientists to develop new models and integrate them with existing models (e.g. recursive least-squares regressor) by specifying appropriate connections in a block-diagram. Then, adaptive middleware transparently implements these user specifications using the full power of remote grid-computing hardware. In effect, the middleware deploys an on-demand and flexible neuroscience research test-bed to provide the neurophysiology laboratory extensive computational power from an outside source. The CW consolidates distributed software and hardware resources to support time-critical and/or resource-demanding computing during data collection from behaving animals. This power and flexibility is important as experimental and theoretical neuroscience evolves based on insights gained from data-intensive experiments, new technologies and engineering methodologies. This paper describes briefly the computational infrastructure and its most relevant components. Each component is discussed within a systematic process of setting up an in vivo, neuroscience experiment. Furthermore, a co-adaptive brain machine interface is implemented on the CW to illustrate how this integrated computational and experimental platform can be used to study systems neurophysiology and learning in a behavior task. We believe this implementation is also the first remote execution and adaptation of a brain-machine interface.

Cyber-Workstation for Computational Neuroscience

PubMed Central

DiGiovanna, Jack; Rattanatamrong, Prapaporn; Zhao, Ming; Mahmoudi, Babak; Hermer, Linda; Figueiredo, Renato; Principe, Jose C.; Fortes, Jose; Sanchez, Justin C.

2009-01-01

A Cyber-Workstation (CW) to study in vivo, real-time interactions between computational models and large-scale brain subsystems during behavioral experiments has been designed and implemented. The design philosophy seeks to directly link the in vivo neurophysiology laboratory with scalable computing resources to enable more sophisticated computational neuroscience investigation. The architecture designed here allows scientists to develop new models and integrate them with existing models (e.g. recursive least-squares regressor) by specifying appropriate connections in a block-diagram. Then, adaptive middleware transparently implements these user specifications using the full power of remote grid-computing hardware. In effect, the middleware deploys an on-demand and flexible neuroscience research test-bed to provide the neurophysiology laboratory extensive computational power from an outside source. The CW consolidates distributed software and hardware resources to support time-critical and/or resource-demanding computing during data collection from behaving animals. This power and flexibility is important as experimental and theoretical neuroscience evolves based on insights gained from data-intensive experiments, new technologies and engineering methodologies. This paper describes briefly the computational infrastructure and its most relevant components. Each component is discussed within a systematic process of setting up an in vivo, neuroscience experiment. Furthermore, a co-adaptive brain machine interface is implemented on the CW to illustrate how this integrated computational and experimental platform can be used to study systems neurophysiology and learning in a behavior task. We believe this implementation is also the first remote execution and adaptation of a brain-machine interface. PMID:20126436

Heart Rate Variability: New Perspectives on Physiological Mechanisms, Assessment of Self-regulatory Capacity, and Health risk

PubMed Central

Shaffer, Fred

2015-01-01

Heart rate variability, the change in the time intervals between adjacent heartbeats, is an emergent property of interdependent regulatory systems that operates on different time scales to adapt to environmental and psychological challenges. This article briefly reviews neural regulation of the heart and offers some new perspectives on mechanisms underlying the very low frequency rhythm of heart rate variability. Interpretation of heart rate variability rhythms in the context of health risk and physiological and psychological self-regulatory capacity assessment is discussed. The cardiovascular regulatory centers in the spinal cord and medulla integrate inputs from higher brain centers with afferent cardiovascular system inputs to adjust heart rate and blood pressure via sympathetic and parasympathetic efferent pathways. We also discuss the intrinsic cardiac nervous system and the heart-brain connection pathways, through which afferent information can influence activity in the subcortical, frontocortical, and motor cortex areas. In addition, the use of real-time HRV feedback to increase self-regulatory capacity is reviewed. We conclude that the heart's rhythms are characterized by both complexity and stability over longer time scales that reflect both physiological and psychological functional status of these internal self-regulatory systems. PMID:25694852

Heart Rate Variability: New Perspectives on Physiological Mechanisms, Assessment of Self-regulatory Capacity, and Health risk.

PubMed

McCraty, Rollin; Shaffer, Fred

2015-01-01

Heart rate variability, the change in the time intervals between adjacent heartbeats, is an emergent property of interdependent regulatory systems that operates on different time scales to adapt to environmental and psychological challenges. This article briefly reviews neural regulation of the heart and offers some new perspectives on mechanisms underlying the very low frequency rhythm of heart rate variability. Interpretation of heart rate variability rhythms in the context of health risk and physiological and psychological self-regulatory capacity assessment is discussed. The cardiovascular regulatory centers in the spinal cord and medulla integrate inputs from higher brain centers with afferent cardiovascular system inputs to adjust heart rate and blood pressure via sympathetic and parasympathetic efferent pathways. We also discuss the intrinsic cardiac nervous system and the heart-brain connection pathways, through which afferent information can influence activity in the subcortical, frontocortical, and motor cortex areas. In addition, the use of real-time HRV feedback to increase self-regulatory capacity is reviewed. We conclude that the heart's rhythms are characterized by both complexity and stability over longer time scales that reflect both physiological and psychological functional status of these internal self-regulatory systems.

The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data.

PubMed

Thompson, Paul M; Stein, Jason L; Medland, Sarah E; Hibar, Derrek P; Vasquez, Alejandro Arias; Renteria, Miguel E; Toro, Roberto; Jahanshad, Neda; Schumann, Gunter; Franke, Barbara; Wright, Margaret J; Martin, Nicholas G; Agartz, Ingrid; Alda, Martin; Alhusaini, Saud; Almasy, Laura; Almeida, Jorge; Alpert, Kathryn; Andreasen, Nancy C; Andreassen, Ole A; Apostolova, Liana G; Appel, Katja; Armstrong, Nicola J; Aribisala, Benjamin; Bastin, Mark E; Bauer, Michael; Bearden, Carrie E; Bergmann, Orjan; Binder, Elisabeth B; Blangero, John; Bockholt, Henry J; Bøen, Erlend; Bois, Catherine; Boomsma, Dorret I; Booth, Tom; Bowman, Ian J; Bralten, Janita; Brouwer, Rachel M; Brunner, Han G; Brohawn, David G; Buckner, Randy L; Buitelaar, Jan; Bulayeva, Kazima; Bustillo, Juan R; Calhoun, Vince D; Cannon, Dara M; Cantor, Rita M; Carless, Melanie A; Caseras, Xavier; Cavalleri, Gianpiero L; Chakravarty, M Mallar; Chang, Kiki D; Ching, Christopher R K; Christoforou, Andrea; Cichon, Sven; Clark, Vincent P; Conrod, Patricia; Coppola, Giovanni; Crespo-Facorro, Benedicto; Curran, Joanne E; Czisch, Michael; Deary, Ian J; de Geus, Eco J C; den Braber, Anouk; Delvecchio, Giuseppe; Depondt, Chantal; de Haan, Lieuwe; de Zubicaray, Greig I; Dima, Danai; Dimitrova, Rali; Djurovic, Srdjan; Dong, Hongwei; Donohoe, Gary; Duggirala, Ravindranath; Dyer, Thomas D; Ehrlich, Stefan; Ekman, Carl Johan; Elvsåshagen, Torbjørn; Emsell, Louise; Erk, Susanne; Espeseth, Thomas; Fagerness, Jesen; Fears, Scott; Fedko, Iryna; Fernández, Guillén; Fisher, Simon E; Foroud, Tatiana; Fox, Peter T; Francks, Clyde; Frangou, Sophia; Frey, Eva Maria; Frodl, Thomas; Frouin, Vincent; Garavan, Hugh; Giddaluru, Sudheer; Glahn, David C; Godlewska, Beata; Goldstein, Rita Z; Gollub, Randy L; Grabe, Hans J; Grimm, Oliver; Gruber, Oliver; Guadalupe, Tulio; Gur, Raquel E; Gur, Ruben C; Göring, Harald H H; Hagenaars, Saskia; Hajek, Tomas; Hall, Geoffrey B; Hall, Jeremy; Hardy, John; Hartman, Catharina A; Hass, Johanna; Hatton, Sean N; Haukvik, Unn K; Hegenscheid, Katrin; Heinz, Andreas; Hickie, Ian B; Ho, Beng-Choon; Hoehn, David; Hoekstra, Pieter J; Hollinshead, Marisa; Holmes, Avram J; Homuth, Georg; Hoogman, Martine; Hong, L Elliot; Hosten, Norbert; Hottenga, Jouke-Jan; Hulshoff Pol, Hilleke E; Hwang, Kristy S; Jack, Clifford R; Jenkinson, Mark; Johnston, Caroline; Jönsson, Erik G; Kahn, René S; Kasperaviciute, Dalia; Kelly, Sinead; Kim, Sungeun; Kochunov, Peter; Koenders, Laura; Krämer, Bernd; Kwok, John B J; Lagopoulos, Jim; Laje, Gonzalo; Landen, Mikael; Landman, Bennett A; Lauriello, John; Lawrie, Stephen M; Lee, Phil H; Le Hellard, Stephanie; Lemaître, Herve; Leonardo, Cassandra D; Li, Chiang-Shan; Liberg, Benny; Liewald, David C; Liu, Xinmin; Lopez, Lorna M; Loth, Eva; Lourdusamy, Anbarasu; Luciano, Michelle; Macciardi, Fabio; Machielsen, Marise W J; Macqueen, Glenda M; Malt, Ulrik F; Mandl, René; Manoach, Dara S; Martinot, Jean-Luc; Matarin, Mar; Mather, Karen A; Mattheisen, Manuel; Mattingsdal, Morten; Meyer-Lindenberg, Andreas; McDonald, Colm; McIntosh, Andrew M; McMahon, Francis J; McMahon, Katie L; Meisenzahl, Eva; Melle, Ingrid; Milaneschi, Yuri; Mohnke, Sebastian; Montgomery, Grant W; Morris, Derek W; Moses, Eric K; Mueller, Bryon A; Muñoz Maniega, Susana; Mühleisen, Thomas W; Müller-Myhsok, Bertram; Mwangi, Benson; Nauck, Matthias; Nho, Kwangsik; Nichols, Thomas E; Nilsson, Lars-Göran; Nugent, Allison C; Nyberg, Lars; Olvera, Rene L; Oosterlaan, Jaap; Ophoff, Roel A; Pandolfo, Massimo; Papalampropoulou-Tsiridou, Melina; Papmeyer, Martina; Paus, Tomas; Pausova, Zdenka; Pearlson, Godfrey D; Penninx, Brenda W; Peterson, Charles P; Pfennig, Andrea; Phillips, Mary; Pike, G Bruce; Poline, Jean-Baptiste; Potkin, Steven G; Pütz, Benno; Ramasamy, Adaikalavan; Rasmussen, Jerod; Rietschel, Marcella; Rijpkema, Mark; Risacher, Shannon L; Roffman, Joshua L; Roiz-Santiañez, Roberto; Romanczuk-Seiferth, Nina; Rose, Emma J; Royle, Natalie A; Rujescu, Dan; Ryten, Mina; Sachdev, Perminder S; Salami, Alireza; Satterthwaite, Theodore D; Savitz, Jonathan; Saykin, Andrew J; Scanlon, Cathy; Schmaal, Lianne; Schnack, Hugo G; Schork, Andrew J; Schulz, S Charles; Schür, Remmelt; Seidman, Larry; Shen, Li; Shoemaker, Jody M; Simmons, Andrew; Sisodiya, Sanjay M; Smith, Colin; Smoller, Jordan W; Soares, Jair C; Sponheim, Scott R; Sprooten, Emma; Starr, John M; Steen, Vidar M; Strakowski, Stephen; Strike, Lachlan; Sussmann, Jessika; Sämann, Philipp G; Teumer, Alexander; Toga, Arthur W; Tordesillas-Gutierrez, Diana; Trabzuni, Daniah; Trost, Sarah; Turner, Jessica; Van den Heuvel, Martijn; van der Wee, Nic J; van Eijk, Kristel; van Erp, Theo G M; van Haren, Neeltje E M; van 't Ent, Dennis; van Tol, Marie-Jose; Valdés Hernández, Maria C; Veltman, Dick J; Versace, Amelia; Völzke, Henry; Walker, Robert; Walter, Henrik; Wang, Lei; Wardlaw, Joanna M; Weale, Michael E; Weiner, Michael W; Wen, Wei; Westlye, Lars T; Whalley, Heather C; Whelan, Christopher D; White, Tonya; Winkler, Anderson M; Wittfeld, Katharina; Woldehawariat, Girma; Wolf, Christiane; Zilles, David; Zwiers, Marcel P; Thalamuthu, Anbupalam; Schofield, Peter R; Freimer, Nelson B; Lawrence, Natalia S; Drevets, Wayne

2014-06-01

The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.

Sleep variability in adolescence is associated with altered brain development.

PubMed

Telzer, Eva H; Goldenberg, Diane; Fuligni, Andrew J; Lieberman, Matthew D; Gálvan, Adriana

2015-08-01

Despite the known importance of sleep for brain development, and the sharp increase in poor sleep during adolescence, we know relatively little about how sleep impacts the developing brain. We present the first longitudinal study to examine how sleep during adolescence is associated with white matter integrity. We find that greater variability in sleep duration one year prior to a DTI scan is associated with lower white matter integrity above and beyond the effects of sleep duration, and variability in bedtime, whereas sleep variability a few months prior to the scan is not associated with white matter integrity. Thus, variability in sleep duration during adolescence may have long-term impairments on the developing brain. White matter integrity should be increasing during adolescence, and so sleep variability is directly at odds with normative developmental trends. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Brain Network Architecture and Global Intelligence in Children with Focal Epilepsy.

PubMed

Paldino, M J; Golriz, F; Chapieski, M L; Zhang, W; Chu, Z D

2017-02-01

The biologic basis for intelligence rests to a large degree on the capacity for efficient integration of information across the cerebral network. We aimed to measure the relationship between network architecture and intelligence in the pediatric, epileptic brain. Patients were retrospectively identified with the following: 1) focal epilepsy; 2) brain MR imaging at 3T, including resting-state functional MR imaging; and 3) full-scale intelligence quotient measured by a pediatric neuropsychologist. The cerebral cortex was parcellated into approximately 700 gray matter network "nodes." The strength of a connection between 2 nodes was defined by the correlation between their blood oxygen level-dependent time-series. We calculated the following topologic properties: clustering coefficient, transitivity, modularity, path length, and global efficiency. A machine learning algorithm was used to measure the independent contribution of each metric to the intelligence quotient after adjusting for all other metrics. Thirty patients met the criteria (4-18 years of age); 20 patients required anesthesia during MR imaging. After we accounted for age and sex, clustering coefficient and path length were independently associated with full-scale intelligence quotient. Neither motion parameters nor general anesthesia was an important variable with regard to accurate intelligence quotient prediction by the machine learning algorithm. A longer history of epilepsy was associated with shorter path lengths ( P = .008), consistent with reorganization of the network on the basis of seizures. Considering only patients receiving anesthesia during machine learning did not alter the patterns of network architecture contributing to global intelligence. These findings support the physiologic relevance of imaging-based metrics of network architecture in the pathologic, developing brain. © 2017 by American Journal of Neuroradiology.

Low-frequency connectivity is associated with mild traumatic brain injury.

PubMed

Dunkley, B T; Da Costa, L; Bethune, A; Jetly, R; Pang, E W; Taylor, M J; Doesburg, S M

2015-01-01

Mild traumatic brain injury (mTBI) occurs from a closed-head impact. Often referred to as concussion, about 20% of cases complain of secondary psychological sequelae, such as disorders of attention and memory. Known as post-concussive symptoms (PCS), these problems can severely disrupt the patient's quality of life. Changes in local spectral power, particularly low-frequency amplitude increases and/or peak alpha slowing have been reported in mTBI, but large-scale connectivity metrics based on inter-regional amplitude correlations relevant for integration and segregation in functional brain networks, and their association with disorders in cognition and behaviour, remain relatively unexplored. Here, we used non-invasive neuroimaging with magnetoencephalography to examine functional connectivity in a resting-state protocol in a group with mTBI (n = 20), and a control group (n = 21). We observed a trend for atypical slow-wave power changes in subcortical, temporal and parietal regions in mTBI, as well as significant long-range increases in amplitude envelope correlations among deep-source, temporal, and frontal regions in the delta, theta, and alpha bands. Subsequently, we conducted an exploratory analysis of patterns of connectivity most associated with variability in secondary symptoms of mTBI, including inattention, anxiety, and depression. Differential patterns of altered resting state neurophysiological network connectivity were found across frequency bands. This indicated that multiple network and frequency specific alterations in large scale brain connectivity may contribute to overlapping cognitive sequelae in mTBI. In conclusion, we show that local spectral power content can be supplemented with measures of correlations in amplitude to define general networks that are atypical in mTBI, and suggest that certain cognitive difficulties are mediated by disturbances in a variety of alterations in network interactions which are differentially expressed across canonical neurophysiological frequency ranges.

Altered Brain Network Segregation in Fragile X Syndrome Revealed by Structural Connectomics.

PubMed

Bruno, Jennifer Lynn; Hosseini, S M Hadi; Saggar, Manish; Quintin, Eve-Marie; Raman, Mira Michelle; Reiss, Allan L

2017-03-01

Fragile X syndrome (FXS), the most common inherited cause of intellectual disability and autism spectrum disorder, is associated with significant behavioral, social, and neurocognitive deficits. Understanding structural brain network topology in FXS provides an important link between neurobiological and behavioral/cognitive symptoms of this disorder. We investigated the connectome via whole-brain structural networks created from group-level morphological correlations. Participants included 100 individuals: 50 with FXS and 50 with typical development, age 11-23 years. Results indicated alterations in topological properties of structural brain networks in individuals with FXS. Significantly reduced small-world index indicates a shift in the balance between network segregation and integration and significantly reduced clustering coefficient suggests that reduced local segregation shifted this balance. Caudate and amygdala were less interactive in the FXS network further highlighting the importance of subcortical region alterations in the neurobiological signature of FXS. Modularity analysis indicates that FXS and typically developing groups' networks decompose into different sets of interconnected sub networks, potentially indicative of aberrant local interconnectivity in individuals with FXS. These findings advance our understanding of the effects of fragile X mental retardation protein on large-scale brain networks and could be used to develop a connectome-level biological signature for FXS. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Complexity in relational processing predicts changes in functional brain network dynamics.

PubMed

Cocchi, Luca; Halford, Graeme S; Zalesky, Andrew; Harding, Ian H; Ramm, Brentyn J; Cutmore, Tim; Shum, David H K; Mattingley, Jason B

2014-09-01

The ability to link variables is critical to many high-order cognitive functions, including reasoning. It has been proposed that limits in relating variables depend critically on relational complexity, defined formally as the number of variables to be related in solving a problem. In humans, the prefrontal cortex is known to be important for reasoning, but recent studies have suggested that such processes are likely to involve widespread functional brain networks. To test this hypothesis, we used functional magnetic resonance imaging and a classic measure of deductive reasoning to examine changes in brain networks as a function of relational complexity. As expected, behavioral performance declined as the number of variables to be related increased. Likewise, increments in relational complexity were associated with proportional enhancements in brain activity and task-based connectivity within and between 2 cognitive control networks: A cingulo-opercular network for maintaining task set, and a fronto-parietal network for implementing trial-by-trial control. Changes in effective connectivity as a function of increased relational complexity suggested a key role for the left dorsolateral prefrontal cortex in integrating and implementing task set in a trial-by-trial manner. Our findings show that limits in relational processing are manifested in the brain as complexity-dependent modulations of large-scale networks. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Validity of semi-quantitative scale for brain MRI in unilateral cerebral palsy due to periventricular white matter lesions: Relationship with hand sensorimotor function and structural connectivity.

PubMed

Fiori, Simona; Guzzetta, Andrea; Pannek, Kerstin; Ware, Robert S; Rossi, Giuseppe; Klingels, Katrijn; Feys, Hilde; Coulthard, Alan; Cioni, Giovanni; Rose, Stephen; Boyd, Roslyn N

2015-01-01

To provide first evidence of construct validity of a semi-quantitative scale for brain structural MRI (sqMRI scale) in children with unilateral cerebral palsy (UCP) secondary to periventricular white matter (PWM) lesions, by examining the relationship with hand sensorimotor function and whole brain structural connectivity. Cross-sectional study of 50 children with UCP due to PWM lesions using 3 T (MRI), diffusion MRI and assessment of hand sensorimotor function. We explored the relationship of lobar, hemispheric and global scores on the sqMRI scale, with fractional anisotropy (FA), as a measure of brain white matter microstructure, and with hand sensorimotor measures (Assisting Hand Assessment, AHA; Jebsen-Taylor Test for Hand Function, JTTHF; Melbourne Assessment of Unilateral Upper Limb Function, MUUL; stereognosis; 2-point discrimination). Lobar and hemispheric scores on the sqMRI scale contralateral to the clinical side of hemiplegia correlated with sensorimotor paretic hand function measures and FA of a number of brain structural connections, including connections of brain areas involved in motor control (postcentral, precentral and paracentral gyri in the parietal lobe). More severe lesions correlated with lower sensorimotor performance, with the posterior limb of internal capsule score being the strongest contributor to impaired hand function. The sqMRI scale demonstrates first evidence of construct validity against impaired motor and sensory function measures and brain structural connectivity in a cohort of children with UCP due to PWM lesions. More severe lesions correlated with poorer paretic hand sensorimotor function and impaired structural connectivity in the hemisphere contralateral to the clinical side of hemiplegia. The quantitative structural MRI scoring may be a useful clinical tool for studying brain structure-function relationships but requires further validation in other populations of CP.

Genetic and Diagnostic Biomarker Development in ASD Toddlers Using Resting State Functional MRI

DTIC Science & Technology

2017-11-01

Integration Theory of intelligence (Jung and Haier, Behave Brain Sci, 2007...predicting a number of age-related phenotypes. Measures of white matter integrity in the brain are heritable and highly sensitive to both normal and...pathological aging processes. We consider the phenotypic and genetic interrelationships between epigenetic age acceleration and white matter integrity

Neuropsychiatric disorders in persons with severe traumatic brain injury: prevalence, phenomenology, and relationship with demographic, clinical, and functional features.

PubMed

Ciurli, Paola; Formisano, Rita; Bivona, Umberto; Cantagallo, Anna; Angelelli, Paola

2011-01-01

To characterize neuropsychiatric symptoms in a large group of individuals with severe traumatic brain injury (TBI) and to correlate these symptoms with demographic, clinical, and functional features. The Neuropsychiatric Inventory (NPI), a frequently used scale to assess behavioral, emotional, and motivational disorders in persons with neurological diseases, was administered to a sample of 120 persons with severe TBI. Controls were 77 healthy subjects. A wide range of neuropsychiatric symptoms was found in the population with severe TBI: apathy (42%), irritability (37%), dysphoria/depressed mood (29%), disinhibition (28%), eating disturbances (27%), and agitation (24%). A clear relationship was also found with other demographic and clinical variables. Neuropsychiatric disorders constitute an important part of the comorbidity in populations with severe TBI. Our study emphasizes the importance of integrating an overall assessment of cognitive disturbances with a specific neuropsychiatric evaluation to improve clinical understanding and treatment of persons with TBI.

Auditory and visual cortex of primates: a comparison of two sensory systems

PubMed Central

Rauschecker, Josef P.

2014-01-01

A comparative view of the brain, comparing related functions across species and sensory systems, offers a number of advantages. In particular, it allows separating the formal purpose of a model structure from its implementation in specific brains. Models of auditory cortical processing can be conceived by analogy to the visual cortex, incorporating neural mechanisms that are found in both the visual and auditory systems. Examples of such canonical features on the columnar level are direction selectivity, size/bandwidth selectivity, as well as receptive fields with segregated versus overlapping on- and off-sub-regions. On a larger scale, parallel processing pathways have been envisioned that represent the two main facets of sensory perception: 1) identification of objects and 2) processing of space. Expanding this model in terms of sensorimotor integration and control offers an overarching view of cortical function independent of sensory modality. PMID:25728177

Neural correlates of three cognitive processes involved in theory of mind and discourse comprehension.

PubMed

Lin, Nan; Yang, Xiaohong; Li, Jing; Wang, Shaonan; Hua, Huimin; Ma, Yujun; Li, Xingshan

2018-04-01

Neuroimaging studies have found that theory of mind (ToM) and discourse comprehension involve similar brain regions. These brain regions may be associated with three cognitive components that are necessarily or frequently involved in ToM and discourse comprehension, including social concept representation and retrieval, domain-general semantic integration, and domain-specific integration of social semantic contents. Using fMRI, we investigated the neural correlates of these three cognitive components by exploring how discourse topic (social/nonsocial) and discourse processing period (ending/beginning) modulate brain activation in a discourse comprehension (and also ToM) task. Different sets of brain areas showed sensitivity to discourse topic, discourse processing period, and the interaction between them, respectively. The most novel finding was that the right temporoparietal junction and middle temporal gyrus showed sensitivity to discourse processing period only during social discourse comprehension, indicating that they selectively contribute to domain-specific semantic integration. Our finding indicates how different domains of semantic information are processed and integrated in the brain and provides new insights into the neural correlates of ToM and discourse comprehension.

Coherence and recurrency: maintenance, control and integration in working memory

PubMed Central

Raffone, Antonino

2007-01-01

Working memory (WM), including a ‘central executive’, is used to guide behavior by internal goals or intentions. We suggest that WM is best described as a set of three interdependent functions which are implemented in the prefrontal cortex (PFC). These functions are maintenance, control of attention and integration. A model for the maintenance function is presented, and we will argue that this model can be extended to incorporate the other functions as well. Maintenance is the capacity to briefly maintain information in the absence of corresponding input, and even in the face of distracting information. We will argue that maintenance is based on recurrent loops between PFC and posterior parts of the brain, and probably within PFC as well. In these loops information can be held temporarily in an active form. We show that a model based on these structural ideas is capable of maintaining a limited number of neural patterns. Not the size, but the coherence of patterns (i.e., a chunking principle based on synchronous firing of interconnected cell assemblies) determines the maintenance capacity. A mechanism that optimizes coherent pattern segregation, also poses a limit to the number of assemblies (about four) that can concurrently reverberate. Top-down attentional control (in perception, action and memory retrieval) can be modelled by the modulation and re-entry of top-down information to posterior parts of the brain. Hierarchically organized modules in PFC create the possibility for information integration. We argue that large-scale multimodal integration of information creates an ‘episodic buffer’, and may even suffice for implementing a central executive. PMID:17901994

Assessing emotional status following acquired brain injury: the clinical potential of the depression, anxiety and stress scales.

PubMed

Ownsworth, Tamara; Little, Trudi; Turner, Ben; Hawkes, Anna; Shum, David

2008-10-01

To investigate the clinical potential of the Depression, Anxiety and Stress Scales (DASS 42) and its shorter version (DASS 21) for assessing emotional status following acquired brain injury. Participants included 23 individuals with traumatic brain injury (TBI), 25 individuals with brain tumour and 29 non-clinical controls. Investigations of internal consistency, test-re-test reliability, theory-consistent differences, sensitivity to change and concurrent validity were conducted. Internal consistency of the DASS was generally acceptable (r > 0.70), with the exception of the anxiety scale for the TBI sample. Test-re-test reliability (1-3 weeks) was sound for the depression scale (r > 0.75) and significant but comparatively lower for other scales (r = 0.60-0.73, p < 0.01). Theory-consistent differences were only evident between the brain tumour sample and non-clinical control sample on the anxiety scale (p < 0.01). Sensitivity to change of the DASS in the context of hospital discharge was demonstrated for depression and stress (p < 0.01), but not for anxiety (p > 0.05). Concurrent validity with the Hospital Anxiety and Depression Scale was significant for all scales of the DASS (p < 0.05). While the results generally support the clinical application of the DASS following ABI, further research examining the factor structure of existing and modified versions of the DASS is recommended.

Midsagittal Brain Variation among Non-Human Primates: Insights into Evolutionary Expansion of the Human Precuneus.

PubMed

Pereira-Pedro, Ana Sofia; Rilling, James K; Chen, Xu; Preuss, Todd M; Bruner, Emiliano

2017-01-01

The precuneus is a major element of the superior parietal lobule, positioned on the medial side of the hemisphere and reaching the dorsal surface of the brain. It is a crucial functional region for visuospatial integration, visual imagery, and body coordination. Previously, we argued that the precuneus expanded in recent human evolution, based on a combination of paleontological, comparative, and intraspecific evidence from fossil and modern human endocasts as well as from human and chimpanzee brains. The longitudinal proportions of this region are a major source of anatomical variation among adult humans and, being much larger in Homo sapiens, is the main characteristic differentiating human midsagittal brain morphology from that of our closest living primate relative, the chimpanzee. In the current shape analysis, we examine precuneus variation in non-human primates through landmark-based models, to evaluate the general pattern of variability in non-human primates, and to test whether precuneus proportions are influenced by allometric effects of brain size. Results show that precuneus proportions do not covary with brain size, and that the main difference between monkeys and apes involves a vertical expansion of the frontal and occipital regions in apes. Such differences might reflect differences in brain proportions or differences in cranial architecture. In this sample, precuneus variation is apparently not influenced by phylogenetic or allometric factors, but does vary consistently within species, at least in chimpanzees and macaques. This result further supports the hypothesis that precuneus expansion in modern humans is not merely a consequence of increasing brain size or of allometric scaling, but rather represents a species-specific morphological change in our lineage. © 2017 S. Karger AG, Basel.

Continuum of neurobehaviour and its associations with brain MRI in infants born preterm

PubMed Central

Eeles, Abbey L; Walsh, Jennifer M; Olsen, Joy E; Cuzzilla, Rocco; Thompson, Deanne K; Anderson, Peter J; Doyle, Lex W; Cheong, Jeanie L Y; Spittle, Alicia J

2017-01-01

Background Infants born very preterm (VPT) and moderate-to-late preterm (MLPT) are at increased risk of long-term neurodevelopmental deficits, but how these deficits relate to early neurobehaviour in MLPT children is unclear. The aims of this study were to compare the neurobehavioural performance of infants born across three different gestational age groups: preterm <30 weeks’ gestational age (PT<30); MLPT (32–36 weeks’ gestational age) and term age (≥37 weeks’ gestational age), and explore the relationships between MRI brain abnormalities and neurobehaviour at term-equivalent age. Methods Neurobehaviour was assessed at term-equivalent age in 149 PT<30, 200 MLPT and 200 term-born infants using the Neonatal Intensive Care UnitNetwork Neurobehavioral Scale (NNNS), the Hammersmith Neonatal Neurological Examination (HNNE) and Prechtl’s Qualitative Assessment of General Movements (GMA). A subset of 110 PT<30 and 198 MLPT infants had concurrent brain MRI. Results Proportions with abnormal neurobehaviour on the NNNS and the HNNE, and abnormal GMA all increased with decreasing gestational age. Higher brain MRI abnormality scores in some regions were associated with suboptimal neurobehaviour on the NNNS and HNNE. The relationships between brain MRI abnormality scores and suboptimal neurobehaviour were similar in both PT<30 and MLPT infants. The relationship between brain MRI abnormality scores and abnormal GMA was stronger in PT<30 infants. Conclusions There was a continuum of neurobehaviour across gestational ages. The relationships between brain abnormality scores and suboptimal neurobehaviour provide evidence that neurobehavioural assessments offer insight into the integrity of the developing brain, and may be useful in earlier identification of the highest-risk infants. PMID:29637152

Development of a cerebral circulation model for the automatic control of brain physiology.

PubMed

Utsuki, T

2015-01-01

In various clinical guidelines of brain injury, intracranial pressure (ICP), cerebral blood flow (CBF) and brain temperature (BT) are essential targets for precise management for brain resuscitation. In addition, the integrated automatic control of BT, ICP, and CBF is required for improving therapeutic effects and reducing medical costs and staff burden. Thus, a new model of cerebral circulation was developed in this study for integrative automatic control. With this model, the CBF and cerebral perfusion pressure of a normal adult male were regionally calculated according to cerebrovascular structure, blood viscosity, blood distribution, CBF autoregulation, and ICP. The analysis results were consistent with physiological knowledge already obtained with conventional studies. Therefore, the developed model is potentially available for the integrative control of the physiological state of the brain as a reference model of an automatic control system, or as a controlled object in various control simulations.

Polytrauma transitional rehabilitation programs: Comprehensive rehabilitation for community integration after brain injury.

PubMed

Duchnick, Jennifer J; Ropacki, Susan; Yutsis, Maya; Petska, Kelly; Pawlowski, Carey

2015-08-01

When the U.S. Congress passed the Veterans Health Programs Improvement Act of 2004 and the Consolidated Appropriations Act in 2005, Veterans Affairs (VA) traumatic brain injury centers responded by establishing and developing the polytrauma rehabilitation centers and polytrauma transitional rehabilitation programs (PTRPs) across 4 sites in Minneapolis, Minnesota, Palo Alto, California, Richmond, Virginia, and Tampa, Florida, in 2007. The 5th PTRP was opened in 2011 in San Antonio, Texas. This article presents the context of establishing these programs within a VA system, describes aspects of programmatic design, and shares characteristics and outcomes of individuals served by the first 4 national centers. PTRPs provide specialized, interdisciplinary brain injury rehabilitation to active-duty service members and veterans with complex rehabilitation needs. A total of 286 individuals participated in the first 4 PTRPs during the first 3 years. Admission and discharge data were collected as part of routine care, and data review focused on describing the demographic, injury, and neurobehavioral functioning outcomes across 4 sites. Mayo-Portland Adaptability Inventory Abilities, Adjustment, and Participation subscales and total scale T-scores served as primary functioning outcome measures. Mean scores are presented. Statistical analysis found a significant change in total scale T-score from admission to discharge, consistent with improved patient functional ability. Challenges associated with the development and implementation of programs are discussed. Elements of programming may be applicable for other health care organizations that seek to improve rehabilitation care delivery. (c) 2015 APA, all rights reserved).

Multiscale modeling of brain dynamics: from single neurons and networks to mathematical tools.

