Allostasis and the human brain: Integrating models of stress from the social and life sciences

PubMed Central

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

2009-01-01

We draw on the theory of allostasis to develop an integrative model of the current stress process that highlights the brain as a dynamically adapting interface between the changing environment and the biological self. We review evidence that the core emotional regions of the brain constitute the primary mediator of the well-established association between stress and health, as well as the neural focus of “wear and tear” due to ongoing adaptation. This mediation, in turn, allows us to model the interplay over time between context, current stressor exposure, internal regulation of bodily processes, and health outcomes. We illustrate how this approach facilitates the integration of current findings in human neuroscience and genetics with key constructs from stress models from the social and life sciences, with implications for future research and the design of interventions targeting individuals at risk. PMID:20063966

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.

Psychophysiological correlates of aggression and violence: an integrative review.

PubMed

Patrick, Christopher J

2008-08-12

This paper reviews existing psychophysiological studies of aggression and violent behaviour including research employing autonomic, electrocortical and neuroimaging measures. Robust physiological correlates of persistent aggressive behaviour evident in this literature include low baseline heart rate, enhanced autonomic reactivity to stressful or aversive stimuli, enhanced EEG slow wave activity, reduced P300 brain potential response and indications from structural and functional neuroimaging studies of dysfunction in frontocortical and limbic brain regions that mediate emotional processing and regulation. The findings are interpreted within a conceptual framework that draws on two integrative models in the literature. The first is a recently developed hierarchical model of impulse control (externalizing) problems, in which various disinhibitory syndromes including aggressive and addictive behaviours of different kinds are seen as arising from common as well as distinctive aetiologic factors. This model represents an approach to organizing these various interrelated phenotypes and investigating their common and distinctive aetiologic substrates. The other is a neurobiological model that posits impairments in affective regulatory circuits in the brain as a key mechanism for impulsive aggressive behaviour. This model provides a perspective for integrating findings from studies employing different measures that have implicated varying brain structures and physiological systems in violent and aggressive behaviour.

In vitro models and systems for evaluating the dynamics of drug delivery to the healthy and diseased brain.

PubMed

Modarres, Hassan Pezeshgi; Janmaleki, Mohsen; Novin, Mana; Saliba, John; El-Hajj, Fatima; RezayatiCharan, Mahdi; Seyfoori, Amir; Sadabadi, Hamid; Vandal, Milène; Nguyen, Minh Dang; Hasan, Anwarul; Sanati-Nezhad, Amir

2018-03-10

The blood-brain barrier (BBB) plays a crucial role in maintaining brain homeostasis and transport of drugs to the brain. The conventional animal and Transwell BBB models along with emerging microfluidic-based BBB-on-chip systems have provided fundamental functionalities of the BBB and facilitated the testing of drug delivery to the brain tissue. However, developing biomimetic and predictive BBB models capable of reasonably mimicking essential characteristics of the BBB functions is still a challenge. In addition, detailed analysis of the dynamics of drug delivery to the healthy or diseased brain requires not only biomimetic BBB tissue models but also new systems capable of monitoring the BBB microenvironment and dynamics of barrier function and delivery mechanisms. This review provides a comprehensive overview of recent advances in microengineering of BBB models with different functional complexity and mimicking capability of healthy and diseased states. It also discusses new technologies that can make the next generation of biomimetic human BBBs containing integrated biosensors for real-time monitoring the tissue microenvironment and barrier function and correlating it with the dynamics of drug delivery. Such integrated system addresses important brain drug delivery questions related to the treatment of brain diseases. We further discuss how the combination of in vitro BBB systems, computational models and nanotechnology supports for characterization of the dynamics of drug delivery to the brain. Copyright © 2018 Elsevier B.V. All rights reserved.

Cross-entropy optimization for neuromodulation.

PubMed

Brar, Harleen K; Yunpeng Pan; Mahmoudi, Babak; Theodorou, Evangelos A

2016-08-01

This study presents a reinforcement learning approach for the optimization of the proportional-integral gains of the feedback controller represented in a computational model of epilepsy. The chaotic oscillator model provides a feedback control systems view of the dynamics of an epileptic brain with an internal feedback controller representative of the natural seizure suppression mechanism within the brain circuitry. Normal and pathological brain activity is simulated in this model by adjusting the feedback gain values of the internal controller. With insufficient gains, the internal controller cannot provide enough feedback to the brain dynamics causing an increase in correlation between different brain sites. This increase in synchronization results in the destabilization of the brain dynamics, which is representative of an epileptic seizure. To provide compensation for an insufficient internal controller an external controller is designed using proportional-integral feedback control strategy. A cross-entropy optimization algorithm is applied to the chaotic oscillator network model to learn the optimal feedback gains for the external controller instead of hand-tuning the gains to provide sufficient control to the pathological brain and prevent seizure generation. The correlation between the dynamics of neural activity within different brain sites is calculated for experimental data to show similar dynamics of epileptic neural activity as simulated by the network of chaotic oscillators.

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

PubMed

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

2018-05-10

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

A Culture-Behavior-Brain Loop Model of Human Development.

PubMed

Han, Shihui; Ma, Yina

2015-11-01

Increasing evidence suggests that cultural influences on brain activity are associated with multiple cognitive and affective processes. These findings prompt an integrative framework to account for dynamic interactions between culture, behavior, and the brain. We put forward a culture-behavior-brain (CBB) loop model of human development that proposes that culture shapes the brain by contextualizing behavior, and the brain fits and modifies culture via behavioral influences. Genes provide a fundamental basis for, and interact with, the CBB loop at both individual and population levels. The CBB loop model advances our understanding of the dynamic relationships between culture, behavior, and the brain, which are crucial for human phylogeny and ontogeny. Future brain changes due to cultural influences are discussed based on the CBB loop model. Copyright © 2015 Elsevier Ltd. All rights reserved.

An in vivo model of functional and vascularized human brain organoids.

PubMed

Mansour, Abed AlFatah; Gonçalves, J Tiago; Bloyd, Cooper W; Li, Hao; Fernandes, Sarah; Quang, Daphne; Johnston, Stephen; Parylak, Sarah L; Jin, Xin; Gage, Fred H

2018-06-01

Differentiation of human pluripotent stem cells to small brain-like structures known as brain organoids offers an unprecedented opportunity to model human brain development and disease. To provide a vascularized and functional in vivo model of brain organoids, we established a method for transplanting human brain organoids into the adult mouse brain. Organoid grafts showed progressive neuronal differentiation and maturation, gliogenesis, integration of microglia, and growth of axons to multiple regions of the host brain. In vivo two-photon imaging demonstrated functional neuronal networks and blood vessels in the grafts. Finally, in vivo extracellular recording combined with optogenetics revealed intragraft neuronal activity and suggested graft-to-host functional synaptic connectivity. This combination of human neural organoids and an in vivo physiological environment in the animal brain may facilitate disease modeling under physiological conditions.

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.

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

Comparison of two integration methods for dynamic causal modeling of electrophysiological data.

PubMed

Lemaréchal, Jean-Didier; George, Nathalie; David, Olivier

2018-06-01

Dynamic causal modeling (DCM) is a methodological approach to study effective connectivity among brain regions. Based on a set of observations and a biophysical model of brain interactions, DCM uses a Bayesian framework to estimate the posterior distribution of the free parameters of the model (e.g. modulation of connectivity) and infer architectural properties of the most plausible model (i.e. model selection). When modeling electrophysiological event-related responses, the estimation of the model relies on the integration of the system of delay differential equations (DDEs) that describe the dynamics of the system. In this technical note, we compared two numerical schemes for the integration of DDEs. The first, and standard, scheme approximates the DDEs (more precisely, the state of the system, with respect to conduction delays among brain regions) using ordinary differential equations (ODEs) and solves it with a fixed step size. The second scheme uses a dedicated DDEs solver with adaptive step sizes to control error, making it theoretically more accurate. To highlight the effects of the approximation used by the first integration scheme in regard to parameter estimation and Bayesian model selection, we performed simulations of local field potentials using first, a simple model comprising 2 regions and second, a more complex model comprising 6 regions. In these simulations, the second integration scheme served as the standard to which the first one was compared. Then, the performances of the two integration schemes were directly compared by fitting a public mismatch negativity EEG dataset with different models. The simulations revealed that the use of the standard DCM integration scheme was acceptable for Bayesian model selection but underestimated the connectivity parameters and did not allow an accurate estimation of conduction delays. Fitting to empirical data showed that the models systematically obtained an increased accuracy when using the second integration scheme. We conclude that inference on connectivity strength and delay based on DCM for EEG/MEG requires an accurate integration scheme. Copyright © 2018 The Authors. Published by 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

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.

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.

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

[Psychotherapy of patients with brain lesions: an integrative model based on neuropsychological and psychodynamic perspectives].

PubMed

Ouss-Ryngaert, Lisa

2010-12-01

Our model of psychotherapy for patients with brain lesions is based on an integrative approach of psychobehavioral symptoms, especially from the neuropsychological and psychodynamic perspectives. Adjustment of technical modalities and aims of psychoanalytical therapy is required for these patients. The analysis of the influence of cognitive disorders on transference and contre-transference plays a major role, including the role of procedural processes in changes in the intersubjective relationship between the patient and the therapist. Two vignettes are presented to illustrate our model, which respects the integrity of the cognitive and psychodynamic approaches and can be implemented by only one therapist, using alternatively each lecture, or by a working team bringing to light the different aspects of the same symptom.

Social Outcomes in Childhood Brain Disorder: A Heuristic Integration of Social Neuroscience and Developmental Psychology

ERIC Educational Resources Information Center

Yeates, Keith Owen; Bigler, Erin D.; Dennis, Maureen; Gerhardt, Cynthia A.; Rubin, Kenneth H.; Stancin, Terry; Taylor, H. Gerry; Vannatta, Kathryn

2007-01-01

The authors propose a heuristic model of the social outcomes of childhood brain disorder that draws on models and methods from both the emerging field of social cognitive neuroscience and the study of social competence in developmental psychology/psychopathology. The heuristic model characterizes the relationships between social adjustment, peer…

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…

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.

MicroCT and microMRI imaging of a prenatal mouse model of increased brain size

NASA Astrophysics Data System (ADS)

López, Elisabeth K. N.; Stock, Stuart R.; Taketo, Makoto M.; Chenn, Anjen; Ravosa, Matthew J.

2008-08-01

There are surprisingly few experimental models of neural growth and cranial integration. This and the dearth of information regarding fetal brain development detract from a mechanistic understanding of cranial integration and its relevance to the patterning of skull form, specifically the role of encephalization on basicranial flexion. To address this shortcoming, our research uses transgenic mice expressing a stabilized form of β-catenin to isolate the effects of relative brain size on craniofacial development. These mice develop highly enlarged brains due to an increase in neural precursors, and differences between transgenic and wild-type mice are predicted to result solely from variation in brain size. Comparisons of wild-type and transgenic mice at several prenatal ages were performed using microCT (Scanco Medical MicroCT 40) and microMRI (Avance 600 WB MR spectrometer). Statistical analyses show that the larger brain of the transgenic mice is associated with a larger neurocranium and an altered basicranial morphology. However, body size and postcranial ossification do not seem to be affected by the transgene. Comparisons of the rate of postcranial and cranial ossification using microCT also point to an unexpected effect of neural growth on skull development: increased fetal encephalization may result in a compensatory decrease in the level of cranial ossification. Therefore, if other life history factors are held constant, the ontogeny of a metabolically costly structure such as a brain may occur at the expense of other cranial structures. These analyses indicate the benefits of a multifactorial approach to cranial integration using a mouse model.

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

Audio-tactile integration and the influence of musical training.

PubMed

Kuchenbuch, Anja; Paraskevopoulos, Evangelos; Herholz, Sibylle C; Pantev, Christo

2014-01-01

Perception of our environment is a multisensory experience; information from different sensory systems like the auditory, visual and tactile is constantly integrated. Complex tasks that require high temporal and spatial precision of multisensory integration put strong demands on the underlying networks but it is largely unknown how task experience shapes multisensory processing. Long-term musical training is an excellent model for brain plasticity because it shapes the human brain at functional and structural levels, affecting a network of brain areas. In the present study we used magnetoencephalography (MEG) to investigate how audio-tactile perception is integrated in the human brain and if musicians show enhancement of the corresponding activation compared to non-musicians. Using a paradigm that allowed the investigation of combined and separate auditory and tactile processing, we found a multisensory incongruency response, generated in frontal, cingulate and cerebellar regions, an auditory mismatch response generated mainly in the auditory cortex and a tactile mismatch response generated in frontal and cerebellar regions. The influence of musical training was seen in the audio-tactile as well as in the auditory condition, indicating enhanced higher-order processing in musicians, while the sources of the tactile MMN were not influenced by long-term musical training. Consistent with the predictive coding model, more basic, bottom-up sensory processing was relatively stable and less affected by expertise, whereas areas for top-down models of multisensory expectancies were modulated by training.

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.

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.

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.

Action and language mechanisms in the brain: data, models and neuroinformatics.

PubMed

Arbib, Michael A; Bonaiuto, James J; Bornkessel-Schlesewsky, Ina; Kemmerer, David; MacWhinney, Brian; Nielsen, Finn Årup; Oztop, Erhan

2014-01-01

We assess the challenges of studying action and language mechanisms in the brain, both singly and in relation to each other to provide a novel perspective on neuroinformatics, integrating the development of databases for encoding – separately or together – neurocomputational models and empirical data that serve systems and cognitive neuroscience.

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.

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

The "proactive" model of learning: Integrative framework for model-free and model-based reinforcement learning utilizing the associative learning-based proactive brain concept.

PubMed

Zsuga, Judit; Biro, Klara; Papp, Csaba; Tajti, Gabor; Gesztelyi, Rudolf

2016-02-01

Reinforcement learning (RL) is a powerful concept underlying forms of associative learning governed by the use of a scalar reward signal, with learning taking place if expectations are violated. RL may be assessed using model-based and model-free approaches. Model-based reinforcement learning involves the amygdala, the hippocampus, and the orbitofrontal cortex (OFC). The model-free system involves the pedunculopontine-tegmental nucleus (PPTgN), the ventral tegmental area (VTA) and the ventral striatum (VS). Based on the functional connectivity of VS, model-free and model based RL systems center on the VS that by integrating model-free signals (received as reward prediction error) and model-based reward related input computes value. Using the concept of reinforcement learning agent we propose that the VS serves as the value function component of the RL agent. Regarding the model utilized for model-based computations we turned to the proactive brain concept, which offers an ubiquitous function for the default network based on its great functional overlap with contextual associative areas. Hence, by means of the default network the brain continuously organizes its environment into context frames enabling the formulation of analogy-based association that are turned into predictions of what to expect. The OFC integrates reward-related information into context frames upon computing reward expectation by compiling stimulus-reward and context-reward information offered by the amygdala and hippocampus, respectively. Furthermore we suggest that the integration of model-based expectations regarding reward into the value signal is further supported by the efferent of the OFC that reach structures canonical for model-free learning (e.g., the PPTgN, VTA, and VS). (c) 2016 APA, 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.

Social Outcomes in Childhood Brain Disorder: A Heuristic Integration of Social Neuroscience and Developmental Psychology

PubMed Central

Yeates, Keith Owen; Bigler, Erin D.; Dennis, Maureen; Gerhardt, Cynthia A.; Rubin, Kenneth H.; Stancin, Terry; Taylor, H. Gerry; Vannatta, Kathryn

2010-01-01

The authors propose a heuristic model of the social outcomes of childhood brain disorder that draws on models and methods from both the emerging field of social cognitive neuroscience and the study of social competence in developmental psychology/psychopathology. The heuristic model characterizes the relationships between social adjustment, peer interactions and relationships, social problem solving and communication, social-affective and cognitive-executive processes, and their neural substrates. The model is illustrated by research on a specific form of childhood brain disorder, traumatic brain injury. The heuristic model may promote research regarding the neural and cognitive-affective substrates of children’s social development. It also may engender more precise methods of measuring impairments and disabilities in children with brain disorder and suggest ways to promote their social adaptation. PMID:17469991

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.

Three-dimensional stereotactic atlas of the adult human skull correlated with the brain, cranial nerves, and intracranial vasculature.

PubMed

Nowinski, Wieslaw L; Thaung, Thant Shoon Let; Chua, Beng Choon; Yi, Su Hnin Wut; Ngai, Vincent; Yang, Yili; Chrzan, Robert; Urbanik, Andrzej

2015-05-15

Although the adult human skull is a complex and multifunctional structure, its 3D, complete, realistic, and stereotactic atlas has not yet been created. This work addresses the construction of a 3D interactive atlas of the adult human skull spatially correlated with the brain, cranial nerves, and intracranial vasculature. The process of atlas construction included computed tomography (CT) high-resolution scan acquisition, skull extraction, skull parcellation, 3D disarticulated bone surface modeling, 3D model simplification, brain-skull registration, 3D surface editing, 3D surface naming and color-coding, integration of the CT-derived 3D bony models with the existing brain atlas, and validation. The virtual skull model created is complete with all 29 bones, including the auditory ossicles (being among the smallest bones). It contains all typical bony features and landmarks. The created skull model is superior to the existing skull models in terms of completeness, realism, and integration with the brain along with blood vessels and cranial nerves. This skull atlas is valuable for medical students and residents to easily get familiarized with the skull and surrounding anatomy with a few clicks. The atlas is also useful for educators to prepare teaching materials. It may potentially serve as a reference aid in the reading and operating rooms. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

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

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

ITI: The Model. Integrated Thematic Instruction. Third Edition.

ERIC Educational Resources Information Center

Kovalik, Susan; Olsen, Karen

This book presents Integrated Thematic Instruction (ITI), a model for implementing a "brain-compatible" learning environment for students and teachers using a year-long theme to organize curriculum content and skills. The book's introduction identifies six "mismemes" (or mistaken ideas) that have hindered educational reform,…

Integrating Conceptual Knowledge within and across Representational Modalities

ERIC Educational Resources Information Center

McNorgan, Chris; Reid, Jackie; McRae, Ken

2011-01-01

Research suggests that concepts are distributed across brain regions specialized for processing information from different sensorimotor modalities. Multimodal semantic models fall into one of two broad classes differentiated by the assumed hierarchy of convergence zones over which information is integrated. In shallow models, communication within-…

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

Action and Language Mechanisms in the Brain: Data, Models and Neuroinformatics

PubMed Central

Bonaiuto, James J.; Bornkessel-Schlesewsky, Ina; Kemmerer, David; MacWhinney, Brian; Nielsen, Finn Årup; Oztop, Erhan

2014-01-01

We assess the challenges of studying action and language mechanisms in the brain, both singly and in relation to each other to provide a novel perspective on neuroinformatics, integrating the development of databases for encoding – separately or together – neurocomputational models and empirical data that serve systems and cognitive neuroscience. PMID:24234916

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.

Trafficking of adeno-associated virus vectors across a model of the blood-brain barrier; a comparative study of transcytosis and transduction using primary human brain endothelial cells.

PubMed

Merkel, Steven F; Andrews, Allison M; Lutton, Evan M; Mu, Dakai; Hudry, Eloise; Hyman, Bradley T; Maguire, Casey A; Ramirez, Servio H

2017-01-01

Developing therapies for central nervous system (CNS) diseases is exceedingly difficult because of the blood-brain barrier (BBB). Notably, emerging technologies may provide promising new options for the treatment of CNS disorders. Adeno-associated virus serotype 9 (AAV9) has been shown to transduce cells in the CNS following intravascular administration in rodents, cats, pigs, and non-human primates. These results suggest that AAV9 is capable of crossing the BBB. However, mechanisms that govern AAV9 transendothelial trafficking at the BBB remain unknown. Furthermore, possibilities that AAV9 may transduce brain endothelial cells or affect BBB integrity still require investigation. Using primary human brain microvascular endothelial cells as a model of the human BBB, we performed transduction and transendothelial trafficking assays comparing AAV9 to AAV2, a serotype that does not cross the BBB or transduce endothelial cells effectively in vivo. Results of our in vitro studies indicate that AAV9 penetrates brain microvascular endothelial cells barriers more effectively than AAV2, but has reduced transduction efficiency. In addition, our data suggest that (i) AAV9 penetrates endothelial barriers through an active, cell-mediated process, and (ii) AAV9 fails to disrupt indicators of BBB integrity such as transendothelial electrical resistance, tight junction protein expression/localization, and inflammatory activation status. Overall, this report shows how human brain endothelial cells configured in BBB models can be utilized for evaluating transendothelial movement and transduction kinetics of various AAV capsids. Importantly, the use of a human in vitro BBB model can provide import insight into the possible effects that candidate AVV gene therapy vectors may have on the status of BBB integrity. Read the Editorial Highlight for this article on page 192. © 2016 International Society for Neurochemistry.

Emotional consciousness: a neural model of how cognitive appraisal and somatic perception interact to produce qualitative experience.

PubMed

Thagard, Paul; Aubie, Brandon

2008-09-01

This paper proposes a theory of how conscious emotional experience is produced by the brain as the result of many interacting brain areas coordinated in working memory. These brain areas integrate perceptions of bodily states of an organism with cognitive appraisals of its current situation. Emotions are neural processes that represent the overall cognitive and somatic state of the organism. Conscious experience arises when neural representations achieve high activation as part of working memory. This theory explains numerous phenomena concerning emotional consciousness, including differentiation, integration, intensity, valence, and change.

Verbal Neuropsychological Functions in Aphasia: An Integrative Model

ERIC Educational Resources Information Center

Vigliecca, Nora Silvana; Báez, Sandra

2015-01-01

A theoretical framework which considers the verbal functions of the brain under a multivariate and comprehensive cognitive model was statistically analyzed. A confirmatory factor analysis was performed to verify whether some recognized aphasia constructs can be hierarchically integrated as latent factors from a homogenously verbal test. The Brief…

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.

BRAIN initiative: fast and parallel solver for real-time monitoring of the eddy current in the brain for TMS applications.

PubMed

Sabouni, Abas; Pouliot, Philippe; Shmuel, Amir; Lesage, Frederic

2014-01-01

This paper introduce a fast and efficient solver for simulating the induced (eddy) current distribution in the brain during transcranial magnetic stimulation procedure. This solver has been integrated with MRI and neuronavigation software to accurately model the electromagnetic field and show eddy current in the head almost in real-time. To examine the performance of the proposed technique, we used a 3D anatomically accurate MRI model of the 25 year old female subject.

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

Integrating Brain and Biomechanical Models—A New Paradigm for Understanding Neuro-muscular Control

PubMed Central

James, Sebastian S.; Papapavlou, Chris; Blenkinsop, Alexander; Cope, Alexander J.; Anderson, Sean R.; Moustakas, Konstantinos; Gurney, Kevin N.

2018-01-01

To date, realistic models of how the central nervous system governs behavior have been restricted in scope to the brain, brainstem or spinal column, as if these existed as disembodied organs. Further, the model is often exercised in relation to an in vivo physiological experiment with input comprising an impulse, a periodic signal or constant activation, and output as a pattern of neural activity in one or more neural populations. Any link to behavior is inferred only indirectly via these activity patterns. We argue that to discover the principles of operation of neural systems, it is necessary to express their behavior in terms of physical movements of a realistic motor system, and to supply inputs that mimic sensory experience. To do this with confidence, we must connect our brain models to neuro-muscular models and provide relevant visual and proprioceptive feedback signals, thereby closing the loop of the simulation. This paper describes an effort to develop just such an integrated brain and biomechanical system using a number of pre-existing models. It describes a model of the saccadic oculomotor system incorporating a neuromuscular model of the eye and its six extraocular muscles. The position of the eye determines how illumination of a retinotopic input population projects information about the location of a saccade target into the system. A pre-existing saccadic burst generator model was incorporated into the system, which generated motoneuron activity patterns suitable for driving the biomechanical eye. The model was demonstrated to make accurate saccades to a target luminance under a set of environmental constraints. Challenges encountered in the development of this model showed the importance of this integrated modeling approach. Thus, we exposed shortcomings in individual model components which were only apparent when these were supplied with the more plausible inputs available in a closed loop design. Consequently we were able to suggest missing functionality which the system would require to reproduce more realistic behavior. The construction of such closed-loop animal models constitutes a new paradigm of computational neurobehavior and promises a more thoroughgoing approach to our understanding of the brain's function as a controller for movement and behavior. PMID:29467606

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

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

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

Synchrony in Psychotherapy: A Review and an Integrative Framework for the Therapeutic Alliance.

PubMed

Koole, Sander L; Tschacher, Wolfgang

2016-01-01

During psychotherapy, patient and therapist tend to spontaneously synchronize their vocal pitch, bodily movements, and even their physiological processes. In the present article, we consider how this pervasive phenomenon may shed new light on the therapeutic relationship- or alliance- and its role within psychotherapy. We first review clinical research on the alliance and the multidisciplinary area of interpersonal synchrony. We then integrate both literatures in the Interpersonal Synchrony (In-Sync) model of psychotherapy. According to the model, the alliance is grounded in the coupling of patient and therapist's brains. Because brains do not interact directly, movement synchrony may help to establish inter-brain coupling. Inter-brain coupling may provide patient and therapist with access to another's internal states, which facilitates common understanding and emotional sharing. Over time, these interpersonal exchanges may improve patients' emotion-regulatory capacities and related therapeutic outcomes. We discuss the empirical assessment of interpersonal synchrony and review preliminary research on synchrony in psychotherapy. Finally, we summarize our main conclusions and consider the broader implications of viewing psychotherapy as the product of two interacting brains.

Synchrony in Psychotherapy: A Review and an Integrative Framework for the Therapeutic Alliance

PubMed Central

Koole, Sander L.; Tschacher, Wolfgang

2016-01-01

During psychotherapy, patient and therapist tend to spontaneously synchronize their vocal pitch, bodily movements, and even their physiological processes. In the present article, we consider how this pervasive phenomenon may shed new light on the therapeutic relationship– or alliance– and its role within psychotherapy. We first review clinical research on the alliance and the multidisciplinary area of interpersonal synchrony. We then integrate both literatures in the Interpersonal Synchrony (In-Sync) model of psychotherapy. According to the model, the alliance is grounded in the coupling of patient and therapist’s brains. Because brains do not interact directly, movement synchrony may help to establish inter-brain coupling. Inter-brain coupling may provide patient and therapist with access to another’s internal states, which facilitates common understanding and emotional sharing. Over time, these interpersonal exchanges may improve patients’ emotion-regulatory capacities and related therapeutic outcomes. We discuss the empirical assessment of interpersonal synchrony and review preliminary research on synchrony in psychotherapy. Finally, we summarize our main conclusions and consider the broader implications of viewing psychotherapy as the product of two interacting brains. PMID:27378968

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.

Iron overload prevents oxidative damage to rat brain after chlorpromazine administration.

PubMed

Piloni, Natacha E; Caro, Andres A; Puntarulo, Susana

2018-05-15

The hypothesis tested is that Fe administration leads to a response in rat brain modulating the effects of later oxidative challenges such as chlorpromazine (CPZ) administration. Either a single dose (acute Fe overload) or 6 doses every second day (sub-chronic Fe overload) of 500 or 50 mg Fe-dextran/kg, respectively, were injected intraperitoneally (ip) to rats. A single dose of 10 mg CPZ/kg was injected ip 8 h after Fe treatment. DNA integrity was evaluated by quantitative PCR, lipid radical (LR · ) generation rate by electron paramagnetic resonance (EPR), and catalase (CAT) activity by UV spectrophotometry in isolated brains. The maximum increase in total Fe brain was detected after 6 or 2 h in the acute and sub-chronic Fe overload model, respectively. Mitochondrial and nuclear DNA integrity decreased after acute Fe overload at the time of maximal Fe content; the decrease in DNA integrity was lower after sub-chronic than after acute Fe overload. CPZ administration increased LR · generation rate in control rat brain after 1 and 2 h; however, CPZ administration after acute or sub-chronic Fe overload did not affect LR · generation rate. CPZ treatment did not affect CAT activity after 1-4 h neither in control rats nor in acute Fe-overloaded rats. However, CPZ administration to rats treated sub-chronically with Fe showed increased brain CAT activity after 2 or 4 h, as compared to control values. Fe supplementation prevented brain damage in both acute and sub-chronic models of Fe overload by selectively activating antioxidant pathways.

Music plus Music Integration: A Model for Music Education Policy Reform That Reflects the Evolution and Success of Arts Integration Practices in 21st Century American Public Schools

ERIC Educational Resources Information Center

Scripp, Lawrence; Gilbert, Josh

2016-01-01

This article explores the special case of integrative teaching and learning in music as a model for 21st century music education policy reform based on the principles that have evolved out of arts integration research and practices over the past century and informed by the recent rising tide of evidence of music's impact on brain capacity and…

A deep learning model integrating FCNNs and CRFs for brain tumor segmentation.

PubMed

Zhao, Xiaomei; Wu, Yihong; Song, Guidong; Li, Zhenye; Zhang, Yazhuo; Fan, Yong

2018-01-01

Accurate and reliable brain tumor segmentation is a critical component in cancer diagnosis, treatment planning, and treatment outcome evaluation. Build upon successful deep learning techniques, a novel brain tumor segmentation method is developed by integrating fully convolutional neural networks (FCNNs) and Conditional Random Fields (CRFs) in a unified framework to obtain segmentation results with appearance and spatial consistency. We train a deep learning based segmentation model using 2D image patches and image slices in following steps: 1) training FCNNs using image patches; 2) training CRFs as Recurrent Neural Networks (CRF-RNN) using image slices with parameters of FCNNs fixed; and 3) fine-tuning the FCNNs and the CRF-RNN using image slices. Particularly, we train 3 segmentation models using 2D image patches and slices obtained in axial, coronal and sagittal views respectively, and combine them to segment brain tumors using a voting based fusion strategy. Our method could segment brain images slice-by-slice, much faster than those based on image patches. We have evaluated our method based on imaging data provided by the Multimodal Brain Tumor Image Segmentation Challenge (BRATS) 2013, BRATS 2015 and BRATS 2016. The experimental results have demonstrated that our method could build a segmentation model with Flair, T1c, and T2 scans and achieve competitive performance as those built with Flair, T1, T1c, and T2 scans. Copyright © 2017 Elsevier B.V. All rights reserved.

Implications of the Vienna Integrated Model of Art Perception for art-based interventions in clinical populations: 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)

Taruffi, Liila; Koelsch, Stefan

2017-07-01

Pelowski et al. present a holistic framework within which the multiple processes underlying art viewing can be systematically organized [1]. The proposed model integrates a broad range of dynamic mechanisms, which can effectively account for empirical as well as humanistic perspectives on art perception. Particularly challenging is the final section of the article, where the authors draw a correspondence between behavioral and cognitive components and brain structures (as well as networks). Here, we comment on the implications of the Vienna Integrated Model of Art Perception for art therapy in clinical populations, particularly focusing on (1) expanding Pelowski et al.'s considerations of the Default Mode Network (DMN) into discussion of its relevance to mental diseases, and (2) elaborating on empathic resonance in aesthetic contexts and the capacity of art to build up empathic skills.

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.

Computational modeling of brain tumors: discrete, continuum or hybrid?

NASA Astrophysics Data System (ADS)

Wang, Zhihui; Deisboeck, Thomas S.

In spite of all efforts, patients diagnosed with highly malignant brain tumors (gliomas), continue to face a grim prognosis. Achieving significant therapeutic advances will also require a more detailed quantitative understanding of the dynamic interactions among tumor cells, and between these cells and their biological microenvironment. Data-driven computational brain tumor models have the potential to provide experimental tumor biologists with such quantitative and cost-efficient tools to generate and test hypotheses on tumor progression, and to infer fundamental operating principles governing bidirectional signal propagation in multicellular cancer systems. This review highlights the modeling objectives of and challenges with developing such in silico brain tumor models by outlining two distinct computational approaches: discrete and continuum, each with representative examples. Future directions of this integrative computational neuro-oncology field, such as hybrid multiscale multiresolution modeling are discussed.

Chronic rapamycin restores brain vascular integrity and function through NO synthase activation and improves memory in symptomatic mice modeling Alzheimer's disease

PubMed Central

Lin, Ai-Ling; Zheng, Wei; Halloran, Jonathan J; Burbank, Raquel R; Hussong, Stacy A; Hart, Matthew J; Javors, Martin; Shih, Yen-Yu Ian; Muir, Eric; Solano Fonseca, Rene; Strong, Randy; Richardson, Arlan G; Lechleiter, James D; Fox, Peter T; Galvan, Veronica

2013-01-01

Vascular pathology is a major feature of Alzheimer's disease (AD) and other dementias. We recently showed that chronic administration of the target-of-rapamycin (TOR) inhibitor rapamycin, which extends lifespan and delays aging, halts the progression of AD-like disease in transgenic human (h)APP mice modeling AD when administered before disease onset. Here we demonstrate that chronic reduction of TOR activity by rapamycin treatment started after disease onset restored cerebral blood flow (CBF) and brain vascular density, reduced cerebral amyloid angiopathy and microhemorrhages, decreased amyloid burden, and improved cognitive function in symptomatic hAPP (AD) mice. Like acetylcholine (ACh), a potent vasodilator, acute rapamycin treatment induced the phosphorylation of endothelial nitric oxide (NO) synthase (eNOS) and NO release in brain endothelium. Administration of the NOS inhibitor L-NG-Nitroarginine methyl ester reversed vasodilation as well as the protective effects of rapamycin on CBF and vasculature integrity, indicating that rapamycin preserves vascular density and CBF in AD mouse brains through NOS activation. Taken together, our data suggest that chronic reduction of TOR activity by rapamycin blocked the progression of AD-like cognitive and histopathological deficits by preserving brain vascular integrity and function. Drugs that inhibit the TOR pathway may have promise as a therapy for AD and possibly for vascular dementias. PMID:23801246

Scan-stratified case-control sampling for modeling blood-brain barrier integrity in multiple sclerosis.

PubMed

Pomann, Gina-Maria; Sweeney, Elizabeth M; Reich, Daniel S; Staicu, Ana-Maria; Shinohara, Russell T

2015-09-10

Multiple sclerosis (MS) is an immune-mediated neurological disease that causes morbidity and disability. In patients with MS, the accumulation of lesions in the white matter of the brain is associated with disease progression and worse clinical outcomes. Breakdown of the blood-brain barrier in newer lesions is indicative of more active disease-related processes and is a primary outcome considered in clinical trials of treatments for MS. Such abnormalities in active MS lesions are evaluated in vivo using contrast-enhanced structural MRI, during which patients receive an intravenous infusion of a costly magnetic contrast agent. In some instances, the contrast agents can have toxic effects. Recently, local image regression techniques have been shown to have modest performance for assessing the integrity of the blood-brain barrier based on imaging without contrast agents. These models have centered on the problem of cross-sectional classification in which patients are imaged at a single study visit and pre-contrast images are used to predict post-contrast imaging. In this paper, we extend these methods to incorporate historical imaging information, and we find the proposed model to exhibit improved performance. We further develop scan-stratified case-control sampling techniques that reduce the computational burden of local image regression models, while respecting the low proportion of the brain that exhibits abnormal vascular permeability. Copyright © 2015 John Wiley & Sons, Ltd.

An Anatomically Constrained Model for Path Integration in the Bee Brain.

PubMed

Stone, Thomas; Webb, Barbara; Adden, Andrea; Weddig, Nicolai Ben; Honkanen, Anna; Templin, Rachel; Wcislo, William; Scimeca, Luca; Warrant, Eric; Heinze, Stanley

2017-10-23

Path integration is a widespread navigational strategy in which directional changes and distance covered are continuously integrated on an outward journey, enabling a straight-line return to home. Bees use vision for this task-a celestial-cue-based visual compass and an optic-flow-based visual odometer-but the underlying neural integration mechanisms are unknown. Using intracellular electrophysiology, we show that polarized-light-based compass neurons and optic-flow-based speed-encoding neurons converge in the central complex of the bee brain, and through block-face electron microscopy, we identify potential integrator cells. Based on plausible output targets for these cells, we propose a complete circuit for path integration and steering in the central complex, with anatomically identified neurons suggested for each processing step. The resulting model circuit is thus fully constrained biologically and provides a functional interpretation for many previously unexplained architectural features of the central complex. Moreover, we show that the receptive fields of the newly discovered speed neurons can support path integration for the holonomic motion (i.e., a ground velocity that is not precisely aligned with body orientation) typical of bee flight, a feature not captured in any previously proposed model of path integration. In a broader context, the model circuit presented provides a general mechanism for producing steering signals by comparing current and desired headings-suggesting a more basic function for central complex connectivity, from which path integration may have evolved. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

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.

SOCIAL: an integrative framework for the development of social skills.

PubMed

Beauchamp, Miriam H; Anderson, Vicki

2010-01-01

Despite significant advances in the field of social neuroscience, much remains to be understood regarding the development and maintenance of social skills across the life span. Few comprehensive models exist that integrate multidisciplinary perspectives and explain the multitude of factors that influence the emergence and expression of social skills. Here, a developmental biopsychosocial model (SOCIAL) is offered that incorporates the biological underpinnings and socio-cognitive skills that underlie social function (attention/executive function, communication, socio-emotional skills), as well as the internal and external (environmental) factors that mediate these skills. The components of the model are discussed in the context of the social brain network and are supported by evidence from 3 conditions known to affect social functioning (autism spectrum disorders, schizophrenia, and traumatic brain injury). This integrative model is intended to provide a theoretical structure for understanding the origins of social dysfunction and the factors that influence the emergence of social skills through childhood and adolescence in both healthy and clinical populations.

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.

Improving the clinical management of traumatic brain injury through the pharmacokinetic modeling of peripheral blood biomarkers.

PubMed

Dadas, Aaron; Washington, Jolewis; Marchi, Nicola; Janigro, Damir

2016-11-30

Blood biomarkers of neurovascular damage are used clinically to diagnose the presence severity or absence of neurological diseases, but data interpretation is confounded by a limited understanding of their dependence on variables other than the disease condition itself. These include half-life in blood, molecular weight, and marker-specific biophysical properties, as well as the effects of glomerular filtration, age, gender, and ethnicity. To study these factors, and to provide a method for markers' analyses, we developed a kinetic model that allows the integrated interpretation of these properties. The pharmacokinetic behaviors of S100B (monomer and homodimer), Glial Fibrillary Acidic Protein and Ubiquitin C-Terminal Hydrolase L1 were modeled using relevant chemical and physical properties; modeling results were validated by comparison with data obtained from healthy subjects or individuals affected by neurological diseases. Brain imaging data were used to model passage of biomarkers across the blood-brain barrier. Our results show the following: (1) changes in biomarker serum levels due to age or disease progression are accounted for by differences in kidney filtration; (2) a significant change in the brain-to-blood volumetric ratio, which is characteristic of infant and adult development, contributes to variation in blood concentration of biomarkers; (3) the effects of extracranial contribution at steady-state are predicted in our model to be less important than suspected, while the contribution of blood-brain barrier disruption is confirmed as a significant factor in controlling markers' appearance in blood, where the biomarkers are typically detected; (4) the contribution of skin to the marker S100B blood levels depends on a direct correlation with pigmentation and not ethnicity; the contribution of extracranial sources for other markers requires further investigation. We developed a multi-compartment, pharmacokinetic model that integrates the biophysical properties of a given brain molecule and predicts its time-dependent concentration in blood, for populations of varying physical and anatomical characteristics. This model emphasizes the importance of the blood-brain barrier as a gatekeeper for markers' blood appearance and, ultimately, for rational clinical use of peripherally-detected brain protein.

[Effect of ginsenoside Rb1 on cerebral infarction volume and IL-1 beta in the brain tissue and sera of focal cerebral ischemia/reperfusion injury model rats].

PubMed

Liu, Jun-Wei; Ren, Ye-Long; Liu, Xu-Ling; Xia, Hong-Lian; Zhang, Hui-Ling; Jin, Shen-Hui; Dai, Qin-Xue; Wang, Jun-Lu

2013-12-01

To investigate the effect of ginsenoside Rb1 on cerebral infarction volume as well as IL-1 beta in the brain tissue and sera of focal cerebral ischemia/reperfusion (I/R) injury model rats. The I/R rat model was established by using thread according to Zea-Longa. SD rats were randomly divided into five groups, i.e., the sham-operation group, the model group, the low dose ginsenoside Rb1 (20 mg/kg) group, the medium dose ginsenoside Rb1 group (40 mg/kg), and the high dose ginsenoside Rb1 group (80 mg/kg), 12 in each group. Rats in the sham-operation group only received middle cerebral artery occlusion (MCAO) but without thread insertion. The MCAO model was prepared in the rest 4 groups, followed by MCAO2 h later. Ginsenoside Rb1 at each dose was peritoneally administrated to rats in corresponding groups immediately after cerebral ischemia. Equal volume of normal saline was administered to rats in the sham-operation group. Rats' cerebral infarction volume, integrals of neurologic defect degree, expression of IL-1 beta content in the brain tissue and sera were observed 24 h after 2-h cerebral I/R. In the model group, integrals of neurologic defect degree were improved (P < 0.01), IL-1 beta positive cells in the brain tissue increased and serum IL-1 beta content elevated (P < 0.05), when compared with the sham-operation group. In comparison of the model group, integrals of neurologic defect degree were lowered in the medium dose and high dose ginsenoside Rb1 groups (P < 0.05, P < 0.01). The cerebral infarction volume was all shrunken in each ginsenoside Rb1 group, IL-1 beta positive cells in the brain tissue decreased, and IL-1 beta content in serum reduced (P < 0.01, P < 0.05). Compared with the low dose ginsenoside Rb1 group, integrals of neurologic defect degree decreased, the cerebral infarction volume shrunken, and IL-1 beta content in serum reduced in the high dose ginsenoside Rb1 group (P < 0.01, P < 0.05). Ginsenoside Rb1 (20, 40, 80 mg/kg) might effectively release local cerebral ischemia by down-regulating the IL-1 beta expression.

Inferring multi-scale neural mechanisms with brain network modelling

PubMed Central

Schirner, Michael; McIntosh, Anthony Randal; Jirsa, Viktor; Deco, Gustavo

2018-01-01

The neurophysiological processes underlying non-invasive brain activity measurements are incompletely understood. Here, we developed a connectome-based brain network model that integrates individual structural and functional data with neural population dynamics to support multi-scale neurophysiological inference. Simulated populations were linked by structural connectivity and, as a novelty, driven by electroencephalography (EEG) source activity. Simulations not only predicted subjects' individual resting-state functional magnetic resonance imaging (fMRI) time series and spatial network topologies over 20 minutes of activity, but more importantly, they also revealed precise neurophysiological mechanisms that underlie and link six empirical observations from different scales and modalities: (1) resting-state fMRI oscillations, (2) functional connectivity networks, (3) excitation-inhibition balance, (4, 5) inverse relationships between α-rhythms, spike-firing and fMRI on short and long time scales, and (6) fMRI power-law scaling. These findings underscore the potential of this new modelling framework for general inference and integration of neurophysiological knowledge to complement empirical studies. PMID:29308767

Network neuroscience

PubMed Central

Bassett, Danielle S; Sporns, Olaf

2017-01-01

Despite substantial recent progress, our understanding of the principles and mechanisms underlying complex brain function and cognition remains incomplete. Network neuroscience proposes to tackle these enduring challenges. Approaching brain structure and function from an explicitly integrative perspective, network neuroscience pursues new ways to map, record, analyze and model the elements and interactions of neurobiological systems. Two parallel trends drive the approach: the availability of new empirical tools to create comprehensive maps and record dynamic patterns among molecules, neurons, brain areas and social systems; and the theoretical framework and computational tools of modern network science. The convergence of empirical and computational advances opens new frontiers of scientific inquiry, including network dynamics, manipulation and control of brain networks, and integration of network processes across spatiotemporal domains. We review emerging trends in network neuroscience and attempt to chart a path toward a better understanding of the brain as a multiscale networked system. PMID:28230844

Social Competence in Pediatric Brain Tumor Survivors: Application of a Model from Social Neuroscience and Developmental Psychology

PubMed Central

Hocking, Matthew C.; McCurdy, Mark; Turner, Elise; Kazak, Anne E.; Noll, Robert B.; Phillips, Peter; Barakat, Lamia P.

2014-01-01

Pediatric brain tumor (BT) survivors are at risk for psychosocial late effects across many domains of functioning, including neurocognitive and social. The literature on the social competence of pediatric BT survivors is still developing and future research is needed that integrates developmental and cognitive neuroscience research methodologies to identify predictors of survivor social adjustment and interventions to ameliorate problems. This review discusses the current literature on survivor social functioning through a model of social competence in childhood brain disorder and suggests future directions based on this model. Interventions pursuing change in survivor social adjustment should consider targeting social ecological factors. PMID:25382825

The hippocampus is an integral part of the temporal limbic system during emotional processing. Comment on "The quartet theory of human emotions: An integrative and neurofunctional model" by S. Koelsch et al.

NASA Astrophysics Data System (ADS)

Trost, Wiebke; Frühholz, Sascha

2015-06-01

The proposed quartet theory of human emotions by Koelsch and colleagues [1] identifies four different affect systems to be involved in the processing of particular types of emotions. Moreover, the theory integrates both basic emotions and more complex emotion concepts, which include also aesthetic emotions such as musical emotions. The authors identify a particular brain system for each kind of emotion type, also by contrasting them to brain structures that are generally involved in emotion processing irrespective of the type of emotion. A brain system that has been less regarded in emotion theories, but which represents one of the four systems of the quartet to induce attachment related emotions, is the hippocampus.

Integrating Retraction Modeling Into an Atlas-Based Framework for Brain Shift Prediction

PubMed Central

Chen, Ishita; Ong, Rowena E.; Simpson, Amber L.; Sun, Kay; Thompson, Reid C.

2015-01-01

In recent work, an atlas-based statistical model for brain shift prediction, which accounts for uncertainty in the intraoperative environment, has been proposed. Previous work reported in the literature using this technique did not account for local deformation caused by surgical retraction. It is challenging to precisely localize the retractor location prior to surgery and the retractor is often moved in the course of the procedure. This paper proposes a technique that involves computing the retractor-induced brain deformation in the operating room through an active model solve and linearly superposing the solution with the precomputed deformation atlas. As a result, the new method takes advantage of the atlas-based framework’s accounting for uncertainties while also incorporating the effects of retraction with minimal intraoperative computing. This new approach was tested using simulation and phantom experiments. The results showed an improvement in average shift correction from 50% (ranging from 14 to 81%) for gravity atlas alone to 80% using the active solve retraction component (ranging from 73 to 85%). This paper presents a novel yet simple way to integrate retraction into the atlas-based brain shift computation framework. PMID:23864146

Biomarker Exposure-Response Analysis in Mild-To-Moderate Alzheimer's Disease Trials of Bapineuzumab.

PubMed

Russu, Alberto; Samtani, Mahesh N; Xu, Steven; Adedokun, Omoniyi J; Lu, Ming; Ito, Kaori; Corrigan, Brian; Raje, Sangeeta; Liu, Enchi; Brashear, H Robert; Styren, Scot; Hu, Chuanpu

2016-05-03

Bapineuzumab, an anti-amyloid monoclonal antibody, was evaluated as a candidate for immunotherapy in mild-to-moderate Alzheimer's disease (AD) patients. To assess the treatment effect of bapineuzumab therapy on disease-relevant biomarkers in patients with mild-to-moderate AD, using exposure-response modeling. Biomarker data from two Phase III studies were combined to model the impact of bapineuzumab exposure on week-71 change from baseline in brain amyloid burden by 11C-labeled Pittsburgh compound B (PiB) PET imaging (global cortical average of the Standardized Uptake Value ratio values), cerebrospinal fluid (CSF) phosphorylated (p)-tau concentrations, and brain volumetrics (brain boundary shift integral) by magnetic resonance imaging. Bapineuzumab or placebo was administered as a 1-hour intravenous infusion every 13 weeks for 78 weeks. Pharmacokinetic/pharmacodynamic modeling helped determine the most appropriate exposure-response model and estimate the impact of disease-relevant covariates (baseline biomarker value, APOE*E4 allele copy number, and baseline disease status as measured by Mini-Mental State Examination score) on the three biomarkers. Linear exposure-response relationships with negative and significant slope terms were observed for PiB PET and CSF p-tau concentration. Baseline biomarker value and APOE*E4 carrier status were significant covariates for both biomarkers. No exposure-response relationship on brain boundary shift integral was detected. Bapineuzumab treatment induced exposure-dependent reductions in brain amyloid burden. Effects on CSF p-tau concentrations were significant only in APOE*E4 carriers. No apparent influence of bapineuzumab exposure on brain volume could be demonstrated.

Multifactorial causal model of brain (dis)organization and therapeutic intervention: Application to Alzheimer's disease.

PubMed

Iturria-Medina, Yasser; Carbonell, Félix M; Sotero, Roberto C; Chouinard-Decorte, Francois; Evans, Alan C

2017-05-15

Generative models focused on multifactorial causal mechanisms in brain disorders are scarce and generally based on limited data. Despite the biological importance of the multiple interacting processes, their effects remain poorly characterized from an integrative analytic perspective. Here, we propose a spatiotemporal multifactorial causal model (MCM) of brain (dis)organization and therapeutic intervention that accounts for local causal interactions, effects propagation via physical brain networks, cognitive alterations, and identification of optimum therapeutic interventions. In this article, we focus on describing the model and applying it at the population-based level for studying late onset Alzheimer's disease (LOAD). By interrelating six different neuroimaging modalities and cognitive measurements, this model accurately predicts spatiotemporal alterations in brain amyloid-β (Aβ) burden, glucose metabolism, vascular flow, resting state functional activity, structural properties, and cognitive integrity. The results suggest that a vascular dysregulation may be the most-likely initial pathologic event leading to LOAD. Nevertheless, they also suggest that LOAD it is not caused by a unique dominant biological factor (e.g. vascular or Aβ) but by the complex interplay among multiple relevant direct interactions. Furthermore, using theoretical control analysis of the identified population-based multifactorial causal network, we show the crucial advantage of using combinatorial over single-target treatments, explain why one-target Aβ based therapies might fail to improve clinical outcomes, and propose an efficiency ranking of possible LOAD interventions. Although still requiring further validation at the individual level, this work presents the first analytic framework for dynamic multifactorial brain (dis)organization that may explain both the pathologic evolution of progressive neurological disorders and operationalize the influence of multiple interventional strategies. Copyright © 2017 Elsevier Inc. All rights reserved.

An Integrated Self-Aware Cognitive Architecture

DTIC Science & Technology

2008-03-01

human-like cognitive growth. Our approach is inspired by studies of the human brain -mind: in particular, by theoretical models of representations of...agency in the higher associative human brain areas. This feature (a theory of mind including representations of one’s self) allows the system to...self-aware cognition that we believe is necessary for human-like cognitive growth. Our approach is inspired by studies of the human brain -mind: in

Developing a comprehensive framework of community integration for people with acquired brain injury: a conceptual analysis.

PubMed

Shaikh, Nusratnaaz M; Kersten, Paula; Siegert, Richard J; Theadom, Alice

2018-03-06

Despite increasing emphasis on the importance of community integration as an outcome for acquired brain injury (ABI), there is still no consensus on the definition of community integration. The aim of this study was to complete a concept analysis of community integration in people with ABI. The method of concept clarification was used to guide concept analysis of community integration based on a literature review. Articles were included if they explored community integration in people with ABI. Data extraction was performed by the initial coding of (1) the definition of community integration used in the articles, (2) attributes of community integration recognized in the articles' findings, and (3) the process of community integration. This information was synthesized to develop a model of community integration. Thirty-three articles were identified that met the inclusion criteria. The construct of community integration was found to be a non-linear process reflecting recovery over time, sequential goals, and transitions. Community integration was found to encompass six components including: independence, sense of belonging, adjustment, having a place to live, involved in a meaningful occupational activity, and being socially connected into the community. Antecedents to community integration included individual, injury-related, environmental, and societal factors. The findings of this concept analysis suggest that the concept of community integration is more diverse than previously recognized. New measures and rehabilitation plans capturing all attributes of community integration are needed in clinical practice. Implications for rehabilitation Understanding of perceptions and lived experiences of people with acquired brain injury through this analysis provides basis to ensure rehabilitation meets patients' needs. This model highlights the need for clinicians to be aware and assess the role of antecedents as well as the attributes of community integration itself to ensure all aspects are addressed in in a manner that will enhance the recovery and improve the level of integration into the community. The finding that community integration is a non-linear process also highlights the need for rehabilitation professionals to review and revise plans over time in response to a person's changing circumstances and recovery journey. This analysis provides the groundwork for an operational model of community integration for the development of a measure of community integration that assesses all six attributes revealed in this review not recognized in previous frameworks.

Breaking symmetry: the zebrafish as a model for understanding left-right asymmetry in the developing brain.

PubMed

Roussigne, Myriam; Blader, Patrick; Wilson, Stephen W

2012-03-01

How does left-right asymmetry develop in the brain and how does the resultant asymmetric circuitry impact on brain function and lateralized behaviors? By enabling scientists to address these questions at the levels of genes, neurons, circuitry and behavior,the zebrafish model system provides a route to resolve the complexity of brain lateralization. In this review, we present the progress made towards characterizing the nature of the gene networks and the sequence of morphogenetic events involved in the asymmetric development of zebrafish epithalamus. In an attempt to integrate the recent extensive knowledge into a working model and to identify the future challenges,we discuss how insights gained at a cellular/developmental level can be linked to the data obtained at a molecular/genetic level. Finally, we present some evolutionary thoughts and discuss how significant discoveries made in zebrafish should provide entry points to better understand the evolutionary origins of brain lateralization.

Integrative Biological Analysis For Neuropsychopharmacology

PubMed Central

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 studes that yield insights based on integrated analyses promise to deliver new therapeutic targets and biomarkers for personalized medicine. PMID:23800968

Your perspective and my benefit: multiple lesion models of self-other integration strategies during social bargaining.

PubMed

Melloni, Margherita; Billeke, Pablo; Baez, Sandra; Hesse, Eugenia; de la Fuente, Laura; Forno, Gonzalo; Birba, Agustina; García-Cordero, Indira; Serrano, Cecilia; Plastino, Angelo; Slachevsky, Andrea; Huepe, David; Sigman, Mariano; Manes, Facundo; García, Adolfo M; Sedeño, Lucas; Ibáñez, Agustín

2016-11-01

Recursive social decision-making requires the use of flexible, context-sensitive long-term strategies for negotiation. To succeed in social bargaining, participants' own perspectives must be dynamically integrated with those of interactors to maximize self-benefits and adapt to the other's preferences, respectively. This is a prerequisite to develop a successful long-term self-other integration strategy. While such form of strategic interaction is critical to social decision-making, little is known about its neurocognitive correlates. To bridge this gap, we analysed social bargaining behaviour in relation to its structural neural correlates, ongoing brain dynamics (oscillations and related source space), and functional connectivity signatures in healthy subjects and patients offering contrastive lesion models of neurodegeneration and focal stroke: behavioural variant frontotemporal dementia, Alzheimer's disease, and frontal lesions. All groups showed preserved basic bargaining indexes. However, impaired self-other integration strategy was found in patients with behavioural variant frontotemporal dementia and frontal lesions, suggesting that social bargaining critically depends on the integrity of prefrontal regions. Also, associations between behavioural performance and data from voxel-based morphometry and voxel-based lesion-symptom mapping revealed a critical role of prefrontal regions in value integration and strategic decisions for self-other integration strategy. Furthermore, as shown by measures of brain dynamics and related sources during the task, the self-other integration strategy was predicted by brain anticipatory activity (alpha/beta oscillations with sources in frontotemporal regions) associated with expectations about others' decisions. This pattern was reduced in all clinical groups, with greater impairments in behavioural variant frontotemporal dementia and frontal lesions than Alzheimer's disease. Finally, connectivity analysis from functional magnetic resonance imaging evidenced a fronto-temporo-parietal network involved in successful self-other integration strategy, with selective compromise of long-distance connections in frontal disorders. In sum, this work provides unprecedented evidence of convergent behavioural and neurocognitive signatures of strategic social bargaining in different lesion models. Our findings offer new insights into the critical roles of prefrontal hubs and associated temporo-parietal networks for strategic social negotiation. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The neural correlates of obsessive-compulsive disorder: a multimodal perspective.

PubMed

Moreira, P S; Marques, P; Soriano-Mas, C; Magalhães, R; Sousa, N; Soares, J M; Morgado, P

2017-08-29

Obsessive-compulsive disorder (OCD) is one of the most debilitating psychiatric conditions. An extensive body of the literature has described some of the neurobiological mechanisms underlying the core manifestations of the disorder. Nevertheless, most reports have focused on individual modalities of structural/functional brain alterations, mainly through targeted approaches, thus possibly precluding the power of unbiased exploratory approaches. Eighty subjects (40 OCD and 40 healthy controls) participated in a multimodal magnetic resonance imaging (MRI) investigation, integrating structural and functional data. Voxel-based morphometry analysis was conducted to compare between-group volumetric differences. The whole-brain functional connectome, derived from resting-state functional connectivity (FC), was analyzed with the network-based statistic methodology. Results from structural and functional analysis were integrated in mediation models. OCD patients revealed volumetric reductions in the right superior temporal sulcus. Patients had significantly decreased FC in two distinct subnetworks: the first, involving the orbitofrontal cortex, temporal poles and the subgenual anterior cingulate cortex; the second, comprising the lingual and postcentral gyri. On the opposite, a network formed by connections between thalamic and occipital regions had significantly increased FC in patients. Integrative models revealed direct and indirect associations between volumetric alterations and FC networks. This study suggests that OCD patients display alterations in brain structure and FC, involving complex networks of brain regions. Furthermore, we provided evidence for direct and indirect associations between structural and functional alterations representing complex patterns of interactions between separate brain regions, which may be of upmost relevance for explaining the pathophysiology of the disorder.

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.

Lysophosphatidic acid receptor, LPA6, regulates endothelial blood-brain barrier function: Implication for hepatic encephalopathy.

