Neurophysiological Basis of Multi-Scale Entropy of Brain Complexity and Its Relationship With Functional Connectivity.

PubMed

Wang, Danny J J; Jann, Kay; Fan, Chang; Qiao, Yang; Zang, Yu-Feng; Lu, Hanbing; Yang, Yihong

2018-01-01

Recently, non-linear statistical measures such as multi-scale entropy (MSE) have been introduced as indices of the complexity of electrophysiology and fMRI time-series across multiple time scales. In this work, we investigated the neurophysiological underpinnings of complexity (MSE) of electrophysiology and fMRI signals and their relations to functional connectivity (FC). MSE and FC analyses were performed on simulated data using neural mass model based brain network model with the Brain Dynamics Toolbox, on animal models with concurrent recording of fMRI and electrophysiology in conjunction with pharmacological manipulations, and on resting-state fMRI data from the Human Connectome Project. Our results show that the complexity of regional electrophysiology and fMRI signals is positively correlated with network FC. The associations between MSE and FC are dependent on the temporal scales or frequencies, with higher associations between MSE and FC at lower temporal frequencies. Our results from theoretical modeling, animal experiment and human fMRI indicate that (1) Regional neural complexity and network FC may be two related aspects of brain's information processing: the more complex regional neural activity, the higher FC this region has with other brain regions; (2) MSE at high and low frequencies may represent local and distributed information processing across brain regions. Based on literature and our data, we propose that the complexity of regional neural signals may serve as an index of the brain's capacity of information processing-increased complexity may indicate greater transition or exploration between different states of brain networks, thereby a greater propensity for information processing.

Mechanical characterization of human brain tumors from patients and comparison to potential surgical phantoms

PubMed Central

Rubiano, Andrés; Dyson, Kyle; Simmons, Chelsey S.

2017-01-01

While mechanical properties of the brain have been investigated thoroughly, the mechanical properties of human brain tumors rarely have been directly quantified due to the complexities of acquiring human tissue. Quantifying the mechanical properties of brain tumors is a necessary prerequisite, though, to identify appropriate materials for surgical tool testing and to define target parameters for cell biology and tissue engineering applications. Since characterization methods vary widely for soft biological and synthetic materials, here, we have developed a characterization method compatible with abnormally shaped human brain tumors, mouse tumors, animal tissue and common hydrogels, which enables direct comparison among samples. Samples were tested using a custom-built millimeter-scale indenter, and resulting force-displacement data is analyzed to quantify the steady-state modulus of each sample. We have directly quantified the quasi-static mechanical properties of human brain tumors with effective moduli ranging from 0.17–16.06 kPa for various pathologies. Of the readily available and inexpensive animal tissues tested, chicken liver (steady-state modulus 0.44 ± 0.13 kPa) has similar mechanical properties to normal human brain tissue while chicken crassus gizzard muscle (steady-state modulus 3.00 ± 0.65 kPa) has similar mechanical properties to human brain tumors. Other materials frequently used to mimic brain tissue in mechanical tests, like ballistic gel and chicken breast, were found to be significantly stiffer than both normal and diseased brain tissue. We have directly compared quasi-static properties of brain tissue, brain tumors, and common mechanical surrogates, though additional tests would be required to determine more complex constitutive models. PMID:28582392

Rhenium and technetium complexes that bind to amyloid-β plaques.

PubMed

Hayne, David J; North, Andrea J; Fodero-Tavoletti, Michelle; White, Jonathan M; Hung, Lin W; Rigopoulos, Angela; McLean, Catriona A; Adlard, Paul A; Ackermann, Uwe; Tochon-Danguy, Henri; Villemagne, Victor L; Barnham, Kevin J; Donnelly, Paul S

2015-03-21

Alzheimer's disease is associated with the presence of insoluble protein deposits in the brain called amyloid plaques. The major constituent of these deposits is aggregated amyloid-β peptide. Technetium-99m complexes that bind to amyloid-β plaques could provide important diagnostic information on amyloid-β plaque burden using Single Photon Emission Computed Tomography (SPECT). Tridentate ligands with a stilbene functional group were used to form complexes with the fac-[M(I)(CO)3](+) (M = Re or (99m)Tc) core. The rhenium carbonyl complexes with tridentate co-ligands that included a stilbene functional group and a dimethylamino substituent bound to amyloid-β present in human frontal cortex brain tissue from subjects with Alzheimer's disease. This chemistry was extended to make the analogous [(99m)Tc(I)(CO)3](+) complexes and the complexes were sufficiently stable in human serum. Whilst the lipophilicity (log D7.4) of the technetium complexes appeared ideally suited for penetration of the blood-brain barrier, preliminary biodistribution studies in an AD mouse model (APP/PS1) revealed relatively low brain uptake (0.24% ID g(-1) at 2 min post injection).

Graph Theory at the Service of Electroencephalograms.

PubMed

Iakovidou, Nantia D

2017-04-01

The brain is one of the largest and most complex organs in the human body and EEG is a noninvasive electrophysiological monitoring method that is used to record the electrical activity of the brain. Lately, the functional connectivity in human brain has been regarded and studied as a complex network using EEG signals. This means that the brain is studied as a connected system where nodes, or units, represent different specialized brain regions and links, or connections, represent communication pathways between the nodes. Graph theory and theory of complex networks provide a variety of measures, methods, and tools that can be useful to efficiently model, analyze, and study EEG networks. This article is addressed to computer scientists who wish to be acquainted and deal with the study of EEG data and also to neuroscientists who would like to become familiar with graph theoretic approaches and tools to analyze EEG data.

Reducing the Complexity Gap: Expanding the Period of Human Nurturance

ERIC Educational Resources Information Center

Kiel, L. Douglas

2014-01-01

Socio-techno-cultural reality, in the current historical era, evolves at a faster rate than do human brain or human institutions. This reality creates a "complexity gap" that reduces human and institutional capacities to adapt to the challenges of late modernity. New insights from the neurosciences may help to reduce the complexity gap.…

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

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

Organoid technology for brain and therapeutics research.

PubMed

Wang, Zhi; Wang, Shu-Na; Xu, Tian-Ying; Miao, Zhu-Wei; Su, Ding-Feng; Miao, Chao-Yu

2017-10-01

Brain is one of the most complex organs in human. The current brain research is mainly based on the animal models and traditional cell culture. However, the inherent species differences between humans and animals as well as the gap between organ level and cell level make it difficult to study human brain development and associated disorders through traditional technologies. Recently, the brain organoids derived from pluripotent stem cells have been reported to recapitulate many key features of human brain in vivo, for example recapitulating the zone of putative outer radial glia cells. Brain organoids offer a new platform for scientists to study brain development, neurological diseases, drug discovery and personalized medicine, regenerative medicine, and so on. Here, we discuss the progress, applications, advantages, limitations, and prospects of brain organoid technology in neurosciences and related therapeutics. © 2017 John Wiley & Sons Ltd.

The neurotechnological revolution: unlocking the brain's secrets to develop innovative technologies as well as treatments for neurological diseases.

PubMed

Banks, Jim

2015-01-01

The brain contains all that makes us human, but its complexity is the source of both inspiration and frailty. Aging population is increasingly in need of effective care and therapies for brain diseases, including stroke, Parkinson's disease and Alzheimer's disease. The world's scientific community working hard to unravel the secrets of the brain's computing power and to devise technologies that can heal it when it fails and restore critical functions to patients with neurological conditions. Neurotechnology is the emerging field that brings together the development of technologies to study the brain and devices that improve and repair brain function. What is certain is the momentum behind neurotechnological research is building, and whether through implants, BCIs, or innovative computational systems inspired by the human brain, more light will be shed on our most complex and most precious organ, which will no doubt lead to effective treatment for many neurological conditions.

BrainNet Viewer: a network visualization tool for human brain connectomics.

PubMed

Xia, Mingrui; Wang, Jinhui; He, Yong

2013-01-01

The human brain is a complex system whose topological organization can be represented using connectomics. Recent studies have shown that human connectomes can be constructed using various neuroimaging technologies and further characterized using sophisticated analytic strategies, such as graph theory. These methods reveal the intriguing topological architectures of human brain networks in healthy populations and explore the changes throughout normal development and aging and under various pathological conditions. However, given the huge complexity of this methodology, toolboxes for graph-based network visualization are still lacking. Here, using MATLAB with a graphical user interface (GUI), we developed a graph-theoretical network visualization toolbox, called BrainNet Viewer, to illustrate human connectomes as ball-and-stick models. Within this toolbox, several combinations of defined files with connectome information can be loaded to display different combinations of brain surface, nodes and edges. In addition, display properties, such as the color and size of network elements or the layout of the figure, can be adjusted within a comprehensive but easy-to-use settings panel. Moreover, BrainNet Viewer draws the brain surface, nodes and edges in sequence and displays brain networks in multiple views, as required by the user. The figure can be manipulated with certain interaction functions to display more detailed information. Furthermore, the figures can be exported as commonly used image file formats or demonstration video for further use. BrainNet Viewer helps researchers to visualize brain networks in an easy, flexible and quick manner, and this software is freely available on the NITRC website (www.nitrc.org/projects/bnv/).

Is the social brain theory applicable to human individual differences? Relationship between sociability personality dimension and brain size.

PubMed

Horváth, Klára; Martos, János; Mihalik, Béla; Bódizs, Róbert

2011-06-17

Our study intends to examine whether the social brain theory is applicable to human individual differences. According to the social brain theory primates have larger brains as it could be expected from their body sizes due to the adaptation to a more complex social life. Regarding humans there were few studies about the relationship between theory of mind and frontal and temporal brain lobes. We hypothesized that these brain lobes, as well as the whole cerebrum and neocortex are in connection with the Sociability personality dimension that is associated with individuals' social lives. Our findings support this hypothesis as Sociability correlated positively with the examined brain structures if we control the effects of body size differences and age. These results suggest that the social brain theory can be extended to human interindividual differences and they have some implications to personality psychology too.

Complexity and multifractality of neuronal noise in mouse and human hippocampal epileptiform dynamics.

PubMed

Serletis, Demitre; Bardakjian, Berj L; Valiante, Taufik A; Carlen, Peter L

2012-10-01

Fractal methods offer an invaluable means of investigating turbulent nonlinearity in non-stationary biomedical recordings from the brain. Here, we investigate properties of complexity (i.e. the correlation dimension, maximum Lyapunov exponent, 1/f(γ) noise and approximate entropy) and multifractality in background neuronal noise-like activity underlying epileptiform transitions recorded at the intracellular and local network scales from two in vitro models: the whole-intact mouse hippocampus and lesional human hippocampal slices. Our results show evidence for reduced dynamical complexity and multifractal signal features following transition to the ictal epileptiform state. These findings suggest that pathological breakdown in multifractal complexity coincides with loss of signal variability or heterogeneity, consistent with an unhealthy ictal state that is far from the equilibrium of turbulent yet healthy fractal dynamics in the brain. Thus, it appears that background noise-like activity successfully captures complex and multifractal signal features that may, at least in part, be used to classify and identify brain state transitions in the healthy and epileptic brain, offering potential promise for therapeutic neuromodulatory strategies for afflicted patients suffering from epilepsy and other related neurological disorders.

The Human Nervous System: A Framework for Teaching and the Teaching Brain

ERIC Educational Resources Information Center

Rodriguez, Vanessa

2013-01-01

The teaching brain is a new concept that mirrors the complex, dynamic, and context-dependent nature of the learning brain. In this article, I use the structure of the human nervous system and its sensing, processing, and responding components as a framework for a re-conceptualized teaching system. This teaching system is capable of responses on an…

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.

Complexity of EEG-signal in Time Domain - Possible Biomedical Application

NASA Astrophysics Data System (ADS)

Klonowski, Wlodzimierz; Olejarczyk, Elzbieta; Stepien, Robert

2002-07-01

Human brain is a highly complex nonlinear system. So it is not surprising that in analysis of EEG-signal, which represents overall activity of the brain, the methods of Nonlinear Dynamics (or Chaos Theory as it is commonly called) can be used. Even if the signal is not chaotic these methods are a motivating tool to explore changes in brain activity due to different functional activation states, e.g. different sleep stages, or to applied therapy, e.g. exposure to chemical agents (drugs) and physical factors (light, magnetic field). The methods supplied by Nonlinear Dynamics reveal signal characteristics that are not revealed by linear methods like FFT. Better understanding of principles that govern dynamics and complexity of EEG-signal can help to find `the signatures' of different physiological and pathological states of human brain, quantitative characteristics that may find applications in medical diagnostics.

Brain Research and Learning.

ERIC Educational Resources Information Center

Claycomb, Mary

Current research on brain activity has many implications for educators. The triune brain concept and the left and right hemisphere concepts are among the many complex theories evolving from experimentation and observation. The triune brain concept suggests that the human forebrain has expanded while retaining three structurally unique formations…

Organization and hierarchy of the human functional brain network lead to a chain-like core.

PubMed

Mastrandrea, Rossana; Gabrielli, Andrea; Piras, Fabrizio; Spalletta, Gianfranco; Caldarelli, Guido; Gili, Tommaso

2017-07-07

The brain is a paradigmatic example of a complex system: its functionality emerges as a global property of local mesoscopic and microscopic interactions. Complex network theory allows to elicit the functional architecture of the brain in terms of links (correlations) between nodes (grey matter regions) and to extract information out of the noise. Here we present the analysis of functional magnetic resonance imaging data from forty healthy humans at rest for the investigation of the basal scaffold of the functional brain network organization. We show how brain regions tend to coordinate by forming a highly hierarchical chain-like structure of homogeneously clustered anatomical areas. A maximum spanning tree approach revealed the centrality of the occipital cortex and the peculiar aggregation of cerebellar regions to form a closed core. We also report the hierarchy of network segregation and the level of clusters integration as a function of the connectivity strength between brain regions.

Scientific meaning of meanings: quests for discoveries concerning our cultural ills.

PubMed

Patterson, C C

1998-08-01

This paper outlines pioneering concepts of fundamental physical and emotional features of the human brain which served as primary operators. These have developed during the past 10,000 years, giving rise to our present global megacultures and their various ancestral culture progenitors. Essential points are these: (1) Biological evolution endowed the human brain (quite inadvertently and unintentionally) with enormous latent powers for complex and sophisticated abstract ratiocinations. (2) Magnitudes of these latent powers grew exponentially with linear enlargements of brain size during the evolution of the genetic ancestors of Homo sapiens sapiens (Hss) during the past 3 million years, but these latent powers never materialized in utilized forms within the environmental contexts in which they evolved. (3) These sophisticated, abstract ratiocinations, both latent powers and operative forms in today's Hss brain, are divided between two major categories: utilitarian thinking and nonutilitarian thinking. (4) These two different types of thinking processes are carried out within separate, different regional combinations of neuronal biochemical entities within the same individual brain. (5) Sensitivities of abstract, sophisticated ratiocination processes within the human brain to influences from communication interactions with other human brains are exponentially greater in comparison with any other species of central nervous system in the earth's biosphere. This makes the brain population density the utmost critical factor, and determines the character of human thought within interacting populations of brains at a given time and place within a particular culture. (6) Abrupt increases of sedentary brain population densities, unnaturally greater by orders of magnitude than those that existed previously in biological evolutionary contexts, were engendered by the inauguration of agricultural practices 10,000 years ago. This enabled latent powers of the human brain used for complex and sophisticated abstract ratiocinations to become manifest in materialized forms of usage within relatively large groups of humans living i certain regions of the earth. (7) Thinking processes of the utilitarian category within brains living in such regions guided and dominated the development of sophisticated and complex social hierarchies and institutions, forms of communication, technologies, and cultures since that time. This dominating factor relegated thinking processes within the nonutilitarian categories of those brains to subservient roles during those developments. (8) Nonutilitarian abstracts ratiocinations possess a potential for proper adjudication and guidance of utilitarian abstract ratiocinations in the latter's development of culture. However, lack of the former's proper role in cultural developments since the beginning of the Holocene interglacial era has resulted in the imprisonment of Hss as aliens in an intellectual hell on a foreign planet.

Convergent transcriptional specializations in the brains of humans and song-learning birds

PubMed Central

Pfenning, Andreas R.; Hara, Erina; Whitney, Osceola; Rivas, Miriam V.; Wang, Rui; Roulhac, Petra L.; Howard, Jason T.; Wirthlin, Morgan; Lovell, Peter V.; Ganapathy, Ganeshkumar; Mouncastle, Jacquelyn; Moseley, M. Arthur; Thompson, J. Will; Soderblom, Erik J.; Iriki, Atsushi; Kato, Masaki; Gilbert, M. Thomas P.; Zhang, Guojie; Bakken, Trygve; Bongaarts, Angie; Bernard, Amy; Lein, Ed; Mello, Claudio V.; Hartemink, Alexander J.; Jarvis, Erich D.

2015-01-01

Song-learning birds and humans share independently evolved similarities in brain pathways for vocal learning that are essential for song and speech and are not found in most other species. Comparisons of brain transcriptomes of song-learning birds and humans relative to vocal nonlearners identified convergent gene expression specializations in specific song and speech brain regions of avian vocal learners and humans. The strongest shared profiles relate bird motor and striatal song-learning nuclei, respectively, with human laryngeal motor cortex and parts of the striatum that control speech production and learning. Most of the associated genes function in motor control and brain connectivity. Thus, convergent behavior and neural connectivity for a complex trait are associated with convergent specialized expression of multiple genes. PMID:25504733

Human Heart Mitochondrial DNA Is Organized in Complex Catenated Networks Containing Abundant Four-way Junctions and Replication Forks*

PubMed Central

Pohjoismäki, Jaakko L. O.; Goffart, Steffi; Tyynismaa, Henna; Willcox, Smaranda; Ide, Tomomi; Kang, Dongchon; Suomalainen, Anu; Karhunen, Pekka J.; Griffith, Jack D.; Holt, Ian J.; Jacobs, Howard T.

2009-01-01

Analysis of human heart mitochondrial DNA (mtDNA) by electron microscopy and agarose gel electrophoresis revealed a complete absence of the θ-type replication intermediates seen abundantly in mtDNA from all other tissues. Instead only Y- and X-junctional forms were detected after restriction digestion. Uncut heart mtDNA was organized in tangled complexes of up to 20 or more genome equivalents, which could be resolved to genomic monomers, dimers, and linear fragments by treatment with the decatenating enzyme topoisomerase IV plus the cruciform-cutting T7 endonuclease I. Human and mouse brain also contained a population of such mtDNA forms, which were absent, however, from mouse, rabbit, or pig heart. Overexpression in transgenic mice of two proteins involved in mtDNA replication, namely human mitochondrial transcription factor A or the mouse Twinkle DNA helicase, generated abundant four-way junctions in mtDNA of heart, brain, and skeletal muscle. The organization of mtDNA of human heart as well as of mouse and human brain in complex junctional networks replicating via a presumed non-θ mechanism is unprecedented in mammals. PMID:19525233

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

PubMed

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

2017-08-30

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

Researching and Reducing the Health Burden of Stroke

MedlinePlus

... the result of continuing research to map the brain and interface it with a computer to enable stroke patients to regain function. How important is the new effort to map the human brain? The brain is more complex than any computer ...

Progress in Application of the Neurosciences to an Understanding of Human Learning: The Challenge of Finding a Middle-Ground Neuroeducational Theory

ERIC Educational Resources Information Center

Anderson, O. Roger

2014-01-01

Modern neuroscientific research has substantially enhanced our understanding of the human brain. However, many challenges remain in developing a strong, brain-based theory of human learning, especially in complex environments such as educational settings. Some of the current issues and challenges in our progress toward developing comprehensive…

Toward a 3D model of human brain development for studying gene/environment interactions

PubMed Central

2013-01-01

This project aims to establish and characterize an in vitro model of the developing human brain for the purpose of testing drugs and chemicals. To accurately assess risk, a model needs to recapitulate the complex interactions between different types of glial cells and neurons in a three-dimensional platform. Moreover, human cells are preferred over cells from rodents to eliminate cross-species differences in sensitivity to chemicals. Previously, we established conditions to culture rat primary cells as three-dimensional aggregates, which will be humanized and evaluated here with induced pluripotent stem cells (iPSCs). The use of iPSCs allows us to address gene/environment interactions as well as the potential of chemicals to interfere with epigenetic mechanisms. Additionally, iPSCs afford us the opportunity to study the effect of chemicals during very early stages of brain development. It is well recognized that assays for testing toxicity in the developing brain must consider differences in sensitivity and susceptibility that arise depending on the time of exposure. This model will reflect critical developmental processes such as proliferation, differentiation, lineage specification, migration, axonal growth, dendritic arborization and synaptogenesis, which will probably display differences in sensitivity to different types of chemicals. Functional endpoints will evaluate the complex cell-to-cell interactions that are affected in neurodevelopment through chemical perturbation, and the efficacy of drug intervention to prevent or reverse phenotypes. The model described is designed to assess developmental neurotoxicity effects on unique processes occurring during human brain development by leveraging human iPSCs from diverse genetic backgrounds, which can be differentiated into different cell types of the central nervous system. Our goal is to demonstrate the feasibility of the personalized model using iPSCs derived from individuals with neurodevelopmental disorders caused by known mutations and chromosomal aberrations. Notably, such a human brain model will be a versatile tool for more complex testing platforms and strategies as well as research into central nervous system physiology and pathology. PMID:24564953

Glutathione in the human brain: Review of its roles and measurement by magnetic resonance spectroscopy.