PubMed

Siettos, Constantinos; Starke, Jens

2016-09-01

The extreme complexity of the brain naturally requires mathematical modeling approaches on a large variety of scales; the spectrum ranges from single neuron dynamics over the behavior of groups of neurons to neuronal network activity. Thus, the connection between the microscopic scale (single neuron activity) to macroscopic behavior (emergent behavior of the collective dynamics) and vice versa is a key to understand the brain in its complexity. In this work, we attempt a review of a wide range of approaches, ranging from the modeling of single neuron dynamics to machine learning. The models include biophysical as well as data-driven phenomenological models. The discussed models include Hodgkin-Huxley, FitzHugh-Nagumo, coupled oscillators (Kuramoto oscillators, Rössler oscillators, and the Hindmarsh-Rose neuron), Integrate and Fire, networks of neurons, and neural field equations. In addition to the mathematical models, important mathematical methods in multiscale modeling and reconstruction of the causal connectivity are sketched. The methods include linear and nonlinear tools from statistics, data analysis, and time series analysis up to differential equations, dynamical systems, and bifurcation theory, including Granger causal connectivity analysis, phase synchronization connectivity analysis, principal component analysis (PCA), independent component analysis (ICA), and manifold learning algorithms such as ISOMAP, and diffusion maps and equation-free techniques. WIREs Syst Biol Med 2016, 8:438-458. doi: 10.1002/wsbm.1348 For further resources related to this article, please visit the WIREs website. © 2016 Wiley Periodicals, Inc.

Large-scale Granger causality analysis on resting-state functional MRI

NASA Astrophysics Data System (ADS)

D'Souza, Adora M.; Abidin, Anas Zainul; Leistritz, Lutz; Wismüller, Axel

2016-03-01

We demonstrate an approach to measure the information flow between each pair of time series in resting-state functional MRI (fMRI) data of the human brain and subsequently recover its underlying network structure. By integrating dimensionality reduction into predictive time series modeling, large-scale Granger Causality (lsGC) analysis method can reveal directed information flow suggestive of causal influence at an individual voxel level, unlike other multivariate approaches. This method quantifies the influence each voxel time series has on every other voxel time series in a multivariate sense and hence contains information about the underlying dynamics of the whole system, which can be used to reveal functionally connected networks within the brain. To identify such networks, we perform non-metric network clustering, such as accomplished by the Louvain method. We demonstrate the effectiveness of our approach to recover the motor and visual cortex from resting state human brain fMRI data and compare it with the network recovered from a visuomotor stimulation experiment, where the similarity is measured by the Dice Coefficient (DC). The best DC obtained was 0.59 implying a strong agreement between the two networks. In addition, we thoroughly study the effect of dimensionality reduction in lsGC analysis on network recovery. We conclude that our approach is capable of detecting causal influence between time series in a multivariate sense, which can be used to segment functionally connected networks in the resting-state fMRI.

Generation of dense statistical connectomes from sparse morphological data

PubMed Central

Egger, Robert; Dercksen, Vincent J.; Udvary, Daniel; Hege, Hans-Christian; Oberlaender, Marcel

2014-01-01

Sensory-evoked signal flow, at cellular and network levels, is primarily determined by the synaptic wiring of the underlying neuronal circuitry. Measurements of synaptic innervation, connection probabilities and subcellular organization of synaptic inputs are thus among the most active fields of research in contemporary neuroscience. Methods to measure these quantities range from electrophysiological recordings over reconstructions of dendrite-axon overlap at light-microscopic levels to dense circuit reconstructions of small volumes at electron-microscopic resolution. However, quantitative and complete measurements at subcellular resolution and mesoscopic scales to obtain all local and long-range synaptic in/outputs for any neuron within an entire brain region are beyond present methodological limits. Here, we present a novel concept, implemented within an interactive software environment called NeuroNet, which allows (i) integration of sparsely sampled (sub)cellular morphological data into an accurate anatomical reference frame of the brain region(s) of interest, (ii) up-scaling to generate an average dense model of the neuronal circuitry within the respective brain region(s) and (iii) statistical measurements of synaptic innervation between all neurons within the model. We illustrate our approach by generating a dense average model of the entire rat vibrissal cortex, providing the required anatomical data, and illustrate how to measure synaptic innervation statistically. Comparing our results with data from paired recordings in vitro and in vivo, as well as with reconstructions of synaptic contact sites at light- and electron-microscopic levels, we find that our in silico measurements are in line with previous results. PMID:25426033

Large-scale recording of thalamocortical circuits: in vivo electrophysiology with the two-dimensional electronic depth control silicon probe

PubMed Central

Fiáth, Richárd; Beregszászi, Patrícia; Horváth, Domonkos; Wittner, Lucia; Aarts, Arno A. A.; Ruther, Patrick; Neves, Hercules P.; Bokor, Hajnalka; Acsády, László

2016-01-01

Recording simultaneous activity of a large number of neurons in distributed neuronal networks is crucial to understand higher order brain functions. We demonstrate the in vivo performance of a recently developed electrophysiological recording system comprising a two-dimensional, multi-shank, high-density silicon probe with integrated complementary metal-oxide semiconductor electronics. The system implements the concept of electronic depth control (EDC), which enables the electronic selection of a limited number of recording sites on each of the probe shafts. This innovative feature of the system permits simultaneous recording of local field potentials (LFP) and single- and multiple-unit activity (SUA and MUA, respectively) from multiple brain sites with high quality and without the actual physical movement of the probe. To evaluate the in vivo recording capabilities of the EDC probe, we recorded LFP, MUA, and SUA in acute experiments from cortical and thalamic brain areas of anesthetized rats and mice. The advantages of large-scale recording with the EDC probe are illustrated by investigating the spatiotemporal dynamics of pharmacologically induced thalamocortical slow-wave activity in rats and by the two-dimensional tonotopic mapping of the auditory thalamus. In mice, spatial distribution of thalamic responses to optogenetic stimulation of the neocortex was examined. Utilizing the benefits of the EDC system may result in a higher yield of useful data from a single experiment compared with traditional passive multielectrode arrays, and thus in the reduction of animals needed for a research study. PMID:27535370

VoxResNet: Deep voxelwise residual networks for brain segmentation from 3D MR images.

PubMed

Chen, Hao; Dou, Qi; Yu, Lequan; Qin, Jing; Heng, Pheng-Ann

2018-04-15

Segmentation of key brain tissues from 3D medical images is of great significance for brain disease diagnosis, progression assessment and monitoring of neurologic conditions. While manual segmentation is time-consuming, laborious, and subjective, automated segmentation is quite challenging due to the complicated anatomical environment of brain and the large variations of brain tissues. We propose a novel voxelwise residual network (VoxResNet) with a set of effective training schemes to cope with this challenging problem. The main merit of residual learning is that it can alleviate the degradation problem when training a deep network so that the performance gains achieved by increasing the network depth can be fully leveraged. With this technique, our VoxResNet is built with 25 layers, and hence can generate more representative features to deal with the large variations of brain tissues than its rivals using hand-crafted features or shallower networks. In order to effectively train such a deep network with limited training data for brain segmentation, we seamlessly integrate multi-modality and multi-level contextual information into our network, so that the complementary information of different modalities can be harnessed and features of different scales can be exploited. Furthermore, an auto-context version of the VoxResNet is proposed by combining the low-level image appearance features, implicit shape information, and high-level context together for further improving the segmentation performance. Extensive experiments on the well-known benchmark (i.e., MRBrainS) of brain segmentation from 3D magnetic resonance (MR) images corroborated the efficacy of the proposed VoxResNet. Our method achieved the first place in the challenge out of 37 competitors including several state-of-the-art brain segmentation methods. Our method is inherently general and can be readily applied as a powerful tool to many brain-related studies, where accurate segmentation of brain structures is critical. Copyright © 2017 Elsevier Inc. All rights reserved.

Brain scaling in mammalian evolution as a consequence of concerted and mosaic changes in numbers of neurons and average neuronal cell size

PubMed Central

Herculano-Houzel, Suzana; Manger, Paul R.; Kaas, Jon H.

2014-01-01

Enough species have now been subject to systematic quantitative analysis of the relationship between the morphology and cellular composition of their brain that patterns begin to emerge and shed light on the evolutionary path that led to mammalian brain diversity. Based on an analysis of the shared and clade-specific characteristics of 41 modern mammalian species in 6 clades, and in light of the phylogenetic relationships among them, here we propose that ancestral mammal brains were composed and scaled in their cellular composition like modern afrotherian and glire brains: with an addition of neurons that is accompanied by a decrease in neuronal density and very little modification in glial cell density, implying a significant increase in average neuronal cell size in larger brains, and the allocation of approximately 2 neurons in the cerebral cortex and 8 neurons in the cerebellum for every neuron allocated to the rest of brain. We also propose that in some clades the scaling of different brain structures has diverged away from the common ancestral layout through clade-specific (or clade-defining) changes in how average neuronal cell mass relates to numbers of neurons in each structure, and how numbers of neurons are differentially allocated to each structure relative to the number of neurons in the rest of brain. Thus, the evolutionary expansion of mammalian brains has involved both concerted and mosaic patterns of scaling across structures. This is, to our knowledge, the first mechanistic model that explains the generation of brains large and small in mammalian evolution, and it opens up new horizons for seeking the cellular pathways and genes involved in brain evolution. PMID:25157220

Loss of integrity and atrophy in cingulate structural covariance networks in Parkinson's disease.

PubMed

de Schipper, Laura J; van der Grond, Jeroen; Marinus, Johan; Henselmans, Johanna M L; van Hilten, Jacobus J

2017-01-01

In Parkinson's disease (PD), the relation between cortical brain atrophy on MRI and clinical progression is not straightforward. Determination of changes in structural covariance networks - patterns of covariance in grey matter density - has shown to be a valuable technique to detect subtle grey matter variations. We evaluated how structural network integrity in PD is related to clinical data. 3 Tesla MRI was performed in 159 PD patients. We used nine standardized structural covariance networks identified in 370 healthy subjects as a template in the analysis of the PD data. Clinical assessment comprised motor features (Movement Disorder Society-Unified Parkinson's Disease Rating Scale; MDS-UPDRS motor scale) and predominantly non-dopaminergic features (SEverity of Non-dopaminergic Symptoms in Parkinson's Disease; SENS-PD scale: postural instability and gait difficulty, psychotic symptoms, excessive daytime sleepiness, autonomic dysfunction, cognitive impairment and depressive symptoms). Voxel-based analyses were performed within networks significantly associated with PD. The anterior and posterior cingulate network showed decreased integrity, associated with the SENS-PD score, p = 0.001 (β = - 0.265, η p 2  = 0.070) and p = 0.001 (β = - 0.264, η p 2  = 0.074), respectively. Of the components of the SENS-PD score, cognitive impairment and excessive daytime sleepiness were associated with atrophy within both networks. We identified loss of integrity and atrophy in the anterior and posterior cingulate networks in PD patients. Abnormalities of both networks were associated with predominantly non-dopaminergic features, specifically cognition and excessive daytime sleepiness. Our findings suggest that (components of) the cingulate networks display a specific vulnerability to the pathobiology of PD and may operate as interfaces between networks involved in cognition and alertness.

Inflammasomes link vascular disease with neuroinflammation and brain disorders

PubMed Central

Lénárt, Nikolett; Brough, David

2016-01-01

The role of inflammation in neurological disorders is increasingly recognised. Inflammatory processes are associated with the aetiology and clinical progression of migraine, psychiatric conditions, epilepsy, cerebrovascular diseases, dementia and neurodegeneration, such as seen in Alzheimer’s or Parkinson’s disease. Both central and systemic inflammatory actions have been linked with the development of brain diseases, suggesting that complex neuro-immune interactions could contribute to pathological changes in the brain across multiple temporal and spatial scales. However, the mechanisms through which inflammation impacts on neurological disease are improperly defined. To develop effective therapeutic approaches, it is imperative to understand how detrimental inflammatory processes could be blocked selectively, or controlled for prolonged periods, without compromising essential immune defence mechanisms. Increasing evidence indicates that common risk factors for brain disorders, such as atherosclerosis, diabetes, hypertension, obesity or infection involve the activation of NLRP3, NLRP1, NLRC4 or AIM2 inflammasomes, which are also associated with various neurological diseases. This review focuses on the mechanisms whereby inflammasomes, which integrate diverse inflammatory signals in response to pathogen-driven stimuli, tissue injury or metabolic alterations in multiple cell types and different organs of the body, could functionally link vascular- and neurological diseases and hence represent a promising therapeutic target. PMID:27486046

SZGR 2.0: a one-stop shop of schizophrenia candidate genes

PubMed Central

Jia, Peilin; Han, Guangchun; Zhao, Junfei; Lu, Pinyi; Zhao, Zhongming

2017-01-01

SZGR 2.0 is a comprehensive resource of candidate variants and genes for schizophrenia, covering genetic, epigenetic, transcriptomic, translational and many other types of evidence. By systematic review and curation of multiple lines of evidence, we included almost all variants and genes that have ever been reported to be associated with schizophrenia. In particular, we collected ∼4200 common variants reported in genome-wide association studies, ∼1000 de novo mutations discovered by large-scale sequencing of family samples, 215 genes spanning rare and replication copy number variations, 99 genes overlapping with linkage regions, 240 differentially expressed genes, 4651 differentially methylated genes and 49 genes as antipsychotic drug targets. To facilitate interpretation, we included various functional annotation data, especially brain eQTL, methylation QTL, brain expression featured in deep categorization of brain areas and developmental stages and brain-specific promoter and enhancer annotations. Furthermore, we conducted cross-study, cross-data type and integrative analyses of the multidimensional data deposited in SZGR 2.0, and made the data and results available through a user-friendly interface. In summary, SZGR 2.0 provides a one-stop shop of schizophrenia variants and genes and their function and regulation, providing an important resource in the schizophrenia and other mental disease community. SZGR 2.0 is available at https://bioinfo.uth.edu/SZGR/. PMID:27733502

Connectivity in the human brain dissociates entropy and complexity of auditory inputs☆

PubMed Central

Nastase, Samuel A.; Iacovella, Vittorio; Davis, Ben; Hasson, Uri

2015-01-01

Complex systems are described according to two central dimensions: (a) the randomness of their output, quantified via entropy; and (b) their complexity, which reflects the organization of a system's generators. Whereas some approaches hold that complexity can be reduced to uncertainty or entropy, an axiom of complexity science is that signals with very high or very low entropy are generated by relatively non-complex systems, while complex systems typically generate outputs with entropy peaking between these two extremes. In understanding their environment, individuals would benefit from coding for both input entropy and complexity; entropy indexes uncertainty and can inform probabilistic coding strategies, whereas complexity reflects a concise and abstract representation of the underlying environmental configuration, which can serve independent purposes, e.g., as a template for generalization and rapid comparisons between environments. Using functional neuroimaging, we demonstrate that, in response to passively processed auditory inputs, functional integration patterns in the human brain track both the entropy and complexity of the auditory signal. Connectivity between several brain regions scaled monotonically with input entropy, suggesting sensitivity to uncertainty, whereas connectivity between other regions tracked entropy in a convex manner consistent with sensitivity to input complexity. These findings suggest that the human brain simultaneously tracks the uncertainty of sensory data and effectively models their environmental generators. PMID:25536493

ADRB2, brain white matter integrity and cognitive ageing in the Lothian Birth Cohort 1936.

PubMed

Lyall, Donald M; Lopez, Lorna M; Bastin, Mark E; Maniega, Susana Muñoz; Penke, Lars; Valdés Hernández, Maria del C; Royle, Natalie A; Starr, John M; Porteous, David J; Wardlaw, Joanna M; Deary, Ian J

2013-01-01

The non-synonymous mutations arg16gly (rs1042713) and gln27glu (rs1042714) in the adrenergic β-2 receptor gene (ADRB2) have been associated with cognitive function and brain white matter integrity. The current study aimed to replicate these findings and expand them to a broader range of cognitive and brain phenotypes. The sample used is a community-dwelling group of older people, the Lothian Birth Cohort 1936. They had been assessed cognitively at age 11 years, and undertook further cognitive assessments and brain diffusion MRI tractography in older age. The sample size range for cognitive function variables was N = 686-765, and for neuroimaging variables was N = 488-587. Previously-reported findings with these genetic variants did not replicate in this cohort. Novel, nominally significant associations were observed; notably, the integrity of the left arcuate fasciculus mediated the association between rs1042714 and the Digit Symbol Coding test of information processing speed. No significant associations of cognitive and brain phenotypes with ADRB2 variants survived correction for false discovery rate. Previous findings may therefore have been subject to type 1 error. Further study into links between ADRB2, cognitive function and brain white matter integrity is required.

Endothelial β-Catenin Signaling Is Required for Maintaining Adult Blood-Brain Barrier Integrity and CNS Homeostasis

PubMed Central

Tran, Khiem A.; Zhang, Xianming; Predescu, Dan; Huang, Xiaojia; Machado, Roberto F.; Göthert, Joachim R.; Malik, Asrar B.; Valyi-Nagy, Tibor; Zhao, You-Yang

2015-01-01

Background The blood-brain barrier (BBB) formed by brain endothelial cells (ECs) interconnected by tight junctions (TJs) is essential for the homeostasis of the central nervous system (CNS). Although studies have shown the importance of various signaling molecules in BBB formation during development, little is known about the molecular basis regulating the integrity of the adult BBB. Methods and Results Using a mouse model with tamoxifen-inducible EC-restricted disruption of ctnnb1 (iCKO), here we show that endothelial β-catenin signaling is essential for maintaining BBB integrity and CNS homeostasis in adult. The iCKO mice developed severe seizures accompanied by neuronal injury, multiple brain petechial hemorrhages, and CNS inflammation, and all died postictal. Disruption of endothelial β-catenin induced BBB breakdown and downregulation of specific TJ proteins Claudin-1 and -3 in adult brain ECs. The clinical relevance of the data is indicated by the observation of decreased expression of Claudin-1 and nuclear β-catenin in brain ECs of hemorrhagic lesions of hemorrhagic stroke patients. Conclusion These results demonstrate the prerequisite role of endothelial β-catenin in maintaining the integrity of adult BBB. The results suggest that BBB dysfunction secondary to defective β-catenin transcription activity is a key pathogenic factor in hemorrhagic stroke, seizure activity and CNS inflammation. PMID:26538583

Characterizing stroke lesions using digital templates and lesion quantification tools in a web-based imaging informatics system for a large-scale stroke rehabilitation clinical trial

NASA Astrophysics Data System (ADS)

Wang, Ximing; Edwardson, Matthew; Dromerick, Alexander; Winstein, Carolee; Wang, Jing; Liu, Brent

2015-03-01

Previously, we presented an Interdisciplinary Comprehensive Arm Rehabilitation Evaluation (ICARE) imaging informatics system that supports a large-scale phase III stroke rehabilitation trial. The ePR system is capable of displaying anonymized patient imaging studies and reports, and the system is accessible to multiple clinical trial sites and users across the United States via the web. However, the prior multicenter stroke rehabilitation trials lack any significant neuroimaging analysis infrastructure. In stroke related clinical trials, identification of the stroke lesion characteristics can be meaningful as recent research shows that lesion characteristics are related to stroke scale and functional recovery after stroke. To facilitate the stroke clinical trials, we hope to gain insight into specific lesion characteristics, such as vascular territory, for patients enrolled into large stroke rehabilitation trials. To enhance the system's capability for data analysis and data reporting, we have integrated new features with the system: a digital brain template display, a lesion quantification tool and a digital case report form. The digital brain templates are compiled from published vascular territory templates at each of 5 angles of incidence. These templates were updated to include territories in the brainstem using a vascular territory atlas and the Medical Image Processing, Analysis and Visualization (MIPAV) tool. The digital templates are displayed for side-by-side comparisons and transparent template overlay onto patients' images in the image viewer. The lesion quantification tool quantifies planimetric lesion area from user-defined contour. The digital case report form stores user input into a database, then displays contents in the interface to allow for reviewing, editing, and new inputs. In sum, the newly integrated system features provide the user with readily-accessible web-based tools to identify the vascular territory involved, estimate lesion area, and store these results in a web-based digital format.

Creating the brain and interacting with the brain: an integrated approach to understanding the brain.

PubMed

Morimoto, Jun; Kawato, Mitsuo

2015-03-06

In the past two decades, brain science and robotics have made gigantic advances in their own fields, and their interactions have generated several interdisciplinary research fields. First, in the 'understanding the brain by creating the brain' approach, computational neuroscience models have been applied to many robotics problems. Second, such brain-motivated fields as cognitive robotics and developmental robotics have emerged as interdisciplinary areas among robotics, neuroscience and cognitive science with special emphasis on humanoid robots. Third, in brain-machine interface research, a brain and a robot are mutually connected within a closed loop. In this paper, we review the theoretical backgrounds of these three interdisciplinary fields and their recent progress. Then, we introduce recent efforts to reintegrate these research fields into a coherent perspective and propose a new direction that integrates brain science and robotics where the decoding of information from the brain, robot control based on the decoded information and multimodal feedback to the brain from the robot are carried out in real time and in a closed loop. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Integrating Neuroscience Knowledge and Neuropsychiatric Skills Into Psychiatry: The Way Forward.

PubMed

Schildkrout, Barbara; Benjamin, Sheldon; Lauterbach, Margo D

2016-05-01

Increasing the integration of neuroscience knowledge and neuropsychiatric skills into general psychiatric practice would facilitate expanded approaches to diagnosis, formulation, and treatment while positioning practitioners to utilize findings from emerging brain research. There is growing consensus that the field of psychiatry would benefit from more familiarity with neuroscience and neuropsychiatry. Yet there remain numerous factors impeding the integration of these domains of knowledge into general psychiatry.The authors make recommendations to move the field forward, focusing on the need for advocacy by psychiatry and medical organizations and changes in psychiatry education at all levels. For individual psychiatrists, the recommendations target obstacles to attaining expanded neuroscience and neuropsychiatry education and barriers stemming from widely held, often unspoken beliefs. For the system of psychiatric care, recommendations address the conceptual and physical separation of psychiatry from medicine, overemphasis on the Diagnostic and Statistical Manual of Mental Disorders and on psychopharmacology, and different systems in medicine and psychiatry for handling reimbursement and patient records. For psychiatry residency training, recommendations focus on expanding neuroscience/neuropsychiatry faculty and integrating neuroscience education throughout the curriculum.Psychiatry traditionally concerns itself with helping individuals construct meaningful life narratives. Brain function is one of the fundamental determinants of individuality. It is now possible for psychiatrists to integrate knowledge of neuroscience into understanding the whole person by asking, What person has this brain? How does this brain make this person unique? How does this brain make this disorder unique? What treatment will help this disorder in this person with this brain?

The dynamics of human cognition: Increasing global integration coupled with decreasing segregation found using iEEG.

PubMed

Cruzat, Josephine; Deco, Gustavo; Tauste-Campo, Adrià; Principe, Alessandro; Costa, Albert; Kringelbach, Morten L; Rocamora, Rodrigo

2018-05-15

Cognitive processing requires the ability to flexibly integrate and process information across large brain networks. How do brain networks dynamically reorganize to allow broad communication between many different brain regions in order to integrate information? We record neural activity from 12 epileptic patients using intracranial EEG while performing three cognitive tasks. We assess how the functional connectivity between different brain areas changes to facilitate communication across them. At the topological level, this facilitation is characterized by measures of integration and segregation. Across all patients, we found significant increases in integration and decreases in segregation during cognitive processing, especially in the gamma band (50-90 Hz). We also found higher levels of global synchronization and functional connectivity during task execution, again particularly in the gamma band. More importantly, functional connectivity modulations were not caused by changes in the level of the underlying oscillations. Instead, these modulations were caused by a rearrangement of the mutual synchronization between the different nodes as proposed by the "Communication Through Coherence" Theory. Copyright © 2018 Elsevier Inc. All rights reserved.

Differential Encoding of Time by Prefrontal and Striatal Network Dynamics.

PubMed

Bakhurin, Konstantin I; Goudar, Vishwa; Shobe, Justin L; Claar, Leslie D; Buonomano, Dean V; Masmanidis, Sotiris C

2017-01-25

Telling time is fundamental to many forms of learning and behavior, including the anticipation of rewarding events. Although the neural mechanisms underlying timing remain unknown, computational models have proposed that the brain represents time in the dynamics of neural networks. Consistent with this hypothesis, changing patterns of neural activity dynamically in a number of brain areas-including the striatum and cortex-has been shown to encode elapsed time. To date, however, no studies have explicitly quantified and contrasted how well different areas encode time by recording large numbers of units simultaneously from more than one area. Here, we performed large-scale extracellular recordings in the striatum and orbitofrontal cortex of mice that learned the temporal relationship between a stimulus and a reward and reported their response with anticipatory licking. We used a machine-learning algorithm to quantify how well populations of neurons encoded elapsed time from stimulus onset. Both the striatal and cortical networks encoded time, but the striatal network outperformed the orbitofrontal cortex, a finding replicated both in simultaneously and nonsimultaneously recorded corticostriatal datasets. The striatal network was also more reliable in predicting when the animals would lick up to ∼1 s before the actual lick occurred. Our results are consistent with the hypothesis that temporal information is encoded in a widely distributed manner throughout multiple brain areas, but that the striatum may have a privileged role in timing because it has a more accurate "clock" as it integrates information across multiple cortical areas. The neural representation of time is thought to be distributed across multiple functionally specialized brain structures, including the striatum and cortex. However, until now, the neural code for time has not been compared quantitatively between these areas. Here, we performed large-scale recordings in the striatum and orbitofrontal cortex of mice trained on a stimulus-reward association task involving a delay period and used a machine-learning algorithm to quantify how well populations of simultaneously recorded neurons encoded elapsed time from stimulus onset. We found that, although both areas encoded time, the striatum consistently outperformed the orbitofrontal cortex. These results suggest that the striatum may refine the code for time by integrating information from multiple inputs. Copyright © 2017 the authors 0270-6474/17/370854-17$15.00/0.

Scales

ScienceCinema

Murray Gibson

2017-12-09

Musical scales involve notes that, sounded simultaneously (chords), sound good together. The result is the left brain meeting the right brain — a Pythagorean interval of overlapping notes. This synergy would suggest less difference between the working of the right brain and the left brain than common wisdom would dictate. The pleasing sound of harmony comes when two notes share a common harmonic, meaning that their frequencies are in simple integer ratios, such as 3/2 (G/C) or 5/4 (E/C).

Integrated But Not Whole? Applying an Ontological Account of Human Organismal Unity to the Brain Death Debate.

PubMed

Moschella, Melissa

2016-10-01

As is clear in the 2008 report of the President's Council on Bioethics, the brain death debate is plagued by ambiguity in the use of such key terms as 'integration' and 'wholeness'. Addressing this problem, I offer a plausible ontological account of organismal unity drawing on the work of Hoffman and Rosenkrantz, and then apply that account to the case of brain death, concluding that a brain dead body lacks the unity proper to a human organism, and has therefore undergone a substantial change. I also show how my view can explain hard cases better than one in which biological integration (as understood by Alan Shewmon and the President's Council) is taken to imply ontological wholeness or unity. © 2016 John Wiley & Sons Ltd.

The Rich Club of the C. elegans Neuronal Connectome

PubMed Central

Vértes, Petra E.; Ahnert, Sebastian E.; Schafer, William R.; Bullmore, Edward T.

2013-01-01

There is increasing interest in topological analysis of brain networks as complex systems, with researchers often using neuroimaging to represent the large-scale organization of nervous systems without precise cellular resolution. Here we used graph theory to investigate the neuronal connectome of the nematode worm Caenorhabditis elegans, which is defined anatomically at a cellular scale as 2287 synaptic connections between 279 neurons. We identified a small number of highly connected neurons as a rich club (N = 11) interconnected with high efficiency and high connection distance. Rich club neurons comprise almost exclusively the interneurons of the locomotor circuits, with known functional importance for coordinated movement. The rich club neurons are connector hubs, with high betweenness centrality, and many intermodular connections to nodes in different modules. On identifying the shortest topological paths (motifs) between pairs of peripheral neurons, the motifs that are found most frequently traverse the rich club. The rich club neurons are born early in development, before visible movement of the animal and before the main phase of developmental elongation of its body. We conclude that the high wiring cost of the globally integrative rich club of neurons in the C. elegans connectome is justified by the adaptive value of coordinated movement of the animal. The economical trade-off between physical cost and behavioral value of rich club organization in a cellular connectome confirms theoretical expectations and recapitulates comparable results from human neuroimaging on much larger scale networks, suggesting that this may be a general and scale-invariant principle of brain network organization. PMID:23575836

Disruption of brain anatomical networks in schizophrenia: A longitudinal, diffusion tensor imaging based study.

PubMed

Sun, Yu; Chen, Yu; Lee, Renick; Bezerianos, Anastasios; Collinson, Simon L; Sim, Kang

2016-03-01

Despite convergent neuroimaging evidence indicating a wide range of brain abnormalities in schizophrenia, our understanding of alterations in the topological architecture of brain anatomical networks and how they are modulated over time, is still rudimentary. Here, we employed graph theoretical analysis of longitudinal diffusion tensor imaging data (DTI) over a 5-year period to investigate brain network topology in schizophrenia and its relationship with clinical manifestations of the illness. Using deterministic tractography, weighted brain anatomical networks were constructed from 31 patients experiencing schizophrenia and 28 age- and gender-matched healthy control subjects. Although the overall small-world characteristics were observed at both baseline and follow-up, a scan-point independent significant deficit of global integration was found in patients compared to controls, suggesting dysfunctional integration of the brain and supporting the notion of schizophrenia as a disconnection syndrome. Specifically, several brain regions (e.g., the inferior frontal gyrus and the bilateral insula) that are crucial for cognitive and emotional integration were aberrant. Furthermore, a significant group-by-longitudinal scan interaction was revealed in the characteristic path length and global efficiency, attributing to a progressive aberration of global integration in patients compared to healthy controls. Moreover, the progressive disruptions of the brain anatomical network topology were associated with the clinical symptoms of the patients. Together, our findings provide insights into the substrates of anatomical dysconnectivity patterns for schizophrenia and highlight the potential for connectome-based metrics as neural markers of illness progression and clinical change with treatment. Copyright © 2016 Elsevier B.V. All rights reserved.

HSP27 Protects the Blood-Brain Barrier Against Ischemia-Induced Loss of Integrity

PubMed Central

Leak, Rehana K.; Zhang, Lili; Stetler, R. Anne; Weng, Zhongfang; Li, Peiying; Atkins, G. Brandon; Gao, Yanqin; Chen, Jun

2014-01-01

Loss of integrity of the blood-brain barrier (BBB) in stroke victims initiates a devastating cascade of events including extravasation of blood-borne molecules, water, and inflammatory cells deep into brain parenchyma. Thus, it is important to identify mechanisms by which BBB integrity can be maintained in the face of ischemic injury in experimental stroke. We previously demonstrated that the phylogenetically conserved small heat shock protein 27 (HSP27) protects against transient middle cerebral artery occlusion (tMCAO). Here we show that HSP27 transgenic overexpression also maintains the integrity of the BBB in mice subjected to tMCAO. Extravasation of endogenous IgG antibodies and exogenous FITC-albumin into the brain following tMCAO was reduced in transgenic mice, as was total brain water content. HSP27 overexpression abolished the appearance of TUNEL-positive profiles in microvessel walls. Transgenics also exhibited less loss of microvessel proteins following tMCAO. Notably, primary endothelial cell cultures were rescued from oxygen-glucose deprivation (OGD) by lentiviral HSP27 overexpression according to four viability assays, supporting a direct effect on this cell type. Finally, HSP27 overexpression reduced the appearance of neutrophils in the brain and inhibited the secretion of five cytokines. These findings reveal a novel role for HSP27 in attenuating ischemia/reperfusion injury - the maintenance of BBB integrity. Endogenous upregulation of HSP27 after ischemia in wild-type animals may exert similar protective functions and warrants further investigation. Exogenous enhancement of HSP27 by rational drug design may lead to future therapies against a host of injuries, including but not limited to a harmful breach in brain vasculature. PMID:23469858

Large-scale automated histology in the pursuit of connectomes.

PubMed

Kleinfeld, David; Bharioke, Arjun; Blinder, Pablo; Bock, Davi D; Briggman, Kevin L; Chklovskii, Dmitri B; Denk, Winfried; Helmstaedter, Moritz; Kaufhold, John P; Lee, Wei-Chung Allen; Meyer, Hanno S; Micheva, Kristina D; Oberlaender, Marcel; Prohaska, Steffen; Reid, R Clay; Smith, Stephen J; Takemura, Shinya; Tsai, Philbert S; Sakmann, Bert

2011-11-09

How does the brain compute? Answering this question necessitates neuronal connectomes, annotated graphs of all synaptic connections within defined brain areas. Further, understanding the energetics of the brain's computations requires vascular graphs. The assembly of a connectome requires sensitive hardware tools to measure neuronal and neurovascular features in all three dimensions, as well as software and machine learning for data analysis and visualization. We present the state of the art on the reconstruction of circuits and vasculature that link brain anatomy and function. Analysis at the scale of tens of nanometers yields connections between identified neurons, while analysis at the micrometer scale yields probabilistic rules of connection between neurons and exact vascular connectivity.

Large-Scale Automated Histology in the Pursuit of Connectomes

PubMed Central

Bharioke, Arjun; Blinder, Pablo; Bock, Davi D.; Briggman, Kevin L.; Chklovskii, Dmitri B.; Denk, Winfried; Helmstaedter, Moritz; Kaufhold, John P.; Lee, Wei-Chung Allen; Meyer, Hanno S.; Micheva, Kristina D.; Oberlaender, Marcel; Prohaska, Steffen; Reid, R. Clay; Smith, Stephen J.; Takemura, Shinya; Tsai, Philbert S.; Sakmann, Bert

2011-01-01

How does the brain compute? Answering this question necessitates neuronal connectomes, annotated graphs of all synaptic connections within defined brain areas. Further, understanding the energetics of the brain's computations requires vascular graphs. The assembly of a connectome requires sensitive hardware tools to measure neuronal and neurovascular features in all three dimensions, as well as software and machine learning for data analysis and visualization. We present the state of the art on the reconstruction of circuits and vasculature that link brain anatomy and function. Analysis at the scale of tens of nanometers yields connections between identified neurons, while analysis at the micrometer scale yields probabilistic rules of connection between neurons and exact vascular connectivity. PMID:22072665

Rehabilitation of traumatic brain injury in active duty military personnel and veterans: Defense and Veterans Brain Injury Center randomized controlled trial of two rehabilitation approaches.