PubMed

Masago, Kayo; Kihara, Yasuyuki; Yanagida, Keisuke; Hamano, Fumie; Nakagawa, Shinsuke; Niwa, Masami; Shimizu, Takao

2018-07-02

Cerebral edema is a life-threatening neurological condition characterized by brain swelling due to the accumulation of excess fluid both intracellularly and extracellularly. Fulminant hepatic failure (FHF) develops cerebral edema by disrupting blood-brain barrier (BBB). However, the mechanisms by which mediator induces brain edema in FHF remain to be elucidated. Here, we assessed a linkage between brain edema and lysophosphatidic acid (LPA) signaling by utilizing an animal model of FHF and in vitro BBB model. Azoxymethane-treated mice developed FHF and hepatic encephalopathy, associated with higher autotaxin (ATX) activities in serum than controls. Using in vitro BBB model, LPA disrupted the structural integrity of tight junction proteins including claudin-5, occludin, and ZO-1. Furthermore, LPA decreased transendothelial electrical resistances in in vitro BBB model, and induced cell contraction in brain endothelial monolayer cultures, both being inhibited by a Rho-associated protein kinase inhibitor, Y-27632. The brain capillary endothelial cells predominantly expressed LPA 6 mRNA, whose knockdown blocked the LPA-induced endothelial cell contraction. Taken together, the up-regulation of serum ATX in hepatic encephalopathy may activate the LPA-LPA 6 -G 12/13 -Rho pathway in brain capillary endothelial cells, leading to enhancement of BBB permeability and brain edema. Copyright © 2018 Elsevier Inc. All rights reserved.

The multisensory brain and its ability to learn music.

PubMed

Zimmerman, Emily; Lahav, Amir

2012-04-01

Playing a musical instrument requires a complex skill set that depends on the brain's ability to quickly integrate information from multiple senses. It has been well documented that intensive musical training alters brain structure and function within and across multisensory brain regions, supporting the experience-dependent plasticity model. Here, we argue that this experience-dependent plasticity occurs because of the multisensory nature of the brain and may be an important contributing factor to musical learning. This review highlights key multisensory regions within the brain and discusses their role in the context of music learning and rehabilitation. © 2012 New York Academy of Sciences.

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

Computer-Based Learning: Graphical Integration of Whole and Sectional Neuroanatomy Improves Long-Term Retention

PubMed Central

Naaz, Farah; Chariker, Julia H.; Pani, John R.

2013-01-01

A study was conducted to test the hypothesis that instruction with graphically integrated representations of whole and sectional neuroanatomy is especially effective for learning to recognize neural structures in sectional imagery (such as MRI images). Neuroanatomy was taught to two groups of participants using computer graphical models of the human brain. Both groups learned whole anatomy first with a three-dimensional model of the brain. One group then learned sectional anatomy using two-dimensional sectional representations, with the expectation that there would be transfer of learning from whole to sectional anatomy. The second group learned sectional anatomy by moving a virtual cutting plane through the three-dimensional model. In tests of long-term retention of sectional neuroanatomy, the group with graphically integrated representation recognized more neural structures that were known to be challenging to learn. This study demonstrates the use of graphical representation to facilitate a more elaborated (deeper) understanding of complex spatial relations. PMID:24563579

Hydrophilic bile acids protect human blood-brain barrier endothelial cells from disruption by unconjugated bilirubin: an in vitro study

PubMed Central

Palmela, Inês; Correia, Leonor; Silva, Rui F. M.; Sasaki, Hiroyuki; Kim, Kwang S.; Brites, Dora; Brito, Maria A.

2015-01-01

Ursodeoxycholic acid and its main conjugate glycoursodeoxycholic acid are bile acids with neuroprotective properties. Our previous studies demonstrated their anti-apoptotic, anti-inflammatory, and antioxidant properties in neural cells exposed to elevated levels of unconjugated bilirubin (UCB) as in severe jaundice. In a simplified model of the blood-brain barrier, formed by confluent monolayers of a cell line of human brain microvascular endothelial cells, UCB has shown to induce caspase-3 activation and cell death, as well as interleukin-6 release and a loss of blood-brain barrier integrity. Here, we tested the preventive and restorative effects of these bile acids regarding the disruption of blood-brain barrier properties by UCB in in vitro conditions mimicking severe neonatal hyperbilirubinemia and using the same experimental blood-brain barrier model. Both bile acids reduced the apoptotic cell death induced by UCB, but only glycoursodeoxycholic acid significantly counteracted caspase-3 activation. Bile acids also prevented the upregulation of interleukin-6 mRNA, whereas only ursodeoxycholic acid abrogated cytokine release. Regarding barrier integrity, only ursodeoxycholic acid abrogated UCB-induced barrier permeability. Better protective effects were obtained by bile acid pre-treatment, but a strong efficacy was still observed by their addition after UCB treatment. Finally, both bile acids showed ability to cross confluent monolayers of human brain microvascular endothelial cells in a time-dependent manner. Collectively, data disclose a therapeutic time-window for preventive and restorative effects of ursodeoxycholic acid and glycoursodeoxycholic acid against UCB-induced blood-brain barrier disruption and damage to human brain microvascular endothelial cells. PMID:25821432

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

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.

Lateral Information Processing by Spiking Neurons: A Theoretical Model of the Neural Correlate of Consciousness

PubMed Central

Ebner, Marc; Hameroff, Stuart

2011-01-01

Cognitive brain functions, for example, sensory perception, motor control and learning, are understood as computation by axonal-dendritic chemical synapses in networks of integrate-and-fire neurons. Cognitive brain functions may occur either consciously or nonconsciously (on “autopilot”). Conscious cognition is marked by gamma synchrony EEG, mediated largely by dendritic-dendritic gap junctions, sideways connections in input/integration layers. Gap-junction-connected neurons define a sub-network within a larger neural network. A theoretical model (the “conscious pilot”) suggests that as gap junctions open and close, a gamma-synchronized subnetwork, or zone moves through the brain as an executive agent, converting nonconscious “auto-pilot” cognition to consciousness, and enhancing computation by coherent processing and collective integration. In this study we implemented sideways “gap junctions” in a single-layer artificial neural network to perform figure/ground separation. The set of neurons connected through gap junctions form a reconfigurable resistive grid or sub-network zone. In the model, outgoing spikes are temporally integrated and spatially averaged using the fixed resistive grid set up by neurons of similar function which are connected through gap-junctions. This spatial average, essentially a feedback signal from the neuron's output, determines whether particular gap junctions between neurons will open or close. Neurons connected through open gap junctions synchronize their output spikes. We have tested our gap-junction-defined sub-network in a one-layer neural network on artificial retinal inputs using real-world images. Our system is able to perform figure/ground separation where the laterally connected sub-network of neurons represents a perceived object. Even though we only show results for visual stimuli, our approach should generalize to other modalities. The system demonstrates a moving sub-network zone of synchrony, within which the contents of perception are represented and contained. This mobile zone can be viewed as a model of the neural correlate of consciousness in the brain. PMID:22046178

Lateral information processing by spiking neurons: a theoretical model of the neural correlate of consciousness.

PubMed

Ebner, Marc; Hameroff, Stuart

2011-01-01

Cognitive brain functions, for example, sensory perception, motor control and learning, are understood as computation by axonal-dendritic chemical synapses in networks of integrate-and-fire neurons. Cognitive brain functions may occur either consciously or nonconsciously (on "autopilot"). Conscious cognition is marked by gamma synchrony EEG, mediated largely by dendritic-dendritic gap junctions, sideways connections in input/integration layers. Gap-junction-connected neurons define a sub-network within a larger neural network. A theoretical model (the "conscious pilot") suggests that as gap junctions open and close, a gamma-synchronized subnetwork, or zone moves through the brain as an executive agent, converting nonconscious "auto-pilot" cognition to consciousness, and enhancing computation by coherent processing and collective integration. In this study we implemented sideways "gap junctions" in a single-layer artificial neural network to perform figure/ground separation. The set of neurons connected through gap junctions form a reconfigurable resistive grid or sub-network zone. In the model, outgoing spikes are temporally integrated and spatially averaged using the fixed resistive grid set up by neurons of similar function which are connected through gap-junctions. This spatial average, essentially a feedback signal from the neuron's output, determines whether particular gap junctions between neurons will open or close. Neurons connected through open gap junctions synchronize their output spikes. We have tested our gap-junction-defined sub-network in a one-layer neural network on artificial retinal inputs using real-world images. Our system is able to perform figure/ground separation where the laterally connected sub-network of neurons represents a perceived object. Even though we only show results for visual stimuli, our approach should generalize to other modalities. The system demonstrates a moving sub-network zone of synchrony, within which the contents of perception are represented and contained. This mobile zone can be viewed as a model of the neural correlate of consciousness in the brain.

The promises and pitfalls of applying computational models to neurological and psychiatric disorders.

PubMed

Teufel, Christoph; Fletcher, Paul C

2016-10-01

Computational models have become an integral part of basic neuroscience and have facilitated some of the major advances in the field. More recently, such models have also been applied to the understanding of disruptions in brain function. In this review, using examples and a simple analogy, we discuss the potential for computational models to inform our understanding of brain function and dysfunction. We argue that they may provide, in unprecedented detail, an understanding of the neurobiological and mental basis of brain disorders and that such insights will be key to progress in diagnosis and treatment. However, there are also potential problems attending this approach. We highlight these and identify simple principles that should always govern the use of computational models in clinical neuroscience, noting especially the importance of a clear specification of a model's purpose and of the mapping between mathematical concepts and reality. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain.

Mixed oligomers and monomeric amyloid-β disrupts endothelial cells integrity and reduces monomeric amyloid-β transport across hCMEC/D3 cell line as an in vitro blood-brain barrier model.

PubMed

Qosa, Hisham; LeVine, Harry; Keller, Jeffrey N; Kaddoumi, Amal

2014-09-01

Senile amyloid plaques are one of the diagnostic hallmarks of Alzheimer's disease (AD). However, the severity of clinical symptoms of AD is weakly correlated with the plaque load. AD symptoms severity is reported to be more strongly correlated with the level of soluble amyloid-β (Aβ) assemblies. Formation of soluble Aβ assemblies is stimulated by monomeric Aβ accumulation in the brain, which has been related to its faulty cerebral clearance. Studies tend to focus on the neurotoxicity of specific Aβ species. There are relatively few studies investigating toxic effects of Aβ on the endothelial cells of the blood-brain barrier (BBB). We hypothesized that a soluble Aβ pool more closely resembling the in vivo situation composed of a mixture of Aβ40 monomer and Aβ42 oligomer would exert higher toxicity against hCMEC/D3 cells as an in vitro BBB model than either component alone. We observed that, in addition to a disruptive effect on the endothelial cells integrity due to enhancement of the paracellular permeability of the hCMEC/D3 monolayer, the Aβ mixture significantly decreased monomeric Aβ transport across the cell culture model. Consistent with its effect on Aβ transport, Aβ mixture treatment for 24h resulted in LRP1 down-regulation and RAGE up-regulation in hCMEC/D3 cells. The individual Aβ species separately failed to alter Aβ clearance or the cell-based BBB model integrity. Our study offers, for the first time, evidence that a mixture of soluble Aβ species, at nanomolar concentrations, disrupts endothelial cells integrity and its own transport across an in vitro model of the BBB. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

Model-based functional neuroimaging using dynamic neural fields: An integrative cognitive neuroscience approach

PubMed Central

Wijeakumar, Sobanawartiny; Ambrose, Joseph P.; Spencer, John P.; Curtu, Rodica

2017-01-01

A fundamental challenge in cognitive neuroscience is to develop theoretical frameworks that effectively span the gap between brain and behavior, between neuroscience and psychology. Here, we attempt to bridge this divide by formalizing an integrative cognitive neuroscience approach using dynamic field theory (DFT). We begin by providing an overview of how DFT seeks to understand the neural population dynamics that underlie cognitive processes through previous applications and comparisons to other modeling approaches. We then use previously published behavioral and neural data from a response selection Go/Nogo task as a case study for model simulations. Results from this study served as the ‘standard’ for comparisons with a model-based fMRI approach using dynamic neural fields (DNF). The tutorial explains the rationale and hypotheses involved in the process of creating the DNF architecture and fitting model parameters. Two DNF models, with similar structure and parameter sets, are then compared. Both models effectively simulated reaction times from the task as we varied the number of stimulus-response mappings and the proportion of Go trials. Next, we directly simulated hemodynamic predictions from the neural activation patterns from each model. These predictions were tested using general linear models (GLMs). Results showed that the DNF model that was created by tuning parameters to capture simultaneously trends in neural activation and behavioral data quantitatively outperformed a Standard GLM analysis of the same dataset. Further, by using the GLM results to assign functional roles to particular clusters in the brain, we illustrate how DNF models shed new light on the neural populations’ dynamics within particular brain regions. Thus, the present study illustrates how an interactive cognitive neuroscience model can be used in practice to bridge the gap between brain and behavior. PMID:29118459

Congruent and Opposite Neurons as Partners in Multisensory Integration and Segregation

NASA Astrophysics Data System (ADS)

Zhang, Wen-Hao; Wong, K. Y. Michael; Wang, He; Wu, Si

Experiments revealed that where visual and vestibular cues are integrated to infer heading direction in the brain, there are two types of neurons with roughly the same number. Respectively, congruent and opposite cells respond similarly and oppositely to visual and vestibular cues. Congruent neurons are known to be responsible for cue integration, but the computational role of opposite neurons remains largely unknown. We propose that opposite neurons may serve to encode the disparity information between cues necessary for multisensory segregation. We build a computational model composed of two reciprocally coupled modules, each consisting of groups of congruent and opposite neurons. Our model reproduces the characteristics of congruent and opposite neurons, and demonstrates that in each module, congruent and opposite neurons can jointly achieve optimal multisensory information integration and segregation. This study sheds light on our understanding of how the brain implements optimal multisensory integration and segregation concurrently in a distributed manner. This work is supported by the Research Grants Council of Hong Kong (N _HKUST606/12, 605813, and 16322616) and National Basic Research Program of China (2014CB846101) and the Natural Science Foundation of China (31261160495).

Rapamycin alleviates brain edema after focal cerebral ischemia reperfusion in rats.

PubMed

Guo, Wei; Feng, Guoying; Miao, Yanying; Liu, Guixiang; Xu, Chunsheng

2014-06-01

Brain edema is a major consequence of cerebral ischemia reperfusion. However, few effective therapeutic options are available for retarding the brain edema progression after cerebral ischemia. Recently, rapamycin has been shown to produce neuroprotective effects in rats after cerebral ischemia reperfusion. Whether rapamycin could alleviate this brain edema injury is still unclear. In this study, the rat stroke model was induced by a 1-h left transient middle cerebral artery occlusion using an intraluminal filament, followed by 48 h of reperfusion. The effects of rapamycin (250 μg/kg body weight, intraperitoneal; i.p.) on brain edema progression were evaluated. The results showed that rapamycin treatment significantly reduced the infarct volume, the water content of the brain tissue and the Evans blue extravasation through the blood-brain barrier (BBB). Rapamycin treatment could improve histological appearance of the brain tissue, increased the capillary lumen space and maintain the integrity of BBB. Rapamycin also inhibited matrix metalloproteinase 9 (MMP9) and aquaporin 4 (AQP4) expression. These data imply that rapamycin could improve brain edema progression after reperfusion injury through maintaining BBB integrity and inhibiting MMP9 and AQP4 expression. The data of this study provide a new possible approach for improving brain edema after cerebral ischemia reperfusion by administration of rapamycin.

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.

Amphiphilic HPMA-LMA copolymers increase the transport of Rhodamine 123 across a BBB model without harming its barrier integrity.

PubMed

Hemmelmann, Mirjam; Metz, Verena V; Koynov, Kaloian; Blank, Kerstin; Postina, Rolf; Zentel, Rudolf

2012-10-28

The successful non-invasive treatment of diseases associated with the central nervous system (CNS) is generally limited by poor brain permeability of various developed drugs. The blood-brain barrier (BBB) prevents the passage of therapeutics to their site of action. Polymeric drug delivery systems are promising solutions to effectively transport drugs into the brain. We recently showed that amphiphilic random copolymers based on the hydrophilic p(N-(2-hydroxypropyl)-methacrylamide), pHPMA, possessing randomly distributed hydrophobic p(laurylmethacrylate), pLMA, are able to mediate delivery of domperidone into the brain of mice in vivo. To gain further insight into structure-property relations, a library of carefully designed polymers based on p(HPMA) and p(LMA) was synthesized and tested applying an in vitro BBB model which consisted of human brain microvascular endothelial cells (HBMEC). Our model drug Rhodamine 123 (Rh123) exhibits, like domperidone, a low brain permeability since both substances are recognized by efflux transporters at the BBB. Transport studies investigating the impact of the polymer architecture in relation to the content of hydrophobic LMA revealed that random p(HPMA)-co-p(LMA) having 10mol% LMA is the most auspicious system. The copolymer significantly increased the permeability of Rh123 across the HBMEC monolayer whereas transcytosis of the polymer was very low. Further investigations on the mechanism of transport showed that integrity and barrier function of the BBB model were not harmed by the polymer. According to our results, p(HPMA)-co-p(LMA) copolymers are a promising delivery system for neurological therapeutics and their application might open alternative treatment strategies. Copyright © 2012 Elsevier B.V. All rights reserved.

Brain coordination dynamics: True and false faces of phase synchrony and metastability

PubMed Central

Tognoli, Emmanuelle; Kelso, J.A. Scott

2009-01-01

Understanding the coordination of multiple parts in a complex system such as the brain is a fundamental challenge. We present a theoretical model of cortical coordination dynamics that shows how brain areas may cooperate (integration) and at the same time retain their functional specificity (segregation). This model expresses a range of desirable properties that the brain is known to exhibit, including self-organization, multi-functionality, metastability and switching. Empirically, the model motivates a thorough investigation of collective phase relationships among brain oscillations in neurophysiological data. The most serious obstacle to interpreting coupled oscillations as genuine evidence of inter-areal coordination in the brain stems from volume conduction of electrical fields. Spurious coupling due to volume conduction gives rise to zero-lag (inphase) and antiphase synchronization whose magnitude and persistence obscure the subtle expression of real synchrony. Through forward modeling and the help of a novel colorimetric method, we show how true synchronization can be deciphered from continuous EEG patterns. Developing empirical efforts along the lines of continuous EEG analysis constitutes a major response to the challenge of understanding how different brain areas work together. Key predictions of cortical coordination dynamics can now be tested thereby revealing the essential modus operandi of the intact living brain. PMID:18938209

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

Brain-mapping projects using the common marmoset.

PubMed

Okano, Hideyuki; Mitra, Partha

2015-04-01

Globally, there is an increasing interest in brain-mapping projects, including the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative project in the USA, the Human Brain Project (HBP) in Europe, and the Brain Mapping by Integrated Neurotechnologies for Disease Studies (Brain/MINDS) project in Japan. These projects aim to map the structure and function of neuronal circuits to ultimately understand the vast complexity of the human brain. Brain/MINDS is focused on structural and functional mapping of the common marmoset (Callithrix jacchus) brain. This non-human primate has numerous advantages for brain mapping, including a well-developed frontal cortex and a compact brain size, as well as the availability of transgenic technologies. In the present review article, we discuss strategies for structural and functional mapping of the marmoset brain and the relation of the common marmoset to other animals models. Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Driving the brain towards creativity and intelligence: A network control theory analysis.

PubMed

Kenett, Yoed N; Medaglia, John D; Beaty, Roger E; Chen, Qunlin; Betzel, Richard F; Thompson-Schill, Sharon L; Qiu, Jiang

2018-01-04

High-level cognitive constructs, such as creativity and intelligence, entail complex and multiple processes, including cognitive control processes. Recent neurocognitive research on these constructs highlight the importance of dynamic interaction across neural network systems and the role of cognitive control processes in guiding such a dynamic interaction. How can we quantitatively examine the extent and ways in which cognitive control contributes to creativity and intelligence? To address this question, we apply a computational network control theory (NCT) approach to structural brain imaging data acquired via diffusion tensor imaging in a large sample of participants, to examine how NCT relates to individual differences in distinct measures of creative ability and intelligence. Recent application of this theory at the neural level is built on a model of brain dynamics, which mathematically models patterns of inter-region activity propagated along the structure of an underlying network. The strength of this approach is its ability to characterize the potential role of each brain region in regulating whole-brain network function based on its anatomical fingerprint and a simplified model of node dynamics. We find that intelligence is related to the ability to "drive" the brain system into easy to reach neural states by the right inferior parietal lobe and lower integration abilities in the left retrosplenial cortex. We also find that creativity is related to the ability to "drive" the brain system into difficult to reach states by the right dorsolateral prefrontal cortex (inferior frontal junction) and higher integration abilities in sensorimotor areas. Furthermore, we found that different facets of creativity-fluency, flexibility, and originality-relate to generally similar but not identical network controllability processes. We relate our findings to general theories on intelligence and creativity. Copyright © 2018 Elsevier Ltd. All rights reserved.

Resolving the neural dynamics of visual and auditory scene processing in the human brain: a methodological approach

PubMed Central

Teng, Santani

2017-01-01

In natural environments, visual and auditory stimulation elicit responses across a large set of brain regions in a fraction of a second, yielding representations of the multimodal scene and its properties. The rapid and complex neural dynamics underlying visual and auditory information processing pose major challenges to human cognitive neuroscience. Brain signals measured non-invasively are inherently noisy, the format of neural representations is unknown, and transformations between representations are complex and often nonlinear. Further, no single non-invasive brain measurement technique provides a spatio-temporally integrated view. In this opinion piece, we argue that progress can be made by a concerted effort based on three pillars of recent methodological development: (i) sensitive analysis techniques such as decoding and cross-classification, (ii) complex computational modelling using models such as deep neural networks, and (iii) integration across imaging methods (magnetoencephalography/electroencephalography, functional magnetic resonance imaging) and models, e.g. using representational similarity analysis. We showcase two recent efforts that have been undertaken in this spirit and provide novel results about visual and auditory scene analysis. Finally, we discuss the limits of this perspective and sketch a concrete roadmap for future research. This article is part of the themed issue ‘Auditory and visual scene analysis’. PMID:28044019

New experimental models of the blood-brain barrier for CNS drug discovery

PubMed Central

Kaisar, Mohammad A.; Sajja, Ravi K.; Prasad, Shikha; Abhyankar, Vinay V.; Liles, Taylor; Cucullo, Luca

2017-01-01

Introduction The blood-brain barrier (BBB) is a dynamic biological interface which actively controls the passage of substances between the blood and the central nervous system (CNS). From a biological and functional standpoint, the BBB plays a crucial role in maintaining brain homeostasis inasmuch that deterioration of BBB functions are prodromal to many CNS disorders. Conversely, the BBB hinders the delivery of drugs targeting the brain to treat a variety of neurological diseases. Area covered This article reviews recent technological improvements and innovation in the field of BBB modeling including static and dynamic cell-based platforms, microfluidic systems and the use of stem cells and 3D printing technologies. Additionally, the authors laid out a roadmap for the integration of microfluidics and stem cell biology as a holistic approach for the development of novel in vitro BBB platforms. Expert opinion Development of effective CNS drugs has been hindered by the lack of reliable strategies to mimic the BBB and cerebrovascular impairments in vitro. Technological advancements in BBB modeling have fostered the development of highly integrative and quasi- physiological in vitro platforms to support the process of drug discovery. These advanced in vitro tools are likely to further current understanding of the cerebrovascular modulatory mechanisms. PMID:27782770

Resolving the neural dynamics of visual and auditory scene processing in the human brain: a methodological approach.

PubMed

Cichy, Radoslaw Martin; Teng, Santani

2017-02-19

In natural environments, visual and auditory stimulation elicit responses across a large set of brain regions in a fraction of a second, yielding representations of the multimodal scene and its properties. The rapid and complex neural dynamics underlying visual and auditory information processing pose major challenges to human cognitive neuroscience. Brain signals measured non-invasively are inherently noisy, the format of neural representations is unknown, and transformations between representations are complex and often nonlinear. Further, no single non-invasive brain measurement technique provides a spatio-temporally integrated view. In this opinion piece, we argue that progress can be made by a concerted effort based on three pillars of recent methodological development: (i) sensitive analysis techniques such as decoding and cross-classification, (ii) complex computational modelling using models such as deep neural networks, and (iii) integration across imaging methods (magnetoencephalography/electroencephalography, functional magnetic resonance imaging) and models, e.g. using representational similarity analysis. We showcase two recent efforts that have been undertaken in this spirit and provide novel results about visual and auditory scene analysis. Finally, we discuss the limits of this perspective and sketch a concrete roadmap for future research.This article is part of the themed issue 'Auditory and visual scene analysis'. © 2017 The Authors.

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.

Brain White Matter Tract Integrity and Cognitive Abilities in Community-Dwelling Older People: The Lothian Birth Cohort, 1936

PubMed Central

2013-01-01

Objective: The present study investigates associations between brain white matter tract integrity and cognitive abilities in community-dwelling older people (N = 655). We explored two potential confounds of white matter tract−cognition associations in later life: (a) whether the associations between tracts and specific cognitive abilities are accounted for by general cognitive ability (g); and (b) how the presence of atrophy and white matter lesions affect these associations. Method: Tract integrity was determined using quantitative diffusion magnetic resonance imaging tractography (tract-averaged fractional anisotropy [FA]). Using confirmatory factor analysis, we compared first-order and bifactor models to investigate whether specific tract-ability associations were accounted for by g. Results: Significant associations were found between g and FA in bilateral anterior thalamic radiations (r range: .16−.18, p < .01), uncinate (r range: .19−.26, p < .001), arcuate fasciculi (r range: .11−.12, p < .05), and the splenium of corpus callosum (r = .14, p < .01). After controlling for g within the bifactor model, some significant specific cognitive domain associations remained. Results also suggest that the primary effects of controlling for whole brain integrity were on g associations, not specific abilities. Conclusion: Results suggest that g accounts for most of, but not all, the tract−cognition associations in the current data. When controlling for age-related overall brain structural changes, only minor attenuations of the tract−cognition associations were found, and these were primarily with g. In totality, the results highlight the importance of controlling for g when investigating associations between specific cognitive abilities and neuropsychology variables. PMID:23937481

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

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.

AlzPharm: integration of neurodegeneration data using RDF.

PubMed

Lam, Hugo Y K; Marenco, Luis; Clark, Tim; Gao, Yong; Kinoshita, June; Shepherd, Gordon; Miller, Perry; Wu, Elizabeth; Wong, Gwendolyn T; Liu, Nian; Crasto, Chiquito; Morse, Thomas; Stephens, Susie; Cheung, Kei-Hoi

2007-05-09

Neuroscientists often need to access a wide range of data sets distributed over the Internet. These data sets, however, are typically neither integrated nor interoperable, resulting in a barrier to answering complex neuroscience research questions. Domain ontologies can enable the querying heterogeneous data sets, but they are not sufficient for neuroscience since the data of interest commonly span multiple research domains. To this end, e-Neuroscience seeks to provide an integrated platform for neuroscientists to discover new knowledge through seamless integration of the very diverse types of neuroscience data. Here we present a Semantic Web approach to building this e-Neuroscience framework by using the Resource Description Framework (RDF) and its vocabulary description language, RDF Schema (RDFS), as a standard data model to facilitate both representation and integration of the data. We have constructed a pilot ontology for BrainPharm (a subset of SenseLab) using RDFS and then converted a subset of the BrainPharm data into RDF according to the ontological structure. We have also integrated the converted BrainPharm data with existing RDF hypothesis and publication data from a pilot version of SWAN (Semantic Web Applications in Neuromedicine). Our implementation uses the RDF Data Model in Oracle Database 10g release 2 for data integration, query, and inference, while our Web interface allows users to query the data and retrieve the results in a convenient fashion. Accessing and integrating biomedical data which cuts across multiple disciplines will be increasingly indispensable and beneficial to neuroscience researchers. The Semantic Web approach we undertook has demonstrated a promising way to semantically integrate data sets created independently. It also shows how advanced queries and inferences can be performed over the integrated data, which are hard to achieve using traditional data integration approaches. Our pilot results suggest that our Semantic Web approach is suitable for realizing e-Neuroscience and generic enough to be applied in other biomedical fields.

AlzPharm: integration of neurodegeneration data using RDF

PubMed Central

Lam, Hugo YK; Marenco, Luis; Clark, Tim; Gao, Yong; Kinoshita, June; Shepherd, Gordon; Miller, Perry; Wu, Elizabeth; Wong, Gwendolyn T; Liu, Nian; Crasto, Chiquito; Morse, Thomas; Stephens, Susie; Cheung, Kei-Hoi

2007-01-01

Background Neuroscientists often need to access a wide range of data sets distributed over the Internet. These data sets, however, are typically neither integrated nor interoperable, resulting in a barrier to answering complex neuroscience research questions. Domain ontologies can enable the querying heterogeneous data sets, but they are not sufficient for neuroscience since the data of interest commonly span multiple research domains. To this end, e-Neuroscience seeks to provide an integrated platform for neuroscientists to discover new knowledge through seamless integration of the very diverse types of neuroscience data. Here we present a Semantic Web approach to building this e-Neuroscience framework by using the Resource Description Framework (RDF) and its vocabulary description language, RDF Schema (RDFS), as a standard data model to facilitate both representation and integration of the data. Results We have constructed a pilot ontology for BrainPharm (a subset of SenseLab) using RDFS and then converted a subset of the BrainPharm data into RDF according to the ontological structure. We have also integrated the converted BrainPharm data with existing RDF hypothesis and publication data from a pilot version of SWAN (Semantic Web Applications in Neuromedicine). Our implementation uses the RDF Data Model in Oracle Database 10g release 2 for data integration, query, and inference, while our Web interface allows users to query the data and retrieve the results in a convenient fashion. Conclusion Accessing and integrating biomedical data which cuts across multiple disciplines will be increasingly indispensable and beneficial to neuroscience researchers. The Semantic Web approach we undertook has demonstrated a promising way to semantically integrate data sets created independently. It also shows how advanced queries and inferences can be performed over the integrated data, which are hard to achieve using traditional data integration approaches. Our pilot results suggest that our Semantic Web approach is suitable for realizing e-Neuroscience and generic enough to be applied in other biomedical fields. PMID:17493287

Multicolor Fluorescence Imaging of Traumatic Brain Injury in a Cryolesion Mouse Model

PubMed Central

2012-01-01

Traumatic brain injury is characterized by initial tissue damage, which then can lead to secondary processes such as cell death and blood-brain-barrier disruption. Clinical and preclinical studies of traumatic brain injury typically employ anatomical imaging techniques and there is a need for new molecular imaging methods that provide complementary biochemical information. Here, we assess the ability of a targeted, near-infrared fluorescent probe, named PSS-794, to detect cell death in a brain cryolesion mouse model that replicates certain features of traumatic brain injury. In short, the model involves brief contact of a cold rod to the head of a living, anesthetized mouse. Using noninvasive whole-body fluorescence imaging, PSS-794 permitted visualization of the cryolesion in the living animal. Ex vivo imaging and histological analysis confirmed PSS-794 localization to site of brain cell death. The nontargeted, deep-red Tracer-653 was validated as a tracer dye for monitoring blood-brain-barrier disruption, and a binary mixture of PSS-794 and Tracer-653 was employed for multicolor imaging of cell death and blood-brain-barrier permeability in a single animal. The imaging data indicates that at 3 days after brain cryoinjury the amount of cell death had decreased significantly, but the integrity of the blood-brain-barrier was still impaired; at 7 days, the blood-brain-barrier was still three times more permeable than before cryoinjury. PMID:22860222

Transcallosal transfer of information and functional asymmetry of the human brain.

PubMed

Nowicka, Anna; Tacikowski, Pawel

2011-01-01

The corpus callosum is the largest commissure in the brain and acts as a "bridge" of nerve fibres connecting the two cerebral hemispheres. It plays a crucial role in interhemispheric integration and is responsible for normal communication and cooperation between the two hemispheres. Evolutionary pressures guiding brain size are accompanied by reduced interhemispheric and enhanced intrahemispheric connectivity. Some lines of evidence suggest that the speed of transcallosal conduction is limited in large brains (e.g., in humans), thus favouring intrahemispheric processing and brain lateralisation. Patterns of directional symmetry/asymmetry of transcallosal transfer time may be related to the degree of brain lateralisation. Neural network modelling and electrophysiological studies on interhemispheric transmission provide data supporting this supposition.

The Relationship between Simultaneous-Successive Processing and Academic Achievement.

ERIC Educational Resources Information Center

Merritt, Frank M.; McCallum, Steve

The Luria-Das Information Processing Model of human learning holds that information is analysed and coded within the brain in either a simultaneous or a successive fashion. Simultaneous integration refers to the synthesis of separate elements into groups, often with spatial characteristics; successive integration means that information is…

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

Utility of the Croatian translation of the community integration questionnaire-revised in a sample of adults with moderate to severe traumatic brain injury.

PubMed

Tršinski, Dubravko; Tadinac, Meri; Bakran, Žarko; Klepo, Ivana

2018-02-23

To examine the utility of the Community Integration Questionnaire-Revised, translated into Croatian, in a sample of adults with moderate to severe traumatic brain injury. The Community Integration Questionnaire-Revised was administered to a sample of 88 adults with traumatic brain injury and to a control sample matched by gender, age and education. Participants with traumatic brain injury were divided into four subgroups according to injury severity. The internal consistency of the Community Integration Questionnaire-Revised was satisfactory. The differences between the group with traumatic brain injury and the control group were statistically significant for the overall Community Integration Questionnaire-Revised score, as well as for all the subscales apart from the Home Integration subscale. The community Integration Questionnaire-Revised score varied significantly for subgroups with different severity of traumatic brain injury. The results show that the Croatian translation of the Community Integration Questionnaire-Revised is useful in assessing participation in adults with traumatic brain injury and confirm previous findings that severity of injury predicts community integration. Results of the new Electronic Social Networking scale indicate that persons who are more active on electronic social networks report better results for other domains of community integration, especially social activities. Implications for rehabilitation The Croatian translation of the Community Integration Questionnaire-Revised is a valid tool for long-term assessment of participation in various domains in persons with moderate to severe traumatic brain injury Persons with traumatic brain injury who are more active in the use of electronic social networking are also more integrated into social and productivity domains. Targeted training in the use of new technologies could enhance participation after traumatic brain injury.

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.

Computational modeling of brain tumors: discrete, continuum or hybrid?

NASA Astrophysics Data System (ADS)

Wang, Zhihui; Deisboeck, Thomas S.

2008-04-01

In spite of all efforts, patients diagnosed with highly malignant brain tumors (gliomas), continue to face a grim prognosis. Achieving significant therapeutic advances will also require a more detailed quantitative understanding of the dynamic interactions among tumor cells, and between these cells and their biological microenvironment. Data-driven computational brain tumor models have the potential to provide experimental tumor biologists with such quantitative and cost-efficient tools to generate and test hypotheses on tumor progression, and to infer fundamental operating principles governing bidirectional signal propagation in multicellular cancer systems. This review highlights the modeling objectives of and challenges with developing such in silicobrain tumor models by outlining two distinct computational approaches: discrete and continuum, each with representative examples. Future directions of this integrative computational neuro-oncology field, such as hybrid multiscale multiresolution modeling are discussed.

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...

From the left to the right: How the brain compensates progressive loss of language function.

PubMed

Thiel, Alexander; Habedank, Birgit; Herholz, Karl; Kessler, Josef; Winhuisen, Lutz; Haupt, Walter F; Heiss, Wolf-Dieter

2006-07-01

In normal right-handed subjects language production usually is a function oft the left brain hemisphere. Patients with aphasia following brain damage to the left hemisphere have a considerable potential to compensate for the loss of this function. Sometimes, but not always, areas of the right hemisphere which are homologous to language areas of the left hemisphere in normal subjects are successfully employed for compensation but this integration process may need time to develop. We investigated right-handed patients with left hemisphere brain tumors as a model of continuously progressive brain damage to left hemisphere language areas using functional neuroimaging and transcranial magnetic stimulation (TMS) to identify factors which determine successful compensation of lost language function. Only patients with slowly progressing brain lesions recovered right-sided language function as detected by TMS. In patients with rapidly progressive lesions no right-sided language function was found and language performance was linearly correlated with the lateralization of language related brain activation to the left hemisphere. It can thus be concluded that time is the factor which determines successful integration of the right hemisphere into the language network for compensation of lost left hemisphere language function.

Bayesian estimation inherent in a Mexican-hat-type neural network

NASA Astrophysics Data System (ADS)

Takiyama, Ken

2016-05-01

Brain functions, such as perception, motor control and learning, and decision making, have been explained based on a Bayesian framework, i.e., to decrease the effects of noise inherent in the human nervous system or external environment, our brain integrates sensory and a priori information in a Bayesian optimal manner. However, it remains unclear how Bayesian computations are implemented in the brain. Herein, I address this issue by analyzing a Mexican-hat-type neural network, which was used as a model of the visual cortex, motor cortex, and prefrontal cortex. I analytically demonstrate that the dynamics of an order parameter in the model corresponds exactly to a variational inference of a linear Gaussian state-space model, a Bayesian estimation, when the strength of recurrent synaptic connectivity is appropriately stronger than that of an external stimulus, a plausible condition in the brain. This exact correspondence can reveal the relationship between the parameters in the Bayesian estimation and those in the neural network, providing insight for understanding brain functions.

Integration of transcriptomic and cytoarchitectonic data implicates a role for MAOA and TAC1 in the limbic-cortical network.

PubMed

Bludau, Sebastian; Mühleisen, Thomas W; Eickhoff, Simon B; Hawrylycz, Michael J; Cichon, Sven; Amunts, Katrin

2018-06-01

Decoding the chain from genes to cognition requires detailed insights how areas with specific gene activities and microanatomical architectures contribute to brain function and dysfunction. The Allen Human Brain Atlas contains regional gene expression data, while the JuBrain Atlas offers three-dimensional cytoarchitectonic maps reflecting interindividual variability. To date, an integrated framework that combines the analytical benefits of both scientific platforms towards a multi-level brain atlas of adult humans was not available. We have, therefore, developed JuGEx, a new method for integrating tissue transcriptome and cytoarchitectonic segregation. We investigated differential gene expression in two JuBrain areas of the frontal pole that we have structurally and functionally characterized in previous studies. Our results show a significant upregulation of MAOA and TAC1 in the medial area frontopolaris which is a node in the limbic-cortical network and known to be susceptible for gray matter loss and behavioral dysfunction in patients with depression. The MAOA gene encodes an enzyme which is involved in the catabolism of dopamine, norepinephrine, serotonin, and other monoaminergic neurotransmitters. The TAC1 locus generates hormones that play a role in neuron excitations and behavioral responses. Overall, JuGEx provides a new tool for the scientific community that empowers research from basic, cognitive and clinical neuroscience in brain regions and disease models with regard to gene expression.

Exendin-4 inhibits high-altitude cerebral edema by protecting against neurobiological dysfunction

PubMed Central

Sun, Zhong-Lei; Jiang, Xian-Feng; Cheng, Yuan-Chi; Liu, Ying-Fu; Yang, Kai; Zhu, Shuang-Long; Kong, Xian-Bin; Tu, Yue; Bian, Ke-Feng; Liu, Zhen-Lin; Chen, Xu-Yi

2018-01-01

The anti-inflammatory and antioxidant effects of exendin-4 (Ex-4) have been reported previously. However, whether (Ex-4) has anti-inflammatory and antioxidant effects on high-altitude cerebral edema (HACE) remains poorly understood. In this study, two rat models of HACE were established by placing rats in a hypoxic environment with a simulated altitude of either 6000- or 7000-m above sea level (MASL) for 72 hours. An altitude of 7000 MASL with 72-hours of hypoxia was found to be the optimized experimental paradigm for establishing HACE models. Then, in rats where a model of HACE was established by introducing them to a 7000 MASL environment with 72-hours of hypoxia treatment, 2, 10 and, 100 μg of Ex-4 was intraperitoneally administrated. The open field test and tail suspension test were used to test animal behavior. Routine methods were used to detect change in inflammatory cells. Hematoxylin-eosin staining was performed to determine pathological changes to brain tissue. Wet/dry weight ratios were used to measure brain water content. Evans blue leakage was used to determine blood-brain barrier integrity. Enzyme-linked immunosorbent assay (ELISA) was performed to measure markers of inflammation and oxidative stress including superoxide dismutase, glutathione, and malonaldehyde values, as well as interleukin-6, tumor necrosis factor-alpha, cyclic adenosine monophosphate levels in the brain tissue. Western blot analysis was performed to determine the levels of occludin, ZO-1, SOCS-3, vascular endothelial growth factor, EPAC1, nuclear factor-kappa B, and aquaporin-4. Our results demonstrate that Ex-4 preconditioning decreased brain water content, inhibited inflammation and oxidative stress, alleviated brain tissue injury, maintain blood-brain barrier integrity, and effectively improved motor function in rat models of HACE. These findings suggest that Ex-4 exhibits therapeutic potential in the treatment of HACE. PMID:29722317

A mechanical model predicts morphological abnormalities in the developing human brain

NASA Astrophysics Data System (ADS)

Budday, Silvia; Raybaud, Charles; Kuhl, Ellen

2014-07-01

The developing human brain remains one of the few unsolved mysteries of science. Advancements in developmental biology, neuroscience, and medical imaging have brought us closer than ever to understand brain development in health and disease. However, the precise role of mechanics throughout this process remains underestimated and poorly understood. Here we show that mechanical stretch plays a crucial role in brain development. Using the nonlinear field theories of mechanics supplemented by the theory of finite growth, we model the human brain as a living system with a morphogenetically growing outer surface and a stretch-driven growing inner core. This approach seamlessly integrates the two popular but competing hypotheses for cortical folding: axonal tension and differential growth. We calibrate our model using magnetic resonance images from very preterm neonates. Our model predicts that deviations in cortical growth and thickness induce morphological abnormalities. Using the gyrification index, the ratio between the total and exposed surface area, we demonstrate that these abnormalities agree with the classical pathologies of lissencephaly and polymicrogyria. Understanding the mechanisms of cortical folding in the developing human brain has direct implications in the diagnostics and treatment of neurological disorders, including epilepsy, schizophrenia, and autism.

[Establishment of MDCK-pHaMDR cell model and standard operation procedure for assessing blood-brain barrier permeability of chemical components of traditional Chinese medicine].

PubMed

Yang, Yan-Fang; Wu, Ni; Yang, Xiu-Wei

2016-07-01

To establish MDCK-pHaMDR cell model and standard operation procedure for assessing the blood-brain barrier permeability of chemical components of traditional Chinese medicine. MDCK-pHaMDR cell model was evaluated by determining the morphology features, transepithelial electrical resistance, bidirectional transport and intracellular accumulation of Rhodamine 123 and the apparent permeability of positive control drugs caffeine and atenolol. The MDCK-pHaMDR cell model had satisfactory integrity and tightness, and stable expression of P-gp. In addition, the transport results of the positive control drugs were consistent with the reported values in literature. All the parameters tested of the MDCK-pHaMDR cell model were consistent with the requirements, so the model can be used to study the blood-brain barrier permeability of chemical components of traditional Chinese medicine. Copyright© by the Chinese Pharmaceutical Association.

Brain systems underlying susceptibility to helplessness and depression.

PubMed

Shumake, J; Gonzalez-Lima, F

2003-09-01

There has been a relative lack of research into the neurobiological predispositions that confer vulnerability to depression. This article reviews functional brain mappings from a genetic animal model, the congenitally helpless rat, which is predisposed to develop learned helplessness. Neurometabolic findings from this model are integrated with the neuroscientific literature from other animal models of depression as well as depressed humans. Changes in four major brain systems are suggested to underlie susceptibility to helplessness and possibly depression: (a) an unbalanced prefrontal-cingulate cortical system, (b) a dissociated hypothalamic-pituitary-adrenal axis, (c) a dissociated septal-hippocampal system, and (d) a hypoactive brain reward system, as exemplified by a hypermetabolic habenula-interpeduncular nucleus pathway and a hypometabolic ventral tegmental area-striatum pathway. Functional interconnections and causal relationships among these systems are considered and further experiments are suggested, with theoretical attention to how an abnormality in any one system could affect the others.

Comparing the landcapes of common retroviral insertion sites across tumor models

NASA Astrophysics Data System (ADS)

Weishaupt, Holger; Čančer, Matko; Engström, Cristopher; Silvestrov, Sergei; Swartling, Fredrik J.

2017-01-01

Retroviral tagging represents an important technique, which allows researchers to screen for candidate cancer genes. The technique is based on the integration of retroviral sequences into the genome of a host organism, which might then lead to the artificial inhibition or expression of proximal genetic elements. The identification of potential cancer genes in this framework involves the detection of genomic regions (common insertion sites; CIS) which contain a number of such viral integration sites that is greater than expected by chance. During the last two decades, a number of different methods have been discussed for the identification of such loci and the respective techniques have been applied to a variety of different retroviruses and/or tumor models. We have previously established a retrovirus driven brain tumor model and reported the CISs which were found based on a Monte Carlo statistics derived detection paradigm. In this study, we consider a recently proposed alternative graph theory based method for identifying CISs and compare the resulting CIS landscape in our brain tumor dataset to those obtained when using the Monte Carlo approach. Finally, we also employ the graph-based method to compare the CIS landscape in our brain tumor model with those of other published retroviral tumor models.

Server-based Approach to Web Visualization of Integrated Three-dimensional Brain Imaging Data

PubMed Central

Poliakov, Andrew V.; Albright, Evan; Hinshaw, Kevin P.; Corina, David P.; Ojemann, George; Martin, Richard F.; Brinkley, James F.

2005-01-01

The authors describe a client-server approach to three-dimensional (3-D) visualization of neuroimaging data, which enables researchers to visualize, manipulate, and analyze large brain imaging datasets over the Internet. All computationally intensive tasks are done by a graphics server that loads and processes image volumes and 3-D models, renders 3-D scenes, and sends the renderings back to the client. The authors discuss the system architecture and implementation and give several examples of client applications that allow visualization and analysis of integrated language map data from single and multiple patients. PMID:15561787

Combining the boundary shift integral and tensor-based morphometry for brain atrophy estimation

NASA Astrophysics Data System (ADS)

Michalkiewicz, Mateusz; Pai, Akshay; Leung, Kelvin K.; Sommer, Stefan; Darkner, Sune; Sørensen, Lauge; Sporring, Jon; Nielsen, Mads

2016-03-01

Brain atrophy from structural magnetic resonance images (MRIs) is widely used as an imaging surrogate marker for Alzheimers disease. Their utility has been limited due to the large degree of variance and subsequently high sample size estimates. The only consistent and reasonably powerful atrophy estimation methods has been the boundary shift integral (BSI). In this paper, we first propose a tensor-based morphometry (TBM) method to measure voxel-wise atrophy that we combine with BSI. The combined model decreases the sample size estimates significantly when compared to BSI and TBM alone.

Learning Computational Models of Video Memorability from fMRI Brain Imaging.

PubMed

Han, Junwei; Chen, Changyuan; Shao, Ling; Hu, Xintao; Han, Jungong; Liu, Tianming

2015-08-01

Generally, various visual media are unequally memorable by the human brain. This paper looks into a new direction of modeling the memorability of video clips and automatically predicting how memorable they are by learning from brain functional magnetic resonance imaging (fMRI). We propose a novel computational framework by integrating the power of low-level audiovisual features and brain activity decoding via fMRI. Initially, a user study experiment is performed to create a ground truth database for measuring video memorability and a set of effective low-level audiovisual features is examined in this database. Then, human subjects' brain fMRI data are obtained when they are watching the video clips. The fMRI-derived features that convey the brain activity of memorizing videos are extracted using a universal brain reference system. Finally, due to the fact that fMRI scanning is expensive and time-consuming, a computational model is learned on our benchmark dataset with the objective of maximizing the correlation between the low-level audiovisual features and the fMRI-derived features using joint subspace learning. The learned model can then automatically predict the memorability of videos without fMRI scans. Evaluations on publically available image and video databases demonstrate the effectiveness of the proposed framework.

Finite element modeling of human brain response to football helmet impacts.

PubMed

Darling, T; Muthuswamy, J; Rajan, S D

2016-10-01

The football helmet is used to help mitigate the occurrence of impact-related traumatic (TBI) and minor traumatic brain injuries (mTBI) in the game of American football. While the current helmet design methodology may be adequate for reducing linear acceleration of the head and minimizing TBI, it however has had less effect in minimizing mTBI. The objectives of this study are (a) to develop and validate a coupled finite element (FE) model of a football helmet and the human body, and (b) to assess responses of different regions of the brain to two different impact conditions - frontal oblique and crown impact conditions. The FE helmet model was validated using experimental results of drop tests. Subsequently, the integrated helmet-human body FE model was used to assess the responses of different regions of the brain to impact loads. Strain-rate, strain, and stress measures in the corpus callosum, midbrain, and brain stem were assessed. Results show that maximum strain-rates of 27 and 19 s(-1) are observed in the brain-stem and mid-brain, respectively. This could potentially lead to axonal injuries and neuronal cell death during crown impact conditions. The developed experimental-numerical framework can be used in the study of other helmet-related impact conditions.

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

Toward an operational model of decision making, emotional regulation, and mental health impact.

PubMed

Collura, Thomas Francis; Zalaquett, Ronald P; Bonnstetter, Carlos Joyce; Chatters, Seria J

2014-01-01

Current brain research increasingly reveals the underlying mechanisms and processes of human behavior, cognition, and emotion. In addition to being of interest to a wide range of scientists, educators, and professionals, as well as laypeople, brain-based models are of particular value in a clinical setting. Psychiatrists, psychologists, counselors, and other mental health professionals are in need of operational models that integrate recent findings in the physical, cognitive, and emotional domains, and offer a common language for interdisciplinary understanding and communication. Based on individual traits, predispositions, and responses to stimuli, we can begin to identify emotional and behavioral pathways and mental processing patterns. The purpose of this article is to present a brain-path activation model to understand individual differences in decision making and psychopathology. The first section discusses the role of frontal lobe electroencephalography (EEG) asymmetry, summarizes state- and trait-based models of decision making, and provides a more complex analysis that supplements the traditional simple left-right brain model. Key components of the new model are the introduction of right hemisphere parallel and left hemisphere serial scanning in rendering decisions, and the proposition of pathways that incorporate both past experiences as well as future implications into the decision process. Main attributes of each decision-making mechanism are provided. The second section applies the model within the realm of clinical mental health as a tool to understand specific human behavior and pathology. Applications include general and chronic anxiety, depression, paranoia, risk taking, and the pathways employed when well-functioning operational integration is observed. Finally, specific applications such as meditation and mindfulness are offered to facilitate positive functioning.

Interactive dualism as a partial solution to the mind-brain problem for psychiatry.

PubMed

McLaren, N

2006-01-01

With the collapse of the psychoanalytic and the behaviorist models, and the failure of reductive biologism to account for mental life, psychiatry has been searching for a broad, integrative theory on which to base daily practice. The most recent attempt at such a model, Engel's 'biopsychosocial model', has been shown to be devoid of any scientific content, meaning that psychiatry, alone among the medical disciplines, has no recognised scientific basis. It is no coincidence that psychiatry is constantly under attack from all quarters. In order to develop, the discipline requires an integrative and interactive model which can take account of both the mental and the physical dimensions of human life, yet still remain within the materialist scientific ethos. This paper proposes an entirely new model of mind based in Chalmers' 'interactive dualism' which satisfies those needs. It attributes the causation of all behaviour to mental life, but proposes a split in the nature of mentality such that mind becomes a composite function with two, profoundly different aspects. Causation is assigned to a fast, inaccessible cognitive realm operating within the brain machinery while conscious experience is seen as the outcome of a higher order level of brain processing. The particular value of this model is that it immediately offers a practical solution to the mind-brain problem in that, while all information-processing takes place in the mental realm, it is not in the same order of abstraction as perception. This leads to a model of rational interaction which acknowledges both psyche and soma. It can fill the gap left by the demise of Engel's empty 'biopsychosocial model'.

Host matrix metalloproteinases in cerebral malaria: new kids on the block against blood–brain barrier integrity?

PubMed Central

2014-01-01

Cerebral malaria (CM) is a life-threatening complication of falciparum malaria, associated with high mortality rates, as well as neurological impairment in surviving patients. Despite disease severity, the etiology of CM remains elusive. Interestingly, although the Plasmodium parasite is sequestered in cerebral microvessels, it does not enter the brain parenchyma: so how does Plasmodium induce neuronal dysfunction? Several independent research groups have suggested a mechanism in which increased blood–brain barrier (BBB) permeability might allow toxic molecules from the parasite or the host to enter the brain. However, the reported severity of BBB damage in CM is variable depending on the model system, ranging from mild impairment to full BBB breakdown. Moreover, the factors responsible for increased BBB permeability are still unknown. Here we review the prevailing theories on CM pathophysiology and discuss new evidence from animal and human CM models implicating BBB damage. Finally, we will review the newly-described role of matrix metalloproteinases (MMPs) and BBB integrity. MMPs comprise a family of proteolytic enzymes involved in modulating inflammatory response, disrupting tight junctions, and degrading sub-endothelial basal lamina. As such, MMPs represent potential innovative drug targets for CM. PMID:24467887

Long-term cilostazol administration ameliorates memory decline in senescence-accelerated mouse prone 8 (SAMP8) through a dual effect on cAMP and blood-brain barrier.

PubMed

Yanai, Shuichi; Toyohara, Jun; Ishiwata, Kiichi; Ito, Hideki; Endo, Shogo

2017-04-01

Phosphodiesterases (PDEs), which hydrolyze and inactivate 3', 5'-cyclic adenosine monophosphate (cAMP) and 3', 5'-cyclic guanosine monophosphate (cGMP), play an important role in synaptic plasticity that underlies memory. Recently, several PDE inhibitors were assessed for their possible therapeutic efficacy in treating cognitive disorders. Here, we examined how cilostazol, a selective PDE3 inhibitor, affects brain functions in senescence-accelerated mouse prone 8 (SAMP8), an animal model of age-related cognitive impairment. Long-term administration of cilostazol restored the impaired context-dependent conditioned fear memory of SAMP8 to match that in normal aging control substrain SAMR1. Cilostazol also increased the number of cells containing phosphorylated cAMP-responsive element binding protein (CREB), a downstream component of the cAMP pathway. Finally, cilostazol improves blood-brain barrier (BBB) integrity, demonstrated by reduced extravasation of 2-deoxy-2- 18 F-fluoro-d-glucose and Evans Blue dye in the brains of SAMP8. This improvement in BBB integrity was associated with an increased amount of zona occludens protein 1 (ZO-1) and occludin proteins, components of tight junctions integral to the BBB. The results suggest that long-term administration of cilostazol exerts its beneficial effects on age-related cognitive impairment through a dual mechanism: by enhancing the cAMP system in the brain and by maintaining or improving BBB integrity. Copyright © 2016 Elsevier Ltd. All rights reserved.

Integrative Analysis of Genetic, Genomic, and Phenotypic Data for Ethanol Behaviors: A Network-Based Pipeline for Identifying Mechanisms and Potential Drug Targets.

PubMed

Bogenpohl, James W; Mignogna, Kristin M; Smith, Maren L; Miles, Michael F

2017-01-01

Complex behavioral traits, such as alcohol abuse, are caused by an interplay of genetic and environmental factors, producing deleterious functional adaptations in the central nervous system. The long-term behavioral consequences of such changes are of substantial cost to both the individual and society. Substantial progress has been made in the last two decades in understanding elements of brain mechanisms underlying responses to ethanol in animal models and risk factors for alcohol use disorder (AUD) in humans. However, treatments for AUD remain largely ineffective and few medications for this disease state have been licensed. Genome-wide genetic polymorphism analysis (GWAS) in humans, behavioral genetic studies in animal models and brain gene expression studies produced by microarrays or RNA-seq have the potential to produce nonbiased and novel insight into the underlying neurobiology of AUD. However, the complexity of such information, both statistical and informational, has slowed progress toward identifying new targets for intervention in AUD. This chapter describes one approach for integrating behavioral, genetic, and genomic information across animal model and human studies. The goal of this approach is to identify networks of genes functioning in the brain that are most relevant to the underlying mechanisms of a complex disease such as AUD. We illustrate an example of how genomic studies in animal models can be used to produce robust gene networks that have functional implications, and to integrate such animal model genomic data with human genetic studies such as GWAS for AUD. We describe several useful analysis tools for such studies: ComBAT, WGCNA, and EW_dmGWAS. The end result of this analysis is a ranking of gene networks and identification of their cognate hub genes, which might provide eventual targets for future therapeutic development. Furthermore, this combined approach may also improve our understanding of basic mechanisms underlying gene x environmental interactions affecting brain functioning in health and disease.

An integrative model of auditory phantom perception: tinnitus as a unified percept of interacting separable subnetworks.

PubMed

De Ridder, Dirk; Vanneste, Sven; Weisz, Nathan; Londero, Alain; Schlee, Winnie; Elgoyhen, Ana Belen; Langguth, Berthold

2014-07-01

Tinnitus is a considered to be an auditory phantom phenomenon, a persistent conscious percept of a salient memory trace, externally attributed, in the absence of a sound source. It is perceived as a phenomenological unified coherent percept, binding multiple separable clinical characteristics, such as its loudness, the sidedness, the type (pure tone, noise), the associated distress and so on. A theoretical pathophysiological framework capable of explaining all these aspects in one model is highly needed. The model must incorporate both the deafferentation based neurophysiological models and the dysfunctional noise canceling model, and propose a 'tinnitus core' subnetwork. The tinnitus core can be defined as the minimal set of brain areas that needs to be jointly activated (=subnetwork) for tinnitus to be consciously perceived, devoid of its affective components. The brain areas involved in the other separable characteristics of tinnitus can be retrieved by studies on spontaneous resting state magnetic and electrical activity in people with tinnitus, evaluated for the specific aspect investigated and controlled for other factors. By combining these functional imaging studies with neuromodulation techniques some of the correlations are turned into causal relationships. Thereof, a heuristic pathophysiological framework is constructed, integrating the tinnitus perceptual core with the other tinnitus related aspects. This phenomenological unified percept of tinnitus can be considered an emergent property of multiple, parallel, dynamically changing and partially overlapping subnetworks, each with a specific spontaneous oscillatory pattern and functional connectivity signature. Communication between these different subnetworks is proposed to occur at hubs, brain areas that are involved in multiple subnetworks simultaneously. These hubs can take part in each separable subnetwork at different frequencies. Communication between the subnetworks is proposed to occur at discrete oscillatory frequencies. As such, the brain uses multiple nonspecific networks in parallel, each with their own oscillatory signature, that adapt to the context to construct a unified percept possibly by synchronized activation integrated at hubs at discrete oscillatory frequencies. Copyright © 2013 Elsevier Ltd. All rights reserved.

INTEGRATIVE ANALYSIS OF GENETIC, GENOMIC AND PHENOTYPIC DATA FOR ETHANOL BEHAVIORS: A NETWORK-BASED PIPELINE FOR IDENTIFYING MECHANISMS AND POTENTIAL DRUG TARGETS

PubMed Central

Bogenpohl, James W.; Mignogna, Kristin M.; Smith, Maren L.; Miles, Michael F.