PubMed

Rae, Caroline D; Williams, Stephen R

2017-07-15

We review the transport, synthesis and catabolism of glutathione in the brain as well as its compartmentation and biochemistry in different brain cells. The major reactions involving glutathione are reviewed and the factors limiting its availability in brain cells are discussed. We also describe and critique current methods for measuring glutathione in the human brain using magnetic resonance spectroscopy, and review the literature on glutathione measurements in healthy brains and in neurological, psychiatric, neurodegenerative and neurodevelopmental conditions In summary: Healthy human brain glutathione concentration is ∼1-2 mM, but it varies by brain region, with evidence of gender differences and age effects; in neurological disease glutathione appears reduced in multiple sclerosis, motor neurone disease and epilepsy, while being increased in meningiomas; in psychiatric disease the picture is complex and confounded by methodological differences, regional effects, length of disease and drug-treatment. Both increases and decreases in glutathione have been reported in depression and schizophrenia. In Alzheimer's disease and mild cognitive impairment there is evidence for a decrease in glutathione compared to age-matched healthy controls. Improved methods to measure glutathione in vivo will provide better precision in glutathione determination and help resolve the complex biochemistry of this molecule in health and disease. Copyright © 2017 Elsevier Inc. All rights reserved.

Hemispherical map for the human brain cortex

NASA Astrophysics Data System (ADS)

Tosun, Duygu; Prince, Jerry L.

2001-07-01

Understanding the function of the human brain cortex is a primary goal in human brain mapping. Methods to unfold and flatten the cortical surface for visualization and measurement have been described in previous literature; but comparison across multiple subjects is still difficult because of the lack of a standard mapping technique. We describe a new approach that maps each hemisphere of the cortex to a portion of a sphere in a standard way, making comparison of anatomy and function across different subjects possible. Starting with a three-dimensional magnetic resonance image of the brain, the cortex is segmented and represented as a triangle mesh. Defining a cut around the corpus collosum identifies the left and right hemispheres. Together, the two hemispheres are mapped to the complex plane using a conformal mapping technique. A Mobius transformation, which is conformal, is used to transform the points on the complex plane so that a projective transformation maps each brain hemisphere onto a spherical segment comprising a sphere with a cap removed. We determined the best size of the spherical cap by minimizing the relative area distortion between hemispherical maps and original cortical surfaces. The relative area distortion between the hemispherical maps and the original cortical surfaces for fifteen human brains is analyzed.

Functional complexity emerging from anatomical constraints in the brain: the significance of network modularity and rich-clubs

NASA Astrophysics Data System (ADS)

Zamora-López, Gorka; Chen, Yuhan; Deco, Gustavo; Kringelbach, Morten L.; Zhou, Changsong

2016-12-01

The large-scale structural ingredients of the brain and neural connectomes have been identified in recent years. These are, similar to the features found in many other real networks: the arrangement of brain regions into modules and the presence of highly connected regions (hubs) forming rich-clubs. Here, we examine how modules and hubs shape the collective dynamics on networks and we find that both ingredients lead to the emergence of complex dynamics. Comparing the connectomes of C. elegans, cats, macaques and humans to surrogate networks in which either modules or hubs are destroyed, we find that functional complexity always decreases in the perturbed networks. A comparison between simulated and empirically obtained resting-state functional connectivity indicates that the human brain, at rest, lies in a dynamical state that reflects the largest complexity its anatomical connectome can host. Last, we generalise the topology of neural connectomes into a new hierarchical network model that successfully combines modular organisation with rich-club forming hubs. This is achieved by centralising the cross-modular connections through a preferential attachment rule. Our network model hosts more complex dynamics than other hierarchical models widely used as benchmarks.

Functional complexity emerging from anatomical constraints in the brain: the significance of network modularity and rich-clubs

PubMed Central

Zamora-López, Gorka; Chen, Yuhan; Deco, Gustavo; Kringelbach, Morten L.; Zhou, Changsong

2016-01-01

The large-scale structural ingredients of the brain and neural connectomes have been identified in recent years. These are, similar to the features found in many other real networks: the arrangement of brain regions into modules and the presence of highly connected regions (hubs) forming rich-clubs. Here, we examine how modules and hubs shape the collective dynamics on networks and we find that both ingredients lead to the emergence of complex dynamics. Comparing the connectomes of C. elegans, cats, macaques and humans to surrogate networks in which either modules or hubs are destroyed, we find that functional complexity always decreases in the perturbed networks. A comparison between simulated and empirically obtained resting-state functional connectivity indicates that the human brain, at rest, lies in a dynamical state that reflects the largest complexity its anatomical connectome can host. Last, we generalise the topology of neural connectomes into a new hierarchical network model that successfully combines modular organisation with rich-club forming hubs. This is achieved by centralising the cross-modular connections through a preferential attachment rule. Our network model hosts more complex dynamics than other hierarchical models widely used as benchmarks. PMID:27917958

Decoding Lifespan Changes of the Human Brain Using Resting-State Functional Connectivity MRI

PubMed Central

Wang, Lubin; Su, Longfei; Shen, Hui; Hu, Dewen

2012-01-01

The development of large-scale functional brain networks is a complex, lifelong process that can be investigated using resting-state functional connectivity MRI (rs-fcMRI). In this study, we aimed to decode the developmental dynamics of the whole-brain functional network in seven decades (8–79 years) of the human lifespan. We first used parametric curve fitting to examine linear and nonlinear age effect on the resting human brain, and then combined manifold learning and support vector machine methods to predict individuals' “brain ages” from rs-fcMRI data. We found that age-related changes in interregional functional connectivity exhibited spatially and temporally specific patterns. During brain development from childhood to senescence, functional connections tended to linearly increase in the emotion system and decrease in the sensorimotor system; while quadratic trajectories were observed in functional connections related to higher-order cognitive functions. The complex patterns of age effect on the whole-brain functional network could be effectively represented by a low-dimensional, nonlinear manifold embedded in the functional connectivity space, which uncovered the inherent structure of brain maturation and aging. Regression of manifold coordinates with age further showed that the manifold representation extracted sufficient information from rs-fcMRI data to make prediction about individual brains' functional development levels. Our study not only gives insights into the neural substrates that underlie behavioral and cognitive changes over age, but also provides a possible way to quantitatively describe the typical and atypical developmental progression of human brain function using rs-fcMRI. PMID:22952990

Decoding lifespan changes of the human brain using resting-state functional connectivity MRI.

PubMed

Wang, Lubin; Su, Longfei; Shen, Hui; Hu, Dewen

2012-01-01

The development of large-scale functional brain networks is a complex, lifelong process that can be investigated using resting-state functional connectivity MRI (rs-fcMRI). In this study, we aimed to decode the developmental dynamics of the whole-brain functional network in seven decades (8-79 years) of the human lifespan. We first used parametric curve fitting to examine linear and nonlinear age effect on the resting human brain, and then combined manifold learning and support vector machine methods to predict individuals' "brain ages" from rs-fcMRI data. We found that age-related changes in interregional functional connectivity exhibited spatially and temporally specific patterns. During brain development from childhood to senescence, functional connections tended to linearly increase in the emotion system and decrease in the sensorimotor system; while quadratic trajectories were observed in functional connections related to higher-order cognitive functions. The complex patterns of age effect on the whole-brain functional network could be effectively represented by a low-dimensional, nonlinear manifold embedded in the functional connectivity space, which uncovered the inherent structure of brain maturation and aging. Regression of manifold coordinates with age further showed that the manifold representation extracted sufficient information from rs-fcMRI data to make prediction about individual brains' functional development levels. Our study not only gives insights into the neural substrates that underlie behavioral and cognitive changes over age, but also provides a possible way to quantitatively describe the typical and atypical developmental progression of human brain function using rs-fcMRI.

Neuronal correlates of the five factor model (FFM) of human personality: Multimodal imaging in a large healthy sample.

PubMed

Bjørnebekk, Astrid; Fjell, Anders M; Walhovd, Kristine B; Grydeland, Håkon; Torgersen, Svenn; Westlye, Lars T

2013-01-15

Advances in neuroimaging techniques have recently provided glimpse into the neurobiology of complex traits of human personality. Whereas some intriguing findings have connected aspects of personality to variations in brain morphology, the relations are complex and our current understanding is incomplete. Therefore, we aimed to provide a comprehensive investigation of brain-personality relations using a multimodal neuroimaging approach in a large sample comprising 265 healthy individuals. The NEO Personality Inventory was used to provide measures of core aspects of human personality, and imaging phenotypes included measures of total and regional brain volumes, regional cortical thickness and arealization, and diffusion tensor imaging indices of white matter (WM) microstructure. Neuroticism was the trait most clearly linked to brain structure. Higher neuroticism including facets reflecting anxiety, depression and vulnerability to stress was associated with smaller total brain volume, widespread decrease in WM microstructure, and smaller frontotemporal surface area. Higher scores on extraversion were associated with thinner inferior frontal gyrus, and conscientiousness was negatively associated with arealization of the temporoparietal junction. No reliable associations between brain structure and agreeableness and openness, respectively, were found. The results provide novel evidence of the associations between brain structure and variations in human personality, and corroborate previous findings of a consistent neuroanatomical basis of negative emotionality. Copyright © 2012 Elsevier Inc. All rights reserved.

Brain Dynamics: Methodological Issues and Applications in Psychiatric and Neurologic Diseases

NASA Astrophysics Data System (ADS)

Pezard, Laurent

The human brain is a complex dynamical system generating the EEG signal. Numerical methods developed to study complex physical dynamics have been used to characterize EEG since the mid-eighties. This endeavor raised several issues related to the specificity of EEG. Firstly, theoretical and methodological studies should address the major differences between the dynamics of the human brain and physical systems. Secondly, this approach of EEG signal should prove to be relevant for dealing with physiological or clinical problems. A set of studies performed in our group is presented here within the context of these two problematic aspects. After the discussion of methodological drawbacks, we review numerical simulations related to the high dimension and spatial extension of brain dynamics. Experimental studies in neurologic and psychiatric disease are then presented. We conclude that if it is now clear that brain dynamics changes in relation with clinical situations, methodological problems remain largely unsolved.

Human brain activity with functional NIR optical imager

NASA Astrophysics Data System (ADS)

Luo, Qingming

2001-08-01

In this paper we reviewed the applications of functional near infrared optical imager in human brain activity. Optical imaging results of brain activity, including memory for new association, emotional thinking, mental arithmetic, pattern recognition ' where's Waldo?, occipital cortex in visual stimulation, and motor cortex in finger tapping, are demonstrated. It is shown that the NIR optical method opens up new fields of study of the human population, in adults under conditions of simulated or real stress that may have important effects upon functional performance. It makes practical and affordable for large populations the complex technology of measuring brain function. It is portable and low cost. In cognitive tasks subjects could report orally. The temporal resolution could be millisecond or less in theory. NIR method will have good prospects in exploring human brain secret.

Intergenerational Neuroimaging of Human Brain Circuitry

PubMed Central

Ho, Tiffany C.; Sanders, Stephan J.; Gotlib, Ian H.; Hoeft, Fumiko

2016-01-01

Neuroscientists are increasingly using advanced neuroimaging methods to elucidate the intergenerational transmission of human brain circuitry. This new line of work promises to shed insight into the ontogeny of complex behavioral traits, including psychiatric disorders, and possible mechanisms of transmission. Here, we highlight recent intergenerational neuroimaging studies and provide recommendations for future work. PMID:27623194

Primary Cortical Folding in the Human Newborn: An Early Marker of Later Functional Development

ERIC Educational Resources Information Center

Dubois, J.; Benders, M.; Borradori-Tolsa, C.; Cachia, A.; Lazeyras, F.; Leuchter, R. Ha-Vinh; Sizonenko, S. V.; Warfield, S. K.; Mangin, J. F.; Huppi, P. S.

2008-01-01

In the human brain, the morphology of cortical gyri and sulci is complex and variable among individuals, and it may reflect pathological functioning with specific abnormalities observed in certain developmental and neuropsychiatric disorders. Since cortical folding occurs early during brain development, these structural abnormalities might be…

How Language Learners Can Improve Their Emotional Functioning: Important Psychological and Psychospiritual Theories

ERIC Educational Resources Information Center

Oxford, Rebecca L.

2015-01-01

Emotion is "the primary human motive" (MacIntyre, 2002, p. 61). The human brain is an emotional brain, creating relationships among thought, emotion, and motivation in a complex dynamic system (Dörnyei, 2009). Emotion "functions as an amplifier, providing the intensity, urgency, and energy to propel our behavior" in…

Is the ferret a suitable species for studying perinatal brain injury?

PubMed Central

Empie, Kristen; Rangarajan, Vijayeta; Juul, Sandra E.

2016-01-01

Complications of prematurity often disrupt normal brain development and/or cause direct damage to the developing brain, resulting in poor neurodevelopmental outcomes. Physiologically relevant animal models of perinatal brain injury can advance our understanding of these influences and thereby provide opportunities to develop therapies and improve long-term outcomes. While there are advantages to currently available small animal models, there are also significant drawbacks that have limited translation of research findings to humans. Large animal models such as newborn pig, sheep and nonhuman primates have complex brain development more similar to humans, but these animals are expensive, and developmental testing of sheep and piglets is limited. Ferrets (Mustela putorius furo) are born lissencephalic and undergo postnatal cortical folding to form complex gyrencephalic brains. This review examines whether ferrets might provide a novel intermediate animal model of neonatal brain disease that has the benefit of a gyrified, altricial brain in a small animal. It summarizes attributes of ferret brain growth and development that make it an appealing animal in which to model perinatal brain injury. We postulate that because of their innate characteristics, ferrets have great potential in neonatal neurodevelopmental studies. PMID:26102988

Disrupted Small-World Networks in Schizophrenia

ERIC Educational Resources Information Center

Liu, Yong; Liang, Meng; Zhou, Yuan; He, Yong; Hao, Yihui; Song, Ming; Yu, Chunshui; Liu, Haihong; Liu, Zhening; Jiang, Tianzi

2008-01-01

The human brain has been described as a large, sparse, complex network characterized by efficient small-world properties, which assure that the brain generates and integrates information with high efficiency. Many previous neuroimaging studies have provided consistent evidence of "dysfunctional connectivity" among the brain regions in…

Neuronal Correlation Parameter and the Idea of Thermodynamic Entropy of an N-Body Gravitationally Bounded System.

PubMed

Haranas, Ioannis; Gkigkitzis, Ioannis; Kotsireas, Ilias; Austerlitz, Carlos

2017-01-01

Understanding how the brain encodes information and performs computation requires statistical and functional analysis. Given the complexity of the human brain, simple methods that facilitate the interpretation of statistical correlations among different brain regions can be very useful. In this report we introduce a numerical correlation measure that may serve the interpretation of correlational neuronal data, and may assist in the evaluation of different brain states. The description of the dynamical brain system, through a global numerical measure may indicate the presence of an action principle which may facilitate a application of physics principles in the study of the human brain and cognition.

How cortical neurons help us see: visual recognition in the human brain

PubMed Central

Blumberg, Julie; Kreiman, Gabriel

2010-01-01

Through a series of complex transformations, the pixel-like input to the retina is converted into rich visual perceptions that constitute an integral part of visual recognition. Multiple visual problems arise due to damage or developmental abnormalities in the cortex of the brain. Here, we provide an overview of how visual information is processed along the ventral visual cortex in the human brain. We discuss how neurophysiological recordings in macaque monkeys and in humans can help us understand the computations performed by visual cortex. PMID:20811161

Cell diversity and network dynamics in photosensitive human brain organoids

PubMed Central

Quadrato, Giorgia; Nguyen, Tuan; Macosko, Evan Z.; Sherwood, John L.; Yang, Sung Min; Berger, Daniel; Maria, Natalie; Scholvin, Jorg; Goldman, Melissa; Kinney, Justin; Boyden, Edward S.; Lichtman, Jeff; Williams, Ziv M.; McCarroll, Steven A.; Arlotta, Paola

2017-01-01

In vitro models of the developing brain such as 3D brain organoids offer an unprecedented opportunity to study aspects of human brain development and disease. However, it remains undefined what cells are generated within organoids and to what extent they recapitulate the regional complexity, cellular diversity, and circuit functionality of the brain. Here, we analyzed gene expression in over 80,000 individual cells isolated from 31 human brain organoids. We find that organoids can generate a broad diversity of cells, which are related to endogenous classes, including cells from the cerebral cortex and the retina. Organoids could be developed over extended periods (over 9 months) enabling unprecedented levels of maturity including the formation of dendritic spines and of spontaneously-active neuronal networks. Finally, neuronal activity within organoids could be controlled using light stimulation of photoreceptor-like cells, which may offer ways to probe the functionality of human neuronal circuits using physiological sensory stimuli. PMID:28445462

Cell diversity and network dynamics in photosensitive human brain organoids.

PubMed

Quadrato, Giorgia; Nguyen, Tuan; Macosko, Evan Z; Sherwood, John L; Min Yang, Sung; Berger, Daniel R; Maria, Natalie; Scholvin, Jorg; Goldman, Melissa; Kinney, Justin P; Boyden, Edward S; Lichtman, Jeff W; Williams, Ziv M; McCarroll, Steven A; Arlotta, Paola

2017-05-04

In vitro models of the developing brain such as three-dimensional brain organoids offer an unprecedented opportunity to study aspects of human brain development and disease. However, the cells generated within organoids and the extent to which they recapitulate the regional complexity, cellular diversity and circuit functionality of the brain remain undefined. Here we analyse gene expression in over 80,000 individual cells isolated from 31 human brain organoids. We find that organoids can generate a broad diversity of cells, which are related to endogenous classes, including cells from the cerebral cortex and the retina. Organoids could be developed over extended periods (more than 9 months), allowing for the establishment of relatively mature features, including the formation of dendritic spines and spontaneously active neuronal networks. Finally, neuronal activity within organoids could be controlled using light stimulation of photosensitive cells, which may offer a way to probe the functionality of human neuronal circuits using physiological sensory stimuli.

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

The Human Brainnetome Atlas: A New Brain Atlas Based on Connectional Architecture.

PubMed

Fan, Lingzhong; Li, Hai; Zhuo, Junjie; Zhang, Yu; Wang, Jiaojian; Chen, Liangfu; Yang, Zhengyi; Chu, Congying; Xie, Sangma; Laird, Angela R; Fox, Peter T; Eickhoff, Simon B; Yu, Chunshui; Jiang, Tianzi

2016-08-01

The human brain atlases that allow correlating brain anatomy with psychological and cognitive functions are in transition from ex vivo histology-based printed atlases to digital brain maps providing multimodal in vivo information. Many current human brain atlases cover only specific structures, lack fine-grained parcellations, and fail to provide functionally important connectivity information. Using noninvasive multimodal neuroimaging techniques, we designed a connectivity-based parcellation framework that identifies the subdivisions of the entire human brain, revealing the in vivo connectivity architecture. The resulting human Brainnetome Atlas, with 210 cortical and 36 subcortical subregions, provides a fine-grained, cross-validated atlas and contains information on both anatomical and functional connections. Additionally, we further mapped the delineated structures to mental processes by reference to the BrainMap database. It thus provides an objective and stable starting point from which to explore the complex relationships between structure, connectivity, and function, and eventually improves understanding of how the human brain works. The human Brainnetome Atlas will be made freely available for download at http://atlas.brainnetome.org, so that whole brain parcellations, connections, and functional data will be readily available for researchers to use in their investigations into healthy and pathological states. © The Author 2016. Published by Oxford University Press.

Biochemical Fractionation and Stable Isotope Dilution Liquid Chromatography-mass Spectrometry for Targeted and Microdomain-specific Protein Quantification in Human Postmortem Brain Tissue*

PubMed Central

MacDonald, Matthew L.; Ciccimaro, Eugene; Prakash, Amol; Banerjee, Anamika; Seeholzer, Steven H.; Blair, Ian A.; Hahn, Chang-Gyu

2012-01-01

Synaptic architecture and its adaptive changes require numerous molecular events that are both highly ordered and complex. A majority of neuropsychiatric illnesses are complex trait disorders, in which multiple etiologic factors converge at the synapse via many signaling pathways. Investigating the protein composition of synaptic microdomains from human patient brain tissues will yield valuable insights into the interactions of risk genes in many disorders. These types of studies in postmortem tissues have been limited by the lack of proper study paradigms. Thus, it is necessary not only to develop strategies to quantify protein and post-translational modifications at the synapse, but also to rigorously validate them for use in postmortem human brain tissues. In this study we describe the development of a liquid chromatography-selected reaction monitoring method, using a stable isotope-labeled neuronal proteome standard prepared from the brain tissue of a stable isotope-labeled mouse, for the multiplexed quantification of target synaptic proteins in mammalian samples. Additionally, we report the use of this method to validate a biochemical approach for the preparation of synaptic microdomain enrichments from human postmortem prefrontal cortex. Our data demonstrate that a targeted mass spectrometry approach with a true neuronal proteome standard facilitates accurate and precise quantification of over 100 synaptic proteins in mammalian samples, with the potential to quantify over 1000 proteins. Using this method, we found that protein enrichments in subcellular fractions prepared from human postmortem brain tissue were strikingly similar to those prepared from fresh mouse brain tissue. These findings demonstrate that biochemical fractionation methods paired with targeted proteomic strategies can be used in human brain tissues, with important implications for the study of neuropsychiatric disease. PMID:22942359

On the nature and evolution of the neural bases of human language

NASA Technical Reports Server (NTRS)

Lieberman, Philip

2002-01-01

The traditional theory equating the brain bases of language with Broca's and Wernicke's neocortical areas is wrong. Neural circuits linking activity in anatomically segregated populations of neurons in subcortical structures and the neocortex throughout the human brain regulate complex behaviors such as walking, talking, and comprehending the meaning of sentences. When we hear or read a word, neural structures involved in the perception or real-world associations of the word are activated as well as posterior cortical regions adjacent to Wernicke's area. Many areas of the neocortex and subcortical structures support the cortical-striatal-cortical circuits that confer complex syntactic ability, speech production, and a large vocabulary. However, many of these structures also form part of the neural circuits regulating other aspects of behavior. For example, the basal ganglia, which regulate motor control, are also crucial elements in the circuits that confer human linguistic ability and abstract reasoning. The cerebellum, traditionally associated with motor control, is active in motor learning. The basal ganglia are also key elements in reward-based learning. Data from studies of Broca's aphasia, Parkinson's disease, hypoxia, focal brain damage, and a genetically transmitted brain anomaly (the putative "language gene," family KE), and from comparative studies of the brains and behavior of other species, demonstrate that the basal ganglia sequence the discrete elements that constitute a complete motor act, syntactic process, or thought process. Imaging studies of intact human subjects and electrophysiologic and tracer studies of the brains and behavior of other species confirm these findings. As Dobzansky put it, "Nothing in biology makes sense except in the light of evolution" (cited in Mayr, 1982). That applies with as much force to the human brain and the neural bases of language as it does to the human foot or jaw. The converse follows: the mark of evolution on the brains of human beings and other species provides insight into the evolution of the brain bases of human language. The neural substrate that regulated motor control in the common ancestor of apes and humans most likely was modified to enhance cognitive and linguistic ability. Speech communication played a central role in this process. However, the process that ultimately resulted in the human brain may have started when our earliest hominid ancestors began to walk.