PubMed

Vanderploeg, Rodney D; Schwab, Karen; Walker, William C; Fraser, Jamie A; Sigford, Barbara J; Date, Elaine S; Scott, Steven G; Curtiss, Glenn; Salazar, Andres M; Warden, Deborah L

2008-12-01

To determine the relative efficacy of 2 different acute traumatic brain injury (TBI) rehabilitation approaches: cognitive didactic versus functional-experiential, and secondarily to determine relative efficacy for different patient subpopulations. Randomized, controlled, intent-to-treat trial comparing 2 alternative TBI treatment approaches. Four Veterans Administration acute inpatient TBI rehabilitation programs. Adult veterans or active duty military service members (N=360) with moderate to severe TBI. One and a half to 2.5 hours of protocol-specific cognitive-didactic versus functional-experiential rehabilitation therapy integrated into interdisciplinary acute Commission for Accreditation of Rehabilitation Facilities-accredited inpatient TBI rehabilitation programs with another 2 to 2.5 hours daily of occupational and physical therapy. Duration of protocol treatment varied from 20 to 60 days depending on the clinical needs and progress of each participant. The 2 primary outcome measures were functional independence in living and return to work and/or school assessed by independent evaluators at 1-year follow-up. Secondary outcome measures consisted of the FIM, Disability Rating Scale score, and items from the Present State Exam, Apathy Evaluation Scale, and Neurobehavioral Rating Scale. The cognitive-didactic and functional-experiential treatments did not result in overall group differences in the broad 1-year primary outcomes. However, analysis of secondary outcomes found differentially better immediate posttreatment cognitive function (mean+/-SD cognitive FIM) in participants randomized to cognitive-didactic treatment (27.3+/-6.2) than to functional treatment (25.6+/-6.0, t332=2.56, P=.01). Exploratory subgroup analyses found that younger participants in the cognitive arm had a higher rate of returning to work or school than younger patients in the functional arm, whereas participants older than 30 years and those with more years of education in the functional arm had higher rates of independent living status at 1 year posttreatment than similar patients in the cognitive arm. Results from this large multicenter randomized controlled trial comparing cognitive-didactic and functional-experiential approaches to brain injury rehabilitation indicated improved but similar long-term global functional outcome. Participants in the cognitive treatment arm achieved better short-term functional cognitive performance than patients in the functional treatment arm. The current increase in war-related brain injuries provides added urgency for rigorous study of rehabilitation treatments. (http://ClinicalTrials.gov ID# NCT00540020.).

Handedness- and brain size-related efficiency differences in small-world brain networks: a resting-state functional magnetic resonance imaging study.

PubMed

Li, Meiling; Wang, Junping; Liu, Feng; Chen, Heng; Lu, Fengmei; Wu, Guorong; Yu, Chunshui; Chen, Huafu

2015-05-01

The human brain has been described as a complex network, which integrates information with high efficiency. However, the relationships between the efficiency of human brain functional networks and handedness and brain size remain unclear. Twenty-one left-handed and 32 right-handed healthy subjects underwent a resting-state functional magnetic resonance imaging scan. The whole brain functional networks were constructed by thresholding Pearson correlation matrices of 90 cortical and subcortical regions. Graph theory-based methods were employed to further analyze their topological properties. As expected, all participants demonstrated small-world topology, suggesting a highly efficient topological structure. Furthermore, we found that smaller brains showed higher local efficiency, whereas larger brains showed higher global efficiency, reflecting a suitable efficiency balance between local specialization and global integration of brain functional activity. Compared with right-handers, significant alterations in nodal efficiency were revealed in left-handers, involving the anterior and median cingulate gyrus, middle temporal gyrus, angular gyrus, and amygdala. Our findings indicated that the functional network organization in the human brain was associated with handedness and brain size.

Topological Schemas of Cognitive Maps and Spatial Learning.

PubMed

Babichev, Andrey; Cheng, Sen; Dabaghian, Yuri A

2016-01-01

Spatial navigation in mammals is based on building a mental representation of their environment-a cognitive map. However, both the nature of this cognitive map and its underpinning in neural structures and activity remains vague. A key difficulty is that these maps are collective, emergent phenomena that cannot be reduced to a simple combination of inputs provided by individual neurons. In this paper we suggest computational frameworks for integrating the spiking signals of individual cells into a spatial map, which we call schemas. We provide examples of four schemas defined by different types of topological relations that may be neurophysiologically encoded in the brain and demonstrate that each schema provides its own large-scale characteristics of the environment-the schema integrals. Moreover, we find that, in all cases, these integrals are learned at a rate which is faster than the rate of complete training of neural networks. Thus, the proposed schema framework differentiates between the cognitive aspect of spatial learning and the physiological aspect at the neural network level.

Effect of skull flexural properties on brain response during dynamic head loading - biomed 2013.

PubMed

Harrigan, T P; Roberts, J C; Ward, E E; Carneal, C M; Merkle, A C

2013-01-01

The skull-brain complex is typically modeled as an integrated structure, similar to a fluid-filled shell. Under dynamic loads, the interaction of the skull and the underlying brain, cerebrospinal fluid, and other tissue produces the pressure and strain histories that are the basis for many theories meant to describe the genesis of traumatic brain injury. In addition, local bone strains are of interest for predicting skull fracture in blunt trauma. However, the role of skull flexure in the intracranial pressure response to blunt trauma is complex. Since the relative time scales for pressure and flexural wave transmission across the skull are not easily separated, it is difficult to separate out the relative roles of the mechanical components in this system. This study uses a finite element model of the head, which is validated for pressure transmission to the brain, to assess the influence of skull table flexural stiffness on pressure in the brain and on strain within the skull. In a Human Head Finite Element Model, the skull component was modified by attaching shell elements to the inner and outer surfaces of the existing solid elements that modeled the skull. The shell elements were given the properties of bone, and the existing solid elements were decreased so that the overall stiffness along the surface of the skull was unchanged, but the skull table bending stiffness increased by a factor of 2.4. Blunt impact loads were applied to the frontal bone centrally, using LS-Dyna. The intracranial pressure predictions and the strain predictions in the skull were compared for models with and without surface shell elements, showing that the pressures in the mid-anterior and mid-posterior of the brain were very similar, but the strains in the skull under the loads and adjacent to the loads were decreased 15% with stiffer flexural properties. Pressure equilibration to nearly hydrostatic distributions occurred, indicating that the important frequency components for typical impact loading are lower than frequencies based on pressure wave propagation across the skull. This indicates that skull flexure has a local effect on intracranial pressures but that the integrated effect of a dome-like structure under load is a significant part of load transfer in the skull in blunt trauma.

Meeting the memory challenges of brain-scale network simulation.

PubMed

Kunkel, Susanne; Potjans, Tobias C; Eppler, Jochen M; Plesser, Hans Ekkehard; Morrison, Abigail; Diesmann, Markus

2011-01-01

The development of high-performance simulation software is crucial for studying the brain connectome. Using connectome data to generate neurocomputational models requires software capable of coping with models on a variety of scales: from the microscale, investigating plasticity, and dynamics of circuits in local networks, to the macroscale, investigating the interactions between distinct brain regions. Prior to any serious dynamical investigation, the first task of network simulations is to check the consistency of data integrated in the connectome and constrain ranges for yet unknown parameters. Thanks to distributed computing techniques, it is possible today to routinely simulate local cortical networks of around 10(5) neurons with up to 10(9) synapses on clusters and multi-processor shared-memory machines. However, brain-scale networks are orders of magnitude larger than such local networks, in terms of numbers of neurons and synapses as well as in terms of computational load. Such networks have been investigated in individual studies, but the underlying simulation technologies have neither been described in sufficient detail to be reproducible nor made publicly available. Here, we discover that as the network model sizes approach the regime of meso- and macroscale simulations, memory consumption on individual compute nodes becomes a critical bottleneck. This is especially relevant on modern supercomputers such as the Blue Gene/P architecture where the available working memory per CPU core is rather limited. We develop a simple linear model to analyze the memory consumption of the constituent components of neuronal simulators as a function of network size and the number of cores used. This approach has multiple benefits. The model enables identification of key contributing components to memory saturation and prediction of the effects of potential improvements to code before any implementation takes place. As a consequence, development cycles can be shorter and less expensive. Applying the model to our freely available Neural Simulation Tool (NEST), we identify the software components dominant at different scales, and develop general strategies for reducing the memory consumption, in particular by using data structures that exploit the sparseness of the local representation of the network. We show that these adaptations enable our simulation software to scale up to the order of 10,000 processors and beyond. As memory consumption issues are likely to be relevant for any software dealing with complex connectome data on such architectures, our approach and our findings should be useful for researchers developing novel neuroinformatics solutions to the challenges posed by the connectome project.

Deep brain stimulation for severe treatment-resistant obsessive-compulsive disorder: An open-label case series.

PubMed

Farrand, Sarah; Evans, Andrew H; Mangelsdorf, Simone; Loi, Samantha M; Mocellin, Ramon; Borham, Adam; Bevilacqua, JoAnne; Blair-West, Scott; Walterfang, Mark A; Bittar, Richard G; Velakoulis, Dennis

2017-09-01

Deep brain stimulation can be of benefit in carefully selected patients with severe intractable obsessive-compulsive disorder. The aim of this paper is to describe the outcomes of the first seven deep brain stimulation procedures for obsessive-compulsive disorder undertaken at the Neuropsychiatry Unit, Royal Melbourne Hospital. The primary objective was to assess the response to deep brain stimulation treatment utilising the Yale-Brown Obsessive Compulsive Scale as a measure of symptom severity. Secondary objectives include assessment of depression and anxiety, as well as socio-occupational functioning. Patients with severe obsessive-compulsive disorder were referred by their treating psychiatrist for assessment of their suitability for deep brain stimulation. Following successful application to the Psychosurgery Review Board, patients proceeded to have deep brain stimulation electrodes implanted in either bilateral nucleus accumbens or bed nucleus of stria terminalis. Clinical assessment and symptom rating scales were undertaken pre- and post-operatively at 6- to 8-week intervals. Rating scales used included the Yale-Brown Obsessive Compulsive Scale, Obsessive Compulsive Inventory, Depression Anxiety Stress Scale and Social and Occupational Functioning Assessment Scale. Seven patients referred from four states across Australia underwent deep brain stimulation surgery and were followed for a mean of 31 months (range, 8-54 months). The sample included four females and three males, with a mean age of 46 years (range, 37-59 years) and mean duration of obsessive-compulsive disorder of 25 years (range, 15-38 years) at the time of surgery. The time from first assessment to surgery was on average 18 months. All patients showed improvement on symptom severity rating scales. Three patients showed a full response, defined as greater than 35% improvement in Yale-Brown Obsessive Compulsive Scale score, with the remaining showing responses between 7% and 20%. Deep brain stimulation was an effective treatment for obsessive-compulsive disorder in these highly selected patients. The extent of the response to deep brain stimulation varied between patients, as well as during the course of treatment for each patient. The results of this series are comparable with the literature, as well as having similar efficacy to ablative psychosurgery techniques such as capsulotomy and cingulotomy. Deep brain stimulation provides advantages over lesional psychosurgery but is more expensive and requires significant multidisciplinary input at all stages, pre- and post-operatively, ideally within a specialised tertiary clinical and/or academic centre. Ongoing research is required to better understand the neurobiological basis for obsessive-compulsive disorder and how this can be manipulated with deep brain stimulation to further improve the efficacy of this emerging treatment.

C5a alters blood-brain barrier integrity in experimental lupus

PubMed Central

Jacob, Alexander; Hack, Bradley; Chiang, Eddie; Garcia, Joe G. N.; Quigg, Richard J.; Alexander, Jessy J.

2010-01-01

The blood-brain barrier (BBB) is a crucial anatomic location in the brain. Its dysfunction complicates many neurodegenerative diseases, from acute conditions, such as sepsis, to chronic diseases, such as systemic lupus erythematosus (SLE). Several studies suggest an altered BBB in lupus, but the underlying mechanism remains unknown. In the current study, we observed a definite loss of BBB integrity in MRL/MpJ-Tnfrsf6lpr (MRL/lpr) lupus mice by IgG infiltration into brain parenchyma. In line with this result, we examined the role of complement activation, a key event in this setting, in maintenance of BBB integrity. Complement activation generates C5a, a molecule with multiple functions. Because the expression of the C5a receptor (C5aR) is significantly increased in brain endothelial cells treated with lupus serum, the study focused on the role of C5a signaling through its G-protein-coupled receptor C5aR in brain endothelial cells, in a lupus setting. Reactive oxygen species production increased significantly in endothelial cells, in both primary cells and the bEnd3 cell line treated with lupus serum from MRL/lpr mice, compared with those treated with control serum from MRL+/+ mice. In addition, increased permeability monitored by changes in transendothelial electrical resistance, cytoskeletal remodeling caused by actin fiber rearrangement, and increased iNOS mRNA expression were observed in bEnd3 cells. These disruptive effects were alleviated by pretreating cells with a C5a receptor antagonist (C5aRant) or a C5a antibody. Furthermore, the structural integrity of the vasculature in MRL/lpr brain was maintained by C5aR inhibition. These results demonstrate the regulation of BBB integrity by the complement system in a neuroinflammatory setting. For the first time, a novel role of C5a in the maintenance of BBB integrity is identified and the potential of C5a/C5aR blockade highlighted as a promising therapeutic strategy in SLE and other neurodegenerative diseases.—Jacob, A., Hack, B., Chiang, E., Garcia, J. G. N., Quigg, R. J., Alexander, J. J. C5a alters blood-brain barrier integrity in experimental lupus. PMID:20065106

Neuronavigation in the surgical management of brain tumors: current and future trends

PubMed Central

Orringer, Daniel A; Golby, Alexandra; Jolesz, Ferenc

2013-01-01

Neuronavigation has become an ubiquitous tool in the surgical management of brain tumors. This review describes the use and limitations of current neuronavigational systems for brain tumor biopsy and resection. Methods for integrating intraoperative imaging into neuronavigational datasets developed to address the diminishing accuracy of positional information that occurs over the course of brain tumor resection are discussed. In addition, the process of integration of functional MRI and tractography into navigational models is reviewed. Finally, emerging concepts and future challenges relating to the development and implementation of experimental imaging technologies in the navigational environment are explored. PMID:23116076

Highly scalable multichannel mesh electronics for stable chronic brain electrophysiology.

PubMed

Fu, Tian-Ming; Hong, Guosong; Viveros, Robert D; Zhou, Tao; Lieber, Charles M

2017-11-21

Implantable electrical probes have led to advances in neuroscience, brain-machine interfaces, and treatment of neurological diseases, yet they remain limited in several key aspects. Ideally, an electrical probe should be capable of recording from large numbers of neurons across multiple local circuits and, importantly, allow stable tracking of the evolution of these neurons over the entire course of study. Silicon probes based on microfabrication can yield large-scale, high-density recording but face challenges of chronic gliosis and instability due to mechanical and structural mismatch with the brain. Ultraflexible mesh electronics, on the other hand, have demonstrated negligible chronic immune response and stable long-term brain monitoring at single-neuron level, although, to date, it has been limited to 16 channels. Here, we present a scalable scheme for highly multiplexed mesh electronics probes to bridge the gap between scalability and flexibility, where 32 to 128 channels per probe were implemented while the crucial brain-like structure and mechanics were maintained. Combining this mesh design with multisite injection, we demonstrate stable 128-channel local field potential and single-unit recordings from multiple brain regions in awake restrained mice over 4 mo. In addition, the newly integrated mesh is used to validate stable chronic recordings in freely behaving mice. This scalable scheme for mesh electronics together with demonstrated long-term stability represent important progress toward the realization of ideal implantable electrical probes allowing for mapping and tracking single-neuron level circuit changes associated with learning, aging, and neurodegenerative diseases. Copyright © 2017 the Author(s). Published by PNAS.

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.

Dexmedetomidine Disrupts the Local and Global Efficiencies of Large-scale Brain Networks.

PubMed

Hashmi, Javeria A; Loggia, Marco L; Khan, Sheraz; Gao, Lei; Kim, Jieun; Napadow, Vitaly; Brown, Emery N; Akeju, Oluwaseun

2017-03-01

A clear understanding of the neural basis of consciousness is fundamental to research in clinical and basic neuroscience disciplines and anesthesia. Recently, decreased efficiency of information integration was suggested as a core network feature of propofol-induced unconsciousness. However, it is unclear whether this finding can be generalized to dexmedetomidine, which has a different molecular target. Dexmedetomidine was administered as a 1-μg/kg bolus over 10 min, followed by a 0.7-μg · kg · h infusion to healthy human volunteers (age range, 18 to 36 yr; n = 15). Resting-state functional magnetic resonance imaging data were acquired during baseline, dexmedetomidine-induced altered arousal, and recovery states. Zero-lag correlations between resting-state functional magnetic resonance imaging signals extracted from 131 brain parcellations were used to construct weighted brain networks. Network efficiency, degree distribution, and node strength were computed using graph analysis. Parcellated brain regions were also mapped to known resting-state networks to study functional connectivity changes. Dexmedetomidine significantly reduced the local and global efficiencies of graph theory-derived networks. Dexmedetomidine also reduced the average brain connectivity strength without impairing the degree distribution. Functional connectivity within and between all resting-state networks was modulated by dexmedetomidine. Dexmedetomidine is associated with a significant drop in the capacity for efficient information transmission at both the local and global levels. These changes result from reductions in the strength of connectivity and also manifest as reduced within and between resting-state network connectivity. These findings strengthen the hypothesis that conscious processing relies on an efficient system of information transfer in the brain.

Regional Variations in Brain Gyrification Are Associated with General Cognitive Ability in Humans

PubMed Central

Gregory, Michael D.; Kippenhan, J. Shane; Dickinson, Dwight; Carrasco, Jessica; Mattay, Venkata S.; Weinberger, Daniel R.; Berman, Karen F.

2016-01-01

Summary Searching for a neurobiological understanding of human intellectual capabilities has long occupied those very capabilities. Brain gyrification, or folding of the cortex, is as highly-evolved and variable a characteristic in humans as is intelligence. Indeed, gyrification scales with brain size, and relationships between brain size and intelligence have been demonstrated in humans [1-3]. However, gyrification shows a large degree of variability that is independent from brain size [4-6], suggesting that the former may independently contribute to cognitive abilities, and thus supporting a direct investigation of this parameter in the context of intelligence. Moreover, uncovering the regional pattern of such an association could offer insights into evolutionary and neural mechanisms. We tested for this brain-behavior relationship in two separate, independently-collected, large cohorts: 440 healthy adults and 662 healthy children, using high-resolution structural neuroimaging and comprehensive neuropsychometric batteries. In both samples, general cognitive ability was significantly associated (pfdr<0.01) with increasing gyrification in a network of neocortical regions, including large portions of the prefrontal cortex, inferior parietal lobule, and temporoparietal junction, as well as the insula, cingulate cortex, and fusiform gyrus, a regional distribution that was nearly identical in both samples (Dice similarity coefficient=0.80). This neuroanatomical pattern is consistent with an existing, well-known proposal, the Parieto-Frontal Integration Theory of Intelligence [7], and is also consistent with research in comparative evolutionary biology showing rapid neocortical expansion of these regions in humans relative to other species. These data provide a framework for understanding the neurobiology of human cognitive abilities, and suggest a potential neurocellular association. PMID:27133866

Subthalamic nucleus deep brain stimulation for Parkinson's disease: evidence for effectiveness and limitations from 12 years' experience.

PubMed

Chan, Anne Y Y; Yeung, Jonas H M; Mok, Vincent C T; Ip, Vincent H L; Wong, Adrian; Kuo, S H; Chan, Danny T M; Zhu, X L; Wong, Edith; Lau, Claire K Y; Wong, Rosanna K M; Tang, Venus; Lau, Christine; Poon, W S

2014-12-01

To present the result and experience of subthalamic nucleus deep brain stimulation for Parkinson's disease. Case series. Prince of Wales Hospital, Hong Kong. A cohort of patients with Parkinson's disease received subthalamic nucleus deep brain stimulation from September 1998 to January 2010. Patient assessment data before and after the operation were collected prospectively. Forty-one patients (21 male and 20 female) with Parkinson's disease underwent bilateral subthalamic nucleus deep brain stimulation and were followed up for a median interval of 12 months. For the whole group, the mean improvements of Unified Parkinson's Disease Rating Scale (UPDRS) parts II and III were 32.5% and 31.5%, respectively (P<0.001). Throughout the years, a multidisciplinary team was gradually built. The deep brain stimulation protocol evolved and was substantiated by updated patient selection criteria and outcome assessment, integrated imaging and neurophysiological targeting, refinement of surgical technique as well as the accumulation of experience in deep brain stimulation programming. Most of the structural improvement occurred before mid-2005. Patients receiving the operation before June 2005 (19 cases) and after (22 cases) were compared; the improvements in UPDRS part III were 13.2% and 55.2%, respectively (P<0.001). There were three operative complications (one lead migration, one cerebral haematoma, and one infection) in the group operated on before 2005. There was no operative mortality. The functional state of Parkinson's disease patients with motor disabilities refractory to best medical treatment improved significantly after subthalamic nucleus deep brain stimulation. A dedicated multidisciplinary team building, refined protocol for patient selection and assessment, improvement of targeting methods, meticulous surgical technique, and experience in programming are the key factors contributing to the improved outcome.

Implementation of the Agitated Behavior Scale in the Electronic Health Record.

PubMed

Wilson, Helen John; Dasgupta, Kritis; Michael, Kathleen

The purpose of the study was to implement an Agitated Behavior Scale through an electronic health record and to evaluate the usability of the scale in a brain injury unit at a rehabilitation hospital. A quality improvement project was conducted in the brain injury unit at a large rehabilitation hospital with registered nurses as participants using convenience sampling. The project consisted of three phases and included education, implementation of the scale in the electronic health record, and administration of the survey questionnaire, which utilized the system usability scale. The Agitated Behavior Scale was found to be usable, and there was 92.2% compliance with the use of the electronic Electronic Agitated Behavior Scale. The Agitated Behavior Scale was effectively implemented in the electronic health record and was found to be usable in the assessment of agitation. Utilization of the scale through the electronic health record on a daily basis will allow for an early identification of agitation in patients with traumatic brain injury and enable prompt interventions to manage agitation.

Cortical parcellation based on structural connectivity: A case for generative models.

PubMed

Tittgemeyer, Marc; Rigoux, Lionel; Knösche, Thomas R

2018-06-01

One of the major challenges in systems neuroscience is to identify brain networks and unravel their significance for brain function -this has led to the concept of the 'connectome'. Connectomes are currently extensively studied in large-scale international efforts at multiple scales, and follow different definitions with respect to their connections as well as their elements. Perhaps the most promising avenue for defining the elements of connectomes originates from the notion that individual brain areas maintain distinct (long-range) connection profiles. These connectivity patterns determine the areas' functional properties and also allow for their anatomical delineation and mapping. This rationale has motivated the concept of connectivity-based cortex parcellation. In the past ten years, non-invasive mapping of human brain connectivity has led to immense advances in the development of parcellation techniques and their applications. Unfortunately, many of these approaches primarily aim for confirmation of well-known, existing architectonic maps and, to that end, unsuitably incorporate prior knowledge and frequently build on circular argumentation. Often, current approaches also tend to disregard the specific apertures of connectivity measurements, as well as the anatomical specificities of cortical areas, such as spatial compactness, regional heterogeneity, inter-subject variability, the multi-scaling nature of connectivity information, and potential hierarchical organisation. From a methodological perspective, however, a useful framework that regards all of these aspects in an unbiased way is technically demanding. In this commentary, we first outline the concept of connectivity-based cortex parcellation and discuss its prospects and limitations in particular with respect to structural connectivity. To improve reliability and efficiency, we then strongly advocate for connectivity-based cortex parcellation as a modelling approach; that is, an approximation of the data based on (model) parameter inference. As such, a parcellation algorithm can be formally tested for robustness -the precision of its predictions can be quantified and statistics about potential generalization of the results can be derived. Such a framework also allows the question of model constraints to be reformulated in terms of hypothesis testing through model selection and offers a formative way to integrate anatomical knowledge in terms of prior distributions. Copyright © 2018 Elsevier Inc. All rights reserved.

Classical Wave Model of Quantum-Like Processing in Brain

NASA Astrophysics Data System (ADS)

Khrennikov, A.

2011-01-01

We discuss the conjecture on quantum-like (QL) processing of information in the brain. It is not based on the physical quantum brain (e.g., Penrose) - quantum physical carriers of information. In our approach the brain created the QL representation (QLR) of information in Hilbert space. It uses quantum information rules in decision making. The existence of such QLR was (at least preliminary) confirmed by experimental data from cognitive psychology. The violation of the law of total probability in these experiments is an important sign of nonclassicality of data. In so called "constructive wave function approach" such data can be represented by complex amplitudes. We presented 1,2 the QL model of decision making. In this paper we speculate on a possible physical realization of QLR in the brain: a classical wave model producing QLR . It is based on variety of time scales in the brain. Each pair of scales (fine - the background fluctuations of electromagnetic field and rough - the cognitive image scale) induces the QL representation. The background field plays the crucial role in creation of "superstrong QL correlations" in the brain.

Validity of semi-quantitative scale for brain MRI in unilateral cerebral palsy due to periventricular white matter lesions: Relationship with hand sensorimotor function and structural connectivity

PubMed Central

Fiori, Simona; Guzzetta, Andrea; Pannek, Kerstin; Ware, Robert S.; Rossi, Giuseppe; Klingels, Katrijn; Feys, Hilde; Coulthard, Alan; Cioni, Giovanni; Rose, Stephen; Boyd, Roslyn N.

2015-01-01

Aim To provide first evidence of construct validity of a semi-quantitative scale for brain structural MRI (sqMRI scale) in children with unilateral cerebral palsy (UCP) secondary to periventricular white matter (PWM) lesions, by examining the relationship with hand sensorimotor function and whole brain structural connectivity. Methods Cross-sectional study of 50 children with UCP due to PWM lesions using 3 T (MRI), diffusion MRI and assessment of hand sensorimotor function. We explored the relationship of lobar, hemispheric and global scores on the sqMRI scale, with fractional anisotropy (FA), as a measure of brain white matter microstructure, and with hand sensorimotor measures (Assisting Hand Assessment, AHA; Jebsen–Taylor Test for Hand Function, JTTHF; Melbourne Assessment of Unilateral Upper Limb Function, MUUL; stereognosis; 2-point discrimination). Results Lobar and hemispheric scores on the sqMRI scale contralateral to the clinical side of hemiplegia correlated with sensorimotor paretic hand function measures and FA of a number of brain structural connections, including connections of brain areas involved in motor control (postcentral, precentral and paracentral gyri in the parietal lobe). More severe lesions correlated with lower sensorimotor performance, with the posterior limb of internal capsule score being the strongest contributor to impaired hand function. Conclusion The sqMRI scale demonstrates first evidence of construct validity against impaired motor and sensory function measures and brain structural connectivity in a cohort of children with UCP due to PWM lesions. More severe lesions correlated with poorer paretic hand sensorimotor function and impaired structural connectivity in the hemisphere contralateral to the clinical side of hemiplegia. The quantitative structural MRI scoring may be a useful clinical tool for studying brain structure–function relationships but requires further validation in other populations of CP. PMID:26106533

Tick-borne encephalitis virus infects human brain microvascular endothelial cells without compromising blood-brain barrier integrity.

PubMed

Palus, Martin; Vancova, Marie; Sirmarova, Jana; Elsterova, Jana; Perner, Jan; Ruzek, Daniel

2017-07-01

Alteration of the blood-brain barrier (BBB) is a hallmark of tick-borne encephalitis (TBE), a life-threating human viral neuroinfection. However, the mechanism of BBB breakdown during TBE, as well as TBE virus (TBEV) entry into the brain is unclear. Here, primary human microvascular endothelial cells (HBMECs) were infected with TBEV to study interactions with the BBB. Although the number of infected cells was relatively low in culture (<5%), the infection was persistent with high TBEV yields (>10 6 pfu/ml). Infection did not induce any significant changes in the expression of key tight junction proteins or upregulate the expression of cell adhesion molecules, and did not alter the highly organized intercellular junctions between HBMECs. In an in vitro BBB model, the virus crossed the BBB via a transcellular pathway without compromising the integrity of the cell monolayer. The results indicate that HBMECs may support TBEV entry into the brain without altering BBB integrity. Copyright © 2017 Elsevier Inc. All rights reserved.

Epigenetic Age Acceleration Assessed with Human White-Matter Images.

PubMed

Hodgson, Karen; Carless, Melanie A; Kulkarni, Hemant; Curran, Joanne E; Sprooten, Emma; Knowles, Emma E; Mathias, Samuel; Göring, Harald H H; Yao, Nailin; Olvera, Rene L; Fox, Peter T; Almasy, Laura; Duggirala, Ravi; Blangero, John; Glahn, David C

2017-05-03

The accurate estimation of age using methylation data has proved a useful and heritable biomarker, with acceleration in epigenetic age predicting a number of age-related phenotypes. Measures of white matter integrity in the brain are also heritable and highly sensitive to both normal and pathological aging processes across adulthood. We consider the phenotypic and genetic interrelationships between epigenetic age acceleration and white matter integrity in humans. Our goal was to investigate processes that underlie interindividual variability in age-related changes in the brain. Using blood taken from a Mexican-American extended pedigree sample ( n = 628; age = 23.28-93.11 years), epigenetic age was estimated using the method developed by Horvath (2013). For n = 376 individuals, diffusion tensor imaging scans were also available. The interrelationship between epigenetic age acceleration and global white matter integrity was investigated with variance decomposition methods. To test for neuroanatomical specificity, 16 specific tracts were additionally considered. We observed negative phenotypic correlations between epigenetic age acceleration and global white matter tract integrity (ρ pheno = -0.119, p = 0.028), with evidence of shared genetic (ρ gene = -0.463, p = 0.013) but not environmental influences. Negative phenotypic and genetic correlations with age acceleration were also seen for a number of specific white matter tracts, along with additional negative phenotypic correlations between granulocyte abundance and white matter integrity. These findings (i.e., increased acceleration in epigenetic age in peripheral blood correlates with reduced white matter integrity in the brain and shares common genetic influences) provide a window into the neurobiology of aging processes within the brain and a potential biomarker of normal and pathological brain aging. SIGNIFICANCE STATEMENT Epigenetic measures can be used to predict age with a high degree of accuracy and so capture acceleration in biological age, relative to chronological age. The white matter tracts within the brain are also highly sensitive to aging processes. We show that increased biological aging (measured using epigenetic data from blood samples) is correlated with reduced integrity of white matter tracts within the human brain (measured using diffusion tensor imaging) with data from a large sample of Mexican-American families. Given the family design of the sample, we are also able to demonstrate that epigenetic aging and white matter tract integrity also share common genetic influences. Therefore, epigenetic age may be a potential, and accessible, biomarker of brain aging. Copyright © 2017 the authors 0270-6474/17/374735-09$15.00/0.

Central Artery Stiffness, Baroreflex Sensitivity, and Brain White Matter Neuronal Fiber Integrity in Older Adults

PubMed Central

Tarumi, Takashi; de Jong, Daan L.K.; Zhu, David C.; Tseng, Benjamin Y.; Liu, Jie; Hill, Candace; Riley, Jonathan; Womack, Kyle B.; Kerwin, Diana R.; Lu, Hanzhang; Cullum, C. Munro; Zhang, Rong

2015-01-01

Cerebral hypoperfusion elevates the risk of brain white matter (WM) lesions and cognitive impairment. Central artery stiffness impairs baroreflex, which controls systemic arterial perfusion, and may deteriorate neuronal fiber integrity of brain WM. The purpose of this study was to examine the associations among brain WM neuronal fiber integrity, baroreflex sensitivity (BRS), and central artery stiffness in older adults. Fifty-four adults (65±6 years) with normal cognitive function or mild cognitive impairment (MCI) were tested. The neuronal fiber integrity of brain WM was assessed from diffusion metrics acquired by diffusion tensor imaging. BRS was measured in response to acute changes in blood pressure induced by bolus injections of vasoactive drugs. Central artery stiffness was measured by carotid-femoral pulse wave velocity (cfPWV). The WM diffusion metrics including fractional anisotropy (FA) and radial (RD) and axial (AD) diffusivities, BRS, and cfPWV were not different between the control and MCI groups. Thus, the data from both groups were combined for subsequent analyses. Across WM, fiber tracts with decreased FA and increased RD were associated with lower BRS and higher cfPWV, with many of the areas presenting spatial overlap. In particular, the BRS assessed during hypotension was strongly correlated with FA and RD when compared with hypertension. Executive function performance was associated with FA and RD in the areas that correlated with cfPWV and BRS. These findings suggest that baroreflex-mediated control of systemic arterial perfusion, especially during hypotension, may play a crucial role in maintaining neuronal fiber integrity of brain WM in older adults. PMID:25623500

The Application of Integrated Knowledge-based Systems for the Biomedical Risk Assessment Intelligent Network (BRAIN)

NASA Technical Reports Server (NTRS)

Loftin, Karin C.; Ly, Bebe; Webster, Laurie; Verlander, James; Taylor, Gerald R.; Riley, Gary; Culbert, Chris; Holden, Tina; Rudisill, Marianne

1993-01-01

One of NASA's goals for long duration space flight is to maintain acceptable levels of crew health, safety, and performance. One way of meeting this goal is through the Biomedical Risk Assessment Intelligent Network (BRAIN), an integrated network of both human and computer elements. The BRAIN will function as an advisor to flight surgeons by assessing the risk of in-flight biomedical problems and recommending appropriate countermeasures. This paper describes the joint effort among various NASA elements to develop BRAIN and an Infectious Disease Risk Assessment (IDRA) prototype. The implementation of this effort addresses the technological aspects of the following: (1) knowledge acquisition; (2) integration of IDRA components; (3) use of expert systems to automate the biomedical prediction process; (4) development of a user-friendly interface; and (5) integration of the IDRA prototype and Exercise Countermeasures Intelligent System (ExerCISys). Because the C Language, CLIPS (the C Language Integrated Production System), and the X-Window System were portable and easily integrated, they were chosen as the tools for the initial IDRA prototype. The feasibility was tested by developing an IDRA prototype that predicts the individual risk of influenza. The application of knowledge-based systems to risk assessment is of great market value to the medical technology industry.

The definition of community integration: perspectives of people with brain injuries.