2016-01-01

Complex behavioral traits, such as alcohol abuse, are caused by an interplay of genetic and environmental factors, producing deleterious functional adaptations in the central nervous system. The long-term behavioral consequences of such changes are of substantial cost to both the individual and society. Substantial progress has been made in the last two decades in understanding elements of brain mechanisms underlying responses to ethanol in animal models and risk factors for alcohol use disorder (AUD) in humans. However, treatments for AUD remain largely ineffective and few medications for this disease state have been licensed. Genome-wide genetic polymorphism analysis (GWAS) in humans, behavioral genetic studies in animal models and brain gene expression studies produced by microarrays or RNA-seq have the potential to produce non-biased and novel insight into the underlying neurobiology of AUD. However, the complexity of such information, both statistical and informational, has slowed progress toward identifying new targets for intervention in AUD. This chapter describes one approach for integrating behavioral, genetic, and genomic information across animal model and human studies. The goal of this approach is to identify networks of genes functioning in the brain that are most relevant to the underlying mechanisms of a complex disease such as AUD. We illustrate an example of how genomic studies in animal models can be used to produce robust gene networks that have functional implications, and to integrate such animal model genomic data with human genetic studies such as GWAS for AUD. We describe several useful analysis tools for such studies: ComBAT, WGCNA and EW_dmGWAS. The end result of this analysis is a ranking of gene networks and identification of their cognate hub genes, which might provide eventual targets for future therapeutic development. Furthermore, this combined approach may also improve our understanding of basic mechanisms underlying gene x environmental interactions affecting brain functioning in health and disease. PMID:27933543

Integrated Arts-Based Teaching (IAT) Model for Brain-Based Learning

ERIC Educational Resources Information Center

Inocian, Reynaldo B.

2015-01-01

This study analyzes teaching strategies among the eight books in Principles and Methods of Teaching recommended for use in the College of Teacher Education in the Philippines. It seeks to answer the following objectives: (1) identify the most commonly used teaching strategies congruent with the integrated arts-based teaching (IAT) and (2) design…

Integration of Neuroimaging and Microarray Datasets through Mapping and Model-Theoretic Semantic Decomposition of Unstructured Phenotypes

PubMed Central

Pantazatos, Spiro P.; Li, Jianrong; Pavlidis, Paul; Lussier, Yves A.

2009-01-01

An approach towards heterogeneous neuroscience dataset integration is proposed that uses Natural Language Processing (NLP) and a knowledge-based phenotype organizer system (PhenOS) to link ontology-anchored terms to underlying data from each database, and then maps these terms based on a computable model of disease (SNOMED CT®). The approach was implemented using sample datasets from fMRIDC, GEO, The Whole Brain Atlas and Neuronames, and allowed for complex queries such as “List all disorders with a finding site of brain region X, and then find the semantically related references in all participating databases based on the ontological model of the disease or its anatomical and morphological attributes”. Precision of the NLP-derived coding of the unstructured phenotypes in each dataset was 88% (n = 50), and precision of the semantic mapping between these terms across datasets was 98% (n = 100). To our knowledge, this is the first example of the use of both semantic decomposition of disease relationships and hierarchical information found in ontologies to integrate heterogeneous phenotypes across clinical and molecular datasets. PMID:20495688

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.

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

Adolescent brain development in normality and psychopathology

PubMed Central

LUCIANA, MONICA

2014-01-01

Since this journal’s inception, the field of adolescent brain development has flourished, as researchers have investigated the underpinnings of adolescent risk-taking behaviors. Explanations based on translational models initially attributed such behaviors to executive control deficiencies and poor frontal lobe function. This conclusion was bolstered by evidence that the prefrontal cortex and its interconnections are among the last brain regions to structurally and functionally mature. As substantial heterogeneity of prefrontal function was revealed, applications of neuroeconomic theory to adolescent development led to dual systems models of behavior. Current epidemiological trends, behavioral observations, and functional magnetic resonance imaging based brain activity patterns suggest a quadratic increase in limbically mediated incentive motivation from childhood to adolescence and a decline thereafter. This elevation occurs in the context of immature prefrontal function, so motivational strivings may be difficult to regulate. Theoretical models explain this patterning through brain-based accounts of subcortical–cortical integration, puberty-based models of adolescent sensation seeking, and neurochemical dynamics. Empirically sound tests of these mechanisms, as well as investigations of biology–context interactions, represent the field’s most challenging future goals, so that applications to psychopathology can be refined and so that developmental cascades that incorporate neurobiological variables can be modeled. PMID:24342843

Adolescent brain development in normality and psychopathology.

PubMed

Luciana, Monica

2013-11-01

Since this journal's inception, the field of adolescent brain development has flourished, as researchers have investigated the underpinnings of adolescent risk-taking behaviors. Explanations based on translational models initially attributed such behaviors to executive control deficiencies and poor frontal lobe function. This conclusion was bolstered by evidence that the prefrontal cortex and its interconnections are among the last brain regions to structurally and functionally mature. As substantial heterogeneity of prefrontal function was revealed, applications of neuroeconomic theory to adolescent development led to dual systems models of behavior. Current epidemiological trends, behavioral observations, and functional magnetic resonance imaging based brain activity patterns suggest a quadratic increase in limbically mediated incentive motivation from childhood to adolescence and a decline thereafter. This elevation occurs in the context of immature prefrontal function, so motivational strivings may be difficult to regulate. Theoretical models explain this patterning through brain-based accounts of subcortical-cortical integration, puberty-based models of adolescent sensation seeking, and neurochemical dynamics. Empirically sound tests of these mechanisms, as well as investigations of biology-context interactions, represent the field's most challenging future goals, so that applications to psychopathology can be refined and so that developmental cascades that incorporate neurobiological variables can be modeled.

Zika virus crosses an in vitro human blood brain barrier model.

PubMed

Alimonti, Judie B; Ribecco-Lutkiewicz, Maria; Sodja, Caroline; Jezierski, Anna; Stanimirovic, Danica B; Liu, Qing; Haqqani, Arsalan S; Conlan, Wayne; Bani-Yaghoub, Mahmud

2018-05-15

Zika virus (ZIKV) is a flavivirus that is highly neurotropic causing congenital abnormalities and neurological damage to the central nervous systems (CNS). In this study, we used a human induced pluripotent stem cell (iPSC)-derived blood brain barrier (BBB) model to demonstrate that ZIKV can infect brain endothelial cells (i-BECs) without compromising the BBB barrier integrity or permeability. Although no disruption to the BBB was observed post-infection, ZIKV particles were released on the abluminal side of the BBB model and infected underlying iPSC-derived neural progenitor cells (i-NPs). AXL, a putative ZIKV cellular entry receptor, was also highly expressed in ZIKV-susceptible i-BEC and i-NPs. This iPSC-derived BBB model can help elucidate the mechanism by which ZIKV can infect BECs, cross the BBB and gain access to the CNS.

Optically enhanced blood-brain-barrier crossing of plasmonic-active nanoparticles in preclinical brain tumor animal models

NASA Astrophysics Data System (ADS)

Yuan, Hsiangkuo; Wilson, Christy M.; Li, Shuqin; Fales, Andrew M.; Liu, Yang; Grant, Gerald; Vo-Dinh, Tuan

2014-02-01

Nanotechnology provides tremendous biomedical opportunities for cancer diagnosis, imaging, and therapy. In contrast to conventional chemotherapeutic agents where their actual target delivery cannot be easily imaged, integrating imaging and therapeutic properties into one platform facilitates the understanding of pharmacokinetic profiles, and enables monitoring of the therapeutic process in each individual. Such a concept dubbed "theranostics" potentiates translational research and improves precision medicine. One particular challenging application of theranostics involves imaging and controlled delivery of nanoplatforms across blood-brain-barrier (BBB) into brain tissues. Typically, the BBB hinders paracellular flux of drug molecules into brain parenchyma. BBB disrupting agents (e.g. mannitol, focused ultrasound), however, suffer from poor spatial confinement. It has been a challenge to design a nanoplatform not only acts as a contrast agent but also improves the BBB permeation. In this study, we demonstrated the feasibility of plasmonic gold nanoparticles as both high-resolution optical contrast agent and focalized tumor BBB permeation-inducing agent. We specifically examined the microscopic distribution of nanoparticles in tumor brain animal models. We observed that most nanoparticles accumulated at the tumor periphery or perivascular spaces. Nanoparticles were present in both endothelial cells and interstitial matrices. This study also demonstrated a novel photothermal-induced BBB permeation. Fine-tuning the irradiating energy induced gentle disruption of the vascular integrity, causing short-term extravasation of nanomaterials but without hemorrhage. We conclude that our gold nanoparticles are a powerful biocompatible contrast agent capable of inducing focal BBB permeation, and therefore envision a strong potential of plasmonic gold nanoparticle in future brain tumor imaging and therapy.

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

A Device for Long-Term Perfusion, Imaging, and Electrical Interfacing of Brain Tissue In vitro

PubMed Central

Killian, Nathaniel J.; Vernekar, Varadraj N.; Potter, Steve M.; Vukasinovic, Jelena

2016-01-01

Distributed microelectrode array (MEA) recordings from consistent, viable, ≥500 μm thick tissue preparations over time periods from days to weeks may aid in studying a wide range of problems in neurobiology that require in vivo-like organotypic morphology. Existing tools for electrically interfacing with organotypic slices do not address necrosis that inevitably occurs within thick slices with limited diffusion of nutrients and gas, and limited removal of waste. We developed an integrated device that enables long-term maintenance of thick, functionally active, brain tissue models using interstitial perfusion and distributed recordings from thick sections of explanted tissue on a perforated multi-electrode array. This novel device allows for automated culturing, in situ imaging, and extracellular multi-electrode interfacing with brain slices, 3-D cell cultures, and potentially other tissue culture models. The device is economical, easy to assemble, and integrable with standard electrophysiology tools. We found that convective perfusion through the culture thickness provided a functional benefit to the preparations as firing rates were generally higher in perfused cultures compared to their respective unperfused controls. This work is a step toward the development of integrated tools for days-long experiments with more consistent, healthier, thicker, and functionally more active tissue cultures with built-in distributed electrophysiological recording and stimulation functionality. The results may be useful for the study of normal processes, pathological conditions, and drug screening strategies currently hindered by the limitations of acute (a few hours long) brain slice preparations. PMID:27065793

Naringin alleviates early brain injury after experimental subarachnoid hemorrhage by reducing oxidative stress and inhibiting apoptosis.

PubMed

Han, Yuwei; Su, Jingyuan; Liu, Xiujuan; Zhao, Yuan; Wang, Chenchen; Li, Xiaoming

2017-07-01

This study aims to clarify the neuroprotective effect of naringin on early brain injury (EBI) following subarachnoid hemorrhage (SAH) and the possible mechanisms of naringin in the treatment of SAH. The endovascular puncture model was performed to induce SAH model in rats and the efficacy of 40mg/kg and 80mg/kg naringin were tested by intraperitoneally administration. SAH grade, neurological score, brain edema, blood-brain barrier permeability, the changes of oxidative stress related factors, apoptosis-related proteins, mitogen-activated protein kinase (MAPK) signaling pathway and neuronal morphology were detected to analyze the potential effect of naringin against SAH. The results demonstrated that naringin significantly ameliorated EBI, including SAH severity, neurologic deficits, brain edema and blood-brain barrier integrity by attenuating SAH-induced oxidative stress and apoptosis, and reduced the oxidant damage and apoptosis by inhibiting the activation of MAPK signaling pathway, which suggested a therapeutic potential of naringin in providing neuroprotection after SAH. Copyright © 2016 Elsevier Inc. All rights reserved.

Correlated gene expression and anatomical communication support synchronized brain activity in the mouse functional connectome.

PubMed

Mills, Brian D; Grayson, David S; Shunmugavel, Anandakumar; Miranda-Dominguez, Oscar; Feczko, Eric; Earl, Eric; Neve, Kim; Fair, Damien A

2018-05-22

Cognition and behavior depend on synchronized intrinsic brain activity that is organized into functional networks across the brain. Research has investigated how anatomical connectivity both shapes and is shaped by these networks, but not how anatomical connectivity interacts with intra-areal molecular properties to drive functional connectivity. Here, we present a novel linear model to explain functional connectivity by integrating systematically obtained measurements of axonal connectivity, gene expression, and resting state functional connectivity MRI in the mouse brain. The model suggests that functional connectivity arises from both anatomical links and inter-areal similarities in gene expression. By estimating these effects, we identify anatomical modules in which correlated gene expression and anatomical connectivity support functional connectivity. Along with providing evidence that not all genes equally contribute to functional connectivity, this research establishes new insights regarding the biological underpinnings of coordinated brain activity measured by BOLD fMRI. SIGNIFICANCE STATEMENT Efforts at characterizing the functional connectome with fMRI have risen exponentially over the last decade. Yet despite this rise, the biological underpinnings of these functional measurements are still largely unknown. The current report begins to fill this void by investigating the molecular underpinnings of the functional connectome through an integration of systematically obtained structural information and gene expression data throughout the rodent brain. We find that both white matter connectivity and similarity in regional gene expression relate to resting state functional connectivity. The current report furthers our understanding of the biological underpinnings of the functional connectome and provides a linear model that can be utilized to streamline preclinical animal studies of disease. Copyright © 2018 the authors.

A programmable laboratory testbed in support of evaluation of functional brain activation and connectivity.

PubMed

Barbour, Randall L; Graber, Harry L; Xu, Yong; Pei, Yaling; Schmitz, Christoph H; Pfeil, Douglas S; Tyagi, Anandita; Andronica, Randy; Lee, Daniel C; Barbour, San-Lian S; Nichols, J David; Pflieger, Mark E

2012-03-01

An important determinant of the value of quantitative neuroimaging studies is the reliability of the derived information, which is a function of the data collection conditions. Near infrared spectroscopy (NIRS) and electroencelphalography are independent sensing domains that are well suited to explore principal elements of the brain's response to neuroactivation, and whose integration supports development of compact, even wearable, systems suitable for use in open environments. In an effort to maximize the translatability and utility of such resources, we have established an experimental laboratory testbed that supports measures and analysis of simulated macroscopic bioelectric and hemodynamic responses of the brain. Principal elements of the testbed include 1) a programmable anthropomorphic head phantom containing a multisignal source array embedded within a matrix that approximates the background optical and bioelectric properties of the brain, 2) integrated translatable headgear that support multimodal studies, and 3) an integrated data analysis environment that supports anatomically based mapping of experiment-derived measures that are directly and not directly observable. Here, we present a description of system components and fabrication, an overview of the analysis environment, and findings from a representative study that document the ability to experimentally validate effective connectivity models based on NIRS tomography.

Patient-tailored multimodal neuroimaging, visualization and quantification of human intra-cerebral hemorrhage

NASA Astrophysics Data System (ADS)

Goh, Sheng-Yang M.; Irimia, Andrei; Vespa, Paul M.; Van Horn, John D.

2016-03-01

In traumatic brain injury (TBI) and intracerebral hemorrhage (ICH), the heterogeneity of lesion sizes and types necessitates a variety of imaging modalities to acquire a comprehensive perspective on injury extent. Although it is advantageous to combine imaging modalities and to leverage their complementary benefits, there are difficulties in integrating information across imaging types. Thus, it is important that efforts be dedicated to the creation and sustained refinement of resources for multimodal data integration. Here, we propose a novel approach to the integration of neuroimaging data acquired from human patients with TBI/ICH using various modalities; we also demonstrate the integrated use of multimodal magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) data for TBI analysis based on both visual observations and quantitative metrics. 3D models of healthy-appearing tissues and TBIrelated pathology are generated, both of which are derived from multimodal imaging data. MRI volumes acquired using FLAIR, SWI, and T2 GRE are used to segment pathology. Healthy tissues are segmented using user-supervised tools, and results are visualized using a novel graphical approach called a `connectogram', where brain connectivity information is depicted within a circle of radially aligned elements. Inter-region connectivity and its strength are represented by links of variable opacities drawn between regions, where opacity reflects the percentage longitudinal change in brain connectivity density. Our method for integrating, analyzing and visualizing structural brain changes due to TBI and ICH can promote knowledge extraction and enhance the understanding of mechanisms underlying recovery.

Brain temperature changes during selective cooling with endovascular intracarotid cold saline infusion: simulation using human data fitted with an integrated mathematical model.

PubMed

Neimark, Matthew Aaron Harold; Konstas, Angelos Aristeidis; Lee, Leslie; Laine, Andrew Francis; Pile-Spellman, John; Choi, Jae

2013-03-01

The feasibility of rapid cerebral hypothermia induction in humans with intracarotid cold saline infusion (ICSI) was investigated using a hybrid approach of jugular venous bulb temperature (JVBT) sampling and mathematical modeling of transient and steady state brain temperature distribution. This study utilized both forward mathematical modeling, in which brain temperatures were predicted based on input saline temperatures, and inverse modeling, where brain temperatures were inferred based on JVBT. Changes in ipsilateral anterior circulation territory temperature (IACT) were estimated in eight patients as a result of 10 min of a cold saline infusion of 33 ml/min. During ICSI, the measured JVBT dropped by 0.76±0.18°C while the modeled JVBT decreased by 0.86±0.18°C. The modeled IACT decreased by 2.1±0.23°C. In the inverse model, IACT decreased by 1.9±0.23°C. The results of this study suggest that mild cerebral hypothermia can be induced rapidly and safely with ICSI in the neuroangiographical setting. The JVBT corrected mathematical model can be used as a non-invasive estimate of transient and steady state cerebral temperature changes.

The use of neurocomputational models as alternatives to animal models in the development of electrical brain stimulation treatments.

PubMed

Beuter, Anne

2017-05-01

Recent publications call for more animal models to be used and more experiments to be performed, in order to better understand the mechanisms of neurodegenerative disorders, to improve human health, and to develop new brain stimulation treatments. In response to these calls, some limitations of the current animal models are examined by using Deep Brain Stimulation (DBS) in Parkinson's disease as an illustrative example. Without focusing on the arguments for or against animal experimentation, or on the history of DBS, the present paper argues that given recent technological and theoretical advances, the time has come to consider bioinspired computational modelling as a valid alternative to animal models, in order to design the next generation of human brain stimulation treatments. However, before computational neuroscience is fully integrated in the translational process and used as a substitute for animal models, several obstacles need to be overcome. These obstacles are examined in the context of institutional, financial, technological and behavioural lock-in. Recommendations include encouraging agreement to change long-term habitual practices, explaining what alternative models can achieve, considering economic stakes, simplifying administrative and regulatory constraints, and carefully examining possible conflicts of interest. 2017 FRAME.

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

PubMed

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

2011-12-01

Recent findings of neurological functioning in autism spectrum disorder (ASD) point to altered brain connectivity as a key feature of its pathophysiology. The cortical underconnectivity theory of ASD (Just et al., 2004) provides an integrated framework for addressing these new findings. This theory suggests that weaker functional connections among brain areas in those with ASD hamper their ability to accomplish complex cognitive and social tasks successfully. We will discuss this theory, but will modify the term underconnectivity to 'disrupted cortical connectivity' to capture patterns of both under- and over-connectivity in the brain. In this paper, we will review the existing literature on ASD to marshal supporting evidence for hypotheses formulated on the disrupted cortical connectivity theory. These hypotheses are: 1) underconnectivity in ASD is manifested mainly in long-distance cortical as well as subcortical connections rather than in short-distance cortical connections; 2) underconnectivity in ASD is manifested only in complex cognitive and social functions and not in low-level sensory and perceptual tasks; 3) functional underconnectivity in ASD may be the result of underlying anatomical abnormalities, such as problems in the integrity of white matter; 4) the ASD brain adapts to underconnectivity through compensatory strategies such as overconnectivity mainly in frontal and in posterior brain areas. This may be manifested as deficits in tasks that require frontal-parietal integration. While overconnectivity can be tested by examining the cortical minicolumn organization, long-distance underconnectivity can be tested by cognitively demanding tasks; and 5) functional underconnectivity in brain areas in ASD will be seen not only during complex tasks but also during task-free resting states. We will also discuss some empirical predictions that can be tested in future studies, such as: 1) how disrupted connectivity relates to cognitive impairments in skills such as Theory-of-Mind, cognitive flexibility, and information processing; and 2) how connection abnormalities relate to, and may determine, behavioral symptoms hallmarked by the triad of Impairments in ASD. Furthermore, we will relate the disrupted cortical connectivity model to existing cognitive and neural models of ASD. Published by Elsevier B.V.

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

Recent findings of neurological functioning in autism spectrum disorder (ASD) point to altered brain connectivity as a key feature of its pathophysiology. The cortical underconnectivity theory of ASD (Just et al., 2004) provides an integrated framework for addressing these new findings. This theory suggests that weaker functional connections among brain areas in those with ASD hamper their ability to accomplish complex cognitive and social tasks successfully. We will discuss this theory, but will modify the term underconnectivity to ‘disrupted cortical connectivity’ to capture patterns of both under- and over-connectivity in the brain. In this paper, we will review the existing literature on ASD to marshal supporting evidence for hypotheses formulated on the disrupted cortical connectivity theory. These hypotheses are: 1) underconnectivity in ASD is manifested mainly in long-distance cortical as well as subcortical connections rather than in short-distance cortical connections; 2) underconnectivity in ASD is manifested only in complex cognitive and social functions and not in low-level sensory and perceptual tasks; 3) functional underconnectivity in ASD may be the result of underlying anatomical abnormalities, such as problems in the integrity of white matter; 4) the ASD brain adapts to underconnectivity through compensatory strategies such as overconnectivity mainly in frontal and in posterior brain areas. This may be manifested as deficits in tasks that require frontal-parietal integration. While overconnectivity can be tested by examining the cortical minicolumn organization, long-distance underconnectivity can be tested by cognitively demanding tasks; and 5) functional underconnectivity in brain areas in ASD will be seen not only during complex tasks but also during task-free resting states. We will also discuss some empirical predictions that can be tested in future studies, such as: 1) how disrupted connectivity relates to cognitive impairments in skills such as Theory-of-Mind, cognitive flexibility, and information processing; and 2) how connection abnormalities relate to, and may determine, behavioral symptoms hallmarked by the triad of Impairments in ASD. Furthermore, we will relate the disrupted cortical connectivity model to existing cognitive and neural models of ASD.

Schizophrenia: an integrated sociodevelopmental-cognitive model

PubMed Central

Howes, Oliver D; Murray, Robin M

2014-01-01

Schizophrenia remains a major burden1. The dopamine (DA) and neurodevelopmental hypotheses attempt to explain the pathogenic mechanisms and origins of the disorder respectively2-4. Recently an alternative, the cognitive model, has gained popularity5. However the first two theories have not been satisfactorily integrated, and the most influential iteration of the cognitive model makes no mention of DA, neurodevelopment, or indeed the brain5. Here we show that developmental alterations secondary to variant genes, early hazards to the brain and childhood adversity, sensitise the DA system, and result in excessive presynaptic DA synthesis and DA release. Social adversity biases the cognitive schema that the individual uses to interpret experiences towards paranoid interpretations. Subsequent stress results in dysregulated DA release, causing the misattribution of salience to stimuli, which are then misinterpreted by the biased cognitive processes. The resulting paranoia and hallucinations in turn cause further stress, and eventually repeated DA dysregulation hard-wires the psychotic beliefs. Finally we consider the implications of this model for understanding and treating schizophrenia. PMID:24315522

Docosahexaenoic acid: brain accretion and roles in neuroprotection after brain hypoxia and ischemia.

PubMed

Mayurasakorn, Korapat; Williams, Jill J; Ten, Vadim S; Deckelbaum, Richard J

2011-03-01

With important effects on neuronal lipid composition, neurochemical signaling and cerebrovascular pathobiology, docosahexaenoic acid (DHA), a n-3 polyunsaturated fatty acid, may emerge as a neuroprotective agent against cerebrovascular disease. This paper examines pathways for DHA accretion in brain and evidence for possible roles of DHA in prophylactic and therapeutic approaches for cerebrovascular disease. DHA is a major n-3 fatty acid in the mammalian central nervous system and enhances synaptic activities in neuronal cells. DHA can be obtained through diet or to a limited extent via conversion from its precursor, α-linolenic acid (α-LNA). DHA attenuates brain necrosis after hypoxic ischemic injury, principally by modulating membrane biophysical properties and maintaining integrity in functions between presynaptic and postsynaptic areas, resulting in better stabilizing intracellular ion balance in hypoxic-ischemic insult. Additionally, DHA alleviates brain apoptosis, by inducing antiapoptotic activities such as decreasing responses to reactive oxygen species, upregulating antiapoptotic protein expression, downregulating apoptotic protein expression, and maintaining mitochondrial integrity and function. DHA in brain relates to a number of efficient delivery and accretion pathways. In animal models DHA renders neuroprotection after hypoxic-ischemic injury by regulating multiple molecular pathways and gene expression.

Disconnected aging: cerebral white matter integrity and age-related differences in cognition.

PubMed

Bennett, I J; Madden, D J

2014-09-12

Cognition arises as a result of coordinated processing among distributed brain regions and disruptions to communication within these neural networks can result in cognitive dysfunction. Cortical disconnection may thus contribute to the declines in some aspects of cognitive functioning observed in healthy aging. Diffusion tensor imaging (DTI) is ideally suited for the study of cortical disconnection as it provides indices of structural integrity within interconnected neural networks. The current review summarizes results of previous DTI aging research with the aim of identifying consistent patterns of age-related differences in white matter integrity, and of relationships between measures of white matter integrity and behavioral performance as a function of adult age. We outline a number of future directions that will broaden our current understanding of these brain-behavior relationships in aging. Specifically, future research should aim to (1) investigate multiple models of age-brain-behavior relationships; (2) determine the tract-specificity versus global effect of aging on white matter integrity; (3) assess the relative contribution of normal variation in white matter integrity versus white matter lesions to age-related differences in cognition; (4) improve the definition of specific aspects of cognitive functioning related to age-related differences in white matter integrity using information processing tasks; and (5) combine multiple imaging modalities (e.g., resting-state and task-related functional magnetic resonance imaging; fMRI) with DTI to clarify the role of cerebral white matter integrity in cognitive aging. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.

Disconnected Aging: Cerebral White Matter Integrity and Age-Related Differences in Cognition

PubMed Central

Bennett, Ilana J.; Madden, David J.

2013-01-01

Cognition arises as a result of coordinated processing among distributed brain regions and disruptions to communication within these neural networks can result in cognitive dysfunction. Cortical disconnection may thus contribute to the declines in some aspects of cognitive functioning observed in healthy aging. Diffusion tensor imaging (DTI) is ideally suited for the study of cortical disconnection as it provides indices of structural integrity within interconnected neural networks. The current review summarizes results of previous DTI aging research with the aim of identifying consistent patterns of age-related differences in white matter integrity, and of relationships between measures of white matter integrity and behavioral performance as a function of adult age. We outline a number of future directions that will broaden our current understanding of these brain-behavior relationships in aging. Specifically, future research should aim to (1) investigate multiple models of age-brain-behavior relationships; (2) determine the tract-specificity versus global effect of aging on white matter integrity; (3) assess the relative contribution of normal variation in white matter integrity versus white matter lesions to age-related differences in cognition; (4) improve the definition of specific aspects of cognitive functioning related to age-related differences in white matter integrity using information processing tasks; and (5) combine multiple imaging modalities (e.g., resting-state and task-related functional magnetic resonance imaging; fMRI) with DTI to clarify the role of cerebral white matter integrity in cognitive aging. PMID:24280637

Dynamic monitoring of blood-brain barrier integrity using water exchange index (WEI) during mannitol and CO2 challenges in mouse brain.

PubMed

Huang, Shuning; Farrar, Christian T; Dai, Guangping; Kwon, Seon Joo; Bogdanov, Alexei A; Rosen, Bruce R; Kim, Young R

2013-04-01

The integrity of the blood-brain barrier (BBB) is critical to normal brain function. Traditional techniques for the assessment of BBB disruption rely heavily on the spatiotemporal analysis of extravasating contrast agents. However, such methods based on the leakage of relatively large molecules are not suitable for the detection of subtle BBB impairment or for the performance of repeated measurements in a short time frame. Quantification of the water exchange rate constant (WER) across the BBB using strictly intravascular contrast agents could provide a much more sensitive method for the quantification of the BBB integrity. To estimate WER, we have recently devised a powerful new method using a water exchange index (WEI) biomarker and demonstrated BBB disruption in an acute stroke model. Here, we confirm that WEI is sensitive to even very subtle changes in the integrity of the BBB caused by: (i) systemic hypercapnia and (ii) low doses of a hyperosmolar solution. In addition, we have examined the sensitivity and accuracy of WEI as a biomarker of WER using computer simulation. In particular, the dependence of the WEI-WER relation on changes in vascular blood volume, T1 relaxation of cellular magnetization and transcytolemmal water exchange was explored. Simulated WEI was found to vary linearly with WER for typically encountered exchange rate constants (1-4 Hz), regardless of the blood volume. However, for very high WER (>5 Hz), WEI became progressively more insensitive to increasing WER. The incorporation of transcytolemmal water exchange, using a three-compartment tissue model, helped to extend the linear WEI regime to slightly higher WER, but had no significant effect for most physiologically important WERs (WER < 4 Hz). Variation in cellular T1 had no effect on WEI. Using both theoretical and experimental approaches, our study validates the utility of the WEI biomarker for the monitoring of BBB integrity. Copyright © 2012 John Wiley & Sons, Ltd.

Dynamic Monitoring of Blood-Brain Barrier Integrity using Water Exchange Index (WEI) During Mannitol and CO2 Challenges in Mouse Brain

PubMed Central

Huang, Shuning; Farrar, Christian T.; Dai, Guangping; Kwon, Seon Joo; Bogdanov, Alexei A.; Rosen, Bruce R.; Kim, Young R.

2012-01-01

The integrity of the blood-brain barrier (BBB) is critical to normal brain function. Traditional techniques for assessing BBB disruption rely heavily on the spatiotemporal analysis of extravasating contrast agents. But such methods based on the leakage of relatively large molecules are not suitable to detect subtle BBB impairment or to perform repeated measurements in a short time frame. Quantification of the water exchange rate constant (WER) across the BBB using strictly intravascular contrast agents could provide a much more sensitive method for quantifying the BBB integrity. For estimating the WER, we have recently devised a powerful new method using a water exchange index (WEI) biomarker and demonstrated BBB disruption in an acute stroke model. Here we confirm that the WEI is sensitive to even very subtle changes in the integrity of the BBB caused by (1) systemic hypercapnia and (2) low doses of a hyperosmolar solution. In addition, we have examined the sensitivity and accuracy of the WEI as a biomarker of the WER using computer simulation. In particular, the dependence of the WEI-WER relation on changes in vascular blood volume, T1 relaxation of cellular magnetization, and transcytolemmal water exchange was explored. The simulated WEI was found to vary linearly with the WER for typically encountered exchange rate constants (1–4 Hz) regardless of the blood volume. However, for very high WER (>5 Hz) the WEI became progressively more insensitive to increasing WER. The incorporation of transcytolemmal water exchange, using a three-compartment tissue model, helped to extend the linear WEI regime to slightly higher WER, but had no significant effect for most physiologically important water exchange rate constants (WER<4 Hz). Variation in the cellular T1 had no effect on the WEI. Using both theoretical and experimental approaches, our study validates the utility of the WEI biomarker for monitoring BBB integrity. PMID:23055278

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.

The role of psychosocial factors and psychiatric disorders in functional dyspepsia.

PubMed

Van Oudenhove, Lukas; Aziz, Qasim

2013-03-01

In this Review, after a brief historical introduction, we first provide an overview of epidemiological studies that demonstrate an association between functional dyspepsia and psychological traits, states or psychiatric disorders. These studies suggest an important intrinsic role for psychosocial factors and psychiatric disorders, especially anxiety and depression, in the aetiopathogenesis of functional dyspepsia, in addition to their putative influence on health-care-seeking behaviour. Second, we describe pathophysiological evidence on how psychosocial factors and psychiatric disorders might exert their role in functional dyspepsia. Novel insights from functional brain imaging studies regarding the integration of gut-brain signals, processed in homeostatic-interoceptive brain regions, with input from the exteroceptive system, the reward system and affective and cognitive circuits, help to clarify the important role of psychological processes and psychiatric morbidity. We therefore propose an integrated model of functional dyspepsia as a disorder of gut-brain signalling, supporting a biopsychosocial approach to the diagnosis and management of this disorder.

Potentiated antibodies to mu-opiate receptors: effect on integrative activity of the brain.

PubMed

Geiko, V V; Vorob'eva, T M; Berchenko, O G; Epstein, O I

2003-01-01

The effect of homeopathically potentiated antibodies to mu-receptors (10(-100) wt %) on integrative activity of rat brain was studied using the models of self-stimulation of the lateral hypothalamus and convulsions produced by electric current. Electric current was delivered through electrodes implanted into the ventromedial hypothalamus. Single treatment with potentiated antibodies to mu-receptors increased the rate of self-stimulation and decreased the threshold of convulsive seizures. Administration of these antibodies for 7 days led to further activation of the positive reinforcement system and decrease in seizure thresholds. Distilled water did not change the rate of self-stimulation and seizure threshold.

The change of the brain activation patterns as children learn algebra equation solving

NASA Astrophysics Data System (ADS)

Qin, Yulin; Carter, Cameron S.; Silk, Eli M.; Stenger, V. Andrew; Fissell, Kate; Goode, Adam; Anderson, John R.

2004-04-01

In a brain imaging study of children learning algebra, it is shown that the same regions are active in children solving equations as are active in experienced adults solving equations. As with adults, practice in symbol manipulation produces a reduced activation in prefrontal cortex area. However, unlike adults, practice seems also to produce a decrease in a parietal area that is holding an image of the equation. This finding suggests that adolescents' brain responses are more plastic and change more with practice. These results are integrated in a cognitive model that predicts both the behavioral and brain imaging results.

Monotonic non-linear transformations as a tool to investigate age-related effects on brain white matter integrity: A Box-Cox investigation.

PubMed

Morozova, Maria; Koschutnig, Karl; Klein, Elise; Wood, Guilherme

2016-01-15

Non-linear effects of age on white matter integrity are ubiquitous in the brain and indicate that these effects are more pronounced in certain brain regions at specific ages. Box-Cox analysis is a technique to increase the log-likelihood of linear relationships between variables by means of monotonic non-linear transformations. Here we employ Box-Cox transformations to flexibly and parsimoniously determine the degree of non-linearity of age-related effects on white matter integrity by means of model comparisons using a voxel-wise approach. Analysis of white matter integrity in a sample of adults between 20 and 89years of age (n=88) revealed that considerable portions of the white matter in the corpus callosum, cerebellum, pallidum, brainstem, superior occipito-frontal fascicle and optic radiation show non-linear effects of age. Global analyses revealed an increase in the average non-linearity from fractional anisotropy to radial diffusivity, axial diffusivity, and mean diffusivity. These results suggest that Box-Cox transformations are a useful and flexible tool to investigate more complex non-linear effects of age on white matter integrity and extend the functionality of the Box-Cox analysis in neuroimaging. Copyright © 2015 Elsevier Inc. All rights reserved.

Social factors predictive of social integration for adults with brain injury.

PubMed

Batchos, Elisabeth; Easton, Amanda; Haak, Christopher; Ditchman, Nicole

2018-08-01

Individuals with acquired brain injury (ABI) may not only struggle with physical and cognitive impairments, but may also face challenges reintegrating into the community socially. Research has demonstrated that following ABI, individuals' social networks tend to dwindle, support may decline, and isolation increases. This study examined factors impacting social integration in a community-based sample of 102 individuals with ABI. Potential predictors included emotional support, instrumental support, problem solving confidence, and approach-avoidance style (AAS) of problem solving, while controlling for age, gender, education, and time since injury. Hierarchical regression was used to analyze whether these factors were predictive of social integration. The final model accounted for 33% of the variance in social integration outcomes. Results demonstrated that emotional support was initially a significant predictor; however, when controlling for emotional support the variance in social integration was better accounted for by social problem solving - specifically, AAS. A follow-up mediation analysis indicated that the relationship between social problem solving (specifically, AAS) and social integration was partially mediated by emotional support. This suggests that for individuals with ABI, a tendency to approach rather than avoid social problem solving issues is a significant predictor for social integration both directly and indirectly through its association with emotional social support. Implications for Rehabilitation Both instrumental and emotional social support should be assessed in patients with acquired brain injury (ABI), ensuring that emotional needs are met in addition to the more obvious instrumental needs. Barriers to problem solving for people with ABI may limit optimal social integration; thus, assessment and intervention aimed at increasing AAS are recommended. To enhance the social integration outcomes of people with brain injury, strength-based psychosocial rehabilitation should optimally balance an individual's abilities with areas requiring compensation, focusing on how to approach rather than avoid problems as well as strategies to cultivate emotional social support.

The stress-vulnerability model how does stress impact on mental illness at the level of the brain and what are the consequences?

PubMed

Goh, Cindy; Agius, Mark

2010-06-01

The stress -vulnerability model (Zubin et al. 1977) is an extremely useful model for identifying and treating relapses of mental illness. We accept that human persons carry genetic and other predisposition to mental illness. However, the question arises as to how stress impacts on a person in order to cause mental illness to develop. Furthermore there arises the issue as to what other effects such stress has on the human body beyond the human brain. Our aim was to research and integrate the current literature in order to establish how stress impacts on the brain at the cellular level, and to establish whether there are other consequences for the human body brought about by the impact of stress on the human brain. Literature Search, using pubmed. We have identified much literature on how stress affects biological mechanisms within the brain, and how it relates to biological vulnerabilities carried by different individuals. We have identified communalities in how the interplay between stress and vulnerability occurs in different disease processes.

Angiotensin receptors and β-catenin regulate brain endothelial integrity in malaria

PubMed Central

Basu-Roy, Upal; Ty, Maureen; Alique, Matilde; Fernandez-Arias, Cristina; Movila, Alexandru; Gomes, Pollyanna; Edagha, Innocent; Wassmer, Samuel C.; Walther, Thomas

2016-01-01

Cerebral malaria is characterized by cytoadhesion of Plasmodium falciparum–infected red blood cells (Pf-iRBCs) to endothelial cells in the brain, disruption of the blood-brain barrier, and cerebral microhemorrhages. No available antimalarial drugs specifically target the endothelial disruptions underlying this complication, which is responsible for the majority of malaria-associated deaths. Here, we have demonstrated that ruptured Pf-iRBCs induce activation of β-catenin, leading to disruption of inter–endothelial cell junctions in human brain microvascular endothelial cells (HBMECs). Inhibition of β-catenin–induced TCF/LEF transcription in the nucleus of HBMECs prevented the disruption of endothelial junctions, confirming that β-catenin is a key mediator of P. falciparum adverse effects on endothelial integrity. Blockade of the angiotensin II type 1 receptor (AT1) or stimulation of the type 2 receptor (AT2) abrogated Pf-iRBC–induced activation of β-catenin and prevented the disruption of HBMEC monolayers. In a mouse model of cerebral malaria, modulation of angiotensin II receptors produced similar effects, leading to protection against cerebral malaria, reduced cerebral hemorrhages, and increased survival. In contrast, AT2-deficient mice were more susceptible to cerebral malaria. The interrelation of the β-catenin and the angiotensin II signaling pathways opens immediate host-targeted therapeutic possibilities for cerebral malaria and other diseases in which brain endothelial integrity is compromised. PMID:27643439

A prediction model for cognitive performance in health ageing using diffusion tensor imaging with graph theory.

PubMed

Yun, Ruijuan; Lin, Chung-Chih; Wu, Shuicai; Huang, Chu-Chung; Lin, Ching-Po; Chao, Yi-Ping

2013-01-01

In this study, we employed diffusion tensor imaging (DTI) to construct brain structural network and then derive the connection matrices from 96 healthy elderly subjects. The correlation analysis between these topological properties of network based on graph theory and the Cognitive Abilities Screening Instrument (CASI) index were processed to extract the significant network characteristics. These characteristics were then integrated to estimate the models by various machine-learning algorithms to predict user's cognitive performance. From the results, linear regression model and Gaussian processes model showed presented better abilities with lower mean absolute errors of 5.8120 and 6.25 to predict the cognitive performance respectively. Moreover, these extracted topological properties of brain structural network derived from DTI also could be regarded as the bio-signatures for further evaluation of brain degeneration in healthy aged and early diagnosis of mild cognitive impairment (MCI).

A Prototype Symbolic Model of Canonical Functional Neuroanatomy of the Motor System

PubMed Central

Rubin, Daniel L.; Halle, Michael; Musen, Mark; Kikinis, Ron

2008-01-01

Recent advances in bioinformatics have opened entire new avenues for organizing, integrating and retrieving neuroscientific data, in a digital, machine-processable format, which can be at the same time understood by humans, using ontological, symbolic data representations. Declarative information stored in ontological format can be perused and maintained by domain experts, interpreted by machines, and serve as basis for a multitude of decision-support, computerized simulation, data mining, and teaching applications. We have developed a prototype symbolic model of canonical neuroanatomy of the motor system. Our symbolic model is intended to support symbolic lookup, logical inference and mathematical modeling by integrating descriptive, qualitative and quantitative functional neuroanatomical knowledge. Furthermore, we show how our approach can be extended to modeling impaired brain connectivity in disease states, such as common movement disorders. In developing our ontology, we adopted a disciplined modeling approach, relying on a set of declared principles, a high-level schema, Aristotelian definitions, and a frame-based authoring system. These features, along with the use of the Unified Medical Language System (UMLS) vocabulary, enable the alignment of our functional ontology with an existing comprehensive ontology of human anatomy, and thus allow for combining the structural and functional views of neuroanatomy for clinical decision support and neuroanatomy teaching applications. Although the scope of our current prototype ontology is limited to a particular functional system in the brain, it may be possible to adapt this approach for modeling other brain functional systems as well. PMID:18164666

Integration of individual and social information for decision-making in groups of different sizes.

PubMed

Park, Seongmin A; Goïame, Sidney; O'Connor, David A; Dreher, Jean-Claude

2017-06-01

When making judgments in a group, individuals often revise their initial beliefs about the best judgment to make given what others believe. Despite the ubiquity of this phenomenon, we know little about how the brain updates beliefs when integrating personal judgments (individual information) with those of others (social information). Here, we investigated the neurocomputational mechanisms of how we adapt our judgments to those made by groups of different sizes, in the context of jury decisions for a criminal. By testing different theoretical models, we showed that a social Bayesian inference model captured changes in judgments better than 2 other models. Our results showed that participants updated their beliefs by appropriately weighting individual and social sources of information according to their respective credibility. When investigating 2 fundamental computations of Bayesian inference, belief updates and credibility estimates of social information, we found that the dorsal anterior cingulate cortex (dACC) computed the level of belief updates, while the bilateral frontopolar cortex (FPC) was more engaged in individuals who assigned a greater credibility to the judgments of a larger group. Moreover, increased functional connectivity between these 2 brain regions reflected a greater influence of group size on the relative credibility of social information. These results provide a mechanistic understanding of the computational roles of the FPC-dACC network in steering judgment adaptation to a group's opinion. Taken together, these findings provide a computational account of how the human brain integrates individual and social information for decision-making in groups.

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.

Gene therapy decreases seizures in a model of Incontinentia pigmenti.

PubMed

Dogbevia, Godwin K; Töllner, Kathrin; Körbelin, Jakob; Bröer, Sonja; Ridder, Dirk A; Grasshoff, Hanna; Brandt, Claudia; Wenzel, Jan; Straub, Beate K; Trepel, Martin; Löscher, Wolfgang; Schwaninger, Markus

2017-07-01

Incontinentia pigmenti (IP) is a genetic disease leading to severe neurological symptoms, such as epileptic seizures, but no specific treatment is available. IP is caused by pathogenic variants that inactivate the Nemo gene. Replacing Nemo through gene therapy might provide therapeutic benefits. In a mouse model of IP, we administered a single intravenous dose of the adeno-associated virus (AAV) vector, AAV-BR1-CAG-NEMO, delivering the Nemo gene to the brain endothelium. Spontaneous epileptic seizures and the integrity of the blood-brain barrier (BBB) were monitored. The endothelium-targeted gene therapy improved the integrity of the BBB. In parallel, it reduced the incidence of seizures and delayed their occurrence. Neonate mice intravenously injected with the AAV-BR1-CAG-NEMO vector developed no hepatocellular carcinoma or other major adverse effects 11 months after vector injection, demonstrating that the vector has a favorable safety profile. The data show that the BBB is a target of antiepileptic treatment and, more specifically, provide evidence for the therapeutic benefit of a brain endothelial-targeted gene therapy in IP. Ann Neurol 2017;82:93-104. © 2017 American Neurological Association.

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

Computational modeling of neurostimulation in brain diseases.

PubMed

Wang, Yujiang; Hutchings, Frances; Kaiser, Marcus

2015-01-01

Neurostimulation as a therapeutic tool has been developed and used for a range of different diseases such as Parkinson's disease, epilepsy, and migraine. However, it is not known why the efficacy of the stimulation varies dramatically across patients or why some patients suffer from severe side effects. This is largely due to the lack of mechanistic understanding of neurostimulation. Hence, theoretical computational approaches to address this issue are in demand. This chapter provides a review of mechanistic computational modeling of brain stimulation. In particular, we will focus on brain diseases, where mechanistic models (e.g., neural population models or detailed neuronal models) have been used to bridge the gap between cellular-level processes of affected neural circuits and the symptomatic expression of disease dynamics. We show how such models have been, and can be, used to investigate the effects of neurostimulation in the diseased brain. We argue that these models are crucial for the mechanistic understanding of the effect of stimulation, allowing for a rational design of stimulation protocols. Based on mechanistic models, we argue that the development of closed-loop stimulation is essential in order to avoid inference with healthy ongoing brain activity. Furthermore, patient-specific data, such as neuroanatomic information and connectivity profiles obtainable from neuroimaging, can be readily incorporated to address the clinical issue of variability in efficacy between subjects. We conclude that mechanistic computational models can and should play a key role in the rational design of effective, fully integrated, patient-specific therapeutic brain stimulation. © 2015 Elsevier B.V. All rights reserved.

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.

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

DTIC Science & Technology

2017-12-01

methodologies , and associated tools, rather than summaries or interpretations of this information, can accelerate research progress by allowing re-analysis of... Research Informatics Systems PRINCIPAL INVESTIGATOR: Cynthia Harrison-Felix, PhD CONTRACTING ORGANIZATION: Craig Hospital Englewood, CO 80113...REPORT DATE: December 2017 TYPE OF REPORT: Final PREPARED FOR: U.S. Army Medical Research and Materiel Command Fort Detrick, Maryland 21702

Neural network configuration and efficiency underlies individual differences in spatial orientation ability.

PubMed

Arnold, Aiden E G F; Protzner, Andrea B; Bray, Signe; Levy, Richard M; Iaria, Giuseppe

2014-02-01

Spatial orientation is a complex cognitive process requiring the integration of information processed in a distributed system of brain regions. Current models on the neural basis of spatial orientation are based primarily on the functional role of single brain regions, with limited understanding of how interaction among these brain regions relates to behavior. In this study, we investigated two sources of variability in the neural networks that support spatial orientation--network configuration and efficiency--and assessed whether variability in these topological properties relates to individual differences in orientation accuracy. Participants with higher accuracy were shown to express greater activity in the right supramarginal gyrus, the right precentral cortex, and the left hippocampus, over and above a core network engaged by the whole group. Additionally, high-performing individuals had increased levels of global efficiency within a resting-state network composed of brain regions engaged during orientation and increased levels of node centrality in the right supramarginal gyrus, the right primary motor cortex, and the left hippocampus. These results indicate that individual differences in the configuration of task-related networks and their efficiency measured at rest relate to the ability to spatially orient. Our findings advance systems neuroscience models of orientation and navigation by providing insight into the role of functional integration in shaping orientation behavior.

Circulating inflammatory biomarkers in relation to brain structural measurements in a non-demented elderly population.

PubMed

Gu, Yian; Vorburger, Robert; Scarmeas, Nikolaos; Luchsinger, José A; Manly, Jennifer J; Schupf, Nicole; Mayeux, Richard; Brickman, Adam M

2017-10-01

The aim of this investigation was to determine whether circulating inflammatory biomarkers c-reactive protein (CRP), interleukin-6 (IL6), and alpha 1-antichymotrypsin (ACT) were related to structural brain measures assessed by magnetic resonance imaging (MRI). High-resolution structural MRI was collected on 680 non-demented elderly (mean age 80.1years) participants of a community-based, multiethnic cohort. Approximately three quarters of these participants also had peripheral inflammatory biomarkers (CRP, IL6, and ACT) measured using ELISA. Structural measures including brain volumes and cortical thickness (with both global and regional measures) were derived from MRI scans, and repeated MRI measures were obtained after 4.5years. Mean fractional anisotropy was used as the indicator of white matter integrity assessed with diffusion tensor imaging. We examined the association of inflammatory biomarkers with brain volume, cortical thickness, and white matter integrity using regression models adjusted for age, gender, ethnicity, education, APOE genotype, and intracranial volume. A doubling in CRP (b=-2.48, p=0.002) was associated with a smaller total gray matter volume, equivalent to approximately 1.5years of aging. A doubling in IL6 was associated with smaller total brain volume (b=-14.96, p<0.0001), equivalent to approximately 9years of aging. Higher IL6 was also associated with smaller gray matter (b=-6.52, p=0.002) and white matter volumes (b=-7.47, p=0.004). The volumes of most cortical regions including frontal, occipital, parietal, temporal, as well as subcortical regions including pallidum and thalamus were associated with IL6. In a model additionally adjusted for depression, vascular factors, BMI, and smoking status, the association between IL6 and brain volumes remained, and a doubling in ACT was marginally associated with 0.054 (p=0.001) millimeter thinner mean cortical thickness, equivalent to that of approximately 2.7years of aging. None of the biomarkers was associated with mean fractional anisotropy or longitudinal change of brain volumes and thickness. Among older adults, increased circulating inflammatory biomarkers were associated with smaller brain volume and cortical thickness but not the white matter tract integrity. Our preliminary findings suggest that peripheral inflammatory processes may be involved in the brain atrophy in the elderly. Copyright © 2017 Elsevier Inc. All rights reserved.

Dynamical Signatures of Structural Connectivity Damage to a Model of the Brain Posed at Criticality.

PubMed

Haimovici, Ariel; Balenzuela, Pablo; Tagliazucchi, Enzo

2016-12-01

Synchronization of brain activity fluctuations is believed to represent communication between spatially distant neural processes. These interareal functional interactions develop in the background of a complex network of axonal connections linking cortical and subcortical neurons, termed the human "structural connectome." Theoretical considerations and experimental evidence support the view that the human brain can be modeled as a system operating at a critical point between ordered (subcritical) and disordered (supercritical) phases. Here, we explore the hypothesis that pathologies resulting from brain injury of different etiologies are related to this model of a critical brain. For this purpose, we investigate how damage to the integrity of the structural connectome impacts on the signatures of critical dynamics. Adopting a hybrid modeling approach combining an empirical weighted network of human structural connections with a conceptual model of critical dynamics, we show that lesions located at highly transited connections progressively displace the model toward the subcritical regime. The topological properties of the nodes and links are of less importance when considered independently of their weight in the network. We observe that damage to midline hubs such as the middle and posterior cingulate cortex is most crucial for the disruption of criticality in the model. However, a similar effect can be achieved by targeting less transited nodes and links whose connection weights add up to an equivalent amount. This implies that brain pathology does not necessarily arise due to insult targeted at well-connected areas and that intersubject variability could obscure lesions located at nonhub regions. Finally, we discuss the predictions of our model in the context of clinical studies of traumatic brain injury and neurodegenerative disorders.

NeuCube: a spiking neural network architecture for mapping, learning and understanding of spatio-temporal brain data.

PubMed

Kasabov, Nikola K

2014-04-01

The brain functions as a spatio-temporal information processing machine. Spatio- and spectro-temporal brain data (STBD) are the most commonly collected data for measuring brain response to external stimuli. An enormous amount of such data has been already collected, including brain structural and functional data under different conditions, molecular and genetic data, in an attempt to make a progress in medicine, health, cognitive science, engineering, education, neuro-economics, Brain-Computer Interfaces (BCI), and games. Yet, there is no unifying computational framework to deal with all these types of data in order to better understand this data and the processes that generated it. Standard machine learning techniques only partially succeeded and they were not designed in the first instance to deal with such complex data. Therefore, there is a need for a new paradigm to deal with STBD. This paper reviews some methods of spiking neural networks (SNN) and argues that SNN are suitable for the creation of a unifying computational framework for learning and understanding of various STBD, such as EEG, fMRI, genetic, DTI, MEG, and NIRS, in their integration and interaction. One of the reasons is that SNN use the same computational principle that generates STBD, namely spiking information processing. This paper introduces a new SNN architecture, called NeuCube, for the creation of concrete models to map, learn and understand STBD. A NeuCube model is based on a 3D evolving SNN that is an approximate map of structural and functional areas of interest of the brain related to the modeling STBD. Gene information is included optionally in the form of gene regulatory networks (GRN) if this is relevant to the problem and the data. A NeuCube model learns from STBD and creates connections between clusters of neurons that manifest chains (trajectories) of neuronal activity. Once learning is applied, a NeuCube model can reproduce these trajectories, even if only part of the input STBD or the stimuli data is presented, thus acting as an associative memory. The NeuCube framework can be used not only to discover functional pathways from data, but also as a predictive system of brain activities, to predict and possibly, prevent certain events. Analysis of the internal structure of a model after training can reveal important spatio-temporal relationships 'hidden' in the data. NeuCube will allow the integration in one model of various brain data, information and knowledge, related to a single subject (personalized modeling) or to a population of subjects. The use of NeuCube for classification of STBD is illustrated in a case study problem of EEG data. NeuCube models result in a better accuracy of STBD classification than standard machine learning techniques. They are robust to noise (so typical in brain data) and facilitate a better interpretation of the results and understanding of the STBD and the brain conditions under which data was collected. Future directions for the use of SNN for STBD are discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.

Graph theoretical modeling of baby brain networks.

PubMed

Zhao, Tengda; Xu, Yuehua; He, Yong

2018-06-12

The human brain undergoes explosive growth during the prenatal period and the first few postnatal years, establishing an early infrastructure for the later development of behaviors and cognitions. Revealing the developmental rules during the early phrase is essential in understanding the emergence of brain function and the origin of developmental disorders. The graph-theoretical network modeling in combination with multiple neuroimaging probes provides an important research framework to explore early development of the topological wiring and organizational paradigms of the brain. Here, we reviewed studies which employed neuroimaging and graph-theoretical modeling to investigate brain network development from approximately 20 gestational weeks to 2 years of age. Specifically, the structural and functional brain networks have evolved to highly efficient topological architectures in the early stage; where the structural network remains ahead and paves the way for the development of functional network. The brain network develops in a heterogeneous order, from primary to higher-order systems and from a tendency of network segregation to network integration in the prenatal and postnatal periods. The early brain network topologies show abilities in predicting certain cognitive and behavior performance in later life, and their impairments are likely to continue into childhood and even adulthood. These macroscopic topological changes are found to be associated with possible microstructural maturations, such as axonal growth and myelinations. Collectively, this review provides a detailed delineation of the early changes of the baby brains in the graph-theoretical modeling framework, which opens up a new avenue to understand the developmental principles of the connectome. Copyright © 2018. Published by Elsevier Inc.

TU-G-210-01: Modeling for Breast and Brain HIFU Treatment Planning

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

Christensen, D.

Modeling can play a vital role in predicting, optimizing and analyzing the results of therapeutic ultrasound treatments. Simulating the propagating acoustic beam in various targeted regions of the body allows for the prediction of the resulting power deposition and temperature profiles. In this session we will apply various modeling approaches to breast, abdominal organ and brain treatments. Of particular interest is the effectiveness of procedures for correcting for phase aberrations caused by intervening irregular tissues, such as the skull in transcranial applications or inhomogeneous breast tissues. Also described are methods to compensate for motion in targeted abdominal organs such asmore » the liver or kidney. Douglas Christensen – Modeling for Breast and Brain HIFU Treatment Planning Tobias Preusser – TRANS-FUSIMO – An Integrative Approach to Model-Based Treatment Planning of Liver FUS Tobias Preusser – TRANS-FUSIMO – An Integrative Approach to Model-Based Treatment Planning of Liver FUS Learning Objectives: Understand the role of acoustic beam modeling for predicting the effectiveness of therapeutic ultrasound treatments. Apply acoustic modeling to specific breast, liver, kidney and transcranial anatomies. Determine how to obtain appropriate acoustic modeling parameters from clinical images. Understand the separate role of absorption and scattering in energy delivery to tissues. See how organ motion can be compensated for in ultrasound therapies. Compare simulated data with clinical temperature measurements in transcranial applications. Supported by NIH R01 HL172787 and R01 EB013433 (DC); EU Seventh Framework Programme (FP7/2007-2013) under 270186 (FUSIMO) and 611889 (TRANS-FUSIMO)(TP); and P01 CA159992, GE, FUSF and InSightec (UV)« less

bFGF Protects Against Blood-Brain Barrier Damage Through Junction Protein Regulation via PI3K-Akt-Rac1 Pathway Following Traumatic Brain Injury.

PubMed

Wang, Zhou-Guang; Cheng, Yi; Yu, Xi-Chong; Ye, Li-Bing; Xia, Qing-Hai; Johnson, Noah R; Wei, Xiaojie; Chen, Da-Qing; Cao, Guodong; Fu, Xiao-Bing; Li, Xiao-Kun; Zhang, Hong-Yu; Xiao, Jian

2016-12-01

Many traumatic brain injury (TBI) survivors sustain neurological disability and cognitive impairments due to the lack of defined therapies to reduce TBI-induced blood-brain barrier (BBB) breakdown. Exogenous basic fibroblast growth factor (bFGF) has been shown to have neuroprotective function in brain injury. The present study therefore investigates the beneficial effects of bFGF on the BBB after TBI and the underlying mechanisms. In this study, we demonstrate that bFGF reduces neurofunctional deficits and preserves BBB integrity in a mouse model of TBI. bFGF suppresses RhoA and upregulates tight junction proteins, thereby mitigating BBB breakdown. In vitro, bFGF exerts a protective effect on BBB by upregulating tight junction proteins claudin-5, occludin, zonula occludens-1, p120-catenin, and β-catenin under oxygen glucose deprivation/reoxygenation (OGD) in human brain microvascular endothelial cells (HBMECs). Both the in vivo and in vitro effects are related to the activation of the downstream signaling pathway, PI3K/Akt/Rac-1. Inhibition of the PI3K/Akt or Rac-1 by specific inhibitors LY294002 or si-Rac-1, respectively, partially reduces the protective effect of bFGF on BBB integrity. Overall, our results indicate that the protective role of bFGF on BBB involves the regulation of tight junction proteins and RhoA in the TBI model and OGD-induced HBMECs injury, and that activation of the PI3K/Akt /Rac-1 signaling pathway underlies these effects.