Accelerated recruitment of new brain development genes into the human genome.

PubMed

Zhang, Yong E; Landback, Patrick; Vibranovski, Maria D; Long, Manyuan

2011-10-01

How the human brain evolved has attracted tremendous interests for decades. Motivated by case studies of primate-specific genes implicated in brain function, we examined whether or not the young genes, those emerging genome-wide in the lineages specific to the primates or rodents, showed distinct spatial and temporal patterns of transcription compared to old genes, which had existed before primate and rodent split. We found consistent patterns across different sources of expression data: there is a significantly larger proportion of young genes expressed in the fetal or infant brain of humans than in mouse, and more young genes in humans have expression biased toward early developing brains than old genes. Most of these young genes are expressed in the evolutionarily newest part of human brain, the neocortex. Remarkably, we also identified a number of human-specific genes which are expressed in the prefrontal cortex, which is implicated in complex cognitive behaviors. The young genes upregulated in the early developing human brain play diverse functional roles, with a significant enrichment of transcription factors. Genes originating from different mechanisms show a similar expression bias in the developing brain. Moreover, we found that the young genes upregulated in early brain development showed rapid protein evolution compared to old genes also expressed in the fetal brain. Strikingly, genes expressed in the neocortex arose soon after its morphological origin. These four lines of evidence suggest that positive selection for brain function may have contributed to the origination of young genes expressed in the developing brain. These data demonstrate a striking recruitment of new genes into the early development of the human brain.

Characteristics of allelic gene expression in human brain cells from single-cell RNA-seq data analysis.

PubMed

Zhao, Dejian; Lin, Mingyan; Pedrosa, Erika; Lachman, Herbert M; Zheng, Deyou

2017-11-10

Monoallelic expression of autosomal genes has been implicated in human psychiatric disorders. However, there is a paucity of allelic expression studies in human brain cells at the single cell and genome wide levels. In this report, we reanalyzed a previously published single-cell RNA-seq dataset from several postmortem human brains and observed pervasive monoallelic expression in individual cells, largely in a random manner. Examining single nucleotide variants with a predicted functional disruption, we found that the "damaged" alleles were overall expressed in fewer brain cells than their counterparts, and at a lower level in cells where their expression was detected. We also identified many brain cell type-specific monoallelically expressed genes. Interestingly, many of these cell type-specific monoallelically expressed genes were enriched for functions important for those brain cell types. In addition, function analysis showed that genes displaying monoallelic expression and correlated expression across neuronal cells from different individual brains were implicated in the regulation of synaptic function. Our findings suggest that monoallelic gene expression is prevalent in human brain cells, which may play a role in generating cellular identity and neuronal diversity and thus increasing the complexity and diversity of brain cell functions.

The evolution of the complex sensory and motor systems of the human brain.

PubMed

Kaas, Jon H

2008-03-18

Inferences about how the complex sensory and motor systems of the human brain evolved are based on the results of comparative studies of brain organization across a range of mammalian species, and evidence from the endocasts of fossil skulls of key extinct species. The endocasts of the skulls of early mammals indicate that they had small brains with little neocortex. Evidence from comparative studies of cortical organization from small-brained mammals of the six major branches of mammalian evolution supports the conclusion that the small neocortex of early mammals was divided into roughly 20-25 cortical areas, including primary and secondary sensory fields. In early primates, vision was the dominant sense, and cortical areas associated with vision in temporal and occipital cortex underwent a significant expansion. Comparative studies indicate that early primates had 10 or more visual areas, and somatosensory areas with expanded representations of the forepaw. Posterior parietal cortex was also expanded, with a caudal half dominated by visual inputs, and a rostral half dominated by somatosensory inputs with outputs to an array of seven or more motor and visuomotor areas of the frontal lobe. Somatosensory areas and posterior parietal cortex became further differentiated in early anthropoid primates. As larger brains evolved in early apes and in our hominin ancestors, the number of cortical areas increased to reach an estimated 200 or so in present day humans, and hemispheric specializations emerged. The large human brain grew primarily by increasing neuron number rather than increasing average neuron size.

Complexity and multifractality of neuronal noise in mouse and human hippocampal epileptiform dynamics

NASA Astrophysics Data System (ADS)

Serletis, Demitre; Bardakjian, Berj L.; Valiante, Taufik A.; Carlen, Peter L.

2012-10-01

Fractal methods offer an invaluable means of investigating turbulent nonlinearity in non-stationary biomedical recordings from the brain. Here, we investigate properties of complexity (i.e. the correlation dimension, maximum Lyapunov exponent, 1/fγ noise and approximate entropy) and multifractality in background neuronal noise-like activity underlying epileptiform transitions recorded at the intracellular and local network scales from two in vitro models: the whole-intact mouse hippocampus and lesional human hippocampal slices. Our results show evidence for reduced dynamical complexity and multifractal signal features following transition to the ictal epileptiform state. These findings suggest that pathological breakdown in multifractal complexity coincides with loss of signal variability or heterogeneity, consistent with an unhealthy ictal state that is far from the equilibrium of turbulent yet healthy fractal dynamics in the brain. Thus, it appears that background noise-like activity successfully captures complex and multifractal signal features that may, at least in part, be used to classify and identify brain state transitions in the healthy and epileptic brain, offering potential promise for therapeutic neuromodulatory strategies for afflicted patients suffering from epilepsy and other related neurological disorders. This paper is based on chapter 5 of Serletis (2010 PhD Dissertation Department of Physiology, Institute of Biomaterials and Biomedical Engineering, University of Toronto).

Logical Interactions in AN Expanded Space

NASA Astrophysics Data System (ADS)

Tadić, Bosiljka

Understanding the emergent behavior in many complex systems in the physical world and society requires a detailed study of dynamical phenomena occurring and mutually coupled at different scales. The brain processes underlying the social conduct of each, and the emergent social behavior of interacting individuals on a larger scale, represent striking examples of the multiscale complexity. Studies of the human brain, a paradigm of a complex functional system, are enabled by a wealth of brain imaging data that provide clues of how we comprehend space, time, languages, numbers, and differentiate normal from diseased individuals, for example. The social brain, a neural basis for social cognition, represents a dynamically organized part of the brain which is involved in the inference of thoughts, feelings, and intentions going on in the brains of others. Research in this currently unexplored area opens a new perspective on the genesis of the societal organization at different levels and the associated social values...

Functional organization of the transcriptome in human brain

PubMed Central

Oldham, Michael C; Konopka, Genevieve; Iwamoto, Kazuya; Langfelder, Peter; Kato, Tadafumi; Horvath, Steve; Geschwind, Daniel H

2009-01-01

The enormous complexity of the human brain ultimately derives from a finite set of molecular instructions encoded in the human genome. These instructions can be directly studied by exploring the organization of the brain’s transcriptome through systematic analysis of gene coexpression relationships. We analyzed gene coexpression relationships in microarray data generated from specific human brain regions and identified modules of coexpressed genes that correspond to neurons, oligodendrocytes, astrocytes and microglia. These modules provide an initial description of the transcriptional programs that distinguish the major cell classes of the human brain and indicate that cell type–specific information can be obtained from whole brain tissue without isolating homogeneous populations of cells. Other modules corresponded to additional cell types, organelles, synaptic function, gender differences and the subventricular neurogenic niche. We found that subventricular zone astrocytes, which are thought to function as neural stem cells in adults, have a distinct gene expression pattern relative to protoplasmic astrocytes. Our findings provide a new foundation for neurogenetic inquiries by revealing a robust and previously unrecognized organization to the human brain transcriptome. PMID:18849986

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.

Dynamic Multi-Coil Shimming of the Human Brain at 7 Tesla

PubMed Central

Juchem, Christoph; Nixon, Terence W.; McIntyre, Scott; Boer, Vincent O.; Rothman, Douglas L.; de Graaf, Robin A.

2011-01-01

High quality magnetic field homogenization of the human brain (i.e. shimming) for MR imaging and spectroscopy is a demanding task. The susceptibility differences between air and tissue are a longstanding problem as they induce complex field distortions in the prefrontal cortex and the temporal lobes. To date, the theoretical gains of high field MR have only been realized partially in the human brain due to limited magnetic field homogeneity. A novel shimming technique for the human brain is presented that is based on the combination of non-orthogonal basis fields from 48 individual, circular coils. Custom-built amplifier electronics enabled the dynamic application of the multi-coil shim fields in a slice-specific fashion. Dynamic multi-coil (DMC) shimming is shown to eliminate most of the magnetic field inhomogeneity apparent in the human brain at 7 Tesla and provided improved performance compared to state-of-the-art dynamic shim updating with zero through third order spherical harmonic functions. The novel technique paves the way for high field MR applications of the human brain for which excellent magnetic field homogeneity is a prerequisite. PMID:21824794

Biological and medical applications of a brain-on-a-chip

PubMed Central

2016-01-01

The desire to develop and evaluate drugs as potential countermeasures for biological and chemical threats requires test systems that can also substitute for the clinical trials normally crucial for drug development. Current animal models have limited predictivity for drug efficacy in humans as the large majority of drugs fails in clinical trials. We have limited understanding of the function of the central nervous system and the complexity of the brain, especially during development and neuronal plasticity. Simple in vitro systems do not represent physiology and function of the brain. Moreover, the difficulty of studying interactions between human genetics and environmental factors leads to lack of knowledge about the events that induce neurological diseases. Microphysiological systems (MPS) promise to generate more complex in vitro human models that better simulate the organ’s biology and function. MPS combine different cell types in a specific three-dimensional (3D) configuration to simulate organs with a concrete function. The final aim of these MPS is to combine different “organoids” to generate a human-on-a-chip, an approach that would allow studies of complex physiological organ interactions. The recent discovery of induced pluripotent stem cells (iPSCs) gives a range of possibilities allowing cellular studies of individuals with different genetic backgrounds (e.g., human disease models). Application of iPSCs from different donors in MPS gives the opportunity to better understand mechanisms of the disease and can be a novel tool in drug development, toxicology, and medicine. In order to generate a brain-on-a-chip, we have established a 3D model from human iPSCs based on our experience with a 3D rat primary aggregating brain model. After four weeks of differentiation, human 3D aggregates stain positive for different neuronal markers and show higher gene expression of various neuronal differentiation markers compared to 2D cultures. Here we present the applications and challenges of this emerging technology. PMID:24912505

Imaging of Cerebral Amyloid Angiopathy with Bivalent 99mTc-Hydroxamamide Complexes

NASA Astrophysics Data System (ADS)

Iikuni, Shimpei; Ono, Masahiro; Watanabe, Hiroyuki; Matsumura, Kenji; Yoshimura, Masashi; Kimura, Hiroyuki; Ishibashi-Ueda, Hatsue; Okamoto, Yoko; Ihara, Masafumi; Saji, Hideo

2016-05-01

Cerebral amyloid angiopathy (CAA), characterized by the deposition of amyloid aggregates in the walls of cerebral vasculature, is a major factor in intracerebral hemorrhage and vascular cognitive impairment and is also associated closely with Alzheimer’s disease (AD). We previously reported 99mTc-hydroxamamide (99mTc-Ham) complexes with a bivalent amyloid ligand showing high binding affinity for β-amyloid peptide (Aβ(1-42)) aggregates present frequently in the form in AD. In this article, we applied them to CAA-specific imaging probes, and evaluated their utility for CAA-specific imaging. In vitro inhibition assay using Aβ(1-40) aggregates deposited mainly in CAA and a brain uptake study were performed for 99mTc-Ham complexes, and all 99mTc-Ham complexes with an amyloid ligand showed binding affinity for Aβ(1-40) aggregates and very low brain uptake. In vitro autoradiography of human CAA brain sections and ex vivo autoradiography of Tg2576 mice were carried out for bivalent 99mTc-Ham complexes ([99mTc]SB2A and [99mTc]BT2B), and they displayed excellent labeling of Aβ depositions in human CAA brain sections and high affinity and selectivity to CAA in transgenic mice. These results may offer new possibilities for the development of clinically useful CAA-specific imaging probes based on the 99mTc-Ham complex.

Imaging of Cerebral Amyloid Angiopathy with Bivalent (99m)Tc-Hydroxamamide Complexes.

PubMed

Iikuni, Shimpei; Ono, Masahiro; Watanabe, Hiroyuki; Matsumura, Kenji; Yoshimura, Masashi; Kimura, Hiroyuki; Ishibashi-Ueda, Hatsue; Okamoto, Yoko; Ihara, Masafumi; Saji, Hideo

2016-05-16

Cerebral amyloid angiopathy (CAA), characterized by the deposition of amyloid aggregates in the walls of cerebral vasculature, is a major factor in intracerebral hemorrhage and vascular cognitive impairment and is also associated closely with Alzheimer's disease (AD). We previously reported (99m)Tc-hydroxamamide ((99m)Tc-Ham) complexes with a bivalent amyloid ligand showing high binding affinity for β-amyloid peptide (Aβ(1-42)) aggregates present frequently in the form in AD. In this article, we applied them to CAA-specific imaging probes, and evaluated their utility for CAA-specific imaging. In vitro inhibition assay using Aβ(1-40) aggregates deposited mainly in CAA and a brain uptake study were performed for (99m)Tc-Ham complexes, and all (99m)Tc-Ham complexes with an amyloid ligand showed binding affinity for Aβ(1-40) aggregates and very low brain uptake. In vitro autoradiography of human CAA brain sections and ex vivo autoradiography of Tg2576 mice were carried out for bivalent (99m)Tc-Ham complexes ([(99m)Tc]SB2A and [(99m)Tc]BT2B), and they displayed excellent labeling of Aβ depositions in human CAA brain sections and high affinity and selectivity to CAA in transgenic mice. These results may offer new possibilities for the development of clinically useful CAA-specific imaging probes based on the (99m)Tc-Ham complex.

Linking brain, mind and behavior.

PubMed

Makeig, Scott; Gramann, Klaus; Jung, Tzyy-Ping; Sejnowski, Terrence J; Poizner, Howard

2009-08-01

Cortical brain areas and dynamics evolved to organize motor behavior in our three-dimensional environment also support more general human cognitive processes. Yet traditional brain imaging paradigms typically allow and record only minimal participant behavior, then reduce the recorded data to single map features of averaged responses. To more fully investigate the complex links between distributed brain dynamics and motivated natural behavior, we propose the development of wearable mobile brain/body imaging (MoBI) systems that continuously capture the wearer's high-density electrical brain and muscle signals, three-dimensional body movements, audiovisual scene and point of regard, plus new data-driven analysis methods to model their interrelationships. The new imaging modality should allow new insights into how spatially distributed brain dynamics support natural human cognition and agency.

2015 Summer Series - Lee Stone - Brain Function Through the Eyes of the Beholder

NASA Image and Video Library

2015-06-09

The Visuomotor Control Laboratory (VCL) at NASA Ames conducts neuroscience research on the link between eye movements and brain function to provide an efficient and quantitative means of monitoring human perceptual performance. The VCL aims to make dramatic improvements in mission success through analysis, experimentation, and modeling of human performance and human-automation interaction. Dr. Lee Stone elaborates on how this research is conducted and how it contributes to NASA's mission and advances human-centered design and operations of complex aerospace systems.

Intersection of diverse neuronal genomes and neuropsychiatric disease: The Brain Somatic Mosaicism Network.

PubMed

McConnell, Michael J; Moran, John V; Abyzov, Alexej; Akbarian, Schahram; Bae, Taejeong; Cortes-Ciriano, Isidro; Erwin, Jennifer A; Fasching, Liana; Flasch, Diane A; Freed, Donald; Ganz, Javier; Jaffe, Andrew E; Kwan, Kenneth Y; Kwon, Minseok; Lodato, Michael A; Mills, Ryan E; Paquola, Apua C M; Rodin, Rachel E; Rosenbluh, Chaggai; Sestan, Nenad; Sherman, Maxwell A; Shin, Joo Heon; Song, Saera; Straub, Richard E; Thorpe, Jeremy; Weinberger, Daniel R; Urban, Alexander E; Zhou, Bo; Gage, Fred H; Lehner, Thomas; Senthil, Geetha; Walsh, Christopher A; Chess, Andrew; Courchesne, Eric; Gleeson, Joseph G; Kidd, Jeffrey M; Park, Peter J; Pevsner, Jonathan; Vaccarino, Flora M

2017-04-28

Neuropsychiatric disorders have a complex genetic architecture. Human genetic population-based studies have identified numerous heritable sequence and structural genomic variants associated with susceptibility to neuropsychiatric disease. However, these germline variants do not fully account for disease risk. During brain development, progenitor cells undergo billions of cell divisions to generate the ~80 billion neurons in the brain. The failure to accurately repair DNA damage arising during replication, transcription, and cellular metabolism amid this dramatic cellular expansion can lead to somatic mutations. Somatic mutations that alter subsets of neuronal transcriptomes and proteomes can, in turn, affect cell proliferation and survival and lead to neurodevelopmental disorders. The long life span of individual neurons and the direct relationship between neural circuits and behavior suggest that somatic mutations in small populations of neurons can significantly affect individual neurodevelopment. The Brain Somatic Mosaicism Network has been founded to study somatic mosaicism both in neurotypical human brains and in the context of complex neuropsychiatric disorders. Copyright © 2017, American Association for the Advancement of Science.

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.

Network Analysis: Applications for the Developing Brain

PubMed Central

Chu-Shore, Catherine J.; Kramer, Mark A.; Bianchi, Matt T.; Caviness, Verne S.; Cash, Sydney S.

2011-01-01

Development of the human brain follows a complex trajectory of age-specific anatomical and physiological changes. The application of network analysis provides an illuminating perspective on the dynamic interregional and global properties of this intricate and complex system. Here, we provide a critical synopsis of methods of network analysis with a focus on developing brain networks. After discussing basic concepts and approaches to network analysis, we explore the primary events of anatomical cortical development from gestation through adolescence. Upon this framework, we describe early work revealing the evolution of age-specific functional brain networks in normal neurodevelopment. Finally, we review how these relationships can be altered in disease and perhaps even rectified with treatment. While this method of description and inquiry remains in early form, there is already substantial evidence that the application of network models and analysis to understanding normal and abnormal human neural development holds tremendous promise for future discovery. PMID:21303762

Learning Predictive Statistics: Strategies and Brain Mechanisms.

PubMed

Wang, Rui; Shen, Yuan; Tino, Peter; Welchman, Andrew E; Kourtzi, Zoe

2017-08-30

When immersed in a new environment, we are challenged to decipher initially incomprehensible streams of sensory information. However, quite rapidly, the brain finds structure and meaning in these incoming signals, helping us to predict and prepare ourselves for future actions. This skill relies on extracting the statistics of event streams in the environment that contain regularities of variable complexity from simple repetitive patterns to complex probabilistic combinations. Here, we test the brain mechanisms that mediate our ability to adapt to the environment's statistics and predict upcoming events. By combining behavioral training and multisession fMRI in human participants (male and female), we track the corticostriatal mechanisms that mediate learning of temporal sequences as they change in structure complexity. We show that learning of predictive structures relates to individual decision strategy; that is, selecting the most probable outcome in a given context (maximizing) versus matching the exact sequence statistics. These strategies engage distinct human brain regions: maximizing engages dorsolateral prefrontal, cingulate, sensory-motor regions, and basal ganglia (dorsal caudate, putamen), whereas matching engages occipitotemporal regions (including the hippocampus) and basal ganglia (ventral caudate). Our findings provide evidence for distinct corticostriatal mechanisms that facilitate our ability to extract behaviorally relevant statistics to make predictions. SIGNIFICANCE STATEMENT Making predictions about future events relies on interpreting streams of information that may initially appear incomprehensible. Past work has studied how humans identify repetitive patterns and associative pairings. However, the natural environment contains regularities that vary in complexity from simple repetition to complex probabilistic combinations. Here, we combine behavior and multisession fMRI to track the brain mechanisms that mediate our ability to adapt to changes in the environment's statistics. We provide evidence for an alternate route for learning complex temporal statistics: extracting the most probable outcome in a given context is implemented by interactions between executive and motor corticostriatal mechanisms compared with visual corticostriatal circuits (including hippocampal cortex) that support learning of the exact temporal statistics. Copyright © 2017 Wang et al.