PubMed

McColl, M A; Carlson, P; Johnston, J; Minnes, P; Shue, K; Davies, D; Karlovits, T

1998-01-01

Despite considerable attention to community integration and related topics in the past decades, a clear definition of community integration continues to elude researchers and service providers. Common to most discussions of the topic, however, are three ideas: that integration involves relationships with others, independence in one's living situation and activities to fill one's time. The present study sought to expand this conceptualization of community integration by asking people with brain injuries for their own perspectives on community integration. This qualitative study resulted in a definition of community integration consisting of nine indicators: orientation, acceptance, conformity, close and diffuse relationships, living situation, independence, productivity and leisure. These indicators were empirically derived from the text of 116 interviews with people with moderate-severe brain injuries living in the community. Eighteen adults living in supported living programmes were followed for 1 year, to track their evolving definition of integration and the factors they felt were related to integration. The study also showed a general trend toward more positive evaluation over the year, and revealed that positive evaluation was frequently related to meeting new people and freedom from staff supervision. These findings are interpreted in the light of recommendations for community programmes.

Markers for blood-brain barrier integrity: how appropriate is Evans blue in the twenty-first century and what are the alternatives?

PubMed Central

Saunders, Norman R.; Dziegielewska, Katarzyna M.; Møllgård, Kjeld; Habgood, Mark D.

2015-01-01

In recent years there has been a resurgence of interest in brain barriers and various roles their intrinsic mechanisms may play in neurological disorders. Such studies require suitable models and markers to demonstrate integrity and functional changes at the interfaces between blood, brain, and cerebrospinal fluid. Studies of brain barrier mechanisms and measurements of plasma volume using dyes have a long-standing history, dating back to the late nineteenth-century. Their use in blood-brain barrier studies continues in spite of their known serious limitations in in vivo applications. These were well known when first introduced, but seem to have been forgotten since. Understanding these limitations is important because Evans blue is still the most commonly used marker of brain barrier integrity and those using it seem oblivious to problems arising from its in vivo application. The introduction of HRP in the mid twentieth-century was an important advance because its reaction product can be visualized at the electron microscopical level, but it also has limitations. Advantages and disadvantages of these markers will be discussed together with a critical evaluation of alternative approaches. There is no single marker suitable for all purposes. A combination of different sized, visualizable dextrans and radiolabeled molecules currently seems to be the most appropriate approach for qualitative and quantitative assessment of barrier integrity. PMID:26578854

Endothelial β-Catenin Signaling Is Required for Maintaining Adult Blood-Brain Barrier Integrity and Central Nervous System Homeostasis.

PubMed

Tran, Khiem A; Zhang, Xianming; Predescu, Dan; Huang, Xiaojia; Machado, Roberto F; Göthert, Joachim R; Malik, Asrar B; Valyi-Nagy, Tibor; Zhao, You-Yang

2016-01-12

The blood-brain barrier (BBB) formed by brain endothelial cells interconnected by tight junctions is essential for the homeostasis of the central nervous system. Although studies have shown the importance of various signaling molecules in BBB formation during development, little is known about the molecular basis regulating the integrity of the adult BBB. Using a mouse model with tamoxifen-inducible endothelial cell-restricted disruption of ctnnb1 (iCKO), we show here that endothelial β-catenin signaling is essential for maintaining BBB integrity and central nervous system homeostasis in adult mice. The iCKO mice developed severe seizures accompanied by neuronal injury, multiple brain petechial hemorrhages, and central nervous system inflammation, and all had postictal death. Disruption of endothelial β-catenin induced BBB breakdown and downregulation of the specific tight junction proteins claudin-1 and -3 in adult brain endothelial cells. The clinical relevance of the data is indicated by the observation of decreased expression of claudin-1 and nuclear β-catenin in brain endothelial cells of hemorrhagic lesions of hemorrhagic stroke patients. These results demonstrate the prerequisite role of endothelial β-catenin in maintaining the integrity of adult BBB. The results suggest that BBB dysfunction secondary to defective β-catenin transcription activity is a key pathogenic factor in hemorrhagic stroke, seizure activity, and central nervous system inflammation. © 2015 American Heart Association, Inc.

Left Brain/Right Brain Learning for Adult Education.

ERIC Educational Resources Information Center

Garvin, Barbara

1986-01-01

Contrasts and compares the theory and practice of adult education as it relates to the issue of right brain/left brain learning. The author stresses the need for a whole-brain approach to teaching and suggests that adult educators, given their philosophical directions, are the perfect potential users of this integrated system. (Editor/CT)

Cross-frequency coupling in deep brain structures upon processing the painful sensory inputs.

PubMed

Liu, C C; Chien, J H; Kim, J H; Chuang, Y F; Cheng, D T; Anderson, W S; Lenz, F A

2015-09-10

Cross-frequency coupling has been shown to be functionally significant in cortical information processing, potentially serving as a mechanism for integrating functionally relevant regions in the brain. In this study, we evaluate the hypothesis that pain-related gamma oscillatory responses are coupled with low-frequency oscillations in the frontal lobe, amygdala and hippocampus, areas known to have roles in pain processing. We delivered painful laser pulses to random locations on the dorsal hand of five patients with uncontrolled epilepsy requiring depth electrode implantation for seizure monitoring. Two blocks of 40 laser stimulations were delivered to each subject and the pain-intensity was controlled at five in a 0-10 scale by adjusting the energy level of the laser pulses. Local-field-potentials (LFPs) were recorded through bilaterally implanted depth electrode contacts to study the oscillatory responses upon processing the painful laser stimulations. Our results show that painful laser stimulations enhanced low-gamma (LH, 40-70 Hz) and high-gamma (HG, 70-110 Hz) oscillatory responses in the amygdala and hippocampal regions on the right hemisphere and these gamma responses were significantly coupled with the phases of theta (4-7 Hz) and alpha (8-1 2 Hz) rhythms during pain processing. Given the roles of these deep brain structures in emotion, these findings suggest that the oscillatory responses in these regions may play a role in integrating the affective component of pain, which may contribute to our understanding of the mechanisms underlying the affective information processing in humans. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.

Cortical thickness correlates of minor neurological signs in patients with first episode psychosis.

PubMed

Ciufolini, Simone; Ponteduro, Maria Francesca; Reis-Marques, Tiago; Taylor, Heather; Mondelli, Valeria; Pariante, Carmine M; Bonaccorso, Stefania; Chan, Raymond; Simmons, Andy; David, Anthony; Di Forti, Marta; Murray, Robin M; Dazzan, Paola

2018-05-18

Neurological soft signs (NSS) are subtle abnormalities of motor and sensory function that are present in the absence of localized brain pathological lesions. In psychoses they have been consistently associated with a distinct pattern of cortical and subcortical brain structural alterations at the level of the heteromodal cortex and basal ganglia. However, a more specific and accurate evaluation of the cytoarchitecture of the cortical mantle could further advance our understanding of the neurobiological substrate of psychosis. We investigated the relationship between brain structure and NSS in a sample of 66 patients at their first episode of psychosis. We used the Neurological Evaluation Scale for neurological assessment and high-resolution MRI and Freesurfer to explore cortical thickness and surface area. Higher rates of NSS were associated with a reduction of cortical thickness in the precentral and postcentral gyri, inferior-parietal, superior temporal, and fusiform gyri. Higher rates of NSS were also associated with smaller surface areas of superior temporal gyrus and frontal regions (including middle frontal, superior and orbito-frontal gyri). Finally, more sensory integration signs were also associated with larger surface area of the latero-occipital region. We conclude that the presence of NSS in psychosis is associated with distinct but widespread changes in cortical thickness and surface area, in areas crucial for sensory-motor integration and for the fluid execution of movement. Studying these morphological correlates with advanced neuroimaging techniques can continue to improve our knowledge on the neurobiological substrate of these important functional correlates of psychosis. Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.

Creating the brain and interacting with the brain: an integrated approach to understanding the brain

PubMed Central

Morimoto, Jun; Kawato, Mitsuo

2015-01-01

In the past two decades, brain science and robotics have made gigantic advances in their own fields, and their interactions have generated several interdisciplinary research fields. First, in the ‘understanding the brain by creating the brain’ approach, computational neuroscience models have been applied to many robotics problems. Second, such brain-motivated fields as cognitive robotics and developmental robotics have emerged as interdisciplinary areas among robotics, neuroscience and cognitive science with special emphasis on humanoid robots. Third, in brain–machine interface research, a brain and a robot are mutually connected within a closed loop. In this paper, we review the theoretical backgrounds of these three interdisciplinary fields and their recent progress. Then, we introduce recent efforts to reintegrate these research fields into a coherent perspective and propose a new direction that integrates brain science and robotics where the decoding of information from the brain, robot control based on the decoded information and multimodal feedback to the brain from the robot are carried out in real time and in a closed loop. PMID:25589568

Highly scalable multichannel mesh electronics for stable chronic brain electrophysiology

PubMed Central

Fu, Tian-Ming; Hong, Guosong; Viveros, Robert D.; Zhou, Tao

2017-01-01

Implantable electrical probes have led to advances in neuroscience, brain−machine interfaces, and treatment of neurological diseases, yet they remain limited in several key aspects. Ideally, an electrical probe should be capable of recording from large numbers of neurons across multiple local circuits and, importantly, allow stable tracking of the evolution of these neurons over the entire course of study. Silicon probes based on microfabrication can yield large-scale, high-density recording but face challenges of chronic gliosis and instability due to mechanical and structural mismatch with the brain. Ultraflexible mesh electronics, on the other hand, have demonstrated negligible chronic immune response and stable long-term brain monitoring at single-neuron level, although, to date, it has been limited to 16 channels. Here, we present a scalable scheme for highly multiplexed mesh electronics probes to bridge the gap between scalability and flexibility, where 32 to 128 channels per probe were implemented while the crucial brain-like structure and mechanics were maintained. Combining this mesh design with multisite injection, we demonstrate stable 128-channel local field potential and single-unit recordings from multiple brain regions in awake restrained mice over 4 mo. In addition, the newly integrated mesh is used to validate stable chronic recordings in freely behaving mice. This scalable scheme for mesh electronics together with demonstrated long-term stability represent important progress toward the realization of ideal implantable electrical probes allowing for mapping and tracking single-neuron level circuit changes associated with learning, aging, and neurodegenerative diseases. PMID:29109247

Tissue-like Neural Probes for Understanding and Modulating the Brain.

PubMed

Hong, Guosong; Viveros, Robert D; Zwang, Theodore J; Yang, Xiao; Lieber, Charles M

2018-03-19

Electrophysiology tools have contributed substantially to understanding brain function, yet the capabilities of conventional electrophysiology probes have remained limited in key ways because of large structural and mechanical mismatches with respect to neural tissue. In this Perspective, we discuss how the general goal of probe design in biochemistry, that the probe or label have a minimal impact on the properties and function of the system being studied, can be realized by minimizing structural, mechanical, and topological differences between neural probes and brain tissue, thus leading to a new paradigm of tissue-like mesh electronics. The unique properties and capabilities of the tissue-like mesh electronics as well as future opportunities are summarized. First, we discuss the design of an ultraflexible and open mesh structure of electronics that is tissue-like and can be delivered in the brain via minimally invasive syringe injection like molecular and macromolecular pharmaceuticals. Second, we describe the unprecedented tissue healing without chronic immune response that leads to seamless three-dimensional integration with a natural distribution of neurons and other key cells through these tissue-like probes. These unique characteristics lead to unmatched stable long-term, multiplexed mapping and modulation of neural circuits at the single-neuron level on a year time scale. Last, we offer insights on several exciting future directions for the tissue-like electronics paradigm that capitalize on their unique properties to explore biochemical interactions and signaling in a "natural" brain environment.

The highly sensitive brain: an fMRI study of sensory processing sensitivity and response to others' emotions.

PubMed

Acevedo, Bianca P; Aron, Elaine N; Aron, Arthur; Sangster, Matthew-Donald; Collins, Nancy; Brown, Lucy L

2014-07-01

Theory and research suggest that sensory processing sensitivity (SPS), found in roughly 20% of humans and over 100 other species, is a trait associated with greater sensitivity and responsiveness to the environment and to social stimuli. Self-report studies have shown that high-SPS individuals are strongly affected by others' moods, but no previous study has examined neural systems engaged in response to others' emotions. This study examined the neural correlates of SPS (measured by the standard short-form Highly Sensitive Person [HSP] scale) among 18 participants (10 females) while viewing photos of their romantic partners and of strangers displaying positive, negative, or neutral facial expressions. One year apart, 13 of the 18 participants were scanned twice. Across all conditions, HSP scores were associated with increased brain activation of regions involved in attention and action planning (in the cingulate and premotor area [PMA]). For happy and sad photo conditions, SPS was associated with activation of brain regions involved in awareness, integration of sensory information, empathy, and action planning (e.g., cingulate, insula, inferior frontal gyrus [IFG], middle temporal gyrus [MTG], and PMA). As predicted, for partner images and for happy facial photos, HSP scores were associated with stronger activation of brain regions involved in awareness, empathy, and self-other processing. These results provide evidence that awareness and responsiveness are fundamental features of SPS, and show how the brain may mediate these traits.

Gradual emergence of spontaneous correlated brain activity during fading of general anesthesia in rats: Evidences from fMRI and local field potentials

PubMed Central

Bettinardi, Ruggero G.; Tort-Colet, Núria; Ruiz-Mejias, Marcel; Sanchez-Vives, Maria V.; Deco, Gustavo

2015-01-01

Intrinsic brain activity is characterized by the presence of highly structured networks of correlated fluctuations between different regions of the brain. Such networks encompass different functions, whose properties are known to be modulated by the ongoing global brain state and are altered in several neurobiological disorders. In the present study, we induced a deep state of anesthesia in rats by means of a ketamine/medetomidine peritoneal injection, and analyzed the time course of the correlation between the brain activity in different areas while anesthesia spontaneously decreased over time. We compared results separately obtained from fMRI and local field potentials (LFPs) under the same anesthesia protocol, finding that while most profound phases of anesthesia can be described by overall sparse connectivity, stereotypical activity and poor functional integration, during lighter states different frequency-specific functional networks emerge, endowing the gradual restoration of structured large-scale activity seen during rest. Noteworthy, our in vivo results show that those areas belonging to the same functional network (the default-mode) exhibited sustained correlated oscillations around 10 Hz throughout the protocol, suggesting the presence of a specific functional backbone that is preserved even during deeper phases of anesthesia. Finally, the overall pattern of results obtained from both imaging and in vivo-recordings suggests that the progressive emergence from deep anesthesia is reflected by a corresponding gradual increase of organized correlated oscillations across the cortex. PMID:25804643

ViSimpl: Multi-View Visual Analysis of Brain Simulation Data

PubMed Central

Galindo, Sergio E.; Toharia, Pablo; Robles, Oscar D.; Pastor, Luis

2016-01-01

After decades of independent morphological and functional brain research, a key point in neuroscience nowadays is to understand the combined relationships between the structure of the brain and its components and their dynamics on multiple scales, ranging from circuits of neurons at micro or mesoscale to brain regions at macroscale. With such a goal in mind, there is a vast amount of research focusing on modeling and simulating activity within neuronal structures, and these simulations generate large and complex datasets which have to be analyzed in order to gain the desired insight. In such context, this paper presents ViSimpl, which integrates a set of visualization and interaction tools that provide a semantic view of brain data with the aim of improving its analysis procedures. ViSimpl provides 3D particle-based rendering that allows visualizing simulation data with their associated spatial and temporal information, enhancing the knowledge extraction process. It also provides abstract representations of the time-varying magnitudes supporting different data aggregation and disaggregation operations and giving also focus and context clues. In addition, ViSimpl tools provide synchronized playback control of the simulation being analyzed. Finally, ViSimpl allows performing selection and filtering operations relying on an application called NeuroScheme. All these views are loosely coupled and can be used independently, but they can also work together as linked views, both in centralized and distributed computing environments, enhancing the data exploration and analysis procedures. PMID:27774062

ViSimpl: Multi-View Visual Analysis of Brain Simulation Data.

PubMed

Galindo, Sergio E; Toharia, Pablo; Robles, Oscar D; Pastor, Luis

2016-01-01

After decades of independent morphological and functional brain research, a key point in neuroscience nowadays is to understand the combined relationships between the structure of the brain and its components and their dynamics on multiple scales, ranging from circuits of neurons at micro or mesoscale to brain regions at macroscale. With such a goal in mind, there is a vast amount of research focusing on modeling and simulating activity within neuronal structures, and these simulations generate large and complex datasets which have to be analyzed in order to gain the desired insight. In such context, this paper presents ViSimpl, which integrates a set of visualization and interaction tools that provide a semantic view of brain data with the aim of improving its analysis procedures. ViSimpl provides 3D particle-based rendering that allows visualizing simulation data with their associated spatial and temporal information, enhancing the knowledge extraction process. It also provides abstract representations of the time-varying magnitudes supporting different data aggregation and disaggregation operations and giving also focus and context clues. In addition, ViSimpl tools provide synchronized playback control of the simulation being analyzed. Finally, ViSimpl allows performing selection and filtering operations relying on an application called NeuroScheme. All these views are loosely coupled and can be used independently, but they can also work together as linked views, both in centralized and distributed computing environments, enhancing the data exploration and analysis procedures.

The highly sensitive brain: an fMRI study of sensory processing sensitivity and response to others' emotions

PubMed Central

Acevedo, Bianca P; Aron, Elaine N; Aron, Arthur; Sangster, Matthew-Donald; Collins, Nancy; Brown, Lucy L

2014-01-01

Background Theory and research suggest that sensory processing sensitivity (SPS), found in roughly 20% of humans and over 100 other species, is a trait associated with greater sensitivity and responsiveness to the environment and to social stimuli. Self-report studies have shown that high-SPS individuals are strongly affected by others' moods, but no previous study has examined neural systems engaged in response to others' emotions. Methods This study examined the neural correlates of SPS (measured by the standard short-form Highly Sensitive Person [HSP] scale) among 18 participants (10 females) while viewing photos of their romantic partners and of strangers displaying positive, negative, or neutral facial expressions. One year apart, 13 of the 18 participants were scanned twice. Results Across all conditions, HSP scores were associated with increased brain activation of regions involved in attention and action planning (in the cingulate and premotor area [PMA]). For happy and sad photo conditions, SPS was associated with activation of brain regions involved in awareness, integration of sensory information, empathy, and action planning (e.g., cingulate, insula, inferior frontal gyrus [IFG], middle temporal gyrus [MTG], and PMA). Conclusions As predicted, for partner images and for happy facial photos, HSP scores were associated with stronger activation of brain regions involved in awareness, empathy, and self-other processing. These results provide evidence that awareness and responsiveness are fundamental features of SPS, and show how the brain may mediate these traits. PMID:25161824

Right-Brain/Left-Brain Integrated Associative Processor Employing Convertible Multiple-Instruction-Stream Multiple-Data-Stream Elements

NASA Astrophysics Data System (ADS)

Hayakawa, Hitoshi; Ogawa, Makoto; Shibata, Tadashi

2005-04-01

A very large scale integrated circuit (VLSI) architecture for a multiple-instruction-stream multiple-data-stream (MIMD) associative processor has been proposed. The processor employs an architecture that enables seamless switching from associative operations to arithmetic operations. The MIMD element is convertible to a regular central processing unit (CPU) while maintaining its high performance as an associative processor. Therefore, the MIMD associative processor can perform not only on-chip perception, i.e., searching for the vector most similar to an input vector throughout the on-chip cache memory, but also arithmetic and logic operations similar to those in ordinary CPUs, both simultaneously in parallel processing. Three key technologies have been developed to generate the MIMD element: associative-operation-and-arithmetic-operation switchable calculation units, a versatile register control scheme within the MIMD element for flexible operations, and a short instruction set for minimizing the memory size for program storage. Key circuit blocks were designed and fabricated using 0.18 μm complementary metal-oxide-semiconductor (CMOS) technology. As a result, the full-featured MIMD element is estimated to be 3 mm2, showing the feasibility of an 8-parallel-MIMD-element associative processor in a single chip of 5 mm× 5 mm.

A Tensor-Product-Kernel Framework for Multiscale Neural Activity Decoding and Control

PubMed Central

Li, Lin; Brockmeier, Austin J.; Choi, John S.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.

2014-01-01

Brain machine interfaces (BMIs) have attracted intense attention as a promising technology for directly interfacing computers or prostheses with the brain's motor and sensory areas, thereby bypassing the body. The availability of multiscale neural recordings including spike trains and local field potentials (LFPs) brings potential opportunities to enhance computational modeling by enriching the characterization of the neural system state. However, heterogeneity on data type (spike timing versus continuous amplitude signals) and spatiotemporal scale complicates the model integration of multiscale neural activity. In this paper, we propose a tensor-product-kernel-based framework to integrate the multiscale activity and exploit the complementary information available in multiscale neural activity. This provides a common mathematical framework for incorporating signals from different domains. The approach is applied to the problem of neural decoding and control. For neural decoding, the framework is able to identify the nonlinear functional relationship between the multiscale neural responses and the stimuli using general purpose kernel adaptive filtering. In a sensory stimulation experiment, the tensor-product-kernel decoder outperforms decoders that use only a single neural data type. In addition, an adaptive inverse controller for delivering electrical microstimulation patterns that utilizes the tensor-product kernel achieves promising results in emulating the responses to natural stimulation. PMID:24829569

The proximal-to-distal sequence in upper-limb motions on multiple levels and time scales.

PubMed

Serrien, Ben; Baeyens, Jean-Pierre

2017-10-01

The proximal-to-distal sequence is a phenomenon that can be observed in a large variety of motions of the upper limbs in both humans and other mammals. The mechanisms behind this sequence are not completely understood and motor control theories able to explain this phenomenon are currently incomplete. The aim of this narrative review is to take a theoretical constraints-led approach to the proximal-to-distal sequence and provide a broad multidisciplinary overview of relevant literature. This sequence exists at multiple levels (brain, spine, muscles, kinetics and kinematics) and on multiple time scales (motion, motor learning and development, growth and possibly even evolution). We hypothesize that the proximodistal spatiotemporal direction on each time scale and level provides part of the organismic constraints that guide the dynamics at the other levels and time scales. The constraint-led approach in this review may serve as a first onset towards integration of evidence and a framework for further experimentation to reveal the dynamics of the proximal-to-distal sequence. Copyright © 2017 Elsevier B.V. All rights reserved.

Lateral automobile impacts and the risk of traumatic brain injury.

PubMed

Bazarian, Jeffrey J; Fisher, Susan Gross; Flesher, William; Lillis, Robert; Knox, Kerry L; Pearson, Thomas A

2004-08-01

We determine the relative risk and severity of traumatic brain injury among occupants of lateral impacts compared with occupants of nonlateral impacts. This was a secondary analysis of the National Highway Traffic Safety Administration's National Automotive Sampling System, Crashworthiness Data Systems for 2000. Analysis was restricted to occupants of vehicles in which at least 1 person experienced an injury with Abbreviated Injury Scale score greater than 2. Traumatic brain injury was defined as an injury to the head or skull with an Abbreviated Injury Scale score greater than 2. Outcomes were analyzed using the chi2 test and multivariate logistic regression, with adjustment of variance to account for weighted probability sampling. Of the 1,115 occupants available for analysis, impact direction was lateral for 230 (18.42%) occupants and nonlateral for 885 (81.58%) occupants. One hundred eighty-seven (16.07%) occupants experienced a traumatic brain injury, 14.63% after lateral and 16.39% after nonlateral impact. The unadjusted relative risk of traumatic brain injury after lateral impact was 0.89 (95% confidence interval [CI] 0.51 to 1.56). After adjusting for several important crash-related variables, the relative risk of traumatic brain injury was 2.60 (95% CI 1.1 to 6.0). Traumatic brain injuries were more severe after lateral impact according to Abbreviated Injury Scale and Glasgow Coma Scale scores. The proportion of fatal or critical crash-related traumatic brain injuries attributable to lateral impact was 23.5%. Lateral impact is an important independent risk factor for the development of traumatic brain injury after a serious motor vehicle crash. Traumatic brain injuries incurred after lateral impact are more severe than those resulting from nonlateral impact. Vehicle modifications that increase head protection could reduce crash-related severe traumatic brain injuries by up to 61% and prevent up to 2,230 fatal or critical traumatic brain injuries each year in the United States.

High-Throughput Screening for Identification of Blood-Brain Barrier Integrity Enhancers: A Drug Repurposing Opportunity to Rectify Vascular Amyloid Toxicity.

PubMed

Qosa, Hisham; Mohamed, Loqman A; Al Rihani, Sweilem B; Batarseh, Yazan S; Duong, Quoc-Viet; Keller, Jeffrey N; Kaddoumi, Amal

2016-07-06

The blood-brain barrier (BBB) is a dynamic interface that maintains brain homeostasis and protects it from free entry of chemicals, toxins, and drugs. The barrier function of the BBB is maintained mainly by capillary endothelial cells that physically separate brain from blood. Several neurological diseases, such as Alzheimer's disease (AD), are known to disrupt BBB integrity. In this study, a high-throughput screening (HTS) was developed to identify drugs that rectify/protect BBB integrity from vascular amyloid toxicity associated with AD progression. Assessing Lucifer Yellow permeation across in-vitro BBB model composed from mouse brain endothelial cells (bEnd3) grown on 96-well plate inserts was used to screen 1280 compounds of Sigma LOPAC®1280 library for modulators of bEnd3 monolayer integrity. HTS identified 62 compounds as disruptors, and 50 compounds as enhancers of the endothelial barrier integrity. From these 50 enhancers, 7 FDA approved drugs were identified with EC50 values ranging from 0.76-4.56 μM. Of these 7 drugs, 5 were able to protect bEnd3-based BBB model integrity against amyloid toxicity. Furthermore, to test the translational potential to humans, the 7 drugs were tested for their ability to rectify the disruptive effect of Aβ in the human endothelial cell line hCMEC/D3. Only 3 (etodolac, granisetron, and beclomethasone) out of the 5 effective drugs in the bEnd3-based BBB model demonstrated a promising effect to protect the hCMEC/D3-based BBB model integrity. These drugs are compelling candidates for repurposing as therapeutic agents that could rectify dysfunctional BBB associated with AD.

High-throughput screening for identification of blood-brain barrier integrity enhancers: a drug repurposing opportunity to rectify vascular amyloid toxicity

PubMed Central

Qosa, Hisham; Mohamed, Loqman A.; Al Rihani, Sweilem B.; Batarseh, Yazan S.; Duong, Quoc-Viet; Keller, Jeffrey N.; Kaddoumi, Amal

2016-01-01

The blood-brain barrier (BBB) is a dynamic interface that maintains brain homeostasis and protects it from free entry of chemicals, toxins and drugs. The barrier function of the BBB is maintained mainly by capillary endothelial cells that physically separate brain from blood. Several neurological diseases, such as Alzheimer’s disease (AD), are known to disrupt BBB integrity. In this study, a high-throughput screening (HTS) was developed to identify drugs that rectify/protect BBB integrity from vascular amyloid toxicity associated with AD progression. Assessing Lucifer Yellow permeation across in-vitro BBB model composed from mouse brain endothelial cells (bEnd3) grown on 96-well plate inserts was used to screen 1280 compounds of Sigma LOPAC®1280 library for modulators of bEnd3 monolayer integrity. HTS identified 62 compounds as disruptors, and 50 compounds as enhancers of the endothelial barrier integrity. From these 50 enhancers, 7 FDA approved drugs were identified with EC50 values ranging from 0.76–4.56 μM. Of these 7 drugs, five were able to protect bEnd3-based BBB model integrity against amyloid toxicity. Furthermore, to test the translational potential to humans, the 7 drugs were tested for their ability to rectify the disruptive effect of Aβ in the human endothelial cell line hCMEC/D3. Only 3 (etodolac, granisetron and beclomethasone) out of the 5 effective drugs in the bEnd3-based BBB model demonstrated a promising effect to protect the hCMEC/D3-based BBB model integrity. These drugs are compelling candidates for repurposing as therapeutic agents that could rectify dysfunctional BBB associated with AD. PMID:27392852

4Bs or Not 4Bs: Bricks, Bytes, Brains, and Bandwidth

ERIC Educational Resources Information Center

Treat, Tod

2011-01-01

The effective integration of planning to include bricks, bytes, brains, and bandwidth (the 4Bs) represents an opportunity for community colleges to extend their capacity as knowledge-intensive organizations, coupling knowledge, technology, and learning. Integration is important to ensure that the interplay among organizations, agents within them,…

The brain as a "hyper-network": the key role of neural networks as main producers of the integrated brain actions especially via the "broadcasted" neuroconnectomics.

PubMed

Agnati, Luigi F; Marcoli, Manuela; Maura, Guido; Woods, Amina; Guidolin, Diego

2018-06-01

Investigations of brain complex integrative actions should consider beside neural networks, glial, extracellular molecular, and fluid channels networks. The present paper proposes that all these networks are assembled into the brain hyper-network that has as fundamental components, the tetra-partite synapses, formed by neural, glial, and extracellular molecular networks. Furthermore, peri-synaptic astrocytic processes by modulating the perviousness of extracellular fluid channels control the signals impinging on the tetra-partite synapses. It has also been surmised that global signalling via astrocytes networks and highly pervasive signals, such as electromagnetic fields (EMFs), allow the appropriate integration of the various networks especially at crucial nodes level, the tetra-partite synapses. As a matter of fact, it has been shown that astrocytes can form gap-junction-coupled syncytia allowing intercellular communication characterised by a rapid and possibly long-distance transfer of signals. As far as the EMFs are concerned, the concept of broadcasted neuroconnectomics (BNC) has been introduced to describe highly pervasive signals involved in resetting the information handling of brain networks at various miniaturisation levels. In other words, BNC creates, thanks to the EMFs, generated especially by neurons, different assemblages among the various networks forming the brain hyper-network. Thus, it is surmised that neuronal networks are the "core components" of the brain hyper-network that has as special "nodes" the multi-facet tetra-partite synapses. Furthermore, it is suggested that investigations on the functional plasticity of multi-partite synapses in response to BNC can be the background for a new understanding and perhaps a new modelling of brain morpho-functional organisation and integrative actions.

Tau depletion prevents progressive blood-brain barrier damage in a mouse model of tauopathy.

PubMed

Blair, Laura J; Frauen, Haley D; Zhang, Bo; Nordhues, Bryce A; Bijan, Sara; Lin, Yen-Chi; Zamudio, Frank; Hernandez, Lidice D; Sabbagh, Jonathan J; Selenica, Maj-Linda B; Dickey, Chad A

2015-01-31

The blood-brain barrier (BBB) is damaged in tauopathies, including progressive supranuclear palsy (PSP) and Alzheimer's disease (AD), which is thought to contribute to pathogenesis later in the disease course. In AD, BBB dysfunction has been associated with amyloid beta (Aß) pathology, but the role of tau in this process is not well characterized. Since increased BBB permeability is found in tauopathies without Aß pathology, like PSP, we suspected that tau accumulation alone could not only be sufficient, but even more important than Aß for BBB damage. Longitudinal evaluation of brain tissue from the tetracycline-regulatable rTg4510 tau transgenic mouse model showed progressive IgG, T cell and red blood cell infiltration. The Evans blue (EB) dye that is excluded from the brain when the BBB is intact also permeated the brains of rTg4510 mice following peripheral administration, indicative of a bonafide BBB defect, but this was only evident later in life. Thus, despite the marked brain atrophy and inflammation that occurs earlier in this model, BBB integrity is maintained. Interestingly, BBB dysfunction emerged at the same time that perivascular tau emerged around major hippocampal blood vessels. However, when tau expression was suppressed using doxycycline, BBB integrity was preserved, suggesting that the BBB can be stabilized in a tauopathic brain by reducing tau levels. For the first time, these data demonstrate that tau alone can initiate breakdown of the BBB, but the BBB is remarkably resilient, maintaining its integrity in the face of marked brain atrophy, neuroinflammation and toxic tau accumulation. Moreover, the BBB can recover integrity when tau levels are reduced. Thus, late stage interventions targeting tau may slow the vascular contributions to cognitive impairment and dementia that occur in tauopathies.

Reliability of a novel, semi-quantitative scale for classification of structural brain magnetic resonance imaging in children with cerebral palsy.

PubMed

Fiori, Simona; Cioni, Giovanni; Klingels, Katrjin; Ortibus, Els; Van Gestel, Leen; Rose, Stephen; Boyd, Roslyn N; Feys, Hilde; Guzzetta, Andrea

2014-09-01

To describe the development of a novel rating scale for classification of brain structural magnetic resonance imaging (MRI) in children with cerebral palsy (CP) and to assess its interrater and intrarater reliability. The scale consists of three sections. Section 1 contains descriptive information about the patient and MRI. Section 2 contains the graphical template of brain hemispheres onto which the lesion is transposed. Section 3 contains the scoring system for the quantitative analysis of the lesion characteristics, grouped into different global scores and subscores that assess separately side, regions, and depth. A larger interrater and intrarater reliability study was performed in 34 children with CP (22 males, 12 females; mean age at scan of 9 y 5 mo [SD 3 y 3 mo], range 4 y-16 y 11 mo; Gross Motor Function Classification System level I, [n=22], II [n=10], and level III [n=2]). Very high interrater and intrarater reliability of the total score was found with indices above 0.87. Reliability coefficients of the lobar and hemispheric subscores ranged between 0.53 and 0.95. Global scores for hemispheres, basal ganglia, brain stem, and corpus callosum showed reliability coefficients above 0.65. This study presents the first visual, semi-quantitative scale for classification of brain structural MRI in children with CP. The high degree of reliability of the scale supports its potential application for investigating the relationship between brain structure and function and examining treatment response according to brain lesion severity in children with CP. © 2014 Mac Keith Press.

Large-scale functional networks connect differently for processing words and symbol strings.