Exploring the Neural Basis of Fairness: A Model of Neuro-Organizational Justice

ERIC Educational Resources Information Center

Beugre, Constant D.

2009-01-01

Drawing from the literature in neuroeconomics, organizational justice, and social cognitive neuroscience, I propose a model of neuro-organizational justice that explores the role of the brain in how people form fairness judgments and react to situations of fairness and/or unfairness in organizations. The model integrates three levels of analysis:…

Integration of Multidisciplinary Sensory Data:

PubMed Central

Miller, Perry L.; Nadkarni, Prakash; Singer, Michael; Marenco, Luis; Hines, Michael; Shepherd, Gordon

2001-01-01

The paper provides an overview of neuroinformatics research at Yale University being performed as part of the national Human Brain Project. This research is exploring the integration of multidisciplinary sensory data, using the olfactory system as a model domain. The neuroinformatics activities fall into three main areas: 1) building databases and related tools that support experimental olfactory research at Yale and can also serve as resources for the field as a whole, 2) using computer models (molecular models and neuronal models) to help understand data being collected experimentally and to help guide further laboratory experiments, 3) performing basic neuroinformatics research to develop new informatics technologies, including a flexible data model (EAV/CR, entity-attribute-value with classes and relationships) designed to facilitate the integration of diverse heterogeneous data within a single unifying framework. PMID:11141511

The Role of Stress Regulation on Neural Plasticity in Pain Chronification.

PubMed

Li, Xiaoyun; Hu, Li

2016-01-01

Pain, especially chronic pain, is one of the most common clinical symptoms and has been considered as a worldwide healthcare problem. The transition from acute to chronic pain is accompanied by a chain of alterations in physiology, pathology, and psychology. Increasing clinical studies and complementary animal models have elucidated effects of stress regulation on the pain chronification via investigating activations of the hypothalamic-pituitary-adrenal (HPA) axis and changes in some crucial brain regions, including the amygdala, prefrontal cortex, and hippocampus. Although individuals suffer from acute pain benefit from such physiological alterations, chronic pain is commonly associated with maladaptive responses, like the HPA dysfunction and abnormal brain plasticity. However, the causal relationship among pain chronification, stress regulation, and brain alterations is rarely discussed. To call for more attention on this issue, we review recent findings obtained from clinical populations and animal models, propose an integrated stress model of pain chronification based on the existing models in perspectives of environmental influences and genetic predispositions, and discuss the significance of investigating the role of stress regulation on brain alteration in pain chronification for various clinical applications.

The Role of Stress Regulation on Neural Plasticity in Pain Chronification

PubMed Central

Li, Xiaoyun

2016-01-01

Pain, especially chronic pain, is one of the most common clinical symptoms and has been considered as a worldwide healthcare problem. The transition from acute to chronic pain is accompanied by a chain of alterations in physiology, pathology, and psychology. Increasing clinical studies and complementary animal models have elucidated effects of stress regulation on the pain chronification via investigating activations of the hypothalamic-pituitary-adrenal (HPA) axis and changes in some crucial brain regions, including the amygdala, prefrontal cortex, and hippocampus. Although individuals suffer from acute pain benefit from such physiological alterations, chronic pain is commonly associated with maladaptive responses, like the HPA dysfunction and abnormal brain plasticity. However, the causal relationship among pain chronification, stress regulation, and brain alterations is rarely discussed. To call for more attention on this issue, we review recent findings obtained from clinical populations and animal models, propose an integrated stress model of pain chronification based on the existing models in perspectives of environmental influences and genetic predispositions, and discuss the significance of investigating the role of stress regulation on brain alteration in pain chronification for various clinical applications. PMID:28053788

Sigmund Freud-early network theories of the brain.

PubMed

Surbeck, Werner; Killeen, Tim; Vetter, Johannes; Hildebrandt, Gerhard

2018-06-01

Since the early days of modern neuroscience, psychological models of brain function have been a key component in the development of new knowledge. These models aim to provide a framework that allows the integration of discoveries derived from the fundamental disciplines of neuroscience, including anatomy and physiology, as well as clinical neurology and psychiatry. During the initial stages of his career, Sigmund Freud (1856-1939), became actively involved in these nascent fields with a burgeoning interest in functional neuroanatomy. In contrast to his contemporaries, Freud was convinced that cognition could not be localised to separate modules and that the brain processes cognition not in a merely serial manner but in a parallel and dynamic fashion-anticipating fundamental aspects of current network theories of brain function. This article aims to shed light on Freud's seminal, yet oft-overlooked, early work on functional neuroanatomy and his reasons for finally abandoning the conventional neuroscientific "brain-based" reference frame in order to conceptualise the mind from a purely psychological perspective.

A pilot study on the operationalization of the Model of Occupational Self Efficacy: A model for the reintegration of persons with brain injuries to their worker roles.

PubMed

Soeker, Shaheed

2015-01-01

Traumatic brain injury causes functional limitations that can cause people to struggle to reintegrate in the workplace despite participating in work rehabilitation programmes. The aim of the study was to explore, and describe the experiences of individuals with Traumatic Brain Injury regarding returning to work through the use of the model of occupational self-efficacy. In the study 10 individuals who were diagnosed with a mild to moderate brain injury participated in the study. The research study was positioned within the qualitative paradigm specifically utilizing case study methodology. In order to gather data from the participants, individual interviews and participant observation techniques were used. Two themes emerged from the findings of the study theme one reflected the barriers related to the use of the model (i.e. Theme one: Effective participation in the model is affected by financial assistance). The second theme related to the enabling factors related to the use of the model (i.e. Theme two: A sense of normality). The findings of this study indicated that the Model of Occupational Self Efficacy (MOS) is a useful model to use in retraining the work skills of individual's who sustained a traumatic brain injury. The participants in this study could maintain employment in the open labour market for a period of at least 12 months and it improved their ability to accept their brain injury as well as adapt to their worker roles. The MOS also provides a framework for facilitating community integration.

Towards a real-time interface between a biomimetic model of sensorimotor cortex and a robotic arm

PubMed Central

Dura-Bernal, Salvador; Chadderdon, George L; Neymotin, Samuel A; Francis, Joseph T; Lytton, William W

2015-01-01

Brain-machine interfaces can greatly improve the performance of prosthetics. Utilizing biomimetic neuronal modeling in brain machine interfaces (BMI) offers the possibility of providing naturalistic motor-control algorithms for control of a robotic limb. This will allow finer control of a robot, while also giving us new tools to better understand the brain’s use of electrical signals. However, the biomimetic approach presents challenges in integrating technologies across multiple hardware and software platforms, so that the different components can communicate in real-time. We present the first steps in an ongoing effort to integrate a biomimetic spiking neuronal model of motor learning with a robotic arm. The biomimetic model (BMM) was used to drive a simple kinematic two-joint virtual arm in a motor task requiring trial-and-error convergence on a single target. We utilized the output of this model in real time to drive mirroring motion of a Barrett Technology WAM robotic arm through a user datagram protocol (UDP) interface. The robotic arm sent back information on its joint positions, which was then used by a visualization tool on the remote computer to display a realistic 3D virtual model of the moving robotic arm in real time. This work paves the way towards a full closed-loop biomimetic brain-effector system that can be incorporated in a neural decoder for prosthetic control, to be used as a platform for developing biomimetic learning algorithms for controlling real-time devices. PMID:26709323

Diffusion tensor imaging reveals adolescent binge ethanol-induced brain structural integrity alterations in adult rats that correlate with behavioral dysfunction.

PubMed

Vetreno, Ryan P; Yaxley, Richard; Paniagua, Beatriz; Crews, Fulton T

2016-07-01

Adolescence is characterized by considerable brain maturation that coincides with the development of adult behavior. Binge drinking is common during adolescence and can have deleterious effects on brain maturation because of the heightened neuroplasticity of the adolescent brain. Using an animal model of adolescent intermittent ethanol [AIE; 5.0 g/kg, intragastric, 20 percent EtOH w/v; 2 days on/2 days off from postnatal day (P)25 to P55], we assessed the adult brain structural volumes and integrity on P80 and P220 using diffusion tensor imaging (DTI). While we did not observe a long-term effect of AIE on structural volumes, AIE did reduce axial diffusivity (AD) in the cerebellum, hippocampus and neocortex. Radial diffusivity (RD) was reduced in the hippocampus and neocortex of AIE-treated animals. Prior AIE treatment did not affect fractional anisotropy (FA), but did lead to long-term reductions of mean diffusivity (MD) in both the cerebellum and corpus callosum. AIE resulted in increased anxiety-like behavior and diminished object recognition memory, the latter of which was positively correlated with DTI measures. Across aging, whole brain volumes increased, as did volumes of the corpus callosum and neocortex. This was accompanied by age-associated AD reductions in the cerebellum and neocortex as well as RD and MD reductions in the cerebellum. Further, we found that FA increased in both the cerebellum and corpus callosum as rats aged from P80 to P220. Thus, both age and AIE treatment caused long-term changes to brain structural integrity that could contribute to cognitive dysfunction. © 2015 Society for the Study of Addiction.

Adolescent Emotional Maturation through Divergent Models of Brain Organization

PubMed Central

Oron Semper, Jose V.; Murillo, Jose I.; Bernacer, Javier

2016-01-01

In this article we introduce the hypothesis that neuropsychological adolescent maturation, and in particular emotional management, may have opposing explanations depending on the interpretation of the assumed brain architecture, that is, whether a componential computational account (CCA) or a dynamic systems perspective (DSP) is used. According to CCA, cognitive functions are associated with the action of restricted brain regions, and this association is temporally stable; by contrast, DSP argues that cognitive functions are better explained by interactions between several brain areas, whose engagement in specific functions is temporal and context-dependent and based on neural reuse. We outline the main neurobiological facts about adolescent maturation, focusing on the neuroanatomical and neurofunctional processes associated with adolescence. We then explain the importance of emotional management in adolescent maturation. We explain the interplay between emotion and cognition under the scope of CCA and DSP, both at neural and behavioral levels. Finally, we justify why, according to CCA, emotional management is understood as regulation, specifically because the cognitive aspects of the brain are in charge of regulating emotion-related modules. However, the key word in DSP is integration, since neural information from different brain areas is integrated from the beginning of the process. Consequently, although the terms should not be conceptually confused, there is no cognition without emotion, and vice versa. Thus, emotional integration is not an independent process that just happens to the subject, but a crucial part of personal growth. Considering the importance of neuropsychological research in the development of educational and legal policies concerning adolescents, we intend to expose that the holistic view of adolescents is dependent on whether one holds the implicit or explicit interpretation of brain functioning. PMID:27602012

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.

Dysfunctional tubular endoplasmic reticulum constitutes a pathological feature of Alzheimer's disease.

PubMed

Sharoar, M G; Shi, Q; Ge, Y; He, W; Hu, X; Perry, G; Zhu, X; Yan, R

2016-09-01

Pathological features in Alzheimer's brains include mitochondrial dysfunction and dystrophic neurites (DNs) in areas surrounding amyloid plaques. Using a mouse model that overexpresses reticulon 3 (RTN3) and spontaneously develops age-dependent hippocampal DNs, here we report that DNs contain both RTN3 and REEPs, topologically similar proteins that can shape tubular endoplasmic reticulum (ER). Importantly, ultrastructural examinations of such DNs revealed gradual accumulation of tubular ER in axonal termini, and such abnormal tubular ER inclusion is found in areas surrounding amyloid plaques in biopsy samples from Alzheimer's disease (AD) brains. Functionally, abnormally clustered tubular ER induces enhanced mitochondrial fission in the early stages of DN formation and eventual mitochondrial degeneration at later stages. Furthermore, such DNs are abrogated when RTN3 is ablated in aging and AD mouse models. Hence, abnormally clustered tubular ER can be pathogenic in brain regions: disrupting mitochondrial integrity, inducing DNs formation and impairing cognitive function in AD and aging brains.

An integrated system for synchronous detection of neuron spikes and dopamine activities in the striatum of Parkinson monkey brain.

PubMed

Xu, Shengwei; Zhang, Yu; Zhang, Song; Xiao, Guihua; Wang, Mixia; Song, Yilin; Gao, Fei; Li, Ziyue; Zhuang, Ping; Chan, Piu; Tao, Guoxian; Yue, Feng; Cai, Xinxia

2018-07-01

Synchronous detecting neuron spikes and dopamine (DA) activities in the non-human primate brain play an important role in understanding of Parkinson's disease (PD). At present, most experiments are carried out by combing of electrodes and commercial instruments, which are inconvenient, time-consuming and inefficient. Herein, this study describes a novel integrated system for monitoring neuron spikes and DA activities in non-human primate brain synchronously. This system integrates an implantable sensor, a dual-function head-stage and a low noise detection instrument. The system was developed efficiently by using the key technologies of noise reduction, interference protection and differential amplification. To demonstrate the utility of this system, synchronous recordings of electrophysiological signals and DA were in vivo performed in a monkey before and after treated as a Parkinson model monkey. The system typically exhibited input-referred noise levels of only ∼ 3 μV RMS , input impedance levels of up to 5.1 GΩ, and a sensitivity of 14.075 pA/μM for DA and could detect electrophysiological signals and DA without mutual interference. In monkey experiments, lower DA concentrations in the striatum and more intensive spikes of the Parkinson model monkey than the normal one were synchronously recorded efficiently. This integrated system will not only significantly simplify the experimental operation and improve the experimental efficiency, but also improve the signal quality and synchronization performance. This integrated system, which is practical, efficient and convenient, can be widely used for the study of PD and other neurological disorders. Copyright © 2018 Elsevier B.V. All rights reserved.

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

Emerging role of the brain in the homeostatic regulation of energy and glucose metabolism.

PubMed

Roh, Eun; Song, Do Kyeong; Kim, Min-Seon

2016-03-11

Accumulated evidence from genetic animal models suggests that the brain, particularly the hypothalamus, has a key role in the homeostatic regulation of energy and glucose metabolism. The brain integrates multiple metabolic inputs from the periphery through nutrients, gut-derived satiety signals and adiposity-related hormones. The brain modulates various aspects of metabolism, such as food intake, energy expenditure, insulin secretion, hepatic glucose production and glucose/fatty acid metabolism in adipose tissue and skeletal muscle. Highly coordinated interactions between the brain and peripheral metabolic organs are critical for the maintenance of energy and glucose homeostasis. Defective crosstalk between the brain and peripheral organs contributes to the development of obesity and type 2 diabetes. Here we comprehensively review the above topics, discussing the main findings related to the role of the brain in the homeostatic regulation of energy and glucose metabolism.

Emerging role of the brain in the homeostatic regulation of energy and glucose metabolism

PubMed Central

Roh, Eun; Song, Do Kyeong; Kim, Min-Seon

2016-01-01

Accumulated evidence from genetic animal models suggests that the brain, particularly the hypothalamus, has a key role in the homeostatic regulation of energy and glucose metabolism. The brain integrates multiple metabolic inputs from the periphery through nutrients, gut-derived satiety signals and adiposity-related hormones. The brain modulates various aspects of metabolism, such as food intake, energy expenditure, insulin secretion, hepatic glucose production and glucose/fatty acid metabolism in adipose tissue and skeletal muscle. Highly coordinated interactions between the brain and peripheral metabolic organs are critical for the maintenance of energy and glucose homeostasis. Defective crosstalk between the brain and peripheral organs contributes to the development of obesity and type 2 diabetes. Here we comprehensively review the above topics, discussing the main findings related to the role of the brain in the homeostatic regulation of energy and glucose metabolism. PMID:26964832

Epsilon Aminocaproic Acid Pretreatment Provides Neuroprotection Following Surgically Induced Brain Injury in a Rat Model.

PubMed

Komanapalli, Esther S; Sherchan, Prativa; Rolland, William; Khatibi, Nikan; Martin, Robert D; Applegate, Richard L; Tang, Jiping; Zhang, John H

2016-01-01

Neurosurgical procedures can damage viable brain tissue unintentionally by a wide range of mechanisms. This surgically induced brain injury (SBI) can be a result of direct incision, electrocauterization, or tissue retraction. Plasmin, a serine protease that dissolves fibrin blood clots, has been shown to enhance cerebral edema and hemorrhage accumulation in the brain through disruption of the blood brain barrier. Epsilon aminocaproic acid (EAA), a recognized antifibrinolytic lysine analogue, can reduce the levels of active plasmin and, in doing so, potentially can preserve the neurovascular unit of the brain. We investigated the role of EAA as a pretreatment neuroprotective modality in a SBI rat model, hypothesizing that EAA therapy would protect brain tissue integrity, translating into preserved neurobehavioral function. Male Sprague-Dawley rats were randomly assigned to one of four groups: sham (n = 7), SBI (n = 7), SBI with low-dose EAA, 150 mg/kg (n = 7), and SBI with high-dose EAA, 450 mg/kg (n = 7). SBI was induced by partial right frontal lobe resection through a frontal craniotomy. Postoperative assessment at 24 h included neurobehavioral testing and measurement of brain water content. Results at 24 h showed both low- and high-dose EAA reduced brain water content and improved neurobehavioral function compared with the SBI groups. This suggests that EAA may be a useful pretherapeutic modality for SBI. Further studies are needed to clarify optimal therapeutic dosing and to identify mechanisms of neuroprotection in rat SBI models.

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.

3D-Reconstructions and Virtual 4D-Visualization to Study Metamorphic Brain Development in the Sphinx Moth Manduca Sexta

PubMed Central

Huetteroth, Wolf; el Jundi, Basil; el Jundi, Sirri; Schachtner, Joachim

2009-01-01

During metamorphosis, the transition from the larva to the adult, the insect brain undergoes considerable remodeling: new neurons are integrated while larval neurons are remodeled or eliminated. One well acknowledged model to study metamorphic brain development is the sphinx moth Manduca sexta. To further understand mechanisms involved in the metamorphic transition of the brain we generated a 3D standard brain based on selected brain areas of adult females and 3D reconstructed the same areas during defined stages of pupal development. Selected brain areas include for example mushroom bodies, central complex, antennal- and optic lobes. With this approach we eventually want to quantify developmental changes in neuropilar architecture, but also quantify changes in the neuronal complement and monitor the development of selected neuronal populations. Furthermore, we used a modeling software (Cinema 4D) to create a virtual 4D brain, morphing through its developmental stages. Thus the didactical advantages of 3D visualization are expanded to better comprehend complex processes of neuropil formation and remodeling during development. To obtain datasets of the M. sexta brain areas, we stained whole brains with an antiserum against the synaptic vesicle protein synapsin. Such labeled brains were then scanned with a confocal laser scanning microscope and selected neuropils were reconstructed with the 3D software AMIRA 4.1. PMID:20339481

3D-Reconstructions and Virtual 4D-Visualization to Study Metamorphic Brain Development in the Sphinx Moth Manduca Sexta.

PubMed

Huetteroth, Wolf; El Jundi, Basil; El Jundi, Sirri; Schachtner, Joachim

2010-01-01

DURING METAMORPHOSIS, THE TRANSITION FROM THE LARVA TO THE ADULT, THE INSECT BRAIN UNDERGOES CONSIDERABLE REMODELING: new neurons are integrated while larval neurons are remodeled or eliminated. One well acknowledged model to study metamorphic brain development is the sphinx moth Manduca sexta. To further understand mechanisms involved in the metamorphic transition of the brain we generated a 3D standard brain based on selected brain areas of adult females and 3D reconstructed the same areas during defined stages of pupal development. Selected brain areas include for example mushroom bodies, central complex, antennal- and optic lobes. With this approach we eventually want to quantify developmental changes in neuropilar architecture, but also quantify changes in the neuronal complement and monitor the development of selected neuronal populations. Furthermore, we used a modeling software (Cinema 4D) to create a virtual 4D brain, morphing through its developmental stages. Thus the didactical advantages of 3D visualization are expanded to better comprehend complex processes of neuropil formation and remodeling during development. To obtain datasets of the M. sexta brain areas, we stained whole brains with an antiserum against the synaptic vesicle protein synapsin. Such labeled brains were then scanned with a confocal laser scanning microscope and selected neuropils were reconstructed with the 3D software AMIRA 4.1.

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.

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...

Docosahexaenoic acid: brain accretion and roles in neuroprotection after brain hypoxia and ischemia

PubMed Central

Mayurasakorn, Korapat; Williams, Jill J.; Ten, Vadim S.; Deckelbaum, Richard J.

2014-01-01

Purpose of review With important effects on neuronal lipid composition, neurochemical signaling and cerebrovascular pathobiology, docosahexaenoic acid (DHA), a n-3 polyunsaturated fatty acid, may emerge as a neuroprotective agent against cerebrovascular disease. This paper examines pathways for DHA accretion in brain and evidence for possible roles of DHA in prophylactic and therapeutic approaches for cerebrovascular disease. Recent findings DHA is a major n-3 fatty acid in the mammalian central nervous system and enhances synaptic activities in neuronal cells. DHA can be obtained through diet or to a limited extent via conversion from its precursor, α-linolenic acid (α-LNA). DHA attenuates brain necrosis after hypoxic ischemic injury, principally by modulating membrane biophysical properties and maintaining integrity in functions between pre-and post-synaptic areas, resulting in better stabilizing intracellular ion balance in hypoxic-ischemic insult. Additionally, DHA alleviates brain apoptosis, by inducing anti-apoptotic activities such as decreasing responses to reactive oxygen species, up-regulating anti-apoptotic protein expression, down-regulating apoptotic protein expression, and maintaining mitochondrial integrity and function. Summary DHA in brain relates to a number of efficient delivery and accretion pathways. In animal models DHA renders neuroprotection after hypoxic-ischemic injury by regulating multiple molecular pathways and gene expression. PMID:21178607

Blood-brain barrier (BBB) toxicity and permeability assessment after L-(4-¹⁰Boronophenyl)alanine, a conventional B-containing drug for boron neutron capture therapy, using an in vitro BBB model.

PubMed

Roda, E; Nion, S; Bernocchi, G; Coccini, T

2014-10-02

Since brain tumours are the primary candidates for treatment by Boron Neutron Capture Therapy, one major challenge in the selective drug delivery to CNS is the crossing of the blood-brain barrier (BBB). The present pilot study investigated (i) the transport of a conventional B-containing product (i.e., L-(4-(10)Boronophenyl)alanine, L-(10)BPA), already used in medicine but still not fully characterized regarding its CNS interactions, as well as (ii) the effects of the L-(10)BPA on the BBB integrity using an in vitro model, consisting of brain capillary endothelial cells co-cultured with glial cells, closely mimicking the in vivo conditions. The multi-step experimental strategy (i.e. Integrity test, Filter study, Transport assay) checked L-(10)BPA toxicity at 80 µg Boron equivalent/ml, and its ability to cross the BBB, additionally by characterizing the cytoskeletal and TJ's proteins by immunocytochemistry and immunoblotting. In conclusion, a lack of toxic effects of L-(10)BPA was demonstrated, nevertheless accompanied by cellular stress phenomena (e.g. vimentin expression modification), paralleled by a low permeability coefficient (0.39 ± 0.01 × 10(-3)cm min(-1)), corroborating the scarce probability that L-(10)BPA would reach therapeutically effective cerebral concentration. These findings emphasized the need for novel strategies aimed at optimizing boron delivery to brain tumours, trying to ameliorate the compound uptake or developing new targeted products suitable to safely and effectively treat head cancer. Thus, the use of in vitro BBB model for screening studies may provide a useful early safety assessment for new effective compounds. Copyright © 2014 Elsevier B.V. All rights reserved.

Phosphorylated recombinant HSP27 protects the brain and attenuates blood-brain barrier disruption following stroke in mice receiving intravenous tissue-plasminogen activator.

PubMed

Shimada, Yoshiaki; Shimura, Hideki; Tanaka, Ryota; Yamashiro, Kazuo; Koike, Masato; Uchiyama, Yasuo; Urabe, Takao; Hattori, Nobutaka

2018-01-01

Loss of integrity of the blood-brain barrier (BBB) in ischemic stroke victims initiates a devastating cascade of events causing brain damage. Maintaining the BBB is important to preserve brain function in ischemic stroke. Unfortunately, recombinant tissue plasminogen activator (tPA), the only effective fibrinolytic treatment at the acute stage of ischemic stroke, also injures the BBB and increases the risk of brain edema and secondary hemorrhagic transformation. Thus, it is important to identify compounds that maintain BBB integrity in the face of ischemic injury in patients with stroke. We previously demonstrated that intravenously injected phosphorylated recombinant heat shock protein 27 (prHSP27) protects the brains of mice with transient middle cerebral artery occlusion (tMCAO), an animal stroke-model. Here, we determined whether prHSP27, in addition to attenuating brain injury, also decreases BBB damage in hyperglycemic tMCAO mice that had received tPA. After induction of hyperglycemia and tMCAO, we examined 4 treatment groups: 1) bovine serum albumin (BSA), 2) prHSP27, 3) tPA, 4) tPA plus prHSP27. We examined the effects of prHSP27 by comparing the BSA and prHSP27 groups and the tPA and tPA plus prHSP27 groups. Twenty-four hours after injection, prHSP27 reduced infarct volume, brain swelling, neurological deficits, the loss of microvessel proteins and endothelial cell walls, and mortality. It also reduced the rates of hemorrhagic transformation, extravasation of endogenous IgG, and MMP-9 activity, signs of BBB damage. Therefore, prHSP27 injection attenuated brain damage and preserved the BBB in tPA-injected, hyperglycemic tMCAO experimental stroke-model mice, in which the BBB is even more severely damaged than in simple tMCAO mice. The attenuation of brain damage and BBB disruption in the presence of tPA suggests the effectiveness of prHSP27 and tPA as a combination therapy. prHSP27 may be a novel therapeutic agent for ischemic stroke patients whose BBBs are injured following tPA injections.

Theory and practice in sport psychology and motor behaviour needs to be constrained by integrative modelling of brain and behaviour.

PubMed

Keil, D; Holmes, P; Bennett, S; Davids, K; Smith, N

2000-06-01

Because of advances in technology, the non-invasive study of the human brain has enhanced the knowledge base within the neurosciences, resulting in an increased impact on the psychological study of human behaviour. We argue that application of this knowledge base should be considered in theoretical modelling within sport psychology and motor behaviour alongside existing ideas. We propose that interventions founded on current theoretical and empirical understanding in both psychology and the neurosciences may ultimately lead to greater benefits for athletes during practice and performance. As vehicles for exploring the arguments of a greater integration of psychology and neurosciences research, imagery and perception-action within the sport psychology and motor behaviour domains will serve as exemplars. Current neuroscience evidence will be discussed in relation to theoretical developments; the implications for sport scientists will be considered.

Fast associative memory + slow neural circuitry = the computational model of the brain.

NASA Astrophysics Data System (ADS)

Berkovich, Simon; Berkovich, Efraim; Lapir, Gennady

1997-08-01

We propose a computational model of the brain based on a fast associative memory and relatively slow neural processors. In this model, processing time is expensive but memory access is not, and therefore most algorithmic tasks would be accomplished by using large look-up tables as opposed to calculating. The essential feature of an associative memory in this context (characteristic for a holographic type memory) is that it works without an explicit mechanism for resolution of multiple responses. As a result, the slow neuronal processing elements, overwhelmed by the flow of information, operate as a set of templates for ranking of the retrieved information. This structure addresses the primary controversy in the brain architecture: distributed organization of memory vs. localization of processing centers. This computational model offers an intriguing explanation of many of the paradoxical features in the brain architecture, such as integration of sensors (through DMA mechanism), subliminal perception, universality of software, interrupts, fault-tolerance, certain bizarre possibilities for rapid arithmetics etc. In conventional computer science the presented type of a computational model did not attract attention as it goes against the technological grain by using a working memory faster than processing elements.

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.

Toward the Language-Ready Brain: Biological Evolution and Primate Comparisons.

PubMed

Arbib, Michael A

2017-02-01

The approach to language evolution suggested here focuses on three questions: How did the human brain evolve so that humans can develop, use, and acquire languages? How can the evolutionary quest be informed by studying brain, behavior, and social interaction in monkeys, apes, and humans? How can computational modeling advance these studies? I hypothesize that the brain is language ready in that the earliest humans had protolanguages but not languages (i.e., communication systems endowed with rich and open-ended lexicons and grammars supporting a compositional semantics), and that it took cultural evolution to yield societies (a cultural constructed niche) in which language-ready brains could become language-using brains. The mirror system hypothesis is a well-developed example of this approach, but I offer it here not as a closed theory but as an evolving framework for the development and analysis of conflicting subhypotheses in the hope of their eventual integration. I also stress that computational modeling helps us understand the evolving role of mirror neurons, not in and of themselves, but only in their interaction with systems "beyond the mirror." Because a theory of evolution needs a clear characterization of what it is that evolved, I also outline ideas for research in neurolinguistics to complement studies of the evolution of the language-ready brain. A clear challenge is to go beyond models of speech comprehension to include sign language and models of production, and to link language to visuomotor interaction with the physical and social world.

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.

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

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.

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.

Vinorelbine Delivery and Efficacy in the MDA-MB-231BR Preclinical Model of Brain Metastases of Breast Cancer.

PubMed

Samala, Ramakrishna; Thorsheim, Helen R; Goda, Satyanarayana; Taskar, Kunal; Gril, Brunilde; Steeg, Patricia S; Smith, Quentin R

2016-12-01

To evaluate vinorelbine drug exposure and activity in brain metastases of the human MDA-MB-231BR breast cancer model using integrated imaging and analysis. Brain and systemic metastases were created by administration of cancer cells in female NuNu mice. After metastases developed, animals were administered vinorelbine at the maximal tolerated dose (12 mg/kg), and were evaluated thereafter for total and unbound drug pharmacokinetics, biomarker TUNEL staining, and barrier permeability to Texas red. Median brain metastasis drug exposure was 4-fold greater than normal brain, yet only ~8% of non-barrier systemic metastases, which suggests restricted brain exposure. Unbound vinorelbine tissue/plasma partition coefficient, K p,uu , equaled ~1.0 in systemic metastases, but 0.03-0.22 in brain metastases, documenting restricted equilibration. In select sub-regions of highest drug-uptake brain metastases, K p,uu approached 1.0, indicating complete focal barrier breakdown. Most vinorelbine-treated brain metastases exhibited little or no positive early apoptosis TUNEL staining in vivo. The in vivo unbound vinorelbine IC 50 for TUNEL-positive staining (56 nM) was 4-fold higher than that measured in vitro (14 nM). Consistent with this finding, P-glycoprotein expression was observed to be substantially upregulated in brain metastasis cells in vivo. Vinorelbine exposure at maximum tolerated dose was less than one-tenth that in systemic metastases in >70% of brain metastases, and was associated with negligible biomarker effect. In small subregions of the highest uptake brain metastases, compromise of blood-tumor barrier appeared complete. The results suggest that restricted delivery accounts for 80% of the compromise in drug efficacy for vinorelbine against this model.

Brain and Social Networks: Fundamental Building Blocks of Human Experience.

PubMed

Falk, Emily B; Bassett, Danielle S

2017-09-01

How do brains shape social networks, and how do social ties shape the brain? Social networks are complex webs by which ideas spread among people. Brains comprise webs by which information is processed and transmitted among neural units. While brain activity and structure offer biological mechanisms for human behaviors, social networks offer external inducers or modulators of those behaviors. Together, these two axes represent fundamental contributors to human experience. Integrating foundational knowledge from social and developmental psychology and sociology on how individuals function within dyads, groups, and societies with recent advances in network neuroscience can offer new insights into both domains. Here, we use the example of how ideas and behaviors spread to illustrate the potential of multilayer network models. Copyright © 2017 Elsevier Ltd. All rights reserved.

Balancing the Imbalance: Integrating a Strength-Based Approach with a Medical Model

ERIC Educational Resources Information Center

Foltz, Robert

2006-01-01

There are major differences in perspective between the traditional medical model of treatment for troubled children and more recent strength-based approaches. This is particularly evident when widespread use of psychoactive drugs becomes a substitute for interpersonal therapeutic interventions. Drugs and relationships both impact the brain, but in…

Integrative Etiopathogenetic Models of Psychotic Disorders: Methods, Evidence and Concepts

PubMed Central

Gaebel, Wolfgang; Zielasek, Jürgen

2011-01-01

Integrative models of the etiopathogesnesis of psychotic disorders are needed since a wealth of information from such diverse fields as neurobiology, psychology, and the social sciences is currently changing the concepts of mental disorders. Several approaches to integrate these streams of information into coherent concepts of psychosis are feasible and will need to be assessed in future experimental studies. Common to these concepts are the notion of psychotic disorders as brain disorders and a polythetic approach in that it is increasingly realized that a multitude of interindividually partially different pathogenetic factors interact in individual persons in a complex fashion resulting in the clinical symptoms of psychosis. PMID:21860047

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.

A Neurobiological Model for the Effects of Early Brainstem Functioning on the Development of Behavior and Emotion Regulation in Infants: Implications for Prenatal and Perinatal Risk

ERIC Educational Resources Information Center

Geva, Ronny; Feldman, Ruth

2008-01-01

Neurobiological models propose an evolutionary, vertical-integrative perspective on emotion and behavior regulation, which postulates that regulatory functions are processed along three core brain systems: the brainstem, limbic, and cortical systems. To date, few developmental studies applied these models to research on prenatal and perinatal…

Integrating Conceptual Knowledge Within and Across Representational Modalities

PubMed Central

McNorgan, Chris; Reid, Jackie; McRae, Ken

2011-01-01

Research suggests that concepts are distributed across brain regions specialized for processing information from different sensorimotor modalities. Multimodal semantic models fall into one of two broad classes differentiated by the assumed hierarchy of convergence zones over which information is integrated. In shallow models, communication within- and between-modality is accomplished using either direct connectivity, or a central semantic hub. In deep models, modalities are connected via cascading integration sites with successively wider receptive fields. Four experiments provide the first direct behavioral tests of these models using speeded tasks involving feature inference and concept activation. Shallow models predict no within-modal versus cross-modal difference in either task, whereas deep models predict a within-modal advantage for feature inference, but a cross-modal advantage for concept activation. Experiments 1 and 2 used relatedness judgments to tap participants’ knowledge of relations for within- and cross-modal feature pairs. Experiments 3 and 4 used a dual feature verification task. The pattern of decision latencies across Experiments 1 to 4 is consistent with a deep integration hierarchy. PMID:21093853

Integration of individual and social information for decision-making in groups of different sizes

PubMed Central

Goïame, Sidney; O'Connor, David A.; Dreher, Jean-Claude

2017-01-01

When making judgments in a group, individuals often revise their initial beliefs about the best judgment to make given what others believe. Despite the ubiquity of this phenomenon, we know little about how the brain updates beliefs when integrating personal judgments (individual information) with those of others (social information). Here, we investigated the neurocomputational mechanisms of how we adapt our judgments to those made by groups of different sizes, in the context of jury decisions for a criminal. By testing different theoretical models, we showed that a social Bayesian inference model captured changes in judgments better than 2 other models. Our results showed that participants updated their beliefs by appropriately weighting individual and social sources of information according to their respective credibility. When investigating 2 fundamental computations of Bayesian inference, belief updates and credibility estimates of social information, we found that the dorsal anterior cingulate cortex (dACC) computed the level of belief updates, while the bilateral frontopolar cortex (FPC) was more engaged in individuals who assigned a greater credibility to the judgments of a larger group. Moreover, increased functional connectivity between these 2 brain regions reflected a greater influence of group size on the relative credibility of social information. These results provide a mechanistic understanding of the computational roles of the FPC-dACC network in steering judgment adaptation to a group’s opinion. Taken together, these findings provide a computational account of how the human brain integrates individual and social information for decision-making in groups. PMID:28658252

Bridging neuroscience and clinical psychology: cognitive behavioral and psychophysiological models in the evaluation and treatment of Gilles de la Tourette syndrome

PubMed Central

Lavoie, Marc E; Leclerc, Julie; O’Connor, Kieron P

2013-01-01

SUMMARY Cognitive neuroscience and clinical psychology have long been considered to be separate disciplines. However, the phenomenon of brain plasticity in the context of a psychological intervention highlights the mechanisms of brain compensation and requires linking both clinical cognition and cognitive psychophysiology. A quantifiable normalization of brain activity seems to be correlated with an improvement of the tic symptoms after cognitive behavioral therapy in patients with Gilles de la Tourette syndrome (GTS). This article presents broad outlines of the state of the current literature in the field of GTS. We present our clinical research model and methodology for the integration of cognitive neuroscience in the psychological evaluation and treatment of GTS to manage chronic tic symptoms. PMID:24795782

A new perspective: a vulnerable population framework to guide research and practice for persons with traumatic brain injury.

PubMed

Bay, Esther; Kreulen, Grace J; Shavers, Clarissa Agee; Currier, Connie

2006-01-01

Recovery from traumatic brain injury (TBI) can be a tumultuous lifelong and expensive process. Guided therapies for community integration within community systems are a focus of treating therapists around the world, yet there are no published discussions concerning the most fitting community context. We propose a theoretical approach for practice and research using Flaskerud and Winslow's conceptual model of vulnerable populations. Using the model constructs of health status, resource availability, and increased relative risk, we offer empirical support for proposed construct relationships applied to persons with traumatic brain injury. We then propose that interventions for health promotion, acute care, and rehabilitation or chronic disease management have a community focus, and we identify relevant goals for community-based practice and research.

Bridging neuroscience and clinical psychology: cognitive behavioral and psychophysiological models in the evaluation and treatment of Gilles de la Tourette syndrome.

PubMed

Lavoie, Marc E; Leclerc, Julie; O'Connor, Kieron P

2013-02-01

Cognitive neuroscience and clinical psychology have long been considered to be separate disciplines. However, the phenomenon of brain plasticity in the context of a psychological intervention highlights the mechanisms of brain compensation and requires linking both clinical cognition and cognitive psychophysiology. A quantifiable normalization of brain activity seems to be correlated with an improvement of the tic symptoms after cognitive behavioral therapy in patients with Gilles de la Tourette syndrome (GTS). This article presents broad outlines of the state of the current literature in the field of GTS. We present our clinical research model and methodology for the integration of cognitive neuroscience in the psychological evaluation and treatment of GTS to manage chronic tic symptoms.

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.

Ethyl pyruvate protects against blood-brain barrier damage and improves long-term neurological outcomes in a rat model of traumatic brain injury.

PubMed

Shi, Hong; Wang, Hai-Lian; Pu, Hong-Jian; Shi, Ye-Jie; Zhang, Jia; Zhang, Wen-Ting; Wang, Guo-Hua; Hu, Xiao-Ming; Leak, Rehana K; Chen, Jun; Gao, Yan-Qin

2015-04-01

Many traumatic brain injury (TBI) survivors sustain neurological disability and cognitive impairments due to the lack of defined therapies to reduce TBI-induced long-term brain damage. Ethyl pyruvate (EP) has shown neuroprotection in several models of acute brain injury. The present study therefore investigated the potential beneficial effect of EP on long-term outcomes after TBI and the underlying mechanisms. Male adult rats were subjected to unilateral controlled cortical impact injury. EP was injected intraperitoneally 15 min after TBI and again at 12, 24, 36, 48, and 60 h after TBI. Neurological deficits, blood-brain barrier (BBB) integrity, and neuroinflammation were assessed. Ethyl pyruvate improved sensorimotor and cognitive functions and ameliorated brain tissue damage up to 28 day post-TBI. BBB breach and brain edema were attenuated by EP at 48 h after TBI. EP suppressed matrix metalloproteinase (MMP)-9 production from peripheral neutrophils and reduced the number of MMP-9-overproducing neutrophils in the spleen, and therefore mitigated MMP-9-mediated BBB breakdown. Moreover, EP exerted potent antiinflammatory effects in cultured microglia and inhibited the elevation of inflammatory mediators in the brain after TBI. Ethyl pyruvate confers long-term neuroprotection against TBI, possibly through breaking the vicious cycle among MMP-9-mediated BBB disruption, neuroinflammation, and long-lasting brain damage. © 2014 John Wiley & Sons Ltd.

Hypomyelination, memory impairment, and blood-brain barrier permeability in a model of sleep apnea.

PubMed

Kim, Lenise Jihe; Martinez, Denis; Fiori, Cintia Zappe; Baronio, Diego; Kretzmann, Nélson Alexandre; Barros, Helena Maria Tannhauser

2015-02-09

We investigated the effect of intermittent hypoxia, mimicking sleep apnea, on axonal integrity, blood-brain barrier permeability, and cognitive function of mice. Forty-seven C57BL mice were exposed to intermittent or sham hypoxia, alternating 30s of progressive hypoxia and 30s of reoxigenation, during 8h/day. The axonal integrity in cerebellum was evaluated by transmission electron microscopy. Short- and long-term memories were assessed by novel object recognition test. The levels of endothelin-1 were measured by ELISA. Blood-brain barrier permeability was quantified by Evans Blue dye. After 14 days, animals exposed to intermittent hypoxia showed hypomyelination in cerebellum white matter and higher serum levels of endothelin-1. The short and long-term memories in novel object recognition test was impaired in the group exposed to intermittent hypoxia as compared to controls. Blood-brain barrier permeability was similar between the groups. These results indicated that hypomyelination and impairment of short- and long-term working memories occurred in C57BL mice after 14 days of intermittent hypoxia mimicking sleep apnea. Copyright © 2014 Elsevier B.V. All rights reserved.

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

PubMed Central

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

2015-01-01

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

Synthesis and deposition of basement membrane proteins by primary brain capillary endothelial cells in a murine model of the blood-brain barrier.

PubMed

Thomsen, Maj Schneider; Birkelund, Svend; Burkhart, Annette; Stensballe, Allan; Moos, Torben

2017-03-01

The brain vascular basement membrane is important for both blood-brain barrier (BBB) development, stability, and barrier integrity and the contribution hereto from brain capillary endothelial cells (BCECs), pericytes, and astrocytes of the BBB is probably significant. The aim of this study was to analyse four different in vitro models of the murine BBB for expression and possible secretion of major basement membrane proteins from murine BCECs (mBCECs). mBCECs, pericytes and glial cells (mainly astrocytes and microglia) were prepared from brains of C57BL/6 mice. The mBCECs were grown as monoculture, in co-culture with pericytes or mixed glial cells, or as a triple-culture with both pericytes and mixed glial cells. The integrity of the BBB models was validated by measures of transendothelial electrical resistance (TEER) and passive permeability to mannitol. The expression of basement membrane proteins was analysed using RT-qPCR, mass spectrometry and immunocytochemistry. Co-culturing mBCECs with pericytes, mixed glial cells, or both significantly increased the TEER compared to the monoculture, and a low passive permeability was correlated with high TEER. The mBCECs expressed all major basement membrane proteins such as laminin-411, laminin-511, collagen [α1(IV)] 2 α2(IV), agrin, perlecan, and nidogen 1 and 2 in vitro. Increased expression of the laminin α5 subunit correlated with the addition of BBB-inducing factors (hydrocortisone, Ro 20-1724, and pCPT-cAMP), whereas increased expression of collagen IV α1 primarily correlated with increased levels of cAMP. In conclusion, BCECs cultured in vitro coherently form a BBB and express basement membrane proteins as a feature of maturation. Cover Image for this issue: doi: 10.1111/jnc.13789. © 2016 International Society for Neurochemistry.

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.

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.

A Holoinformational Model of the Physical Observer

NASA Astrophysics Data System (ADS)

di Biase, Francisco

2013-09-01

The author proposes a holoinformational view of the observer based, on the holonomic theory of brain/mind function and quantum brain dynamics developed by Karl Pribram, Sir John Eccles, R.L. Amoroso, Hameroff, Jibu and Yasue, and in the quantumholographic and holomovement theory of David Bohm. This conceptual framework is integrated with nonlocal information properties of the Quantum Field Theory of Umesawa, with the concept of negentropy, order, and organization developed by Shannon, Wiener, Szilard and Brillouin, and to the theories of self-organization and complexity of Prigogine, Atlan, Jantsch and Kauffman. Wheeler's "it from bit" concept of a participatory universe, and the developments of the physics of information made by Zureck and others with the concepts of statistical entropy and algorithmic entropy, related to the number of bits being processed in the mind of the observer are also considered. This new synthesis gives a self-organizing quantum nonlocal informational basis for a new model of awareness in a participatory universe. In this synthesis, awareness is conceived as meaningful quantum nonlocal information interconnecting the brain and the cosmos, by a holoinformational unified field (integrating nonlocal holistic (quantum) and local (Newtonian). We propose that the cosmology of the physical observer is this unified nonlocal quantum-holographic cosmos manifesting itself through awareness, interconnected in a participatory holistic and indivisible way the human mind-brain to all levels of the self-organizing holographic anthropic multiverse.

Clostridium butyricum exerts a neuroprotective effect in a mouse model of traumatic brain injury via the gut-brain axis.

PubMed

Li, H; Sun, J; Du, J; Wang, F; Fang, R; Yu, C; Xiong, J; Chen, W; Lu, Z; Liu, J

2018-05-01

Traumatic brain injury (TBI) is a common occurrence following gastrointestinal dysfunction. Recently, more and more attentions are being focused on gut microbiota in brain and behavior. Glucagon-like peptide-1 (GLP-1) is considered as a mediator that links the gut-brain axis. The aim of this study was to explore the neuroprotective effects of Clostridium butyricum (Cb) on brain damage in a mouse model of TBI. Male C57BL/6 mice were subjected to a model of TBI-induced by weight-drop impact head injury and were treated intragastrically with Cb. The cognitive deficits, brain water content, neuronal death, and blood-brain barrier (BBB) permeability were evaluated. The expression of tight junction (TJ) proteins, Bcl-2, Bax, GLP-1 receptor (GLP-1R), and phosphorylation of Akt (p-Akt) in the brain were also measured. Moreover, the intestinal barrier permeability, the expression of TJ protein and GLP-1, and IL-6 level in the intestine were detected. Cb treatment significantly improved neurological dysfunction, brain edema, neurodegeneration, and BBB impairment. Meanwhile, Cb treatment also significantly increased the expression of TJ proteins (occludin and zonula occluden-1), p-Akt and Bcl-2, but decreased expression of Bax. Moreover, Cb treatment exhibited more prominent effects on decreasing the levels of plasma d-lactate and colonic IL-6, upregulating expression of Occludin, and protecting intestinal barrier integrity. Furthermore, Cb-treated mice showed increased the secretion of intestinal GLP-1 and upregulated expression of cerebral GLP-1R. Our findings demonstrated the neuroprotective effect of Cb in TBI mice and the involved mechanisms were partially attributed to the elevating GLP-1 secretion through the gut-brain axis. © 2017 John Wiley & Sons Ltd.

Direction-dependent arm kinematics reveal optimal integration of gravity cues.

PubMed

Gaveau, Jeremie; Berret, Bastien; Angelaki, Dora E; Papaxanthis, Charalambos

2016-11-02

The brain has evolved an internal model of gravity to cope with life in the Earth's gravitational environment. How this internal model benefits the implementation of skilled movement has remained unsolved. One prevailing theory has assumed that this internal model is used to compensate for gravity's mechanical effects on the body, such as to maintain invariant motor trajectories. Alternatively, gravity force could be used purposely and efficiently for the planning and execution of voluntary movements, thereby resulting in direction-depending kinematics. Here we experimentally interrogate these two hypotheses by measuring arm kinematics while varying movement direction in normal and zero-G gravity conditions. By comparing experimental results with model predictions, we show that the brain uses the internal model to implement control policies that take advantage of gravity to minimize movement effort.

Early intake of long-chain polyunsaturated fatty acids preserves brain structure and function in diet-induced obesity.

PubMed

Arnoldussen, Ilse A C; Zerbi, Valerio; Wiesmann, Maximilian; Noordman, Rikko H J; Bolijn, Simone; Mutsaers, Martina P C; Dederen, Pieter J W C; Kleemann, Robert; Kooistra, Teake; van Tol, Eric A F; Gross, Gabriele; Schoemaker, Marieke H; Heerschap, Arend; Wielinga, Peter Y; Kiliaan, Amanda J

2016-04-01

Worldwide, the incidence of obesity is increasing at an alarming rate, and the number of children with obesity is especially worrisome. These developments raise concerns about the physical, psychosocial and cognitive consequences of obesity. It was shown that early dietary intake of arachidonic acid (ARA) and docosahexaenoic acid (DHA) can reduce the detrimental effects of later obesogenic feeding on lipid metabolism and adipogenesis in an animal model of mild obesity. In the present study, the effects of early dietary ARA and DHA on cognition and brain structure were examined in mildly obesogenic ApoE*3Leiden mouse model. We used cognitive tests and neuroimaging during early and later life. During their early development after weaning (4-13weeks of age), mice were fed a chow diet or ARA and DHA diet for 8 weeks and then switched to a high-fat and high-carbohydrate (HFHC) diet for 12weeks (14-26weeks of age). An HFHC-diet led to increased energy storage in white adipose tissue, increased cholesterol levels, decreased triglycerides levels, increased cerebral blood flow and decreased functional connectivity between brain regions as well as cerebrovascular and gray matter integrity. ARA and DHA intake reduced the HFHC-diet-induced increase in body weight, attenuated plasma triglycerides levels and improved cerebrovasculature, gray matter integrity and functional connectivity in later life. In conclusion, an HFHC diet causes adverse structural brain and metabolic adaptations, most of which can be averted by dietary ARA and DHA intake early in life supporting metabolic flexibility and cerebral integrity later in life. Copyright © 2016 Elsevier Inc. All rights reserved.

Sex differences in the developing brain as a source of inherent risk.

PubMed

McCarthy, Margaret M

2016-12-01

Brain development diverges in males and females in response to androgen production by the fetal testis. This sexual differentiation of the brain occurs during a sensitive window and induces enduring neuroanatomical and physiological changes that profoundly impact behavior. What we know about the contribution of sex chromosomes is still emerging, highlighting the need to integrate multiple factors into understanding sex differences, including the importance of context. The cellular mechanisms are best modeled in rodents and have provided both unifying principles and surprising specifics. Markedly distinct signaling pathways direct differentiation in specific brain regions, resulting in mosaicism of relative maleness, femaleness, and sameness through-out the brain, while canalization both exaggerates and constrains sex differences. Non-neuronal cells and inflammatory mediators are found in greater number and at higher levels in parts of male brains. This higher baseline of inflammation is speculated to increase male vulnerability to developmental neuropsychiatric disorders that are triggered by inflammation.

Assessment of Cognitive Function in the Water Maze Task: Maximizing Data Collection and Analysis in Animal Models of Brain Injury.

PubMed

Whiting, Mark D; Kokiko-Cochran, Olga N

2016-01-01

Animal models play a critical role in understanding the biomechanical, pathophysiological, and behavioral consequences of traumatic brain injury (TBI). In preclinical studies, cognitive impairment induced by TBI is often assessed using the Morris water maze (MWM). Frequently described as a hippocampally dependent spatial navigation task, the MWM is a highly integrative behavioral task that requires intact functioning in numerous brain regions and involves an interdependent set of mnemonic and non-mnemonic processes. In this chapter, we review the special considerations involved in using the MWM in animal models of TBI, with an emphasis on maximizing the degree of information extracted from performance data. We include a theoretical framework for examining deficits in discrete stages of cognitive function and offer suggestions for how to make inferences regarding the specific nature of TBI-induced cognitive impairment. The ultimate goal is more precise modeling of the animal equivalents of the cognitive deficits seen in human TBI.

Seeking Synthesis: The Integrative Problem in Understanding Language and Its Evolution.

PubMed

Dale, Rick; Kello, Christopher T; Schoenemann, P Thomas

2016-04-01

We discuss two problems for a general scientific understanding of language, sequences and synergies: how language is an intricately sequenced behavior and how language is manifested as a multidimensionally structured behavior. Though both are central in our understanding, we observe that the former tends to be studied more than the latter. We consider very general conditions that hold in human brain evolution and its computational implications, and identify multimodal and multiscale organization as two key characteristics of emerging cognitive function in our species. This suggests that human brains, and cognitive function specifically, became more adept at integrating diverse information sources and operating at multiple levels for linguistic performance. We argue that framing language evolution, learning, and use in terms of synergies suggests new research questions, and it may be a fruitful direction for new developments in theory and modeling of language as an integrated system. Copyright © 2016 Cognitive Science Society, Inc.

Angiopoietin-2 mediates blood-brain barrier impairment and colonization of triple-negative breast cancer cells in brain.

PubMed

Avraham, Hava Karsenty; Jiang, Shuxian; Fu, Yigong; Nakshatri, Harikrishna; Ovadia, Haim; Avraham, Shalom

2014-02-01

Although the incidence of breast cancer metastasis (BCM) in brain has increased significantly in triple-negative breast cancer (TNBC), the mechanisms remain elusive. Using in vivo mouse models for BCM in brain, we observed that TNBC cells crossed the blood-brain barrier (BBB), lodged in the brain microvasculature and remained adjacent to brain microvascular endothelial cells (BMECs). Breaching of the BBB in vivo by TNBCs resulted in increased BBB permeability and changes in ZO-1 and claudin-5 tight junction (TJ) protein structures. Angiopoietin-2 expression was elevated in BMECs and was correlated with BBB disruption. Secreted Ang-2 impaired TJ structures and increased BBB permeability. Treatment of mice with the neutralizing Ang-2 peptibody trebananib prevented changes in the BBB integrity and BMEC destabilization, resulting in inhibition of TNBC colonization in brain. Thus, Ang-2 is involved in initial steps of brain metastasis cascade, and inhibitors for Ang-2 may serve as potential therapeutics for brain metastasis. Copyright © 2013 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Animal models for studying transport across the blood-brain barrier.

PubMed

Bonate, P L

1995-01-01

There are many reasons for wishing to determine the rate of uptake of a drug from blood into brain parenchyma. However, when faced with doing so for the first time, choosing a method can be a formidable task. There are at least 7 methods from which to choose: indicator dilution, brain uptake index, microdialysis, external registration, PET scanning, in situ perfusion, and compartmental modeling. Each method has advantages and disadvantages. Some methods require very little equipment while others require equipment that can cost millions of dollars. Some methods require very little technical experience whereas others require complex surgical manipulation. The mathematics alone for the various methods range from simple algebra to complex integral calculus and differential equations. Like most things in science, as the complexity of the technique increases, so does the quantity of information it provides. This review is meant to serve as a starting point for the researcher who wishes to study transport and uptake across the blood-brain barrier in animal models. An overview of the mathematical theory, as well as an introduction to the techniques, is presented.

Bridging animal and human models of exercise-induced brain plasticity

PubMed Central

Voss, Michelle W.; Vivar, Carmen; Kramer, Arthur F.; van Praag, Henriette

2015-01-01

Significant progress has been made in understanding the neurobiological mechanisms through which exercise protects and restores the brain. In this feature review, we integrate animal and human research, examining physical activity effects across multiple levels of description (neurons up to inter-regional pathways). We evaluate the influence of exercise on hippocampal structure and function, addressing common themes such as spatial memory and pattern separation, brain structure and plasticity, neurotrophic factors, and vasculature. Areas of research focused more within species, such as hippocampal neurogenesis in rodents, also provide crucial insight into the protective role of physical activity. Overall, converging evidence suggests exercise benefits brain function and cognition across the mammalian lifespan, which may translate into reduced risk for Alzheimer’s disease (AD) in humans. PMID:24029446

Representational geometry: integrating cognition, computation, and the brain

PubMed Central

Kriegeskorte, Nikolaus; Kievit, Rogier A.

2013-01-01

The cognitive concept of representation plays a key role in theories of brain information processing. However, linking neuronal activity to representational content and cognitive theory remains challenging. Recent studies have characterized the representational geometry of neural population codes by means of representational distance matrices, enabling researchers to compare representations across stages of processing and to test cognitive and computational theories. Representational geometry provides a useful intermediate level of description, capturing both the information represented in a neuronal population code and the format in which it is represented. We review recent insights gained with this approach in perception, memory, cognition, and action. Analyses of representational geometry can compare representations between models and the brain, and promise to explain brain computation as transformation of representational similarity structure. PMID:23876494

Modeling of inter-neuronal coupling medium and its impact on neuronal synchronization

PubMed Central

Iqbal, Muhammad; Hong, Keum-Shik

2017-01-01

In this paper, modeling of the coupling medium between two neurons, the effects of the model parameters on the synchronization of those neurons, and compensation of coupling strength deficiency in synchronization are studied. Our study exploits the inter-neuronal coupling medium and investigates its intrinsic properties in order to get insight into neuronal-information transmittance and, there from, brain-information processing. A novel electrical model of the coupling medium that represents a well-known RLC circuit attributable to the coupling medium’s intrinsic resistive, inductive, and capacitive properties is derived. Surprisingly, the integration of such properties reveals the existence of a natural three-term control strategy, referred to in the literature as the proportional integral derivative (PID) controller, which can be responsible for synchronization between two neurons. Consequently, brain-information processing can rely on a large number of PID controllers based on the coupling medium properties responsible for the coherent behavior of neurons in a neural network. Herein, the effects of the coupling model (or natural PID controller) parameters are studied and, further, a supervisory mechanism is proposed that follows a learning and adaptation policy based on the particle swarm optimization algorithm for compensation of the coupling strength deficiency. PMID:28486505

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.

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.

Individualized Gaussian process-based prediction and detection of local and global gray matter abnormalities in elderly subjects.

PubMed

Ziegler, G; Ridgway, G R; Dahnke, R; Gaser, C

2014-08-15

Structural imaging based on MRI is an integral component of the clinical assessment of patients with potential dementia. We here propose an individualized Gaussian process-based inference scheme for clinical decision support in healthy and pathological aging elderly subjects using MRI. The approach aims at quantitative and transparent support for clinicians who aim to detect structural abnormalities in patients at risk of Alzheimer's disease or other types of dementia. Firstly, we introduce a generative model incorporating our knowledge about normative decline of local and global gray matter volume across the brain in elderly. By supposing smooth structural trajectories the models account for the general course of age-related structural decline as well as late-life accelerated loss. Considering healthy subjects' demography and global brain parameters as informative about normal brain aging variability affords individualized predictions in single cases. Using Gaussian process models as a normative reference, we predict new subjects' brain scans and quantify the local gray matter abnormalities in terms of Normative Probability Maps (NPM) and global z-scores. By integrating the observed expectation error and the predictive uncertainty, the local maps and global scores exploit the advantages of Bayesian inference for clinical decisions and provide a valuable extension of diagnostic information about pathological aging. We validate the approach in simulated data and real MRI data. We train the GP framework using 1238 healthy subjects with ages 18-94 years, and predict in 415 independent test subjects diagnosed as healthy controls, Mild Cognitive Impairment and Alzheimer's disease. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Individualized Gaussian process-based prediction and detection of local and global gray matter abnormalities in elderly subjects

PubMed Central

Ziegler, G.; Ridgway, G.R.; Dahnke, R.; Gaser, C.