Can a few non‐coding mutations make a human brain?

PubMed Central

Franchini, Lucía F.

2015-01-01

The recent finding that the human version of a neurodevelopmental enhancer of the Wnt receptor Frizzled 8 (FZD8) gene alters neural progenitor cell cycle timing and brain size is a step forward to understanding human brain evolution. The human brain is distinctive in terms of its cognitive abilities as well as its susceptibility to neurological disease. Identifying which of the millions of genomic changes that occurred during human evolution led to these and other uniquely human traits is extremely challenging. Recent studies have demonstrated that many of the fastest evolving regions of the human genome function as gene regulatory enhancers during embryonic development and that the human‐specific mutations in them might alter expression patterns. However, elucidating molecular and cellular effects of sequence or expression pattern changes is a major obstacle to discovering the genetic bases of the evolution of our species. There is much work to do before human‐specific genetic and genomic changes are linked to complex human traits. Also watch the Video Abstract. PMID:26350501

Handedness- and brain size-related efficiency differences in small-world brain networks: a resting-state functional magnetic resonance imaging study.

PubMed

Li, Meiling; Wang, Junping; Liu, Feng; Chen, Heng; Lu, Fengmei; Wu, Guorong; Yu, Chunshui; Chen, Huafu

2015-05-01

The human brain has been described as a complex network, which integrates information with high efficiency. However, the relationships between the efficiency of human brain functional networks and handedness and brain size remain unclear. Twenty-one left-handed and 32 right-handed healthy subjects underwent a resting-state functional magnetic resonance imaging scan. The whole brain functional networks were constructed by thresholding Pearson correlation matrices of 90 cortical and subcortical regions. Graph theory-based methods were employed to further analyze their topological properties. As expected, all participants demonstrated small-world topology, suggesting a highly efficient topological structure. Furthermore, we found that smaller brains showed higher local efficiency, whereas larger brains showed higher global efficiency, reflecting a suitable efficiency balance between local specialization and global integration of brain functional activity. Compared with right-handers, significant alterations in nodal efficiency were revealed in left-handers, involving the anterior and median cingulate gyrus, middle temporal gyrus, angular gyrus, and amygdala. Our findings indicated that the functional network organization in the human brain was associated with handedness and brain size.

Insights into Brain Glycogen Metabolism: THE STRUCTURE OF HUMAN BRAIN GLYCOGEN PHOSPHORYLASE.

PubMed

Mathieu, Cécile; Li de la Sierra-Gallay, Ines; Duval, Romain; Xu, Ximing; Cocaign, Angélique; Léger, Thibaut; Woffendin, Gary; Camadro, Jean-Michel; Etchebest, Catherine; Haouz, Ahmed; Dupret, Jean-Marie; Rodrigues-Lima, Fernando

2016-08-26

Brain glycogen metabolism plays a critical role in major brain functions such as learning or memory consolidation. However, alteration of glycogen metabolism and glycogen accumulation in the brain contributes to neurodegeneration as observed in Lafora disease. Glycogen phosphorylase (GP), a key enzyme in glycogen metabolism, catalyzes the rate-limiting step of glycogen mobilization. Moreover, the allosteric regulation of the three GP isozymes (muscle, liver, and brain) by metabolites and phosphorylation, in response to hormonal signaling, fine-tunes glycogenolysis to fulfill energetic and metabolic requirements. Whereas the structures of muscle and liver GPs have been known for decades, the structure of brain GP (bGP) has remained elusive despite its critical role in brain glycogen metabolism. Here, we report the crystal structure of human bGP in complex with PEG 400 (2.5 Å) and in complex with its allosteric activator AMP (3.4 Å). These structures demonstrate that bGP has a closer structural relationship with muscle GP, which is also activated by AMP, contrary to liver GP, which is not. Importantly, despite the structural similarities between human bGP and the two other mammalian isozymes, the bGP structures reveal molecular features unique to the brain isozyme that provide a deeper understanding of the differences in the activation properties of these allosteric enzymes by the allosteric effector AMP. Overall, our study further supports that the distinct structural and regulatory properties of GP isozymes contribute to the different functions of muscle, liver, and brain glycogen. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Respiration and substrate transport rates as well as reactive oxygen species production distinguish mitochondria from brain and liver.

PubMed

Gusdon, Aaron M; Fernandez-Bueno, Gabriel A; Wohlgemuth, Stephanie; Fernandez, Jenelle; Chen, Jing; Mathews, Clayton E

2015-09-10

Aberrant mitochondrial function, including excessive reactive oxygen species (ROS) production, has been implicated in the pathogenesis of human diseases. The use of mitochondrial inhibitors to ascertain the sites in the electron transport chain (ETC) resulting in altered ROS production can be an important tool. However, the response of mouse mitochondria to ETC inhibitors has not been thoroughly assessed. Here we set out to characterize the differences in phenotypic response to ETC inhibitors between the more energetically demanding brain mitochondria and less energetically demanding liver mitochondria in commonly utilized C57BL/6J mice. We show that in contrast to brain mitochondria, inhibiting distally within complex I or within complex III does not increase liver mitochondrial ROS production supported by complex I substrates, and liver mitochondrial ROS production supported by complex II substrates occurred primarily independent of membrane potential. Complex I, II, and III enzymatic activities and membrane potential were equivalent between liver and brain and responded to ETC. inhibitors similarly. Brain mitochondria exhibited an approximately two-fold increase in complex I and II supported respiration compared with liver mitochondria while exhibiting similar responses to inhibitors. Elevated NADH transport and heightened complex II-III coupled activity accounted for increased complex I and II supported respiration, respectively in brain mitochondria. We conclude that important mechanistic differences exist between mouse liver and brain mitochondria and that mouse mitochondria exhibit phenotypic differences compared with mitochondria from other species.

Metabolic Mapping of the Brain's Response to Visual Stimulation: Studies in Humans.

ERIC Educational Resources Information Center

Phelps, Michael E.; Kuhl, David E.

1981-01-01

Studies demonstrate increasing glucose metabolic rates in human primary (PVC) and association (AVC) visual cortex as complexity of visual scenes increase. AVC increased more rapidly with scene complexity than PVC and increased local metabolic activities above control subject with eyes closed; indicates wide range and metabolic reserve of visual…

Blood-brain barrier-on-a-chip: Microphysiological systems that capture the complexity of the blood-central nervous system interface.

PubMed

Phan, Duc Tt; Bender, R Hugh F; Andrejecsk, Jillian W; Sobrino, Agua; Hachey, Stephanie J; George, Steven C; Hughes, Christopher Cw

2017-11-01

The blood-brain barrier is a dynamic and highly organized structure that strictly regulates the molecules allowed to cross the brain vasculature into the central nervous system. The blood-brain barrier pathology has been associated with a number of central nervous system diseases, including vascular malformations, stroke/vascular dementia, Alzheimer's disease, multiple sclerosis, and various neurological tumors including glioblastoma multiforme. There is a compelling need for representative models of this critical interface. Current research relies heavily on animal models (mostly mice) or on two-dimensional (2D) in vitro models, neither of which fully capture the complexities of the human blood-brain barrier. Physiological differences between humans and mice make translation to the clinic problematic, while monolayer cultures cannot capture the inherently three-dimensional (3D) nature of the blood-brain barrier, which includes close association of the abluminal side of the endothelium with astrocyte foot-processes and pericytes. Here we discuss the central nervous system diseases associated with blood-brain barrier pathology, recent advances in the development of novel 3D blood-brain barrier -on-a-chip systems that better mimic the physiological complexity and structure of human blood-brain barrier, and provide an outlook on how these blood-brain barrier-on-a-chip systems can be used for central nervous system disease modeling. Impact statement The field of microphysiological systems is rapidly evolving as new technologies are introduced and our understanding of organ physiology develops. In this review, we focus on Blood-Brain Barrier (BBB) models, with a particular emphasis on how they relate to neurological disorders such as Alzheimer's disease, multiple sclerosis, stroke, cancer, and vascular malformations. We emphasize the importance of capturing the three-dimensional nature of the brain and the unique architecture of the BBB - something that until recently had not been well modeled by in vitro systems. Our hope is that this review will provide a launch pad for new ideas and methodologies that can provide us with truly physiological BBB models capable of yielding new insights into the function of this critical interface.

Human development XIII: the connection between the structure of the overtone system and the tone language of music. Some implications for our understanding of the human brain.

PubMed

Ventegodt, Søren; Hermansen, Tyge Dahl; Kandel, Isack; Merrick, Joav

2008-07-13

The functioning brain behaves like one highly-structured, coherent, informational field. It can be popularly described as a "coherent ball of energy", making the idea of a local highly-structured quantum field that carries the consciousness very appealing. If that is so, the structure of the experience of music might be a quite unique window into a hidden quantum reality of the brain, and even of life itself. The structure of music is then a mirror of a much more complex, but similar, structure of the energetic field of the working brain. This paper discusses how the perception of music is organized in the human brain with respect to the known tone scales of major and minor. The patterns used by the brain seem to be similar to the overtones of vibrating matter, giving a positive experience of harmonies in major. However, we also like the minor scale, which can explain brain patterns as fractal-like, giving a symmetric "downward reflection" of the major scale into the minor scale. We analyze the implication of beautiful and ugly tones and harmonies for the model. We conclude that when it comes to simple perception of harmonies, the most simple is the most beautiful and the most complex is the most ugly, but in music, even the most disharmonic harmony can be beautiful, if experienced as a part of a dynamic release of musical tension. This can be taken as a general metaphor of painful, yet meaningful, and developing experiences in human life.

The evolution of the complex sensory and motor systems of the human brain

PubMed Central

Kaas, Jon H.

2008-01-01

Inferences about how the complex sensory and motor systems of the human brain evolved are based on the results of comparative studies of brain organization across a range of mammalian species, and evidence from the endocasts of fossil skulls of key extinct species. The endocasts of the skulls of early mammals indicate that they had small brains with little neocortex. Evidence from comparative studies of cortical organization from small-brained mammals of the six major branches of mammalian evolution supports the conclusion that the small neocortex of early mammals was divided into roughly 20–25 cortical areas, including primary and secondary sensory fields. In early primates, vision was the dominant sense, and cortical areas associated with vision in temporal and occipital cortex underwent a significant expansion. Comparative studies indicate that early primates had 10 or more visual areas, and somatosensory areas with expanded representations of the forepaw. Posterior parietal cortex was also expanded, with a caudal half dominated by visual inputs, and a rostral half dominated by somatosensory inputs with outputs to an array of seven or more motor and visuomotor areas of the frontal lobe. Somatosensory areas and posterior parietal cortex became further differentiated in early anthropoid primates. As larger brains evolved in early apes and in our hominin ancestors, the number of cortical areas increased to reach an estimated 200 or so in present day humans, and hemispheric specializations emerged. The large human brain grew primarily by increasing neuron number rather than increasing average neuron size. PMID:18331903

Renewal Processes in the Critical Brain

NASA Astrophysics Data System (ADS)

Allegrini, Paolo; Paradisi, Paolo; Menicucci, Danilo; Gemignani, Angelo

We describe herein a multidisciplinary research, as it developes and applies concepts of the theory of complexity, in turn stemming from recent advancements of statistical physics, onto cognitive neuroscience. We discuss (define) complexity, and how the human brain is a paradigm of it. We discuss how the hypothesis of brain activity dynamically behaving as a critical system is taking momentum in literature, then we focus on a feature of critical systems (hence of the brain), which is the intermittent passage between metastable states, marked by events, locally resetting the memory, but giving rise to correlation functions with infinite correlation times. The events, extracted from multi-channel ElectroEncephaloGrams, mark (are interpreted as) a birth/death process of cooperation, namely of system elements being recruited into collective states. Finally we discuss a recently discovered form of control (in the form of a new Linear Response Theory), that allows an optimized information transmission between complex systems, named Complexity Matching.

[Anesthesia and Consciousness].

PubMed

Ogino, Yuichi; Kawamichi, Hiroaki; Saiot, Shigeru

2016-05-01

The mechanism of consciousness and loss of conciousness by general anesthetics are crucial issue for the anesthesiologists. Recent non-invasive brain-imaging technology brings about light to various our emotions and sensations in human brain; however, neural correlate of consciousness is not yet still elucidated. The concept "the seat of the consciousness (is in the subcortical nuclei)" is now completely denied, but instead the consciousness is based on the idea that connectivity and communications across cortical and thalamocortical networks. Anesthetics and sleep disrupt the networks that encompass complexity and integration. The compatibility between complexity and integration is the key feature of the consciousness, which is represented by complex, extensive, communicative and integrative electroencephalograph currents evoked by transcranial magnetic stimulation, provoking a single unified conscious experience in us, humans.

From data processing to mental organs: an interdisciplinary path to cognitive neuroscience.

PubMed

Patharkar, Manoj

2011-01-01

Human brain is a highly evolved coordinating mechanism in the species Homo sapiens. It is only in the last 100 years that extensive knowledge of the intricate structure and complex functioning of the human brain has been acquired, though a lot is yet to be known. However, from the beginning of civilisation, people have been conscious of a 'mind' which has been considered the origin of all scientific and cultural development. Philosophers have discussed at length the various attributes of consciousness. At the same time, most of the philosophical or scientific frameworks have directly or indirectly implied mind-body duality. It is now imperative that we develop an integrated approach to understand the interconnection between mind and consciousness on one hand and brain on the other. This paper begins with the proposition that the structure of the brain is analogous, at least to certain extent, to that of the computer system. Of course, it is much more sophisticated and complex. The second proposition is that the Chomskyean concept of 'mental organs' is a good working hypothesis that tries to characterise this complexity in terms of an innate cognitive framework. By following this dual approach, brain as a data processing system and brain as a superstructure of intricately linked mental organs, we can move toward a better understanding of 'mind' within the framework of empirical science. The one 'mental organ' studied extensively in Chomskyean terms is 'language faculty' which is unique in its relation to brain, mind and consciousness.

Content of endoplasmic reticulum and Golgi complex membranes positively correlates with the proliferative status of brain cells.

PubMed

Silvestre, David C; Maccioni, Hugo J F; Caputto, Beatriz L

2009-03-01

Although the molecular and cellular basis of particular events that lead to the biogenesis of membranes in eukaryotic cells has been described in detail, understanding of the intrinsic complexity of the pleiotropic response by which a cell adjusts the overall activity of its endomembrane system to accomplish these requirements is limited. Here we carried out an immunocytochemical and biochemical examination of the content and quality of the endoplasmic reticulum (ER) and Golgi apparatus membranes in two in vivo situations characterized by a phase of active cell proliferation followed by a phase of declination in proliferation (rat brain tissue at early and late developmental stages) or by permanent active proliferation (gliomas and their most malignant manifestation, glioblastomas multiforme). It was found that, in highly proliferative phases of brain development (early embryo brain cells), the content of ER and Golgi apparatus membranes, measured as total lipid phosphorous content, is higher than in adult brain cells. In addition, the concentration of protein markers of ER and Golgi is also higher in early embryo brain cells and in human glioblastoma multiforme cells than in adult rat brain or in nonpathological human brain cells. Results suggest that the amount of endomembranes and the concentration of constituent functional proteins diminish as cells decline in their proliferative activity.

Robust estimation of fractal measures for characterizing the structural complexity of the human brain: optimization and reproducibility

PubMed Central

Goñi, Joaquín; Sporns, Olaf; Cheng, Hu; Aznárez-Sanado, Maite; Wang, Yang; Josa, Santiago; Arrondo, Gonzalo; Mathews, Vincent P; Hummer, Tom A; Kronenberger, William G; Avena-Koenigsberger, Andrea; Saykin, Andrew J.; Pastor, María A.

2013-01-01

High-resolution isotropic three-dimensional reconstructions of human brain gray and white matter structures can be characterized to quantify aspects of their shape, volume and topological complexity. In particular, methods based on fractal analysis have been applied in neuroimaging studies to quantify the structural complexity of the brain in both healthy and impaired conditions. The usefulness of such measures for characterizing individual differences in brain structure critically depends on their within-subject reproducibility in order to allow the robust detection of between-subject differences. This study analyzes key analytic parameters of three fractal-based methods that rely on the box-counting algorithm with the aim to maximize within-subject reproducibility of the fractal characterizations of different brain objects, including the pial surface, the cortical ribbon volume, the white matter volume and the grey matter/white matter boundary. Two separate datasets originating from different imaging centers were analyzed, comprising, 50 subjects with three and 24 subjects with four successive scanning sessions per subject, respectively. The reproducibility of fractal measures was statistically assessed by computing their intra-class correlations. Results reveal differences between different fractal estimators and allow the identification of several parameters that are critical for high reproducibility. Highest reproducibility with intra-class correlations in the range of 0.9–0.95 is achieved with the correlation dimension. Further analyses of the fractal dimensions of parcellated cortical and subcortical gray matter regions suggest robustly estimated and region-specific patterns of individual variability. These results are valuable for defining appropriate parameter configurations when studying changes in fractal descriptors of human brain structure, for instance in studies of neurological diseases that do not allow repeated measurements or for disease-course longitudinal studies. PMID:23831414

The Encephalopathy of Prematurity: One Pediatric Neuropathologist’s Perspective

PubMed Central

Kinney, Hannah C.

2010-01-01

A major challenge in understanding brain injury in the premature brain is the establishment of the precise human neuropathology at the cellular and molecular levels, as such knowledge is the foundation upon which the elucidation of the cause(s), scientific experimentation, and therapies in the field is by necessity based. In this essay, I provide my perspective as a pediatric neuropathologist upon pathologic studies in the developing human brain itself, including a review of past, present, and future aspects. My focus is upon the path that has brought us to the current recognition that preterm brain injury is a complex of white and gray matter damage that results in the modification of key developmental pathways during a critical period, which in turn defines the adverse clinical outcomes as important as the primary insult itself. The evolution of this recognition, as well as the introduction of the term “encephalopathy of prematurity” for the complex of gray and white matter damage because of acquired and developmental mechanisms, is discussed. Our enhanced understanding of the fundamental neuropathology of the human preterm brain should bring us closer to more effective therapy as the need to prevent and treat injury to developing oligodendrocytes and neurons in combination is appreciated. PMID:19945652

Neuropsychology and cognitive neuroscience in the fMRI era: A recapitulation of localizationist and connectionist views.

PubMed

Sutterer, Matthew J; Tranel, Daniel

2017-11-01

We highlight the past 25 years of cognitive neuroscience and neuropsychology, focusing on the impact to the field of the introduction in 1992 of functional MRI (fMRI). We reviewed the past 25 years of literature in cognitive neuroscience and neuropsychology, focusing on the relation and interplay of fMRI studies and studies utilizing the "lesion method" in human participants with focal brain damage. Our review highlights the state of localist/connectionist research debates in cognitive neuroscience and neuropsychology circa 1992, and details how the introduction of fMRI into the field at that time catalyzed a new wave of efforts to map complex human behavior to specific brain regions. This, in turn, eventually evolved into many studies that focused on networks and connections between brain areas, culminating in recent years with large-scale investigations such as the Human Connectome Project. We argue that throughout the past 25 years, neuropsychology-and more precisely, the "lesion method" in humans-has continued to play a critical role in arbitrating conclusions and theories derived from inferred patterns of local brain activity or wide-spread connectivity from functional imaging approaches. We conclude by highlighting the future for neuropsychology in the context of an increasingly complex methodological armamentarium. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Cerebral cartography and connectomics

PubMed Central

Sporns, Olaf

2015-01-01

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

A guide to the metabolic pathways and function of metabolites observed in human brain 1H magnetic resonance spectra.

PubMed

Rae, Caroline D

2014-01-01

The current knowledge of the normal biochemistry of compounds that give rise to resonances in human brain proton magnetic resonance spectra measureable at readily available field strengths (i.e. ≤3 T) is reviewed. Molecules covered include myo- and scyllo-inositol, glycerophospho- and phospho-choline and choline, creatine and phosphocreatine, N-acetylaspartate, N-acetylaspartylglutamate, glutamate, glutamine, γ-aminobutyrate, glucose, glutathione and lactate. The factors which influence changes in the levels of these compounds are discussed. As most proton resonances in the brain at low field are derived from a combination of moieties whose biochemistry is complex and interrelated, an understanding of the mechanisms underlying why these species change is crucial to meaningful interpretation of human brain spectra.

Connectome-harmonic decomposition of human brain activity reveals dynamical repertoire re-organization under LSD.

PubMed

Atasoy, Selen; Roseman, Leor; Kaelen, Mendel; Kringelbach, Morten L; Deco, Gustavo; Carhart-Harris, Robin L

2017-12-15

Recent studies have started to elucidate the effects of lysergic acid diethylamide (LSD) on the human brain but the underlying dynamics are not yet fully understood. Here we used 'connectome-harmonic decomposition', a novel method to investigate the dynamical changes in brain states. We found that LSD alters the energy and the power of individual harmonic brain states in a frequency-selective manner. Remarkably, this leads to an expansion of the repertoire of active brain states, suggestive of a general re-organization of brain dynamics given the non-random increase in co-activation across frequencies. Interestingly, the frequency distribution of the active repertoire of brain states under LSD closely follows power-laws indicating a re-organization of the dynamics at the edge of criticality. Beyond the present findings, these methods open up for a better understanding of the complex brain dynamics in health and disease.