PubMed

Liljeström, Mia; Vartiainen, Johanna; Kujala, Jan; Salmelin, Riitta

2018-01-01

Reconfigurations of synchronized large-scale networks are thought to be central neural mechanisms that support cognition and behavior in the human brain. Magnetoencephalography (MEG) recordings together with recent advances in network analysis now allow for sub-second snapshots of such networks. In the present study, we compared frequency-resolved functional connectivity patterns underlying reading of single words and visual recognition of symbol strings. Word reading emphasized coherence in a left-lateralized network with nodes in classical perisylvian language regions, whereas symbol processing recruited a bilateral network, including connections between frontal and parietal regions previously associated with spatial attention and visual working memory. Our results illustrate the flexible nature of functional networks, whereby processing of different form categories, written words vs. symbol strings, leads to the formation of large-scale functional networks that operate at distinct oscillatory frequencies and incorporate task-relevant regions. These results suggest that category-specific processing should be viewed not so much as a local process but as a distributed neural process implemented in signature networks. For words, increased coherence was detected particularly in the alpha (8-13 Hz) and high gamma (60-90 Hz) frequency bands, whereas increased coherence for symbol strings was observed in the high beta (21-29 Hz) and low gamma (30-45 Hz) frequency range. These findings attest to the role of coherence in specific frequency bands as a general mechanism for integrating stimulus-dependent information across brain regions.

Foundational perspectives on causality in large-scale brain networks

NASA Astrophysics Data System (ADS)

Mannino, Michael; Bressler, Steven L.

2015-12-01

A profusion of recent work in cognitive neuroscience has been concerned with the endeavor to uncover causal influences in large-scale brain networks. However, despite the fact that many papers give a nod to the important theoretical challenges posed by the concept of causality, this explosion of research has generally not been accompanied by a rigorous conceptual analysis of the nature of causality in the brain. This review provides both a descriptive and prescriptive account of the nature of causality as found within and between large-scale brain networks. In short, it seeks to clarify the concept of causality in large-scale brain networks both philosophically and scientifically. This is accomplished by briefly reviewing the rich philosophical history of work on causality, especially focusing on contributions by David Hume, Immanuel Kant, Bertrand Russell, and Christopher Hitchcock. We go on to discuss the impact that various interpretations of modern physics have had on our understanding of causality. Throughout all this, a central focus is the distinction between theories of deterministic causality (DC), whereby causes uniquely determine their effects, and probabilistic causality (PC), whereby causes change the probability of occurrence of their effects. We argue that, given the topological complexity of its large-scale connectivity, the brain should be considered as a complex system and its causal influences treated as probabilistic in nature. We conclude that PC is well suited for explaining causality in the brain for three reasons: (1) brain causality is often mutual; (2) connectional convergence dictates that only rarely is the activity of one neuronal population uniquely determined by another one; and (3) the causal influences exerted between neuronal populations may not have observable effects. A number of different techniques are currently available to characterize causal influence in the brain. Typically, these techniques quantify the statistical likelihood that a change in the activity of one neuronal population affects the activity in another. We argue that these measures access the inherently probabilistic nature of causal influences in the brain, and are thus better suited for large-scale brain network analysis than are DC-based measures. Our work is consistent with recent advances in the philosophical study of probabilistic causality, which originated from inherent conceptual problems with deterministic regularity theories. It also resonates with concepts of stochasticity that were involved in establishing modern physics. In summary, we argue that probabilistic causality is a conceptually appropriate foundation for describing neural causality in the brain.

Foundational perspectives on causality in large-scale brain networks.

PubMed

Mannino, Michael; Bressler, Steven L

2015-12-01

A profusion of recent work in cognitive neuroscience has been concerned with the endeavor to uncover causal influences in large-scale brain networks. However, despite the fact that many papers give a nod to the important theoretical challenges posed by the concept of causality, this explosion of research has generally not been accompanied by a rigorous conceptual analysis of the nature of causality in the brain. This review provides both a descriptive and prescriptive account of the nature of causality as found within and between large-scale brain networks. In short, it seeks to clarify the concept of causality in large-scale brain networks both philosophically and scientifically. This is accomplished by briefly reviewing the rich philosophical history of work on causality, especially focusing on contributions by David Hume, Immanuel Kant, Bertrand Russell, and Christopher Hitchcock. We go on to discuss the impact that various interpretations of modern physics have had on our understanding of causality. Throughout all this, a central focus is the distinction between theories of deterministic causality (DC), whereby causes uniquely determine their effects, and probabilistic causality (PC), whereby causes change the probability of occurrence of their effects. We argue that, given the topological complexity of its large-scale connectivity, the brain should be considered as a complex system and its causal influences treated as probabilistic in nature. We conclude that PC is well suited for explaining causality in the brain for three reasons: (1) brain causality is often mutual; (2) connectional convergence dictates that only rarely is the activity of one neuronal population uniquely determined by another one; and (3) the causal influences exerted between neuronal populations may not have observable effects. A number of different techniques are currently available to characterize causal influence in the brain. Typically, these techniques quantify the statistical likelihood that a change in the activity of one neuronal population affects the activity in another. We argue that these measures access the inherently probabilistic nature of causal influences in the brain, and are thus better suited for large-scale brain network analysis than are DC-based measures. Our work is consistent with recent advances in the philosophical study of probabilistic causality, which originated from inherent conceptual problems with deterministic regularity theories. It also resonates with concepts of stochasticity that were involved in establishing modern physics. In summary, we argue that probabilistic causality is a conceptually appropriate foundation for describing neural causality in the brain. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

Manufacturing, assembling and packaging of miniaturized implants for neural prostheses and brain-machine interfaces

NASA Astrophysics Data System (ADS)

Stieglitz, Thomas

2009-05-01

Implantable medical devices to interface with muscles, peripheral nerves, and the brain have been developed for many applications over the last decades. They have been applied in fundamental neuroscientific studies as well as in diagnosis, therapy and rehabilitation in clinical practice. Success stories of these implants have been written with help of precision mechanics manufacturing techniques. Latest cutting edge research approaches to restore vision in blind persons and to develop an interface with the human brain as motor control interface, however, need more complex systems and larger scales of integration and higher degrees of miniaturization. Microsystems engineering offers adequate tools, methods, and materials but so far, no MEMS based active medical device has been transferred into clinical practice. Silicone rubber, polyimide, parylene as flexible materials and silicon and alumina (aluminum dioxide ceramics) as substrates and insulation or packaging materials, respectively, and precious metals as electrodes have to be combined to systems that do not harm the biological target structure and have to work reliably in a wet environment with ions and proteins. Here, different design, manufacturing and packaging paradigms will be presented and strengths and drawbacks will be discussed in close relation to the envisioned biological and medical applications.

Comprehensive optical and data management infrastructure for high-throughput light-sheet microscopy of whole mouse brains.

PubMed

Müllenbroich, M Caroline; Silvestri, Ludovico; Onofri, Leonardo; Costantini, Irene; Hoff, Marcel Van't; Sacconi, Leonardo; Iannello, Giulio; Pavone, Francesco S

2015-10-01

Comprehensive mapping and quantification of neuronal projections in the central nervous system requires high-throughput imaging of large volumes with microscopic resolution. To this end, we have developed a confocal light-sheet microscope that has been optimized for three-dimensional (3-D) imaging of structurally intact clarified whole-mount mouse brains. We describe the optical and electromechanical arrangement of the microscope and give details on the organization of the microscope management software. The software orchestrates all components of the microscope, coordinates critical timing and synchronization, and has been written in a versatile and modular structure using the LabVIEW language. It can easily be adapted and integrated to other microscope systems and has been made freely available to the light-sheet community. The tremendous amount of data routinely generated by light-sheet microscopy further requires novel strategies for data handling and storage. To complete the full imaging pipeline of our high-throughput microscope, we further elaborate on big data management from streaming of raw images up to stitching of 3-D datasets. The mesoscale neuroanatomy imaged at micron-scale resolution in those datasets allows characterization and quantification of neuronal projections in unsectioned mouse brains.

The neuroscience of musical improvisation.

PubMed

Beaty, Roger E

2015-04-01

Researchers have recently begun to examine the neural basis of musical improvisation, one of the most complex forms of creative behavior. The emerging field of improvisation neuroscience has implications not only for the study of artistic expertise, but also for understanding the neural underpinnings of domain-general processes such as motor control and language production. This review synthesizes functional magnetic resonance imagining (fMRI) studies of musical improvisation, including vocal and instrumental improvisation, with samples of jazz pianists, classical musicians, freestyle rap artists, and non-musicians. A network of prefrontal brain regions commonly linked to improvisatory behavior is highlighted, including the pre-supplementary motor area, medial prefrontal cortex, inferior frontal gyrus, dorsolateral prefrontal cortex, and dorsal premotor cortex. Activation of premotor and lateral prefrontal regions suggests that a seemingly unconstrained behavior may actually benefit from motor planning and cognitive control. Yet activation of cortical midline regions points to a role of spontaneous cognition characteristic of the default network. Together, such results may reflect cooperation between large-scale brain networks associated with cognitive control and spontaneous thought. The improvisation literature is integrated with Pressing's theoretical model, and discussed within the broader context of research on the brain basis of creative cognition. Copyright © 2015 Elsevier Ltd. All rights reserved.

Retinotopic patterns of functional connectivity between V1 and large-scale brain networks during resting fixation

PubMed Central

Griffis, Joseph C.; Elkhetali, Abdurahman S.; Burge, Wesley K.; Chen, Richard H.; Bowman, Anthony D.; Szaflarski, Jerzy P.; Visscher, Kristina M.

2016-01-01

Psychophysical and neurobiological evidence suggests that central and peripheral vision are specialized for different functions. This specialization of function might be expected to lead to differences in the large-scale functional interactions of early cortical areas that represent central and peripheral visual space. Here, we characterize differences in whole-brain functional connectivity among sectors in primary visual cortex (V1) corresponding to central, near-peripheral, and far-peripheral vision during resting fixation. Importantly, our analyses reveal that eccentricity sectors in V1 have different functional connectivity with non-visual areas associated with large-scale brain networks. Regions associated with the fronto-parietal control network are most strongly connected with central sectors of V1, regions associated with the cingulo-opercular control network are most strongly connected with near-peripheral sectors of V1, and regions associated with the default mode and auditory networks are most strongly connected with far-peripheral sectors of V1. Additional analyses suggest that similar patterns are present during eyes-closed rest. These results suggest that different types of visual information may be prioritized by large-scale brain networks with distinct functional profiles, and provide insights into how the small-scale functional specialization within early visual regions such as V1 relates to the large-scale organization of functionally distinct whole-brain networks. PMID:27554527

3-D in vivo brain tumor geometry study by scaling analysis

NASA Astrophysics Data System (ADS)

Torres Hoyos, F.; Martín-Landrove, M.

2012-02-01

A new method, based on scaling analysis, is used to calculate fractal dimension and local roughness exponents to characterize in vivo 3-D tumor growth in the brain. Image acquisition was made according to the standard protocol used for brain radiotherapy and radiosurgery, i.e., axial, coronal and sagittal magnetic resonance T1-weighted images, and comprising the brain volume for image registration. Image segmentation was performed by the application of the k-means procedure upon contrasted images. We analyzed glioblastomas, astrocytomas, metastases and benign brain tumors. The results show significant variations of the parameters depending on the tumor stage and histological origin.

Relationship between alcohol-related expectancies and anterior brain functioning in young men at risk for developing alcoholism.

PubMed

Deckel, A W; Hesselbrock, V; Bauer, L

1995-04-01

This experiment examined the relationship between anterior brain functioning and alcohol-related expectancies. Ninety-one young men at risk for developing alcoholism were assessed on the Alcohol Expectancy Questionnaire (AEQ) and administered neuropsychological and EEG tests. Three of the scales on the AEQ, including the "Enhanced Sexual Functioning" scale, the "Increased Social Assertiveness" scale, and items from the "Global/Positive Change scale," were used, because each of these scales has been found to discriminate alcohol-based expectancies adequately by at least two separate sets of investigators. Regression analysis found that anterior neuropsychological tests (including the Wisconsin Card Sorting test, the Porteus Maze test, the Controlled Oral Word Fluency test, and the Luria-Nebraska motor functioning tests) were predictive of the AEQ scale scores on regression analysis. One of the AEQ scales, "Enhanced Sexual Functioning," was also predicted by WAIS-R-Verbal scales, whereas the "Global/Positive" AEQ scale was predicted by the WAIS-R Performance scales. Regression analysis using EEG power as predictors found that left versus right hemisphere "difference" scores obtained from frontal EEG leads were predictive of the three AEQ scales. Conversely, parietal EEG power did not significantly predict any of the expectancy scales. It is concluded that anterior brain any of the expectancy scales. It is concluded that anterior brain functioning is associated with alcohol-related expectancies. These findings suggest that alcohol-related expectancy may be, in part, biologically determined by frontal/prefrontal systems, and that dysfunctioning in these systems may serve as a risk factor for the development of alcohol-related behaviors.

Integrated Electrode Arrays for Neuro-Prosthetic Implants

NASA Technical Reports Server (NTRS)

Brandon, Erik; Mojarradi, Mohammede

2003-01-01

Arrays of electrodes integrated with chip-scale packages and silicon-based integrated circuits have been proposed for use as medical electronic implants, including neuro-prosthetic devices that might be implanted in brains of patients who suffer from strokes, spinal-cord injuries, or amyotrophic lateral sclerosis. The electrodes of such a device would pick up signals from neurons in the cerebral cortex, and the integrated circuit would perform acquisition and preprocessing of signal data. The output of the integrated circuit could be used to generate, for example, commands for a robotic arm. Electrode arrays capable of acquiring electrical signals from neurons already exist, but heretofore, there has been no convenient means to integrate these arrays with integrated-circuit chips. Such integration is needed in order to eliminate the need for the extensive cabling now used to pass neural signals to data-acquisition and -processing equipment outside the body. The proposed integration would enable progress toward neuro-prostheses that would be less restrictive of patients mobility. An array of electrodes would comprise a set of thin wires of suitable length and composition protruding from and supported by a fine-pitch micro-ball grid array or chip-scale package (see figure). The associated integrated circuit would be mounted on the package face opposite the probe face, using the solder bumps (the balls of the ball grid array) to make the electrical connections between the probes and the input terminals of the integrated circuit. The key innovation is the insertion of probe wires of the appropriate length and material into the solder bumps through a reflow process, thereby fixing the probes in place and electrically connecting them with the integrated circuit. The probes could be tailored to any distribution of lengths and made of any suitable metal that could be drawn into fine wires. Furthermore, the wires could be coated with an insulating layer using anodization or other processes, to achieve the correct electrical impedance. The probe wires and the packaging materials must be biocompatible using such materials as lead-free solders. For protection, the chip and package can be coated with parylene.

Large-scale recording of thalamocortical circuits: in vivo electrophysiology with the two-dimensional electronic depth control silicon probe.

PubMed

Fiáth, Richárd; Beregszászi, Patrícia; Horváth, Domonkos; Wittner, Lucia; Aarts, Arno A A; Ruther, Patrick; Neves, Hercules P; Bokor, Hajnalka; Acsády, László; Ulbert, István

2016-11-01

Recording simultaneous activity of a large number of neurons in distributed neuronal networks is crucial to understand higher order brain functions. We demonstrate the in vivo performance of a recently developed electrophysiological recording system comprising a two-dimensional, multi-shank, high-density silicon probe with integrated complementary metal-oxide semiconductor electronics. The system implements the concept of electronic depth control (EDC), which enables the electronic selection of a limited number of recording sites on each of the probe shafts. This innovative feature of the system permits simultaneous recording of local field potentials (LFP) and single- and multiple-unit activity (SUA and MUA, respectively) from multiple brain sites with high quality and without the actual physical movement of the probe. To evaluate the in vivo recording capabilities of the EDC probe, we recorded LFP, MUA, and SUA in acute experiments from cortical and thalamic brain areas of anesthetized rats and mice. The advantages of large-scale recording with the EDC probe are illustrated by investigating the spatiotemporal dynamics of pharmacologically induced thalamocortical slow-wave activity in rats and by the two-dimensional tonotopic mapping of the auditory thalamus. In mice, spatial distribution of thalamic responses to optogenetic stimulation of the neocortex was examined. Utilizing the benefits of the EDC system may result in a higher yield of useful data from a single experiment compared with traditional passive multielectrode arrays, and thus in the reduction of animals needed for a research study. Copyright © 2016 the American Physiological Society.

Variety in emotional life: within-category typicality of emotional experiences is associated with neural activity in large-scale brain networks

PubMed Central

Barrett, Lisa Feldman; Barsalou, Lawrence W.

2015-01-01

The tremendous variability within categories of human emotional experience receives little empirical attention. We hypothesized that atypical instances of emotion categories (e.g. pleasant fear of thrill-seeking) would be processed less efficiently than typical instances of emotion categories (e.g. unpleasant fear of violent threat) in large-scale brain networks. During a novel fMRI paradigm, participants immersed themselves in scenarios designed to induce atypical and typical experiences of fear, sadness or happiness (scenario immersion), and then focused on and rated the pleasant or unpleasant feeling that emerged (valence focus) in most trials. As predicted, reliably greater activity in the ‘default mode’ network (including medial prefrontal cortex and posterior cingulate) was observed for atypical (vs typical) emotional experiences during scenario immersion, suggesting atypical instances require greater conceptual processing to situate the socio-emotional experience. During valence focus, reliably greater activity was observed for atypical (vs typical) emotional experiences in the ‘salience’ network (including anterior insula and anterior cingulate), suggesting atypical instances place greater demands on integrating shifting body signals with the sensory and social context. Consistent with emerging psychological construction approaches to emotion, these findings demonstrate that is it important to study the variability within common categories of emotional experience. PMID:24563528

Predicting treatment response to cognitive behavioral therapy in panic disorder with agoraphobia by integrating local neural information.

PubMed

Hahn, Tim; Kircher, Tilo; Straube, Benjamin; Wittchen, Hans-Ulrich; Konrad, Carsten; Ströhle, Andreas; Wittmann, André; Pfleiderer, Bettina; Reif, Andreas; Arolt, Volker; Lueken, Ulrike

2015-01-01

Although neuroimaging research has made substantial progress in identifying the large-scale neural substrate of anxiety disorders, its value for clinical application lags behind expectations. Machine-learning approaches have predictive potential for individual-patient prognostic purposes and might thus aid translational efforts in psychiatric research. To predict treatment response to cognitive behavioral therapy (CBT) on an individual-patient level based on functional magnetic resonance imaging data in patients with panic disorder with agoraphobia (PD/AG). We included 49 patients free of medication for at least 4 weeks and with a primary diagnosis of PD/AG in a longitudinal study performed at 8 clinical research institutes and outpatient centers across Germany. The functional magnetic resonance imaging study was conducted between July 2007 and March 2010. Twelve CBT sessions conducted 2 times a week focusing on behavioral exposure. Treatment response was defined as exceeding a 50% reduction in Hamilton Anxiety Rating Scale scores. Blood oxygenation level-dependent signal was measured during a differential fear-conditioning task. Regional and whole-brain gaussian process classifiers using a nested leave-one-out cross-validation were used to predict the treatment response from data acquired before CBT. Although no single brain region was predictive of treatment response, integrating regional classifiers based on data from the acquisition and the extinction phases of the fear-conditioning task for the whole brain yielded good predictive performance (accuracy, 82%; sensitivity, 92%; specificity, 72%; P < .001). Data from the acquisition phase enabled 73% correct individual-patient classifications (sensitivity, 80%; specificity, 67%; P < .001), whereas data from the extinction phase led to an accuracy of 74% (sensitivity, 64%; specificity, 83%; P < .001). Conservative reanalyses under consideration of potential confounders yielded nominally lower but comparable accuracy rates (acquisition phase, 70%; extinction phase, 71%; combined, 79%). Predicting treatment response to CBT based on functional neuroimaging data in PD/AG is possible with high accuracy on an individual-patient level. This novel machine-learning approach brings personalized medicine within reach, directly supporting clinical decisions for the selection of treatment options, thus helping to improve response rates.

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

An Animal-to-Human Scaling Law for Blast-Induced Traumatic Brain Injury Risk Assessment

DTIC Science & Technology

2014-10-28

TERMS b. ABSTRACT 2. REPORT TYPE 17. LIMITATION OF ABSTRACT 15. NUMBER OF PAGES 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 5c...brain, as well as their acoustic impedance. Peak stresses transmitted to the brain tissue by the blast are then shown to be a power function of the...be a power function of the scaling parameter for a range of blast conditions relevant to TBI. In particu- lar, it is found that human brain

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.

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

Reduced integration and improved segregation of functional brain networks in Alzheimer’s disease

NASA Astrophysics Data System (ADS)

Kabbara, A.; Eid, H.; El Falou, W.; Khalil, M.; Wendling, F.; Hassan, M.

2018-04-01

Objective. Emerging evidence shows that cognitive deficits in Alzheimer’s disease (AD) are associated with disruptions in brain functional connectivity. Thus, the identification of alterations in AD functional networks has become a topic of increasing interest. However, to what extent AD induces disruption of the balance of local and global information processing in the human brain remains elusive. The main objective of this study is to explore the dynamic topological changes of AD networks in terms of brain network segregation and integration. Approach. We used electroencephalography (EEG) data recorded from 20 participants (10 AD patients and 10 healthy controls) during resting state. Functional brain networks were reconstructed using EEG source connectivity computed in different frequency bands. Graph theoretical analyses were performed assess differences between both groups. Main results. Results revealed that AD networks, compared to networks of age-matched healthy controls, are characterized by lower global information processing (integration) and higher local information processing (segregation). Results showed also significant correlation between the alterations in the AD patients’ functional brain networks and their cognitive scores. Significance. These findings may contribute to the development of EEG network-based test that could strengthen results obtained from currently-used neurophysiological tests in neurodegenerative diseases.

Reduced integration and improved segregation of functional brain networks in Alzheimer's disease.

PubMed

Kabbara, A; Eid, H; El Falou, W; Khalil, M; Wendling, F; Hassan, M

2018-04-01

Emerging evidence shows that cognitive deficits in Alzheimer's disease (AD) are associated with disruptions in brain functional connectivity. Thus, the identification of alterations in AD functional networks has become a topic of increasing interest. However, to what extent AD induces disruption of the balance of local and global information processing in the human brain remains elusive. The main objective of this study is to explore the dynamic topological changes of AD networks in terms of brain network segregation and integration. We used electroencephalography (EEG) data recorded from 20 participants (10 AD patients and 10 healthy controls) during resting state. Functional brain networks were reconstructed using EEG source connectivity computed in different frequency bands. Graph theoretical analyses were performed assess differences between both groups. Results revealed that AD networks, compared to networks of age-matched healthy controls, are characterized by lower global information processing (integration) and higher local information processing (segregation). Results showed also significant correlation between the alterations in the AD patients' functional brain networks and their cognitive scores. These findings may contribute to the development of EEG network-based test that could strengthen results obtained from currently-used neurophysiological tests in neurodegenerative diseases.

Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size.

PubMed

Schwalger, Tilo; Deger, Moritz; Gerstner, Wulfram

2017-04-01

Neural population equations such as neural mass or field models are widely used to study brain activity on a large scale. However, the relation of these models to the properties of single neurons is unclear. Here we derive an equation for several interacting populations at the mesoscopic scale starting from a microscopic model of randomly connected generalized integrate-and-fire neuron models. Each population consists of 50-2000 neurons of the same type but different populations account for different neuron types. The stochastic population equations that we find reveal how spike-history effects in single-neuron dynamics such as refractoriness and adaptation interact with finite-size fluctuations on the population level. Efficient integration of the stochastic mesoscopic equations reproduces the statistical behavior of the population activities obtained from microscopic simulations of a full spiking neural network model. The theory describes nonlinear emergent dynamics such as finite-size-induced stochastic transitions in multistable networks and synchronization in balanced networks of excitatory and inhibitory neurons. The mesoscopic equations are employed to rapidly integrate a model of a cortical microcircuit consisting of eight neuron types, which allows us to predict spontaneous population activities as well as evoked responses to thalamic input. Our theory establishes a general framework for modeling finite-size neural population dynamics based on single cell and synapse parameters and offers an efficient approach to analyzing cortical circuits and computations.

Allen Brain Atlas: an integrated spatio-temporal portal for exploring the central nervous system

PubMed Central

Sunkin, Susan M.; Ng, Lydia; Lau, Chris; Dolbeare, Tim; Gilbert, Terri L.; Thompson, Carol L.; Hawrylycz, Michael; Dang, Chinh

2013-01-01

The Allen Brain Atlas (http://www.brain-map.org) provides a unique online public resource integrating extensive gene expression data, connectivity data and neuroanatomical information with powerful search and viewing tools for the adult and developing brain in mouse, human and non-human primate. Here, we review the resources available at the Allen Brain Atlas, describing each product and data type [such as in situ hybridization (ISH) and supporting histology, microarray, RNA sequencing, reference atlases, projection mapping and magnetic resonance imaging]. In addition, standardized and unique features in the web applications are described that enable users to search and mine the various data sets. Features include both simple and sophisticated methods for gene searches, colorimetric and fluorescent ISH image viewers, graphical displays of ISH, microarray and RNA sequencing data, Brain Explorer software for 3D navigation of anatomy and gene expression, and an interactive reference atlas viewer. In addition, cross data set searches enable users to query multiple Allen Brain Atlas data sets simultaneously. All of the Allen Brain Atlas resources can be accessed through the Allen Brain Atlas data portal. PMID:23193282

Spectral fingerprints of large-scale neuronal interactions.

PubMed

Siegel, Markus; Donner, Tobias H; Engel, Andreas K

2012-01-11

Cognition results from interactions among functionally specialized but widely distributed brain regions; however, neuroscience has so far largely focused on characterizing the function of individual brain regions and neurons therein. Here we discuss recent studies that have instead investigated the interactions between brain regions during cognitive processes by assessing correlations between neuronal oscillations in different regions of the primate cerebral cortex. These studies have opened a new window onto the large-scale circuit mechanisms underlying sensorimotor decision-making and top-down attention. We propose that frequency-specific neuronal correlations in large-scale cortical networks may be 'fingerprints' of canonical neuronal computations underlying cognitive processes.

Retinopathy of prematurity and brain damage in the very preterm newborn.

PubMed

Allred, Elizabeth N; Capone, Antonio; Fraioli, Anthony; Dammann, Olaf; Droste, Patrick; Duker, Jay; Gise, Robert; Kuban, Karl; Leviton, Alan; O'Shea, T Michael; Paneth, Nigel; Petersen, Robert; Trese, Michael; Stoessel, Kathleen; Vanderveen, Deborah; Wallace, David K; Weaver, Grey

2014-06-01

To explain why very preterm newborns who develop retinopathy of prematurity (ROP) appear to be at increased risk of abnormalities of both brain structure and function. A total of 1,085 children born at <28 weeks' gestation had clinically indicated retinal examinations and had a developmental assessment at 2 years corrected age. Relationships between ROP categories and brain abnormalities were explored using logistic regression models with adjustment for potential confounders. The 173 children who had severe ROP, defined as prethreshold ROP (n = 146) or worse (n = 27) were somewhat more likely than their peers without ROP to have brain ultrasound lesions or cerebral palsy. They were approximately twice as likely to have very low Bayley Scales scores. After adjusting for risk factors common to both ROP and brain disorders, infants who developed severe ROP were at increased risk of low Bayley Scales only. Among children with prethreshold ROP, exposure to anesthesia was not associated with low Bayley Scales. Some but not all of the association of ROP with brain disorders can be explained by common risk factors. Most of the increased risks of very low Bayley Scales associated with ROP are probably not a consequence of exposure to anesthetic agents. Copyright © 2014 American Association for Pediatric Ophthalmology and Strabismus. Published by Mosby, Inc. All rights reserved.

A Multiscale Parallel Computing Architecture for Automated Segmentation of the Brain Connectome

PubMed Central

Knobe, Kathleen; Newton, Ryan R.; Schlimbach, Frank; Blower, Melanie; Reid, R. Clay

2015-01-01

Several groups in neurobiology have embarked into deciphering the brain circuitry using large-scale imaging of a mouse brain and manual tracing of the connections between neurons. Creating a graph of the brain circuitry, also called a connectome, could have a huge impact on the understanding of neurodegenerative diseases such as Alzheimer’s disease. Although considerably smaller than a human brain, a mouse brain already exhibits one billion connections and manually tracing the connectome of a mouse brain can only be achieved partially. This paper proposes to scale up the tracing by using automated image segmentation and a parallel computing approach designed for domain experts. We explain the design decisions behind our parallel approach and we present our results for the segmentation of the vasculature and the cell nuclei, which have been obtained without any manual intervention. PMID:21926011

Prenatal Exposure of Guinea Pigs to the Organophosphorus Pesticide Chlorpyrifos Disrupts the Structural and Functional Integrity of the Brain

PubMed Central

Mullins, Roger J.; Xu, Su; Pereira, Edna F.R.; Pescrille, Joseph D.; Todd, Spencer W.; Mamczarz, Jacek; Albuquerque, Edson X.; Gullapalli, Rao P.

2015-01-01

This study was designed to test the hypothesis that prenatal exposure of guinea pigs to the organophosphorus (OP) pesticide chlorpyrifos (CPF) disrupts the structural and functional integrity of the brain. Pregnant guinea pigs were injected with chlorpyrifos (20 mg/kg, s.c.) or vehicle (peanut oil) once per day for ten consecutive days, starting approximately on the 50th day of gestation. Cognitive behavior of female offspring was examined starting at 40–45 post-natal days (PND) using the Morris Water Maze (MWM), and brain structural integrity was analyzed at PND 70 using magnetic resonance imaging (MRI) methods, including T2-weighted anatomical scans and Diffusion Kurtosis Imaging (DKI). The offspring of exposed mothers had significantly decreased body weight and brain volume, particularly in the frontal regions of the brain including the striatum. Furthermore, the offspring demonstrated significant spatial learning deficits in MWM recall compared to the vehicle group. Diffusion measures revealed reduced white matter integrity within the striatum and amygdala that correlated with spatial learning performance. These findings reveal the lasting effect of pre-natal exposure to CPF as well as the danger of mother to child transmission of CPF in the environment. PMID:25704171

Integrative analyses of RNA editing, alternative splicing, and expression of young genes in human brain transcriptome by deep RNA sequencing.

PubMed

Wu, Dong-Dong; Ye, Ling-Qun; Li, Yan; Sun, Yan-Bo; Shao, Yi; Chen, Chunyan; Zhu, Zhu; Zhong, Li; Wang, Lu; Irwin, David M; Zhang, Yong E; Zhang, Ya-Ping

2015-08-01

Next-generation RNA sequencing has been successfully used for identification of transcript assembly, evaluation of gene expression levels, and detection of post-transcriptional modifications. Despite these large-scale studies, additional comprehensive RNA-seq data from different subregions of the human brain are required to fully evaluate the evolutionary patterns experienced by the human brain transcriptome. Here, we provide a total of 6.5 billion RNA-seq reads from different subregions of the human brain. A significant correlation was observed between the levels of alternative splicing and RNA editing, which might be explained by a competition between the molecular machineries responsible for the splicing and editing of RNA. Young human protein-coding genes demonstrate biased expression to the neocortical and non-neocortical regions during evolution on the lineage leading to humans. We also found that a significantly greater number of young human protein-coding genes are expressed in the putamen, a tissue that was also observed to have the highest level of RNA-editing activity. The putamen, which previously received little attention, plays an important role in cognitive ability, and our data suggest a potential contribution of the putamen to human evolution. © The Author (2015). Published by Oxford University Press on behalf of Journal of Molecular Cell Biology, IBCB, SIBS, CAS. All rights reserved.

SZGR 2.0: a one-stop shop of schizophrenia candidate genes.

PubMed

Jia, Peilin; Han, Guangchun; Zhao, Junfei; Lu, Pinyi; Zhao, Zhongming

2017-01-04

SZGR 2.0 is a comprehensive resource of candidate variants and genes for schizophrenia, covering genetic, epigenetic, transcriptomic, translational and many other types of evidence. By systematic review and curation of multiple lines of evidence, we included almost all variants and genes that have ever been reported to be associated with schizophrenia. In particular, we collected ∼4200 common variants reported in genome-wide association studies, ∼1000 de novo mutations discovered by large-scale sequencing of family samples, 215 genes spanning rare and replication copy number variations, 99 genes overlapping with linkage regions, 240 differentially expressed genes, 4651 differentially methylated genes and 49 genes as antipsychotic drug targets. To facilitate interpretation, we included various functional annotation data, especially brain eQTL, methylation QTL, brain expression featured in deep categorization of brain areas and developmental stages and brain-specific promoter and enhancer annotations. Furthermore, we conducted cross-study, cross-data type and integrative analyses of the multidimensional data deposited in SZGR 2.0, and made the data and results available through a user-friendly interface. In summary, SZGR 2.0 provides a one-stop shop of schizophrenia variants and genes and their function and regulation, providing an important resource in the schizophrenia and other mental disease community. SZGR 2.0 is available at https://bioinfo.uth.edu/SZGR/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Connectivity in the human brain dissociates entropy and complexity of auditory inputs.

PubMed

Nastase, Samuel A; Iacovella, Vittorio; Davis, Ben; Hasson, Uri

2015-03-01

Complex systems are described according to two central dimensions: (a) the randomness of their output, quantified via entropy; and (b) their complexity, which reflects the organization of a system's generators. Whereas some approaches hold that complexity can be reduced to uncertainty or entropy, an axiom of complexity science is that signals with very high or very low entropy are generated by relatively non-complex systems, while complex systems typically generate outputs with entropy peaking between these two extremes. In understanding their environment, individuals would benefit from coding for both input entropy and complexity; entropy indexes uncertainty and can inform probabilistic coding strategies, whereas complexity reflects a concise and abstract representation of the underlying environmental configuration, which can serve independent purposes, e.g., as a template for generalization and rapid comparisons between environments. Using functional neuroimaging, we demonstrate that, in response to passively processed auditory inputs, functional integration patterns in the human brain track both the entropy and complexity of the auditory signal. Connectivity between several brain regions scaled monotonically with input entropy, suggesting sensitivity to uncertainty, whereas connectivity between other regions tracked entropy in a convex manner consistent with sensitivity to input complexity. These findings suggest that the human brain simultaneously tracks the uncertainty of sensory data and effectively models their environmental generators. Copyright © 2014. Published by Elsevier Inc.

What We Know About the Brain Structure-Function Relationship.