2014-01-01

Structural imaging based on MRI is an integral component of the clinical assessment of patients with potential dementia. We here propose an individualized Gaussian process-based inference scheme for clinical decision support in healthy and pathological aging elderly subjects using MRI. The approach aims at quantitative and transparent support for clinicians who aim to detect structural abnormalities in patients at risk of Alzheimer's disease or other types of dementia. Firstly, we introduce a generative model incorporating our knowledge about normative decline of local and global gray matter volume across the brain in elderly. By supposing smooth structural trajectories the models account for the general course of age-related structural decline as well as late-life accelerated loss. Considering healthy subjects' demography and global brain parameters as informative about normal brain aging variability affords individualized predictions in single cases. Using Gaussian process models as a normative reference, we predict new subjects' brain scans and quantify the local gray matter abnormalities in terms of Normative Probability Maps (NPM) and global z-scores. By integrating the observed expectation error and the predictive uncertainty, the local maps and global scores exploit the advantages of Bayesian inference for clinical decisions and provide a valuable extension of diagnostic information about pathological aging. We validate the approach in simulated data and real MRI data. We train the GP framework using 1238 healthy subjects with ages 18–94 years, and predict in 415 independent test subjects diagnosed as healthy controls, Mild Cognitive Impairment and Alzheimer's disease. PMID:24742919

Construction of multi-scale consistent brain networks: methods and applications.

PubMed

Ge, Bao; Tian, Yin; Hu, Xintao; Chen, Hanbo; Zhu, Dajiang; Zhang, Tuo; Han, Junwei; Guo, Lei; Liu, Tianming

2015-01-01

Mapping human brain networks provides a basis for studying brain function and dysfunction, and thus has gained significant interest in recent years. However, modeling human brain networks still faces several challenges including constructing networks at multiple spatial scales and finding common corresponding networks across individuals. As a consequence, many previous methods were designed for a single resolution or scale of brain network, though the brain networks are multi-scale in nature. To address this problem, this paper presents a novel approach to constructing multi-scale common structural brain networks from DTI data via an improved multi-scale spectral clustering applied on our recently developed and validated DICCCOLs (Dense Individualized and Common Connectivity-based Cortical Landmarks). Since the DICCCOL landmarks possess intrinsic structural correspondences across individuals and populations, we employed the multi-scale spectral clustering algorithm to group the DICCCOL landmarks and their connections into sub-networks, meanwhile preserving the intrinsically-established correspondences across multiple scales. Experimental results demonstrated that the proposed method can generate multi-scale consistent and common structural brain networks across subjects, and its reproducibility has been verified by multiple independent datasets. As an application, these multi-scale networks were used to guide the clustering of multi-scale fiber bundles and to compare the fiber integrity in schizophrenia and healthy controls. In general, our methods offer a novel and effective framework for brain network modeling and tract-based analysis of DTI data.

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

The Virtual Brain: Modeling Biological Correlates of Recovery after Chronic Stroke

PubMed Central

Falcon, Maria Inez; Riley, Jeffrey D.; Jirsa, Viktor; McIntosh, Anthony R.; Shereen, Ahmed D.; Chen, E. Elinor; Solodkin, Ana

2015-01-01

There currently remains considerable variability in stroke survivor recovery. To address this, developing individualized treatment has become an important goal in stroke treatment. As a first step, it is necessary to determine brain dynamics associated with stroke and recovery. While recent methods have made strides in this direction, we still lack physiological biomarkers. The Virtual Brain (TVB) is a novel application for modeling brain dynamics that simulates an individual’s brain activity by integrating their own neuroimaging data with local biophysical models. Here, we give a detailed description of the TVB modeling process and explore model parameters associated with stroke. In order to establish a parallel between this new type of modeling and those currently in use, in this work we establish an association between a specific TVB parameter (long-range coupling) that increases after stroke with metrics derived from graph analysis. We used TVB to simulate the individual BOLD signals for 20 patients with stroke and 10 healthy controls. We performed graph analysis on their structural connectivity matrices calculating degree centrality, betweenness centrality, and global efficiency. Linear regression analysis demonstrated that long-range coupling is negatively correlated with global efficiency (P = 0.038), but is not correlated with degree centrality or betweenness centrality. Our results suggest that the larger influence of local dynamics seen through the long-range coupling parameter is closely associated with a decreased efficiency of the system. We thus propose that the increase in the long-range parameter in TVB (indicating a bias toward local over global dynamics) is deleterious because it reduces communication as suggested by the decrease in efficiency. The new model platform TVB hence provides a novel perspective to understanding biophysical parameters responsible for global brain dynamics after stroke, allowing the design of focused therapeutic interventions. PMID:26579071

Python scripting in the nengo simulator.

PubMed

Stewart, Terrence C; Tripp, Bryan; Eliasmith, Chris

2009-01-01

Nengo (http://nengo.ca) is an open-source neural simulator that has been greatly enhanced by the recent addition of a Python script interface. Nengo provides a wide range of features that are useful for physiological simulations, including unique features that facilitate development of population-coding models using the neural engineering framework (NEF). This framework uses information theory, signal processing, and control theory to formalize the development of large-scale neural circuit models. Notably, it can also be used to determine the synaptic weights that underlie observed network dynamics and transformations of represented variables. Nengo provides rich NEF support, and includes customizable models of spike generation, muscle dynamics, synaptic plasticity, and synaptic integration, as well as an intuitive graphical user interface. All aspects of Nengo models are accessible via the Python interface, allowing for programmatic creation of models, inspection and modification of neural parameters, and automation of model evaluation. Since Nengo combines Python and Java, it can also be integrated with any existing Java or 100% Python code libraries. Current work includes connecting neural models in Nengo with existing symbolic cognitive models, creating hybrid systems that combine detailed neural models of specific brain regions with higher-level models of remaining brain areas. Such hybrid models can provide (1) more realistic boundary conditions for the neural components, and (2) more realistic sub-components for the larger cognitive models.

Python Scripting in the Nengo Simulator

PubMed Central

Stewart, Terrence C.; Tripp, Bryan; Eliasmith, Chris

2008-01-01

Nengo (http://nengo.ca) is an open-source neural simulator that has been greatly enhanced by the recent addition of a Python script interface. Nengo provides a wide range of features that are useful for physiological simulations, including unique features that facilitate development of population-coding models using the neural engineering framework (NEF). This framework uses information theory, signal processing, and control theory to formalize the development of large-scale neural circuit models. Notably, it can also be used to determine the synaptic weights that underlie observed network dynamics and transformations of represented variables. Nengo provides rich NEF support, and includes customizable models of spike generation, muscle dynamics, synaptic plasticity, and synaptic integration, as well as an intuitive graphical user interface. All aspects of Nengo models are accessible via the Python interface, allowing for programmatic creation of models, inspection and modification of neural parameters, and automation of model evaluation. Since Nengo combines Python and Java, it can also be integrated with any existing Java or 100% Python code libraries. Current work includes connecting neural models in Nengo with existing symbolic cognitive models, creating hybrid systems that combine detailed neural models of specific brain regions with higher-level models of remaining brain areas. Such hybrid models can provide (1) more realistic boundary conditions for the neural components, and (2) more realistic sub-components for the larger cognitive models. PMID:19352442

A Comparison of the neural correlates that underlie rule-based and information-integration category learning.

PubMed

Carpenter, Kathryn L; Wills, Andy J; Benattayallah, Abdelmalek; Milton, Fraser

2016-10-01

The influential competition between verbal and implicit systems (COVIS) model proposes that category learning is driven by two competing neural systems-an explicit, verbal, system, and a procedural-based, implicit, system. In the current fMRI study, participants learned either a conjunctive, rule-based (RB), category structure that is believed to engage the explicit system, or an information-integration category structure that is thought to preferentially recruit the implicit system. The RB and information-integration category structures were matched for participant error rate, the number of relevant stimulus dimensions, and category separation. Under these conditions, considerable overlap in brain activation, including the prefrontal cortex, basal ganglia, and the hippocampus, was found between the RB and information-integration category structures. Contrary to the predictions of COVIS, the medial temporal lobes and in particular the hippocampus, key regions for explicit memory, were found to be more active in the information-integration condition than in the RB condition. No regions were more activated in RB than information-integration category learning. The implications of these results for theories of category learning are discussed. Hum Brain Mapp 37:3557-3574, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

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.

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

A whole-brain computational modeling approach to explain the alterations in resting-state functional connectivity during progression of Alzheimer's disease.

PubMed

Demirtaş, Murat; Falcon, Carles; Tucholka, Alan; Gispert, Juan Domingo; Molinuevo, José Luis; Deco, Gustavo

2017-01-01

Alzheimer's disease (AD) is the most common dementia with dramatic consequences. The research in structural and functional neuroimaging showed altered brain connectivity in AD. In this study, we investigated the whole-brain resting state functional connectivity (FC) of the subjects with preclinical Alzheimer's disease (PAD), mild cognitive impairment due to AD (MCI) and mild dementia due to Alzheimer's disease (AD), the impact of APOE4 carriership, as well as in relation to variations in core AD CSF biomarkers. The synchronization in the whole-brain was monotonously decreasing during the course of the disease progression. Furthermore, in AD patients we found widespread significant decreases in functional connectivity (FC) strengths particularly in the brain regions with high global connectivity. We employed a whole-brain computational modeling approach to study the mechanisms underlying these alterations. To characterize the causal interactions between brain regions, we estimated the effective connectivity (EC) in the model. We found that the significant EC differences in AD were primarily located in left temporal lobe. Then, we systematically manipulated the underlying dynamics of the model to investigate simulated changes in FC based on the healthy control subjects. Furthermore, we found distinct patterns involving CSF biomarkers of amyloid-beta (Aβ1 - 42) total tau (t-tau) and phosphorylated tau (p-tau). CSF Aβ1 - 42 was associated to the contrast between healthy control subjects and clinical groups. Nevertheless, tau CSF biomarkers were associated to the variability in whole-brain synchronization and sensory integration regions. These associations were robust across clinical groups, unlike the associations that were found for CSF Aβ1 - 42. APOE4 carriership showed no significant correlations with the connectivity measures.

Integrative Therapies in Anxiety Treatment with Special Emphasis on the Gut Microbiome.

PubMed

Schnorr, Stephanie L; Bachner, Harriet A

2016-09-01

Over the past decade, research has shown that diet and gut health affects symptoms expressed in stress related disorders, depression, and anxiety through changes in the gut microbiota. Psycho-behavioral function and somatic health interaction have often been ignored in health care with resulting deficits in treatment quality and outcomes. While mental health care requires the professional training in counseling, psychotherapy and psychiatry, complimentary therapeutic strategies, such as attention to a nutritional and diverse diet and supplementation of probiotic foods, may be integrated alongside psychotherapy treatment models. Development of these alternative strategies is predicated on experimental evidence and diligent research on the biology of stress, fear, anxiety-related behaviors, and the gut-brain connection. This article provides a brief overview on biological markers of anxiety and the expanding nutritional literature relating to brain health and mental disorders. A case study demonstrates an example of a biopsychosocial approach integrating cognitive psychotherapy, dietary changes, and mindfulness activities, in treating symptoms of anxiety. This case study shows a possible treatment protocol to explore the efficacy of targeting the gut-brain-axis that may be used as an impetus for future controlled studies.

The functional integration of the anterior cingulate cortex during conflict processing.

PubMed

Fan, Jin; Hof, Patrick R; Guise, Kevin G; Fossella, John A; Posner, Michael I

2008-04-01

Although functional activation of the anterior cingulate cortex (ACC) related to conflict processing has been studied extensively, the functional integration of the subdivisions of the ACC and other brain regions during conditions of conflict is still unclear. In this study, participants performed a task designed to elicit conflict processing by using flanker interference on target response while they were scanned using event-related functional magnetic resonance imaging. The physiological response of several brain regions in terms of an interaction between conflict processing and activity of the anterior rostral cingulate zone (RCZa) of the ACC, and the effective connectivity between this zone and other regions were examined using psychophysiological interaction analysis and dynamic causal modeling, respectively. There was significant integration of the RCZa with the caudal cingulate zone (CCZ) of the ACC and other brain regions such as the lateral prefrontal, primary, and supplementary motor areas above and beyond the main effect of conflict and baseline connectivity. The intrinsic connectivity from the RCZa to the CCZ was modulated by the context of conflict. These findings suggest that conflict processing is associated with the effective contribution of the RCZa to the neuronal activity of CCZ, as well as other cortical regions.

Silencing microRNA-143 protects the integrity of the blood-brain barrier: implications for methamphetamine abuse

PubMed Central

Bai, Ying; Zhang, Yuan; Hua, Jun; Yang, Xiangyu; Zhang, Xiaotian; Duan, Ming; Zhu, Xinjian; Huang, Wenhui; Chao, Jie; Zhou, Rongbin; Hu, Gang; Yao, Honghong

2016-01-01

MicroRNA-143 (miR-143) plays a critical role in various cellular processes; however, the role of miR-143 in the maintenance of blood-brain barrier (BBB) integrity remains poorly defined. Silencing miR-143 in a genetic animal model or via an anti-miR-143 lentivirus prevented the BBB damage induced by methamphetamine. miR-143, which targets p53 unregulated modulator of apoptosis (PUMA), increased the permeability of human brain endothelial cells and concomitantly decreased the expression of tight junction proteins (TJPs). Silencing miR-143 increased the expression of TJPs and protected the BBB integrity against the effects of methamphetamine treatment. PUMA overexpression increased the TJP expression through a mechanism that involved the NF-κB and p53 transcription factor pathways. Mechanistically, methamphetamine mediated up-regulation of miR-143 via sigma-1 receptor with sequential activation of the mitogen-activated protein kinase (MAPK) and phosphatidylinositol-3′ kinase (PI3K)/Akt and STAT3 pathways. These results indicated that silencing miR-143 could provide a novel therapeutic strategy for BBB damage-related vascular dysfunction. PMID:27767041

A discriminative model-constrained graph cuts approach to fully automated pediatric brain tumor segmentation in 3-D MRI.

PubMed

Wels, Michael; Carneiro, Gustavo; Aplas, Alexander; Huber, Martin; Hornegger, Joachim; Comaniciu, Dorin

2008-01-01

In this paper we present a fully automated approach to the segmentation of pediatric brain tumors in multi-spectral 3-D magnetic resonance images. It is a top-down segmentation approach based on a Markov random field (MRF) model that combines probabilistic boosting trees (PBT) and lower-level segmentation via graph cuts. The PBT algorithm provides a strong discriminative observation model that classifies tumor appearance while a spatial prior takes into account the pair-wise homogeneity in terms of classification labels and multi-spectral voxel intensities. The discriminative model relies not only on observed local intensities but also on surrounding context for detecting candidate regions for pathology. A mathematically sound formulation for integrating the two approaches into a unified statistical framework is given. The proposed method is applied to the challenging task of detection and delineation of pediatric brain tumors. This segmentation task is characterized by a high non-uniformity of both the pathology and the surrounding non-pathologic brain tissue. A quantitative evaluation illustrates the robustness of the proposed method. Despite dealing with more complicated cases of pediatric brain tumors the results obtained are mostly better than those reported for current state-of-the-art approaches to 3-D MR brain tumor segmentation in adult patients. The entire processing of one multi-spectral data set does not require any user interaction, and takes less time than previously proposed methods.

A self-resetting spiking phase-change neuron

NASA Astrophysics Data System (ADS)

Cobley, R. A.; Hayat, H.; Wright, C. D.

2018-05-01

Neuromorphic, or brain-inspired, computing applications of phase-change devices have to date concentrated primarily on the implementation of phase-change synapses. However, the so-called accumulation mode of operation inherent in phase-change materials and devices can also be used to mimic the integrative properties of a biological neuron. Here we demonstrate, using physical modelling of nanoscale devices and SPICE modelling of associated circuits, that a single phase-change memory cell integrated into a comparator type circuit can deliver a basic hardware mimic of an integrate-and-fire spiking neuron with self-resetting capabilities. Such phase-change neurons, in combination with phase-change synapses, can potentially open a new route for the realisation of all-phase-change neuromorphic computing.

A self-resetting spiking phase-change neuron.

PubMed

Cobley, R A; Hayat, H; Wright, C D

2018-05-11

Neuromorphic, or brain-inspired, computing applications of phase-change devices have to date concentrated primarily on the implementation of phase-change synapses. However, the so-called accumulation mode of operation inherent in phase-change materials and devices can also be used to mimic the integrative properties of a biological neuron. Here we demonstrate, using physical modelling of nanoscale devices and SPICE modelling of associated circuits, that a single phase-change memory cell integrated into a comparator type circuit can deliver a basic hardware mimic of an integrate-and-fire spiking neuron with self-resetting capabilities. Such phase-change neurons, in combination with phase-change synapses, can potentially open a new route for the realisation of all-phase-change neuromorphic computing.

Brain-based treatment-A new approach or a well-forgotten old one?

PubMed

Matanova, Vanya; Kostova, Zlatomira; Kolev, Martin

2018-04-24

For a relatively long period of time, mental functioning was mainly associated with personal profile while brain functioning went by the wayside. After the 90s of the 20th century, or the so called "Decade of the Brain", today, contemporary specialists work on the boundary between fundamental science and medicine. This brings neuroscience, neuropsychology, psychiatry, and psychotherapy closer to each other. Today, we definitely know that brain structures are being built and altered thanks to experience. Psychotherapy can be more effective when based on a neuropsychological approach-this implies identification of the neural foundations of various disorders and will lead to specific psychotherapeutic conclusions. The knowledge about the brain is continually enriched, which leads to periodic rethinking and updating of the therapeutic approaches to various diseases of the nervous system and brain dysfunctions. The aim of translational studies is to match and combine scientific areas, resources, experience and techniques to improve prevention, diagnosis and therapies, and "transformation" of scientific discoveries into potential treatments of various diseases done in laboratory conditions. Neuropsychological studies prove that cognition is a key element that links together brain functioning and behaviour. According to Dr. Kandel, all experimental events, including psychotherapeutic interventions, affect the structure and function of neuronal synapses. The story of why psychotherapy works is a story of understanding the brain mechanisms of psychic processes, a story of how the brain has been evolving to ensure learning, forgetting, and the mechanisms of permanent psychological change. The new evidence on brain functioning necessitates the integration of neuropsychological achievements in the psychotherapeutic process. An integrative approach is needed to take into account the dynamic interaction between brain functioning, psyche, soul, spirit, and social interaction, ie, development of a model of psychotherapeutic work based on cerebral plasticity! Brain-based psychotherapy aims at changing brain functioning not directly, but through experiences. This is neuro-psychologically informed psychotherapy. © 2018 John Wiley & Sons, Ltd.

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

PubMed

van Elk, Michiel; Aleman, André

2017-02-01

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

A Single-Cell Roadmap of Lineage Bifurcation in Human ESC Models of Embryonic Brain Development.

PubMed

Yao, Zizhen; Mich, John K; Ku, Sherman; Menon, Vilas; Krostag, Anne-Rachel; Martinez, Refugio A; Furchtgott, Leon; Mulholland, Heather; Bort, Susan; Fuqua, Margaret A; Gregor, Ben W; Hodge, Rebecca D; Jayabalu, Anu; May, Ryan C; Melton, Samuel; Nelson, Angelique M; Ngo, N Kiet; Shapovalova, Nadiya V; Shehata, Soraya I; Smith, Michael W; Tait, Leah J; Thompson, Carol L; Thomsen, Elliot R; Ye, Chaoyang; Glass, Ian A; Kaykas, Ajamete; Yao, Shuyuan; Phillips, John W; Grimley, Joshua S; Levi, Boaz P; Wang, Yanling; Ramanathan, Sharad

2017-01-05

During human brain development, multiple signaling pathways generate diverse cell types with varied regional identities. Here, we integrate single-cell RNA sequencing and clonal analyses to reveal lineage trees and molecular signals underlying early forebrain and mid/hindbrain cell differentiation from human embryonic stem cells (hESCs). Clustering single-cell transcriptomic data identified 41 distinct populations of progenitor, neuronal, and non-neural cells across our differentiation time course. Comparisons with primary mouse and human gene expression data demonstrated rostral and caudal progenitor and neuronal identities from early brain development. Bayesian analyses inferred a unified cell-type lineage tree that bifurcates between cortical and mid/hindbrain cell types. Two methods of clonal analyses confirmed these findings and further revealed the importance of Wnt/β-catenin signaling in controlling this lineage decision. Together, these findings provide a rich transcriptome-based lineage map for studying human brain development and modeling developmental disorders. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

Dapsone protects brain microvascular integrity from high-fat diet induced LDL oxidation.

PubMed

Zhan, Rui; Zhao, Mingming; Zhou, Ting; Chen, Yue; Yu, Weiwei; Zhao, Lei; Zhang, Tao; Wang, Hecheng; Yang, Huan; Jin, Yinglan; He, Qihua; Yang, Xiaoda; Guo, Xiangyang; Willard, Belinda; Pan, Bing; Huang, Yining; Chen, Yingyu; Chui, Dehua; Zheng, Lemin

2018-06-07

Atherosclerosis was considered to induce many vascular-related complications, such as acute myocardial infarction and stroke. Abnormal lipid metabolism and its peroxidation inducing blood-brain barrier (BBB) leakage were associated with the pre-clinical stage of stroke. Dapsone (DDS), an anti-inflammation and anti-oxidation drug, has been found to have protective effects on vascular. However, whether DDS has a protective role on brain microvessels during lipid oxidation had yet to be elucidated. We investigated brain microvascular integrity in a high-fat diet (HFD) mouse model. We designed this study to explore whether DDS had protective effects on brain microvessels under lipid oxidation and tried to explain the underlying mechanism. In our live optical study, we found that DDS significantly attenuated brain microvascular leakage through reducing serum oxidized low-density lipoprotein (oxLDL) in HFD mice (p < 0.001), and DDS significantly inhibited LDL oxidation in vitro (p < 0.001). Our study showed that DDS protected tight junction proteins: ZO-1 (p < 0.001), occludin (p < 0.01), claudin-5 (p < 0.05) of microvascular endothelial cells in vivo and in vitro. DDS reversed LAMP1 aggregation in cytoplasm, and decreased the destruction of tight junction protein: ZO-1 in vitro. We first revealed that DDS had a protective role on cerebral microvessels through preventing tight junction ZO-1 from abnormal degradation by autophagy and reducing lysosome accumulation. Our findings suggested the significance of DDS in protecting brain microvessels under lipid metabolic disorders, which revealed a novel potential therapeutic strategy in brain microvascular-related diseases.

Brain age and other bodily 'ages': implications for neuropsychiatry.

PubMed

Cole, James H; Marioni, Riccardo E; Harris, Sarah E; Deary, Ian J

2018-06-11

As our brains age, we tend to experience cognitive decline and are at greater risk of neurodegenerative disease and dementia. Symptoms of chronic neuropsychiatric diseases are also exacerbated during ageing. However, the ageing process does not affect people uniformly; nor, in fact, does the ageing process appear to be uniform even within an individual. Here, we outline recent neuroimaging research into brain ageing and the use of other bodily ageing biomarkers, including telomere length, the epigenetic clock, and grip strength. Some of these techniques, using statistical approaches, have the ability to predict chronological age in healthy people. Moreover, they are now being applied to neurological and psychiatric disease groups to provide insights into how these diseases interact with the ageing process and to deliver individualised predictions about future brain and body health. We discuss the importance of integrating different types of biological measurements, from both the brain and the rest of the body, to build more comprehensive models of the biological ageing process. Finally, we propose seven steps for the field of brain-ageing research to take in coming years. This will help us reach the long-term goal of developing clinically applicable statistical models of biological processes to measure, track and predict brain and body health in ageing and disease.

Characterization of the resting-state brain network topology in the 6-hydroxydopamine rat model of Parkinson’s disease

PubMed Central

Simmons, Camilla; Mesquita, Michel B.; Wood, Tobias C.; Williams, Steve C. R.; Vernon, Anthony C.; Cash, Diana

2017-01-01

Resting-state functional MRI (rsfMRI) is an imaging technology that has recently gained attention for its ability to detect disruptions in functional brain networks in humans, including in patients with Parkinson’s disease (PD), revealing early and widespread brain network abnormalities. This methodology is now readily applicable to experimental animals offering new possibilities for cross-species translational imaging. In this context, we herein describe the application of rsfMRI to the unilaterally-lesioned 6-hydroxydopamine (6-OHDA) rat, a robust experimental model of the dopamine depletion implicated in PD. Using graph theory to analyse the rsfMRI data, we were able to provide meaningful and translatable measures of integrity, influence and segregation of the underlying functional brain architecture. Specifically, we confirm that rats share a similar functional brain network topology as observed in humans, characterised by small-worldness and modularity. Interestingly, we observed significantly reduced functional connectivity in the 6-OHDA rats, primarily in the ipsilateral (lesioned) hemisphere as evidenced by significantly lower node degree, local efficiency and clustering coefficient in the motor, orbital and sensorimotor cortices. In contrast, we found significantly, and bilaterally, increased thalamic functional connectivity in the lesioned rats. The unilateral deficits in the cortex are consistent with the unilateral nature of this model and further support the validity of the rsfMRI technique in rodents. We thereby provide a methodological framework for the investigation of brain networks in other rodent experimental models of PD, as well as of animal models in general, for cross-comparison with human data. PMID:28249008

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

Development of an RF-EMF Exposure Surrogate for Epidemiologic Research.

PubMed

Roser, Katharina; Schoeni, Anna; Bürgi, Alfred; Röösli, Martin

2015-05-22

Exposure assessment is a crucial part in studying potential effects of RF-EMF. Using data from the HERMES study on adolescents, we developed an integrative exposure surrogate combining near-field and far-field RF-EMF exposure in a single brain and whole-body exposure measure. Contributions from far-field sources were modelled by propagation modelling and multivariable regression modelling using personal measurements. Contributions from near-field sources were assessed from both, questionnaires and mobile phone operator records. Mean cumulative brain and whole-body doses were 1559.7 mJ/kg and 339.9 mJ/kg per day, respectively. 98.4% of the brain dose originated from near-field sources, mainly from GSM mobile phone calls (93.1%) and from DECT phone calls (4.8%). Main contributors to the whole-body dose were GSM mobile phone calls (69.0%), use of computer, laptop and tablet connected to WLAN (12.2%) and data traffic on the mobile phone via WLAN (6.5%). The exposure from mobile phone base stations contributed 1.8% to the whole-body dose, while uplink exposure from other people's mobile phones contributed 3.6%. In conclusion, the proposed approach is considered useful to combine near-field and far-field exposure to an integrative exposure surrogate for exposure assessment in epidemiologic studies. However, substantial uncertainties remain about exposure contributions from various near-field and far-field sources.

Development of an RF-EMF Exposure Surrogate for Epidemiologic Research

PubMed Central

Roser, Katharina; Schoeni, Anna; Bürgi, Alfred; Röösli, Martin

2015-01-01

Exposure assessment is a crucial part in studying potential effects of RF-EMF. Using data from the HERMES study on adolescents, we developed an integrative exposure surrogate combining near-field and far-field RF-EMF exposure in a single brain and whole-body exposure measure. Contributions from far-field sources were modelled by propagation modelling and multivariable regression modelling using personal measurements. Contributions from near-field sources were assessed from both, questionnaires and mobile phone operator records. Mean cumulative brain and whole-body doses were 1559.7 mJ/kg and 339.9 mJ/kg per day, respectively. 98.4% of the brain dose originated from near-field sources, mainly from GSM mobile phone calls (93.1%) and from DECT phone calls (4.8%). Main contributors to the whole-body dose were GSM mobile phone calls (69.0%), use of computer, laptop and tablet connected to WLAN (12.2%) and data traffic on the mobile phone via WLAN (6.5%). The exposure from mobile phone base stations contributed 1.8% to the whole-body dose, while uplink exposure from other people’s mobile phones contributed 3.6%. In conclusion, the proposed approach is considered useful to combine near-field and far-field exposure to an integrative exposure surrogate for exposure assessment in epidemiologic studies. However, substantial uncertainties remain about exposure contributions from various near-field and far-field sources. PMID:26006132

Neural pathways in processing of sexual arousal: a dynamic causal modeling study.

PubMed

Seok, J-W; Park, M-S; Sohn, J-H

2016-09-01

Three decades of research have investigated brain processing of visual sexual stimuli with neuroimaging methods. These researchers have found that sexual arousal stimuli elicit activity in a broad neural network of cortical and subcortical brain areas that are known to be associated with cognitive, emotional, motivational and physiological components. However, it is not completely understood how these neural systems integrate and modulated incoming information. Therefore, we identify cerebral areas whose activations were correlated with sexual arousal using event-related functional magnetic resonance imaging and used the dynamic causal modeling method for searching the effective connectivity about the sexual arousal processing network. Thirteen heterosexual males were scanned while they passively viewed alternating short trials of erotic and neutral pictures on a monitor. We created a subset of seven models based on our results and previous studies and selected a dominant connectivity model. Consequently, we suggest a dynamic causal model of the brain processes mediating the cognitive, emotional, motivational and physiological factors of human male sexual arousal. These findings are significant implications for the neuropsychology of male sexuality.

Associated degeneration of ventral tegmental area dopaminergic neurons in the rat nigrostriatal lactacystin model of parkinsonism and their neuroprotection by valproate

PubMed Central

Harrison, Ian F.; Anis, Hiba K.; Dexter, David T.

2016-01-01

Parkinson’s disease (PD) manifests clinically as bradykinesia, rigidity, and development of a resting tremor, primarily due to degeneration of dopaminergic nigrostriatal pathways in the brain. Intranigral administration of the irreversible ubiquitin proteasome system inhibitor, lactacystin, has been used extensively to model nigrostriatal degeneration in rats, and study the effects of candidate neuroprotective agents on the integrity of the dopaminergic nigrostriatal system. Recently however, adjacent extra-nigral brain regions such as the ventral tegmental area (VTA) have been noted to also become affected in this model, yet their integrity in studies of candidate neuroprotective agents in the model have largely been overlooked. Here we quantify the extent and distribution of dopaminergic degeneration in the VTA of rats intranigrally lesioned with lactacystin, and quantify the extent of VTA dopaminergic neuroprotection after systemic treatment with an epigenetic therapeutic agent, valproate, shown previously to protect dopaminergic SNpc neurons in this model. We found that unilateral intranigral administration of lactacystin resulted in a 53.81% and 31.72% interhemispheric loss of dopaminergic SNpc and VTA neurons, respectively. Daily systemic treatment of lactacystin lesioned rats with valproate however resulted in dose-dependant neuroprotection of VTA neurons. Our findings demonstrate that not only is the VTA also affected in the intranigral lactacystin rat model of PD, but that this extra-nigral brain region is substrate for neuroprotection by valproate, an agent shown previously to induce neuroprotection and neurorestoration of SNpc dopaminergic neurons in this model. Our results therefore suggest that valproate is a candidate for extra-nigral as well as intra-nigral neuroprotection. PMID:26742637

Associated degeneration of ventral tegmental area dopaminergic neurons in the rat nigrostriatal lactacystin model of parkinsonism and their neuroprotection by valproate.

PubMed

Harrison, Ian F; Anis, Hiba K; Dexter, David T

2016-02-12

Parkinson's disease (PD) manifests clinically as bradykinesia, rigidity, and development of a resting tremor, primarily due to degeneration of dopaminergic nigrostriatal pathways in the brain. Intranigral administration of the irreversible ubiquitin proteasome system inhibitor, lactacystin, has been used extensively to model nigrostriatal degeneration in rats, and study the effects of candidate neuroprotective agents on the integrity of the dopaminergic nigrostriatal system. Recently however, adjacent extra-nigral brain regions such as the ventral tegmental area (VTA) have been noted to also become affected in this model, yet their integrity in studies of candidate neuroprotective agents in the model have largely been overlooked. Here we quantify the extent and distribution of dopaminergic degeneration in the VTA of rats intranigrally lesioned with lactacystin, and quantify the extent of VTA dopaminergic neuroprotection after systemic treatment with an epigenetic therapeutic agent, valproate, shown previously to protect dopaminergic SNpc neurons in this model. We found that unilateral intranigral administration of lactacystin resulted in a 53.81% and 31.72% interhemispheric loss of dopaminergic SNpc and VTA neurons, respectively. Daily systemic treatment of lactacystin lesioned rats with valproate however resulted in dose-dependant neuroprotection of VTA neurons. Our findings demonstrate that not only is the VTA also affected in the intranigral lactacystin rat model of PD, but that this extra-nigral brain region is substrate for neuroprotection by valproate, an agent shown previously to induce neuroprotection and neurorestoration of SNpc dopaminergic neurons in this model. Our results therefore suggest that valproate is a candidate for extra-nigral as well as intra-nigral neuroprotection. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Goal-Directed Behavior and Instrumental Devaluation: A Neural System-Level Computational Model

PubMed Central

Mannella, Francesco; Mirolli, Marco; Baldassarre, Gianluca

2016-01-01

Devaluation is the key experimental paradigm used to demonstrate the presence of instrumental behaviors guided by goals in mammals. We propose a neural system-level computational model to address the question of which brain mechanisms allow the current value of rewards to control instrumental actions. The model pivots on and shows the computational soundness of the hypothesis for which the internal representation of instrumental manipulanda (e.g., levers) activate the representation of rewards (or “action-outcomes”, e.g., foods) while attributing to them a value which depends on the current internal state of the animal (e.g., satiation for some but not all foods). The model also proposes an initial hypothesis of the integrated system of key brain components supporting this process and allowing the recalled outcomes to bias action selection: (a) the sub-system formed by the basolateral amygdala and insular cortex acquiring the manipulanda-outcomes associations and attributing the current value to the outcomes; (b) three basal ganglia-cortical loops selecting respectively goals, associative sensory representations, and actions; (c) the cortico-cortical and striato-nigro-striatal neural pathways supporting the selection, and selection learning, of actions based on habits and goals. The model reproduces and explains the results of several devaluation experiments carried out with control rats and rats with pre- and post-training lesions of the basolateral amygdala, the nucleus accumbens core, the prelimbic cortex, and the dorso-medial striatum. The results support the soundness of the hypotheses of the model and show its capacity to integrate, at the system-level, the operations of the key brain structures underlying devaluation. Based on its hypotheses and predictions, the model also represents an operational framework to support the design and analysis of new experiments on the motivational aspects of goal-directed behavior. PMID:27803652

GENETICS OF WHITE MATTER DEVELOPMENT: A DTI STUDY OF 705 TWINS AND THEIR SIBLINGS AGED 12 TO 29

PubMed Central

Chiang, Ming-Chang; McMahon, Katie L.; de Zubicaray, Greig I.; Martin, Nicholas G.; Hickie, Ian; Toga, Arthur W.; Wright, Margaret J.; Thompson, Paul M.

2011-01-01

White matter microstructure is under strong genetic control, yet it is largely unknown how genetic influences change from childhood into adulthood. In one of the largest brain mapping studies ever performed, we determined whether the genetic control over white matter architecture depends on age, sex, socioeconomic status (SES), and intelligence quotient (IQ). We assessed white matter integrity voxelwise using diffusion tensor imaging at high magnetic field (4-Tesla), in 705 twins and their siblings (age range 12–29; 290 M/415 F). White matter integrity was quantified using a widely accepted measure, fractional anisotropy (FA). We fitted gene-environment interaction models pointwise, to visualize brain regions where age, sex, SES and IQ modulate heritability of fiber integrity. We hypothesized that environmental factors would start to outweigh genetic factors during late childhood and adolescence. Genetic influences were greater in adolescence versus adulthood, and greater in males than in females. Socioeconomic status significantly interacted with genes that affect fiber integrity: heritability was higher in those with higher SES. In people with above-average IQ, genetic factors explained over 800% of the observed FA variability in the thalamus, genu, posterior internal capsule, and superior corona radiata. In those with below-average IQ, however, only around 40% FA variability in the same regions was attributable to genetic factors. Genes affect fiber integrity, but their effects vary with age, sex, SES and IQ. Gene-environment interactions are vital to consider in the search for specific genetic polymorphisms that affect brain integrity and connectivity. PMID:20950689

A quest for antipsychotic drug actions in the brain: personal experiences from 50 years of neuropsychiatric research at Karolinska Institutet.

PubMed

Sedvall, Göran

2007-09-10

The exploration of physiological and molecular actions of psychoactive drugs in the brain represents a fundamental approach to the understanding of emerging psychological phenomena. The author gives a personal account of his medical training and research career at Karolinska Institutet over the past 50 years. The paper aims at illustrating how a broad medical education and the integration of basic and clinical neuroscience research is a fruitful ground for the development of new methods and knowledge in this complicated field. Important aspects for an optimal research environment are recruitment of well-educated students, a high intellectual identity of teachers and active researchers, international input and collaboration in addition to good physical resources. In depth exploration of specific signaling pathways as well as an integrative analysis of genes, molecules and systems using multivariate modeling, and bioinformatics, brain mechanisms behind mental phenomena may be understood at a basic level and will ultimately be used for the alleviation and treatment of mental disorders.

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.

An Evolutionary Game Theory Model of Spontaneous Brain Functioning.

PubMed

Madeo, Dario; Talarico, Agostino; Pascual-Leone, Alvaro; Mocenni, Chiara; Santarnecchi, Emiliano

2017-11-22

Our brain is a complex system of interconnected regions spontaneously organized into distinct networks. The integration of information between and within these networks is a continuous process that can be observed even when the brain is at rest, i.e. not engaged in any particular task. Moreover, such spontaneous dynamics show predictive value over individual cognitive profile and constitute a potential marker in neurological and psychiatric conditions, making its understanding of fundamental importance in modern neuroscience. Here we present a theoretical and mathematical model based on an extension of evolutionary game theory on networks (EGN), able to capture brain's interregional dynamics by balancing emulative and non-emulative attitudes among brain regions. This results in the net behavior of nodes composing resting-state networks identified using functional magnetic resonance imaging (fMRI), determining their moment-to-moment level of activation and inhibition as expressed by positive and negative shifts in BOLD fMRI signal. By spontaneously generating low-frequency oscillatory behaviors, the EGN model is able to mimic functional connectivity dynamics, approximate fMRI time series on the basis of initial subset of available data, as well as simulate the impact of network lesions and provide evidence of compensation mechanisms across networks. Results suggest evolutionary game theory on networks as a new potential framework for the understanding of human brain network dynamics.

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

PubMed

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

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

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.

What can autism teach us about the role of sensorimotor systems in higher cognition? New clues from studies on language, action semantics, and abstract emotional concept processing.

PubMed

Moseley, Rachel L; Pulvermüller, Friedemann

2018-03-01

Within the neurocognitive literature there is much debate about the role of the motor system in language, social communication and conceptual processing. We suggest, here, that autism spectrum conditions (ASC) may afford an excellent test case for investigating and evaluating contemporary neurocognitive models, most notably a neurobiological theory of action perception integration where widely-distributed cell assemblies linking neurons in action and perceptual brain regions act as the building blocks of many higher cognitive functions. We review a literature of functional motor abnormalities in ASC, following this with discussion of their neural correlates and aberrancies in language development, explaining how these might arise with reference to the typical formation of cell assemblies linking action and perceptual brain regions. This model gives rise to clear hypotheses regarding language comprehension, and we highlight a recent set of studies reporting differences in brain activation and behaviour in the processing of action-related and abstract-emotional concepts in individuals with ASC. At the neuroanatomical level, we discuss structural differences in long-distance frontotemporal and frontoparietal connections in ASC, such as would compromise information transfer between sensory and motor regions. This neurobiological model of action perception integration may shed light on the cognitive and social-interactive symptoms of ASC, building on and extending earlier proposals linking autistic symptomatology to motor disorder and dysfunction in action perception integration. Further investigating the contribution of motor dysfunction to higher cognitive and social impairment, we suggest, is timely and promising as it may advance both neurocognitive theory and the development of new clinical interventions for this population and others characterised by early and pervasive motor disruption. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

A Neural Signature of Divisive Normalization at the Level of Multisensory Integration in Primate Cortex.

PubMed

Ohshiro, Tomokazu; Angelaki, Dora E; DeAngelis, Gregory C

2017-07-19

Studies of multisensory integration by single neurons have traditionally emphasized empirical principles that describe nonlinear interactions between inputs from two sensory modalities. We previously proposed that many of these empirical principles could be explained by a divisive normalization mechanism operating in brain regions where multisensory integration occurs. This normalization model makes a critical diagnostic prediction: a non-preferred sensory input from one modality, which activates the neuron on its own, should suppress the response to a preferred input from another modality. We tested this prediction by recording from neurons in macaque area MSTd that integrate visual and vestibular cues regarding self-motion. We show that many MSTd neurons exhibit the diagnostic form of cross-modal suppression, whereas unisensory neurons in area MT do not. The normalization model also fits population responses better than a model based on subtractive inhibition. These findings provide strong support for a divisive normalization mechanism in multisensory integration. Copyright © 2017 Elsevier Inc. All rights reserved.

A theory of marks and mind: the effect of notational systems on hominid brain evolution and child development with an emphasis on exchanges between mothers and children.

PubMed

Sheridan, Susan Rich

2005-01-01

A model of human language requires a theory of meaningful marks. Humans are the only species who use marks to think. A theory of marks identifies children's scribbles as significant behavior, while hypothesizing the importance of rotational systems to hominid brain evolution. By recognizing the importance of children's scribbles and drawings in developmental terms as well as in evolutionary terms, a marks-based rather than a predominantly speech-based theory of the human brain, language, and consciousness emerges. Combined research in anthropology, primatology, art history, neurology, child development (including research with deaf and blind children), gender studies and literacy suggests the importance of notational systems to human language, revealing the importance of mother/child interactions around marks and sounds to the development of an expressive, communicative, symbolic human brain. An understanding of human language is enriched by identifying marks carved on bone 1.9 million years ago as observational lunar calendar-keeping, pushing proto-literacy back dramatically. Neurologically, children recapitulate the meaningful marks of early hominins when they scribble and draw, reminding us that literacy belongs to humankind's earliest history. Even more than speech, such meaningful marks played - and continue to play - decisive roles in human brain evolution. The hominid brain required a model for integrative, transformative neural transfer. The research strongly suggests that humankind's multiple literacies (art, literature, scientific writing, mathematics and music) depended upon dyadic exchanges between hominid mothers and children, and that this exchange and sharing of visuo-spatial information drove the elaboration of human speech in terms of syntax, grammar and vocabulary. The human brain was spatial before it was linguistic. The child scribbles and draws before it speaks or writes. Children babble and scribble within the first two years of life. Hands and mouths are proximal on the sensory-motor cortex. Gestures accompany speech. Illiterate brains mis-pronounce nonsense sounds. Literate brains do not. Written language (work of the hands) enhances spoken language (work of the mouth). Until brain scans map the neurological links between human gesture, speech and marks in the context of mother/caregiver/child interactions, and research with literate and illiterate brains document even more precisely the long-term differences between these brains, the evolutionary pressure of marks on especially flexible maternal and infant brain tissue that occurred 1.9 million years, radically changing primate brain capabilities, requires an integrated theory of marks and mind.

Abnormalities in Structural Covariance of Cortical Gyrification in Parkinson's Disease.

PubMed

Xu, Jinping; Zhang, Jiuquan; Zhang, Jinlei; Wang, Yue; Zhang, Yanling; Wang, Jian; Li, Guanglin; Hu, Qingmao; Zhang, Yuanchao

2017-01-01

Although abnormal cortical morphology and connectivity between brain regions (structural covariance) have been reported in Parkinson's disease (PD), the topological organizations of large-scale structural brain networks are still poorly understood. In this study, we investigated large-scale structural brain networks in a sample of 37 PD patients and 34 healthy controls (HC) by assessing the structural covariance of cortical gyrification with local gyrification index (lGI). We demonstrated prominent small-world properties of the structural brain networks for both groups. Compared with the HC group, PD patients showed significantly increased integrated characteristic path length and integrated clustering coefficient, as well as decreased integrated global efficiency in structural brain networks. Distinct distributions of hub regions were identified between the two groups, showing more hub regions in the frontal cortex in PD patients. Moreover, the modular analyses revealed significantly decreased integrated regional efficiency in lateral Fronto-Insula-Temporal module, and increased integrated regional efficiency in Parieto-Temporal module in the PD group as compared to the HC group. In summary, our study demonstrated altered topological properties of structural networks at a global, regional and modular level in PD patients. These findings suggests that the structural networks of PD patients have a suboptimal topological organization, resulting in less effective integration of information between brain regions.

"Mayan Eyes Have Seen the Glory..." or "Please Don't Squeeze the Shaman!" An Interdisciplinary, Integrated, Thematic Study "Chaac" Full of Culture and "Jaded" History of the Mayan Civilization. Fulbright-Hays Summer Seminars Abroad Program, 2000 (Mexico/Guatemala).

ERIC Educational Resources Information Center

Radkey, Tom

This curriculum unit, intended for students in grade 6, covers the Mayas, Mayan history, and ancient civilizations. The unit was developed using Roger Taylor's collaborative team model "Connecting the Curriculum: Using an Integrated, Interdisciplinary, Thematic Approach." The unit addresses multiple intelligences, brain research,…

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.

TU-G-210-02: TRANS-FUSIMO - An Integrative Approach to Model-Based Treatment Planning of Liver FUS

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

Preusser, T.

Modeling can play a vital role in predicting, optimizing and analyzing the results of therapeutic ultrasound treatments. Simulating the propagating acoustic beam in various targeted regions of the body allows for the prediction of the resulting power deposition and temperature profiles. In this session we will apply various modeling approaches to breast, abdominal organ and brain treatments. Of particular interest is the effectiveness of procedures for correcting for phase aberrations caused by intervening irregular tissues, such as the skull in transcranial applications or inhomogeneous breast tissues. Also described are methods to compensate for motion in targeted abdominal organs such asmore » the liver or kidney. Douglas Christensen – Modeling for Breast and Brain HIFU Treatment Planning Tobias Preusser – TRANS-FUSIMO – An Integrative Approach to Model-Based Treatment Planning of Liver FUS Tobias Preusser – TRANS-FUSIMO – An Integrative Approach to Model-Based Treatment Planning of Liver FUS Learning Objectives: Understand the role of acoustic beam modeling for predicting the effectiveness of therapeutic ultrasound treatments. Apply acoustic modeling to specific breast, liver, kidney and transcranial anatomies. Determine how to obtain appropriate acoustic modeling parameters from clinical images. Understand the separate role of absorption and scattering in energy delivery to tissues. See how organ motion can be compensated for in ultrasound therapies. Compare simulated data with clinical temperature measurements in transcranial applications. Supported by NIH R01 HL172787 and R01 EB013433 (DC); EU Seventh Framework Programme (FP7/2007-2013) under 270186 (FUSIMO) and 611889 (TRANS-FUSIMO)(TP); and P01 CA159992, GE, FUSF and InSightec (UV)« less

An Augmented Two-Layer Model Captures Nonlinear Analog Spatial Integration Effects in Pyramidal Neuron Dendrites.

PubMed

Jadi, Monika P; Behabadi, Bardia F; Poleg-Polsky, Alon; Schiller, Jackie; Mel, Bartlett W

2014-05-01

In pursuit of the goal to understand and eventually reproduce the diverse functions of the brain, a key challenge lies in reverse engineering the peculiar biology-based "technology" that underlies the brain's remarkable ability to process and store information. The basic building block of the nervous system is the nerve cell, or "neuron," yet after more than 100 years of neurophysiological study and 60 years of modeling, the information processing functions of individual neurons, and the parameters that allow them to engage in so many different types of computation (sensory, motor, mnemonic, executive, etc.) remain poorly understood. In this paper, we review both historical and recent findings that have led to our current understanding of the analog spatial processing capabilities of dendrites, the major input structures of neurons, with a focus on the principal cell type of the neocortex and hippocampus, the pyramidal neuron (PN). We encapsulate our current understanding of PN dendritic integration in an abstract layered model whose spatially sensitive branch-subunits compute multidimensional sigmoidal functions. Unlike the 1-D sigmoids found in conventional neural network models, multidimensional sigmoids allow the cell to implement a rich spectrum of nonlinear modulation effects directly within their dendritic trees.

Representational geometry: integrating cognition, computation, and the brain.

PubMed

Kriegeskorte, Nikolaus; Kievit, Rogier A

2013-08-01

The cognitive concept of representation plays a key role in theories of brain information processing. However, linking neuronal activity to representational content and cognitive theory remains challenging. Recent studies have characterized the representational geometry of neural population codes by means of representational distance matrices, enabling researchers to compare representations across stages of processing and to test cognitive and computational theories. Representational geometry provides a useful intermediate level of description, capturing both the information represented in a neuronal population code and the format in which it is represented. We review recent insights gained with this approach in perception, memory, cognition, and action. Analyses of representational geometry can compare representations between models and the brain, and promise to explain brain computation as transformation of representational similarity structure. Copyright © 2013 Elsevier Ltd. All rights reserved.

Probing the brain with molecular fMRI.

PubMed

Ghosh, Souparno; Harvey, Peter; Simon, Jacob C; Jasanoff, Alan

2018-06-01

One of the greatest challenges of modern neuroscience is to incorporate our growing knowledge of molecular and cellular-scale physiology into integrated, organismic-scale models of brain function in behavior and cognition. Molecular-level functional magnetic resonance imaging (molecular fMRI) is a new technology that can help bridge these scales by mapping defined microscopic phenomena over large, optically inaccessible regions of the living brain. In this review, we explain how MRI-detectable imaging probes can be used to sensitize noninvasive imaging to mechanistically significant components of neural processing. We discuss how a combination of innovative probe design, advanced imaging methods, and strategies for brain delivery can make molecular fMRI an increasingly successful approach for spatiotemporally resolved studies of diverse neural phenomena, perhaps eventually in people. Copyright © 2018 Elsevier Ltd. All rights reserved.

The graphical brain: Belief propagation and active inference

PubMed Central

Friston, Karl J.; Parr, Thomas; de Vries, Bert

2018-01-01

This paper considers functional integration in the brain from a computational perspective. We ask what sort of neuronal message passing is mandated by active inference—and what implications this has for context-sensitive connectivity at microscopic and macroscopic levels. In particular, we formulate neuronal processing as belief propagation under deep generative models. Crucially, these models can entertain both discrete and continuous states, leading to distinct schemes for belief updating that play out on the same (neuronal) architecture. Technically, we use Forney (normal) factor graphs to elucidate the requisite message passing in terms of its form and scheduling. To accommodate mixed generative models (of discrete and continuous states), one also has to consider link nodes or factors that enable discrete and continuous representations to talk to each other. When mapping the implicit computational architecture onto neuronal connectivity, several interesting features emerge. For example, Bayesian model averaging and comparison, which link discrete and continuous states, may be implemented in thalamocortical loops. These and other considerations speak to a computational connectome that is inherently state dependent and self-organizing in ways that yield to a principled (variational) account. We conclude with simulations of reading that illustrate the implicit neuronal message passing, with a special focus on how discrete (semantic) representations inform, and are informed by, continuous (visual) sampling of the sensorium. Author Summary This paper considers functional integration in the brain from a computational perspective. We ask what sort of neuronal message passing is mandated by active inference—and what implications this has for context-sensitive connectivity at microscopic and macroscopic levels. In particular, we formulate neuronal processing as belief propagation under deep generative models that can entertain both discrete and continuous states. This leads to distinct schemes for belief updating that play out on the same (neuronal) architecture. Technically, we use Forney (normal) factor graphs to characterize the requisite message passing, and link this formal characterization to canonical microcircuits and extrinsic connectivity in the brain. PMID:29417960

Integrating conceptual knowledge within and across representational modalities.

PubMed

McNorgan, Chris; Reid, Jackie; McRae, Ken

2011-02-01

Research suggests that concepts are distributed across brain regions specialized for processing information from different sensorimotor modalities. Multimodal semantic models fall into one of two broad classes differentiated by the assumed hierarchy of convergence zones over which information is integrated. In shallow models, communication within- and between-modality is accomplished using either direct connectivity, or a central semantic hub. In deep models, modalities are connected via cascading integration sites with successively wider receptive fields. Four experiments provide the first direct behavioral tests of these models using speeded tasks involving feature inference and concept activation. Shallow models predict no within-modal versus cross-modal difference in either task, whereas deep models predict a within-modal advantage for feature inference, but a cross-modal advantage for concept activation. Experiments 1 and 2 used relatedness judgments to tap participants' knowledge of relations for within- and cross-modal feature pairs. Experiments 3 and 4 used a dual-feature verification task. The pattern of decision latencies across Experiments 1-4 is consistent with a deep integration hierarchy. Copyright © 2010 Elsevier B.V. All rights reserved.

The Neuronal Infrastructure of Speaking

ERIC Educational Resources Information Center

Menenti, Laura; Segaert, Katrien; Hagoort, Peter

2012-01-01

Models of speaking distinguish producing meaning, words and syntax as three different linguistic components of speaking. Nevertheless, little is known about the brain's integrated neuronal infrastructure for speech production. We investigated semantic, lexical and syntactic aspects of speaking using fMRI. In a picture description task, we…

Lesion-induced increase in survival and migration of human neural progenitor cells releasing GDNF

PubMed Central

Behrstock, Soshana; Ebert, Allison D.; Klein, Sandra; Schmitt, Melanie; Moore, Jeannette M.; Svendsen, Clive N.

2009-01-01

The use of human neural progenitor cells (hNPC) has been proposed to provide neuronal replacement or astrocytes delivering growth factors for brain disorders such as Parkinson’s and Huntington’s disease. Success in such studies likely requires migration from the site of transplantation and integration into host tissue in the face of ongoing damage. In the current study, hNPC modified to release glial cell line derived neurotrophic factor (hNPCGDNF) were transplanted into either intact or lesioned animals. GDNF release itself had no effect on the survival, migration or differentiation of the cells. The most robust migration and survival was found using a direct lesion of striatum (Huntington’s model) with indirect lesions of the dopamine system (Parkinson’s model) or intact animals showing successively less migration and survival. No lesion affected differentiation patterns. We conclude that the type of brain injury dictates migration and integration of hNPC which has important consequences when considering transplantation of these cells as a therapy for neurodegenerative diseases. PMID:19044202

Multisensory Integration and Internal Models for Sensing Gravity Effects in Primates

PubMed Central

Lacquaniti, Francesco; La Scaleia, Barbara; Maffei, Vincenzo

2014-01-01

Gravity is crucial for spatial perception, postural equilibrium, and movement generation. The vestibular apparatus is the main sensory system involved in monitoring gravity. Hair cells in the vestibular maculae respond to gravitoinertial forces, but they cannot distinguish between linear accelerations and changes of head orientation relative to gravity. The brain deals with this sensory ambiguity (which can cause some lethal airplane accidents) by combining several cues with the otolith signals: angular velocity signals provided by the semicircular canals, proprioceptive signals from muscles and tendons, visceral signals related to gravity, and visual signals. In particular, vision provides both static and dynamic signals about body orientation relative to the vertical, but it poorly discriminates arbitrary accelerations of moving objects. However, we are able to visually detect the specific acceleration of gravity since early infancy. This ability depends on the fact that gravity effects are stored in brain regions which integrate visual, vestibular, and neck proprioceptive signals and combine this information with an internal model of gravity effects. PMID:25061610

Multisensory integration and internal models for sensing gravity effects in primates.

PubMed

Lacquaniti, Francesco; Bosco, Gianfranco; Gravano, Silvio; Indovina, Iole; La Scaleia, Barbara; Maffei, Vincenzo; Zago, Myrka

2014-01-01

Gravity is crucial for spatial perception, postural equilibrium, and movement generation. The vestibular apparatus is the main sensory system involved in monitoring gravity. Hair cells in the vestibular maculae respond to gravitoinertial forces, but they cannot distinguish between linear accelerations and changes of head orientation relative to gravity. The brain deals with this sensory ambiguity (which can cause some lethal airplane accidents) by combining several cues with the otolith signals: angular velocity signals provided by the semicircular canals, proprioceptive signals from muscles and tendons, visceral signals related to gravity, and visual signals. In particular, vision provides both static and dynamic signals about body orientation relative to the vertical, but it poorly discriminates arbitrary accelerations of moving objects. However, we are able to visually detect the specific acceleration of gravity since early infancy. This ability depends on the fact that gravity effects are stored in brain regions which integrate visual, vestibular, and neck proprioceptive signals and combine this information with an internal model of gravity effects.

Spatial analysis and high resolution mapping of the human whole-brain transcriptome for integrative analysis in neuroimaging.

PubMed

Gryglewski, Gregor; Seiger, René; James, Gregory Miles; Godbersen, Godber Mathis; Komorowski, Arkadiusz; Unterholzner, Jakob; Michenthaler, Paul; Hahn, Andreas; Wadsak, Wolfgang; Mitterhauser, Markus; Kasper, Siegfried; Lanzenberger, Rupert

2018-08-01

The quantification of big pools of diverse molecules provides important insights on brain function, but is often restricted to a limited number of observations, which impairs integration with other modalities. To resolve this issue, a method allowing for the prediction of mRNA expression in the entire brain based on microarray data provided in the Allen Human Brain Atlas was developed. Microarray data of 3702 samples from 6 brain donors was registered to MNI and cortical surface space using FreeSurfer. For each of 18,686 genes, spatial dependence of transcription was assessed using variogram modelling. Variogram models were employed in Gaussian process regression to calculate best linear unbiased predictions for gene expression at all locations represented in well-established imaging atlases for cortex, subcortical structures and cerebellum. For validation, predicted whole-brain transcription of the HTR1A gene was correlated with [carbonyl- 11 C]WAY-100635 positron emission tomography data collected from 30 healthy subjects. Prediction results showed minimal bias ranging within ±0.016 (cortical surface), ±0.12 (subcortical regions) and ±0.14 (cerebellum) in units of log2 expression intensity for all genes. Across genes, the correlation of predicted and observed mRNA expression in leave-one-out cross-validation correlated with the strength of spatial dependence (cortical surface: r = 0.91, subcortical regions: r = 0.85, cerebellum: r = 0.84). 816 out of 18,686 genes exhibited a high spatial dependence accounting for more than 50% of variance in the difference of gene expression on the cortical surface. In subcortical regions and cerebellum, different sets of genes were implicated by high spatially structured variability. For the serotonin 1A receptor, correlation between PET binding potentials and predicted comprehensive mRNA expression was markedly higher (Spearman ρ = 0.72 for cortical surface, ρ = 0.84 for subcortical regions) than correlation of PET and discrete samples only (ρ = 0.55 and ρ = 0.63, respectively). Prediction of mRNA expression in the entire human brain allows for intuitive visualization of gene transcription and seamless integration in multimodal analysis without bias arising from non-uniform distribution of available samples. Extension of this methodology promises to facilitate translation of omics research and enable investigation of human brain function at a systems level. Copyright © 2018 Elsevier Inc. All rights reserved.