The Power of Secret Stories: Constructing Mental Patterns during the Reading-Writing Process

ERIC Educational Resources Information Center

Krisell, Meredith; Counsell, Shelly

2017-01-01

The brain is a complex organ with an intellectual capacity that is unique to humans. For educators, it is wise to study the brain's many attributes and how it functions to help guide, inform, and improve teaching practice. Learners' brains are particularly sensitive to certain kinds of stimuli--that is social, physical, cognitive, and emotional…

The impact of poverty on the development of brain networks

PubMed Central

Lipina, Sebastián J.; Posner, Michael I.

2012-01-01

Although the study of brain development in non-human animals is an old one, recent imaging methods have allowed non-invasive studies of the gray and white matter of the human brain over the lifespan. Classic animal studies show clearly that impoverished environments reduce cortical gray matter in relation to complex environments and cognitive and imaging studies in humans suggest which networks may be most influenced by poverty. Studies have been clear in showing the plasticity of many brain systems, but whether sensitivity to learning differs over the lifespan and for which networks is still unclear. A major task for current research is a successful integration of these methods to understand how development and learning shape the neural networks underlying achievements in literacy, numeracy, and attention. This paper seeks to foster further integration by reviewing the current state of knowledge relating brain changes to behavior and indicating possible future directions. PMID:22912613

Human Development XIII: The Connection Between the Structure of the Overtone System and the Tone Language of Music. Some Implications for Our Understanding of the Human Brain

PubMed Central

Ventegodt, Søren; Hermansen, Tyge Dahl; Kandel, Isack; Merrick, Joav

2008-01-01

The functioning brain behaves like one highly-structured, coherent, informational field. It can be popularly described as a “coherent ball of energy”, making the idea of a local highly-structured quantum field that carries the consciousness very appealing. If that is so, the structure of the experience of music might be a quite unique window into a hidden quantum reality of the brain, and even of life itself. The structure of music is then a mirror of a much more complex, but similar, structure of the energetic field of the working brain. This paper discusses how the perception of music is organized in the human brain with respect to the known tone scales of major and minor. The patterns used by the brain seem to be similar to the overtones of vibrating matter, giving a positive experience of harmonies in major. However, we also like the minor scale, which can explain brain patterns as fractal-like, giving a symmetric “downward reflection” of the major scale into the minor scale. We analyze the implication of beautiful and ugly tones and harmonies for the model. We conclude that when it comes to simple perception of harmonies, the most simple is the most beautiful and the most complex is the most ugly, but in music, even the most disharmonic harmony can be beautiful, if experienced as a part of a dynamic release of musical tension. This can be taken as a general metaphor of painful, yet meaningful, and developing experiences in human life. PMID:18661052

Selective Limbic Blood–Brain Barrier Breakdown in a Feline Model of Limbic Encephalitis with LGI1 Antibodies

PubMed Central

Tröscher, Anna R.; Klang, Andrea; French, Maria; Quemada-Garrido, Lucía; Kneissl, Sibylle Maria; Bien, Christian G.; Pákozdy, Ákos; Bauer, Jan

2017-01-01

Human leucine-rich glioma-inactivated protein 1 encephalitis (LGI1) is an autoimmune limbic encephalitis in which serum and cerebrospinal fluid contain antibodies targeting LGI1, a protein of the voltage gated potassium channel (VGKC) complex. Recently, we showed that a feline model of limbic encephalitis with LGI1 antibodies, called feline complex partial seizures with orofacial involvement (FEPSO), is highly comparable to human LGI1 encephalitis. In human LGI1 encephalitis, neuropathological investigations are difficult because very little material is available. Taking advantage of this natural animal model to study pathological mechanisms will, therefore, contribute to a better understanding of its human counterpart. Here, we present a brain-wide histopathological analysis of FEPSO. We discovered that blood–brain barrier (BBB) leakage was present not only in all regions of the hippocampus but also in other limbic structures such as the subiculum, amygdale, and piriform lobe. However, in other regions, such as the cerebellum, no leakage was observed. In addition, this brain-region-specific immunoglobulin leakage was associated with the breakdown of endothelial tight junctions. Brain areas affected by BBB dysfunction also revealed immunoglobulin and complement deposition as well as neuronal cell death. These neuropathological findings were supported by magnetic resonance imaging showing signal and volume increase in the amygdala and the piriform lobe. Importantly, we could show that BBB disturbance in LGI1 encephalitis does not depend on T cell infiltrates, which were present brain-wide. This finding points toward another, so far unknown, mechanism of opening the BBB. The limbic predilection sites of immunoglobulin antibody leakage into the brain may explain why most patients with LGI1 antibodies have a limbic phenotype even though LGI1, the target protein, is ubiquitously distributed across the central nervous system. PMID:29093718

Selective Limbic Blood-Brain Barrier Breakdown in a Feline Model of Limbic Encephalitis with LGI1 Antibodies.

PubMed

Tröscher, Anna R; Klang, Andrea; French, Maria; Quemada-Garrido, Lucía; Kneissl, Sibylle Maria; Bien, Christian G; Pákozdy, Ákos; Bauer, Jan

2017-01-01

Human leucine-rich glioma-inactivated protein 1 encephalitis (LGI1) is an autoimmune limbic encephalitis in which serum and cerebrospinal fluid contain antibodies targeting LGI1, a protein of the voltage gated potassium channel (VGKC) complex. Recently, we showed that a feline model of limbic encephalitis with LGI1 antibodies, called feline complex partial seizures with orofacial involvement (FEPSO), is highly comparable to human LGI1 encephalitis. In human LGI1 encephalitis, neuropathological investigations are difficult because very little material is available. Taking advantage of this natural animal model to study pathological mechanisms will, therefore, contribute to a better understanding of its human counterpart. Here, we present a brain-wide histopathological analysis of FEPSO. We discovered that blood-brain barrier (BBB) leakage was present not only in all regions of the hippocampus but also in other limbic structures such as the subiculum, amygdale, and piriform lobe. However, in other regions, such as the cerebellum, no leakage was observed. In addition, this brain-region-specific immunoglobulin leakage was associated with the breakdown of endothelial tight junctions. Brain areas affected by BBB dysfunction also revealed immunoglobulin and complement deposition as well as neuronal cell death. These neuropathological findings were supported by magnetic resonance imaging showing signal and volume increase in the amygdala and the piriform lobe. Importantly, we could show that BBB disturbance in LGI1 encephalitis does not depend on T cell infiltrates, which were present brain-wide. This finding points toward another, so far unknown, mechanism of opening the BBB. The limbic predilection sites of immunoglobulin antibody leakage into the brain may explain why most patients with LGI1 antibodies have a limbic phenotype even though LGI1, the target protein, is ubiquitously distributed across the central nervous system.

Minding the ecological body: neuropsychoanalysis and ecopsychoanalysis.

PubMed

Dodds, Joseph

2013-01-01

Neuropsychoanalysis explores experimentally and theoretically the philosophically ancient discussion of the relation of mind and body, and seems well placed to overcome the problem of a "mindless" neuroscience and a "brainless" psychology and psychotherapy, especially when combined with a greater awareness that the body itself, not only the brain, provides the material substrate for the emergent phenomenon we call mind. However, the mind-brain-body is itself situated within a complex ecological world, interacting with other mind-brain-bodies and the "non-human environment." This occurs both synchronically and diachronically as the organism and its environment (living and non-living) interact in highly complex often non-linear ways. Psychoanalysis can do much to help unmask the anxieties, deficits, conflicts, phantasies, and defenses crucial in understanding the human dimension of the ecological crisis. Yet, psychoanalysis still largely remains not only a "psychology without biology," which neuropsychoanalysis seeks to remedy, but also a "psychology without ecology." Ecopsychoanalysis (Dodds, 2011b; Dodds and Jordan, 2012) is a new transdisciplinary approach drawing on a range of fields such as psychoanalysis, psychology, ecology, philosophy, science, complexity theory, esthetics, and the humanities. It attempts to play with what each approach has to offer in the sense of a heterogeneous assemblage of ideas and processes, mirroring the interlocking complexity, chaos, and turbulence of nature itself. By emphasizing the way the mind-brain-body studied by neuropsychoanalysis is embedded in wider social and ecological networks, ecopsychoanalysis can help open up the relevance of neuropsychoanalysis to wider fields of study, including those who are concerned with what Wilson (2003) called "the future of life."

Analysis of Brain Recurrence

NASA Astrophysics Data System (ADS)

Frilot, Clifton; Kim, Paul Y.; Carrubba, Simona; McCarty, David E.; Chesson, Andrew L.; Marino, Andrew A.

Analysis of Brain Recurrence (ABR) is a method for extracting physiologically significant information from the electroencephalogram (EEG), a non-stationary electrical output of the brain, the ultimate complex dynamical system. ABR permits quantification of temporal patterns in the EEG produced by the non-autonomous differential laws that govern brain metabolism. In the context of appropriate experimental and statistical designs, ABR is ideally suited to the task of interpreting the EEG. Present applications of ABR include discovery of a human magnetic sense, increased mechanistic understanding of neuronal membrane processes, diagnosis of degenerative neurological disease, detection of changes in brain metabolism caused by weak environmental electromagnetic fields, objective characterization of the quality of human sleep, and evaluation of sleep disorders. ABR has important beneficial implications for the development of clinical and experimental neuroscience.

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

PubMed Central

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

2016-01-01

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

A Novel Human Body Area Network for Brain Diseases Analysis.

PubMed

Lin, Kai; Xu, Tianlang

2016-10-01

Development of wireless sensor and mobile communication technology provide an unprecedented opportunity for realizing smart and interactive healthcare systems. Designing such systems aims to remotely monitor the health and diagnose the diseases for users. In this paper, we design a novel human body area network for brain diseases analysis, which is named BABDA. Considering the brain is one of the most complex organs in the human body, the BABDA system provides four function modules to ensure the high quality of the analysis result, which includes initial data collection, data correction, data transmission and comprehensive data analysis. The performance evaluation conducted in a realistic environment with several criteria shows the availability and practicability of the BABDA system.

Brain Activation During Singing: "Clef de Sol Activation" Is the "Concert" of the Human Brain.

PubMed

Mavridis, Ioannis N; Pyrgelis, Efstratios-Stylianos

2016-03-01

Humans are the most complex singers in nature, and the human voice is thought by many to be the most beautiful musical instrument. Aside from spoken language, singing represents a second mode of acoustic communication in humans. The purpose of this review article is to explore the functional anatomy of the "singing" brain. Methodologically, the existing literature regarding activation of the human brain during singing was carefully reviewed, with emphasis on the anatomic localization of such activation. Relevant human studies are mainly neuroimaging studies, namely functional magnetic resonance imaging and positron emission tomography studies. Singing necessitates activation of several cortical, subcortical, cerebellar, and brainstem areas, served and coordinated by multiple neural networks. Functionally vital cortical areas of the frontal, parietal, and temporal lobes bilaterally participate in the brain's activation process during singing, confirming the latter's role in human communication. Perisylvian cortical activity of the right hemisphere seems to be the most crucial component of this activation. This also explains why aphasic patients due to left hemispheric lesions are able to sing but not speak the same words. The term clef de sol activation is proposed for this crucial perisylvian cortical activation due to the clef de sol shape of the topographical distribution of these cortical areas around the sylvian fissure. Further research is needed to explore the connectivity and sequence of how the human brain activates to sing.

Brain evolution by brain pathway duplication

PubMed Central

Chakraborty, Mukta; Jarvis, Erich D.

2015-01-01

Understanding the mechanisms of evolution of brain pathways for complex behaviours is still in its infancy. Making further advances requires a deeper understanding of brain homologies, novelties and analogies. It also requires an understanding of how adaptive genetic modifications lead to restructuring of the brain. Recent advances in genomic and molecular biology techniques applied to brain research have provided exciting insights into how complex behaviours are shaped by selection of novel brain pathways and functions of the nervous system. Here, we review and further develop some insights to a new hypothesis on one mechanism that may contribute to nervous system evolution, in particular by brain pathway duplication. Like gene duplication, we propose that whole brain pathways can duplicate and the duplicated pathway diverge to take on new functions. We suggest that one mechanism of brain pathway duplication could be through gene duplication, although other mechanisms are possible. We focus on brain pathways for vocal learning and spoken language in song-learning birds and humans as example systems. This view presents a new framework for future research in our understanding of brain evolution and novel behavioural traits. PMID:26554045

Gene expression links functional networks across cortex and striatum.

PubMed

Anderson, Kevin M; Krienen, Fenna M; Choi, Eun Young; Reinen, Jenna M; Yeo, B T Thomas; Holmes, Avram J

2018-04-12

The human brain is comprised of a complex web of functional networks that link anatomically distinct regions. However, the biological mechanisms supporting network organization remain elusive, particularly across cortical and subcortical territories with vastly divergent cellular and molecular properties. Here, using human and primate brain transcriptional atlases, we demonstrate that spatial patterns of gene expression show strong correspondence with limbic and somato/motor cortico-striatal functional networks. Network-associated expression is consistent across independent human datasets and evolutionarily conserved in non-human primates. Genes preferentially expressed within the limbic network (encompassing nucleus accumbens, orbital/ventromedial prefrontal cortex, and temporal pole) relate to risk for psychiatric illness, chloride channel complexes, and markers of somatostatin neurons. Somato/motor associated genes are enriched for oligodendrocytes and markers of parvalbumin neurons. These analyses indicate that parallel cortico-striatal processing channels possess dissociable genetic signatures that recapitulate distributed functional networks, and nominate molecular mechanisms supporting cortico-striatal circuitry in health and disease.

From Data Processing to Mental Organs: An Interdisciplinary Path to Cognitive Neuroscience**

PubMed Central

Patharkar, Manoj

2011-01-01

Human brain is a highly evolved coordinating mechanism in the species Homo sapiens. It is only in the last 100 years that extensive knowledge of the intricate structure and complex functioning of the human brain has been acquired, though a lot is yet to be known. However, from the beginning of civilisation, people have been conscious of a ‘mind’ which has been considered the origin of all scientific and cultural development. Philosophers have discussed at length the various attributes of consciousness. At the same time, most of the philosophical or scientific frameworks have directly or indirectly implied mind-body duality. It is now imperative that we develop an integrated approach to understand the interconnection between mind and consciousness on one hand and brain on the other. This paper begins with the proposition that the structure of the brain is analogous, at least to certain extent, to that of the computer system. Of course, it is much more sophisticated and complex. The second proposition is that the Chomskyean concept of ‘mental organs’ is a good working hypothesis that tries to characterise this complexity in terms of an innate cognitive framework. By following this dual approach, brain as a data processing system and brain as a superstructure of intricately linked mental organs, we can move toward a better understanding of ‘mind’ within the framework of empirical science. The one ‘mental organ’ studied extensively in Chomskyean terms is ‘language faculty’ which is unique in its relation to brain, mind and consciousness. PMID:21694973

A pediatric brain structure atlas from T1-weighted MR images

NASA Astrophysics Data System (ADS)

Shan, Zuyao Y.; Parra, Carlos; Ji, Qing; Ogg, Robert J.; Zhang, Yong; Laningham, Fred H.; Reddick, Wilburn E.

2006-03-01

In this paper, we have developed a digital atlas of the pediatric human brain. Human brain atlases, used to visualize spatially complex structures of the brain, are indispensable tools in model-based segmentation and quantitative analysis of brain structures. However, adult brain atlases do not adequately represent the normal maturational patterns of the pediatric brain, and the use of an adult model in pediatric studies may introduce substantial bias. Therefore, we proposed to develop a digital atlas of the pediatric human brain in this study. The atlas was constructed from T1 weighted MR data set of a 9 year old, right-handed girl. Furthermore, we extracted and simplified boundary surfaces of 25 manually defined brain structures (cortical and subcortical) based on surface curvature. Higher curvature surfaces were simplified with more reference points; lower curvature surfaces, with fewer. We constructed a 3D triangular mesh model for each structure by triangulation of the structure's reference points. Kappa statistics (cortical, 0.97; subcortical, 0.91) indicated substantial similarities between the mesh-defined and the original volumes. Our brain atlas and structural mesh models (www.stjude.org/BrainAtlas) can be used to plan treatment, to conduct knowledge and modeldriven segmentation, and to analyze the shapes of brain structures in pediatric patients.

Revealing topological organization of human brain functional networks with resting-state functional near infrared spectroscopy.

PubMed

Niu, Haijing; Wang, Jinhui; Zhao, Tengda; Shu, Ni; He, Yong

2012-01-01

The human brain is a highly complex system that can be represented as a structurally interconnected and functionally synchronized network, which assures both the segregation and integration of information processing. Recent studies have demonstrated that a variety of neuroimaging and neurophysiological techniques such as functional magnetic resonance imaging (MRI), diffusion MRI and electroencephalography/magnetoencephalography can be employed to explore the topological organization of human brain networks. However, little is known about whether functional near infrared spectroscopy (fNIRS), a relatively new optical imaging technology, can be used to map functional connectome of the human brain and reveal meaningful and reproducible topological characteristics. We utilized resting-state fNIRS (R-fNIRS) to investigate the topological organization of human brain functional networks in 15 healthy adults. Brain networks were constructed by thresholding the temporal correlation matrices of 46 channels and analyzed using graph-theory approaches. We found that the functional brain network derived from R-fNIRS data had efficient small-world properties, significant hierarchical modular structure and highly connected hubs. These results were highly reproducible both across participants and over time and were consistent with previous findings based on other functional imaging techniques. Our results confirmed the feasibility and validity of using graph-theory approaches in conjunction with optical imaging techniques to explore the topological organization of human brain networks. These results may expand a methodological framework for utilizing fNIRS to study functional network changes that occur in association with development, aging and neurological and psychiatric disorders.

Localization of migraine susceptibility genes in human brain by single-cell RNA sequencing.

PubMed

Renthal, William

2018-01-01

Background Migraine is a debilitating disorder characterized by severe headaches and associated neurological symptoms. A key challenge to understanding migraine has been the cellular complexity of the human brain and the multiple cell types implicated in its pathophysiology. The present study leverages recent advances in single-cell transcriptomics to localize the specific human brain cell types in which putative migraine susceptibility genes are expressed. Methods The cell-type specific expression of both familial and common migraine-associated genes was determined bioinformatically using data from 2,039 individual human brain cells across two published single-cell RNA sequencing datasets. Enrichment of migraine-associated genes was determined for each brain cell type. Results Analysis of single-brain cell RNA sequencing data from five major subtypes of cells in the human cortex (neurons, oligodendrocytes, astrocytes, microglia, and endothelial cells) indicates that over 40% of known migraine-associated genes are enriched in the expression profiles of a specific brain cell type. Further analysis of neuronal migraine-associated genes demonstrated that approximately 70% were significantly enriched in inhibitory neurons and 30% in excitatory neurons. Conclusions This study takes the next step in understanding the human brain cell types in which putative migraine susceptibility genes are expressed. Both familial and common migraine may arise from dysfunction of discrete cell types within the neurovascular unit, and localization of the affected cell type(s) in an individual patient may provide insight into to their susceptibility to migraine.

Our Brains Extended

ERIC Educational Resources Information Center

Prensky, Marc

2013-01-01

Technology is an extension of the brain; it is a new way of thinking. It is the solution humans have created to deal with the difficult new context of variability, uncertainty, complexity, and ambiguity. Wise integration of evolving and powerful technology demands a rethinking of the curriculum. This article discusses technology as the new way of…

The Neuroanatomy and Neuroendocrinology of Fragile X Syndrome

ERIC Educational Resources Information Center

Hessl, David; Rivera, Susan M.; Reiss, Allan L.

2004-01-01

Fragile X syndrome (FXS), caused by a single gene mutation on the X chromosome, offers a unique opportunity for investigation of gene-brain-behavior relationships. Recent advances in molecular genetics, human brain imaging, and behavioral studies have started to unravel the complex pathways leading to the cognitive, psychiatric, and physical…

Wavelet multiresolution complex network for decoding brain fatigued behavior from P300 signals

NASA Astrophysics Data System (ADS)

Gao, Zhong-Ke; Wang, Zi-Bo; Yang, Yu-Xuan; Li, Shan; Dang, Wei-Dong; Mao, Xiao-Qian

2018-09-01

Brain-computer interface (BCI) enables users to interact with the environment without relying on neural pathways and muscles. P300 based BCI systems have been extensively used to achieve human-machine interaction. However, the appearance of fatigue symptoms during operation process leads to the decline in classification accuracy of P300. Characterizing brain cognitive process underlying normal and fatigue conditions constitutes a problem of vital importance in the field of brain science. We in this paper propose a novel wavelet decomposition based complex network method to efficiently analyze the P300 signals recorded in the image stimulus test based on classical 'Oddball' paradigm. Initially, multichannel EEG signals are decomposed into wavelet coefficient series. Then we construct complex network by treating electrodes as nodes and determining the connections according to the 2-norm distances between wavelet coefficient series. The analysis of topological structure and statistical index indicates that the properties of brain network demonstrate significant distinctions between normal status and fatigue status. More specifically, the brain network reconfiguration in response to the cognitive task in fatigue status is reflected as the enhancement of the small-worldness.