PubMed

Batista-García-Ramó, Karla; Fernández-Verdecia, Caridad Ivette

2018-04-18

How the human brain works is still a question, as is its implication with brain architecture: the non-trivial structure–function relationship. The main hypothesis is that the anatomic architecture conditions, but does not determine, the neural network dynamic. The functional connectivity cannot be explained only considering the anatomical substrate. This involves complex and controversial aspects of the neuroscience field and that the methods and methodologies to obtain structural and functional connectivity are not always rigorously applied. The goal of the present article is to discuss about the progress made to elucidate the structure–function relationship of the Central Nervous System, particularly at the brain level, based on results from human and animal studies. The current novel systems and neuroimaging techniques with high resolutive physio-structural capacity have brought about the development of an integral framework of different structural and morphometric tools such as image processing, computational modeling and graph theory. Different laboratories have contributed with in vivo, in vitro and computational/mathematical models to study the intrinsic neural activity patterns based on anatomical connections. We conclude that multi-modal techniques of neuroimaging are required such as an improvement on methodologies for obtaining structural and functional connectivity. Even though simulations of the intrinsic neural activity based on anatomical connectivity can reproduce much of the observed patterns of empirical functional connectivity, future models should be multifactorial to elucidate multi-scale relationships and to infer disorder mechanisms.

Early brain development toward shaping of human mind: an integrative psychoneurodevelopmental model in prenatal and perinatal medicine.

PubMed

Hruby, Radovan; Maas, Lili M; Fedor-Freybergh, P G

2013-01-01

The article introduces an integrative psychoneurodevelopmental model of complex human brain and mind development based on the latest findings in prenatal and perinatal medicine in terms of integrative neuroscience. The human brain development is extraordinarily complex set of events and could be influenced by a lot of factors. It is supported by new insights into the early neuro-ontogenic processes with the help of structural 3D magnetic resonance imaging or diffusion tensor imaging of fetal human brain. Various factors and targets for neural development including birth weight variability, fetal and early-life programming, fetal neurobehavioral states and fetal behavioral responses to various stimuli and others are discussed. Molecular biology reveals increasing sets of genes families as well as transcription and neurotropic factors together with critical epigenetic mechanisms to be deeply employed in the crucial neurodevelopmental events. Another field of critical importance is psychoimmuno-neuroendocrinology. Various effects of glucocorticoids as well as other hormones, prenatal stress and fetal HPA axis modulation are thought to be of special importance for brain development. The early postnatal period is characterized by the next intense shaping of complex competences, induced mainly by the very unique mother - newborn´s interactions and bonding. All these mechanisms serve to shape individual human mind with complex abilities and neurobehavioral strategies. Continuous research elucidating these special competences of human fetus and newborn/child supports integrative neuroscientific approach to involve various scientific disciplines for the next progress in human brain and mind research, and opens new scientific challenges and philosophic attitudes. New findings and approaches in this field could establish new methods in science, in primary prevention and treatment strategies, and markedly contribute to the development of modern integrative and personalized medicine.

Cyberinfrastructure for the digital brain: spatial standards for integrating rodent brain atlases

PubMed Central

Zaslavsky, Ilya; Baldock, Richard A.; Boline, Jyl

2014-01-01

Biomedical research entails capture and analysis of massive data volumes and new discoveries arise from data-integration and mining. This is only possible if data can be mapped onto a common framework such as the genome for genomic data. In neuroscience, the framework is intrinsically spatial and based on a number of paper atlases. This cannot meet today's data-intensive analysis and integration challenges. A scalable and extensible software infrastructure that is standards based but open for novel data and resources, is required for integrating information such as signal distributions, gene-expression, neuronal connectivity, electrophysiology, anatomy, and developmental processes. Therefore, the International Neuroinformatics Coordinating Facility (INCF) initiated the development of a spatial framework for neuroscience data integration with an associated Digital Atlasing Infrastructure (DAI). A prototype implementation of this infrastructure for the rodent brain is reported here. The infrastructure is based on a collection of reference spaces to which data is mapped at the required resolution, such as the Waxholm Space (WHS), a 3D reconstruction of the brain generated using high-resolution, multi-channel microMRI. The core standards of the digital atlasing service-oriented infrastructure include Waxholm Markup Language (WaxML): XML schema expressing a uniform information model for key elements such as coordinate systems, transformations, points of interest (POI)s, labels, and annotations; and Atlas Web Services: interfaces for querying and updating atlas data. The services return WaxML-encoded documents with information about capabilities, spatial reference systems (SRSs) and structures, and execute coordinate transformations and POI-based requests. Key elements of INCF-DAI cyberinfrastructure have been prototyped for both mouse and rat brain atlas sources, including the Allen Mouse Brain Atlas, UCSD Cell-Centered Database, and Edinburgh Mouse Atlas Project. PMID:25309417

Cyberinfrastructure for the digital brain: spatial standards for integrating rodent brain atlases.

PubMed

Zaslavsky, Ilya; Baldock, Richard A; Boline, Jyl

2014-01-01

Biomedical research entails capture and analysis of massive data volumes and new discoveries arise from data-integration and mining. This is only possible if data can be mapped onto a common framework such as the genome for genomic data. In neuroscience, the framework is intrinsically spatial and based on a number of paper atlases. This cannot meet today's data-intensive analysis and integration challenges. A scalable and extensible software infrastructure that is standards based but open for novel data and resources, is required for integrating information such as signal distributions, gene-expression, neuronal connectivity, electrophysiology, anatomy, and developmental processes. Therefore, the International Neuroinformatics Coordinating Facility (INCF) initiated the development of a spatial framework for neuroscience data integration with an associated Digital Atlasing Infrastructure (DAI). A prototype implementation of this infrastructure for the rodent brain is reported here. The infrastructure is based on a collection of reference spaces to which data is mapped at the required resolution, such as the Waxholm Space (WHS), a 3D reconstruction of the brain generated using high-resolution, multi-channel microMRI. The core standards of the digital atlasing service-oriented infrastructure include Waxholm Markup Language (WaxML): XML schema expressing a uniform information model for key elements such as coordinate systems, transformations, points of interest (POI)s, labels, and annotations; and Atlas Web Services: interfaces for querying and updating atlas data. The services return WaxML-encoded documents with information about capabilities, spatial reference systems (SRSs) and structures, and execute coordinate transformations and POI-based requests. Key elements of INCF-DAI cyberinfrastructure have been prototyped for both mouse and rat brain atlas sources, including the Allen Mouse Brain Atlas, UCSD Cell-Centered Database, and Edinburgh Mouse Atlas Project.

Integration of altitude and airspeed information into a primary flight display via moving-tape formats: Evaluation during random tracking task

NASA Technical Reports Server (NTRS)

Abbott, Terence S.; Nataupsky, Mark; Steinmetz, George G.

1987-01-01

A ground-based aircraft simulation study was conducted to determine the effects on pilot preference and performance of integrating airspeed and altitude information into an advanced electronic primary flight display via moving-tape (linear moving scale) formats. Several key issues relating to the implementation of moving-tape formats were examined in this study: tape centering, tape orientation, and trend information. The factor of centering refers to whether the tape was centered about the actual airspeed or altitude or about some other defined reference value. Tape orientation refers to whether the represented values are arranged in descending or ascending order. Two pilots participated in this study, with each performing 32 runs along seemingly random, previously unknown flight profiles. The data taken, analyzed, and presented consisted of path performance parameters, pilot-control inputs, and electrical brain response measurements.

Neurophysiological Basis of Multi-Scale Entropy of Brain Complexity and Its Relationship With Functional Connectivity.

PubMed

Wang, Danny J J; Jann, Kay; Fan, Chang; Qiao, Yang; Zang, Yu-Feng; Lu, Hanbing; Yang, Yihong

2018-01-01

Recently, non-linear statistical measures such as multi-scale entropy (MSE) have been introduced as indices of the complexity of electrophysiology and fMRI time-series across multiple time scales. In this work, we investigated the neurophysiological underpinnings of complexity (MSE) of electrophysiology and fMRI signals and their relations to functional connectivity (FC). MSE and FC analyses were performed on simulated data using neural mass model based brain network model with the Brain Dynamics Toolbox, on animal models with concurrent recording of fMRI and electrophysiology in conjunction with pharmacological manipulations, and on resting-state fMRI data from the Human Connectome Project. Our results show that the complexity of regional electrophysiology and fMRI signals is positively correlated with network FC. The associations between MSE and FC are dependent on the temporal scales or frequencies, with higher associations between MSE and FC at lower temporal frequencies. Our results from theoretical modeling, animal experiment and human fMRI indicate that (1) Regional neural complexity and network FC may be two related aspects of brain's information processing: the more complex regional neural activity, the higher FC this region has with other brain regions; (2) MSE at high and low frequencies may represent local and distributed information processing across brain regions. Based on literature and our data, we propose that the complexity of regional neural signals may serve as an index of the brain's capacity of information processing-increased complexity may indicate greater transition or exploration between different states of brain networks, thereby a greater propensity for information processing.

C5a alters blood-brain barrier integrity in experimental lupus.

PubMed

Jacob, Alexander; Hack, Bradley; Chiang, Eddie; Garcia, Joe G N; Quigg, Richard J; Alexander, Jessy J

2010-06-01

The blood-brain barrier (BBB) is a crucial anatomic location in the brain. Its dysfunction complicates many neurodegenerative diseases, from acute conditions, such as sepsis, to chronic diseases, such as systemic lupus erythematosus (SLE). Several studies suggest an altered BBB in lupus, but the underlying mechanism remains unknown. In the current study, we observed a definite loss of BBB integrity in MRL/MpJ-Tnfrsf6(lpr) (MRL/lpr) lupus mice by IgG infiltration into brain parenchyma. In line with this result, we examined the role of complement activation, a key event in this setting, in maintenance of BBB integrity. Complement activation generates C5a, a molecule with multiple functions. Because the expression of the C5a receptor (C5aR) is significantly increased in brain endothelial cells treated with lupus serum, the study focused on the role of C5a signaling through its G-protein-coupled receptor C5aR in brain endothelial cells, in a lupus setting. Reactive oxygen species production increased significantly in endothelial cells, in both primary cells and the bEnd3 cell line treated with lupus serum from MRL/lpr mice, compared with those treated with control serum from MRL(+/+) mice. In addition, increased permeability monitored by changes in transendothelial electrical resistance, cytoskeletal remodeling caused by actin fiber rearrangement, and increased iNOS mRNA expression were observed in bEnd3 cells. These disruptive effects were alleviated by pretreating cells with a C5a receptor antagonist (C5aRant) or a C5a antibody. Furthermore, the structural integrity of the vasculature in MRL/lpr brain was maintained by C5aR inhibition. These results demonstrate the regulation of BBB integrity by the complement system in a neuroinflammatory setting. For the first time, a novel role of C5a in the maintenance of BBB integrity is identified and the potential of C5a/C5aR blockade highlighted as a promising therapeutic strategy in SLE and other neurodegenerative diseases.

Development of large-scale functional brain networks in children.

PubMed

Supekar, Kaustubh; Musen, Mark; Menon, Vinod

2009-07-01

The ontogeny of large-scale functional organization of the human brain is not well understood. Here we use network analysis of intrinsic functional connectivity to characterize the organization of brain networks in 23 children (ages 7-9 y) and 22 young-adults (ages 19-22 y). Comparison of network properties, including path-length, clustering-coefficient, hierarchy, and regional connectivity, revealed that although children and young-adults' brains have similar "small-world" organization at the global level, they differ significantly in hierarchical organization and interregional connectivity. We found that subcortical areas were more strongly connected with primary sensory, association, and paralimbic areas in children, whereas young-adults showed stronger cortico-cortical connectivity between paralimbic, limbic, and association areas. Further, combined analysis of functional connectivity with wiring distance measures derived from white-matter fiber tracking revealed that the development of large-scale brain networks is characterized by weakening of short-range functional connectivity and strengthening of long-range functional connectivity. Importantly, our findings show that the dynamic process of over-connectivity followed by pruning, which rewires connectivity at the neuronal level, also operates at the systems level, helping to reconfigure and rebalance subcortical and paralimbic connectivity in the developing brain. Our study demonstrates the usefulness of network analysis of brain connectivity to elucidate key principles underlying functional brain maturation, paving the way for novel studies of disrupted brain connectivity in neurodevelopmental disorders such as autism.

Development of Large-Scale Functional Brain Networks in Children

PubMed Central

Supekar, Kaustubh; Musen, Mark; Menon, Vinod

2009-01-01

The ontogeny of large-scale functional organization of the human brain is not well understood. Here we use network analysis of intrinsic functional connectivity to characterize the organization of brain networks in 23 children (ages 7–9 y) and 22 young-adults (ages 19–22 y). Comparison of network properties, including path-length, clustering-coefficient, hierarchy, and regional connectivity, revealed that although children and young-adults' brains have similar “small-world” organization at the global level, they differ significantly in hierarchical organization and interregional connectivity. We found that subcortical areas were more strongly connected with primary sensory, association, and paralimbic areas in children, whereas young-adults showed stronger cortico-cortical connectivity between paralimbic, limbic, and association areas. Further, combined analysis of functional connectivity with wiring distance measures derived from white-matter fiber tracking revealed that the development of large-scale brain networks is characterized by weakening of short-range functional connectivity and strengthening of long-range functional connectivity. Importantly, our findings show that the dynamic process of over-connectivity followed by pruning, which rewires connectivity at the neuronal level, also operates at the systems level, helping to reconfigure and rebalance subcortical and paralimbic connectivity in the developing brain. Our study demonstrates the usefulness of network analysis of brain connectivity to elucidate key principles underlying functional brain maturation, paving the way for novel studies of disrupted brain connectivity in neurodevelopmental disorders such as autism. PMID:19621066

Alterations in Cerebral White Matter and Neuropsychology in Patients with Cirrhosis and Falls

PubMed Central

Gómez-Ansón, Beatriz; Román, Eva; Fernández de Bobadilla, Ramón; Pires-Encuentra, Patricia; Díaz-Manera, Jordi; Núñez, Fidel; Martinez-Horta, Saül; Vives-Gilabert, Yolanda; Pagonabarraga, Javier; Kulisevsky, Jaume; Guarner, Carlos; Soriano, Germán

2015-01-01

Background & Aim Falls are frequent in patients with cirrhosis but underlying mechanisms are unknown. The aim was to determine the neuropsychological, neurological and brain alterations using magnetic resonance-diffusion tensor imaging (MR-DTI) in cirrhotic patients with falls. Patients and methods Twelve patients with cirrhosis and falls in the previous year were compared to 9 cirrhotic patients without falls. A comprehensive neuropsychological and neurological evaluation of variables that may predispose to falls included: the Mini-Mental State Examination, Psychometric Hepatic Encephalopathy Score (PHES), Parkinson’s Disease-Cognitive Rating Scale, specific tests to explore various cognitive domains, Unified Parkinson’s Disease Rating Scale to evaluate parkinsonism, scales for ataxia and muscular strength, and electroneurography. High-field MR (3T) including DTI and structural sequences was performed in all patients. Results The main neuropsychological findings were impairment in PHES (p = 0.03), Parkinson’s Disease-Cognitive Rating Scale (p = 0.04) and in executive (p<0.05) and visuospatial-visuoconstructive functions (p<0.05) in patients with falls compared to those without. There were no statistical differences between the two groups in the neurological evaluation or in the visual assessment of MRI. MR-DTI showed alterations in white matter integrity in patients with falls compared to those without falls (p<0.05), with local maxima in the superior longitudinal fasciculus and corticospinal tract. These alterations were independent of PHES as a covariate and correlated with executive dysfunction (p<0.05). Conclusions With the limitation of the small sample size, our results suggest that patients with cirrhosis and falls present alterations in brain white matter tracts related to executive dysfunction. These alterations are independent of PHES impairment. PMID:25793766

Disruption of White Matter Integrity in Adult Survivors of Childhood Brain Tumors: Correlates with Long-Term Intellectual Outcomes.

PubMed

King, Tricia Z; Wang, Liya; Mao, Hui

2015-01-01

Although chemotherapy and radiation treatment have contributed to increased survivorship, treatment-induced brain injury has been a concern when examining long-term intellectual outcomes of survivors. Specifically, disruption of brain white matter integrity and its relationship to intellectual outcomes in adult survivors of childhood brain tumors needs to be better understood. Fifty-four participants underwent diffusion tensor imaging in addition to structural MRI and an intelligence test (IQ). Voxel-wise group comparisons of fractional anisotropy calculated from DTI data were performed using Tract Based Spatial Statistics (TBSS) on 27 survivors (14 treated with radiation with and without chemotherapy and 13 treated without radiation treatment on average over 13 years since diagnosis) and 27 healthy comparison participants. Whole brain white matter fractional anisotropy (FA) differences were explored between each group. The relationships between IQ and FA in the regions where statistically lower FA values were found in survivors were examined, as well as the role of cumulative neurological factors. The group of survivors treated with radiation with and without chemotherapy had lower IQ relative to the group of survivors without radiation treatment and the healthy comparison group. TBSS identified white matter regions with significantly different mean fractional anisotropy between the three different groups. A lower level of white matter integrity was found in the radiation with or without chemotherapy treated group compared to the group without radiation treatment and also the healthy control group. The group without radiation treatment had a lower mean FA relative to healthy controls. The white matter disruption of the radiation with or without chemotherapy treated survivors was positively correlated with IQ and cumulative neurological factors. Lower long-term intellectual outcomes of childhood brain tumor survivors are associated with lower white matter integrity. Radiation and adjunct chemotherapy treatment may play a role in greater white matter disruption. The relationships between white matter integrity and IQ, as well as cumulative neurological risk factors exist in young adult survivors of childhood brain tumors.

Visual feature integration with an attention deficit.

PubMed

Arguin, M; Cavanagh, P; Joanette, Y

1994-01-01

Treisman's feature integration theory proposes that the perception of illusory conjunctions of correctly encoded visual features is due to the failure of an attentional process. This hypothesis was examined by studying brain-damaged subjects who had previously been shown to have difficulty in attending to contralesional stimulation. These subjects exhibited a massive feature integration deficit for contralesional stimulation relative to ipsilesional displays. In contrast, both normal age-matched controls and brain-damaged subjects who did not exhibit any evidence of an attention deficit showed comparable feature integration performance with left- and right-hemifield stimulation. These observations indicate the crucial function of attention for visual feature integration in normal perception.

Human brain mass: similar body composition associations as observed across mammals.

PubMed

Heymsfield, Steven B; Müller, Manfred J; Bosy-Westphal, Anja; Thomas, Diana; Shen, Wei

2012-01-01

A classic association is the link between brain mass and body mass across mammals that has now been shown to derive from fat-free mass (FFM) and not fat mass (FM). This study aimed to establish for the first time the associations between human brain mass and body composition and to compare these relations with those established for liver as a reference organ. Subjects were 112 men and 148 women who had brain and liver mass measured by magnetic resonance imaging with FM and FFM measured by dual-energy X-ray absorptiometry. Brain mass scaled to height (H) with powers of ≤0.6 in men and women; liver mass and FFM both scaled similarly as H(~2) . The fraction of FFM as brain thus scaled inversely to height (P < 0.001) while liver mass/FFM was independent of height. After controlling for age, brain, and liver mass were associated with FFM while liver was additionally associated with FM (all models P ≤ 0.01). After controlling for age and sex, FFM accounted for ~5% of the variance in brain mass while levels were substantially higher for liver mass (~60%). Brain mass was significantly larger (P < 0.001) in men than in women, even after controlling for age and FFM. As across mammals, human brain mass associates significantly, although weakly, with FFM and not FM; the fraction of FFM as brain relates inversely to height; brain differs in these relations from liver, another small high metabolic rate organ; and the sexual dimorphism in brain mass persists even after adjusting for age and FFM. Copyright © 2012 Wiley Periodicals, Inc.

A conserved BDNF, glutamate- and GABA-enriched gene module related to human depression identified by coexpression meta-analysis and DNA variant genome-wide association studies.

PubMed

Chang, Lun-Ching; Jamain, Stephane; Lin, Chien-Wei; Rujescu, Dan; Tseng, George C; Sibille, Etienne

2014-01-01

Large scale gene expression (transcriptome) analysis and genome-wide association studies (GWAS) for single nucleotide polymorphisms have generated a considerable amount of gene- and disease-related information, but heterogeneity and various sources of noise have limited the discovery of disease mechanisms. As systematic dataset integration is becoming essential, we developed methods and performed meta-clustering of gene coexpression links in 11 transcriptome studies from postmortem brains of human subjects with major depressive disorder (MDD) and non-psychiatric control subjects. We next sought enrichment in the top 50 meta-analyzed coexpression modules for genes otherwise identified by GWAS for various sets of disorders. One coexpression module of 88 genes was consistently and significantly associated with GWAS for MDD, other neuropsychiatric disorders and brain functions, and for medical illnesses with elevated clinical risk of depression, but not for other diseases. In support of the superior discriminative power of this novel approach, we observed no significant enrichment for GWAS-related genes in coexpression modules extracted from single studies or in meta-modules using gene expression data from non-psychiatric control subjects. Genes in the identified module encode proteins implicated in neuronal signaling and structure, including glutamate metabotropic receptors (GRM1, GRM7), GABA receptors (GABRA2, GABRA4), and neurotrophic and development-related proteins [BDNF, reelin (RELN), Ephrin receptors (EPHA3, EPHA5)]. These results are consistent with the current understanding of molecular mechanisms of MDD and provide a set of putative interacting molecular partners, potentially reflecting components of a functional module across cells and biological pathways that are synchronously recruited in MDD, other brain disorders and MDD-related illnesses. Collectively, this study demonstrates the importance of integrating transcriptome data, gene coexpression modules and GWAS results for providing novel and complementary approaches to investigate the molecular pathology of MDD and other complex brain disorders.

Brain Volume, Connectivity, and Neuropsychological Performance in Mild Traumatic Brain Injury: The Impact of Post-Traumatic Stress Disorder Symptoms.

PubMed

Lopez, Katherine C; Leary, Jacob B; Pham, Dzung L; Chou, Yi-Yu; Dsurney, John; Chan, Leighton

2017-01-01

Post-traumatic stress disorder (PTSD) is commonly associated with mild traumatic brain injury (mTBI). To better understand their relationship, we examined neuroanatomical structures and neuropsychological performance in a sample of individuals with mTBI, with and without PTSD symptoms. Thirty-nine subjects with mTBI were dichotomized into those with (n = 12) and without (n = 27) significant PTSD symptoms based on scores on the PTSD Checklist. Using a region-of-interest approach, fronto-temporal volumes, fiber bundles obtained by diffusion tensor imaging, and neuropsychological scores were compared between the two groups. After controlling for total intracranial volume and age, subjects with mTBI and PTSD symptoms exhibited volumetric differences in the entorhinal cortex, an area associated with memory networks, relative to mTBI-only patients (F = 4.28; p = 0.046). Additionally, subjects with PTSD symptoms showed reduced white matter integrity in the right cingulum bundle (axial diffusivity, F = 6.04; p = 0.020). Accompanying these structural alterations, mTBI and PTSD subjects also showed impaired performance in encoding (F = 5.98; p = 0.019) and retrieval (F = 7.32; p = 0.010) phases of list learning and in tests of processing speed (Wechsler Adult Intelligence Scale Processing Speed Index, F = 12.23; p = 0.001; Trail Making Test A, F = 5.56; p = 0.024). Increased volume and white matter disruptions in these areas, commonly associated with memory functions, may be related to functional disturbances during cognitively demanding tasks. Differences in brain volume and white matter integrity between mTBI subjects and those with mTBI and co-morbid PTSD symptoms point to neuroanatomical differences that may underlie poorer recovery of mTBI subjects who experience PTSD symptoms. These findings support theoretical models of PTSD and its relationship to learning deficits.

Distinguished Neuropsychologist Award Lecture 1999. The lesion(s) in traumatic brain injury: implications for clinical neuropsychology.

PubMed

Bigler, E D

2001-02-01

This paper overviews the current status of neuroimaging in neuropsychological outcome in traumatic brain injury (TBI). The pathophysiology of TBI is reviewed and integrated with expected neuroimaging and neuropsychological findings. The integration of clinical and quantitative magnetic resonance (QMR) imaging is the main topic of review, but these findings are integrated with single photon emission computed tomography (SPECT) and magnetoencephalography (MEG). Various clinical caveats are offered for the clinician.

Optogenetic interrogation of neural circuits: technology for probing mammalian brain structures

PubMed Central

Zhang, Feng; Gradinaru, Viviana; Adamantidis, Antoine R; Durand, Remy; Airan, Raag D; de Lecea, Luis; Deisseroth, Karl

2015-01-01

Elucidation of the neural substrates underlying complex animal behaviors depends on precise activity control tools, as well as compatible readout methods. Recent developments in optogenetics have addressed this need, opening up new possibilities for systems neuroscience. Interrogation of even deep neural circuits can be conducted by directly probing the necessity and sufficiency of defined circuit elements with millisecond-scale, cell type-specific optical perturbations, coupled with suitable readouts such as electrophysiology, optical circuit dynamics measures and freely moving behavior in mammals. Here we collect in detail our strategies for delivering microbial opsin genes to deep mammalian brain structures in vivo, along with protocols for integrating the resulting optical control with compatible readouts (electrophysiological, optical and behavioral). The procedures described here, from initial virus preparation to systems-level functional readout, can be completed within 4–5 weeks. Together, these methods may help in providing circuit-level insight into the dynamics underlying complex mammalian behaviors in health and disease. PMID:20203662

A model of the temporal dynamics of multisensory enhancement

PubMed Central

Rowland, Benjamin A.; Stein, Barry E.

2014-01-01

The senses transduce different forms of environmental energy, and the brain synthesizes information across them to enhance responses to salient biological events. We hypothesize that the potency of multisensory integration is attributable to the convergence of independent and temporally aligned signals derived from cross-modal stimulus configurations onto multisensory neurons. The temporal profile of multisensory integration in neurons of the deep superior colliculus (SC) is consistent with this hypothesis. The responses of these neurons to visual, auditory, and combinations of visual–auditory stimuli reveal that multisensory integration takes place in real-time; that is, the input signals are integrated as soon as they arrive at the target neuron. Interactions between cross-modal signals may appear to reflect linear or nonlinear computations on a moment-by-moment basis, the aggregate of which determines the net product of multisensory integration. Modeling observations presented here suggest that the early nonlinear components of the temporal profile of multisensory integration can be explained with a simple spiking neuron model, and do not require more sophisticated assumptions about the underlying biology. A transition from nonlinear “super-additive” computation to linear, additive computation can be accomplished via scaled inhibition. The findings provide a set of design constraints for artificial implementations seeking to exploit the basic principles and potency of biological multisensory integration in contexts of sensory substitution or augmentation. PMID:24374382

From Hippocampus to Whole-Brain: The Role of Integrative Processing in Episodic Memory Retrieval

PubMed Central

Geib, Benjamin R.; Stanley, Matthew L.; Dennis, Nancy A.; Woldorff, Marty G.; Cabeza, Roberto

2017-01-01

Multivariate functional connectivity analyses of neuroimaging data have revealed the importance of complex, distributed interactions between disparate yet interdependent brain regions. Recent work has shown that topological properties of functional brain networks are associated with individual and group differences in cognitive performance, including in episodic memory. After constructing functional whole-brain networks derived from an event-related fMRI study of memory retrieval, we examined differences in functional brain network architecture between forgotten and remembered words. This study yielded three main findings. First, graph theory analyses showed that successfully remembering compared to forgetting was associated with significant changes in the connectivity profile of the left hippocampus and a corresponding increase in efficient communication with the rest of the brain. Second, bivariate functional connectivity analyses indicated stronger interactions between the left hippocampus and a retrieval assembly for remembered versus forgotten items. This assembly included the left precuneus, left caudate, bilateral supramarginal gyrus, and the bilateral dorsolateral superior frontal gyrus. Integrative properties of the retrieval assembly were greater for remembered than forgotten items. Third, whole-brain modularity analyses revealed that successful memory retrieval was marginally significantly associated with a less segregated modular architecture in the network. The magnitude of the decreases in modularity between remembered and forgotten conditions was related to memory performance. These findings indicate that increases in integrative properties at the nodal, retrieval assembly, and whole-brain topological levels facilitate memory retrieval, while also underscoring the potential of multivariate brain connectivity approaches for providing valuable new insights into the neural bases of memory processes. PMID:28112460

Coordinated Gene Expression of Neuroinflammatory and Cell Signaling Markers in Dorsolateral Prefrontal Cortex during Human Brain Development and Aging

PubMed Central

Primiani, Christopher T.; Ryan, Veronica H.; Rao, Jagadeesh S.; Cam, Margaret C.; Ahn, Kwangmi; Modi, Hiren R.; Rapoport, Stanley I.

2014-01-01

Background Age changes in expression of inflammatory, synaptic, and neurotrophic genes are not well characterized during human brain development and senescence. Knowing these changes may elucidate structural, metabolic, and functional brain processes over the lifespan, as well vulnerability to neurodevelopmental or neurodegenerative diseases. Hypothesis Expression levels of inflammatory, synaptic, and neurotrophic genes in the human brain are coordinated over the lifespan and underlie changes in phenotypic networks or cascades. Methods We used a large-scale microarray dataset from human prefrontal cortex, BrainCloud, to quantify age changes over the lifespan, divided into Development (0 to 21 years, 87 brains) and Aging (22 to 78 years, 144 brains) intervals, in transcription levels of 39 genes. Results Gene expression levels followed different trajectories over the lifespan. Many changes were intercorrelated within three similar groups or clusters of genes during both Development and Aging, despite different roles of the gene products in the two intervals. During Development, changes were related to reported neuronal loss, dendritic growth and pruning, and microglial events; TLR4, IL1R1, NFKB1, MOBP, PLA2G4A, and PTGS2 expression increased in the first years of life, while expression of synaptic genes GAP43 and DBN1 decreased, before reaching plateaus. During Aging, expression was upregulated for potentially pro-inflammatory genes such as NFKB1, TRAF6, TLR4, IL1R1, TSPO, and GFAP, but downregulated for neurotrophic and synaptic integrity genes such as BDNF, NGF, PDGFA, SYN, and DBN1. Conclusions Coordinated changes in gene transcription cascades underlie changes in synaptic, neurotrophic, and inflammatory phenotypic networks during brain Development and Aging. Early postnatal expression changes relate to neuronal, glial, and myelin growth and synaptic pruning events, while late Aging is associated with pro-inflammatory and synaptic loss changes. Thus, comparable transcriptional regulatory networks that operate throughout the lifespan underlie different phenotypic processes during Aging compared to Development. PMID:25329999

Coordinated gene expression of neuroinflammatory and cell signaling markers in dorsolateral prefrontal cortex during human brain development and aging.

PubMed

Primiani, Christopher T; Ryan, Veronica H; Rao, Jagadeesh S; Cam, Margaret C; Ahn, Kwangmi; Modi, Hiren R; Rapoport, Stanley I

2014-01-01

Age changes in expression of inflammatory, synaptic, and neurotrophic genes are not well characterized during human brain development and senescence. Knowing these changes may elucidate structural, metabolic, and functional brain processes over the lifespan, as well vulnerability to neurodevelopmental or neurodegenerative diseases. Expression levels of inflammatory, synaptic, and neurotrophic genes in the human brain are coordinated over the lifespan and underlie changes in phenotypic networks or cascades. We used a large-scale microarray dataset from human prefrontal cortex, BrainCloud, to quantify age changes over the lifespan, divided into Development (0 to 21 years, 87 brains) and Aging (22 to 78 years, 144 brains) intervals, in transcription levels of 39 genes. Gene expression levels followed different trajectories over the lifespan. Many changes were intercorrelated within three similar groups or clusters of genes during both Development and Aging, despite different roles of the gene products in the two intervals. During Development, changes were related to reported neuronal loss, dendritic growth and pruning, and microglial events; TLR4, IL1R1, NFKB1, MOBP, PLA2G4A, and PTGS2 expression increased in the first years of life, while expression of synaptic genes GAP43 and DBN1 decreased, before reaching plateaus. During Aging, expression was upregulated for potentially pro-inflammatory genes such as NFKB1, TRAF6, TLR4, IL1R1, TSPO, and GFAP, but downregulated for neurotrophic and synaptic integrity genes such as BDNF, NGF, PDGFA, SYN, and DBN1. Coordinated changes in gene transcription cascades underlie changes in synaptic, neurotrophic, and inflammatory phenotypic networks during brain Development and Aging. Early postnatal expression changes relate to neuronal, glial, and myelin growth and synaptic pruning events, while late Aging is associated with pro-inflammatory and synaptic loss changes. Thus, comparable transcriptional regulatory networks that operate throughout the lifespan underlie different phenotypic processes during Aging compared to Development.

Phenotypic Integration of Neurocranium and Brain

PubMed Central

RICHTSMEIER, JOAN T.; ALDRIDGE, KRISTINA; DeLEON, VALERIE B.; PANCHAL, JAYESH; KANE, ALEX A.; MARSH, JEFFREY L.; YAN, PENG; COLE, THEODORE M.

2009-01-01

Evolutionary history of Mammalia provides strong evidence that the morphology of skull and brain change jointly in evolution. Formation and development of brain and skull co-occur and are dependent upon a series of morphogenetic and patterning processes driven by genes and their regulatory programs. Our current concept of skull and brain as separate tissues results in distinct analyses of these tissues by most researchers. In this study, we use 3D computed tomography and magnetic resonance images of pediatric individuals diagnosed with premature closure of cranial sutures (craniosynostosis) to investigate phenotypic relationships between the brain and skull. It has been demonstrated previously that the skull and brain acquire characteristic dysmorphologies in isolated craniosynostosis, but relatively little is known of the developmental interactions that produce these anomalies. Our comparative analysis of phenotypic integration of brain and skull in premature closure of the sagittal and the right coronal sutures demonstrates that brain and skull are strongly integrated and that the significant differences in patterns of association do not occur local to the prematurely closed suture. We posit that the current focus on the suture as the basis for this condition may identify a proximate, but not the ultimate cause for these conditions. Given that premature suture closure reduces the number of cranial bones, and that a persistent loss of skull bones is demonstrated over the approximately 150 million years of synapsid evolution, craniosynostosis may serve as an informative model for evolution of the mammalian skull. PMID:16526048

Phenotypic integration of neurocranium and brain.