Bipolar disorder: a neural network perspective on a disorder of emotion and motivation.

PubMed

Wessa, Michèle; Kanske, Philipp; Linke, Julia

2014-01-01

Bipolar disorder (BD) is a severe, chronic disease with a heritability of 60-80%. BD is frequently misdiagnosed due to phenomenological overlap with other psychopathologies, an important issue that calls for the identification of biological and psychological vulnerability and disease markers. Altered structural and functional connectivity, mainly between limbic and prefrontal brain areas, have been proposed to underlie emotional and motivational dysregulation in BD and might represent relevant vulnerability and disease markers. In the present laboratory review we discuss functional and structural neuroimaging findings on emotional and motivational dysregulation from our research group in BD patients and healthy individuals at risk to develop BD. As a main result of our studies, we observed altered orbitofrontal and limbic activity and reduced connectivity between dorsal prefrontal and limbic brain regions, as well as reduced integrity of fiber tracts connecting prefrontal and subcortical brain structures in BD patients and high-risk individuals. Our results provide novel insights into pathophysiological mechanisms of bipolar disorder. The current laboratory review provides a specific view of our group on altered brain connectivity and underlying psychological processes in bipolar disorder based on our own work, integrating relevant findings from others. Thereby we attempt to advance neuropsychobiological models of BD.

[Neural mechanism underlying autistic savant and acquired savant syndrome].

PubMed

Takahata, Keisuke; Kato, Motoichiro

2008-07-01

It is well known that the cases with savant syndrome, demonstrate outstanding mental capability despite coexisting severe mental disabilities. In many cases, savant skills are characterized by its domain-specificity, enhanced memory capability, and excessive focus on low-level perceptual processing. In addition, impaired integrative cognitive processing such as social cognition or executive function, restricted interest, and compulsive repetition of the same act are observed in savant individuals. All these are significantly relevant to the behavioral characteristics observed in individuals with autistic spectrum disorders (ASD). A neurocognitive model of savant syndrome should explain these cognitive features and the juxtaposition of outstanding talents with cognitive disabilities. In recent neuropsychological studies, Miller (1998) reported clinical cases of "acquired savant," i.e., patients who improved or newly acquired an artistic savant-like skill in the early stage of frontotemporal dementia (FTD). Although the relationship between an autistic savant and acquired savant remains to be elucidated, the advent of neuroimaging study of ASD and the clarification of FTD patients with savant-like skills may clarify the shared neural mechanisms of both types of talent. In this review, we classified current cognitive models of savant syndrome into the following 3 categories. (1) A hypermnesic model that suggests that savant skills develop from existing or dormant cognitive functions such as memory. However, recent findings obtained through neuropsychological examinations imply that savant individuals solve problems using a strategy that is fairly different from a non-autistic one. (2) A paradoxical functional facilitation model (Kapur, 1996) that offers possible explanations about how pathological states in the brain lead to development of prodigious skills. This model emphasizes the role of reciprocal inhibitory interaction among adjacent or distant cortical regions, especially that of the prefrontal cortex and the posterior regions of the brain. (3) Autistic models, including those based on weak central coherence theory (Frith, 1989), that focus on how savant skills emerge from an autistic brain. Based on recent neuroimaging studies of ASD, Just et al. (2004) suggested the underconnectivity theory, which emphasizes the disruption of long-range connectivity and the relative intact or even more enhanced local connectivity in the autistic brain. All the models listed above have certain advantages and shortcomings. At the end of this review, we propose another integrative model of savant syndrome. In this model, we predict an altered balance of local/global connectivity patterns that contribute to an altered functional segregation/integration ratio. In particular, we emphasize the crucial role played by the disruption of global connectivity in a parallel distributed cortical network, which might result in impairment in integrated cognitive processing, such as impairment in executive function and social cognition. On the other hand, the reduced inter-regional collaboration could lead to a disinhibitory enhancement of neural activity and connectivity in local cortical regions. In addition, enhanced connectivity in the local brain regions is partly due to the abnormal organization of the cortical network as a result of developmental and pathological states. This enhanced local connectivity results in the specialization and facilitation of low-level cognitive processing. The disruption of connectivity between the prefrontal cortex and other regions is considered to be a particularly important factor because the prefrontal region shows the most influential inhibitory control on other cortical areas. We propose that these neural mechanisms as the underlying causes for the emergence of savant ability in ASD and FTD patients.

Tracer kinetic modelling for DCE-MRI quantification of subtle blood-brain barrier permeability.

PubMed

Heye, Anna K; Thrippleton, Michael J; Armitage, Paul A; Valdés Hernández, Maria Del C; Makin, Stephen D; Glatz, Andreas; Sakka, Eleni; Wardlaw, Joanna M

2016-01-15

There is evidence that subtle breakdown of the blood-brain barrier (BBB) is a pathophysiological component of several diseases, including cerebral small vessel disease and some dementias. Dynamic contrast-enhanced MRI (DCE-MRI) combined with tracer kinetic modelling is widely used for assessing permeability and perfusion in brain tumours and body tissues where contrast agents readily accumulate in the extracellular space. However, in diseases where leakage is subtle, the optimal approach for measuring BBB integrity is likely to differ since the magnitude and rate of enhancement caused by leakage are extremely low; several methods have been reported in the literature, yielding a wide range of parameters even in healthy subjects. We hypothesised that the Patlak model is a suitable approach for measuring low-level BBB permeability with low temporal resolution and high spatial resolution and brain coverage, and that normal levels of scanner instability would influence permeability measurements. DCE-MRI was performed in a cohort of mild stroke patients (n=201) with a range of cerebral small vessel disease severity. We fitted these data to a set of nested tracer kinetic models, ranking their performance according to the Akaike information criterion. To assess the influence of scanner drift, we scanned 15 healthy volunteers that underwent a "sham" DCE-MRI procedure without administration of contrast agent. Numerical simulations were performed to investigate model validity and the effect of scanner drift. The Patlak model was found to be most appropriate for fitting low-permeability data, and the simulations showed vp and K(Trans) estimates to be reasonably robust to the model assumptions. However, signal drift (measured at approximately 0.1% per minute and comparable to literature reports in other settings) led to systematic errors in calculated tracer kinetic parameters, particularly at low permeabilities. Our findings justify the growing use of the Patlak model in low-permeability states, which has the potential to provide valuable information regarding BBB integrity in a range of diseases. However, absolute values of the resulting tracer kinetic parameters should be interpreted with extreme caution, and the size and influence of signal drift should be measured where possible. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Tracer kinetic modelling for DCE-MRI quantification of subtle blood–brain barrier permeability

PubMed Central

Heye, Anna K.; Thrippleton, Michael J.; Armitage, Paul A.; Valdés Hernández, Maria del C.; Makin, Stephen D.; Glatz, Andreas; Sakka, Eleni; Wardlaw, Joanna M.

2016-01-01

There is evidence that subtle breakdown of the blood–brain barrier (BBB) is a pathophysiological component of several diseases, including cerebral small vessel disease and some dementias. Dynamic contrast-enhanced MRI (DCE-MRI) combined with tracer kinetic modelling is widely used for assessing permeability and perfusion in brain tumours and body tissues where contrast agents readily accumulate in the extracellular space. However, in diseases where leakage is subtle, the optimal approach for measuring BBB integrity is likely to differ since the magnitude and rate of enhancement caused by leakage are extremely low; several methods have been reported in the literature, yielding a wide range of parameters even in healthy subjects. We hypothesised that the Patlak model is a suitable approach for measuring low-level BBB permeability with low temporal resolution and high spatial resolution and brain coverage, and that normal levels of scanner instability would influence permeability measurements. DCE-MRI was performed in a cohort of mild stroke patients (n = 201) with a range of cerebral small vessel disease severity. We fitted these data to a set of nested tracer kinetic models, ranking their performance according to the Akaike information criterion. To assess the influence of scanner drift, we scanned 15 healthy volunteers that underwent a “sham” DCE-MRI procedure without administration of contrast agent. Numerical simulations were performed to investigate model validity and the effect of scanner drift. The Patlak model was found to be most appropriate for fitting low-permeability data, and the simulations showed vp and KTrans estimates to be reasonably robust to the model assumptions. However, signal drift (measured at approximately 0.1% per minute and comparable to literature reports in other settings) led to systematic errors in calculated tracer kinetic parameters, particularly at low permeabilities. Our findings justify the growing use of the Patlak model in low-permeability states, which has the potential to provide valuable information regarding BBB integrity in a range of diseases. However, absolute values of the resulting tracer kinetic parameters should be interpreted with extreme caution, and the size and influence of signal drift should be measured where possible. PMID:26477653

Focused ultrasound-mediated drug delivery through the blood-brain barrier

PubMed Central

Burgess, Alison; Shah, Kairavi; Hough, Olivia; Hynynen, Kullervo

2015-01-01

Despite recent advances in blood-brain barrier (BBB) research, it remains a significant hurdle for the pharmaceutical treatment of brain diseases. Focused ultrasound (FUS) is one method to transiently increase permeability of the BBB to promote drug delivery to specific brain regions. An introduction to the BBB and a brief overview of the methods which can be used to circumvent the BBB to promote drug delivery is provided. In particular, we discuss the advantages and limitations of FUS technology and the efficacy of FUS-mediated drug delivery in models of disease. MRI for targeting and evaluating FUS treatments, combined with administration of microbubbles, allows for transient, reproducible BBB opening. The integration of a real-time acoustic feedback controller has improved treatment safety. Successful clinical translation of FUS has the potential to transform the treatment of brain disease worldwide without requiring the development of new pharmaceutical agents. PMID:25936845

Law, evolution and the brain: applications and open questions.

PubMed Central

Jones, Owen D

2004-01-01

This paper discusses several issues at the intersection of law and brain science. It focuses principally on ways in which an improved understanding of how evolutionary processes affect brain function and human behaviour may improve law's ability to regulate behaviour. It explores sample uses of such 'evolutionary analysis in law' and also raises questions about how that analysis might be improved in the future. Among the discussed uses are: (i) clarifying cost-benefit analyses; (ii) providing theoretical foundation and potential predictive power; (iii) assessing comparative effectiveness of legal strategies; and (iv) revealing deep patterns in legal architecture. Throughout, the paper emphasizes the extent to which effective law requires: (i) building effective behavioural models; (ii) integrating life-science perspectives with social-science perspectives; (iii) considering the effects of brain biology on behaviours that law seeks to regulate; and (iv) examining the effects of evolutionary processes on brain design. PMID:15590611

Law, evolution and the brain: applications and open questions.

PubMed

Jones, Owen D

2004-11-29

This paper discusses several issues at the intersection of law and brain science. It focuses principally on ways in which an improved understanding of how evolutionary processes affect brain function and human behaviour may improve law's ability to regulate behaviour. It explores sample uses of such 'evolutionary analysis in law' and also raises questions about how that analysis might be improved in the future. Among the discussed uses are: (i) clarifying cost-benefit analyses; (ii) providing theoretical foundation and potential predictive power; (iii) assessing comparative effectiveness of legal strategies; and (iv) revealing deep patterns in legal architecture. Throughout, the paper emphasizes the extent to which effective law requires: (i) building effective behavioural models; (ii) integrating life-science perspectives with social-science perspectives; (iii) considering the effects of brain biology on behaviours that law seeks to regulate; and (iv) examining the effects of evolutionary processes on brain design.

Three-dimensional atlas of iron, copper, and zinc in the mouse cerebrum and brainstem.

PubMed

Hare, Dominic J; Lee, Jason K; Beavis, Alison D; van Gramberg, Amanda; George, Jessica; Adlard, Paul A; Finkelstein, David I; Doble, Philip A

2012-05-01

Atlases depicting molecular and functional features of the brain are becoming an integral part of modern neuroscience. In this study we used laser ablation-inductively coupled plasma-mass spectrometry (LA-ICPMS) to quantitatively measure iron (Fe), copper (Cu), and zinc (Zn) levels in a serially sectioned C57BL/6 mouse brain (cerebrum and brainstem). Forty-six sections were analyzed in a single experiment of approximately 158 h in duration. We constructed a 46-plate reference atlas by aligning quantified images of metal distribution with corresponding coronal sections from the Allen Mouse Brain Reference Atlas. The 46 plates were also used to construct three-dimensional models of Fe, Cu, and Zn distribution. This atlas represents the first reconstruction of quantitative trace metal distribution through the brain by LA-ICPMS and will facilitate the study of trace metals in the brain and help to elucidate their role in neurobiology.

Association Between Brain-Derived Neurotrophic Factor Genotype and Upper Extremity Motor Outcome After Stroke.

PubMed

Chang, Won Hyuk; Park, Eunhee; Lee, Jungsoo; Lee, Ahee; Kim, Yun-Hee

2017-06-01

The identification of intrinsic factors for predicting upper extremity motor outcome could aid the design of individualized treatment plans in stroke rehabilitation. The aim of this study was to identify prognostic factors, including intrinsic genetic factors, for upper extremity motor outcome in patients with subacute stroke. A total of 97 patients with subacute stroke were enrolled. Upper limb motor impairment was scored according to the upper limb of Fugl-Meyer assessment score at 3 months after stroke. The prediction of upper extremity motor outcome at 3 months was modeled using various factors that could potentially influence this impairment, including patient characteristics, baseline upper extremity motor impairment, functional and structural integrity of the corticospinal tract, and brain-derived neurotrophic factor genotype. Multivariate ordinal logistic regression models were used to identify the significance of each factor. The independent predictors of motor outcome at 3 months were baseline upper extremity motor impairment, age, stroke type, and corticospinal tract functional integrity in all stroke patients. However, in the group with severe motor impairment at baseline (upper limb score of Fugl-Meyer assessment <25), the number of Met alleles in the brain-derived neurotrophic factor genotype was also an independent predictor of upper extremity motor outcome 3 months after stroke. Brain-derived neurotrophic factor genotype may be a potentially useful predictor of upper extremity motor outcome in patients with subacute stroke with severe baseline motor involvement. © 2017 American Heart Association, Inc.

Nicotinamide Forestalls Pathology and Cognitive Decline in Alzheimer Mice: Evidence for Improved Neuronal Bioenergetics and Autophagy Procession

PubMed Central

Liu, Dong; Pitta, Michael; Jiang, Haiyang; Lee, Jong-Hwan; Zhang, Guofeng; Chen, Xinzhi; Kawamoto, Elisa M.; Mattson, Mark P.

2012-01-01

Impaired brain energy metabolism and oxidative stress are implicated in cognitive decline and the pathological accumulations of amyloid β-peptide (Aβ) and hyperphosphorylated Tau (p-Tau) in Alzheimer's disease (AD). To determine whether improving brain energy metabolism will forestall disease progress in AD, the impact of the NAD+ precursor nicotinamide on brain cell mitochondrial function and macroautophagy, bioenergetics-related signaling and cognitive performance were studied in cultured neurons and in a mouse model of AD. Oxidative stress resulted in decreased mitochondrial mass, mitochondrial degeneration and autophagosome accumulation in neurons. Nicotinamide preserved mitochondrial integrity and autophagy function, and reduced neuronal vulnerability to oxidative/metabolic insults and Aβ toxicity. NAD+ biosynthesis, autophagy and PI3K signaling were required for the neuroprotective action of nicotinamide. Treatment of 3xTgAD mice with nicotinamide for 8 months resulted in improved cognitive performance, and reduced Aβ and p-Tau pathologies in hippocampus and cerebral cortex. Nicotinamide treatment preserved mitochondrial integrity, and improved autophagy-lysosome procession by enhancing lysosome/autolysosome acidification to reduce autophagosome accumulation. Treatment of 3xTgAD mice with nicotinamide resulted in elevated levels of activated neuroplasticity-related kinases (Akt and ERKs) and the transcription factor cyclic AMP response element-binding protein in the hippocampus and cerebral cortex. Thus, nicotinamide suppresses AD pathology and cognitive decline in a mouse model of AD by a mechanism involving improved brain bioenergetics with preserved functionality of mitochondria and the autophagy system. PMID:23273573

Advance Preparation in Task-Switching: Converging Evidence from Behavioral, Brain Activation, and Model-Based Approaches

PubMed Central

Karayanidis, Frini; Jamadar, Sharna; Ruge, Hannes; Phillips, Natalie; Heathcote, Andrew; Forstmann, Birte U.

2010-01-01

Recent research has taken advantage of the temporal and spatial resolution of event-related brain potentials (ERPs) and functional magnetic resonance imaging (fMRI) to identify the time course and neural circuitry of preparatory processes required to switch between different tasks. Here we overview some key findings contributing to understanding strategic processes in advance preparation. Findings from these methodologies are compatible with advance preparation conceptualized as a set of processes activated for both switch and repeat trials, but with substantial variability as a function of individual differences and task requirements. We then highlight new approaches that attempt to capitalize on this variability to link behavior and brain activation patterns. One approach examines correlations among behavioral, ERP and fMRI measures. A second “model-based” approach accounts for differences in preparatory processes by estimating quantitative model parameters that reflect latent psychological processes. We argue that integration of behavioral and neuroscientific methodologies is key to understanding the complex nature of advance preparation in task-switching. PMID:21833196

Stepwise Connectivity of the Modal Cortex Reveals the Multimodal Organization of the Human Brain

PubMed Central

Sepulcre, Jorge; Sabuncu, Mert R.; Yeo, Thomas B.; Liu, Hesheng; Johnson, Keith A.

2012-01-01

How human beings integrate information from external sources and internal cognition to produce a coherent experience is still not well understood. During the past decades, anatomical, neurophysiological and neuroimaging research in multimodal integration have stood out in the effort to understand the perceptual binding properties of the brain. Areas in the human lateral occipito-temporal, prefrontal and posterior parietal cortices have been associated with sensory multimodal processing. Even though this, rather patchy, organization of brain regions gives us a glimpse of the perceptual convergence, the articulation of the flow of information from modality-related to the more parallel cognitive processing systems remains elusive. Using a method called Stepwise Functional Connectivity analysis, the present study analyzes the functional connectome and transitions from primary sensory cortices to higher-order brain systems. We identify the large-scale multimodal integration network and essential connectivity axes for perceptual integration in the human brain. PMID:22855814

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

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.

Help, I need to develop communication skills on donation: the "VIDEO" model.

PubMed

Smudla, A; Mihály, S; Hegedüs, K; Nemes, B; Fazakas, J

2011-05-01

Information about brain stem death and donation can be influence the consent rate for donation and its psychosocial effects. The aim of this study was to create a "VIDEO" model that could be used to help physicians to develop communication skills. A video recorded 32 simulations of family interviews: 16 under-age and 16 adult donors. They were analyzed during 8 courses conducted in 2008 and 2009. During the VIDEO process, the visual presentation was followed by participants (n=192) discussing interactively the donation situation. After the transcription of the video records, family interviews were explored retrospectively regarding informing relatives about brain stem death and donation, typical communication gaps and common questions from families. The data were examined qualitatively and semiquantitatively. We think that teaching can be optimized by our results. A comprehensible explanation about brain stem death was provided to relatives in 65.63% of cases. The consent of the family was more important for the physicians than the application of the law in 93.75%; 78.13% of physicians emphasized altruism to support donation. Remarkable mistakes of communication included using the teams coma and brain stem death interchangeably (9.38%); applying expressions connected with life in the present tense (21.88%) and mechanically kept alive (21.88%); organ-focused behavior such as "organs to be usable" (34.38%). The frequent questions and statements of "relatives" were "heart beats" (100%), "did he really die?" (65.63%), "fear of loss of integrity of the corpse" (59.38%), and "wake up from the coma" (46.88%). Interaction with the family requires great preparation. The communication skills of physicians can be developed through the VIDEO model. The results can be integrated into educational programs that consider the particular features of the given country. Copyright © 2011 Elsevier Inc. All rights reserved.

Hyperbrain features of team mental models within a juggling paradigm: a proof of concept

PubMed Central

Filho, Edson; Tamburro, Gabriella; Schinaia, Lorenzo; Chatel-Goldman, Jonas; di Fronso, Selenia; Robazza, Claudio

2016-01-01

Background Research on cooperative behavior and the social brain exists, but little research has focused on real-time motor cooperative behavior and its neural correlates. In this proof of concept study, we explored the conceptual notion of shared and complementary mental models through EEG mapping of two brains performing a real-world interactive motor task of increasing difficulty. We used the recently introduced participative “juggling paradigm,” and collected neuro-physiological and psycho-social data. We were interested in analyzing the between-brains coupling during a dyadic juggling task, and in exploring the relationship between the motor task execution, the jugglers’skill level and the task difficulty. We also investigated how this relationship could be mirrored in the coupled functional organization of the interacting brains. Methods To capture the neural schemas underlying the notion of shared and complementary mental models, we examined the functional connectivity patterns and hyperbrain features of a juggling dyad involved in cooperative motor tasks of increasing difficulty. Jugglers’ cortical activity was measured using two synchronized 32-channel EEG systems during dyadic juggling performed with 3, 4, 5 and 6 balls. Individual and hyperbrain functional connections were quantified through coherence maps calculated across all electrode pairs in the theta and alpha bands (4–8 and 8–12 Hz). Graph metrics were used to typify the global topology and efficiency of the functional networks for the four difficulty levels in the theta and alpha bands. Results Results indicated that, as task difficulty increased, the cortical functional organization of the more skilled juggler became progressively more segregated in both frequency bands, with a small-world organization in the theta band during easier tasks, indicative of a flow-like state in line with the neural efficiency hypothesis. Conversely, more integrated functional patterns were observed for the less skilled juggler in both frequency bands, possibly related to cognitive overload due to the difficulty of the task at hand (reinvestment hypothesis). At the hyperbrain level, a segregated functional organization involving areas of the visuo-attentional networks of both jugglers was observed in both frequency bands and for the easier task only. Discussion These results suggest that cooperative juggling is supported by integrated activity of specialized cortical areas from both brains only during easier tasks, whereas it relies on individual skills, mirrored in uncorrelated individual brain activations, during more difficult tasks. These findings suggest that task difficulty and jugglers’ personal skills may influence the features of the hyperbrain network in its shared/integrative and complementary/segregative tendencies. PMID:27688968

Development of an experimental model of brain tissue heterotopia in the lung

PubMed Central

Quemelo, Paulo Roberto Veiga; Sbragia, Lourenço; Peres, Luiz Cesar

2007-01-01

Summary The presence of heterotopic brain tissue in the lung is a rare abnormality. The cases reported thus far are usually associated with neural tube defects (NTD). As there are no reports of experimental models of NTD that present this abnormality, the objective of the present study was to develop a surgical method of brain tissue heterotopia in the lung. We used 24 pregnant Swiss mice divided into two groups of 12 animals each, denoted 17GD and 18GD according to the gestational day (GD) when caesarean section was performed to collect the fetuses. Surgery was performed on the 15th GD, one fetus was removed by hysterectomy and its brain tissue was cut into small fragments and implanted in the lung of its litter mates. Thirty-four live fetuses were obtained from the 17GD group. Of these, eight (23.5%) were used as control (C), eight (23.5%) were sham operated (S) and 18 (52.9%) were used for pulmonary brain tissue implantation (PBI). Thirty live fetuses were obtained from the females of the 18GD group. Of these, eight (26.6%) were C, eight (26.6%) S and 14 (46.6%) were used for PBI. Histological examination of the fetal trunks showed implantation of GFAP-positive brain tissue in 85% of the fetuses of the 17GD group and in 100% of those of the 18GD group, with no significant difference between groups for any of the parameters analysed. The experimental model proved to be efficient and of relatively simple execution, showing complete integration of the brain tissue with pulmonary and pleural tissue and thus representing a model that will permit the study of different aspects of cell implantation and interaction. PMID:17877535

Patient-specific non-linear finite element modelling for predicting soft organ deformation in real-time: application to non-rigid neuroimage registration.

PubMed

Wittek, Adam; Joldes, Grand; Couton, Mathieu; Warfield, Simon K; Miller, Karol

2010-12-01

Long computation times of non-linear (i.e. accounting for geometric and material non-linearity) biomechanical models have been regarded as one of the key factors preventing application of such models in predicting organ deformation for image-guided surgery. This contribution presents real-time patient-specific computation of the deformation field within the brain for six cases of brain shift induced by craniotomy (i.e. surgical opening of the skull) using specialised non-linear finite element procedures implemented on a graphics processing unit (GPU). In contrast to commercial finite element codes that rely on an updated Lagrangian formulation and implicit integration in time domain for steady state solutions, our procedures utilise the total Lagrangian formulation with explicit time stepping and dynamic relaxation. We used patient-specific finite element meshes consisting of hexahedral and non-locking tetrahedral elements, together with realistic material properties for the brain tissue and appropriate contact conditions at the boundaries. The loading was defined by prescribing deformations on the brain surface under the craniotomy. Application of the computed deformation fields to register (i.e. align) the preoperative and intraoperative images indicated that the models very accurately predict the intraoperative deformations within the brain. For each case, computing the brain deformation field took less than 4 s using an NVIDIA Tesla C870 GPU, which is two orders of magnitude reduction in computation time in comparison to our previous study in which the brain deformation was predicted using a commercial finite element solver executed on a personal computer. Copyright © 2010 Elsevier Ltd. All rights reserved.

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

Sex differences in the developing brain as a source of inherent risk

PubMed Central

McCarthy, Margaret M.

2016-01-01

Brain development diverges in males and females in response to androgen production by the fetal testis. This sexual differentiation of the brain occurs during a sensitive window and induces enduring neuroanatomical and physiological changes that profoundly impact behavior. What we know about the contribution of sex chromosomes is still emerging, highlighting the need to integrate multiple factors into understanding sex differences, including the importance of context. The cellular mechanisms are best modeled in rodents and have provided both unifying principles and surprising specifics. Markedly distinct signaling pathways direct differentiation in specific brain regions, resulting in mosaicism of relative maleness, femaleness, and sameness through-out the brain, while canalization both exaggerates and constrains sex differences. Non-neuronal cells and inflammatory mediators are found in greater number and at higher levels in parts of male brains. This higher baseline of inflammation is speculated to increase male vulnerability to developmental neuropsychiatric disorders that are triggered by inflammation. PMID:28179808

Interactive natural language acquisition in a multi-modal recurrent neural architecture

NASA Astrophysics Data System (ADS)

Heinrich, Stefan; Wermter, Stefan

2018-01-01

For the complex human brain that enables us to communicate in natural language, we gathered good understandings of principles underlying language acquisition and processing, knowledge about sociocultural conditions, and insights into activity patterns in the brain. However, we were not yet able to understand the behavioural and mechanistic characteristics for natural language and how mechanisms in the brain allow to acquire and process language. In bridging the insights from behavioural psychology and neuroscience, the goal of this paper is to contribute a computational understanding of appropriate characteristics that favour language acquisition. Accordingly, we provide concepts and refinements in cognitive modelling regarding principles and mechanisms in the brain and propose a neurocognitively plausible model for embodied language acquisition from real-world interaction of a humanoid robot with its environment. In particular, the architecture consists of a continuous time recurrent neural network, where parts have different leakage characteristics and thus operate on multiple timescales for every modality and the association of the higher level nodes of all modalities into cell assemblies. The model is capable of learning language production grounded in both, temporal dynamic somatosensation and vision, and features hierarchical concept abstraction, concept decomposition, multi-modal integration, and self-organisation of latent representations.

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.

β-cyclodextrin-poly(β-amino ester) nanoparticles for sustained drug delivery across the blood-brain barrier.

PubMed

Gil, Eun Seok; Wu, Linfeng; Xu, Lichong; Lowe, Tao Lu

2012-11-12

Novel biodegradable polymeric nanoparticles composed of β-cyclodextrin and poly(β-amino ester) segments have been developed for sustained drug delivery across the blood-brain barrier (BBB). The nanoparticles have been synthesized by cross-linking β-cyclodextrin with poly(β-amino ester) via the Michael addition method. The chemical, physical, and degradation properties of the nanoparticles have been characterized by matrix-assisted laser desoption/ionization time-of-flight, attenuated total reflectance Fourier transform infrared spectroscopy, nuclear magnetic resonance, dynamic light scattering, and atomic force microscopy techniques. Bovine and human brain microvascular endothelial cell monolayers have been constructed as in vitro BBB models. Preliminary results show that the nanoparticles do not affect the integrity of the in vitro BBB models, and the nanoparticles have much higher permeability than dextran control across the in vitro BBB models. Doxorubicin has been loaded into the nanoparticles with a loading efficiency of 86%, and can be released from the nanoparticles for at least one month. The developed β-cyclodextrin-poly(β-amino ester) nanoparticles might be useful as drug carriers for transporting drugs across the BBB to treat chronic diseases in the brain.

Systems Nutrigenomics Reveals Brain Gene Networks Linking Metabolic and Brain Disorders.

PubMed

Meng, Qingying; Ying, Zhe; Noble, Emily; Zhao, Yuqi; Agrawal, Rahul; Mikhail, Andrew; Zhuang, Yumei; Tyagi, Ethika; Zhang, Qing; Lee, Jae-Hyung; Morselli, Marco; Orozco, Luz; Guo, Weilong; Kilts, Tina M; Zhu, Jun; Zhang, Bin; Pellegrini, Matteo; Xiao, Xinshu; Young, Marian F; Gomez-Pinilla, Fernando; Yang, Xia

2016-05-01

Nutrition plays a significant role in the increasing prevalence of metabolic and brain disorders. Here we employ systems nutrigenomics to scrutinize the genomic bases of nutrient-host interaction underlying disease predisposition or therapeutic potential. We conducted transcriptome and epigenome sequencing of hypothalamus (metabolic control) and hippocampus (cognitive processing) from a rodent model of fructose consumption, and identified significant reprogramming of DNA methylation, transcript abundance, alternative splicing, and gene networks governing cell metabolism, cell communication, inflammation, and neuronal signaling. These signals converged with genetic causal risks of metabolic, neurological, and psychiatric disorders revealed in humans. Gene network modeling uncovered the extracellular matrix genes Bgn and Fmod as main orchestrators of the effects of fructose, as validated using two knockout mouse models. We further demonstrate that an omega-3 fatty acid, DHA, reverses the genomic and network perturbations elicited by fructose, providing molecular support for nutritional interventions to counteract diet-induced metabolic and brain disorders. Our integrative approach complementing rodent and human studies supports the applicability of nutrigenomics principles to predict disease susceptibility and to guide personalized medicine. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Quantifying the association between white matter integrity changes and subconcussive head impact exposure from a single season of youth and high school football using 3D convolutional neural networks

NASA Astrophysics Data System (ADS)

Saghafi, Behrouz; Murugesan, Gowtham; Davenport, Elizabeth; Wagner, Ben; Urban, Jillian; Kelley, Mireille; Jones, Derek; Powers, Alexander; Whitlow, Christopher; Stitzel, Joel; Maldjian, Joseph; Montillo, Albert

2018-02-01

The effect of subconcussive head impact exposure during contact sports, including American football, on brain health is poorly understood particularly in young and adolescent players, who may be more vulnerable to brain injury during periods of rapid brain maturation. This study aims to quantify the association between cumulative effects of head impact exposure from a single season of football on white matter (WM) integrity as measured with diffusion MRI. The study targets football players aged 9-18 years old. All players were imaged pre- and post-season with structural MRI and diffusion tensor MRI (DTI). Fractional Anisotropy (FA) maps, shown to be closely correlated with WM integrity, were computed for each subject, co-registered and subtracted to compute the change in FA per subject. Biomechanical metrics were collected at every practice and game using helmet mounted accelerometers. Each head impact was converted into a risk of concussion, and the risk of concussion-weighted cumulative exposure (RWE) was computed for each player for the season. Athletes with high and low RWE were selected for a two-category classification task. This task was addressed by developing a 3D Convolutional Neural Network (CNN) to automatically classify players into high and low impact exposure groups from the change in FA maps. Using the proposed model, high classification performance, including ROC Area Under Curve score of 85.71% and F1 score of 83.33% was achieved. This work adds to the growing body of evidence for the presence of detectable neuroimaging brain changes in white matter integrity from a single season of contact sports play, even in the absence of a clinically diagnosed concussion.

Validation of UHPLC-MS/MS methods for the determination of kaempferol and its metabolite 4-hydroxyphenyl acetic acid, and application to in vitro blood-brain barrier and intestinal drug permeability studies.

PubMed

Moradi-Afrapoli, Fahimeh; Oufir, Mouhssin; Walter, Fruzsina R; Deli, Maria A; Smiesko, Martin; Zabela, Volha; Butterweck, Veronika; Hamburger, Matthias

2016-09-05

Sedative and anxiolytic-like properties of flavonoids such as kaempferol and quercetin, and of some of their intestinal metabolites, have been demonstrated in pharmacological studies. However, routes of administration were shown to be critical for observing in vivo activity. Therefore, the ability to cross intestinal and blood-brain barriers was assessed in cell-based models for kaempferol (KMF), and for the major intestinal metabolite of KMF, 4-hydroxyphenylacetic acid (4-HPAA). Intestinal transport studies were performed with Caco-2 cells, and blood-brain barrier transport studies with an immortalized monoculture human model and a primary triple-co-culture rat model. UHPLC-MS/MS methods for KMF and 4-HPAA in Ringer-HEPES buffer and in Hank's balanced salt solution were validated according to industry guidelines. For all methods, calibration curves were fitted by least-squares quadratic regression with 1/X(2) as weighing factor, and mean coefficients of determination (R(2)) were >0.99. Data obtained with all barrier models showed high intestinal and blood-brain barrier permeation of KMF, and no permeability of 4-HPAA, when compared to barrier integrity markers. Copyright © 2016 Elsevier B.V. All rights reserved.

Learning dynamics by theoretical tools of game theory. 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 M. Pelowski et al.

NASA Astrophysics Data System (ADS)

Burini, Diletta; De Lillo, Silvana

2017-07-01

The VIMAP model presented in the survey [5] aims at analyzing the processes that can occur in the human perception in the front of an artwork. Such a model combines the bottom-up (artwork derived) processes with the top-down mechanisms which describe how individuals adapt or change their own art processing experience. The cognitive flow consists of seven stages connected to five outcomes, which account for all the main ways of responding to art. Moreover this model can also identify the specific regions of the brain that are posited to be main centers of the processes that may coincide with the proposed cognitive checks.

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.

Endothelium-targeted overexpression of heat shock protein 27 ameliorates blood–brain barrier disruption after ischemic brain injury

PubMed Central

Jiang, Xiaoyan; Zhang, Lili; Pu, Hongjian; Hu, Xiaoming; Zhang, Wenting; Cai, Wei; Gao, Yanqin; Leak, Rehana K.; Keep, Richard F.; Bennett, Michael V. L.; Chen, Jun

2017-01-01

The damage borne by the endothelial cells (ECs) forming the blood–brain barrier (BBB) during ischemic stroke and other neurological conditions disrupts the structure and function of the neurovascular unit and contributes to poor patient outcomes. We recently reported that structural aberrations in brain microvascular ECs—namely, uncontrolled actin polymerization and subsequent disassembly of junctional proteins, are a possible cause of the early onset BBB breach that arises within 30–60 min of reperfusion after transient focal ischemia. Here, we investigated the role of heat shock protein 27 (HSP27) as a direct inhibitor of actin polymerization and protectant against BBB disruption after ischemia/reperfusion (I/R). Using in vivo and in vitro models, we found that targeted overexpression of HSP27 specifically within ECs—but not within neurons—ameliorated BBB impairment 1–24 h after I/R. Mechanistically, HSP27 suppressed I/R-induced aberrant actin polymerization, stress fiber formation, and junctional protein translocation in brain microvascular ECs, independent of its protective actions against cell death. By preserving BBB integrity after I/R, EC-targeted HSP27 overexpression attenuated the infiltration of potentially destructive neutrophils and macrophages into brain parenchyma, thereby improving long-term stroke outcome. Notably, early poststroke administration of HSP27 attached to a cell-penetrating transduction domain (TAT-HSP27) rapidly elevated HSP27 levels in brain microvessels and ameliorated I/R-induced BBB disruption and subsequent neurological deficits. Thus, the present study demonstrates that HSP27 can function at the EC level to preserve BBB integrity after I/R brain injury. HSP27 may be a therapeutic agent for ischemic stroke and other neurological conditions involving BBB breakdown. PMID:28137866

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.

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.

Direction-dependent arm kinematics reveal optimal integration of gravity cues

PubMed Central

Gaveau, Jeremie; Berret, Bastien; Angelaki, Dora E; Papaxanthis, Charalambos

2016-01-01

The brain has evolved an internal model of gravity to cope with life in the Earth's gravitational environment. How this internal model benefits the implementation of skilled movement has remained unsolved. One prevailing theory has assumed that this internal model is used to compensate for gravity's mechanical effects on the body, such as to maintain invariant motor trajectories. Alternatively, gravity force could be used purposely and efficiently for the planning and execution of voluntary movements, thereby resulting in direction-depending kinematics. Here we experimentally interrogate these two hypotheses by measuring arm kinematics while varying movement direction in normal and zero-G gravity conditions. By comparing experimental results with model predictions, we show that the brain uses the internal model to implement control policies that take advantage of gravity to minimize movement effort. DOI: http://dx.doi.org/10.7554/eLife.16394.001 PMID:27805566

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

NASA Astrophysics Data System (ADS)

Pelowski, Matthew; Markey, Patrick S.; Forster, Michael; Gerger, Gernot; Leder, Helmut

2017-07-01

This paper has a rather audacious purpose: to present a comprehensive theory explaining, and further providing hypotheses for the empirical study of, the multiple ways by which people respond to art. Despite common agreement that interaction with art can be based on a compelling, and occasionally profound, psychological experience, the nature of these interactions is still under debate. We propose a model, The Vienna Integrated Model of Art Perception (VIMAP), with the goal of resolving the multifarious processes that can occur when we perceive and interact with visual art. Specifically, we focus on the need to integrate bottom-up, artwork-derived processes, which have formed the bulk of previous theoretical and empirical assessments, with top-down mechanisms which can describe how individuals adapt or change within their processing experience, and thus how individuals may come to particularly moving, disturbing, transformative, as well as mundane, results. This is achieved by combining several recent lines of theoretical research into a new integrated approach built around three processing checks, which we argue can be used to systematically delineate the possible outcomes in art experience. We also connect our model's processing stages to specific hypotheses for emotional, evaluative, and physiological factors, and address main topics in psychological aesthetics including provocative reactions-chills, awe, thrills, sublime-and difference between ;aesthetic; and ;everyday; emotional response. Finally, we take the needed step of connecting stages to functional regions in the brain, as well as broader core networks that may coincide with the proposed cognitive checks, and which taken together can serve as a basis for future empirical and theoretical art research.

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.

PubMed

Pelowski, Matthew; Markey, Patrick S; Forster, Michael; Gerger, Gernot; Leder, Helmut

2017-07-01

This paper has a rather audacious purpose: to present a comprehensive theory explaining, and further providing hypotheses for the empirical study of, the multiple ways by which people respond to art. Despite common agreement that interaction with art can be based on a compelling, and occasionally profound, psychological experience, the nature of these interactions is still under debate. We propose a model, The Vienna Integrated Model of Art Perception (VIMAP), with the goal of resolving the multifarious processes that can occur when we perceive and interact with visual art. Specifically, we focus on the need to integrate bottom-up, artwork-derived processes, which have formed the bulk of previous theoretical and empirical assessments, with top-down mechanisms which can describe how individuals adapt or change within their processing experience, and thus how individuals may come to particularly moving, disturbing, transformative, as well as mundane, results. This is achieved by combining several recent lines of theoretical research into a new integrated approach built around three processing checks, which we argue can be used to systematically delineate the possible outcomes in art experience. We also connect our model's processing stages to specific hypotheses for emotional, evaluative, and physiological factors, and address main topics in psychological aesthetics including provocative reactions-chills, awe, thrills, sublime-and difference between "aesthetic" and "everyday" emotional response. Finally, we take the needed step of connecting stages to functional regions in the brain, as well as broader core networks that may coincide with the proposed cognitive checks, and which taken together can serve as a basis for future empirical and theoretical art research. Copyright © 2017 Elsevier B.V. All rights reserved.

Neuroscience is awaiting for a breakthrough: an essay bridging the concepts of Descartes, Einstein, Heisenberg, Hebb and Hayek with the explanatory formulations in this special issue.

PubMed

Başar, Erol; Karakaş, Sirel

2006-05-01

The paper presents gedankenmodels which, based on the theories and models in the present special issue, describe the conditions for a breakthrough in brain sciences and neuroscience. The new model is based on contemporary findings which show that the brain and its cognitive processes show super-synchronization. Accordingly, understanding the brain/body-mind complex is possible only when these three are considered as a wholistic entity and not as discrete structures or functions. Such a breakthrough and the related perspectives to the brain/body-mind complex will involve a transition from the mechanistic Cartesian system to a nebulous Cartesian system, one that is basically characterized by parallel computing and is further parallel to quantum mechanics. This integrated outlook on the brain/body-mind, or dynamic functionality, will make the treatment of also the meta-cognitive processes and the greater part of the iceberg, the unconscious, possible. All this will be possible only through the adoption of a multidisciplinary approach that will bring together the knowledge and the technology of the four P's which consist of physics, physiology, psychology and philosophy. The genetic approach to the functional dynamics of the brain/body-mind, where the oscillatory responses were found to be laws of brain activity, is presented in this volume as one of the most recent perspectives of neuroscience.

Brains striving for coherence: Long-term cumulative plot formation in the default mode network.

PubMed

Tylén, K; Christensen, P; Roepstorff, A; Lund, T; Østergaard, S; Donald, M

2015-11-01

Many everyday activities, such as engaging in conversation or listening to a story, require us to sustain attention over a prolonged period of time while integrating and synthesizing complex episodic content into a coherent mental model. Humans are remarkably capable of navigating and keeping track of all the parallel social activities of everyday life even when confronted with interruptions or changes in the environment. However, the underlying cognitive and neurocognitive mechanisms of such long-term integration and profiling of information remain a challenge to neuroscience. While brain activity is generally traceable within the short time frame of working memory (milliseconds to seconds), these integrative processes last for minutes, hours or even days. Here we report two experiments on story comprehension. Experiment I establishes a cognitive dissociation between our comprehension of plot and incidental facts in narratives: when episodic material allows for long-term integration in a coherent plot, we recall fewer factual details. However, when plot formation is challenged, we pay more attention to incidental facts. Experiment II investigates the neural underpinnings of plot formation. Results suggest a central role for the brain's default mode network related to comprehension of coherent narratives while incoherent episodes rather activate the frontoparietal control network. Moreover, an analysis of cortical activity as a function of the cumulative integration of narrative material into a coherent story reveals to linear modulations of right hemisphere posterior temporal and parietal regions. Together these findings point to key neural mechanisms involved in the fundamental human capacity for cumulative plot formation. Copyright © 2015 Elsevier Inc. All rights reserved.

Superior Prognostic Value of Cumulative Intracranial Tumor Volume Relative to Largest Intracranial Tumor Volume for Stereotactic Radiosurgery-Treated Brain Metastasis Patients.

PubMed

Hirshman, Brian R; Wilson, Bayard; Ali, Mir Amaan; Proudfoot, James A; Koiso, Takao; Nagano, Osamu; Carter, Bob S; Serizawa, Toru; Yamamoto, Masaaki; Chen, Clark C

2018-04-01

Two intracranial tumor volume variables have been shown to prognosticate survival of stereotactic-radiosurgery-treated brain metastasis patients: the largest intracranial tumor volume (LITV) and the cumulative intracranial tumor volume (CITV). To determine whether the prognostic value of the Scored Index for Radiosurgery (SIR) model can be improved by replacing one of its components-LITV-with CITV. We compared LITV and CITV in terms of their survival prognostication using a series of multivariable models that included known components of the SIR: age, Karnofsky Performance Score, status of extracranial disease, and the number of brain metastases. Models were compared using established statistical measures, including the net reclassification improvement (NRI > 0) and integrated discrimination improvement (IDI). The analysis was performed in 2 independent cohorts, each consisting of ∼3000 patients. In both cohorts, CITV was shown to be independently predictive of patient survival. Replacement of LITV with CITV in the SIR model improved the model's ability to predict 1-yr survival. In the first cohort, the CITV model showed an NRI > 0 improvement of 0.2574 (95% confidence interval [CI] 0.1890-0.3257) and IDI of 0.0088 (95% CI 0.0057-0.0119) relative to the LITV model. In the second cohort, the CITV model showed a NRI > 0 of 0.2604 (95% CI 0.1796-0.3411) and IDI of 0.0051 (95% CI 0.0029-0.0073) relative to the LITV model. After accounting for covariates within the SIR model, CITV offers superior prognostic value relative to LITV for stereotactic radiosurgery-treated brain metastasis patients.

Image segmentation by EM-based adaptive pulse coupled neural networks in brain magnetic resonance imaging.

PubMed

Fu, J C; Chen, C C; Chai, J W; Wong, S T C; Li, I C

2010-06-01

We propose an automatic hybrid image segmentation model that integrates the statistical expectation maximization (EM) model and the spatial pulse coupled neural network (PCNN) for brain magnetic resonance imaging (MRI) segmentation. In addition, an adaptive mechanism is developed to fine tune the PCNN parameters. The EM model serves two functions: evaluation of the PCNN image segmentation and adaptive adjustment of the PCNN parameters for optimal segmentation. To evaluate the performance of the adaptive EM-PCNN, we use it to segment MR brain image into gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF). The performance of the adaptive EM-PCNN is compared with that of the non-adaptive EM-PCNN, EM, and Bias Corrected Fuzzy C-Means (BCFCM) algorithms. The result is four sets of boundaries for the GM and the brain parenchyma (GM+WM), the two regions of most interest in medical research and clinical applications. Each set of boundaries is compared with the golden standard to evaluate the segmentation performance. The adaptive EM-PCNN significantly outperforms the non-adaptive EM-PCNN, EM, and BCFCM algorithms in gray mater segmentation. In brain parenchyma segmentation, the adaptive EM-PCNN significantly outperforms the BCFCM only. However, the adaptive EM-PCNN is better than the non-adaptive EM-PCNN and EM on average. We conclude that of the three approaches, the adaptive EM-PCNN yields the best results for gray matter and brain parenchyma segmentation. Copyright 2009 Elsevier Ltd. All rights reserved.

Serum extravasation and cytoskeletal alterations following traumatic brain injury in rats. Comparison of lateral fluid percussion and cortical impact models.

PubMed

Hicks, R R; Baldwin, S A; Scheff, S W

1997-01-01

Disruption of the blood-brain barrier (BBB) and neuronal cytoskeletal damage were evaluated in two commonly used rat models of traumatic brain injury. Adult rats received a lateral cortical impact (CI) or lateral fluid percussion (FP) injury of mild or moderate severity or a sham procedure. Six hours after trauma, the brains were removed and analyzed with immunocytochemical techniques for alterations in the serum protein, IgG, and the cytoskeletal protein, microtubule-associated protein 2 (MAP2). Both models induced profound alterations in these proteins in the ipsilateral cortex and hippocampus compared to sham-injured controls. Following an injury of moderate severity, the CI injury resulted in greater IgG extravasation in the cortex and hippocampus than the FP injury. Conversely, after a mild injury, IgG extravasation in the hippocampus was greater for FP than CI. All of the animals in the CI group and most of the FP group showed a loss of MAP2 in the hippocampus. The specific subregions within the cortex and hippocampus that were affected by the injury varied between models, despite having identical impact sites. These data demonstrate that there are both similarities and differences between a CI and FP injury on vascular and neuronal cystoskeletal integrity, which should be considered when utilizing these animal models to study selected features of human head injury.

The Neurobiology of Autism: Theoretical Applications

ERIC Educational Resources Information Center

Schroeder, Jessica H.; Desrocher, Mary; Bebko, James M.; Cappadocia, M. Catherine

2010-01-01

Autism spectrum disorders (ASD) are complex neurological disorders characterized by heterogeneity in skills and impairments. A variety of models have been developed to describe the disorders and a wide range of brain processes have been implicated. This review attempts to integrate some of the consistent neurological findings in the research with…

Cortical Interactions Underlying the Production of Speech Sounds

ERIC Educational Resources Information Center

Guenther, Frank H.

2006-01-01

Speech production involves the integration of auditory, somatosensory, and motor information in the brain. This article describes a model of speech motor control in which a feedforward control system, involving premotor and primary motor cortex and the cerebellum, works in concert with auditory and somatosensory feedback control systems that…

On the organization of the perisylvian cortex: Insights from the electrophysiology of language. Comment on "Towards a Computational Comparative Neuroprimatology: Framing the language-ready brain" by M.A. Arbib

NASA Astrophysics Data System (ADS)

Brouwer, Harm; Crocker, Matthew W.

2016-03-01

The Mirror System Hypothesis (MSH) on the evolution of the language-ready brain draws upon the parallel dorsal-ventral stream architecture for vision [1]. The dorsal ;how; stream provides a mapping of parietally-mediated affordances onto the motor system (supporting preshape), whereas the ventral ;what; stream engages in object recognition and visual scene analysis (supporting pantomime and verbal description). Arbib attempts to integrate this MSH perspective with a recent conceptual dorsal-ventral stream model of auditory language comprehension [5] (henceforth, the B&S model). In the B&S model, the dorsal stream engages in time-dependent combinatorial processing, which subserves syntactic structuring and linkage to action, whereas the ventral stream performs time-independent unification of conceptual schemata. These streams are integrated in the left Inferior Frontal Gyrus (lIFG), which is assumed to subserve cognitive control, and no linguistic processing functions. Arbib criticizes the B&S model on two grounds: (i) the time-independence of the semantic processing in the ventral stream (by arguing that semantic processing is just as time-dependent as syntactic processing), and (ii) the absence of linguistic processing in the lIFG (reconciling syntactic and semantic representations is very much linguistic processing proper). Here, we provide further support for these two points of criticism on the basis of insights from the electrophysiology of language. In the course of our argument, we also sketch the contours of an alternative model that may prove better suited for integration with the MSH.

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

Functional network organization of the human brain

PubMed Central

Power, Jonathan D; Cohen, Alexander L; Nelson, Steven M; Wig, Gagan S; Barnes, Kelly Anne; Church, Jessica A; Vogel, Alecia C; Laumann, Timothy O; Miezin, Fran M; Schlaggar, Bradley L; Petersen, Steven E

2011-01-01

Summary Real-world complex systems may be mathematically modeled as graphs, revealing properties of the system. Here we study graphs of functional brain organization in healthy adults using resting state functional connectivity MRI. We propose two novel brain-wide graphs, one of 264 putative functional areas, the other a modification of voxelwise networks that eliminates potentially artificial short-distance relationships. These graphs contain many subgraphs in good agreement with known functional brain systems. Other subgraphs lack established functional identities; we suggest possible functional characteristics for these subgraphs. Further, graph measures of the areal network indicate that the default mode subgraph shares network properties with sensory and motor subgraphs: it is internally integrated but isolated from other subgraphs, much like a “processing” system. The modified voxelwise graph also reveals spatial motifs in the patterning of systems across the cortex. PMID:22099467

Mosaic evolution and adaptive brain component alteration under domestication seen on the background of evolutionary theory.

PubMed

Rehkämper, Gerd; Frahm, Heiko D; Cnotka, Julia

2008-01-01

Brain sizes and brain component sizes of five domesticated pigeon breeds including homing (racing) pigeons are compared with rock doves (Columba livia) based on an allometric approach to test the influence of domestication on brain and brain component size. Net brain volume, the volumes of cerebellum and telencephalon as a whole are significantly smaller in almost all domestic pigeons. Inside the telencephalon, mesopallium, nidopallium (+ entopallium + arcopallium) and septum are smaller as well. The hippocampus is significantly larger, particularly in homing pigeons. This finding is in contrast to the predictions of the 'regression hypothesis' of brain alteration under domestication. Among the domestic pigeons homing pigeons have significantly larger olfactory bulbs. These data are interpreted as representing a functional adaptation to homing that is based on spatial cognition and sensory integration. We argue that domestication as seen in domestic pigeons is not principally different from evolution in the wild, but represents a heuristic model to understand the evolutionary process in terms of adaptation and optimization. Copyright 2007 S. Karger AG, Basel.

Test-retest reliability of effective connectivity in the face perception network.

PubMed

Frässle, Stefan; Paulus, Frieder Michel; Krach, Sören; Jansen, Andreas

2016-02-01

Computational approaches have great potential for moving neuroscience toward mechanistic models of the functional integration among brain regions. Dynamic causal modeling (DCM) offers a promising framework for inferring the effective connectivity among brain regions and thus unraveling the neural mechanisms of both normal cognitive function and psychiatric disorders. While the benefit of such approaches depends heavily on their reliability, systematic analyses of the within-subject stability are rare. Here, we present a thorough investigation of the test-retest reliability of an fMRI paradigm for DCM analysis dedicated to unraveling intra- and interhemispheric integration among the core regions of the face perception network. First, we examined the reliability of face-specific BOLD activity in 25 healthy volunteers, who performed a face perception paradigm in two separate sessions. We found good to excellent reliability of BOLD activity within the DCM-relevant regions. Second, we assessed the stability of effective connectivity among these regions by analyzing the reliability of Bayesian model selection and model parameter estimation in DCM. Reliability was excellent for the negative free energy and good for model parameter estimation, when restricting the analysis to parameters with substantial effect sizes. Third, even when the experiment was shortened, reliability of BOLD activity and DCM results dropped only slightly as a function of the length of the experiment. This suggests that the face perception paradigm presented here provides reliable estimates for both conventional activation and effective connectivity measures. We conclude this paper with an outlook on potential clinical applications of the paradigm for studying psychiatric disorders. Hum Brain Mapp 37:730-744, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Micro-computed tomography in murine models of cerebral cavernous malformations as a paradigm for brain disease.

PubMed

Girard, Romuald; Zeineddine, Hussein A; Orsbon, Courtney; Tan, Huan; Moore, Thomas; Hobson, Nick; Shenkar, Robert; Lightle, Rhonda; Shi, Changbin; Fam, Maged D; Cao, Ying; Shen, Le; Neander, April I; Rorrer, Autumn; Gallione, Carol; Tang, Alan T; Kahn, Mark L; Marchuk, Douglas A; Luo, Zhe-Xi; Awad, Issam A

2016-09-15

Cerebral cavernous malformations (CCMs) are hemorrhagic brain lesions, where murine models allow major mechanistic discoveries, ushering genetic manipulations and preclinical assessment of therapies. Histology for lesion counting and morphometry is essential yet tedious and time consuming. We herein describe the application and validations of X-ray micro-computed tomography (micro-CT), a non-destructive technique allowing three-dimensional CCM lesion count and volumetric measurements, in transgenic murine brains. We hereby describe a new contrast soaking technique not previously applied to murine models of CCM disease. Volumetric segmentation and image processing paradigm allowed for histologic correlations and quantitative validations not previously reported with the micro-CT technique in brain vascular disease. Twenty-two hyper-dense areas on micro-CT images, identified as CCM lesions, were matched by histology. The inter-rater reliability analysis showed strong consistency in the CCM lesion identification and staging (K=0.89, p<0.0001) between the two techniques. Micro-CT revealed a 29% greater CCM lesion detection efficiency, and 80% improved time efficiency. Serial integrated lesional area by histology showed a strong positive correlation with micro-CT estimated volume (r(2)=0.84, p<0.0001). Micro-CT allows high throughput assessment of lesion count and volume in pre-clinical murine models of CCM. This approach complements histology with improved accuracy and efficiency, and can be applied for lesion burden assessment in other brain diseases. Copyright © 2016 Elsevier B.V. All rights reserved.

Signals that regulate the oncogenic fate of neural stem cells and progenitors

PubMed Central

Swartling, Fredrik J.; Bolin, Sara; Phillips, Joanna J.; Persson, Anders I.

2013-01-01

Brain tumors have frequently been associated with a neural stem cell (NSC) origin and contain stem-like tumor cells, so-called brain tumor stem cells (BTSCs) that share many features with normal NSCs. A stem cell state of BTSCs confers resistance to radiotherapy and treatment with alkylating agents. It is also a hallmark of aggressive brain tumors and is maintained by transcriptional networks that are also active in embryonic stem cells. Advances in reprogramming of somatic cells into induced pluripotent stem (iPS) cells have further identified genes that drive stemness. In this review, we will highlight the possible drivers of stemness in medulloblastoma and glioma, the most frequent types of primary malignant brain cancer in children and adults, respectively. Signals that drive expansion of developmentally defined neural precursor cells are also active in corresponding brain tumors. Transcriptomal subgroups of human medulloblastoma and glioma match features of NSCs but also more restricted progenitors. Lessons from genetically-engineered mouse (GEM) models show that temporally and regionally defined NSCs can give rise to distinct subgroups of medulloblastoma and glioma. We will further discuss how acquisition of stem cell features may drive brain tumorigenesis from a non-NSC origin. Genetic alterations, signaling pathways, and therapy-induced changes in the tumor microenvironment can drive reprogramming networks and induce stemness in brain tumors. Finally, we propose a model where dysregulation of microRNAs (miRNAs) that normally provide barriers against reprogramming plays an integral role in promoting stemness in brain tumors. PMID:23376224

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…

Bayesian switching factor analysis for estimating time-varying functional connectivity in fMRI.

PubMed

Taghia, Jalil; Ryali, Srikanth; Chen, Tianwen; Supekar, Kaustubh; Cai, Weidong; Menon, Vinod

2017-07-15

There is growing interest in understanding the dynamical properties of functional interactions between distributed brain regions. However, robust estimation of temporal dynamics from functional magnetic resonance imaging (fMRI) data remains challenging due to limitations in extant multivariate methods for modeling time-varying functional interactions between multiple brain areas. Here, we develop a Bayesian generative model for fMRI time-series within the framework of hidden Markov models (HMMs). The model is a dynamic variant of the static factor analysis model (Ghahramani and Beal, 2000). We refer to this model as Bayesian switching factor analysis (BSFA) as it integrates factor analysis into a generative HMM in a unified Bayesian framework. In BSFA, brain dynamic functional networks are represented by latent states which are learnt from the data. Crucially, BSFA is a generative model which estimates the temporal evolution of brain states and transition probabilities between states as a function of time. An attractive feature of BSFA is the automatic determination of the number of latent states via Bayesian model selection arising from penalization of excessively complex models. Key features of BSFA are validated using extensive simulations on carefully designed synthetic data. We further validate BSFA using fingerprint analysis of multisession resting-state fMRI data from the Human Connectome Project (HCP). Our results show that modeling temporal dependencies in the generative model of BSFA results in improved fingerprinting of individual participants. Finally, we apply BSFA to elucidate the dynamic functional organization of the salience, central-executive, and default mode networks-three core neurocognitive systems with central role in cognitive and affective information processing (Menon, 2011). Across two HCP sessions, we demonstrate a high level of dynamic interactions between these networks and determine that the salience network has the highest temporal flexibility among the three networks. Our proposed methods provide a novel and powerful generative model for investigating dynamic brain connectivity. Copyright © 2017 Elsevier Inc. All rights reserved.