MRI Segmentation of the Human Brain: Challenges, Methods, and Applications

PubMed Central

Despotović, Ivana

2015-01-01

Image segmentation is one of the most important tasks in medical image analysis and is often the first and the most critical step in many clinical applications. In brain MRI analysis, image segmentation is commonly used for measuring and visualizing the brain's anatomical structures, for analyzing brain changes, for delineating pathological regions, and for surgical planning and image-guided interventions. In the last few decades, various segmentation techniques of different accuracy and degree of complexity have been developed and reported in the literature. In this paper we review the most popular methods commonly used for brain MRI segmentation. We highlight differences between them and discuss their capabilities, advantages, and limitations. To address the complexity and challenges of the brain MRI segmentation problem, we first introduce the basic concepts of image segmentation. Then, we explain different MRI preprocessing steps including image registration, bias field correction, and removal of nonbrain tissue. Finally, after reviewing different brain MRI segmentation methods, we discuss the validation problem in brain MRI segmentation. PMID:25945121

Comparative Study of Human and Mouse Postsynaptic Proteomes Finds High Compositional Conservation and Abundance Differences for Key Synaptic Proteins

PubMed Central

Bayés, Àlex; Collins, Mark O.; Croning, Mike D. R.; van de Lagemaat, Louie N.; Choudhary, Jyoti S.; Grant, Seth G. N.

2012-01-01

Direct comparison of protein components from human and mouse excitatory synapses is important for determining the suitability of mice as models of human brain disease and to understand the evolution of the mammalian brain. The postsynaptic density is a highly complex set of proteins organized into molecular networks that play a central role in behavior and disease. We report the first direct comparison of the proteome of triplicate isolates of mouse and human cortical postsynaptic densities. The mouse postsynaptic density comprised 1556 proteins and the human one 1461. A large compositional overlap was observed; more than 70% of human postsynaptic density proteins were also observed in the mouse postsynaptic density. Quantitative analysis of postsynaptic density components in both species indicates a broadly similar profile of abundance but also shows that there is higher abundance variation between species than within species. Well known components of this synaptic structure are generally more abundant in the mouse postsynaptic density. Significant inter-species abundance differences exist in some families of key postsynaptic density proteins including glutamatergic neurotransmitter receptors and adaptor proteins. Furthermore, we have identified a closely interacting set of molecules enriched in the human postsynaptic density that could be involved in dendrite and spine structural plasticity. Understanding synapse proteome diversity within and between species will be important to further our understanding of brain complexity and disease. PMID:23071613

Neural basis of processing threatening voices in a crowded auditory world

PubMed Central

Mothes-Lasch, Martin; Becker, Michael P. I.; Miltner, Wolfgang H. R.

2016-01-01

In real world situations, we typically listen to voice prosody against a background crowded with auditory stimuli. Voices and background can both contain behaviorally relevant features and both can be selectively in the focus of attention. Adequate responses to threat-related voices under such conditions require that the brain unmixes reciprocally masked features depending on variable cognitive resources. It is unknown which brain systems instantiate the extraction of behaviorally relevant prosodic features under varying combinations of prosody valence, auditory background complexity and attentional focus. Here, we used event-related functional magnetic resonance imaging to investigate the effects of high background sound complexity and attentional focus on brain activation to angry and neutral prosody in humans. Results show that prosody effects in mid superior temporal cortex were gated by background complexity but not attention, while prosody effects in the amygdala and anterior superior temporal cortex were gated by attention but not background complexity, suggesting distinct emotional prosody processing limitations in different regions. Crucially, if attention was focused on the highly complex background, the differential processing of emotional prosody was prevented in all brain regions, suggesting that in a distracting, complex auditory world even threatening voices may go unnoticed. PMID:26884543

Minding the Ecological Body: Neuropsychoanalysis and Ecopsychoanalysis

PubMed Central

Dodds, Joseph

2013-01-01

Neuropsychoanalysis explores experimentally and theoretically the philosophically ancient discussion of the relation of mind and body, and seems well placed to overcome the problem of a “mindless” neuroscience and a “brainless” psychology and psychotherapy, especially when combined with a greater awareness that the body itself, not only the brain, provides the material substrate for the emergent phenomenon we call mind. However, the mind-brain-body is itself situated within a complex ecological world, interacting with other mind-brain-bodies and the “non-human environment.” This occurs both synchronically and diachronically as the organism and its environment (living and non-living) interact in highly complex often non-linear ways. Psychoanalysis can do much to help unmask the anxieties, deficits, conflicts, phantasies, and defenses crucial in understanding the human dimension of the ecological crisis. Yet, psychoanalysis still largely remains not only a “psychology without biology,” which neuropsychoanalysis seeks to remedy, but also a “psychology without ecology.” Ecopsychoanalysis (Dodds, 2011b; Dodds and Jordan, 2012) is a new transdisciplinary approach drawing on a range of fields such as psychoanalysis, psychology, ecology, philosophy, science, complexity theory, esthetics, and the humanities. It attempts to play with what each approach has to offer in the sense of a heterogeneous assemblage of ideas and processes, mirroring the interlocking complexity, chaos, and turbulence of nature itself. By emphasizing the way the mind-brain-body studied by neuropsychoanalysis is embedded in wider social and ecological networks, ecopsychoanalysis can help open up the relevance of neuropsychoanalysis to wider fields of study, including those who are concerned with what Wilson (2003) called “the future of life.” PMID:23533027

Insights into Brain Glycogen Metabolism

PubMed Central

Mathieu, Cécile; de la Sierra-Gallay, Ines Li; Duval, Romain; Xu, Ximing; Cocaign, Angélique; Léger, Thibaut; Woffendin, Gary; Camadro, Jean-Michel; Etchebest, Catherine; Haouz, Ahmed; Dupret, Jean-Marie; Rodrigues-Lima, Fernando

2016-01-01

Brain glycogen metabolism plays a critical role in major brain functions such as learning or memory consolidation. However, alteration of glycogen metabolism and glycogen accumulation in the brain contributes to neurodegeneration as observed in Lafora disease. Glycogen phosphorylase (GP), a key enzyme in glycogen metabolism, catalyzes the rate-limiting step of glycogen mobilization. Moreover, the allosteric regulation of the three GP isozymes (muscle, liver, and brain) by metabolites and phosphorylation, in response to hormonal signaling, fine-tunes glycogenolysis to fulfill energetic and metabolic requirements. Whereas the structures of muscle and liver GPs have been known for decades, the structure of brain GP (bGP) has remained elusive despite its critical role in brain glycogen metabolism. Here, we report the crystal structure of human bGP in complex with PEG 400 (2.5 Å) and in complex with its allosteric activator AMP (3.4 Å). These structures demonstrate that bGP has a closer structural relationship with muscle GP, which is also activated by AMP, contrary to liver GP, which is not. Importantly, despite the structural similarities between human bGP and the two other mammalian isozymes, the bGP structures reveal molecular features unique to the brain isozyme that provide a deeper understanding of the differences in the activation properties of these allosteric enzymes by the allosteric effector AMP. Overall, our study further supports that the distinct structural and regulatory properties of GP isozymes contribute to the different functions of muscle, liver, and brain glycogen. PMID:27402852

Developments in deep brain stimulation using time dependent magnetic fields

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

Crowther, L.J.; Nlebedim, I.C.; Jiles, D.C.

2012-03-07

The effect of head model complexity upon the strength of field in different brain regions for transcranial magnetic stimulation (TMS) has been investigated. Experimental measurements were used to verify the validity of magnetic field calculations and induced electric field calculations for three 3D human head models of varying complexity. Results show the inability for simplified head models to accurately determine the site of high fields that lead to neuronal stimulation and highlight the necessity for realistic head modeling for TMS applications.

Developments in deep brain stimulation using time dependent magnetic fields

NASA Astrophysics Data System (ADS)

Crowther, L. J.; Nlebedim, I. C.; Jiles, D. C.

2012-04-01

The effect of head model complexity upon the strength of field in different brain regions for transcranial magnetic stimulation (TMS) has been investigated. Experimental measurements were used to verify the validity of magnetic field calculations and induced electric field calculations for three 3D human head models of varying complexity. Results show the inability for simplified head models to accurately determine the site of high fields that lead to neuronal stimulation and highlight the necessity for realistic head modeling for TMS applications.

Life history, cognition and the evolution of complex foraging niches.

PubMed

Schuppli, Caroline; Graber, Sereina M; Isler, Karin; van Schaik, Carel P

2016-03-01

Animal species that live in complex foraging niches have, in general, improved access to energy-rich and seasonally stable food sources. Because human food procurement is uniquely complex, we ask here which conditions may have allowed species to evolve into such complex foraging niches, and also how niche complexity is related to relative brain size. To do so, we divided niche complexity into a knowledge-learning and a motor-learning dimension. Using a sample of 78 primate and 65 carnivoran species, we found that two life-history features are consistently correlated with complex niches: slow, conservative development or provisioning of offspring over extended periods of time. Both act to buffer low energy yields during periods of learning, and may thus act as limiting factors for the evolution of complex niches. Our results further showed that the knowledge and motor dimensions of niche complexity were correlated with pace of development in primates only, and with the length of provisioning in only carnivorans. Accordingly, in primates, but not carnivorans, living in a complex foraging niche requires enhanced cognitive abilities, i.e., a large brain. The patterns in these two groups of mammals show that selection favors evolution into complex niches (in either the knowledge or motor dimension) in species that either develop more slowly or provision their young for an extended period of time. These findings help to explain how humans constructed by far the most complex niche: our ancestors managed to combine slow development (as in other primates) with systematic provisioning of immatures and even adults (as in carnivorans). This study also provides strong support for the importance of ecological factors in brain size evolution. Copyright © 2015 Elsevier Ltd. All rights reserved.

Where the thoughts dwell: the physiology of neuronal-glial "diffuse neural net".

PubMed

Verkhratsky, Alexei; Parpura, Vladimir; Rodríguez, José J

2011-01-07

The mechanisms underlying the production of thoughts by exceedingly complex cellular networks that construct the human brain constitute the most challenging problem of natural sciences. Our understanding of the brain function is very much shaped by the neuronal doctrine that assumes that neuronal networks represent the only substrate for cognition. These neuronal networks however are embedded into much larger and probably more complex network formed by neuroglia. The latter, although being electrically silent, employ many different mechanisms for intercellular signalling. It appears that astrocytes can control synaptic networks and in such a capacity they may represent an integral component of the computational power of the brain rather than being just brain "connective tissue". The fundamental question of whether neuroglia is involved in cognition and information processing remains, however, open. Indeed, a remarkable increase in the number of glial cells that distinguishes the human brain can be simply a result of exceedingly high specialisation of the neuronal networks, which delegated all matters of survival and maintenance to the neuroglia. At the same time potential power of analogue processing offered by internally connected glial networks may represent the alternative mechanism involved in cognition. Copyright © 2010 Elsevier B.V. All rights reserved.

Cerebral cartography and connectomics.

PubMed

Sporns, Olaf

2015-05-19

Cerebral cartography and connectomics pursue similar goals in attempting to create maps that can inform our understanding of the structural and functional organization of the cortex. Connectome maps explicitly aim at representing the brain as a complex network, a collection of nodes and their interconnecting edges. This article reflects on some of the challenges that currently arise in the intersection of cerebral cartography and connectomics. Principal challenges concern the temporal dynamics of functional brain connectivity, the definition of areal parcellations and their hierarchical organization into large-scale networks, the extension of whole-brain connectivity to cellular-scale networks, and the mapping of structure/function relations in empirical recordings and computational models. Successfully addressing these challenges will require extensions of methods and tools from network science to the mapping and analysis of human brain connectivity data. The emerging view that the brain is more than a collection of areas, but is fundamentally operating as a complex networked system, will continue to drive the creation of ever more detailed and multi-modal network maps as tools for on-going exploration and discovery in human connectomics. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

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

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.

Segmenting Brain Tissues from Chinese Visible Human Dataset by Deep-Learned Features with Stacked Autoencoder

PubMed Central

Zhao, Guangjun; Wang, Xuchu; Niu, Yanmin; Tan, Liwen; Zhang, Shao-Xiang

2016-01-01

Cryosection brain images in Chinese Visible Human (CVH) dataset contain rich anatomical structure information of tissues because of its high resolution (e.g., 0.167 mm per pixel). Fast and accurate segmentation of these images into white matter, gray matter, and cerebrospinal fluid plays a critical role in analyzing and measuring the anatomical structures of human brain. However, most existing automated segmentation methods are designed for computed tomography or magnetic resonance imaging data, and they may not be applicable for cryosection images due to the imaging difference. In this paper, we propose a supervised learning-based CVH brain tissues segmentation method that uses stacked autoencoder (SAE) to automatically learn the deep feature representations. Specifically, our model includes two successive parts where two three-layer SAEs take image patches as input to learn the complex anatomical feature representation, and then these features are sent to Softmax classifier for inferring the labels. Experimental results validated the effectiveness of our method and showed that it outperformed four other classical brain tissue detection strategies. Furthermore, we reconstructed three-dimensional surfaces of these tissues, which show their potential in exploring the high-resolution anatomical structures of human brain. PMID:27057543

Segmenting Brain Tissues from Chinese Visible Human Dataset by Deep-Learned Features with Stacked Autoencoder.

PubMed

Zhao, Guangjun; Wang, Xuchu; Niu, Yanmin; Tan, Liwen; Zhang, Shao-Xiang

2016-01-01

Cryosection brain images in Chinese Visible Human (CVH) dataset contain rich anatomical structure information of tissues because of its high resolution (e.g., 0.167 mm per pixel). Fast and accurate segmentation of these images into white matter, gray matter, and cerebrospinal fluid plays a critical role in analyzing and measuring the anatomical structures of human brain. However, most existing automated segmentation methods are designed for computed tomography or magnetic resonance imaging data, and they may not be applicable for cryosection images due to the imaging difference. In this paper, we propose a supervised learning-based CVH brain tissues segmentation method that uses stacked autoencoder (SAE) to automatically learn the deep feature representations. Specifically, our model includes two successive parts where two three-layer SAEs take image patches as input to learn the complex anatomical feature representation, and then these features are sent to Softmax classifier for inferring the labels. Experimental results validated the effectiveness of our method and showed that it outperformed four other classical brain tissue detection strategies. Furthermore, we reconstructed three-dimensional surfaces of these tissues, which show their potential in exploring the high-resolution anatomical structures of human brain.

Influence of White and Gray Matter Connections on Endogenous Human Cortical Oscillations

PubMed Central

Hawasli, Ammar H.; Kim, DoHyun; Ledbetter, Noah M.; Dahiya, Sonika; Barbour, Dennis L.; Leuthardt, Eric C.

2016-01-01

Brain oscillations reflect changes in electrical potentials summated across neuronal populations. Low- and high-frequency rhythms have different modulation patterns. Slower rhythms are spatially broad, while faster rhythms are more local. From this observation, we hypothesized that low- and high-frequency oscillations reflect white- and gray-matter communications, respectively, and synchronization between low-frequency phase with high-frequency amplitude represents a mechanism enabling distributed brain-networks to coordinate local processing. Testing this common understanding, we selectively disrupted white or gray matter connections to human cortex while recording surface field potentials. Counter to our original hypotheses, we found that cortex consists of independent oscillatory-units (IOUs) that maintain their own complex endogenous rhythm structure. IOUs are differentially modulated by white and gray matter connections. White-matter connections maintain topographical anatomic heterogeneity (i.e., separable processing in cortical space) and gray-matter connections segregate cortical synchronization patterns (i.e., separable temporal processing through phase-power coupling). Modulation of distinct oscillatory modules enables the functional diversity necessary for complex processing in the human brain. PMID:27445767

Decoding the time-course of object recognition in the human brain: From visual features to categorical decisions.

PubMed

Contini, Erika W; Wardle, Susan G; Carlson, Thomas A

2017-10-01

Visual object recognition is a complex, dynamic process. Multivariate pattern analysis methods, such as decoding, have begun to reveal how the brain processes complex visual information. Recently, temporal decoding methods for EEG and MEG have offered the potential to evaluate the temporal dynamics of object recognition. Here we review the contribution of M/EEG time-series decoding methods to understanding visual object recognition in the human brain. Consistent with the current understanding of the visual processing hierarchy, low-level visual features dominate decodable object representations early in the time-course, with more abstract representations related to object category emerging later. A key finding is that the time-course of object processing is highly dynamic and rapidly evolving, with limited temporal generalisation of decodable information. Several studies have examined the emergence of object category structure, and we consider to what degree category decoding can be explained by sensitivity to low-level visual features. Finally, we evaluate recent work attempting to link human behaviour to the neural time-course of object processing. Copyright © 2017 Elsevier Ltd. All rights reserved.

Growth and development of the brain and impact on cognitive outcomes.

PubMed

Hüppi, Petra S

2010-01-01

Understanding human brain development from the fetal life to adulthood is of great clinical importance as many neurological and neurobehavioral disorders have their origin in early structural and functional cerebral maturation. The developing brain is particularly prone to being affected by endogenous and exogenous events through the fetal and early postnatal life. The concept of 'developmental plasticity or disruption of the developmental program' summarizes these events. Increases in white matter, which speed up communication between brain cells, growing complexity of neuronal networks suggested by gray and white matter changes, and environmentally sensitive plasticity are all essential aspects in a child's ability to mentalize and maintain the adaptive flexibility necessary for achieving high sociocognitive functioning. Advancement in neuroimaging has opened up new ways for examining the developing human brain in vivo, the study of the effects of early antenatal, perinatal and neonatal events on later structural and functional brain development resulting in developmental disabilities or developmental resilience. In this review, methods of quantitative assessment of human brain development, such as 3D-MRI with image segmentation, diffusion tensor imaging to assess connectivity and functional MRI to visualize brain function will be presented. Copyright (c) 2010 S. Karger AG, Basel.

Bacteroides fragilis Lipopolysaccharide and Inflammatory Signaling in Alzheimer’s Disease

PubMed Central

Lukiw, Walter J.

2016-01-01

The human microbiome consists of ~3.8 × 1013 symbiotic microorganisms that form a highly complex and dynamic ecosystem: the gastrointestinal (GI) tract constitutes the largest repository of the human microbiome by far, and its impact on human neurological health and disease is becoming increasingly appreciated. Bacteroidetes, the largest phylum of Gram-negative bacteria in the GI tract microbiome, while generally beneficial to the host when confined to the GI tract, have potential to secrete a remarkably complex array of pro-inflammatory neurotoxins that include surface lipopolysaccharides (LPSs) and toxic proteolytic peptides. The deleterious effects of these bacterial exudates appear to become more important as GI tract and blood-brain barriers alter or increase their permeability with aging and disease. For example, presence of the unique LPSs of the abundant Bacteroidetes species Bacteroides fragilis (BF-LPS) in the serum represents a major contributing factor to systemic inflammation. BF-LPS is further recognized by TLR2, TLR4, and/or CD14 microglial cell receptors as are the pro-inflammatory 42 amino acid amyloid-beta (Aβ42) peptides that characterize Alzheimer’s disease (AD) brain. Here we provide the first evidence that BF-LPS exposure to human primary brain cells is an exceptionally potent inducer of the pro-inflammatory transcription factor NF-kB (p50/p65) complex, a known trigger in the expression of pathogenic pathways involved in inflammatory neurodegeneration. This ‘Perspectives communication’ will in addition highlight work from recent studies that advance novel and emerging concepts on the potential contribution of microbiome-generated factors, such as BF-LPS, in driving pro-inflammatory degenerative neuropathology in the AD brain. PMID:27725817

Distributed Neural Activity Patterns during Human-to-Human Competition

PubMed Central

Piva, Matthew; Zhang, Xian; Noah, J. Adam; Chang, Steve W. C.; Hirsch, Joy

2017-01-01

Interpersonal interaction is the essence of human social behavior. However, conventional neuroimaging techniques have tended to focus on social cognition in single individuals rather than on dyads or groups. As a result, relatively little is understood about the neural events that underlie face-to-face interaction. We resolved some of the technical obstacles inherent in studying interaction using a novel imaging modality and aimed to identify neural mechanisms engaged both within and across brains in an ecologically valid instance of interpersonal competition. Functional near-infrared spectroscopy was utilized to simultaneously measure hemodynamic signals representing neural activity in pairs of subjects playing poker against each other (human–human condition) or against computer opponents (human–computer condition). Previous fMRI findings concerning single subjects confirm that neural areas recruited during social cognition paradigms are individually sensitive to human–human and human–computer conditions. However, it is not known whether face-to-face interactions between opponents can extend these findings. We hypothesize distributed effects due to live processing and specific variations in across-brain coherence not observable in single-subject paradigms. Angular gyrus (AG), a component of the temporal-parietal junction (TPJ) previously found to be sensitive to socially relevant cues, was selected as a seed to measure within-brain functional connectivity. Increased connectivity was confirmed between AG and bilateral dorsolateral prefrontal cortex (dlPFC) as well as a complex including the left subcentral area (SCA) and somatosensory cortex (SS) during interaction with a human opponent. These distributed findings were supported by contrast measures that indicated increased activity at the left dlPFC and frontopolar area that partially overlapped with the region showing increased functional connectivity with AG. Across-brain analyses of neural coherence between the players revealed synchrony between dlPFC and supramarginal gyrus (SMG) and SS in addition to synchrony between AG and the fusiform gyrus (FG) and SMG. These findings present the first evidence of a frontal-parietal neural complex including the TPJ, dlPFC, SCA, SS, and FG that is more active during human-to-human social cognition both within brains (functional connectivity) and across brains (across-brain coherence), supporting a model of functional integration of socially and strategically relevant information during live face-to-face competitive behaviors. PMID:29218005

The development of Human Functional Brain Networks

PubMed Central

Power, Jonathan D; Fair, Damien A; Schlaggar, Bradley L

2010-01-01

Recent advances in MRI technology have enabled precise measurements of correlated activity throughout the brain, leading to the first comprehensive descriptions of functional brain networks in humans. This article reviews the growing literature on the development of functional networks, from infancy through adolescence, as measured by resting state functional connectivity MRI. We note several limitations of traditional approaches to describing brain networks, and describe a powerful framework for analyzing networks, called graph theory. We argue that characterization of the development of brain systems (e.g. the default mode network) should be comprehensive, considering not only relationships within a given system, but also how these relationships are situated within wider network contexts. We note that, despite substantial reorganization of functional connectivity, several large-scale network properties appear to be preserved across development, suggesting that functional brain networks, even in children, are organized in manners similar to other complex systems. PMID:20826306

Listening to humans walking together activates the social brain circuitry.