PubMed

Richtsmeier, Joan T; Aldridge, Kristina; DeLeon, Valerie B; Panchal, Jayesh; Kane, Alex A; Marsh, Jeffrey L; Yan, Peng; Cole, Theodore M

2006-07-15

Evolutionary history of Mammalia provides strong evidence that the morphology of skull and brain change jointly in evolution. Formation and development of brain and skull co-occur and are dependent upon a series of morphogenetic and patterning processes driven by genes and their regulatory programs. Our current concept of skull and brain as separate tissues results in distinct analyses of these tissues by most researchers. In this study, we use 3D computed tomography and magnetic resonance images of pediatric individuals diagnosed with premature closure of cranial sutures (craniosynostosis) to investigate phenotypic relationships between the brain and skull. It has been demonstrated previously that the skull and brain acquire characteristic dysmorphologies in isolated craniosynostosis, but relatively little is known of the developmental interactions that produce these anomalies. Our comparative analysis of phenotypic integration of brain and skull in premature closure of the sagittal and the right coronal sutures demonstrates that brain and skull are strongly integrated and that the significant differences in patterns of association do not occur local to the prematurely closed suture. We posit that the current focus on the suture as the basis for this condition may identify a proximate, but not the ultimate cause for these conditions. Given that premature suture closure reduces the number of cranial bones, and that a persistent loss of skull bones is demonstrated over the approximately 150 million years of synapsid evolution, craniosynostosis may serve as an informative model for evolution of the mammalian skull. Copyright 2006 Wiley-Liss, Inc.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-01-01

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

Cross-frequency coupling in real and virtual brain networks

PubMed Central

Jirsa, Viktor; Müller, Viktor

2013-01-01

Information processing in the brain is thought to rely on the convergence and divergence of oscillatory behaviors of widely distributed brain areas. This information flow is captured in its simplest form via the concepts of synchronization and desynchronization and related metrics. More complex forms of information flow are transient synchronizations and multi-frequency behaviors with metrics related to cross-frequency coupling (CFC). It is supposed that CFC plays a crucial role in the organization of large-scale networks and functional integration across large distances. In this study, we describe different CFC measures and test their applicability in simulated and real electroencephalographic (EEG) data obtained during resting state. For these purposes, we derive generic oscillator equations from full brain network models. We systematically model and simulate the various scenarios of CFC under the influence of noise to obtain biologically realistic oscillator dynamics. We find that (i) specific CFC-measures detect correctly in most cases the nature of CFC under noise conditions, (ii) bispectrum (BIS) and bicoherence (BIC) correctly detect the CFCs in simulated data, (iii) empirical resting state EEG show a prominent delta-alpha CFC as identified by specific CFC measures and the more classic BIS and BIC. This coupling was mostly asymmetric (directed) and generally higher in the eyes closed (EC) than in the eyes open (EO) condition. In conjunction, these two sets of measures provide a powerful toolbox to reveal the nature of couplings from experimental data and as such allow inference on the brain state dependent information processing. Methodological advantages of using CFC measures and theoretical significance of delta and alpha interactions during resting and other brain states are discussed. PMID:23840188

Face classification using electronic synapses

NASA Astrophysics Data System (ADS)

Yao, Peng; Wu, Huaqiang; Gao, Bin; Eryilmaz, Sukru Burc; Huang, Xueyao; Zhang, Wenqiang; Zhang, Qingtian; Deng, Ning; Shi, Luping; Wong, H.-S. Philip; Qian, He

2017-05-01

Conventional hardware platforms consume huge amount of energy for cognitive learning due to the data movement between the processor and the off-chip memory. Brain-inspired device technologies using analogue weight storage allow to complete cognitive tasks more efficiently. Here we present an analogue non-volatile resistive memory (an electronic synapse) with foundry friendly materials. The device shows bidirectional continuous weight modulation behaviour. Grey-scale face classification is experimentally demonstrated using an integrated 1024-cell array with parallel online training. The energy consumption within the analogue synapses for each iteration is 1,000 × (20 ×) lower compared to an implementation using Intel Xeon Phi processor with off-chip memory (with hypothetical on-chip digital resistive random access memory). The accuracy on test sets is close to the result using a central processing unit. These experimental results consolidate the feasibility of analogue synaptic array and pave the way toward building an energy efficient and large-scale neuromorphic system.

Face classification using electronic synapses.

PubMed

Yao, Peng; Wu, Huaqiang; Gao, Bin; Eryilmaz, Sukru Burc; Huang, Xueyao; Zhang, Wenqiang; Zhang, Qingtian; Deng, Ning; Shi, Luping; Wong, H-S Philip; Qian, He

2017-05-12

Conventional hardware platforms consume huge amount of energy for cognitive learning due to the data movement between the processor and the off-chip memory. Brain-inspired device technologies using analogue weight storage allow to complete cognitive tasks more efficiently. Here we present an analogue non-volatile resistive memory (an electronic synapse) with foundry friendly materials. The device shows bidirectional continuous weight modulation behaviour. Grey-scale face classification is experimentally demonstrated using an integrated 1024-cell array with parallel online training. The energy consumption within the analogue synapses for each iteration is 1,000 × (20 ×) lower compared to an implementation using Intel Xeon Phi processor with off-chip memory (with hypothetical on-chip digital resistive random access memory). The accuracy on test sets is close to the result using a central processing unit. These experimental results consolidate the feasibility of analogue synaptic array and pave the way toward building an energy efficient and large-scale neuromorphic system.

The modulatory effect of semantic familiarity on the audiovisual integration of face-name pairs.

PubMed

Li, Yuanqing; Wang, Fangyi; Huang, Biao; Yang, Wanqun; Yu, Tianyou; Talsma, Durk

2016-12-01

To recognize individuals, the brain often integrates audiovisual information from familiar or unfamiliar faces, voices, and auditory names. To date, the effects of the semantic familiarity of stimuli on audiovisual integration remain unknown. In this functional magnetic resonance imaging (fMRI) study, we used familiar/unfamiliar facial images, auditory names, and audiovisual face-name pairs as stimuli to determine the influence of semantic familiarity on audiovisual integration. First, we performed a general linear model analysis using fMRI data and found that audiovisual integration occurred for familiar congruent and unfamiliar face-name pairs but not for familiar incongruent pairs. Second, we decoded the familiarity categories of the stimuli (familiar vs. unfamiliar) from the fMRI data and calculated the reproducibility indices of the brain patterns that corresponded to familiar and unfamiliar stimuli. The decoding accuracy rate was significantly higher for familiar congruent versus unfamiliar face-name pairs (83.2%) than for familiar versus unfamiliar faces (63.9%) and for familiar versus unfamiliar names (60.4%). This increase in decoding accuracy was not observed for familiar incongruent versus unfamiliar pairs. Furthermore, compared with the brain patterns associated with facial images or auditory names, the reproducibility index was significantly improved for the brain patterns of familiar congruent face-name pairs but not those of familiar incongruent or unfamiliar pairs. Our results indicate the modulatory effect that semantic familiarity has on audiovisual integration. Specifically, neural representations were enhanced for familiar congruent face-name pairs compared with visual-only faces and auditory-only names, whereas this enhancement effect was not observed for familiar incongruent or unfamiliar pairs. Hum Brain Mapp 37:4333-4348, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

From hippocampus to whole-brain: The role of integrative processing in episodic memory retrieval.

PubMed

Geib, Benjamin R; Stanley, Matthew L; Dennis, Nancy A; Woldorff, Marty G; Cabeza, Roberto

2017-04-01

Multivariate functional connectivity analyses of neuroimaging data have revealed the importance of complex, distributed interactions between disparate yet interdependent brain regions. Recent work has shown that topological properties of functional brain networks are associated with individual and group differences in cognitive performance, including in episodic memory. After constructing functional whole-brain networks derived from an event-related fMRI study of memory retrieval, we examined differences in functional brain network architecture between forgotten and remembered words. This study yielded three main findings. First, graph theory analyses showed that successfully remembering compared to forgetting was associated with significant changes in the connectivity profile of the left hippocampus and a corresponding increase in efficient communication with the rest of the brain. Second, bivariate functional connectivity analyses indicated stronger interactions between the left hippocampus and a retrieval assembly for remembered versus forgotten items. This assembly included the left precuneus, left caudate, bilateral supramarginal gyrus, and the bilateral dorsolateral superior frontal gyrus. Integrative properties of the retrieval assembly were greater for remembered than forgotten items. Third, whole-brain modularity analyses revealed that successful memory retrieval was marginally significantly associated with a less segregated modular architecture in the network. The magnitude of the decreases in modularity between remembered and forgotten conditions was related to memory performance. These findings indicate that increases in integrative properties at the nodal, retrieval assembly, and whole-brain topological levels facilitate memory retrieval, while also underscoring the potential of multivariate brain connectivity approaches for providing valuable new insights into the neural bases of memory processes. Hum Brain Mapp 38:2242-2259, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Label-free, multi-scale imaging of ex-vivo mouse brain using spatial light interference microscopy

NASA Astrophysics Data System (ADS)

Min, Eunjung; Kandel, Mikhail E.; Ko, Chemyong J.; Popescu, Gabriel; Jung, Woonggyu; Best-Popescu, Catherine

2016-12-01

Brain connectivity spans over broad spatial scales, from nanometers to centimeters. In order to understand the brain at multi-scale, the neural network in wide-field has been visualized in detail by taking advantage of light microscopy. However, the process of staining or addition of fluorescent tags is commonly required, and the image contrast is insufficient for delineation of cytoarchitecture. To overcome this barrier, we use spatial light interference microscopy to investigate brain structure with high-resolution, sub-nanometer pathlength sensitivity without the use of exogenous contrast agents. Combining wide-field imaging and a mosaic algorithm developed in-house, we show the detailed architecture of cells and myelin, within coronal olfactory bulb and cortical sections, and from sagittal sections of the hippocampus and cerebellum. Our technique is well suited to identify laminar characteristics of fiber tract orientation within white matter, e.g. the corpus callosum. To further improve the macro-scale contrast of anatomical structures, and to better differentiate axons and dendrites from cell bodies, we mapped the tissue in terms of its scattering property. Based on our results, we anticipate that spatial light interference microscopy can potentially provide multiscale and multicontrast perspectives of gross and microscopic brain anatomy.

Altered Blood-Brain Barrier Permeability in Patients With Systemic Lupus Erythematosus: A Novel Imaging Approach.

PubMed

Gulati, Gaurav; Jones, Jordan T; Lee, Gregory; Altaye, Mekibib; Beebe, Dean W; Meyers-Eaton, Jamie; Wiley, Kasha; Brunner, Hermine I; DiFrancesco, Mark W

2017-02-01

To evaluate a safe, noninvasive magnetic resonance imaging (MRI) method to measure regional blood-brain barrier integrity and investigate its relationship with neurocognitive function and regional gray matter volume in juvenile-onset systemic lupus erythematosus (SLE). In this cross-sectional, case-control study, capillary permeability was measured as a marker of blood-brain barrier integrity in juvenile SLE patients and matched healthy controls, using a combination of arterial spin labeling and diffusion-weighted brain MRI. Regional gray matter volume was measured by voxel-based morphometry. Correlation analysis was done to investigate the relationship between regional capillary permeability and regional gray matter volume. Formal neurocognitive testing was completed (measuring attention, visuoconstructional ability, working memory, and psychomotor speed), and scores were regressed against regional blood-brain barrier integrity among juvenile SLE patients. Formal cognitive testing confirmed normal cognitive ability in all juvenile SLE subjects (n = 11) included in the analysis. Regional capillary permeability was negatively associated (P = 0.026) with neurocognitive performance concerning psychomotor speed in the juvenile SLE cohort. Compared with controls (n = 11), juvenile SLE patients had significantly greater capillary permeability involving Brodmann's areas 19, 28, 36, and 37 and caudate structures (P < 0.05 for all). There is imaging evidence of increased regional capillary permeability in juvenile SLE patients with normal cognitive performance using a novel noninvasive MRI technique. These blood-brain barrier outcomes appear consistent with functional neuronal network alterations and gray matter volume loss previously observed in juvenile SLE patients with overt neurocognitive deficits, supporting the notion that blood-brain barrier integrity loss precedes the loss of cognitive ability in juvenile SLE. Longitudinal studies are needed to confirm the findings of this pilot study. © 2016, American College of Rheumatology.

Integrative biological analysis for neuropsychopharmacology.

PubMed

Emmett, Mark R; Kroes, Roger A; Moskal, Joseph R; Conrad, Charles A; Priebe, Waldemar; Laezza, Fernanda; Meyer-Baese, Anke; Nilsson, Carol L

2014-01-01

Although advances in psychotherapy have been made in recent years, drug discovery for brain diseases such as schizophrenia and mood disorders has stagnated. The need for new biomarkers and validated therapeutic targets in the field of neuropsychopharmacology is widely unmet. The brain is the most complex part of human anatomy from the standpoint of number and types of cells, their interconnections, and circuitry. To better meet patient needs, improved methods to approach brain studies by understanding functional networks that interact with the genome are being developed. The integrated biological approaches--proteomics, transcriptomics, metabolomics, and glycomics--have a strong record in several areas of biomedicine, including neurochemistry and neuro-oncology. Published applications of an integrated approach to projects of neurological, psychiatric, and pharmacological natures are still few but show promise to provide deep biological knowledge derived from cells, animal models, and clinical materials. Future studies that yield insights based on integrated analyses promise to deliver new therapeutic targets and biomarkers for personalized medicine.

Assessment of abnormal brain structures and networks in major depressive disorder using morphometric and connectome analyses.

PubMed

Chen, Vincent Chin-Hung; Shen, Chao-Yu; Liang, Sophie Hsin-Yi; Li, Zhen-Hui; Tyan, Yeu-Sheng; Liao, Yin-To; Huang, Yin-Chen; Lee, Yena; McIntyre, Roger S; Weng, Jun-Cheng

2016-11-15

It is hypothesized that the phenomenology of major depressive disorder (MDD) is subserved by disturbances in the structure and function of brain circuits; however, findings of structural abnormalities using MRI have been inconsistent. Generalized q-sampling imaging (GQI) methodology provides an opportunity to assess the functional integrity of white matter tracts in implicated circuits. The study population was comprised of 16 outpatients with MDD (mean age 44.81±2.2 years) and 30 age- and gender-matched healthy controls (mean age 45.03±1.88 years). We excluded participants with any other primary mental disorder, substance use disorder, or any neurological illnesses. We used T1-weighted 3D MRI with voxel-based morphometry (VBM) and vertex-wise shape analysis, and GQI with voxel-based statistical analysis (VBA), graph theoretical analysis (GTA) and network-based statistical (NBS) analysis to evaluate brain structure and connectivity abnormalities in MDD compared to healthy controls correlates with clinical measures of depressive symptom severity, Hamilton Depression Rating Scale 17-item (HAMD) and Hospital Anxiety and Depression Scale (HADS). Using VBM and vertex-wise shape analyses, we found significant volumetric decreases in the hippocampus and amygdala among subjects with MDD (p<0.001). Using GQI, we found decreases in diffusion anisotropy in the superior longitudinal fasciculus and increases in diffusion probability distribution in the frontal lobe among subjects with MDD (p<0.01). In GTA and NBS analyses, we found several disruptions in connectivity among subjects with MDD, particularly in the frontal lobes (p<0.05). In addition, structural alterations were correlated with depressive symptom severity (p<0.01). Small sample size; the cross-sectional design did not allow us to observe treatment effects in the MDD participants. Our results provide further evidence indicating that MDD may be conceptualized as a brain disorder with abnormal circuit structure and connectivity. Copyright © 2016 Elsevier B.V. All rights reserved.

Physical Exercise Keeps the Brain Connected: Biking Increases White Matter Integrity in Patients With Schizophrenia and Healthy Controls

PubMed Central

Svatkova, Alena; Mandl, René C.W.; Scheewe, Thomas W.; Cahn, Wiepke; Kahn, René S.; Hulshoff Pol, Hilleke E.

2015-01-01

It has been shown that learning a new skill leads to structural changes in the brain. However, it is unclear whether it is the acquisition or continuous practicing of the skill that causes this effect and whether brain connectivity of patients with schizophrenia can benefit from such practice. We examined the effect of 6 months exercise on a stationary bicycle on the brain in patients with schizophrenia and healthy controls. Biking is an endemic skill in the Netherlands and thus offers an ideal situation to disentangle the effects of learning vs practice. The 33 participating patients with schizophrenia and 48 healthy individuals were assigned to either one of two conditions, ie, physical exercise or life-as-usual, balanced for diagnosis. Diffusion tensor imaging brain scans were made prior to and after intervention. We demonstrate that irrespective of diagnosis regular physical exercise of an overlearned skill, such as bicycling, significantly increases the integrity, especially of motor functioning related, white matter fiber tracts whereas life-as-usual leads to a decrease in fiber integrity. Our findings imply that exercise of an overlearned physical skill improves brain connectivity in patients and healthy individuals. This has important implications for understanding the effect of fitness programs on the brain in both healthy subjects and patients with schizophrenia. Moreover, the outcome may even apply to the nonphysical realm. PMID:25829377

Integrating Whole Brain Teaching Strategies to Create a More Engaged Learning Environment

ERIC Educational Resources Information Center

Palasigue, Jesame Torres

2009-01-01

In today's postmodern society, it is getting harder and harder to get the students engaged in classroom instruction and learning. The purpose of this research project was to seek ways to create a more engaged learning environment for the students. The teacher-researcher integrated the most current educational reform "Whole Brain Teaching" method…

Integrating Retinoic Acid Signaling with Brain Function

ERIC Educational Resources Information Center

Luo, Tuanlian; Wagner, Elisabeth; Drager, Ursula C.

2009-01-01

The vitamin A derivative retinoic acid (RA) regulates the transcription of about a 6th of the human genome. Compelling evidence indicates a role of RA in cognitive activities, but its integration with the molecular mechanisms of higher brain functions is not known. Here we describe the properties of RA signaling in the mouse, which point to…

Deep Brain Stimulation

PubMed Central

Lyketsos, Constantine G.; Pendergrass, Jo Cara; Lozano, Andres M.

2012-01-01

Recent studies have identified an association between memory deficits and defects of the integrated neuronal cortical areas known collectively as the default mode network. It is conceivable that the amyloid deposition or other molecular abnormalities seen in patients with Alzheimer’s disease may interfere with this network and disrupt neuronal circuits beyond the localized brain areas. Therefore, Alzheimer’s disease may be both a degenerative disease and a broader system-level disorder affecting integrated neuronal pathways involved in memory. In this paper, we describe the rationale and provide some evidence to support the study of deep brain stimulation of the hippocampal fornix as a novel treatment to improve neuronal circuitry within these integrated networks and thereby sustain memory function in early Alzheimer’s disease. PMID:23346514

The Holographic Brain: Implications for Training Design.

ERIC Educational Resources Information Center

Jones, James R.

Without special training, most people predominantly process data in one of four ways. Few achieve a coveted whole brain state that integrates such important but separate brain functions as logic and intuition. With new training techniques that exploit the holographic properties of the brain, organizations may be able to tap powerful whole brain…

Complex network analysis of brain functional connectivity under a multi-step cognitive task

NASA Astrophysics Data System (ADS)

Cai, Shi-Min; Chen, Wei; Liu, Dong-Bai; Tang, Ming; Chen, Xun

2017-01-01

Functional brain network has been widely studied to understand the relationship between brain organization and behavior. In this paper, we aim to explore the functional connectivity of brain network under a multi-step cognitive task involving consecutive behaviors, and further understand the effect of behaviors on the brain organization. The functional brain networks are constructed based on a high spatial and temporal resolution fMRI dataset and analyzed via complex network based approach. We find that at voxel level the functional brain network shows robust small-worldness and scale-free characteristics, while its assortativity and rich-club organization are slightly restricted to the order of behaviors performed. More interestingly, the functional connectivity of brain network in activated ROIs strongly correlates with behaviors and is obviously restricted to the order of behaviors performed. These empirical results suggest that the brain organization has the generic properties of small-worldness and scale-free characteristics, and its diverse functional connectivity emerging from activated ROIs is strongly driven by these behavioral activities via the plasticity of brain.

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.

Nutritional Cognitive Neuroscience: Innovations for Healthy Brain Aging.

PubMed

Zamroziewicz, Marta K; Barbey, Aron K

2016-01-01

Nutritional cognitive neuroscience is an emerging interdisciplinary field of research that seeks to understand nutrition's impact on cognition and brain health across the life span. Research in this burgeoning field demonstrates that many aspects of nutrition-from entire diets to specific nutrients-affect brain structure and function, and therefore have profound implications for understanding the nature of healthy brain aging. The aim of this Focused Review is to examine recent advances in nutritional cognitive neuroscience, with an emphasis on methods that enable discovery of nutrient biomarkers that predict healthy brain aging. We propose an integrative framework that calls for the synthesis of research in nutritional epidemiology and cognitive neuroscience, incorporating: (i) methods for the precise characterization of nutritional health based on the analysis of nutrient biomarker patterns (NBPs), along with (ii) modern indices of brain health derived from high-resolution magnetic resonance imaging (MRI). By integrating cutting-edge techniques from nutritional epidemiology and cognitive neuroscience, nutritional cognitive neuroscience will continue to advance our understanding of the beneficial effects of nutrition on the aging brain and establish effective nutritional interventions to promote healthy brain aging.

Nutritional Cognitive Neuroscience: Innovations for Healthy Brain Aging

PubMed Central

Zamroziewicz, Marta K.; Barbey, Aron K.

2016-01-01

Nutritional cognitive neuroscience is an emerging interdisciplinary field of research that seeks to understand nutrition's impact on cognition and brain health across the life span. Research in this burgeoning field demonstrates that many aspects of nutrition—from entire diets to specific nutrients—affect brain structure and function, and therefore have profound implications for understanding the nature of healthy brain aging. The aim of this Focused Review is to examine recent advances in nutritional cognitive neuroscience, with an emphasis on methods that enable discovery of nutrient biomarkers that predict healthy brain aging. We propose an integrative framework that calls for the synthesis of research in nutritional epidemiology and cognitive neuroscience, incorporating: (i) methods for the precise characterization of nutritional health based on the analysis of nutrient biomarker patterns (NBPs), along with (ii) modern indices of brain health derived from high-resolution magnetic resonance imaging (MRI). By integrating cutting-edge techniques from nutritional epidemiology and cognitive neuroscience, nutritional cognitive neuroscience will continue to advance our understanding of the beneficial effects of nutrition on the aging brain and establish effective nutritional interventions to promote healthy brain aging. PMID:27375409

Phantom limbs: pain, embodiment, and scientific advances in integrative therapies.

PubMed

Lenggenhager, Bigna; Arnold, Carolyn A; Giummarra, Melita J

2014-03-01

Research over the past two decades has begun to identify some of the key mechanisms underlying phantom limb pain and sensations; however, this continues to be a clinically challenging condition to manage. Treatment of phantom pain, like all chronic pain conditions, demands a holistic approach that takes into consideration peripheral, spinal, and central neuroplastic mechanisms. In this review, we focus on nonpharmacological treatments tailored to reverse the maladaptive neuroplasticity associated with phantom pain. Recent scientific advances emerging from interdisciplinary research between neuroscience, virtual reality, robotics, and prosthetics show the greatest promise for alternative embodiment and maintaining the integrity of the multifaceted representation of the body in the brain. Importantly, these advances have been found to prevent and reduce phantom limb pain. In particular, therapies that involve sensory and/or motor retraining, most naturally through the use of integrative prosthetic devices, as well as peripheral (e.g., transcutaneous electrical nerve stimulation) or central (e.g., transcranial magnetic stimulation or deep brain stimulation) stimulation techniques, have been found to both restore the neural representation of the missing limb and to reduce the intensity of phantom pain. While the evidence for the efficacy of these therapies is mounting, but well-controlled and large-scale studies are still needed. WIREs Cogn Sci 2014, 5:221-231. doi: 10.1002/wcs.1277 CONFLICT OF INTEREST: The authors have no financial or other relationship that might lead to a conflict of interest. For further resources related to this article, please visit the WIREs website. © 2014 John Wiley & Sons, Ltd.

Lentivector Integration Sites in Ependymal Cells From a Model of Metachromatic Leukodystrophy: Non-B DNA as a New Factor Influencing Integration

PubMed Central

McAllister, Robert G; Liu, Jiahui; Woods, Matthew W; Tom, Sean K; Rupar, C Anthony; Barr, Stephen D

2014-01-01

The blood–brain barrier controls the passage of molecules from the blood into the central nervous system (CNS) and is a major challenge for treatment of neurological diseases. Metachromatic leukodystrophy is a neurodegenerative lysosomal storage disease caused by loss of arylsulfatase A (ARSA) activity. Gene therapy via intraventricular injection of a lentiviral vector is a potential approach to rapidly and permanently deliver therapeutic levels of ARSA to the CNS. We present the distribution of integration sites of a lentiviral vector encoding human ARSA (LV-ARSA) in murine brain choroid plexus and ependymal cells, administered via a single intracranial injection into the CNS. LV-ARSA did not exhibit a strong preference for integration in or near actively transcribed genes, but exhibited a strong preference for integration in or near satellite DNA. We identified several genomic hotspots for LV-ARSA integration and identified a consensus target site sequence characterized by two G-quadruplex-forming motifs flanking the integration site. In addition, our analysis identified several other non-B DNA motifs as new factors that potentially influence lentivirus integration, including human immunodeficiency virus type-1 in human cells. Together, our data demonstrate a clinically favorable integration site profile in the murine brain and identify non-B DNA as a potential new host factor that influences lentiviral integration in murine and human cells. PMID:25158091

Brain Volume as an Integrated Marker for the Risk of Death in a Community-Based Sample: Age Gene/Environment Susceptibility--Reykjavik Study.

PubMed

Van Elderen, Saskia S G C; Zhang, Qian; Sigurdsson, Sigudur; Haight, Thaddeus J; Lopez, Oscar; Eiriksdottir, Gudny; Jonsson, Palmi; de Jong, Laura; Harris, Tamara B; Garcia, Melissa; Gudnason, Vilmundar; van Buchem, Mark A; Launer, Lenore J

2016-01-01

Total brain volume is an integrated measure of health and may be an independent indicator of mortality risk independent of any one clinical or subclinical disease state. We investigate the association of brain volume to total and cause-specific mortality in a large nondemented stroke-free community-based cohort. The analysis includes 3,543 men and women (born 1907-1935) participating in the Age, Gene, Environment Susceptibility-Reykjavik Study. Participants with a known brain-related high risk for mortality (cognitive impairment or stroke) were excluded from these analyses. Quantitative estimates of total brain volume, white matter, white matter lesions, total gray matter (GM; cortical GM and subcortical GM separately), and focal cerebral vascular disease were generated from brain magnetic resonance imaging. Brain atrophy was expressed as brain tissue volume divided by total intracranial volume, yielding a percentage. Mean follow-up duration was 7.2 (0-10) years, with 647 deaths. Cox regression was used to analyze the association of mortality to brain atrophy, adjusting for demographics, cardiovascular risk factors, and cerebral vascular disease. Reduced risk of mortality was significantly associated with higher total brain volume (hazard ratio, 95% confidence interval = 0.71, 0.65-0.78), white matter (0.85, 0.78-0.93), total GM (0.74, 0.68-0.81), and cortical GM (0.78, 0.70-0.87). Overall, the associations were similar for cardiovascular and noncardiovascular-related deaths. Independent of multiple risk factors and cerebral vascular damage, global brain volume predicts mortality in a large nondemented stroke-free community-dwelling older cohort. Total brain volume may be an integrated measure reflecting a range of health and with further investigation could be a useful clinical tool when assessing risk for mortality. Published by Oxford University Press on behalf of the Gerontological Society of America 2014.

Inter-subject FDG PET Brain Networks Exhibit Multi-scale Community Structure with Different Normalization Techniques.

PubMed

Sperry, Megan M; Kartha, Sonia; Granquist, Eric J; Winkelstein, Beth A

2018-07-01

Inter-subject networks are used to model correlations between brain regions and are particularly useful for metabolic imaging techniques, like 18F-2-deoxy-2-(18F)fluoro-D-glucose (FDG) positron emission tomography (PET). Since FDG PET typically produces a single image, correlations cannot be calculated over time. Little focus has been placed on the basic properties of inter-subject networks and if they are affected by group size and image normalization. FDG PET images were acquired from rats (n = 18), normalized by whole brain, visual cortex, or cerebellar FDG uptake, and used to construct correlation matrices. Group size effects on network stability were investigated by systematically adding rats and evaluating local network connectivity (node strength and clustering coefficient). Modularity and community structure were also evaluated in the differently normalized networks to assess meso-scale network relationships. Local network properties are stable regardless of normalization region for groups of at least 10. Whole brain-normalized networks are more modular than visual cortex- or cerebellum-normalized network (p < 0.00001); however, community structure is similar at network resolutions where modularity differs most between brain and randomized networks. Hierarchical analysis reveals consistent modules at different scales and clustering of spatially-proximate brain regions. Findings suggest inter-subject FDG PET networks are stable for reasonable group sizes and exhibit multi-scale modularity.

Spontaneous alterations of regional brain activity in patients with adult generalized anxiety disorder

PubMed Central

Xia, Likun; Li, Shumei; Wang, Tianyue; Guo, Yaping; Meng, Lihong; Feng, Yunping; Cui, Yu; Wang, Fan; Ma, Jian; Jiang, Guihua

2017-01-01

Objective We aimed to examine how spontaneous brain activity might be related to the pathophysiology of generalized anxiety disorder (GAD). Patients and methods Using resting-state functional MRI, we examined spontaneous regional brain activity in 31 GAD patients (mean age, 36.87±9.16 years) and 36 healthy control participants (mean age, 39.53±8.83 years) matched for age, education, and sex from December 2014 to October 2015. We performed a two-sample t-test on the voxel-based analysis of the regional homogeneity (ReHo) maps. We used Pearson correlation analysis to compare scores from the Hamilton Anxiety Rating Scale, Hamilton Depression Rating Scale, State–Trait Anxiety Scale-Trait Scale, and mean ReHo values. Results We found abnormal spontaneous activity in multiple regions of brain in GAD patients, especially in the sensorimotor cortex and emotional regions. GAD patients showed decreased ReHo values in the right orbital middle frontal gyrus, left anterior cingulate cortex, right middle frontal gyrus, and bilateral supplementary motor areas, with increased ReHo values in the left middle temporal gyrus, left superior temporal gyrus, and right superior occipital gyrus. The ReHo value of the left middle temporal gyrus correlated positively with the Hamilton Anxiety Rating Scale scores. Conclusion These results suggest that altered local synchronization of spontaneous brain activity may be related to the pathophysiology of GAD. PMID:28790831

Elastic and viscoelastic mechanical properties of brain tissues on the implanting trajectory of sub-thalamic nucleus stimulation.

PubMed

Li, Yan; Deng, Jianxin; Zhou, Jun; Li, Xueen

2016-11-01

Corresponding to pre-puncture and post-puncture insertion, elastic and viscoelastic mechanical properties of brain tissues on the implanting trajectory of sub-thalamic nucleus stimulation are investigated, respectively. Elastic mechanical properties in pre-puncture are investigated through pre-puncture needle insertion experiments using whole porcine brains. A linear polynomial and a second order polynomial are fitted to the average insertion force in pre-puncture. The Young's modulus in pre-puncture is calculated from the slope of the two fittings. Viscoelastic mechanical properties of brain tissues in post-puncture insertion are investigated through indentation stress relaxation tests for six interested regions along a planned trajectory. A linear viscoelastic model with a Prony series approximation is fitted to the average load trace of each region using Boltzmann hereditary integral. Shear relaxation moduli of each region are calculated using the parameters of the Prony series approximation. The results show that, in pre-puncture insertion, needle force almost increases linearly with needle displacement. Both fitting lines can perfectly fit the average insertion force. The Young's moduli calculated from the slope of the two fittings are worthy of trust to model linearly or nonlinearly instantaneous elastic responses of brain tissues, respectively. In post-puncture insertion, both region and time significantly affect the viscoelastic behaviors. Six tested regions can be classified into three categories in stiffness. Shear relaxation moduli decay dramatically in short time scales but equilibrium is never truly achieved. The regional and temporal viscoelastic mechanical properties in post-puncture insertion are valuable for guiding probe insertion into each region on the implanting trajectory.

A High-Performance Application Specific Integrated Circuit for Electrical and Neurochemical Traumatic Brain Injury Monitoring.

PubMed

Pagkalos, Ilias; Rogers, Michelle L; Boutelle, Martyn G; Drakakis, Emmanuel M

2018-05-22

This paper presents the first application specific integrated chip (ASIC) for the monitoring of patients who have suffered a Traumatic Brain Injury (TBI). By monitoring the neurophysiological (ECoG) and neurochemical (glucose, lactate and potassium) signals of the injured human brain tissue, it is possible to detect spreading depolarisations, which have been shown to be associated with poor TBI patient outcome. This paper describes the testing of a new 7.5 mm 2 ASIC fabricated in the commercially available AMS 0.35 μm CMOS technology. The ASIC has been designed to meet the demands of processing the injured brain tissue's ECoG signals, recorded by means of depth or brain surface electrodes, and neurochemical signals, recorded using microdialysis coupled to microfluidics-based electrochemical biosensors. The potentiostats use switchedcapacitor charge integration to record currents with 100 fA resolution, and allow automatic gain changing to track the falling sensitivity of a biosensor. This work supports the idea of a "behind the ear" wireless microplatform modality, which could enable the monitoring of currently non-monitored mobile TBI patients for the onset of secondary brain injury. ©2018 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Effective connectivity inferred from fMRI transition dynamics during movie viewing points to a balanced reconfiguration of cortical interactions.

PubMed

Gilson, Matthieu; Deco, Gustavo; Friston, Karl J; Hagmann, Patric; Mantini, Dante; Betti, Viviana; Romani, Gian Luca; Corbetta, Maurizio

2017-10-09

Our behavior entails a flexible and context-sensitive interplay between brain areas to integrate information according to goal-directed requirements. However, the neural mechanisms governing the entrainment of functionally specialized brain areas remain poorly understood. In particular, the question arises whether observed changes in the regional activity for different cognitive conditions are explained by modifications of the inputs to the brain or its connectivity? We observe that transitions of fMRI activity between areas convey information about the tasks performed by 19 subjects, watching a movie versus a black screen (rest). We use a model-based framework that explains this spatiotemporal functional connectivity pattern by the local variability for 66 cortical regions and the network effective connectivity between them. We find that, among the estimated model parameters, movie viewing affects to a larger extent the local activity, which we interpret as extrinsic changes related to the increased stimulus load. However, detailed changes in the effective connectivity preserve a balance in the propagating activity and select specific pathways such that high-level brain regions integrate visual and auditory information, in particular boosting the communication between the two brain hemispheres. These findings speak to a dynamic coordination underlying the functional integration in the brain. Copyright © 2017. Published by Elsevier Inc.