Heterogeneous blood-tumor barrier permeability determines drug efficacy in experimental brain metastases of breast cancer.

PubMed

Lockman, Paul R; Mittapalli, Rajendar K; Taskar, Kunal S; Rudraraju, Vinay; Gril, Brunilde; Bohn, Kaci A; Adkins, Chris E; Roberts, Amanda; Thorsheim, Helen R; Gaasch, Julie A; Huang, Suyun; Palmieri, Diane; Steeg, Patricia S; Smith, Quentin R

2010-12-01

Brain metastases of breast cancer appear to be increasing in incidence, confer significant morbidity, and threaten to compromise gains made in systemic chemotherapy. The blood-tumor barrier (BTB) is compromised in many brain metastases; however, the extent to which this influences chemotherapeutic delivery and efficacy is unknown. Herein, we answer this question by measuring BTB passive integrity, chemotherapeutic drug uptake, and anticancer efficacy in vivo in two breast cancer models that metastasize preferentially to brain. Experimental brain metastasis drug uptake and BTB permeability were simultaneously measured using novel fluorescent and phosphorescent imaging techniques in immune-compromised mice. Drug-induced apoptosis and vascular characteristics were assessed using immunofluorescent microscopy. Analysis of over 2,000 brain metastases from two models (human 231-BR-Her2 and murine 4T1-BR5) showed partial BTB permeability compromise in greater than 89% of lesions, varying in magnitude within and between metastases. Brain metastasis uptake of ¹⁴C-paclitaxel and ¹⁴C-doxorubicin was generally greater than normal brain but less than 15% of that of other tissues or peripheral metastases, and only reached cytotoxic concentrations in a small subset (∼10%) of the most permeable metastases. Neither drug significantly decreased the experimental brain metastatic ability of 231-BR-Her2 tumor cells. BTB permeability was associated with vascular remodeling and correlated with overexpression of the pericyte protein desmin. This work shows that the BTB remains a significant impediment to standard chemotherapeutic delivery and efficacy in experimental brain metastases of breast cancer. New brain permeable drugs will be needed. Evidence is presented for vascular remodeling in BTB permeability alterations. ©2010 AACR.

Heterogeneous Blood-Tumor Barrier Permeability Determines Drug Efficacy in Experimental Brain Metastases of Breast Cancer

PubMed Central

Lockman, Paul R.; Mittapalli, Rajendar K.; Taskar, Kunal S.; Rudraraju, Vinay; Gril, Brunilde; Bohn, Kaci A.; Adkins, Chris E.; Roberts, Amanda; Thorsheim, Helen R.; Gaasch, Julie A.; Huang, Suyun; Palmieri, Diane; Steeg, Patricia S.; Smith, Quentin R.

2010-01-01

Purpose Brain metastases of breast cancer appear to be increasing in incidence, confer significant morbidity, and threaten to compromise gains made in systemic chemotherapy. The blood-tumor barrier (BTB) is compromised in many brain metastases, however, the extent to which this influences chemotherapeutic delivery and efficacy is unknown. Herein, we answer this question by measuring BTB passive integrity, chemotherapeutic drug uptake, and anticancer efficacy in vivo in two breast cancer models that metastasize preferentially to brain. Experimental Design Experimental brain metastasis drug uptake and BTB permeability were simultaneously measured using novel fluorescent and phosphorescent imaging techniques in immune compromised mice. Drug-induced apoptosis and vascular characteristics were assessed using immunofluorescent microscopy. Results Analysis of >2000 brain metastases from two models (human 231-BR-Her2 and murine 4T1-BR5) demonstrated partial BTB permeability compromise in >89% lesions, varying in magnitude within and between metastases. Brain metastasis uptake of 14C- paclitaxel and 14C- doxorubicin was generally greater than normal brain but <15% of that of other tissues or peripheral metastases, and only reached cytotoxic concentrations in a small subset (~10%) of the most permeable metastases. Neither drug significantly decreased the experimental brain metastatic ability of 231-BR-Her2 tumor cells. BTB permeability was associated with vascular remodeling and correlated with over expression of the pericyte protein, desmin. Conclusions This work demonstrates that the BTB remains a significant impediment to standard chemotherapeutic delivery and efficacy in experimental brain metastases of breast cancer. New brain permeable drugs will be needed. Evidence is presented for vascular remodeling in BTB permeability alterations. PMID:20829328

Integrating EEG and fMRI in epilepsy.

PubMed

Formaggio, Emanuela; Storti, Silvia Francesca; Bertoldo, Alessandra; Manganotti, Paolo; Fiaschi, Antonio; Toffolo, Gianna Maria

2011-02-14

Integrating electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) studies enables to non-invasively investigate human brain function and to find the direct correlation of these two important measures of brain activity. Presurgical evaluation of patients with epilepsy is one of the areas where EEG and fMRI integration has considerable clinical relevance for localizing the brain regions generating interictal epileptiform activity. The conventional analysis of EEG-fMRI data is based on the visual identification of the interictal epileptiform discharges (IEDs) on scalp EEG. The convolution of these EEG events, represented as stick functions, with a model of the fMRI response, i.e. the hemodynamic response function, provides the regressor for general linear model (GLM) analysis of fMRI data. However, the conventional analysis is not automatic and suffers of some subjectivity in IEDs classification. Here, we present an easy-to-use and automatic approach for combined EEG-fMRI analysis able to improve IEDs identification based on Independent Component Analysis and wavelet analysis. EEG signal due to IED is reconstructed and its wavelet power is used as a regressor in GLM. The method was validated on simulated data and then applied on real data set consisting of 2 normal subjects and 5 patients with partial epilepsy. In all continuous EEG-fMRI recording sessions a good quality EEG was obtained allowing the detection of spontaneous IEDs and the analysis of the related BOLD activation. The main clinical finding in EEG-fMRI studies of patients with partial epilepsy is that focal interictal slow-wave activity was invariably associated with increased focal BOLD responses in a spatially related brain area. Our study extends current knowledge on epileptic foci localization and confirms previous reports suggesting that BOLD activation associated with slow activity might have a role in localizing the epileptogenic region even in the absence of clear interictal spikes. Copyright © 2010 Elsevier Inc. All rights reserved.

The Contribution of Network Organization and Integration to the Development of Cognitive Control

PubMed Central

Marek, Scott; Hwang, Kai; Foran, William; Hallquist, Michael N.; Luna, Beatriz

2015-01-01

Abstract Cognitive control, which continues to mature throughout adolescence, is supported by the ability for well-defined organized brain networks to flexibly integrate information. However, the development of intrinsic brain network organization and its relationship to observed improvements in cognitive control are not well understood. In the present study, we used resting state functional magnetic resonance imaging (RS-fMRI), graph theory, the antisaccade task, and rigorous head motion control to characterize and relate developmental changes in network organization, connectivity strength, and integration to inhibitory control development. Subjects were 192 10–26-y-olds who were imaged during 5 min of rest. In contrast to initial studies, our results indicate that network organization is stable throughout adolescence. However, cross-network integration, predominantly of the cingulo-opercular/salience network, increased with age. Importantly, this increased integration of the cingulo-opercular/salience network significantly moderated the robust effect of age on the latency to initiate a correct inhibitory control response. These results provide compelling evidence that the transition to adult-level inhibitory control is dependent upon the refinement and strengthening of integration between specialized networks. Our findings support a novel, two-stage model of neural development, in which networks stabilize prior to adolescence and subsequently increase their integration to support the cross-domain incorporation of information processing critical for mature cognitive control. PMID:26713863

The Contribution of Network Organization and Integration to the Development of Cognitive Control.

PubMed

Marek, Scott; Hwang, Kai; Foran, William; Hallquist, Michael N; Luna, Beatriz

2015-12-01

Cognitive control, which continues to mature throughout adolescence, is supported by the ability for well-defined organized brain networks to flexibly integrate information. However, the development of intrinsic brain network organization and its relationship to observed improvements in cognitive control are not well understood. In the present study, we used resting state functional magnetic resonance imaging (RS-fMRI), graph theory, the antisaccade task, and rigorous head motion control to characterize and relate developmental changes in network organization, connectivity strength, and integration to inhibitory control development. Subjects were 192 10-26-y-olds who were imaged during 5 min of rest. In contrast to initial studies, our results indicate that network organization is stable throughout adolescence. However, cross-network integration, predominantly of the cingulo-opercular/salience network, increased with age. Importantly, this increased integration of the cingulo-opercular/salience network significantly moderated the robust effect of age on the latency to initiate a correct inhibitory control response. These results provide compelling evidence that the transition to adult-level inhibitory control is dependent upon the refinement and strengthening of integration between specialized networks. Our findings support a novel, two-stage model of neural development, in which networks stabilize prior to adolescence and subsequently increase their integration to support the cross-domain incorporation of information processing critical for mature cognitive control.

Exposure to Lipopolysaccharide and/or Unconjugated Bilirubin Impair the Integrity and Function of Brain Microvascular Endothelial Cells

PubMed Central

Cardoso, Filipa L.; Kittel, Ágnes; Veszelka, Szilvia; Palmela, Inês; Tóth, Andrea; Brites, Dora; Deli, Mária A.; Brito, Maria A.

2012-01-01

Background Sepsis and jaundice are common conditions in newborns that can lead to brain damage. Though lipopolysaccharide (LPS) is known to alter the integrity of the blood-brain barrier (BBB), little is known on the effects of unconjugated bilirubin (UCB) and even less on the joint effects of UCB and LPS on brain microvascular endothelial cells (BMEC). Methodology/Principal Findings Monolayers of primary rat BMEC were treated with 1 µg/ml LPS and/or 50 µM UCB, in the presence of 100 µM human serum albumin, for 4 or 24 h. Co-cultures of BMEC with astroglial cells, a more complex BBB model, were used in selected experiments. LPS led to apoptosis and UCB induced both apoptotic and necrotic-like cell death. LPS and UCB led to inhibition of P-glycoprotein and activation of matrix metalloproteinases-2 and -9 in mono-cultures. Transmission electron microscopy evidenced apoptotic bodies, as well as damaged mitochondria and rough endoplasmic reticulum in BMEC by either insult. Shorter cell contacts and increased caveolae-like invaginations were noticeable in LPS-treated cells and loss of intercellular junctions was observed upon treatment with UCB. Both compounds triggered impairment of endothelial permeability and transendothelial electrical resistance both in mono- and co-cultures. The functional changes were confirmed by alterations in immunostaining for junctional proteins β-catenin, ZO-1 and claudin-5. Enlargement of intercellular spaces, and redistribution of junctional proteins were found in BMEC after exposure to LPS and UCB. Conclusions LPS and/or UCB exert direct toxic effects on BMEC, with distinct temporal profiles and mechanisms of action. Therefore, the impairment of brain endothelial integrity upon exposure to these neurotoxins may favor their access to the brain, thus increasing the risk of injury and requiring adequate clinical management of sepsis and jaundice in the neonatal period. PMID:22586454

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.

Prediction of specific damage or infarction from the measurement of tissue impedance following repetitive brain ischaemia in the rat.

PubMed

Klein, H C; Krop-Van Gastel, W; Go, K G; Korf, J

1993-02-01

The development of irreversible brain damage during repetitive periods of hypoxia and normoxia was studied in anaesthetized rats with unilateral occlusion of the carotid artery (modified Levine model). Rats were exposed to 10 min hypoxia and normoxia until severe damage developed. As indices of damage, whole striatal tissue impedance (reflecting cellular water uptake), sodium/potassium contents (due to exchange with blood). Evans Blue staining (blood-brain barrier [BBB] integrity) and silver staining (increased in irreversibly damaged neurons) were used. A substantial decrease in blood pressure was observed during the hypoxic periods possibly producing severe ischaemia. Irreversibly increased impedance, massive changes in silver staining, accumulation of whole tissue Na and loss of K occurred only after a minimum of two periods of hypoxia, but there was no disruption of the BBB. Microscopic examination of tissue sections revealed that cell death was selective with reversible impedance changes, but became massive and non-specific after irreversible increase of the impedance. The development of brain infarcts could, however, not be predicted from measurements of physiological parameters in the blood. We suggest that the development of cerebral infarction during repetitive periods of hypoxia may serve as a model for the development of brain damage in a variety of clinical conditions. Furthermore, the present model allows the screening of potential therapeutic measuring of the prevention and treatment of both infarction and selective cell death.

Numerical analysis of the diffusive mass transport in brain tissues with applications to optical sensors

NASA Astrophysics Data System (ADS)

Neculae, Adrian P.; Otte, Andreas; Curticapean, Dan

2013-03-01

In the brain-cell microenvironment, diffusion plays an important role: apart from delivering glucose and oxygen from the vascular system to brain cells, it also moves informational substances between cells. The brain is an extremely complex structure of interwoven, intercommunicating cells, but recent theoretical and experimental works showed that the classical laws of diffusion, cast in the framework of porous media theory, can deliver an accurate quantitative description of the way molecules are transported through this tissue. The mathematical modeling and the numerical simulations are successfully applied in the investigation of diffusion processes in tissues, replacing the costly laboratory investigations. Nevertheless, modeling must rely on highly accurate information regarding the main parameters (tortuosity, volume fraction) which characterize the tissue, obtained by structural and functional imaging. The usual techniques to measure the diffusion mechanism in brain tissue are the radiotracer method, the real time iontophoretic method and integrative optical imaging using fluorescence microscopy. A promising technique for obtaining the values for characteristic parameters of the transport equation is the direct optical investigation using optical fibers. The analysis of these parameters also reveals how the local geometry of the brain changes with time or under pathological conditions. This paper presents a set of computations concerning the mass transport inside the brain tissue, for different types of cells. By measuring the time evolution of the concentration profile of an injected substance and using suitable fitting procedures, the main parameters characterizing the tissue can be determined. This type of analysis could be an important tool in understanding the functional mechanisms of effective drug delivery in complex structures such as the brain tissue. It also offers possibilities to realize optical imaging methods for in vitro and in vivo measurements using optical fibers. The model also may help in radiotracer biomarker models for the understanding of the mechanism of action of new chemical entities.

Integrating language models into classifiers for BCI communication: a review

NASA Astrophysics Data System (ADS)

Speier, W.; Arnold, C.; Pouratian, N.

2016-06-01

Objective. The present review systematically examines the integration of language models to improve classifier performance in brain-computer interface (BCI) communication systems. Approach. The domain of natural language has been studied extensively in linguistics and has been used in the natural language processing field in applications including information extraction, machine translation, and speech recognition. While these methods have been used for years in traditional augmentative and assistive communication devices, information about the output domain has largely been ignored in BCI communication systems. Over the last few years, BCI communication systems have started to leverage this information through the inclusion of language models. Main results. Although this movement began only recently, studies have already shown the potential of language integration in BCI communication and it has become a growing field in BCI research. BCI communication systems using language models in their classifiers have progressed down several parallel paths, including: word completion; signal classification; integration of process models; dynamic stopping; unsupervised learning; error correction; and evaluation. Significance. Each of these methods have shown significant progress, but have largely been addressed separately. Combining these methods could use the full potential of language model, yielding further performance improvements. This integration should be a priority as the field works to create a BCI system that meets the needs of the amyotrophic lateral sclerosis population.

Integrating language models into classifiers for BCI communication: a review.

PubMed

Speier, W; Arnold, C; Pouratian, N

2016-06-01

The present review systematically examines the integration of language models to improve classifier performance in brain-computer interface (BCI) communication systems. The domain of natural language has been studied extensively in linguistics and has been used in the natural language processing field in applications including information extraction, machine translation, and speech recognition. While these methods have been used for years in traditional augmentative and assistive communication devices, information about the output domain has largely been ignored in BCI communication systems. Over the last few years, BCI communication systems have started to leverage this information through the inclusion of language models. Although this movement began only recently, studies have already shown the potential of language integration in BCI communication and it has become a growing field in BCI research. BCI communication systems using language models in their classifiers have progressed down several parallel paths, including: word completion; signal classification; integration of process models; dynamic stopping; unsupervised learning; error correction; and evaluation. Each of these methods have shown significant progress, but have largely been addressed separately. Combining these methods could use the full potential of language model, yielding further performance improvements. This integration should be a priority as the field works to create a BCI system that meets the needs of the amyotrophic lateral sclerosis population.

Oxytocin receptor mRNA expression in rat brain: implications for behavioral integration and reproductive success.

PubMed

Ostrowski, N L

1998-11-01

The nonapeptide, oxytocin (OT), has been implicated in a wide range of physiological, behavioral and pharmacological effects related to learning and memory, parturition and lactation, maternal and sexual behavior, and the formation of social attachments. Specific G-protein linked membrane bound OT receptors mediate OTs effects. The unavailability of highly selective pharmacological ligands that discriminate the OT receptor from the highly homologous vasopressin receptors (V1a, V1b and V2 subtypes) has made it difficult to confirm specific effects of oxytocin, particularly in brain regions where OT and multiple AVP receptor subtypes may be coexpressed. Here, data on the oxytocin receptor (OTR) messenger ribonucleic acid (mRNA) localization in brain are presented in the context of a model that proposes a reproductive state-dependent role for steroid-hormone restructuring of neural circuits, and a role for oxytocin in the integration of neural transmission in pathways subserving: (1) steroid-sensitive reproductive behaviors; (2) learning; and (3) reinforcement. It is hypothesized that social attachments emerge as a consequence of a conditioned association between OT-related activity in these pathways and the eliciting stimulus.

Relationship between time-resolved and non-time-resolved Beer-Lambert law in turbid media.

PubMed

Nomura, Y; Hazeki, O; Tamura, M

1997-06-01

The time-resolved Beer-Lambert law proposed for oxygen monitoring using pulsed light was extended to the non-time-resolved case in a scattered medium such as living tissues with continuous illumination. The time-resolved Beer-Lambert law was valid for the phantom model and living tissues in the visible and near-infrared regions. The absolute concentration and oxygen saturation of haemoglobin in rat brain and thigh muscle could be determined. The temporal profile of rat brain was reproduced by Monte Carlo simulation. When the temporal profiles of rat brain under different oxygenation states were integrated with time, the absorbance difference was linearly related to changes in the absorption coefficient. When the simulated profiles were integrated, there was a linear relationship within the absorption coefficient which was predicted for fractional inspiratory oxygen concentration from 10 to 100% and, in the case beyond the range of the absorption coefficient, the deviation from linearity was slight. We concluded that an optical pathlength which is independent of changes in the absorption coefficient is a good approximation for near-infrared oxygen monitoring.

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.

State-dependencies of learning across brain scales

PubMed Central

Ritter, Petra; Born, Jan; Brecht, Michael; Dinse, Hubert R.; Heinemann, Uwe; Pleger, Burkhard; Schmitz, Dietmar; Schreiber, Susanne; Villringer, Arno; Kempter, Richard

2015-01-01

Learning is a complex brain function operating on different time scales, from milliseconds to years, which induces enduring changes in brain dynamics. The brain also undergoes continuous “spontaneous” shifts in states, which, amongst others, are characterized by rhythmic activity of various frequencies. Besides the most obvious distinct modes of waking and sleep, wake-associated brain states comprise modulations of vigilance and attention. Recent findings show that certain brain states, particularly during sleep, are essential for learning and memory consolidation. Oscillatory activity plays a crucial role on several spatial scales, for example in plasticity at a synaptic level or in communication across brain areas. However, the underlying mechanisms and computational rules linking brain states and rhythms to learning, though relevant for our understanding of brain function and therapeutic approaches in brain disease, have not yet been elucidated. Here we review known mechanisms of how brain states mediate and modulate learning by their characteristic rhythmic signatures. To understand the critical interplay between brain states, brain rhythms, and learning processes, a wide range of experimental and theoretical work in animal models and human subjects from the single synapse to the large-scale cortical level needs to be integrated. By discussing results from experiments and theoretical approaches, we illuminate new avenues for utilizing neuronal learning mechanisms in developing tools and therapies, e.g., for stroke patients and to devise memory enhancement strategies for the elderly. PMID:25767445

[Sensory integration: hierarchy and synchronization].

PubMed

Kriukov, V I

2005-01-01

This is the first in the series of mini-reviews devoted to the basic problems and most important effects of attention in terms of neuronal modeling. We believe that the absence of the unified view on wealth of new date on attention is the main obstacle for further understanding of higher nervous activity. The present work deals with the main ground problem of reconciling two competing architectures designed to integrate the sensory information in the brain. The other mini-reviews will be concerned with the remaining five or six problems of attention, all of them to be ultimately resolved uniformly in the framework of small modification of dominant model of attention and memory.

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

Declarative Consciousness for Reconstruction

NASA Astrophysics Data System (ADS)

Seymour, Leslie G.

2013-12-01

Existing information technology tools are harnessed and integrated to provide digital specification of human consciousness of individual persons. An incremental compilation technology is proposed as a transformation of LifeLog derived persona specifications into a Canonical representation of the neocortex architecture of the human brain. The primary purpose is to gain an understanding of the semantical allocation of the neocortex capacity. Novel neocortex content allocation simulators with browsers are proposed to experiment with various approaches of relieving the brain from overload conditions. An IT model of the neocortex is maintained, which is then updated each time new stimuli are received from the LifeLog data stream; new information is gained from brain signal measurements; and new functional dependencies are discovered between live persona consumed/produced signals

Integrative strategies to identify candidate genes in rodent models of human alcoholism.

PubMed

Treadwell, Julie A

2006-01-01

The search for genes underlying alcohol-related behaviours in rodent models of human alcoholism has been ongoing for many years with only limited success. Recently, new strategies that integrate several of the traditional approaches have provided new insights into the molecular mechanisms underlying ethanol's actions in the brain. We have used alcohol-preferring C57BL/6J (B6) and alcohol-avoiding DBA/2J (D2) genetic strains of mice in an integrative strategy combining high-throughput gene expression screening, genetic segregation analysis, and mapping to previously published quantitative trait loci to uncover candidate genes for the ethanol-preference phenotype. In our study, 2 genes, retinaldehyde binding protein 1 (Rlbp1) and syntaxin 12 (Stx12), were found to be strong candidates for ethanol preference. Such experimental approaches have the power and the potential to greatly speed up the laborious process of identifying candidate genes for the animal models of human alcoholism.

Oscillatory neural representations in the sensory thalamus predict neuropathic pain relief by deep brain stimulation.

PubMed

Huang, Yongzhi; Green, Alexander L; Hyam, Jonathan; Fitzgerald, James; Aziz, Tipu Z; Wang, Shouyan

2018-01-01

Understanding the function of sensory thalamic neural activity is essential for developing and improving interventions for neuropathic pain. However, there is a lack of investigation of the relationship between sensory thalamic oscillations and pain relief in patients with neuropathic pain. This study aims to identify the oscillatory neural characteristics correlated with pain relief induced by deep brain stimulation (DBS), and develop a quantitative model to predict pain relief by integrating characteristic measures of the neural oscillations. Measures of sensory thalamic local field potentials (LFPs) in thirteen patients with neuropathic pain were screened in three dimensional feature space according to the rhythm, balancing, and coupling neural behaviours, and correlated with pain relief. An integrated approach based on principal component analysis (PCA) and multiple regression analysis is proposed to integrate the multiple measures and provide a predictive model. This study reveals distinct thalamic rhythms of theta, alpha, high beta and high gamma oscillations correlating with pain relief. The balancing and coupling measures between these neural oscillations were also significantly correlated with pain relief. The study enriches the series research on the function of thalamic neural oscillations in neuropathic pain and relief, and provides a quantitative approach for predicting pain relief by DBS using thalamic neural oscillations. Copyright © 2017 Elsevier Inc. All rights reserved.

Some Behavioral and Neurobiological Constraints on Theories of Audiovisual Speech Integration: A Review and Suggestions for New Directions

PubMed Central

Altieri, Nicholas; Pisoni, David B.; Townsend, James T.

2012-01-01

Summerfield (1987) proposed several accounts of audiovisual speech perception, a field of research that has burgeoned in recent years. The proposed accounts included the integration of discrete phonetic features, vectors describing the values of independent acoustical and optical parameters, the filter function of the vocal tract, and articulatory dynamics of the vocal tract. The latter two accounts assume that the representations of audiovisual speech perception are based on abstract gestures, while the former two assume that the representations consist of symbolic or featural information obtained from visual and auditory modalities. Recent converging evidence from several different disciplines reveals that the general framework of Summerfield’s feature-based theories should be expanded. An updated framework building upon the feature-based theories is presented. We propose a processing model arguing that auditory and visual brain circuits provide facilitatory information when the inputs are correctly timed, and that auditory and visual speech representations do not necessarily undergo translation into a common code during information processing. Future research on multisensory processing in speech perception should investigate the connections between auditory and visual brain regions, and utilize dynamic modeling tools to further understand the timing and information processing mechanisms involved in audiovisual speech integration. PMID:21968081

Some behavioral and neurobiological constraints on theories of audiovisual speech integration: a review and suggestions for new directions.

PubMed

Altieri, Nicholas; Pisoni, David B; Townsend, James T

2011-01-01

Summerfield (1987) proposed several accounts of audiovisual speech perception, a field of research that has burgeoned in recent years. The proposed accounts included the integration of discrete phonetic features, vectors describing the values of independent acoustical and optical parameters, the filter function of the vocal tract, and articulatory dynamics of the vocal tract. The latter two accounts assume that the representations of audiovisual speech perception are based on abstract gestures, while the former two assume that the representations consist of symbolic or featural information obtained from visual and auditory modalities. Recent converging evidence from several different disciplines reveals that the general framework of Summerfield's feature-based theories should be expanded. An updated framework building upon the feature-based theories is presented. We propose a processing model arguing that auditory and visual brain circuits provide facilitatory information when the inputs are correctly timed, and that auditory and visual speech representations do not necessarily undergo translation into a common code during information processing. Future research on multisensory processing in speech perception should investigate the connections between auditory and visual brain regions, and utilize dynamic modeling tools to further understand the timing and information processing mechanisms involved in audiovisual speech integration.

Cortical and subcortical atrophy in Alzheimer disease: parallel atrophy of thalamus and hippocampus.

PubMed

Štěpán-Buksakowska, Irena; Szabó, Nikoletta; Hořínek, Daniel; Tóth, Eszter; Hort, Jakub; Warner, Joshua; Charvát, František; Vécsei, László; Roček, Miloslav; Kincses, Zsigmond T

2014-01-01

Brain atrophy is a key imaging hallmark of Alzheimer disease (AD). In this study, we carried out an integrative evaluation of AD-related atrophy. Twelve patients with AD and 13 healthy controls were enrolled. We conducted a cross-sectional analysis of total brain tissue volumes with SIENAX. Localized gray matter atrophy was identified with optimized voxel-wise morphometry (FSL-VBM), and subcortical atrophy was evaluated by active shape model implemented in FMRIB's Integrated Registration Segmentation Toolkit. SIENAX analysis demonstrated total brain atrophy in AD patients; voxel-based morphometry analysis showed atrophy in the bilateral mediotemporal regions and in the posterior brain regions. In addition, regarding the diminished volumes of thalami and hippocampi in AD patients, subsequent vertex analysis of the segmented structures indicated shrinkage of the bilateral anterior thalami and the left medial hippocampus. Interestingly, the volume of the thalami and hippocampi were highly correlated with the volume of the thalami and amygdalae on both sides in AD patients, but not in healthy controls. This complex structural information proved useful in the detailed interpretation of AD-related neurodegenerative process, as the multilevel approach showed both global and local atrophy on cortical and subcortical levels. Most importantly, our results raise the possibility that subcortical structure atrophy is not independent in AD patients.

An alkaline phosphatase transport mechanism in the pathogenesis of Alzheimer's disease and neurodegeneration.

PubMed

Pike, Adrianne F; Kramer, Nynke I; Blaauboer, Bas J; Seinen, Willem; Brands, Ruud

2015-01-25

Systemic inflammation is associated with loss of blood-brain barrier integrity and neuroinflammation that lead to the exacerbation of neurodegenerative diseases. It is also associated specifically with the characteristic amyloid-β and tau pathologies of Alzheimer's disease. We have previously proposed an immunosurveillance mechanism for epithelial barriers involving negative feedback-regulated alkaline phosphatase transcytosis as an acute phase anti-inflammatory response that hangs in the balance between the resolution and the progression of inflammation. We now extend this model to endothelial barriers, particularly the blood-brain barrier, and present a literature-supported mechanistic explanation for Alzheimer's disease pathology with this system at its foundation. In this mechanism, a switch in the role of alkaline phosphatase from its baseline duties to a stopgap anti-inflammatory function results in the loss of alkaline phosphatase from cell membranes into circulation, thereby decreasing blood-brain barrier integrity and functionality. This occurs with impairment of both amyloid-β efflux and tau dephosphorylating activity in the brain as alkaline phosphatase is replenished at the barrier by receptor-mediated transport. We suggest systemic alkaline phosphatase administration as a potential therapy for the resolution of inflammation and the prevention of Alzheimer's disease pathology as well as that of other inflammation-related neurodegenerative diseases. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

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.

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

Conditional N-WASP knockout in mouse brain implicates actin cytoskeleton regulation in hydrocephalus pathology.

PubMed

Jain, Neeraj; Lim, Lee Wei; Tan, Wei Ting; George, Bhawana; Makeyev, Eugene; Thanabalu, Thirumaran

2014-04-01

Cerebrospinal fluid (CSF) is produced by the choroid plexus and moved by multi-ciliated ependymal cells through the ventricular system of the vertebrate brain. Defects in the ependymal layer functionality are a common cause of hydrocephalus. N-WASP (Neural-Wiskott Aldrich Syndrome Protein) is a brain-enriched regulator of actin cytoskeleton and N-WASP knockout caused embryonic lethality in mice with neural tube and cardiac abnormalities. To shed light on the role of N-WASP in mouse brain development, we generated N-WASP conditional knockout mouse model N-WASP(fl/fl); Nestin-Cre (NKO-Nes). NKO-Nes mice were born with Mendelian ratios but exhibited reduced growth characteristics compared to their littermates containing functional N-WASP alleles. Importantly, all NKO-Nes mice developed cranial deformities due to excessive CSF accumulation and did not survive past weaning. Coronal brain sections of these animals revealed dilated lateral ventricles, defects in ciliogenesis, loss of ependymal layer integrity, reduced thickness of cerebral cortex and aqueductal stenosis. Immunostaining for N-cadherin suggests that ependymal integrity in NKO-Nes mice is lost as compared to normal morphology in the wild-type controls. Moreover, scanning electron microscopy and immunofluorescence analyses of coronal brain sections with anti-acetylated tubulin antibodies revealed the absence of cilia in ventricular walls of NKO-Nes mice indicative of ciliogenesis defects. N-WASP deficiency does not lead to altered expression of N-WASP regulatory proteins, Fyn and Cdc42, which have been previously implicated in hydrocephalus pathology. Taken together, our results suggest that N-WASP plays a critical role in normal brain development and implicate actin cytoskeleton regulation as a vulnerable axis frequently deregulated in hydrocephalus. Copyright © 2014 Elsevier Inc. All rights reserved.

On quantum models of the human mind.

PubMed

Wang, Hongbin; Sun, Yanlong

2014-01-01

Recent years have witnessed rapidly increasing interests in developing quantum theoretical models of human cognition. Quantum mechanisms have been taken seriously to describe how the mind reasons and decides. Papers in this special issue report the newest results in the field. Here we discuss why the two levels of commitment, treating the human brain as a quantum computer and merely adopting abstract quantum probability principles to model human cognition, should be integrated. We speculate that quantum cognition models gain greater modeling power due to a richer representation scheme. Copyright © 2013 Cognitive Science Society, Inc.

A new method of regional CBF measurement using one point arterial sampling based on microsphere model with I-123 IMP SPECT

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

Odano, I.; Takahashi, N.; Ohkubo, M.

1994-05-01

We developed a new method for quantitative measurement of rCBF with Iodine-123-IMP based on the microsphere model, which was accurate, more simple and relatively non-invasive than the continuous withdrawal method. IMP is assumed to behave as a chemical microsphere in the brain. Then regional CBF is measured by the continuous withdrawal of arterial blood and the microsphere model as follows: F=Cb(t)/integral Ca(t)*N, where F is rCBF (ml/100g/min), Cb(t) is the brain activity concentration. The integral Ca(t) is the total activity of arterial whole-blood withdrawn, and N is the fraction of the integral Ca(t) that is true tracer activity. We analyzedmore » 14 patients. A dose of 222 MBq of IMP was injected i.v. over 1 min, and withdrawal of the arterial blood was performed from 0 to 5 min (integral Ca(t)), after which arterial blood samples (one point Ca(t)) were obtained at 5, 6, 7, 8, 9, 10 min, respectively. Then the integral Ca(t) was mathematically inferred from the value of one point Ca(t). When we examined the correlation between integral Ca(t)*N and one point Ca(t), and % error of one point Ca(t) compared with integral Ca(t)*N, the minimum of the % error was 8.1% and the maximum of the correlation coefficient was 0.943, the both values of which were obtained at 6 min. We concluded that 6 min was the best time to take arterial blood sample by one point sampling method for assuming the integral Ca(t)*N. IMP SPECT studies were performed with a ring-type SPECT scanner, Compared with rCBF measured by Xe-133 method, a significant correlation was observed in this method (r=0.773). One point Ca(t) method is very easy and quickly for measurement of rCBF without inserting catheters and without arterial blood treatment with octanol.« less

Intact blood-brain barrier transport of small molecular drugs in animal models of amyloid beta and alpha-synuclein pathology.

PubMed

Gustafsson, Sofia; Lindström, Veronica; Ingelsson, Martin; Hammarlund-Udenaes, Margareta; Syvänen, Stina

2018-01-01

Pathophysiological impairment of the neurovascular unit, including the integrity and dynamics of the blood-brain barrier (BBB), has been denoted both a cause and consequence of neurodegenerative diseases. Pathological impact on BBB drug delivery has also been debated. The aim of the present study was to investigate BBB drug transport, by determining the unbound brain-to-plasma concentration ratio (K p,uu,brain ), in aged AβPP-transgenic mice, α-synuclein transgenic mice, and wild type mice. Mice were dosed with a cassette of five compounds, including digoxin, levofloxacin (1 mg/kg, s.c.), paliperidone, oxycodone, and diazepam (0.25 mg/kg, s.c.). Brain and blood were collected at 0.5, 1, or 3 h after dosage. Drug concentrations were measured using LC-MS/MS. The total brain-to-plasma concentration ratio was calculated and equilibrium dialysis was used to determine the fraction of unbound drug in brain and plasma for all compounds. Together, these three measures were used to determine the K p,uu,brain value. Despite Aβ or α-synuclein pathology in the current animal models, no difference was observed in the extent of drug transport across the BBB compared to wild type animals for any of the compounds investigated. Hence, the present study shows that the concept of a leaking barrier within neurodegenerative conditions has to be interpreted with caution when estimating drug transport into the brain. The capability of the highly dynamic BBB to regulate brain drug exposure still seems to be intact despite the presence of pathology. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

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.

On viewer motivation, unit of analysis, and the VIMAP. 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)

Tinio, Pablo P. L.

2017-07-01

The Vienna Integrated Model of Art Perception (VIMAP; [5]) is the most comprehensive model of the art experience today. The model incorporates bottom-up and top-down cognitive processes and accounts for different outcomes of the art experience, such as aesthetic evaluations, emotions, and physiological and neurological responses to art. In their presentation of the model, Pelowski et al. also present hypotheses that are amenable to empirical testing. These features make the VIMAP an ambitious model that attempts to explain how meaningful, complex, and profound aspects of the art experience come about, which is a significant extension of previous models of the art experience (e.g., [1-3,10]), and which gives the VIMAP good explanatory power.

Modelling information flow along the human connectome using maximum flow.

PubMed

Lyoo, Youngwook; Kim, Jieun E; Yoon, Sujung

2018-01-01

The human connectome is a complex network that transmits information between interlinked brain regions. Using graph theory, previously well-known network measures of integration between brain regions have been constructed under the key assumption that information flows strictly along the shortest paths possible between two nodes. However, it is now apparent that information does flow through non-shortest paths in many real-world networks such as cellular networks, social networks, and the internet. In the current hypothesis, we present a novel framework using the maximum flow to quantify information flow along all possible paths within the brain, so as to implement an analogy to network traffic. We hypothesize that the connection strengths of brain networks represent a limit on the amount of information that can flow through the connections per unit of time. This allows us to compute the maximum amount of information flow between two brain regions along all possible paths. Using this novel framework of maximum flow, previous network topological measures are expanded to account for information flow through non-shortest paths. The most important advantage of the current approach using maximum flow is that it can integrate the weighted connectivity data in a way that better reflects the real information flow of the brain network. The current framework and its concept regarding maximum flow provides insight on how network structure shapes information flow in contrast to graph theory, and suggests future applications such as investigating structural and functional connectomes at a neuronal level. Copyright © 2017 Elsevier Ltd. All rights reserved.

Hand in glove: brain and skull in development and dysmorphogenesis

PubMed Central

Flaherty, Kevin

2013-01-01

The brain originates relatively early in development from differentiated ectoderm that forms a hollow tube and takes on an exceedingly complex shape with development. The skull is made up of individual bony elements that form from neural crest- and mesoderm-derived mesenchyme that unite to provide support and protection for soft tissues and spaces of the head. The meninges provide a protective and permeable membrane between brain and skull. Across evolutionary and developmental time, dynamic changes in brain and skull shape track one another so that their integration is evidenced in two structures that fit soundly regardless of changes in biomechanical and physiologic functions. Evidence for this tight correspondence is also seen in diseases of the craniofacial complex that are often classified as diseases of the skull (e.g., craniosynostosis) or diseases of the brain (e.g., holoprosencephaly) even when both tissues are affected. Our review suggests a model that links brain and skull morphogenesis through coordinated integration of signaling pathways (e.g., FGF, TGFβ, Wnt) via processes that are not currently understood, perhaps involving the meninges. Differences in the earliest signaling of biological structure establish divergent designs that will be enhanced during morphogenesis. Signaling systems that pattern the developing brain are also active in patterning required for growth and assembly of the skull and some members of these signaling families have been indicated as causal for craniofacial diseases. Because cells of early brain and skull are sensitive to similar signaling families, variation in the strength or timing of signals or shifts in patterning boundaries that affect one system (neural or skull) could also affect the other system and appropriate co-adjustments in development would be made. Interactions of these signaling systems and of the tissues that they pattern are fundamental to the consistent but labile functional and structural association of brain and skull conserved over evolutionary time obvious in the study of development and disease. PMID:23525521

Examination of Blood-Brain Barrier (BBB) Integrity In A Mouse Brain Tumor Model

PubMed Central

On, Ngoc; Mitchell, Ryan; Savant, Sanjot D.; Bachmeier, Corbin. J.; Hatch, Grant M.; Miller, Donald W.

2013-01-01

The present study evaluates, both functionally and biochemically, brain tumor-induced alterations in brain capillary endothelial cells. Brain tumors were induced in Balb/c mice via intracranial injection of Lewis Lung carcinoma (3LL) cells into the right hemisphere of the mouse brain using stereotaxic apparatus. Blood-brain barrier (BBB) permeability was assessed at various stages of tumor development, using both radiolabeled tracer permeability and magnetic resonance imaging (MRI) with gadolinium diethylene-triamine-pentaacetate contrast enhancement (Gad-DTPA). The expression of the drug efflux transporter, P-glycoprotein (P-gp), in the BBB at various stages of tumor development was also evaluated by Western blot and immunohistochemistry. Median mouse survival following tumor cell injection was 17 days. The permeability of the BBB to 3H-mannitol was similar in both brain hemispheres at 7 and 10 days post-injection. By day 15, there was a 2-fold increase in 3H-mannitol permeability in the tumor bearing hemispheres compared to the non-tumor hemispheres. Examination of BBB permeability with Gad-DTPA contrast enhanced MRI indicated cerebral vascular permeability changes were confined to the tumor area. The permeability increase observed at the later stages of tumor development correlated with an increase in cerebral vascular volume suggesting angiogenesis within the tumor bearing hemisphere. Furthermore, the Gad-DPTA enhancement observed within the tumor area was significantly less than Gad-DPTA enhancement within the circumventricular organs not protected by the BBB. Expression of P-gp in both the tumor bearing and non-tumor bearing portions of the brain appeared similar at all time points examined. These studies suggest that although BBB integrity is altered within the tumor site at later stages of development, the BBB is still functional and limiting in terms of solute and drug permeability in and around the tumor. PMID:23184143

"Neuro-semeiotics" and "free-energy minimization" suggest a unified perspective for integrative brain actions: focus on receptor heteromers and Roamer type of volume transmission.

PubMed

Agnati, Luigi F; Guidolin, Diego; Marcoli, Manuela; Genedani, Susanna; Borroto-Escuela, Dasiel; Maura, Guido; Fuxe, Kjell

2014-01-01

Two far-reaching theoretical approaches, namely "Neuro-semeiotics" (NS) and "Free-energy Minimization" (FEM), have been recently proposed as frames within which to put forward heuristic hypotheses on integrative brain actions. In the present paper these two theoretical approaches are briefly discussed in the perspective of a recent model of brain architecture and information handling based on what we suggest calling Jacob's tinkering principle, whereby "to create is to recombine!". The NS and FEM theoretical approaches will be discussed from the perspective both of the Roamer-Type Volume Transmission (especially exosome-mediated) of intercellular communication and of the impact of receptor oligomers and Receptor-Receptor Interactions (RRIs) on signal recognition/decoding processes. In particular, the Bio-semeiotics concept of "adaptor" will be used to analyze RRIs as an important feature of NS. Furthermore, the concept of phenotypic plasticity of cells will be introduced in view of the demonstration of the possible transfer of receptors (i.e., adaptors) into a computational network via exosomes (see also Appendix). Thus, Jacob's tinkering principle will be proposed as a theoretical basis for some learning processes both at the network level (Turing-like type of machine) and at the molecular level as a consequence of both the plastic changes in the adaptors caused by the allosteric interactions in the receptor oligomers and the intercellular transfer of receptors. Finally, on the basis of NS and FEM theories, a unified perspective for integrative brain actions will be proposed.

Harnessing the potential of biomaterials for brain repair after stroke

NASA Astrophysics Data System (ADS)

Tuladhar, Anup; Payne, Samantha L.; Shoichet, Molly S.

2018-03-01

Stroke is a devastating disease for which no clinical treatment exists to regenerate lost tissue. Strategies for brain repair in animal models of stroke include the delivery of drug or cell-based therapeutics; however, the complex anatomy and functional organization of the brain presents many challenges. Biomaterials may alleviate some of these challenges by providing a scaffold, localizing the therapy to the site of action, and/or modulating cues to brain cells. Here, the challenges associated with delivery of therapeutics to the brain and the biomaterial strategies used to overcome these challenges are described. For example, innovative hydrogel delivery systems have been designed to provide sustained trophic factor delivery for endogenous repair and to support transplanted cell survival and integration. Novel treatments, such as electrical stimulation of transplanted cells and the delivery of factors for the direct reprogramming of astrocytes into neurons, may be further enhanced by biomaterial delivery systems. Ultimately, improved clinical translation will be achieved by combining clinically relevant therapies with biomaterials strategies.

Patterns of craniofacial integration in extant Homo, Pan, and Gorilla.

PubMed

Polanski, Joshua M; Franciscus, Robert G

2006-09-01

Brain size increased greatly during Pleistocene human evolution, while overall facial and dentognathic size decreased markedly. This mosaic pattern is due to either selective forces that acted uniquely on each functional unit in a modularized, developmentally uncoupled craniofacial complex, or alternatively, selection that acted primarily on one unit, with the other responding passively as part of a coevolved set of ontogenetically and evolutionarily integrated structures. Using conditional independence modeling on homologous linear measurements of the height, breadth, and depth of the cranium in Pan (n = 95), Gorilla (n = 102), and recent Homo (n = 120), we reject the null hypothesis of equal levels of overall cranial integration. While all three groups share the pattern of greater neurocranial integration with distinct separation between the face and neurocranium (modularization), family differences do exist. The apes are more integrated in their entire crania, but display a particularly strong pattern of integration within the facial complex related to prognathism. Modern humans display virtually no facial integration, a pattern which is likely related to their markedly decreased facial projection. Modern humans also differ from their great ape counterparts in being more integrated within the breadth dimension of the cranial vault, likely tied to the increase in brain size and eventual globularity seen in human evolution. That the modern human integration pattern differs from the ancestral African great ape pattern along the inverse neurocranial-facial trend seen in human evolution indicates that this shift in the pattern of integration is evolutionarily significant, and may help to clarify aspects of the current debate over defining modern humans. 2006 Wiley-Liss, Inc.

Recognition Memory: A Review of the Critical Findings and an Integrated Theory for Relating Them

ERIC Educational Resources Information Center

Malmberg, Kenneth J.

2008-01-01

The development of formal models has aided theoretical progress in recognition memory research. Here, I review the findings that are critical for testing them, including behavioral and brain imaging results of single-item recognition, plurality discrimination, and associative recognition experiments under a variety of testing conditions. I also…

The Functional Neuroanatomy of Prelexical Processing in Speech Perception

ERIC Educational Resources Information Center

Scott, Sophie K.; Wise, Richard J. S.

2004-01-01

In this paper we attempt to relate the prelexical processing of speech, with particular emphasis on functional neuroimaging studies, to the study of auditory perceptual systems by disciplines in the speech and hearing sciences. The elaboration of the sound-to-meaning pathways in the human brain enables their integration into models of the human…

Processes of Discourse Integration: Evidence from Event-Related Brain Potentials

ERIC Educational Resources Information Center

Ferretti, Todd R.; Singer, Murray; Harwood, Jenna

2013-01-01

We used ERP methodology to investigate how readers validate discourse concepts and update situation models when those concepts followed factive (e.g., knew) and nonfactive (e.g., "guessed") verbs, and also when they were true, false, or indeterminate with reference to previous discourse. Following factive verbs, early (P2) and later brain…

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

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.

How humans integrate the prospects of pain and reward during choice

PubMed Central

Talmi, Deborah; Dayan, Peter; Kiebel, Stefan J.; Frith, Chris D.; Dolan, Raymond J.

2010-01-01

The maxim “no pain, no gain” summarises scenarios where an action leading to reward also entails a cost. Although we know a substantial amount about how the brain represents pain and reward separately, we know little about how they are integrated during goal directed behaviour. Two theoretical models might account for the integration of reward and pain. An additive model specifies that the disutility of costs is summed linearly with the utility of benefits, while an interactive model suggests that cost and benefit utilities interact so that the sensitivity to benefits is attenuated as costs become increasingly aversive. Using a novel task that required integration of physical pain and monetary reward, we examined the mechanism underlying cost-benefit integration in humans. We provide evidence in support of an interactive model in behavioural choice. Using functional neuroimaging we identify a neural signature for this interaction such that when the consequences of actions embody a mixture of reward and pain, there is an attenuation of a predictive reward-signal in both ventral anterior cingulate cortex and ventral striatum. We conclude that these regions subserve integration of action costs and benefits in humans, a finding that suggests a cross-species similarity in neural substrates that implement this function and illuminates mechanisms that underlie altered decision making under aversive conditions. PMID:19923294

Oligodendroglial Alterations and the Role of Microglia in White Matter Injury: Relevance to Schizophrenia

PubMed Central

Chew, Li-Jin; Fusar-Poli, Paolo; Schmitz, Thomas

2015-01-01

Schizophrenia is a chronic and debilitating mental illness characterized by a broad range of abnormal behaviors, including delusions and hallucinations, impaired cognitive function, as well as mood disturbances and social withdrawal. Due to the heterogeneous nature of the disease, the causes of schizophrenia are very complex; its etiology is believed to involve multiple brain regions and the connections between them, and includes alterations in both gray and white matter regions. The onset of symptoms varies with age and severity, and there is some debate over a degenerative or developmental etiology. Longitudinal magnetic resonance imaging studies have detected progressive gray matter loss in the first years of disease, suggesting neurodegeneration; but there is also increasing recognition of a temporal association between clinical complications at birth and disease onset that supports a neurodevelopmental origin. Presently, neuronal abnormalities in schizophrenia are better understood than alterations in myelin-producing cells of the brain, the oligodendrocytes, which are the predominant constituents of white matter structures. Proper white matter development and its structural integrity critically impacts brain connectivity, which affects sensorimotor coordination and cognitive ability. Evidence of defective white matter growth and compromised white matter integrity has been found in individuals at high risk of psychosis, and decreased numbers of mature oligodendrocytes are detected in schizophrenia patients. Inflammatory markers, including proinflammatory cytokines and chemokines, are also associated with psychosis. A relationship between risk of psychosis, white matter defects and prenatal inflammation is being established. Animal models of perinatal brain injury are successful in producing white matter damage in the brain, typified by hypomyelination and/or dysmyelination, impaired motor coordination and prepulse inhibition of the acoustic startle reflex, recapitulating structural and functional characteristics observed in schizophrenia. In addition, elevated expression of inflammation-related genes in brain tissue and increased production of cytokines by blood cells from patients with schizophrenia indicate immunological dysfunction and abnormal inflammatory responses, which are also important underlying features in experimental models. Microglia, resident immune defenders of the central nervous system, play important roles in the development and protection of neural cells, but can contribute to injury under pathological conditions. This article discusses oligodendroglial changes in schizophrenia and focuses on microglial activity in the context of the disease, in neonatal brain injury and in various experimental models of white matter damage. These include disorders associated with premature birth, and animal models of perinatal bacterial and viral infection, oxygen deprivation (hypoxia) and excess (hyperoxia), and elevated systemic proinflammatory cytokine levels. We briefly review the effects of treatment with antipsychotic and anti-inflammatory agents in models of perinatal brain injury, and comment on the therapeutic potential of these strategies. By understanding the neurobiological basis of oligodendroglial abnormalities in schizophrenia, it is hoped that patients will benefit from the availability of targeted and more efficacious treatment options. PMID:23446060

Neuroimaging Feature Terminology: A Controlled Terminology for the Annotation of Brain Imaging Features.

PubMed

Iyappan, Anandhi; Younesi, Erfan; Redolfi, Alberto; Vrooman, Henri; Khanna, Shashank; Frisoni, Giovanni B; Hofmann-Apitius, Martin

2017-01-01

Ontologies and terminologies are used for interoperability of knowledge and data in a standard manner among interdisciplinary research groups. Existing imaging ontologies capture general aspects of the imaging domain as a whole such as methodological concepts or calibrations of imaging instruments. However, none of the existing ontologies covers the diagnostic features measured by imaging technologies in the context of neurodegenerative diseases. Therefore, the Neuro-Imaging Feature Terminology (NIFT) was developed to organize the knowledge domain of measured brain features in association with neurodegenerative diseases by imaging technologies. The purpose is to identify quantitative imaging biomarkers that can be extracted from multi-modal brain imaging data. This terminology attempts to cover measured features and parameters in brain scans relevant to disease progression. In this paper, we demonstrate the systematic retrieval of measured indices from literature and how the extracted knowledge can be further used for disease modeling that integrates neuroimaging features with molecular processes.

The subtle body: an interoceptive map of central nervous system function and meditative mind-brain-body integration.

PubMed

Loizzo, Joseph J

2016-06-01

Meditation research has begun to clarify the brain effects and mechanisms of contemplative practices while generating a range of typologies and explanatory models to guide further study. This comparative review explores a neglected area relevant to current research: the validity of a traditional central nervous system (CNS) model that coevolved with the practices most studied today and that provides the first comprehensive neural-based typology and mechanistic framework of contemplative practices. The subtle body model, popularly known as the chakra system from Indian yoga, was and is used as a map of CNS function in traditional Indian and Tibetan medicine, neuropsychiatry, and neuropsychology. The study presented here, based on the Nalanda tradition, shows that the subtle body model can be cross-referenced with modern CNS maps and challenges modern brain maps with its embodied network model of CNS function. It also challenges meditation research by: (1) presenting a more rigorous, neural-based typology of contemplative practices; (2) offering a more refined and complete network model of the mechanisms of contemplative practices; and (3) serving as an embodied, interoceptive neurofeedback aid that is more user friendly and complete than current teaching aids for clinical and practical applications of contemplative practice. © 2016 New York Academy of Sciences.

Dynamic information processing states revealed through neurocognitive models of object semantics

PubMed Central

Clarke, Alex

2015-01-01

Recognising objects relies on highly dynamic, interactive brain networks to process multiple aspects of object information. To fully understand how different forms of information about objects are represented and processed in the brain requires a neurocognitive account of visual object recognition that combines a detailed cognitive model of semantic knowledge with a neurobiological model of visual object processing. Here we ask how specific cognitive factors are instantiated in our mental processes and how they dynamically evolve over time. We suggest that coarse semantic information, based on generic shared semantic knowledge, is rapidly extracted from visual inputs and is sufficient to drive rapid category decisions. Subsequent recurrent neural activity between the anterior temporal lobe and posterior fusiform supports the formation of object-specific semantic representations – a conjunctive process primarily driven by the perirhinal cortex. These object-specific representations require the integration of shared and distinguishing object properties and support the unique recognition of objects. We conclude that a valuable way of understanding the cognitive activity of the brain is though testing the relationship between specific cognitive measures and dynamic neural activity. This kind of approach allows us to move towards uncovering the information processing states of the brain and how they evolve over time. PMID:25745632

A putative model of overeating and obesity based on brain-derived neurotrophic factor: direct and indirect effects.

PubMed

Ooi, Cara L; Kennedy, James L; Levitan, Robert D

2012-08-01

Increased food intake is a major contributor to the obesity epidemic in all age groups. Elucidating brain systems that drive overeating and that might serve as targets for novel prevention and treatment interventions is thus a high priority for obesity research. The authors consider 2 major pathways by which decreased activity of brain-derived neurotrophic factor (BDNF) may confer vulnerability to overeating and weight gain in an obesogenic environment. The first "direct" pathway focuses on the specific role of BDNF as a mediator of food intake control at brain areas rich in BDNF receptors, including the hypothalamus and hindbrain. It is proposed that low BDNF activity limited to this direct pathway may best explain overeating and obesity outside the context of major neuropsychiatric disturbance. A second "indirect" pathway considers the broad neurotrophic effects of BDNF on key monoamine systems that mediate mood dysregulation, impulsivity, and executive dysfunction as well as feeding behavior per se. Disruption in this pathway may best explain overeating and obesity in the context of various neuropsychiatric disturbances including mood disorders, attention-deficit disorder, and/or binge eating disorders. An integrative model that considers these potential roles of BDNF in promoting obesity is presented. The implications of this model for the early prevention and treatment of obesity are also considered.

Gut-brain actions underlying comorbid anxiety and depression associated with inflammatory bowel disease.

PubMed

Abautret-Daly, Áine; Dempsey, Elaine; Parra-Blanco, Adolfo; Medina, Carlos; Harkin, Andrew

2017-03-08

Introduction Inflammatory bowel disease (IBD) is a chronic relapsing and remitting disorder characterised by inflammation of the gastrointestinal tract. There is a growing consensus that IBD is associated with anxiety- and depression-related symptoms. Psychological symptoms appear to be more prevalent during active disease states with no difference in prevalence between Crohn's disease and ulcerative colitis. Behavioural disturbances including anxiety- and depression-like symptoms have also been observed in animal models of IBD. The likely mechanisms underlying the association are discussed with particular reference to communication between the gut and brain. The close bidirectional relationship known as the gut-brain axis includes neural, hormonal and immune communication links. Evidence is provided for a number of interacting factors including activation of the inflammatory response system in the brain, the hypothalamic-pituitary-adrenal axis, and brain areas implicated in altered behaviours, changes in blood brain barrier integrity, and an emerging role for gut microbiota and response to probiotics in IBD. Discussion The impact of psychological stress in models of IBD remains somewhat conflicted, however, it is weighted in favour of stress or early stressful life events as risk factors in the development of IBD, stress-induced exacerbation of inflammation and relapse. It is recommended that patients with IBD be screened for psychological disturbance and treated accordingly as intervention can improve quality of life and may reduce relapse rates.

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.

In silico cancer modeling: is it ready for primetime?

PubMed Central

Deisboeck, Thomas S; Zhang, Le; Yoon, Jeongah; Costa, Jose

2011-01-01

SUMMARY At the dawn of the era of personalized, systems-driven medicine, computational or in silico modeling and the simulation of disease processes is becoming increasingly important for hypothesis generation and data integration in both experiment and clinics alike. Arguably, this is nowhere more visible than in oncology. To illustrate the field’s vast potential as well as its current limitations we briefly review selected works on modeling malignant brain tumors. Implications for clinical practice, including trial design and outcome prediction are also discussed. PMID:18852721

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.

Association between resting-state brain network topological organization and creative ability: Evidence from a multiple linear regression model.

PubMed

Jiao, Bingqing; Zhang, Delong; Liang, Aiying; Liang, Bishan; Wang, Zengjian; Li, Junchao; Cai, Yuxuan; Gao, Mengxia; Gao, Zhenni; Chang, Song; Huang, Ruiwang; Liu, Ming

2017-10-01

Previous studies have indicated a tight linkage between resting-state functional connectivity of the human brain and creative ability. This study aimed to further investigate the association between the topological organization of resting-state brain networks and creativity. Therefore, we acquired resting-state fMRI data from 22 high-creativity participants and 22 low-creativity participants (as determined by their Torrance Tests of Creative Thinking scores). We then constructed functional brain networks for each participant and assessed group differences in network topological properties before exploring the relationships between respective network topological properties and creative ability. We identified an optimized organization of intrinsic brain networks in both groups. However, compared with low-creativity participants, high-creativity participants exhibited increased global efficiency and substantially decreased path length, suggesting increased efficiency of information transmission across brain networks in creative individuals. Using a multiple linear regression model, we further demonstrated that regional functional integration properties (i.e., the betweenness centrality and global efficiency) of brain networks, particularly the default mode network (DMN) and sensorimotor network (SMN), significantly predicted the individual differences in creative ability. Furthermore, the associations between network regional properties and creative performance were creativity-level dependent, where the difference in the resource control component may be important in explaining individual difference in creative performance. These findings provide novel insights into the neural substrate of creativity and may facilitate objective identification of creative ability. Copyright © 2017 Elsevier B.V. All rights reserved.

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 science and illness beliefs: an unexpected explanation of the healing power of therapeutic conversations and the family interventions that matter.