PubMed

Saarela, Miiamaaria V; Hari, Riitta

2008-01-01

Human footsteps carry a vast amount of social information, which is often unconsciously noted. Using functional magnetic resonance imaging, we analyzed brain networks activated by footstep sounds of one or two persons walking. Listening to two persons walking together activated brain areas previously associated with affective states and social interaction, such as the subcallosal gyrus bilaterally, the right temporal pole, and the right amygdala. These areas seem to be involved in the analysis of persons' identity and complex social stimuli on the basis of auditory cues. Single footsteps activated only the biological motion area in the posterior STS region. Thus, hearing two persons walking together involved a more widespread brain network than did hearing footsteps from a single person.

Parallel workflow tools to facilitate human brain MRI post-processing

PubMed Central

Cui, Zaixu; Zhao, Chenxi; Gong, Gaolang

2015-01-01

Multi-modal magnetic resonance imaging (MRI) techniques are widely applied in human brain studies. To obtain specific brain measures of interest from MRI datasets, a number of complex image post-processing steps are typically required. Parallel workflow tools have recently been developed, concatenating individual processing steps and enabling fully automated processing of raw MRI data to obtain the final results. These workflow tools are also designed to make optimal use of available computational resources and to support the parallel processing of different subjects or of independent processing steps for a single subject. Automated, parallel MRI post-processing tools can greatly facilitate relevant brain investigations and are being increasingly applied. In this review, we briefly summarize these parallel workflow tools and discuss relevant issues. PMID:26029043

Major Shifts in Glial Regional Identity Are a Transcriptional Hallmark of Human Brain Aging.

PubMed

Soreq, Lilach; Rose, Jamie; Soreq, Eyal; Hardy, John; Trabzuni, Daniah; Cookson, Mark R; Smith, Colin; Ryten, Mina; Patani, Rickie; Ule, Jernej

2017-01-10

Gene expression studies suggest that aging of the human brain is determined by a complex interplay of molecular events, although both its region- and cell-type-specific consequences remain poorly understood. Here, we extensively characterized aging-altered gene expression changes across ten human brain regions from 480 individuals ranging in age from 16 to 106 years. We show that astrocyte- and oligodendrocyte-specific genes, but not neuron-specific genes, shift their regional expression patterns upon aging, particularly in the hippocampus and substantia nigra, while the expression of microglia- and endothelial-specific genes increase in all brain regions. In line with these changes, high-resolution immunohistochemistry demonstrated decreased numbers of oligodendrocytes and of neuronal subpopulations in the aging brain cortex. Finally, glial-specific genes predict age with greater precision than neuron-specific genes, thus highlighting the need for greater mechanistic understanding of neuron-glia interactions in aging and late-life diseases. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Does menaquinone participate in brain astrocyte electron transport?

PubMed

Lovern, Douglas; Marbois, Beth

2013-10-01

Quinone compounds act as membrane resident carriers of electrons between components of the electron transport chain in the periplasmic space of prokaryotes and in the mitochondria of eukaryotes. Vitamin K is a quinone compound in the human body in a storage form as menaquinone (MK); distribution includes regulated amounts in mitochondrial membranes. The human brain, which has low amounts of typical vitamin K dependent function (e.g., gamma carboxylase) has relatively high levels of MK, and different regions of brain have different amounts. Coenzyme Q (Q), is a quinone synthesized de novo, and the levels of synthesis decline with age. The levels of MK are dependent on dietary intake and generally increase with age. MK has a characterized role in the transfer of electrons to fumarate in prokaryotes. A newly recognized fumarate cycle has been identified in brain astrocytes. The MK precursor menadione has been shown to donate electrons directly to mitochondrial complex III. Vitamin K compounds function in the electron transport chain of human brain astrocytes. Copyright © 2013 Elsevier Ltd. All rights reserved.

Association between increased EEG signal complexity and cannabis dependence.

PubMed

Laprevote, Vincent; Bon, Laura; Krieg, Julien; Schwitzer, Thomas; Bourion-Bedes, Stéphanie; Maillard, Louis; Schwan, Raymund

2017-12-01

Both acute and regular cannabis use affects the functioning of the brain. While several studies have demonstrated that regular cannabis use can impair the capacity to synchronize neural assemblies during specific tasks, less is known about spontaneous brain activity. This can be explored by measuring EEG complexity, which reflects the spontaneous variability of human brain activity. A recent study has shown that acute cannabis use can affect that complexity. Since the characteristics of cannabis use can affect the impact on brain functioning, this study sets out to measure EEG complexity in regular cannabis users with or without dependence, in comparison with healthy controls. We recruited 26 healthy controls, 25 cannabis users without cannabis dependence and 14 cannabis users with cannabis dependence, based on DSM IV TR criteria. The EEG signal was extracted from at least 250 epochs of the 500ms pre-stimulation phase during a visual evoked potential paradigm. Brain complexity was estimated using Lempel-Ziv Complexity (LZC), which was compared across groups by non-parametric Kruskall-Wallis ANOVA. The analysis revealed a significant difference between the groups, with higher LZC in participants with cannabis dependence than in non-dependent cannabis users. There was no specific localization of this effect across electrodes. We showed that cannabis dependence is associated to an increased spontaneous brain complexity in regular users. This result is in line with previous results in acute cannabis users. It may reflect increased randomness of neural activity in cannabis dependence. Future studies should explore whether this effect is permanent or diminishes with cannabis cessation. Copyright © 2017 Elsevier B.V. and ECNP. All rights reserved.

Putting the brain to work: neuroergonomics past, present, and future.

PubMed

Parasuraman, Raja; Wilson, Glenn F

2008-06-01

The authors describe research and applications in prominent areas of neuroergonomics. Because human factors/ergonomics examines behavior and mind at work, it should include the study of brain mechanisms underlying human performance. Neuroergonomic studies are reviewed in four areas: workload and vigilance, adaptive automation, neuroengineering, and molecular genetics and individual differences. Neuroimaging studies have helped identify the components of mental workload, workload assessment in complex tasks, and resource depletion in vigilance. Furthermore, real-time neurocognitive assessment of workload can trigger adaptive automation. Neural measures can also drive brain-computer interfaces to provide disabled users new communication channels. Finally, variants of particular genes can be associated with individual differences in specific cognitive functions. Neuroergonomics shows that considering what makes work possible - the human brain - can enrich understanding of the use of technology by humans and can inform technological design. Applications of neuroergonomics include the assessment of operator workload and vigilance, implementation of real-time adaptive automation, neuroengineering for people with disabilities, and design of selection and training methods.

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

PubMed

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

2014-09-01

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

Asymmetry of Hemispheric Network Topology Reveals Dissociable Processes between Functional and Structural Brain Connectome in Community-Living Elders

PubMed Central

Sun, Yu; Li, Junhua; Suckling, John; Feng, Lei

2017-01-01

Human brain is structurally and functionally asymmetrical and the asymmetries of brain phenotypes have been shown to change in normal aging. Recent advances in graph theoretical analysis have showed topological lateralization between hemispheric networks in the human brain throughout the lifespan. Nevertheless, apparent discrepancies of hemispheric asymmetry were reported between the structural and functional brain networks, indicating the potentially complex asymmetry patterns between structural and functional networks in aging population. In this study, using multimodal neuroimaging (resting-state fMRI and structural diffusion tensor imaging), we investigated the characteristics of hemispheric network topology in 76 (male/female = 15/61, age = 70.08 ± 5.30 years) community-dwelling older adults. Hemispheric functional and structural brain networks were obtained for each participant. Graph theoretical approaches were then employed to estimate the hemispheric topological properties. We found that the optimal small-world properties were preserved in both structural and functional hemispheric networks in older adults. Moreover, a leftward asymmetry in both global and local levels were observed in structural brain networks in comparison with a symmetric pattern in functional brain network, suggesting a dissociable process of hemispheric asymmetry between structural and functional connectome in healthy older adults. Finally, the scores of hemispheric asymmetry in both structural and functional networks were associated with behavioral performance in various cognitive domains. Taken together, these findings provide new insights into the lateralized nature of multimodal brain connectivity, highlight the potentially complex relationship between structural and functional brain network alterations, and augment our understanding of asymmetric structural and functional specializations in normal aging. PMID:29209197

Algebraic Topology of Multi-Brain Connectivity Networks Reveals Dissimilarity in Functional Patterns during Spoken Communications

PubMed Central

Tadić, Bosiljka; Andjelković, Miroslav; Boshkoska, Biljana Mileva; Levnajić, Zoran

2016-01-01

Human behaviour in various circumstances mirrors the corresponding brain connectivity patterns, which are suitably represented by functional brain networks. While the objective analysis of these networks by graph theory tools deepened our understanding of brain functions, the multi-brain structures and connections underlying human social behaviour remain largely unexplored. In this study, we analyse the aggregate graph that maps coordination of EEG signals previously recorded during spoken communications in two groups of six listeners and two speakers. Applying an innovative approach based on the algebraic topology of graphs, we analyse higher-order topological complexes consisting of mutually interwoven cliques of a high order to which the identified functional connections organise. Our results reveal that the topological quantifiers provide new suitable measures for differences in the brain activity patterns and inter-brain synchronisation between speakers and listeners. Moreover, the higher topological complexity correlates with the listener’s concentration to the story, confirmed by self-rating, and closeness to the speaker’s brain activity pattern, which is measured by network-to-network distance. The connectivity structures of the frontal and parietal lobe consistently constitute distinct clusters, which extend across the listener’s group. Formally, the topology quantifiers of the multi-brain communities exceed the sum of those of the participating individuals and also reflect the listener’s rated attributes of the speaker and the narrated subject. In the broader context, the presented study exposes the relevance of higher topological structures (besides standard graph measures) for characterising functional brain networks under different stimuli. PMID:27880802

A dynamic in vivo-like organotypic blood-brain barrier model to probe metastatic brain tumors

NASA Astrophysics Data System (ADS)

Xu, Hui; Li, Zhongyu; Yu, Yue; Sizdahkhani, Saman; Ho, Winson S.; Yin, Fangchao; Wang, Li; Zhu, Guoli; Zhang, Min; Jiang, Lei; Zhuang, Zhengping; Qin, Jianhua

2016-11-01

The blood-brain barrier (BBB) restricts the uptake of many neuro-therapeutic molecules, presenting a formidable hurdle to drug development in brain diseases. We proposed a new and dynamic in vivo-like three-dimensional microfluidic system that replicates the key structural, functional and mechanical properties of the blood-brain barrier in vivo. Multiple factors in this system work synergistically to accentuate BBB-specific attributes-permitting the analysis of complex organ-level responses in both normal and pathological microenvironments in brain tumors. The complex BBB microenvironment is reproduced in this system via physical cell-cell interaction, vascular mechanical cues and cell migration. This model possesses the unique capability to examine brain metastasis of human lung, breast and melanoma cells and their therapeutic responses to chemotherapy. The results suggest that the interactions between cancer cells and astrocytes in BBB microenvironment might affect the ability of malignant brain tumors to traverse between brain and vascular compartments. Furthermore, quantification of spatially resolved barrier functions exists within a single assay, providing a versatile and valuable platform for pharmaceutical development, drug testing and neuroscientific research.

Ultrastructural pathology of cortical capillary pericytes in human traumatic brain oedema.

PubMed

Castejón, Orlando J

2011-01-01

In human traumatic brain oedema pericytes exhibit remarkable oedematous changes, increased vacuolar and vesicular transport, transient transpericytal channels, and tubular structures demonstrating pericyte brain barrier dysfunction. They show nuclear invaginations, actin and myosin-like filaments, and coupled interaction with endothelial cells through the macula occludens. Some pericytes display hypertrophic and necrotic changes, and phagocytic capacity. Hypertrophic pericytes induce basement membrane splitting. Degenerated pericytes exhibit lacunar enlargement of endoplasmic reticulum, dense osmiophilic bodies, glycogen granules, vacuolization, oedematous Golgi apparatus, and pleomorphic mitochondria. Certain micropinocytotic vesicles are orientated to the Golgi complex and multivesicular bodies, suggesting that pericytes play some role in oedema resolution.

Natural and Artificial Intelligence, Language, Consciousness, Emotion, and Anticipation

NASA Astrophysics Data System (ADS)

Dubois, Daniel M.

2010-11-01

The classical paradigm of the neural brain as the seat of human natural intelligence is too restrictive. This paper defends the idea that the neural ectoderm is the actual brain, based on the development of the human embryo. Indeed, the neural ectoderm includes the neural crest, given by pigment cells in the skin and ganglia of the autonomic nervous system, and the neural tube, given by the brain, the spinal cord, and motor neurons. So the brain is completely integrated in the ectoderm, and cannot work alone. The paper presents fundamental properties of the brain as follows. Firstly, Paul D. MacLean proposed the triune human brain, which consists to three brains in one, following the species evolution, given by the reptilian complex, the limbic system, and the neo-cortex. Secondly, the consciousness and conscious awareness are analysed. Thirdly, the anticipatory unconscious free will and conscious free veto are described in agreement with the experiments of Benjamin Libet. Fourthly, the main section explains the development of the human embryo and shows that the neural ectoderm is the whole neural brain. Fifthly, a conjecture is proposed that the neural brain is completely programmed with scripts written in biological low-level and high-level languages, in a manner similar to the programmed cells by the genetic code. Finally, it is concluded that the proposition of the neural ectoderm as the whole neural brain is a breakthrough in the understanding of the natural intelligence, and also in the future design of robots with artificial intelligence.

What can music tell us about social interaction?

PubMed

D'Ausilio, Alessandro; Novembre, Giacomo; Fadiga, Luciano; Keller, Peter E

2015-03-01

Humans are innately social creatures, but cognitive neuroscience, that has traditionally focused on individual brains, is only now beginning to investigate social cognition through realistic interpersonal interaction. Music provides an ideal domain for doing so because it offers a promising solution for balancing the trade-off between ecological validity and experimental control when testing cognitive and brain functions. Musical ensembles constitute a microcosm that provides a platform for parametrically modeling the complexity of human social interaction. Copyright © 2015 Elsevier Ltd. All rights reserved.

Deep Neural Networks Reveal a Gradient in the Complexity of Neural Representations across the Ventral Stream.

PubMed

Güçlü, Umut; van Gerven, Marcel A J

2015-07-08

Converging evidence suggests that the primate ventral visual pathway encodes increasingly complex stimulus features in downstream areas. We quantitatively show that there indeed exists an explicit gradient for feature complexity in the ventral pathway of the human brain. This was achieved by mapping thousands of stimulus features of increasing complexity across the cortical sheet using a deep neural network. Our approach also revealed a fine-grained functional specialization of downstream areas of the ventral stream. Furthermore, it allowed decoding of representations from human brain activity at an unsurpassed degree of accuracy, confirming the quality of the developed approach. Stimulus features that successfully explained neural responses indicate that population receptive fields were explicitly tuned for object categorization. This provides strong support for the hypothesis that object categorization is a guiding principle in the functional organization of the primate ventral stream. Copyright © 2015 the authors 0270-6474/15/3510005-10$15.00/0.

Fractal dimension assessment of brain white matter structural complexity post stroke in relation to upper-extremity motor function

PubMed Central

Zhang, Luduan; Butler, Andrew J.; Sun, Chang-Kai; Sahgal, Vinod; Wittenberg, George F.; Yue, Guang H.

2008-01-01

Little is known about the association between brain white matter (WM) structure and motor function in humans. This study investigated complexity of brain WM interior shape as determined by magnetic resonance imaging (MRI) and its relationship with upper-extremity (UE) motor function in patients post stroke. We hypothesized that (1) the WM complexity would decrease following stroke, and (2) higher WM complexity in non-affected cortical areas would be related to greater UE motor function. Thirty-eight stroke patients (16 with left-hemisphere lesions) underwent MRI anatomical brain scans. Fractal dimension (FD), a quantitative shape metric, was applied onto skeletonized brain WM images to evaluate WM internal structural complexity. Wolf Motor Function Test (WMFT) and Fugl-Meyer Motor Assessment (FM) scores were measured to assess motor function of the affected limb. The WM complexity was lower in the stroke-affected hemisphere. The FD was associated with better motor function in two subgroups: with left-subcortical lesions, FD values of the lesion-free areas of the left hemisphere were associated with better FM scores; with right-cortical lesions, FD values of lesion-free regions were robustly associated with better WMFT scores. These findings suggest that greater residual WM complexity is associated with less impaired UE motor function, which is more robust in patients with right-hemisphere lesions. No correlations were found between lesion volume and WMFT or FM scores. This study addressed WM complexity in stroke patients and its relationship with UE motor function. Measurement of brain WM reorganization may be a sensitive correlate of UE function in people recovering from stroke. PMID:18590710

Following the Hand: The First Three Years of Life.

ERIC Educational Resources Information Center

Orion, Judy

2001-01-01

Discusses the development of the human hand from birth to age three as it contributes to the formation of human personality. Considers how parallels in eye, hand, brain, and motor skill development portray the evolving complexity and adaptation of the human grasp and illustrate Montessori theories about the relationship between physical experience…

Describing the Neuron Axons Network of the Human Brain by Continuous Flow Models

NASA Astrophysics Data System (ADS)

Hizanidis, J.; Katsaloulis, P.; Verganelakis, D. A.; Provata, A.

2014-12-01

The multifractal spectrum Dq (Rényi dimensions) is used for the analysis and comparison between the Neuron Axons Network (NAN) of healthy and pathological human brains because it conveys information about the statistics in many scales, from the very rare to the most frequent network configurations. Comparison of the Fractional Anisotropy Magnetic Resonance Images between healthy and pathological brains is performed with and without noise reduction. Modelling the complex structure of the NAN in the human brain is undertaken using the dynamics of the Lorenz model in the chaotic regime. The Lorenz multifractal spectra capture well the human brain characteristics in the large negative q's which represent the rare network configurations. In order to achieve a closer approximation in the positive part of the spectrum (q > 0) two independent modifications are considered: a) redistribution of the dense parts of the Lorenz model's phase space into their neighbouring areas and b) inclusion of additive uniform noise in the Lorenz model. Both modifications, independently, drive the Lorenz spectrum closer to the human NAN one in the positive q region without destroying the already good correspondence of the negative spectra. The modelling process shows that the unmodified Lorenz model in its full chaotic regime has a phase space distribution with high fluctuations in its dense parts, while the fluctuations in the human brain NAN are smoother. The induced modifications (phase space redistribution or additive noise) moderate the fluctuations only in the positive part of the Lorenz spectrum leading to a faithful representation of the human brain axons network in all scales.

Research of Hubs Location Method for Weighted Brain Network Based on NoS-FA.

PubMed

Weng, Zhengkui; Wang, Bin; Xue, Jie; Yang, Baojie; Liu, Hui; Xiong, Xin

2017-01-01

As a complex network of many interlinked brain regions, there are some central hub regions which play key roles in the structural human brain network based on T1 and diffusion tensor imaging (DTI) technology. Since most studies about hubs location method in the whole human brain network are mainly concerned with the local properties of each single node but not the global properties of all the directly connected nodes, a novel hubs location method based on global importance contribution evaluation index is proposed in this study. The number of streamlines (NoS) is fused with normalized fractional anisotropy (FA) for more comprehensive brain bioinformation. The brain region importance contribution matrix and information transfer efficiency value are constructed, respectively, and then by combining these two factors together we can calculate the importance value of each node and locate the hubs. Profiting from both local and global features of the nodes and the multi-information fusion of human brain biosignals, the experiment results show that this method can detect the brain hubs more accurately and reasonably compared with other methods. Furthermore, the proposed location method is used in impaired brain hubs connectivity analysis of schizophrenia patients and the results are in agreement with previous studies.

Exploiting Complexity Information for Brain Activation Detection

PubMed Central

Zhang, Yan; Liang, Jiali; Lin, Qiang; Hu, Zhenghui

2016-01-01

We present a complexity-based approach for the analysis of fMRI time series, in which sample entropy (SampEn) is introduced as a quantification of the voxel complexity. Under this hypothesis the voxel complexity could be modulated in pertinent cognitive tasks, and it changes through experimental paradigms. We calculate the complexity of sequential fMRI data for each voxel in two distinct experimental paradigms and use a nonparametric statistical strategy, the Wilcoxon signed rank test, to evaluate the difference in complexity between them. The results are compared with the well known general linear model based Statistical Parametric Mapping package (SPM12), where a decided difference has been observed. This is because SampEn method detects brain complexity changes in two experiments of different conditions and the data-driven method SampEn evaluates just the complexity of specific sequential fMRI data. Also, the larger and smaller SampEn values correspond to different meanings, and the neutral-blank design produces higher predictability than threat-neutral. Complexity information can be considered as a complementary method to the existing fMRI analysis strategies, and it may help improving the understanding of human brain functions from a different perspective. PMID:27045838

Effect of bulk modulus on deformation of the brain under rotational accelerations

NASA Astrophysics Data System (ADS)

Ganpule, S.; Daphalapurkar, N. P.; Cetingul, M. P.; Ramesh, K. T.