Permeability of ergot alkaloids across the blood-brain barrier in vitro and influence on the barrier integrity

PubMed Central

Mulac, Dennis; Hüwel, Sabine; Galla, Hans-Joachim; Humpf, Hans-Ulrich

2012-01-01

Scope Ergot alkaloids are secondary metabolites of Claviceps spp. and they have been in the focus of research for many years. Experiments focusing on ergotamine as a former migraine drug referring to the ability to reach the brain revealed controversial results. The question to which extent ergot alkaloids are able to cross the blood-brain barrier is still not answered. Methods and results In order to answer this question we have studied the ability of ergot alkaloids to penetrate the blood-brain barrier in a well established in vitro model system using primary porcine brain endothelial cells. It could clearly be demonstrated that ergot alkaloids are able to cross the blood-brain barrier in high quantities in only a few hours. We could further identify an active transport for ergometrine as a substrate for the BCRP/ABCG2 transporter. Investigations concerning barrier integrity properties have identified ergocristinine as a potent substance to accumulate in these cells ultimately leading to a weakened barrier function. Conclusion For the first time we could show that the so far as biologically inactive described 8-(S) isomers of ergot alkaloids seem to have an influence on barrier integrity underlining the necessity for a risk assessment of ergot alkaloids in food and feed. PMID:22147614

Tracking the development of brain connectivity in adolescence through a fast Bayesian integrative method

NASA Astrophysics Data System (ADS)

Zhang, Aiying; Jia, Bochao; Wang, Yu-Ping

2018-03-01

Adolescence is a transitional period between childhood and adulthood with physical changes, as well as increasing emotional activity. Studies have shown that the emotional sensitivity is related to a second dramatical brain growth. However, there is little focus on the trend of brain development during this period. In this paper, we aim to track the functional brain connectivity development in adolescence using resting state fMRI (rs-fMRI), which amounts to a time-series analysis problem. Most existing methods either require the time point to be fairly long or are only applicable to small graphs. To this end, we adapted a fast Bayesian integrative analysis (FBIA) to address the short time-series difficulty, and combined with adaptive sum of powered score (aSPU) test for group difference. The data we used are the resting state fMRI (rs-fMRI) obtained from the publicly available Philadelphia Neurodevelopmental Cohort (PNC). They include 861 individuals aged 8-22 years who were divided into five different adolescent stages. We summarized the networks with global measurements: segregation and integration, and provided full brain functional connectivity pattern in various stages of adolescence. Moreover, our research revealed several brain functional modules development trends. Our results are shown to be both statistically and biologically significant.

Altered blood-brain barrier permeability in rats with prehepatic portal hypertension turns to normal when portal pressure is lowered

PubMed Central

Eizayaga, Francisco; Scorticati, Camila; Prestifilippo, Juan P; Romay, Salvador; Fernandez, Maria A; Castro, José L; Lemberg, Abraham; Perazzo, Juan C

2006-01-01

AIM: To study the blood-brain barrier integrity in prehepatic portal hypertensive rats induced by partial portal vein ligation, at 14 and 40 d after ligation when portal pressure is spontaneously normalized. METHODS: Adult male Wistar rats were divided into four groups: Group I: Sham14d , sham operated; Group II: PH14d , portal vein stenosis; (both groups were used 14 days after surgery); Group III: Sham40d, Sham operated and Group IV: PH40d Portal vein stenosis (Groups II and IV used 40 d after surgery). Plasma ammonia, plasma and cerebrospinal fluid protein and liver enzymes concentrations were determined. Trypan and Evans blue dyes, systemically injected, were investigated in hippocampus to study blood-brain barrier integrity. Portal pressure was periodically recorded. RESULTS: Forty days after stricture, portal pressure was normalized, plasma ammonia was moderately high, and both dyes were absent in central nervous system parenchyma. All other parameters were reestablished. When portal pressure was normalized and ammonia level was lowered, but not normal, the altered integrity of blood-brain barrier becomes reestablished. CONCLUSION: The impairment of blood-brain barrier and subsequent normalization could be a mechanism involved in hepatic encephalopathy reversibility. Hemodynamic changes and ammonia could trigger blood-brain barrier alterations and its reestablishment. PMID:16552803

Changes in aspects of social functioning depend upon prior changes in neurodisability in people with acquired brain injury undergoing post-acute neurorehabilitation.

PubMed

Fortune, Dónal G; Walsh, R Stephen; Waldron, Brian; McGrath, Caroline; Harte, Maurice; Casey, Sarah; McClean, Brian

2015-01-01

Post-acute community-based rehabilitation is effective in reducing disability. However, while social participation and quality of life are valued as distal outcomes of neurorehabilitation, it is often not possible to observe improvements on these outcomes within the limited time-frames used in most investigations of rehabilitation. The aim of the current study was to examine differences in the sequence of attainments for people with acquired brain injury (ABI) undergoing longer term post-acute neurorehabilitation. Participants with ABI who were referred to comprehensive home and community-based neurorehabilitation were assessed at induction to service, at 6 months and again at 1.5 years while still in service on the Mayo-Portland Adaptability Index (MPAI-4), Community Integration Questionnaire, Hospital Anxiety and Depression Scale, and World Health Organisation Quality of Life measure. At 6 months post-induction to service, significant differences were evident in MPAI abilities, adjustment, and total neurodisability; and in anxiety and depression. By contrast, there was no significant effect at 6 months on more socially oriented features of experience namely quality of life (QoL), Community Integration and Participation. Eighteen month follow-up showed continuation of the significant positive effects with the addition of QoL-related to physical health, Psychological health, Social aspects of QoL and Participation at this later time point. Regression analyses demonstrated that change in QoL and Participation were dependent upon prior changes in aspects of neurodisability. Age, severity or type of brain injury did not significantly affect outcome. Results suggest that different constructs may respond to neurorehabilitation at different time points in a dose effect manner, and that change in social aspects of experience may be dependent upon the specific nature of prior neurorehabilitation attainments.

Multi-timescale modeling of activity-dependent metabolic coupling in the neuron-glia-vasculature ensemble.

PubMed

Jolivet, Renaud; Coggan, Jay S; Allaman, Igor; Magistretti, Pierre J

2015-02-01

Glucose is the main energy substrate in the adult brain under normal conditions. Accumulating evidence, however, indicates that lactate produced in astrocytes (a type of glial cell) can also fuel neuronal activity. The quantitative aspects of this so-called astrocyte-neuron lactate shuttle (ANLS) are still debated. To address this question, we developed a detailed biophysical model of the brain's metabolic interactions. Our model integrates three modeling approaches, the Buxton-Wang model of vascular dynamics, the Hodgkin-Huxley formulation of neuronal membrane excitability and a biophysical model of metabolic pathways. This approach provides a template for large-scale simulations of the neuron-glia-vasculature (NGV) ensemble, and for the first time integrates the respective timescales at which energy metabolism and neuronal excitability occur. The model is constrained by relative neuronal and astrocytic oxygen and glucose utilization, by the concentration of metabolites at rest and by the temporal dynamics of NADH upon activation. These constraints produced four observations. First, a transfer of lactate from astrocytes to neurons emerged in response to activity. Second, constrained by activity-dependent NADH transients, neuronal oxidative metabolism increased first upon activation with a subsequent delayed astrocytic glycolysis increase. Third, the model correctly predicted the dynamics of extracellular lactate and oxygen as observed in vivo in rats. Fourth, the model correctly predicted the temporal dynamics of tissue lactate, of tissue glucose and oxygen consumption, and of the BOLD signal as reported in human studies. These findings not only support the ANLS hypothesis but also provide a quantitative mathematical description of the metabolic activation in neurons and glial cells, as well as of the macroscopic measurements obtained during brain imaging.

Transformational electronics: a powerful way to revolutionize our information world

NASA Astrophysics Data System (ADS)

Rojas, Jhonathan P.; Torres Sevilla, Galo A.; Ghoneim, Mohamed T.; Hussain, Aftab M.; Ahmed, Sally M.; Nassar, Joanna M.; Bahabry, Rabab R.; Nour, Maha; Kutbee, Arwa T.; Byas, Ernesto; Al-Saif, Bidoor; Alamri, Amal M.; Hussain, Muhammad M.

2014-06-01

With the emergence of cloud computation, we are facing the rising waves of big data. It is our time to leverage such opportunity by increasing data usage both by man and machine. We need ultra-mobile computation with high data processing speed, ultra-large memory, energy efficiency and multi-functionality. Additionally, we have to deploy energy-efficient multi-functional 3D ICs for robust cyber-physical system establishment. To achieve such lofty goals we have to mimic human brain, which is inarguably the world's most powerful and energy efficient computer. Brain's cortex has folded architecture to increase surface area in an ultra-compact space to contain its neuron and synapses. Therefore, it is imperative to overcome two integration challenges: (i) finding out a low-cost 3D IC fabrication process and (ii) foldable substrates creation with ultra-large-scale-integration of high performance energy efficient electronics. Hence, we show a low-cost generic batch process based on trench-protect-peel-recycle to fabricate rigid and flexible 3D ICs as well as high performance flexible electronics. As of today we have made every single component to make a fully flexible computer including non-planar state-of-the-art FinFETs. Additionally we have demonstrated various solid-state memory, movable MEMS devices, energy harvesting and storage components. To show the versatility of our process, we have extended our process towards other inorganic semiconductor substrates such as silicon germanium and III-V materials. Finally, we report first ever fully flexible programmable silicon based microprocessor towards foldable brain computation and wirelessly programmable stretchable and flexible thermal patch for pain management for smart bionics.

Changes in aspects of social functioning depend upon prior changes in neurodisability in people with acquired brain injury undergoing post-acute neurorehabilitation

PubMed Central

Fortune, Dónal G.; Walsh, R. Stephen; Waldron, Brian; McGrath, Caroline; Harte, Maurice; Casey, Sarah; McClean, Brian

2015-01-01

Post-acute community-based rehabilitation is effective in reducing disability. However, while social participation and quality of life are valued as distal outcomes of neurorehabilitation, it is often not possible to observe improvements on these outcomes within the limited time-frames used in most investigations of rehabilitation. The aim of the current study was to examine differences in the sequence of attainments for people with acquired brain injury (ABI) undergoing longer term post-acute neurorehabilitation. Participants with ABI who were referred to comprehensive home and community-based neurorehabilitation were assessed at induction to service, at 6 months and again at 1.5 years while still in service on the Mayo-Portland Adaptability Index (MPAI-4), Community Integration Questionnaire, Hospital Anxiety and Depression Scale, and World Health Organisation Quality of Life measure. At 6 months post-induction to service, significant differences were evident in MPAI abilities, adjustment, and total neurodisability; and in anxiety and depression. By contrast, there was no significant effect at 6 months on more socially oriented features of experience namely quality of life (QoL), Community Integration and Participation. Eighteen month follow-up showed continuation of the significant positive effects with the addition of QoL-related to physical health, Psychological health, Social aspects of QoL and Participation at this later time point. Regression analyses demonstrated that change in QoL and Participation were dependent upon prior changes in aspects of neurodisability. Age, severity or type of brain injury did not significantly affect outcome. Results suggest that different constructs may respond to neurorehabilitation at different time points in a dose effect manner, and that change in social aspects of experience may be dependent upon the specific nature of prior neurorehabilitation attainments. PMID:26441744

Structural Integrity of Normal Appearing White Matter and Sex-Specific Outcomes After Acute Ischemic Stroke.

PubMed

Etherton, Mark R; Wu, Ona; Cougo, Pedro; Giese, Anne-Katrin; Cloonan, Lisa; Fitzpatrick, Kaitlin M; Kanakis, Allison S; Boulouis, Gregoire; Karadeli, Hasan H; Lauer, Arne; Rosand, Jonathan; Furie, Karen L; Rost, Natalia S

2017-12-01

Women have worse poststroke outcomes than men. We evaluated sex-specific clinical and neuroimaging characteristics of white matter in association with functional recovery after acute ischemic stroke. We performed a retrospective analysis of acute ischemic stroke patients with admission brain MRI and 3- to 6-month modified Rankin Scale score. White matter hyperintensity and acute infarct volume were quantified on fluid-attenuated inversion recovery and diffusion tensor imaging MRI, respectively. Diffusivity anisotropy metrics were calculated in normal appearing white matter contralateral to the acute ischemia. Among 319 patients with acute ischemic stroke, women were older (68.0 versus 62.7 years; P =0.004), had increased incidence of atrial fibrillation (21.4% versus 12.2%; P =0.04), and lower rate of tobacco use (21.1% versus 35.9%; P =0.03). There was no sex-specific difference in white matter hyperintensity volume, acute infarct volume, National Institutes of Health Stroke Scale, prestroke modified Rankin Scale score, or normal appearing white matter diffusivity anisotropy metrics. However, women were less likely to have an excellent outcome (modified Rankin Scale score <2: 49.6% versus 67.0%; P =0.005). In logistic regression analysis, female sex and the interaction of sex with fractional anisotropy, radial diffusivity, and axial diffusivity were independent predictors of functional outcome. Female sex is associated with decreased likelihood of excellent outcome after acute ischemic stroke. The correlation between markers of white matter integrity and functional outcomes in women, but not men, suggests a potential sex-specific mechanism. © 2017 American Heart Association, Inc.

Which brain networks related to art perception are we talking about?. Comment on "Move me, astonish me…" delight my eyes and brain: The Vienna Integrated Model of top-down and bottom-up processes in Art Perception (VIMAP) and corresponding affective, evaluative, and neurophysiological correlates; by Matthew Pelowski et al.

NASA Astrophysics Data System (ADS)

Ayala, Francisco J.; Cela-Conde, Camilo J.

2017-07-01

The proposal by the Vienna Integrated Model of Art Perception (Pelowski et al., [4]; VIMAP, hereafter) is a valuable and much needed attempt to summarize and understand the cognitive processes underlying art perception. Very important in their model is, as expected, to ascertain the psychological and brain processes correlated with the perception of beauty in art works. In this commentary we'll focus exclusively on the consideration of VIMAP's section 5, ;Model stages and corresponding areas of the brain.; We'll examine the evidence advanced by VIMAP in the section about brain networks related to the perception of art.

Reliability of the Client-Centeredness of Goal Setting (C-COGS) Scale in Acquired Brain Injury Rehabilitation.

PubMed

Doig, Emmah; Prescott, Sarah; Fleming, Jennifer; Cornwell, Petrea; Kuipers, Pim

2016-01-01

To examine the internal reliability and test-retest reliability of the Client-Centeredness of Goal Setting (C-COGS) scale. The C-COGS scale was administered to 42 participants with acquired brain injury after completion of multidisciplinary goal planning. Internal reliability of scale items was examined using item-partial total correlations and Cronbach's α coefficient. The scale was readministered within a 1-mo period to a subsample of 12 participants to examine test-retest reliability by calculating exact and close percentage agreement for each item. After examination of item-partial total correlations, test items were revised. The revised items demonstrated stronger internal consistency than the original items. Preliminary evaluation of test-retest reliability was fair, with an average exact percent agreement across all test items of 67%. Findings support the preliminary reliability of the C-COGS scale as a tool to evaluate and promote client-centered goal planning in brain injury rehabilitation. Copyright © 2016 by the American Occupational Therapy Association, Inc.

Brain pathology after mild traumatic brain injury: an exploratory study by repeated magnetic resonance examination.

PubMed

Lannsjö, Marianne; Raininko, Raili; Bustamante, Mariana; von Seth, Charlotta; Borg, Jörgen

2013-09-01

To explore brain pathology after mild traumatic brain injury by repeated magnetic resonance examination. A prospective follow-up study. Nineteen patients with mild traumatic brain injury presenting with Glasgow Coma Scale (GCS) 14-15. The patients were examined on day 2 or 3 and 3-7 months after the injury. The magnetic resonance protocol comprised conventional T1- and T2-weighted sequences including fluid attenuated inversion recovery (FLAIR), two susceptibility-weighted sequences to reveal haemorrhages, and diffusion-weighted sequences. Computer-aided volume comparison was performed. Clinical outcome was assessed by the Rivermead Post-Concussion Symptoms Questionnaire (RPQ), Hospital Anxiety and Depression Scale (HADS) and Glasgow Outcome Scale Extended (GOSE). At follow-up, 7 patients (37%) reported ≥  3 symptoms in RPQ, 5 reported some anxiety and 1 reported mild depression. Fifteen patients reported upper level of good recovery and 4 patients lower level of good recovery (GOSE 8 and 7, respectively). Magnetic resonance pathology was found in 1 patient at the first examination, but 4 patients (21%) showed volume loss at the second examination, at which 3 of them reported < 3 symptoms and 1 ≥ 3 symptoms, all exhibiting GOSE scores of 8. Loss of brain volume, demonstrated by computer-aided magnetic resonance imaging volumetry, may be a feasible marker of brain pathology after mild traumatic brain injury.

Automatic Brain Portion Segmentation From Magnetic Resonance Images of Head Scans Using Gray Scale Transformation and Morphological Operations.

PubMed

Somasundaram, Karuppanagounder; Ezhilarasan, Kamalanathan

2015-01-01

To develop an automatic skull stripping method for magnetic resonance imaging (MRI) of human head scans. The proposed method is based on gray scale transformation and morphological operations. The proposed method has been tested with 20 volumes of normal T1-weighted images taken from Internet Brain Segmentation Repository. Experimental results show that the proposed method gives better results than the popular skull stripping methods Brain Extraction Tool and Brain Surface Extractor. The average value of Jaccard and Dice coefficients are 0.93 and 0.962 respectively. In this article, we have proposed a novel skull stripping method using intensity transformation and morphological operations. This is a low computational complexity method but gives competitive or better results than that of the popular skull stripping methods Brain Surface Extractor and Brain Extraction Tool.

Successful tactile based visual sensory substitution use functions independently of visual pathway integrity

PubMed Central

Lee, Vincent K.; Nau, Amy C.; Laymon, Charles; Chan, Kevin C.; Rosario, Bedda L.; Fisher, Chris

2014-01-01

Purpose: Neuronal reorganization after blindness is of critical interest because it has implications for the rational prescription of artificial vision devices. The purpose of this study was to distinguish the microstructural differences between perinatally blind (PB), acquired blind (AB), and normally sighted controls (SCs) and relate these differences to performance on functional tasks using a sensory substitution device (BrainPort). Methods: We enrolled 52 subjects (PB n = 11; AB n = 35; SC n = 6). All subjects spent 15 h undergoing BrainPort device training. Outcomes of light perception, motion, direction, temporal resolution, grating, and acuity were tested at baseline and after training. Twenty-six of the subjects were scanned with a three Tesla MRI scanner for diffusion tensor imaging (DTI), and with a positron emission tomography (PET) scanner for mapping regional brain glucose consumption during sensory substitution function. Non-parametric models were used to analyze fractional anisotropy (FA; a DTI measure of microstructural integrity) of the brain via region-of-interest (ROI) analysis and tract-based spatial statistics (TBSS). Results: At baseline, all subjects performed all tasks at chance level. After training, light perception, time resolution, location and grating acuity tasks improved significantly for all subject groups. ROI and TBSS analyses of FA maps show areas of statistically significant differences (p ≤ 0.025) in the bilateral optic radiations and some visual association connections between all three groups. No relationship was found between FA and functional performance with the BrainPort. Discussion: All subjects showed performance improvements using the BrainPort irrespective of nature and duration of blindness. Definite brain areas with significant microstructural integrity changes exist among PB, AB, and NC, and these variations are most pronounced in the visual pathways. However, the use of sensory substitution devices is feasible irrespective of microstructural integrity of the primary visual pathways between the eye and the brain. Therefore, tongue based devices devices may be usable for a broad array of non-sighted patients. PMID:24860473

Notch3 is necessary for blood vessel integrity in the central nervous system.

PubMed

Henshall, Tanya L; Keller, Annika; He, Liqun; Johansson, Bengt R; Wallgard, Elisabet; Raschperger, Elisabeth; Mäe, Maarja Andaloussi; Jin, Shaobo; Betsholtz, Christer; Lendahl, Urban

2015-02-01

Vascular smooth muscle cells (VSMC) are important for contraction, blood flow distribution, and regulation of blood vessel diameter, but to what extent they contribute to the integrity of blood vessels and blood-brain barrier function is less well understood. In this report, we explored the impact of the loss of VSMC in the Notch3(-/-) mouse on blood vessel integrity in the central nervous system. Notch3(-/-) mice showed focal disruptions of the blood-brain barrier demonstrated by extravasation of tracers accompanied by fibrin deposition in the retinal vasculature. This blood-brain barrier leakage was accompanied by a regionalized and patchy loss of VSMC, with VSMC gaps predominantly in arterial resistance vessels of larger caliber. The loss of VSMC appeared to be caused by progressive degeneration of VSMC resulting in a gradual loss of VSMC marker expression and a progressive acquisition of an aberrant VSMC phenotype closer to the gaps, followed by enhanced apoptosis and cellular disintegration in the gaps. Arterial VSMC were the only mural cell type that was morphologically affected, despite Notch3 also being expressed in pericytes. Transcriptome analysis of isolated brain microvessels revealed gene expression changes in Notch3(-/-) mice consistent with loss of arterial VSMC and presumably secondary transcriptional changes were observed in endothelial genes, which may explain the compromised vascular integrity. We demonstrate that Notch3 is important for survival of VSMC, and reveal a critical role for Notch3 and VSMC in blood vessel integrity and blood-brain barrier function in the mammalian vasculature. © 2014 American Heart Association, Inc.

Cellular scaling rules for the brain of afrotherians

PubMed Central

Neves, Kleber; Ferreira, Fernanda M.; Tovar-Moll, Fernanda; Gravett, Nadine; Bennett, Nigel C.; Kaswera, Consolate; Gilissen, Emmanuel; Manger, Paul R.; Herculano-Houzel, Suzana

2014-01-01

Quantitative analysis of the cellular composition of rodent, primate and eulipotyphlan brains has shown that non-neuronal scaling rules are similar across these mammalian orders that diverged about 95 million years ago, and therefore appear to be conserved in evolution, while neuronal scaling rules appear to be free to vary in evolution in a clade-specific manner. Here we analyze the cellular scaling rules that apply to the brain of afrotherians, believed to be the first clade to radiate from the common eutherian ancestor. We find that afrotherians share non-neuronal scaling rules with rodents, primates and eulipotyphlans, as well as the coordinated scaling of numbers of neurons in the cerebral cortex and cerebellum. Afrotherians share with rodents and eulipotyphlans, but not with primates, the scaling of number of neurons in the cortex and in the cerebellum as a function of the number of neurons in the rest of the brain. Afrotheria also share with rodents and eulipotyphlans the neuronal scaling rules that apply to the cerebral cortex. Afrotherians share with rodents, but not with eulipotyphlans nor primates, the neuronal scaling rules that apply to the cerebellum. Importantly, the scaling of the folding index of the cerebral cortex with the number of neurons in the cerebral cortex is not shared by either afrotherians, rodents, or primates. The sharing of some neuronal scaling rules between afrotherians and rodents, and of some additional features with eulipotyphlans and primates, raise the interesting possibility that these shared characteristics applied to the common eutherian ancestor. In turn, the clade-specific characteristics that relate to the distribution of neurons along the surface of the cerebral cortex and to its degree of gyrification suggest that these characteristics compose an evolutionarily plastic suite of features that may have defined and distinguished mammalian groups in evolution. PMID:24596544

Penetrating the Blood-Brain Barrier: Promise of Novel Nanoplatforms and Delivery Vehicles.

PubMed

Ali, Iqbal Unnisa; Chen, Xiaoyuan

2015-10-27

Multifunctional nanoplatforms combining versatile therapeutic modalities with a variety of imaging options have the potential to diagnose, monitor, and treat brain diseases. The promise of nanotechnology can only be realized by the simultaneous development of innovative brain-targeting delivery vehicles capable of penetrating the blood-brain barrier without compromising its structural integrity.

Integrated and Contextual Basic Science Instruction in Preclinical Education: Problem-Based Learning Experience Enriched with Brain/Mind Learning Principles

ERIC Educational Resources Information Center

Gülpinar, Mehmet Ali; Isoglu-Alkaç, Ümmühan; Yegen, Berrak Çaglayan

2015-01-01

Recently, integrated and contextual learning models such as problem-based learning (PBL) and brain/mind learning (BML) have become prominent. The present study aimed to develop and evaluate a PBL program enriched with BML principles. In this study, participants were 295 first-year medical students. The study used both quantitative and qualitative…

The Dynamics of Integration and Separation: ERP, MEG, and Neural Network Studies of Immediate Repetition Effects

ERIC Educational Resources Information Center

Huber, David E.; Tian, Xing; Curran, Tim; O'Reilly, Randall C.; Woroch, Brion

2008-01-01

This article presents data and theory concerning the fundamental question of how the brain achieves a balance between integrating and separating perceptual information over time. This theory was tested in the domain of word reading by examining brain responses to briefly presented words that were either new or immediate repetitions. Critically,…

Cognitive reserve and preinjury educational attainment: effects on outcome of community-based rehabilitation for longer-term individuals with acquired brain injury.

PubMed

Fortune, Dónal G; Walsh, R Stephen; Richards, Helen L

2016-09-01

The cognitive reserve hypothesis has been proposed to account for the mismatch between brain pathology and its clinical expression. The aim of the current research was to explore, in a longitudinal data set, the effects of level of educational attainment before brain injury (cognitive reserve) and clinical factors on the level of rehabilitation-induced changes in disability and community integration. Participants in receipt of postacute rehabilitation were assessed at induction to the service and again at between 14 and 18 months of follow-up while still in service on changes in aspects of their abilities, adjustment and participation (Mayo Portland Adaptability Indices) and community integration (Community Integration Questionnaire). Controlling for type and severity of injury, age at onset of injury and duration of time since injury, participants with higher previous educational attainment showed significantly greater changes over the course of rehabilitation on adjustment to their injury and participation, but not on abilities, or community integration following postacute rehabilitation. Level of education would appear to be an important element of cognitive reserve in brain injury that serves to aid responses to postacute rehabilitation in terms of an individual's adjustment to disability and participation.

Multi-sensory integration in a small brain

NASA Astrophysics Data System (ADS)

Gepner, Ruben; Wolk, Jason; Gershow, Marc

Understanding how fluctuating multi-sensory stimuli are integrated and transformed in neural circuits has proved a difficult task. To address this question, we study the sensori-motor transformations happening in the brain of the Drosophila larva, a tractable model system with about 10,000 neurons. Using genetic tools that allow us to manipulate the activity of individual brain cells through their transparent body, we observe the stochastic decisions made by freely-behaving animals as their visual and olfactory environments fluctuate independently. We then use simple linear-nonlinear models to correlate outputs with relevant features in the inputs, and adaptive filtering processes to track changes in these relevant parameters used by the larva's brain to make decisions. We show how these techniques allow us to probe how statistics of stimuli from different sensory modalities combine to affect behavior, and can potentially guide our understanding of how neural circuits are anatomically and functionally integrated. Supported by NIH Grant 1DP2EB022359 and NSF Grant PHY-1455015.

Speed of perceptual grouping in acquired brain injury.

PubMed

Kurylo, Daniel D; Larkin, Gabriella Brick; Waxman, Richard; Bukhari, Farhan

2014-09-01

Evidence exists that damage to white matter connections may contribute to reduced speed of information processing in traumatic brain injury and stroke. Damage to such axonal projections suggests a particular vulnerability to functions requiring integration across cortical sites. To test this prediction, measurements were made of perceptual grouping, which requires integration of stimulus components. A group of traumatic brain injury and cerebral vascular accident patients and a group of age-matched healthy control subjects viewed arrays of dots and indicated the pattern into which stimuli were perceptually grouped. Psychophysical measurements were made of perceptual grouping as well as processing speed. The patient group showed elevated grouping thresholds as well as extended processing time. In addition, most patients showed progressive slowing of processing speed across levels of difficulty, suggesting reduced resources to accommodate increased demands on grouping. These results support the prediction that brain injury results in a particular vulnerability to functions requiring integration of information across the cortex, which may result from dysfunction of long-range axonal connection.

Measurement of plantarflexor spasticity in traumatic brain injury: correlational study of resistance torque compared with the modified Ashworth scale.

PubMed

Annaswamy, Thiru; Mallempati, Srinivas; Allison, Stephen C; Abraham, Lawrence D

2007-05-01

To examine the usefulness of a biomechanical measure, resistance torque (RT), in quantifying spasticity by comparing its use with a clinical scale, the modified Ashworth scale (MAS), and quantitative electrophysiological measures. This is a correlational study of spasticity measurements in 34 adults with traumatic brain injury and plantarflexor spasticity. Plantarflexor spasticity was measured in the seated position before and after cryotherapy using the MAS and also by strapping each subject's foot and ankle to an apparatus that provided a ramp and hold stretch. The quantitative measures were (1) reflex threshold angle (RTA) calculated through electromyographic signals and joint angle traces, (2) Hdorsiflexion (Hdf)/Hcontrol (Hctrl) amplitude ratio obtained through reciprocal inhibition of the soleus H-reflex, (3) Hvibration (Hvib)/Hctrl ratio obtained through vibratory inhibition of the soleus H-reflex, and (4) RT calculated as the time integral of the torque graph between the starting and ending pulses of the stretch. Correlation coefficients between RT and MAS scores in both pre-ice (0.41) and post-ice trials (0.42) were fair (P = 0.001). The correlation coefficients between RT scores and RTA scores in both the pre-ice (0.66) and post-ice trials (0.75) were moderate (P

Decreased integration and information capacity in stroke measured by whole brain models of resting state activity.

PubMed

Adhikari, Mohit H; Hacker, Carl D; Siegel, Josh S; Griffa, Alessandra; Hagmann, Patric; Deco, Gustavo; Corbetta, Maurizio

2017-04-01

While several studies have shown that focal lesions affect the communication between structurally normal regions of the brain, and that these changes may correlate with behavioural deficits, their impact on brain's information processing capacity is currently unknown. Here we test the hypothesis that focal lesions decrease the brain's information processing capacity, of which changes in functional connectivity may be a measurable correlate. To measure processing capacity, we turned to whole brain computational modelling to estimate the integration and segregation of information in brain networks. First, we measured functional connectivity between different brain areas with resting state functional magnetic resonance imaging in healthy subjects (n = 26), and subjects who had suffered a cortical stroke (n = 36). We then used a whole-brain network model that coupled average excitatory activities of local regions via anatomical connectivity. Model parameters were optimized in each healthy or stroke participant to maximize correlation between model and empirical functional connectivity, so that the model's effective connectivity was a veridical representation of healthy or lesioned brain networks. Subsequently, we calculated two model-based measures: 'integration', a graph theoretical measure obtained from functional connectivity, which measures the connectedness of brain networks, and 'information capacity', an information theoretical measure that cannot be obtained empirically, representative of the segregative ability of brain networks to encode distinct stimuli. We found that both measures were decreased in stroke patients, as compared to healthy controls, particularly at the level of resting-state networks. Furthermore, we found that these measures, especially information capacity, correlate with measures of behavioural impairment and the segregation of resting-state networks empirically measured. This study shows that focal lesions affect the brain's ability to represent stimuli and task states, and that information capacity measured through whole brain models is a theory-driven measure of processing capacity that could be used as a biomarker of injury for outcome prediction or target for rehabilitation intervention. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Aortic stiffness is associated with white matter integrity in patients with type 1 diabetes.

PubMed

Tjeerdema, Nathanja; Van Schinkel, Linda D; Westenberg, Jos J; Van Elderen, Saskia G; Van Buchem, Mark A; Smit, Johannes W; Van der Grond, Jeroen; De Roos, Albert

2014-09-01

To assess the association between aortic pulse wave velocity (PWV) as a marker of arterial stiffness and diffusion tensor imaging of brain white matter integrity in patients with type 1 diabetes using advanced magnetic resonance imaging (MRI) technology. Forty-one patients with type 1 diabetes (23 men, mean age 44 ± 12 years, mean diabetes duration 24 ± 13 years) were included. Aortic PWV was assessed using through-plane velocity-encoded MRI. Brain diffusion tensor imaging (DTI) measurements were performed on 3-T MRI. Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) were calculated for white and grey matter integrity. Pearson correlation and multivariable linear regression analyses including cardiovascular risk factors as covariates were assessed. Multivariable linear regression analyses revealed that aortic PWV is independently associated with white matter integrity FA (β = -0.777, p = 0.008) in patients with type 1 diabetes. This effect was independent of age, gender, mean arterial pressure, body mass index, smoking, duration of diabetes and glycated haemoglobin levels. Aortic PWV was not significantly related to grey matter integrity. Our data suggest that aortic stiffness is independently associated with reduced white matter integrity in patients with type 1 diabetes. Aortic stiffness is associated with brain injury. Aortic stiffness exposes small vessels to high pressure fluctuations and flow. Aortic stiffness is associated with microvascular brain injury in diabetes. This suggests a vascular contribution to early subtle microstructural deficits.

Human development XIII: the connection between the structure of the overtone system and the tone language of music. Some implications for our understanding of the human brain.

PubMed

Ventegodt, Søren; Hermansen, Tyge Dahl; Kandel, Isack; Merrick, Joav

2008-07-13

The functioning brain behaves like one highly-structured, coherent, informational field. It can be popularly described as a "coherent ball of energy", making the idea of a local highly-structured quantum field that carries the consciousness very appealing. If that is so, the structure of the experience of music might be a quite unique window into a hidden quantum reality of the brain, and even of life itself. The structure of music is then a mirror of a much more complex, but similar, structure of the energetic field of the working brain. This paper discusses how the perception of music is organized in the human brain with respect to the known tone scales of major and minor. The patterns used by the brain seem to be similar to the overtones of vibrating matter, giving a positive experience of harmonies in major. However, we also like the minor scale, which can explain brain patterns as fractal-like, giving a symmetric "downward reflection" of the major scale into the minor scale. We analyze the implication of beautiful and ugly tones and harmonies for the model. We conclude that when it comes to simple perception of harmonies, the most simple is the most beautiful and the most complex is the most ugly, but in music, even the most disharmonic harmony can be beautiful, if experienced as a part of a dynamic release of musical tension. This can be taken as a general metaphor of painful, yet meaningful, and developing experiences in human life.