PubMed

Wright, Lorraine M

2015-05-01

Paradigm families and paradigm practice moments have shown me that therapeutic conversations between nurses and families can profoundly and positively change illness beliefs in family members and nurses and contribute to healing from serious illness. The integration of brain science into nursing practice offers further understanding of the importance of illness beliefs and the role they may play in helping individual and family healing. Brain science offers explanations that connect how certain family nursing interventions that soften suffering and challenge constraining illness beliefs may result in changes in brain structure and functioning. New illness beliefs may result in new neural pathways in the brain, and therefore, possibilities for a new way of being in relationship with illness and in relationship with others can also develop. Newly acquired practice skills and interventions that have emerged from an understanding of brain science plus the reemphasis of other interventions utilized in the Illness Beliefs Model are offered to enhance our care of families suffering with illness. © The Author(s) 2015.

Small-world human brain networks: Perspectives and challenges.

PubMed

Liao, Xuhong; Vasilakos, Athanasios V; He, Yong

2017-06-01

Modelling the human brain as a complex network has provided a powerful mathematical framework to characterize the structural and functional architectures of the brain. In the past decade, the combination of non-invasive neuroimaging techniques and graph theoretical approaches enable us to map human structural and functional connectivity patterns (i.e., connectome) at the macroscopic level. One of the most influential findings is that human brain networks exhibit prominent small-world organization. Such a network architecture in the human brain facilitates efficient information segregation and integration at low wiring and energy costs, which presumably results from natural selection under the pressure of a cost-efficiency balance. Moreover, the small-world organization undergoes continuous changes during normal development and ageing and exhibits dramatic alterations in neurological and psychiatric disorders. In this review, we survey recent advances regarding the small-world architecture in human brain networks and highlight the potential implications and applications in multidisciplinary fields, including cognitive neuroscience, medicine and engineering. Finally, we highlight several challenging issues and areas for future research in this rapidly growing field. Copyright © 2017 Elsevier Ltd. All rights reserved.

Large-scale network integration in the human brain tracks temporal fluctuations in memory encoding performance.

PubMed

Keerativittayayut, Ruedeerat; Aoki, Ryuta; Sarabi, Mitra Taghizadeh; Jimura, Koji; Nakahara, Kiyoshi

2018-06-18

Although activation/deactivation of specific brain regions have been shown to be predictive of successful memory encoding, the relationship between time-varying large-scale brain networks and fluctuations of memory encoding performance remains unclear. Here we investigated time-varying functional connectivity patterns across the human brain in periods of 30-40 s, which have recently been implicated in various cognitive functions. During functional magnetic resonance imaging, participants performed a memory encoding task, and their performance was assessed with a subsequent surprise memory test. A graph analysis of functional connectivity patterns revealed that increased integration of the subcortical, default-mode, salience, and visual subnetworks with other subnetworks is a hallmark of successful memory encoding. Moreover, multivariate analysis using the graph metrics of integration reliably classified the brain network states into the period of high (vs. low) memory encoding performance. Our findings suggest that a diverse set of brain systems dynamically interact to support successful memory encoding. © 2018, Keerativittayayut et al.

Voxelwise multivariate analysis of multimodality magnetic resonance imaging

PubMed Central

Naylor, Melissa G.; Cardenas, Valerie A.; Tosun, Duygu; Schuff, Norbert; Weiner, Michael; Schwartzman, Armin

2015-01-01

Most brain magnetic resonance imaging (MRI) studies concentrate on a single MRI contrast or modality, frequently structural MRI. By performing an integrated analysis of several modalities, such as structural, perfusion-weighted, and diffusion-weighted MRI, new insights may be attained to better understand the underlying processes of brain diseases. We compare two voxelwise approaches: (1) fitting multiple univariate models, one for each outcome and then adjusting for multiple comparisons among the outcomes and (2) fitting a multivariate model. In both cases, adjustment for multiple comparisons is performed over all voxels jointly to account for the search over the brain. The multivariate model is able to account for the multiple comparisons over outcomes without assuming independence because the covariance structure between modalities is estimated. Simulations show that the multivariate approach is more powerful when the outcomes are correlated and, even when the outcomes are independent, the multivariate approach is just as powerful or more powerful when at least two outcomes are dependent on predictors in the model. However, multiple univariate regressions with Bonferroni correction remains a desirable alternative in some circumstances. To illustrate the power of each approach, we analyze a case control study of Alzheimer's disease, in which data from three MRI modalities are available. PMID:23408378

[Sleep-wake cycle and memory consolidation].

PubMed

Baratti, Carlos M; Boccia, Mariano M; Blake, Mariano G; Acosta, Gabriela B

2007-01-01

Although several hypothesis and theories have been advanced as explanations for the functions of sleep, a unified theory of sleep function remains elusive. Sleep has been implicated in the plastic cerebral changes that underlie learning and memory, in particular those related to memory consolidation of recently acquired new information. Despite steady accumulations of positive findings over the last ten years, the precise role of sleep in memory and brain plasticity is unproven at all. This situation might be solved by more integrated approaches that combine behavioral and neurophysiological measurements in well described in vivo models of neuronal activity and brain plasticity.

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

Food-induced brain responses and eating behaviour.

PubMed

Smeets, Paul A M; Charbonnier, Lisette; van Meer, Floor; van der Laan, Laura N; Spetter, Maartje S

2012-11-01

The brain governs food intake behaviour by integrating many different internal and external state and trait-related signals. Understanding how the decisions to start and to stop eating are made is crucial to our understanding of (maladaptive patterns of) eating behaviour. Here, we aim to (1) review the current state of the field of 'nutritional neuroscience' with a focus on the interplay between food-induced brain responses and eating behaviour and (2) highlight research needs and techniques that could be used to address these. The brain responses associated with sensory stimulation (sight, olfaction and taste), gastric distension, gut hormone administration and food consumption are the subject of increasing investigation. Nevertheless, only few studies have examined relations between brain responses and eating behaviour. However, the neural circuits underlying eating behaviour are to a large extent generic, including reward, self-control, learning and decision-making circuitry. These limbic and prefrontal circuits interact with the hypothalamus, a key homeostatic area. Target areas for further elucidating the regulation of food intake are: (eating) habit and food preference formation and modification, the neural correlates of self-control, nutrient sensing and dietary learning, and the regulation of body adiposity. Moreover, to foster significant progress, data from multiple studies need to be integrated. This requires standardisation of (neuroimaging) measures, data sharing and the application and development of existing advanced analysis and modelling techniques to nutritional neuroscience data. In the next 20 years, nutritional neuroscience will have to prove its potential for providing insights that can be used to tackle detrimental eating behaviour.

[The mind-brain problem (II): about consciousness].

PubMed

Tirapu-Ustarroz, J; Goni-Saez, F

2016-08-16

Consciousness is the result of a series of neurobiological processes in the brain and is, in turn, a feature of the level of its complexity. In fact, being conscious and being aware place us before what Chalmers called the 'soft problem' and the 'hard problem' of consciousness. The first refers to aspects such as wakefulness, attention or knowledge, while the second is concerned with such complex concepts as self-awareness, 'neural self' or social cognition. In this sense it can be said that the concept of consciousness as a unitary thing poses problems of approaching a highly complex reality. We outline the main models that have addressed the topic of consciousness from a neuroscientific perspective. On the one hand, there are the conscious experience models of Crick, Edelman and Tononi, and Llinas, and, on the other, the models and neuronal bases of self-consciousness by authors such as Damasio (core and extended consciousness), Tulving (autonoetic and noetic consciousness and chronesthesia), the problem of qualia (Dennett, Popper, Ramachandran) and the cognit model (Fuster). All the stimuli we receive from the outside world and from our own internal world are converted and processed by the brain so as to integrate them, and from there they become part of our identity. The perception of a dog and being able to recognise it as such or the understanding of our own consciousness are the result of the functioning of brain, neuronal and synaptic structures. The more complex processes of consciousness, such as self-awareness or empathy, are probably emergent brain processes.

Support vector machine learning-based fMRI data group analysis.

PubMed

Wang, Ze; Childress, Anna R; Wang, Jiongjiong; Detre, John A

2007-07-15

To explore the multivariate nature of fMRI data and to consider the inter-subject brain response discrepancies, a multivariate and brain response model-free method is fundamentally required. Two such methods are presented in this paper by integrating a machine learning algorithm, the support vector machine (SVM), and the random effect model. Without any brain response modeling, SVM was used to extract a whole brain spatial discriminance map (SDM), representing the brain response difference between the contrasted experimental conditions. Population inference was then obtained through the random effect analysis (RFX) or permutation testing (PMU) on the individual subjects' SDMs. Applied to arterial spin labeling (ASL) perfusion fMRI data, SDM RFX yielded lower false-positive rates in the null hypothesis test and higher detection sensitivity for synthetic activations with varying cluster size and activation strengths, compared to the univariate general linear model (GLM)-based RFX. For a sensory-motor ASL fMRI study, both SDM RFX and SDM PMU yielded similar activation patterns to GLM RFX and GLM PMU, respectively, but with higher t values and cluster extensions at the same significance level. Capitalizing on the absence of temporal noise correlation in ASL data, this study also incorporated PMU in the individual-level GLM and SVM analyses accompanied by group-level analysis through RFX or group-level PMU. Providing inferences on the probability of being activated or deactivated at each voxel, these individual-level PMU-based group analysis methods can be used to threshold the analysis results of GLM RFX, SDM RFX or SDM PMU.

Brain microvascular endothelial-astrocyte cell responses following Japanese encephalitis virus infection in an in vitro human blood-brain barrier model.

PubMed

Patabendige, Adjanie; Michael, Benedict D; Craig, Alister G; Solomon, Tom

2018-06-01

Japanese encephalitis virus (JEV) remains a leading cause of encephalitis, globally, which continues to grow in importance despite the availability of vaccines. Viral entry into the brain can occur via the blood-brain barrier (BBB), and inflammation at the BBB is a common final pathway in many brain infections. However, the role of the BBB during JEV infection and the contribution of the endothelial and astrocytic cell inflammation in facilitating virus entry into the brain are incompletely understood. We established a BBB model using human brain endothelial cells (HBECs) and human astrocytes. HBECs are polarised, and therefore the model was inoculated by JEV from the apical side to simulate the in vivo situation. The effects of JEV on the BBB permeability and release of inflammatory mediators from both apical and basolateral sides, representing the blood and the brain side respectively were investigated. JEV infected HBECs with limited active virus production, before crossing the BBB and infecting astrocytes. Control of JEV production by HBECs was associated with a significant increase in permeability, and with elevation of many host mediators, including cytokines, chemokines, cellular adhesion molecules, and matrix metalloproteases. When compared to the controls, significantly higher amounts of mediators were released from the apical side as opposed to the basolateral side. The increased release of mediators over time also correlated with increased BBB permeability. Treatment with dexamethasone led to a significant reduction in the release of interleukin 6 (IL6), C-C motif chemokine ligand 5 (CCL5) and C-X-C motif chemokine ligand 10 (CXCL10) from the apical side with a reduction in BBB disruption and no change in JEV production. The results are consistent with the hypothesis that JEV infection of the BBB triggers the production of a range of host mediators from both endothelial cells and astrocytes, which control JEV production but disrupt BBB integrity thus allowing virus entry into the brain. Dexamethasone treatment controlled the host response and limited BBB disruption in the model without increasing JEV production, supporting a re-investigation of its use therapeutically. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

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.

Hierarchical Brain Networks Active in Approach and Avoidance Goal Pursuit

PubMed Central

Spielberg, Jeffrey M.; Heller, Wendy; Miller, Gregory A.

2013-01-01

Effective approach/avoidance goal pursuit is critical for attaining long-term health and well-being. Research on the neural correlates of key goal-pursuit processes (e.g., motivation) has long been of interest, with lateralization in prefrontal cortex being a particularly fruitful target of investigation. However, this literature has often been limited by a lack of spatial specificity and has not delineated the precise aspects of approach/avoidance motivation involved. Additionally, the relationships among brain regions (i.e., network connectivity) vital to goal-pursuit remain largely unexplored. Specificity in location, process, and network relationship is vital for moving beyond gross characterizations of function and identifying the precise cortical mechanisms involved in motivation. The present paper integrates research using more spatially specific methodologies (e.g., functional magnetic resonance imaging) with the rich psychological literature on approach/avoidance to propose an integrative network model that takes advantage of the strengths of each of these literatures. PMID:23785328

Hierarchical brain networks active in approach and avoidance goal pursuit.

PubMed

Spielberg, Jeffrey M; Heller, Wendy; Miller, Gregory A

2013-01-01

Effective approach/avoidance goal pursuit is critical for attaining long-term health and well-being. Research on the neural correlates of key goal-pursuit processes (e.g., motivation) has long been of interest, with lateralization in prefrontal cortex being a particularly fruitful target of investigation. However, this literature has often been limited by a lack of spatial specificity and has not delineated the precise aspects of approach/avoidance motivation involved. Additionally, the relationships among brain regions (i.e., network connectivity) vital to goal-pursuit remain largely unexplored. Specificity in location, process, and network relationship is vital for moving beyond gross characterizations of function and identifying the precise cortical mechanisms involved in motivation. The present paper integrates research using more spatially specific methodologies (e.g., functional magnetic resonance imaging) with the rich psychological literature on approach/avoidance to propose an integrative network model that takes advantage of the strengths of each of these literatures.

Magnetoencephalography in ellipsoidal geometry

NASA Astrophysics Data System (ADS)

Dassios, George; Kariotou, Fotini

2003-01-01

An exact analytic solution for the forward problem in the theory of biomagnetics of the human brain is known only for the (1D) case of a sphere and the (2D) case of a spheroid, where the excitation field is due to an electric dipole within the corresponding homogeneous conductor. In the present work the corresponding problem for the more realistic ellipsoidal brain model is solved and the leading quadrupole approximation for the exterior magnetic field is obtained in a form that exhibits the anisotropic character of the ellipsoidal geometry. The results are obtained in a straightforward manner through the evaluation of the interior electric potential and a subsequent calculation of the surface integral over the ellipsoid, using Lamé functions and ellipsoidal harmonics. The basic formulas are expressed in terms of the standard elliptic integrals that enter the expressions for the exterior Lamé functions. The laborious task of reducing the results to the spherical geometry is also included.

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

Machine learning approaches for integrating clinical and imaging features in late-life depression classification and response prediction.

PubMed

Patel, Meenal J; Andreescu, Carmen; Price, Julie C; Edelman, Kathryn L; Reynolds, Charles F; Aizenstein, Howard J

2015-10-01

Currently, depression diagnosis relies primarily on behavioral symptoms and signs, and treatment is guided by trial and error instead of evaluating associated underlying brain characteristics. Unlike past studies, we attempted to estimate accurate prediction models for late-life depression diagnosis and treatment response using multiple machine learning methods with inputs of multi-modal imaging and non-imaging whole brain and network-based features. Late-life depression patients (medicated post-recruitment) (n = 33) and older non-depressed individuals (n = 35) were recruited. Their demographics and cognitive ability scores were recorded, and brain characteristics were acquired using multi-modal magnetic resonance imaging pretreatment. Linear and nonlinear learning methods were tested for estimating accurate prediction models. A learning method called alternating decision trees estimated the most accurate prediction models for late-life depression diagnosis (87.27% accuracy) and treatment response (89.47% accuracy). The diagnosis model included measures of age, Mini-mental state examination score, and structural imaging (e.g. whole brain atrophy and global white mater hyperintensity burden). The treatment response model included measures of structural and functional connectivity. Combinations of multi-modal imaging and/or non-imaging measures may help better predict late-life depression diagnosis and treatment response. As a preliminary observation, we speculate that the results may also suggest that different underlying brain characteristics defined by multi-modal imaging measures-rather than region-based differences-are associated with depression versus depression recovery because to our knowledge this is the first depression study to accurately predict both using the same approach. These findings may help better understand late-life depression and identify preliminary steps toward personalized late-life depression treatment. Copyright © 2015 John Wiley & Sons, Ltd.

Representational Similarity Analysis – Connecting the Branches of Systems Neuroscience

PubMed Central

Kriegeskorte, Nikolaus; Mur, Marieke; Bandettini, Peter

2008-01-01

A fundamental challenge for systems neuroscience is to quantitatively relate its three major branches of research: brain-activity measurement, behavioral measurement, and computational modeling. Using measured brain-activity patterns to evaluate computational network models is complicated by the need to define the correspondency between the units of the model and the channels of the brain-activity data, e.g., single-cell recordings or voxels from functional magnetic resonance imaging (fMRI). Similar correspondency problems complicate relating activity patterns between different modalities of brain-activity measurement (e.g., fMRI and invasive or scalp electrophysiology), and between subjects and species. In order to bridge these divides, we suggest abstracting from the activity patterns themselves and computing representational dissimilarity matrices (RDMs), which characterize the information carried by a given representation in a brain or model. Building on a rich psychological and mathematical literature on similarity analysis, we propose a new experimental and data-analytical framework called representational similarity analysis (RSA), in which multi-channel measures of neural activity are quantitatively related to each other and to computational theory and behavior by comparing RDMs. We demonstrate RSA by relating representations of visual objects as measured with fMRI in early visual cortex and the fusiform face area to computational models spanning a wide range of complexities. The RDMs are simultaneously related via second-level application of multidimensional scaling and tested using randomization and bootstrap techniques. We discuss the broad potential of RSA, including novel approaches to experimental design, and argue that these ideas, which have deep roots in psychology and neuroscience, will allow the integrated quantitative analysis of data from all three branches, thus contributing to a more unified systems neuroscience. PMID:19104670

Beauty and sublime. 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)

Perlovsky, Leonid

2017-07-01

The VIMAP model presented in this review [1] is an interesting and detailed model of neural mechanisms of aesthetic perception. In this Comment I address one deficiency of this model: it does not address in details the fundamental notions of the VIMAP, beauty and sublime. In this regard VIMAP is similar to other publications on aesthetics.

Protective effects of angiopoietin-like 4 on the blood-brain barrier in acute ischemic stroke treated with thrombolysis in mice.

PubMed

Zhang, Bin; Xu, Xiaofeng; Chu, Xiuli; Yu, Xiaoyang; Zhao, Yuwu

2017-04-03

Given the risk of blood-brain barrier damage (BBB) caused by ischemic and tissue plasminogen activator thrombolysis, the preservation of vascular integrity is important. Angiopoietin-like 4 (ANGPTL4), a protein secreted in hypoxia, is involved in the regulation of vascular permeability. We hypothesized that Angptl4 might exert a protective effect in thrombolysis through stabilizing blood-brain barrier and inhibit hyper-permeability. We investigated the role of Angptl4 in stroke using a transient focal cerebral ischemia mouse model. The treated mice were administered Angptl4 1h after the ischemic event upon reperfusion. Our results showed that Angptl4 combined with thrombolysis greatly reduced the infarct volume and consequent neurological deficit. Western blot analyses and gelatin zymography revealed that Angptl4 protected the integrity of the endothelium damaged by thrombolysis. Angptl4 inhibited the up-regulation of vascular endothelial growth factor (VEGF) in the vascular endothelium after stroke, which was suppressed by counteracting VEGFR signaling and diminishing downstream Src signaling, and led to the increased stability of junctions and improved endothelial cell barrier integrity. These findings demonstrated that Angptl4 protects the permeability of the BBB damaged by ischemic and thrombolysis. Suggested that Angptl4 might be a promising target molecule in therapies for vasoprotection after thrombolysis treatment. Copyright © 2017 Elsevier B.V. All rights reserved.

Genetic evidence for role of integration of fast and slow neurotransmission in schizophrenia.

PubMed

Devor, A; Andreassen, O A; Wang, Y; Mäki-Marttunen, T; Smeland, O B; Fan, C-C; Schork, A J; Holland, D; Thompson, W K; Witoelar, A; Chen, C-H; Desikan, R S; McEvoy, L K; Djurovic, S; Greengard, P; Svenningsson, P; Einevoll, G T; Dale, A M

2017-06-01

The most recent genome-wide association studies (GWAS) of schizophrenia (SCZ) identified hundreds of risk variants potentially implicated in the disease. Further, novel statistical methodology designed for polygenic architecture revealed more potential risk variants. This can provide a link between individual genetic factors and the mechanistic underpinnings of SCZ. Intriguingly, a large number of genes coding for ionotropic and metabotropic receptors for various neurotransmitters-glutamate, γ-aminobutyric acid (GABA), dopamine, serotonin, acetylcholine and opioids-and numerous ion channels were associated with SCZ. Here, we review these findings from the standpoint of classical neurobiological knowledge of neuronal synaptic transmission and regulation of electrical excitability. We show that a substantial proportion of the identified genes are involved in intracellular cascades known to integrate 'slow' (G-protein-coupled receptors) and 'fast' (ionotropic receptors) neurotransmission converging on the protein DARPP-32. Inspection of the Human Brain Transcriptome Project database confirms that that these genes are indeed expressed in the brain, with the expression profile following specific developmental trajectories, underscoring their relevance to brain organization and function. These findings extend the existing pathophysiology hypothesis by suggesting a unifying role of dysregulation in neuronal excitability and synaptic integration in SCZ. This emergent model supports the concept of SCZ as an 'associative' disorder-a breakdown in the communication across different slow and fast neurotransmitter systems through intracellular signaling pathways-and may unify a number of currently competing hypotheses of SCZ pathophysiology.

Brain network segregation and integration during an epoch-related working memory fMRI experiment.

PubMed

Fransson, Peter; Schiffler, Björn C; Thompson, William Hedley

2018-05-17

The characterization of brain subnetwork segregation and integration has previously focused on changes that are detectable at the level of entire sessions or epochs of imaging data. In this study, we applied time-varying functional connectivity analysis together with temporal network theory to calculate point-by-point estimates in subnetwork segregation and integration during an epoch-based (2-back, 0-back, baseline) working memory fMRI experiment as well as during resting-state. This approach allowed us to follow task-related changes in subnetwork segregation and integration at a high temporal resolution. At a global level, the cognitively more taxing 2-back epochs elicited an overall stronger response of integration between subnetworks compared to the 0-back epochs. Moreover, the visual, sensorimotor and fronto-parietal subnetworks displayed characteristic and distinct temporal profiles of segregation and integration during the 0- and 2-back epochs. During the interspersed epochs of baseline, several subnetworks, including the visual, fronto-parietal, cingulo-opercular and dorsal attention subnetworks showed pronounced increases in segregation. Using a drift diffusion model we show that the response time for the 2-back trials are correlated with integration for the fronto-parietal subnetwork and correlated with segregation for the visual subnetwork. Our results elucidate the fast-evolving events with regard to subnetwork integration and segregation that occur in an epoch-related task fMRI experiment. Our findings suggest that minute changes in subnetwork integration are of importance for task performance. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

APPROACHING THE BIOLOGY OF HUMAN PARENTAL ATTACHMENT: BRAIN IMAGING, OXYTOCIN AND COORDINATED ASSESSMENTS OF MOTHERS AND FATHERS

PubMed Central

Swain, JE; Kim, P; Spicer, J; Ho, SS; Dayton, CJ; Elmadih, A; Abel, KM

2014-01-01

Brain networks that govern parental response to infant signals have been studied with imaging techniques over the last 15 years. The complex interaction of thoughts and behaviors required for sensitive parenting of offspring enable formation of each individual’s first social bonds and critically shape infants’ behavior. This review concentrates on magnetic resonance imaging experiments which directly examine the brain systems involved in parental responses to infant cues. First, we introduce themes in the literature on parental brain circuits studied to date. Next, we present a thorough chronological review of state-of-the-art fMRI studies that probe the parental brain with a range of baby audio and visual stimuli. We also highlight the putative role of oxytocin and effects of psychopathology, as well as the most recent work on the paternal brain. Taken together, a new model emerges in which we propose that cortico-limbic networks interact to support parental brain responses to infants for arousal/salience/motivation/reward, reflexive/instrumental caring, emotion response/regulation and integrative/complex cognitive processing. Maternal sensitivity and the quality of caregiving behavior are likely determined by the responsiveness of these circuits toward long-term influence of early-life experiences on offspring. The function of these circuits is modifiable by current and early-life experiences, hormonal and other factors. Known deviation from the range of normal function in these systems is particularly associated with (maternal) mental illnesses – commonly, depression and anxiety, but also schizophrenia and bipolar disorder. Finally, we discuss the limits and extent to which brain imaging may broaden our understanding of the parental brain, and consider a current model and future directions that may have profound implications for intervention long term outcomes in families across risk and resilience profiles. PMID:24637261

Gpr124 is essential for blood-brain barrier integrity in central nervous system disease.

PubMed

Chang, Junlei; Mancuso, Michael R; Maier, Carolina; Liang, Xibin; Yuki, Kanako; Yang, Lu; Kwong, Jeffrey W; Wang, Jing; Rao, Varsha; Vallon, Mario; Kosinski, Cynthia; Zhang, J J Haijing; Mah, Amanda T; Xu, Lijun; Li, Le; Gholamin, Sharareh; Reyes, Teresa F; Li, Rui; Kuhnert, Frank; Han, Xiaoyuan; Yuan, Jenny; Chiou, Shin-Heng; Brettman, Ari D; Daly, Lauren; Corney, David C; Cheshier, Samuel H; Shortliffe, Linda D; Wu, Xiwei; Snyder, Michael; Chan, Pak; Giffard, Rona G; Chang, Howard Y; Andreasson, Katrin; Kuo, Calvin J

2017-04-01

Although blood-brain barrier (BBB) compromise is central to the etiology of diverse central nervous system (CNS) disorders, endothelial receptor proteins that control BBB function are poorly defined. The endothelial G-protein-coupled receptor (GPCR) Gpr124 has been reported to be required for normal forebrain angiogenesis and BBB function in mouse embryos, but the role of this receptor in adult animals is unknown. Here Gpr124 conditional knockout (CKO) in the endothelia of adult mice did not affect homeostatic BBB integrity, but resulted in BBB disruption and microvascular hemorrhage in mouse models of both ischemic stroke and glioblastoma, accompanied by reduced cerebrovascular canonical Wnt-β-catenin signaling. Constitutive activation of Wnt-β-catenin signaling fully corrected the BBB disruption and hemorrhage defects of Gpr124-CKO mice, with rescue of the endothelial gene tight junction, pericyte coverage and extracellular-matrix deficits. We thus identify Gpr124 as an endothelial GPCR specifically required for endothelial Wnt signaling and BBB integrity under pathological conditions in adult mice. This finding implicates Gpr124 as a potential therapeutic target for human CNS disorders characterized by BBB disruption.

Rat brain sagittal organotypic slice cultures as an ex vivo dopamine cell loss system.

PubMed

McCaughey-Chapman, Amy; Connor, Bronwen

2017-02-01

Organotypic brain slice cultures are a useful tool to study neurological function as they provide a more complex, 3-dimensional system than standard 2-dimensional in vitro cell cultures. Building on a previously developed mouse brain slice culture protocol, we have developed a rat sagittal brain slice culture system as an ex vivo model of dopamine cell loss. We show that rat brain organotypic slice cultures remain viable for up to 6 weeks in culture. Using Fluoro-Gold axonal tracing, we demonstrate that the slice 3-dimensional cytoarchitecture is maintained over a 4 week culturing period, with particular focus on the nigrostriatal pathway. Treatment of the cultures with 6-hydroxydopamine and desipramine induces a progressive loss of Fluoro-Gold-positive nigral cells with a sustained loss of tyrosine hydroxylase-positive nigral cells. This recapitulates the pattern of dopaminergic degeneration observed in the rat partial 6-hydroxydopamine lesion model and, most importantly, the progressive pathology of Parkinson's disease. Our slice culture platform provides an advance over other systems, as we demonstrate for the first time 3-dimensional cytoarchitecture maintenance of rat nigrostriatal sagittal slices for up to 6 weeks. Our ex vivo organotypic slice culture system provides a long term cellular platform to model Parkinson's disease, allowing for the elucidation of mechanisms involved in dopaminergic neuron degeneration and the capability to study cellular integration and plasticity ex vivo. Copyright © 2017 Elsevier B.V. All rights reserved.

Strategic Resource Allocation in the Human Brain Supports Cognitive Coordination of Object and Spatial Working Memory

PubMed Central

Jackson, Margaret C; Morgan, Helen M; Shapiro, Kimron L; Mohr, Harald; Linden, David EJ

2011-01-01

The ability to integrate different types of information (e.g., object identity and spatial orientation) and maintain or manipulate them concurrently in working memory (WM) facilitates the flow of ongoing tasks and is essential for normal human cognition. Research shows that object and spatial information is maintained and manipulated in WM via separate pathways in the brain (object/ventral versus spatial/dorsal). How does the human brain coordinate the activity of different specialized systems to conjoin different types of information? Here we used functional magnetic resonance imaging to investigate conjunction- versus single-task manipulation of object (compute average color blend) and spatial (compute intermediate angle) information in WM. Object WM was associated with ventral (inferior frontal gyrus, occipital cortex), and spatial WM with dorsal (parietal cortex, superior frontal, and temporal sulci) regions. Conjoined object/spatial WM resulted in intermediate activity in these specialized areas, but greater activity in different prefrontal and parietal areas. Unique to our study, we found lower temporo-occipital activity and greater deactivation in temporal and medial prefrontal cortices for conjunction- versus single-tasks. Using structural equation modeling, we derived a conjunction-task connectivity model that comprises a frontoparietal network with a bidirectional DLPFC-VLPFC connection, and a direct parietal-extrastriate pathway. We suggest that these activation/deactivation patterns reflect efficient resource allocation throughout the brain and propose a new extended version of the biased competition model of WM. Hum Brain Mapp, 2011. © 2010 Wiley-Liss, Inc. PMID:20715083

The forgotten artist: Why to consider intentions and interaction in a model of aesthetic experience. 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)

Brattico, Elvira; Brattico, Pauli; Vuust, Peter

2017-07-01

In their target article published in this journal issue, Pelowski et al. [1] address the question of how humans experience, and respond to, visual art. They propose a multi-layered model of the representations and processes involved in assessing visual art objects that, furthermore, involves both bottom-up and top-down elements. Their model provides predictions for seven different outcomes of human aesthetic experience, based on few distinct features (schema congruence, self-relevance, and coping necessity), and connects the underlying processing stages to ;specific correlates of the brain; (a similar attempt was previously done for music by [2-4]). In doing this, the model aims to account for the (often profound) experience of an individual viewer in front of an art object.

Aggressive Behavior and Altered Amounts of Brain Serotonin and Norepinephrine in Mice Lacking MAOA

PubMed Central

Cases, Olivier; Grimsby, Joseph; Gaspar, Patricia; Chen, Kevin; Pournin, Sandrine; Müller, Ulrike; Aguet, Michel; Babinet, Charles; Shih, Jean Chen; De Maeyer, Edward

2010-01-01

Deficiency in monoamine oxidase A (MAOA), an enzyme that degrades serotonin and norepinephrine, has recently been shown to be associated with aggressive behavior in men of a Dutch family. A line of transgenic mice was isolated in which transgene integration caused a deletion in the gene encoding MAOA, providing an animal model of MAOA deficiency. In pup brains, serotonin concentrations were increased up to ninefold, and serotonin-like immunoreactivity was present in catecholaminergic neurons. In pup and adult brains, norepinephrine concentrations were increased up to twofold, and cytoarchitectural changes were observed in the somatosensory cortex. Pup behavioral alterations, including trembling, difficulty in righting, and fearfulness were reversed by the serotonin synthesis inhibitor parachlorophenylalanine. Adults manifested a distinct behavioral syndrome, including enhanced aggression in males. PMID:7792602

Neurite sprouting and synapse deterioration in the aging Caenorhabditis elegans nervous system.

PubMed

Toth, Marton Lorant; Melentijevic, Ilija; Shah, Leena; Bhatia, Aatish; Lu, Kevin; Talwar, Amish; Naji, Haaris; Ibanez-Ventoso, Carolina; Ghose, Piya; Jevince, Angela; Xue, Jian; Herndon, Laura A; Bhanot, Gyan; Rongo, Chris; Hall, David H; Driscoll, Monica

2012-06-27

Caenorhabditis elegans is a powerful model for analysis of the conserved mechanisms that modulate healthy aging. In the aging nematode nervous system, neuronal death and/or detectable loss of processes are not readily apparent, but because dendrite restructuring and loss of synaptic integrity are hypothesized to contribute to human brain decline and dysfunction, we combined fluorescence microscopy and electron microscopy (EM) to screen at high resolution for nervous system changes. We report two major components of morphological change in the aging C. elegans nervous system: (1) accumulation of novel outgrowths from specific neurons, and (2) physical decline in synaptic integrity. Novel outgrowth phenotypes, including branching from the main dendrite or new growth from somata, appear at a high frequency in some aging neurons, but not all. Mitochondria are often associated with age-associated branch sites. Lowered insulin signaling confers some maintenance of ALM and PLM neuron structural integrity into old age, and both DAF-16/FOXO and heat shock factor transcription factor HSF-1 exert neuroprotective functions. hsf-1 can act cell autonomously in this capacity. EM evaluation in synapse-rich regions reveals a striking decline in synaptic vesicle numbers and a diminution of presynaptic density size. Interestingly, old animals that maintain locomotory prowess exhibit less synaptic decline than same-age decrepit animals, suggesting that synaptic integrity correlates with locomotory healthspan. Our data reveal similarities between the aging C. elegans nervous system and mammalian brain, suggesting conserved neuronal responses to age. Dissection of neuronal aging mechanisms in C. elegans may thus influence the development of brain healthspan-extending therapies.

Radiobiological and treatment planning study of a simultaneously integrated boost for canine nasal tumors using helical tomotherapy.

PubMed

Gutíerrez, Alonso N; Deveau, Michael; Forrest, Lisa J; Tomé, Wolfgang A; Mackie, Thomas R

2007-01-01

Feasibility of delivering a simultaneously integrated boost to canine nasal tumors using helical tomotherapy to improve tumor control probability (TCP) via an increase in total biological equivalent uniform dose (EUD) was evaluated. Eight dogs with varying size nasal tumors (5.8-110.9 cc) were replanned to 42 Gy to the nasal cavity and integrated dose boosts to gross disease of 45.2, 48.3, and 51.3 Gy in 10 fractions. EUD values were calculated for tumors and mean normalized total doses (NTD(mean)) for organs at risk (OAR). Normal Tissue Complication Probability (NTCP) values were obtained for OARs, and estimated TCP values were computed using a logistic dose-response model and based on deliverable EUD boost doses. Significant increases in estimated TCP to 54%, 74%, and 86% can be achieved with 10%, 23%, and 37% mean relative EUD boosts to the gross disease, respectively. NTCP values for blindness of either eye and for brain necrosis were < 0.01% for all boosts. Values for cataract development were 31%, 42%, and 46% for studied boost schemas, respectively. Average NTD(mean) to eyes and brain for mean EUD boosts were 10.2, 11.3, and 12.1 Gy3, and 7.5, 7.2, and 7.9 Gy2, respectively. Using helical tomotherapy, simultaneously integrated dose boosts can be delivered to increase the estimated TCP at 1-year without significantly increasing the NTD(mean) to eyes and brain. Delivery of these treatments in a prospective trial may allow quantification of a dose-response relationship in canine nasal tumors.

Neurite Sprouting and Synapse Deterioration in the Aging C. elegans Nervous System

PubMed Central

Toth, Marton; Melentijevic, Ilija; Shah, Leena; Bhatia, Aatish; Lu, Kevin; Talwar, Amish; Naji, Haaris; Ibanez-Ventoso, Carolina; Ghose, Piya; Jevince, Angela; Xue, Jian; Herndon, Laura A.; Bhanot, Gyan; Rongo, Chris; Hall, David H

2012-01-01

C. elegans is a powerful model for analysis of the conserved mechanisms that modulate healthy aging. In the aging nematode nervous system, neuronal death and/or detectable loss of processes are not readily apparent, but because dendrite restructuring and loss of synaptic integrity are hypothesized to contribute to human brain decline and dysfunction, we combined fluorescence microscopy and electron microscopy (EM) to screen at high resolution for nervous system changes. We report two major components of morphological change in the aging C. elegans nervous system: 1) accumulation of novel outgrowths from specific neurons, and 2) physical decline in synaptic integrity. Novel outgrowth phenotypes, including branching from the main dendrite or new growth from somata, appear at a high frequency in some aging neurons, but not all. Mitochondria are often associated with age-associated branch sites. Lowered insulin signaling confers some maintenance of ALM and PLM neuron structural integrity into old age, and both DAF-16/FOXO and heat shock factor transcription factor HSF-1 exert neuroprotective functions. hsf-1 can act cell autonomously in this capacity. EM evaluation in synapse-rich regions reveals a striking decline in synaptic vesicle numbers and a dimunition of presynaptic density size. Interestingly, old animals that maintain locomotory prowess exhibit less synaptic decline than same-age decrepit animals, suggesting that synaptic integrity correlates with locomotory healthspan. Our data reveal similarities between the aging C. elegans nervous system and mammalian brain, suggesting conserved neuronal responses to age. Dissection of neuronal aging mechanisms in C. elegans may thus influence the development of brain healthspan-extending therapies. PMID:22745480

Causal Evidence for a Mechanism of Semantic Integration in the Angular Gyrus as Revealed by High-Definition Transcranial Direct Current Stimulation

PubMed Central

Peelle, Jonathan E.; Bonner, Michael F.; Grossman, Murray

2016-01-01

A defining aspect of human cognition is the ability to integrate conceptual information into complex semantic combinations. For example, we can comprehend “plaid” and “jacket” as individual concepts, but we can also effortlessly combine these concepts to form the semantic representation of “plaid jacket.” Many neuroanatomic models of semantic memory propose that heteromodal cortical hubs integrate distributed semantic features into coherent representations. However, little work has specifically examined these proposed integrative mechanisms and the causal role of these regions in semantic integration. Here, we test the hypothesis that the angular gyrus (AG) is critical for integrating semantic information by applying high-definition transcranial direct current stimulation (tDCS) to an fMRI-guided region-of-interest in the left AG. We found that anodal stimulation to the left AG modulated semantic integration but had no effect on a letter-string control task. Specifically, anodal stimulation to the left AG resulted in faster comprehension of semantically meaningful combinations like “tiny radish” relative to non-meaningful combinations, such as “fast blueberry,” when compared to the effects observed during sham stimulation and stimulation to a right-hemisphere control brain region. Moreover, the size of the effect from brain stimulation correlated with the degree of semantic coherence between the word pairs. These findings demonstrate that the left AG plays a causal role in the integration of lexical-semantic information, and that high-definition tDCS to an associative cortical hub can selectively modulate integrative processes in semantic memory. SIGNIFICANCE STATEMENT A major goal of neuroscience is to understand the neural basis of behaviors that are fundamental to human intelligence. One essential behavior is the ability to integrate conceptual knowledge from semantic memory, allowing us to construct an almost unlimited number of complex concepts from a limited set of basic constituents (e.g., “leaf” and “wet” can be combined into the more complex representation “wet leaf”). Here, we present a novel approach to studying integrative processes in semantic memory by applying focal brain stimulation to a heteromodal cortical hub implicated in semantic processing. Our findings demonstrate a causal role of the left angular gyrus in lexical-semantic integration and provide motivation for novel therapeutic applications in patients with lexical-semantic deficits. PMID:27030767

Causal Evidence for a Mechanism of Semantic Integration in the Angular Gyrus as Revealed by High-Definition Transcranial Direct Current Stimulation.

PubMed

Price, Amy Rose; Peelle, Jonathan E; Bonner, Michael F; Grossman, Murray; Hamilton, Roy H

2016-03-30

A defining aspect of human cognition is the ability to integrate conceptual information into complex semantic combinations. For example, we can comprehend "plaid" and "jacket" as individual concepts, but we can also effortlessly combine these concepts to form the semantic representation of "plaid jacket." Many neuroanatomic models of semantic memory propose that heteromodal cortical hubs integrate distributed semantic features into coherent representations. However, little work has specifically examined these proposed integrative mechanisms and the causal role of these regions in semantic integration. Here, we test the hypothesis that the angular gyrus (AG) is critical for integrating semantic information by applying high-definition transcranial direct current stimulation (tDCS) to an fMRI-guided region-of-interest in the left AG. We found that anodal stimulation to the left AG modulated semantic integration but had no effect on a letter-string control task. Specifically, anodal stimulation to the left AG resulted in faster comprehension of semantically meaningful combinations like "tiny radish" relative to non-meaningful combinations, such as "fast blueberry," when compared to the effects observed during sham stimulation and stimulation to a right-hemisphere control brain region. Moreover, the size of the effect from brain stimulation correlated with the degree of semantic coherence between the word pairs. These findings demonstrate that the left AG plays a causal role in the integration of lexical-semantic information, and that high-definition tDCS to an associative cortical hub can selectively modulate integrative processes in semantic memory. A major goal of neuroscience is to understand the neural basis of behaviors that are fundamental to human intelligence. One essential behavior is the ability to integrate conceptual knowledge from semantic memory, allowing us to construct an almost unlimited number of complex concepts from a limited set of basic constituents (e.g., "leaf" and "wet" can be combined into the more complex representation "wet leaf"). Here, we present a novel approach to studying integrative processes in semantic memory by applying focal brain stimulation to a heteromodal cortical hub implicated in semantic processing. Our findings demonstrate a causal role of the left angular gyrus in lexical-semantic integration and provide motivation for novel therapeutic applications in patients with lexical-semantic deficits. Copyright © 2016 the authors 0270-6474/16/363829-10$15.00/0.

TU-G-210-00: Treatment Planning Strategies, Modeling, Control

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

NONE

Modeling can play a vital role in predicting, optimizing and analyzing the results of therapeutic ultrasound treatments. Simulating the propagating acoustic beam in various targeted regions of the body allows for the prediction of the resulting power deposition and temperature profiles. In this session we will apply various modeling approaches to breast, abdominal organ and brain treatments. Of particular interest is the effectiveness of procedures for correcting for phase aberrations caused by intervening irregular tissues, such as the skull in transcranial applications or inhomogeneous breast tissues. Also described are methods to compensate for motion in targeted abdominal organs such asmore » the liver or kidney. Douglas Christensen – Modeling for Breast and Brain HIFU Treatment Planning Tobias Preusser – TRANS-FUSIMO – An Integrative Approach to Model-Based Treatment Planning of Liver FUS Tobias Preusser – TRANS-FUSIMO – An Integrative Approach to Model-Based Treatment Planning of Liver FUS Learning Objectives: Understand the role of acoustic beam modeling for predicting the effectiveness of therapeutic ultrasound treatments. Apply acoustic modeling to specific breast, liver, kidney and transcranial anatomies. Determine how to obtain appropriate acoustic modeling parameters from clinical images. Understand the separate role of absorption and scattering in energy delivery to tissues. See how organ motion can be compensated for in ultrasound therapies. Compare simulated data with clinical temperature measurements in transcranial applications. Supported by NIH R01 HL172787 and R01 EB013433 (DC); EU Seventh Framework Programme (FP7/2007-2013) under 270186 (FUSIMO) and 611889 (TRANS-FUSIMO)(TP); and P01 CA159992, GE, FUSF and InSightec (UV)« less

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.

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.

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?

Brain-shift compensation using intraoperative ultrasound and constraint-based biomechanical simulation.

PubMed

Morin, Fanny; Courtecuisse, Hadrien; Reinertsen, Ingerid; Le Lann, Florian; Palombi, Olivier; Payan, Yohan; Chabanas, Matthieu

2017-08-01

During brain tumor surgery, planning and guidance are based on preoperative images which do not account for brain-shift. However, this deformation is a major source of error in image-guided neurosurgery and affects the accuracy of the procedure. In this paper, we present a constraint-based biomechanical simulation method to compensate for craniotomy-induced brain-shift that integrates the deformations of the blood vessels and cortical surface, using a single intraoperative ultrasound acquisition. Prior to surgery, a patient-specific biomechanical model is built from preoperative images, accounting for the vascular tree in the tumor region and brain soft tissues. Intraoperatively, a navigated ultrasound acquisition is performed directly in contact with the organ. Doppler and B-mode images are recorded simultaneously, enabling the extraction of the blood vessels and probe footprint, respectively. A constraint-based simulation is then executed to register the pre- and intraoperative vascular trees as well as the cortical surface with the probe footprint. Finally, preoperative images are updated to provide the surgeon with images corresponding to the current brain shape for navigation. The robustness of our method is first assessed using sparse and noisy synthetic data. In addition, quantitative results for five clinical cases are provided, first using landmarks set on blood vessels, then based on anatomical structures delineated in medical images. The average distances between paired vessels landmarks ranged from 3.51 to 7.32 (in mm) before compensation. With our method, on average 67% of the brain-shift is corrected (range [1.26; 2.33]) against 57% using one of the closest existing works (range [1.71; 2.84]). Finally, our method is proven to be fully compatible with a surgical workflow in terms of execution times and user interactions. In this paper, a new constraint-based biomechanical simulation method is proposed to compensate for craniotomy-induced brain-shift. While being efficient to correct this deformation, the method is fully integrable in a clinical process. Copyright © 2017 Elsevier B.V. All rights reserved.

Toward an Integrative Model for CBT: Encompassing Behavior, Cognition, Affect, and Process

ERIC Educational Resources Information Center

Mischel, Walter

2004-01-01

Dramatic changes in our science in recent years have profound implications for how psychologists conceptualize, assess, and treat people. I comment on these developments and the contributions to this special series, focusing on how they speak to new directions and challenges for the future of CBT. Discoveries about mind, brain, and behavior that…

A Neurocomputational Model of the N400 and the P600 in Language Processing

ERIC Educational Resources Information Center

Brouwer, Harm; Crocker, Matthew W.; Venhuizen, Noortje J.; Hoeks, John C. J.

2017-01-01

Ten years ago, researchers using event-related brain potentials (ERPs) to study language comprehension were puzzled by what looked like a "Semantic Illusion": Semantically anomalous, but structurally well-formed sentences did not affect the N400 component--traditionally taken to reflect semantic integration--but instead produced a P600…

Adaptation, expertise, and giftedness: towards an understanding of cortical, subcortical, and cerebellar network contributions.

PubMed

Koziol, Leonard F; Budding, Deborah Ely; Chidekel, Dana

2010-12-01

Current cortico-centric models of cognition lack a cohesive neuroanatomic framework that sufficiently considers overlapping levels of function, from "pathological" through "normal" to "gifted" or exceptional ability. While most cognitive theories presume an evolutionary context, few actively consider the process of adaptation, including concepts of neurodevelopment. Further, the frequent co-occurrence of "gifted" and "pathological" function is difficult to explain from a cortico-centric point of view. This comprehensive review paper proposes a framework that includes the brain's vertical organization and considers "giftedness" from an evolutionary and neurodevelopmental vantage point. We begin by discussing the current cortico-centric model of cognition and its relationship to intelligence. We then review an integrated, dual-tiered model of cognition that better explains the process of adaptation by simultaneously allowing for both stimulus-based processing and higher-order cognitive control. We consider the role of the basal ganglia within this model, particularly in relation to reward circuitry and instrumental learning. We review the important role of white matter tracts in relation to speed of adaptation and development of behavioral mastery. We examine the cerebellum's critical role in behavioral refinement and in cognitive and behavioral automation, particularly in relation to expertise and giftedness. We conclude this integrated model of brain function by considering the savant syndrome, which we believe is best understood within the context of a dual-tiered model of cognition that allows for automaticity in adaptation as well as higher-order executive control.

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.

Mild fluid percussion injury in mice produces evolving selective axonal pathology and cognitive deficits relevant to human brain injury.

PubMed

Spain, Aisling; Daumas, Stephanie; Lifshitz, Jonathan; Rhodes, Jonathan; Andrews, Peter J D; Horsburgh, Karen; Fowler, Jill H

2010-08-01

Mild traumatic brain injury (TBI) accounts for up to 80% of clinical TBI and can result in cognitive impairment and white matter damage that may develop and persist over several years. Clinically relevant models of mild TBI for investigation of neurobiological changes and the development of therapeutic strategies are poorly developed. In this study we investigated the temporal profile of axonal and somal injury that may contribute to cognitive impairments in a mouse model of mild TBI. Neuronal perikaryal damage (hematoxylin and eosin and Fluoro-Jade C), myelin integrity (myelin basic protein and myelin-associated glycoprotein), and axonal damage (amyloid precursor protein), were evaluated by immunohistochemistry at 4 h, 24 h, 72 h, 4 weeks, and 6 weeks after mild lateral fluid percussion brain injury (0.9 atm; righting time 167 +/- 15 sec). At 3 weeks post-injury spatial reference learning and memory were tested in the Morris water maze (MWM). Levels of damage to neuronal cell bodies were comparable in the brain-injured and sham groups. Myelin integrity was minimally altered following injury. Clear alterations in axonal damage were observed at various time points after injury. Axonal damage was localized to the cingulum at 4 h post-injury. At 4 and 6 weeks post-injury, axonal damage was evident in the external capsule, and was seen at 6 weeks in the dorsal thalamic nuclei. At 3 weeks post-injury, injured mice showed an impaired ability to learn the water maze task, suggesting injury-induced alterations in search strategy learning. The evolving localization of axonal damage points to ongoing degeneration after injury that is concomitant with a deficit in learning.

Assessment of Blood-brain Barrier Permeability by Intravenous Infusion of FITC-labeled Albumin in a Mouse Model of Neurodegenerative Disease.

PubMed

Di Pardo, Alba; Castaldo, Salvatore; Capocci, Luca; Amico, Enrico; Vittorio, Maglione

2017-11-08

Disruption of blood-brain barrier (BBB) integrity is a common feature for different neurological and neurodegenerative diseases. Although the interplay between perturbed BBB homeostasis and the pathogenesis of brain disorders needs further investigation, the development and validation of a reliable procedure to accurately detect BBB alterations may be crucial and represent a useful tool for potentially predicting disease progression and developing targeted therapeutic strategies. Here, we present an easy and efficient procedure for evaluating BBB leakage in a neurodegenerative condition like that occurring in a preclinical mouse model of Huntington disease, in which defects in the permeability of BBB are clearly detectable precociously in the disease. Specifically, the high molecular weight fluorescein isothiocyanate labelled (FITC)-albumin, which is able to cross the BBB only when the latter is impaired, is acutely infused into a mouse jugular vein and its distribution in the vascular or parenchymal districts is then determined by fluorescence microscopy. Accumulation of green fluorescent-albumin in the brain parenchyma functions as an index of aberrant BBB permeability and, when quantitated by using Image J processing software, is reported as Green Fluorescence Intensity.

Relative timing: from behaviour to neurons

PubMed Central

Aghdaee, S. Mehdi; Battelli, Lorella; Assad, John A.

2014-01-01

Processing of temporal information is critical to behaviour. Here, we review the phenomenology and mechanism of relative timing, ordinal comparisons between the timing of occurrence of events. Relative timing can be an implicit component of particular brain computations or can be an explicit, conscious judgement. Psychophysical measurements of explicit relative timing have revealed clues about the interaction of sensory signals in the brain as well as in the influence of internal states, such as attention, on those interactions. Evidence from human neurophysiological and functional imaging studies, neuropsychological examination in brain-lesioned patients, and temporary disruptive interventions such as transcranial magnetic stimulation (TMS), point to a role of the parietal cortex in relative timing. Relative timing has traditionally been modelled as a ‘race’ between competing neural signals. We propose an updated race process based on the integration of sensory evidence towards a decision threshold rather than simple signal propagation. The model suggests a general approach for identifying brain regions involved in relative timing, based on looking for trial-by-trial correlations between neural activity and temporal order judgements (TOJs). Finally, we show how the paradigm can be used to reveal signals related to TOJs in parietal cortex of monkeys trained in a TOJ task. PMID:24446505

Moving Beyond ERP Components: A Selective Review of Approaches to Integrate EEG and Behavior

PubMed Central

Bridwell, David A.; Cavanagh, James F.; Collins, Anne G. E.; Nunez, Michael D.; Srinivasan, Ramesh; Stober, Sebastian; Calhoun, Vince D.

2018-01-01

Relationships between neuroimaging measures and behavior provide important clues about brain function and cognition in healthy and clinical populations. While electroencephalography (EEG) provides a portable, low cost measure of brain dynamics, it has been somewhat underrepresented in the emerging field of model-based inference. We seek to address this gap in this article by highlighting the utility of linking EEG and behavior, with an emphasis on approaches for EEG analysis that move beyond focusing on peaks or “components” derived from averaging EEG responses across trials and subjects (generating the event-related potential, ERP). First, we review methods for deriving features from EEG in order to enhance the signal within single-trials. These methods include filtering based on user-defined features (i.e., frequency decomposition, time-frequency decomposition), filtering based on data-driven properties (i.e., blind source separation, BSS), and generating more abstract representations of data (e.g., using deep learning). We then review cognitive models which extract latent variables from experimental tasks, including the drift diffusion model (DDM) and reinforcement learning (RL) approaches. Next, we discuss ways to access associations among these measures, including statistical models, data-driven joint models and cognitive joint modeling using hierarchical Bayesian models (HBMs). We think that these methodological tools are likely to contribute to theoretical advancements, and will help inform our understandings of brain dynamics that contribute to moment-to-moment cognitive function. PMID:29632480

Integrated Stress Response as a Therapeutic Target for CNS Injuries.

PubMed

Romero-Ramírez, Lorenzo; Nieto-Sampedro, Manuel; Barreda-Manso, M Asunción

2017-01-01

Central nervous system (CNS) injuries, caused by cerebrovascular pathologies or mechanical contusions (e.g., traumatic brain injury, TBI) comprise a diverse group of disorders that share the activation of the integrated stress response (ISR). This pathway is an innate protective mechanism, with encouraging potential as therapeutic target for CNS injury repair. In this review, we will focus on the progress in understanding the role of the ISR and we will discuss the effects of various small molecules that target the ISR on different animal models of CNS injury.

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.

Brain-computer interface controlled functional electrical stimulation system for ankle movement.

PubMed

Do, An H; Wang, Po T; King, Christine E; Abiri, Ahmad; Nenadic, Zoran

2011-08-26

Many neurological conditions, such as stroke, spinal cord injury, and traumatic brain injury, can cause chronic gait function impairment due to foot-drop. Current physiotherapy techniques provide only a limited degree of motor function recovery in these individuals, and therefore novel therapies are needed. Brain-computer interface (BCI) is a relatively novel technology with a potential to restore, substitute, or augment lost motor behaviors in patients with neurological injuries. Here, we describe the first successful integration of a noninvasive electroencephalogram (EEG)-based BCI with a noninvasive functional electrical stimulation (FES) system that enables the direct brain control of foot dorsiflexion in able-bodied individuals. A noninvasive EEG-based BCI system was integrated with a noninvasive FES system for foot dorsiflexion. Subjects underwent computer-cued epochs of repetitive foot dorsiflexion and idling while their EEG signals were recorded and stored for offline analysis. The analysis generated a prediction model that allowed EEG data to be analyzed and classified in real time during online BCI operation. The real-time online performance of the integrated BCI-FES system was tested in a group of five able-bodied subjects who used repetitive foot dorsiflexion to elicit BCI-FES mediated dorsiflexion of the contralateral foot. Five able-bodied subjects performed 10 alternations of idling and repetitive foot dorsifiexion to trigger BCI-FES mediated dorsifiexion of the contralateral foot. The epochs of BCI-FES mediated foot dorsifiexion were highly correlated with the epochs of voluntary foot dorsifiexion (correlation coefficient ranged between 0.59 and 0.77) with latencies ranging from 1.4 sec to 3.1 sec. In addition, all subjects achieved a 100% BCI-FES response (no omissions), and one subject had a single false alarm. This study suggests that the integration of a noninvasive BCI with a lower-extremity FES system is feasible. With additional modifications, the proposed BCI-FES system may offer a novel and effective therapy in the neuro-rehabilitation of individuals with lower extremity paralysis due to neurological injuries.

Multimodality imaging and mathematical modelling of drug delivery to glioblastomas.

PubMed

Boujelben, Ahmed; Watson, Michael; McDougall, Steven; Yen, Yi-Fen; Gerstner, Elizabeth R; Catana, Ciprian; Deisboeck, Thomas; Batchelor, Tracy T; Boas, David; Rosen, Bruce; Kalpathy-Cramer, Jayashree; Chaplain, Mark A J

2016-10-06

Patients diagnosed with glioblastoma, an aggressive brain tumour, have a poor prognosis, with a median overall survival of less than 15 months. Vasculature within these tumours is typically abnormal, with increased tortuosity, dilation and disorganization, and they typically exhibit a disrupted blood-brain barrier (BBB). Although it has been hypothesized that the 'normalization' of the vasculature resulting from anti-angiogenic therapies could improve drug delivery through improved blood flow, there is also evidence that suggests that the restoration of BBB integrity might limit the delivery of therapeutic agents and hence their effectiveness. In this paper, we apply mathematical models of blood flow, vascular permeability and diffusion within the tumour microenvironment to investigate the effect of these competing factors on drug delivery. Preliminary results from the modelling indicate that all three physiological parameters investigated-flow rate, vessel permeability and tissue diffusion coefficient-interact nonlinearly to produce the observed average drug concentration in the microenvironment.

Schizophrenia in childhood and adolescence.

PubMed

Mala, Eva

2008-12-01

Schizophrenia is a disorder characterized by delay in neurodevelopment and by a central disorder of recognition (i.e. with generalized cognitive deficit). Connectivity impairments in the areas of the social brain and cerebellum are the "messenger" of abnormal CNS development in schizophrenia. Processes of neuronal reorganization in cortical and subcortical structures, aberrant forms of pruning, sprouting, and myelinization may play a major role in the pathogenesis of a schizophrenic breakdown. Models of neuroplasticity during adolescence can be connected with models of neurodevelopmental vulnerability and models of neurotoxicity to form an integrated approach in order to better understand premorbid adjustment, onset, and course of schizophrenia. The loss of plasticity and aberrant myelinization lead to a deterioration in cognitive functions, social dysfunction and, in individuals with specific genetic vulnerability, to expression of schizophrenia. This article discusses brain development in relation to the diagnosis of schizophrenia and the basic symptoms of childhood schizophrenia (with early and very early onset) and of adolescent schizophrenia.

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

Representing the sublime in the VIMAP and empirical aesthetics: Reviving Edmund Burke's A Philosophical Enquiry into the Origins of Our Ideas of the Sublime and Beautiful. 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)

Hur, Y.-J.; McManus, I. C.

2017-07-01

This commentary considers the role of the sublime in the Vienna Integrated Model of Art Perception (VIMAP; Pelowski, Markey, Forster, Gerger, & Leder [17]), and suggest that it is not precisely conceptualised in the model. In part that reflects different views and usages of the sublime in the literature, and here it is recommended that Burke's [2] view of the sublime is used as a primary framework for empirical research on the sublime.