2018-01-01

Traumatic brain injury such as that developed as a consequence of blast is a complex injury with a broad range of symptoms and disabilities. Computational models of brain biomechanics hold promise for illuminating the mechanics of traumatic brain injury and for developing preventive devices. However, reliable material parameters are needed for models to be predictive. Unfortunately, the properties of human brain tissue are difficult to measure, and the bulk modulus of brain tissue in particular is not well characterized. Thus, a wide range of bulk modulus values are used in computational models of brain biomechanics, spanning up to three orders of magnitude in the differences between values. However, the sensitivity of these variations on computational predictions is not known. In this work, we study the sensitivity of a 3D computational human head model to various bulk modulus values. A subject-specific human head model was constructed from T1-weighted MRI images at 2-mm3 voxel resolution. Diffusion tensor imaging provided data on spatial distribution and orientation of axonal fiber bundles for modeling white matter anisotropy. Non-injurious, full-field brain deformations in a human volunteer were used to assess the simulated predictions. The comparison suggests that a bulk modulus value on the order of GPa gives the best agreement with experimentally measured in vivo deformations in the human brain. Further, simulations of injurious loading suggest that bulk modulus values on the order of GPa provide the closest match with the clinical findings in terms of predicated injured regions and extent of injury.

Is a Universal Science of Complexity Conceivable?

NASA Astrophysics Data System (ADS)

West, Geoffrey B.

Over the past quarter of a century, terms like complex adaptive system, the science of complexity, emergent behavior, self-organization, and adaptive dynamics have entered the literature, reflecting the rapid growth in collaborative, trans-disciplinary research on fundamental problems in complex systems ranging across the entire spectrum of science from the origin and dynamics of organisms and ecosystems to financial markets, corporate dynamics, urbanization and the human brain...

Genetic mouse models of brain ageing and Alzheimer's disease.

PubMed

Bilkei-Gorzo, Andras

2014-05-01

Progression of brain ageing is influenced by a complex interaction of genetic and environmental factors. Analysis of genetically modified animals with uniform genetic backgrounds in a standardised, controlled environment enables the dissection of critical determinants of brain ageing on a molecular level. Human and animal studies suggest that increased load of damaged macromolecules, efficacy of DNA maintenance, mitochondrial activity, and cellular stress defences are critical determinants of brain ageing. Surprisingly, mouse lines with genetic impairment of anti-oxidative capacity generally did not show enhanced cognitive ageing but rather an increased sensitivity to oxidative challenge. Mouse lines with impaired mitochondrial activity had critically short life spans or severe and rapidly progressing neurodegeneration. Strains with impaired clearance in damaged macromolecules or defects in the regulation of cellular stress defences showed alterations in the onset and progression of cognitive decline. Importantly, reduced insulin/insulin-like growth factor signalling generally increased life span but impaired cognitive functions revealing a complex interaction between ageing of the brain and of the body. Brain ageing is accompanied by an increased risk of developing Alzheimer's disease. Transgenic mouse models expressing high levels of mutant human amyloid precursor protein showed a number of symptoms and pathophysiological processes typical for early phase of Alzheimer's disease. Generally, therapeutic strategies effective against Alzheimer's disease in humans were also active in the Tg2576, APP23, APP/PS1 and 5xFAD lines, but a large number of false positive findings were also reported. The 3xtg AD model likely has the highest face and construct validity but further studies are needed. Copyright © 2013 Elsevier Inc. All rights reserved.

Individual T1-weighted/T2-weighted ratio brain networks: Small-worldness, hubs and modular organization

NASA Astrophysics Data System (ADS)

Wu, Huijun; Wang, Hao; Lü, Linyuan

Applying network science to investigate the complex systems has become a hot topic. In neuroscience, understanding the architectures of complex brain networks was a vital issue. An enormous amount of evidence had supported the brain was cost/efficiency trade-off with small-worldness, hubness and modular organization through the functional MRI and structural MRI investigations. However, the T1-weighted/T2-weighted (T1w/T2w) ratio brain networks were mostly unexplored. Here, we utilized a KL divergence-based method to construct large-scale individual T1w/T2w ratio brain networks and investigated the underlying topological attributes of these networks. Our results supported that the T1w/T2w ratio brain networks were comprised of small-worldness, an exponentially truncated power-law degree distribution, frontal-parietal hubs and modular organization. Besides, there were significant positive correlations between the network metrics and fluid intelligence. Thus, the T1w/T2w ratio brain networks open a new avenue to understand the human brain and are a necessary supplement for future MRI studies.

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

PubMed

Barch, Deanna M

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

Systemic combinatorial peptide selection yields a non-canonical iron-mimicry mechanism for targeting tumors in a mouse model of human glioblastoma

PubMed Central

Staquicini, Fernanda I.; Ozawa, Michael G.; Moya, Catherine A.; Driessen, Wouter H.P.; Barbu, E. Magda; Nishimori, Hiroyuki; Soghomonyan, Suren; Flores, Leo G.; Liang, Xiaowen; Paolillo, Vincenzo; Alauddin, Mian M.; Basilion, James P.; Furnari, Frank B.; Bogler, Oliver; Lang, Frederick F.; Aldape, Kenneth D.; Fuller, Gregory N.; Höök, Magnus; Gelovani, Juri G.; Sidman, Richard L.; Cavenee, Webster K.; Pasqualini, Renata; Arap, Wadih

2010-01-01

The management of CNS tumors is limited by the blood-brain barrier (BBB), a vascular interface that restricts the passage of most molecules from the blood into the brain. Here we show that phage particles targeted with certain ligand motifs selected in vivo from a combinatorial peptide library can cross the BBB under normal and pathological conditions. Specifically, we demonstrated that phage clones displaying an iron-mimic peptide were able to target a protein complex of transferrin and transferrin receptor (TfR) through a non-canonical allosteric binding mechanism and that this functional protein complex mediated transport of the corresponding viral particles into the normal mouse brain. We also showed that, in an orthotopic mouse model of human glioblastoma, a combination of TfR overexpression plus extended vascular permeability and ligand retention resulted in remarkable brain tumor targeting of chimeric adeno-associated virus/phage particles displaying the iron-mimic peptide and carrying a gene of interest. As a proof of concept, we delivered the HSV thymidine kinase gene for molecular-genetic imaging and targeted therapy of intracranial xenografted tumors. Finally, we established that these experimental findings might be clinically relevant by determining through human tissue microarrays that many primary astrocytic tumors strongly express TfR. Together, our combinatorial selection system and results may provide a translational avenue for the targeted detection and treatment of brain tumors. PMID:21183793

The microbiota-gut-brain axis: neurobehavioral correlates, health and sociality

PubMed Central

Montiel-Castro, Augusto J.; González-Cervantes, Rina M.; Bravo-Ruiseco, Gabriela; Pacheco-López, Gustavo

2013-01-01

Recent data suggest that the human body is not such a neatly self-sufficient island after all. It is more like a super-complex ecosystem containing trillions of bacteria and other microorganisms that inhabit all our surfaces; skin, mouth, sexual organs, and specially intestines. It has recently become evident that such microbiota, specifically within the gut, can greatly influence many physiological parameters, including cognitive functions, such as learning, memory and decision making processes. Human microbiota is a diverse and dynamic ecosystem, which has evolved in a mutualistic relationship with its host. Ontogenetically, it is vertically inoculated from the mother during birth, established during the first year of life and during lifespan, horizontally transferred among relatives, mates or close community members. This micro-ecosystem serves the host by protecting it against pathogens, metabolizing complex lipids and polysaccharides that otherwise would be inaccessible nutrients, neutralizing drugs and carcinogens, modulating intestinal motility, and making visceral perception possible. It is now evident that the bidirectional signaling between the gastrointestinal tract and the brain, mainly through the vagus nerve, the so called “microbiota–gut–vagus–brain axis,” is vital for maintaining homeostasis and it may be also involved in the etiology of several metabolic and mental dysfunctions/disorders. Here we review evidence on the ability of the gut microbiota to communicate with the brain and thus modulate behavior, and also elaborate on the ethological and cultural strategies of human and non-human primates to select, transfer and eliminate microorganisms for selecting the commensal profile. PMID:24109440

The microbiota-gut-brain axis: neurobehavioral correlates, health and sociality.

PubMed

Montiel-Castro, Augusto J; González-Cervantes, Rina M; Bravo-Ruiseco, Gabriela; Pacheco-López, Gustavo

2013-10-07

Recent data suggest that the human body is not such a neatly self-sufficient island after all. It is more like a super-complex ecosystem containing trillions of bacteria and other microorganisms that inhabit all our surfaces; skin, mouth, sexual organs, and specially intestines. It has recently become evident that such microbiota, specifically within the gut, can greatly influence many physiological parameters, including cognitive functions, such as learning, memory and decision making processes. Human microbiota is a diverse and dynamic ecosystem, which has evolved in a mutualistic relationship with its host. Ontogenetically, it is vertically inoculated from the mother during birth, established during the first year of life and during lifespan, horizontally transferred among relatives, mates or close community members. This micro-ecosystem serves the host by protecting it against pathogens, metabolizing complex lipids and polysaccharides that otherwise would be inaccessible nutrients, neutralizing drugs and carcinogens, modulating intestinal motility, and making visceral perception possible. It is now evident that the bidirectional signaling between the gastrointestinal tract and the brain, mainly through the vagus nerve, the so called "microbiota-gut-vagus-brain axis," is vital for maintaining homeostasis and it may be also involved in the etiology of several metabolic and mental dysfunctions/disorders. Here we review evidence on the ability of the gut microbiota to communicate with the brain and thus modulate behavior, and also elaborate on the ethological and cultural strategies of human and non-human primates to select, transfer and eliminate microorganisms for selecting the commensal profile.

Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence

PubMed Central

Cichy, Radoslaw Martin; Khosla, Aditya; Pantazis, Dimitrios; Torralba, Antonio; Oliva, Aude

2016-01-01

The complex multi-stage architecture of cortical visual pathways provides the neural basis for efficient visual object recognition in humans. However, the stage-wise computations therein remain poorly understood. Here, we compared temporal (magnetoencephalography) and spatial (functional MRI) visual brain representations with representations in an artificial deep neural network (DNN) tuned to the statistics of real-world visual recognition. We showed that the DNN captured the stages of human visual processing in both time and space from early visual areas towards the dorsal and ventral streams. Further investigation of crucial DNN parameters revealed that while model architecture was important, training on real-world categorization was necessary to enforce spatio-temporal hierarchical relationships with the brain. Together our results provide an algorithmically informed view on the spatio-temporal dynamics of visual object recognition in the human visual brain. PMID:27282108

Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence.

PubMed

Cichy, Radoslaw Martin; Khosla, Aditya; Pantazis, Dimitrios; Torralba, Antonio; Oliva, Aude

2016-06-10

The complex multi-stage architecture of cortical visual pathways provides the neural basis for efficient visual object recognition in humans. However, the stage-wise computations therein remain poorly understood. Here, we compared temporal (magnetoencephalography) and spatial (functional MRI) visual brain representations with representations in an artificial deep neural network (DNN) tuned to the statistics of real-world visual recognition. We showed that the DNN captured the stages of human visual processing in both time and space from early visual areas towards the dorsal and ventral streams. Further investigation of crucial DNN parameters revealed that while model architecture was important, training on real-world categorization was necessary to enforce spatio-temporal hierarchical relationships with the brain. Together our results provide an algorithmically informed view on the spatio-temporal dynamics of visual object recognition in the human visual brain.

On the characterization of the heterogeneous mechanical response of human brain tissue.

PubMed

Forte, Antonio E; Gentleman, Stephen M; Dini, Daniele

2017-06-01

The mechanical characterization of brain tissue is a complex task that scientists have tried to accomplish for over 50 years. The results in the literature often differ by orders of magnitude because of the lack of a standard testing protocol. Different testing conditions (including humidity, temperature, strain rate), the methodology adopted, and the variety of the species analysed are all potential sources of discrepancies in the measurements. In this work, we present a rigorous experimental investigation on the mechanical properties of human brain, covering both grey and white matter. The influence of testing conditions is also shown and thoroughly discussed. The material characterization performed is finally adopted to provide inputs to a mathematical formulation suitable for numerical simulations of brain deformation during surgical procedures.

Concept of software interface for BCI systems

NASA Astrophysics Data System (ADS)

Svejda, Jaromir; Zak, Roman; Jasek, Roman

2016-06-01

Brain Computer Interface (BCI) technology is intended to control external system by brain activity. One of main part of such system is software interface, which carries about clear communication between brain and either computer or additional devices connected to computer. This paper is organized as follows. Firstly, current knowledge about human brain is briefly summarized to points out its complexity. Secondly, there is described a concept of BCI system, which is then used to build an architecture of proposed software interface. Finally, there are mentioned disadvantages of sensing technology discovered during sensing part of our research.

[Testosterone and psyche].

PubMed

Leiber, C; Wetterauer, U; Berner, M

2010-01-01

Testosterone, like other steroid hormones, crosses the blood-brain barrier, and the androgen receptor is present in most parts of the human brain. Therefore, testosterone has many effects on the psyche, mainly in men but also in women. Most often discussed is its influence on sexuality, especially on desire and sexual fantasies, spontaneous nighttime erections, sexual activity, and the number of orgasms and ejaculations. Mood and energy are also testosterone related. Testosterone deficiency in male patients can lead to depressive disorders. In the past, elevated testosterone levels were seen as responsible for strongly aggressive behaviour. Some cognitive functions (spatial and mathematical sense, verbal skills) are, at least to a certain point, testosterone related. Due to the extremely complex functioning of the human brain, a scientifically exact statement regarding the true relationship between testosterone and human behaviour is not possible. On the one hand, the cause is definitively multifactorial, but on the other, testosterone is metabolised in the brain, and the metabolites act by themselves. Furthermore, a bidirectional relationship exists between hormones and human behaviour: Human behaviour is influenced by hormones, and human behaviour also has a direct influence on the levels of many hormones in the human body. Finally, much data in this field are derived from animal studies; studies on humans cannot be conducted because of ethical reasons or scientific and technical problems.

Hurst Exponent Analysis of Resting-State fMRI Signal Complexity across the Adult Lifespan

PubMed Central

Dong, Jianxin; Jing, Bin; Ma, Xiangyu; Liu, Han; Mo, Xiao; Li, Haiyun

2018-01-01

Exploring functional information among various brain regions across time enables understanding of healthy aging process and holds great promise for age-related brain disease diagnosis. This paper proposed a method to explore fractal complexity of the resting-state functional magnetic resonance imaging (rs-fMRI) signal in the human brain across the adult lifespan using Hurst exponent (HE). We took advantage of the examined rs-fMRI data from 116 adults 19 to 85 years of age (44.3 ± 19.4 years, 49 females) from NKI/Rockland sample. Region-wise and voxel-wise analyses were performed to investigate the effects of age, gender, and their interaction on complexity. In region-wise analysis, we found that the healthy aging is accompanied by a loss of complexity in frontal and parietal lobe and increased complexity in insula, limbic, and temporal lobe. Meanwhile, differences in HE between genders were found to be significant in parietal lobe (p = 0.04, corrected). However, there was no interaction between gender and age. In voxel-wise analysis, the significant complexity decrease with aging was found in frontal and parietal lobe, and complexity increase was found in insula, limbic lobe, occipital lobe, and temporal lobe with aging. Meanwhile, differences in HE between genders were found to be significant in frontal, parietal, and limbic lobe. Furthermore, we found age and sex interaction in right parahippocampal gyrus (p = 0.04, corrected). Our findings reveal HE variations of the rs-fMRI signal across the human adult lifespan and show that HE may serve as a new parameter to assess healthy aging process. PMID:29456489

Data-driven analysis of functional brain interactions during free listening to music and speech.

PubMed

Fang, Jun; Hu, Xintao; Han, Junwei; Jiang, Xi; Zhu, Dajiang; Guo, Lei; Liu, Tianming

2015-06-01

Natural stimulus functional magnetic resonance imaging (N-fMRI) such as fMRI acquired when participants were watching video streams or listening to audio streams has been increasingly used to investigate functional mechanisms of the human brain in recent years. One of the fundamental challenges in functional brain mapping based on N-fMRI is to model the brain's functional responses to continuous, naturalistic and dynamic natural stimuli. To address this challenge, in this paper we present a data-driven approach to exploring functional interactions in the human brain during free listening to music and speech streams. Specifically, we model the brain responses using N-fMRI by measuring the functional interactions on large-scale brain networks with intrinsically established structural correspondence, and perform music and speech classification tasks to guide the systematic identification of consistent and discriminative functional interactions when multiple subjects were listening music and speech in multiple categories. The underlying premise is that the functional interactions derived from N-fMRI data of multiple subjects should exhibit both consistency and discriminability. Our experimental results show that a variety of brain systems including attention, memory, auditory/language, emotion, and action networks are among the most relevant brain systems involved in classic music, pop music and speech differentiation. Our study provides an alternative approach to investigating the human brain's mechanism in comprehension of complex natural music and speech.

A physical multifield model predicts the development of volume and structure in the human brain

NASA Astrophysics Data System (ADS)

Rooij, Rijk de; Kuhl, Ellen

2018-03-01

The prenatal development of the human brain is characterized by a rapid increase in brain volume and a development of a highly folded cortex. At the cellular level, these events are enabled by symmetric and asymmetric cell division in the ventricular regions of the brain followed by an outwards cell migration towards the peripheral regions. The role of mechanics during brain development has been suggested and acknowledged in past decades, but remains insufficiently understood. Here we propose a mechanistic model that couples cell division, cell migration, and brain volume growth to accurately model the developing brain between weeks 10 and 29 of gestation. Our model accurately predicts a 160-fold volume increase from 1.5 cm3 at week 10 to 235 cm3 at week 29 of gestation. In agreement with human brain development, the cortex begins to form around week 22 and accounts for about 30% of the total brain volume at week 29. Our results show that cell division and coupling between cell density and volume growth are essential to accurately model brain volume development, whereas cell migration and diffusion contribute mainly to the development of the cortex. We demonstrate that complex folding patterns, including sinusoidal folds and creases, emerge naturally as the cortex develops, even for low stiffness contrasts between the cortex and subcortex.

Rhenium(i) complexes of N-heterocyclic carbene ligands that bind to amyloid plaques of Alzheimer's disease.

PubMed

Chan, Chung Ying; Noor, Asif; McLean, Catriona A; Donnelly, Paul S; Barnard, Peter J

2017-02-16

A series of [Re(i)L(CO) 3 ] + complexes (where L is a bifunctional bis(NHC)-amine ligand) that are analogues of potential Tc-99m diagnostic imaging agents for Alzheimer's disease have been synthesised. One of the complexes bound to amyloid plaques in human frontal cortex brain tissue from subjects with Alzheimer's disease.

Task-Based Core-Periphery Organization of Human Brain Dynamics

PubMed Central

Bassett, Danielle S.; Wymbs, Nicholas F.; Rombach, M. Puck; Porter, Mason A.; Mucha, Peter J.; Grafton, Scott T.

2013-01-01

As a person learns a new skill, distinct synapses, brain regions, and circuits are engaged and change over time. In this paper, we develop methods to examine patterns of correlated activity across a large set of brain regions. Our goal is to identify properties that enable robust learning of a motor skill. We measure brain activity during motor sequencing and characterize network properties based on coherent activity between brain regions. Using recently developed algorithms to detect time-evolving communities, we find that the complex reconfiguration patterns of the brain's putative functional modules that control learning can be described parsimoniously by the combined presence of a relatively stiff temporal core that is composed primarily of sensorimotor and visual regions whose connectivity changes little in time and a flexible temporal periphery that is composed primarily of multimodal association regions whose connectivity changes frequently. The separation between temporal core and periphery changes over the course of training and, importantly, is a good predictor of individual differences in learning success. The core of dynamically stiff regions exhibits dense connectivity, which is consistent with notions of core-periphery organization established previously in social networks. Our results demonstrate that core-periphery organization provides an insightful way to understand how putative functional modules are linked. This, in turn, enables the prediction of fundamental human capacities, including the production of complex goal-directed behavior. PMID:24086116

Cognitive Navigation: Toward a Biological Basis for Instructional Design.

ERIC Educational Resources Information Center

Tripp, Steven

2001-01-01

Discusses cognitive navigation, cognitive maps and online learning, and the role of the hippocampus in navigation. Topics include brain research in animal and human studies; types of memory; human navigation, including land navigation and information navigation; instructional strategies; tree maps of curriculum structure; cognitive complexity; and…

[Molecular organization of glutamate-sensitive chemoexcitatory membranes of nerve cells. Comparative analysis of glutamate-binding membrane proteins from the cerebral cortex of rats and humans].

PubMed

Dambinova, S A; Gorodinskiĭ, A I; Lekomtseva, T M; Koreshonkov, O N

1987-10-01

The kinetics of 3H-L-glutamate binding to human brain synaptic membranes revealed the existence of one type of binding sites with Kd and Vmax comparable with those for freshly isolated rat brain membranes. The fraction of glutamate-binding proteins (GBP) was shown to contain three components with Mr of 14, 60 and 280 kD whose stoichiometry is specific for human and rat brain. All fractions were found to bind the radiolabeled neurotransmitter and to dissociate into subunits with Mr of 14 kD after treatment with-potent detergents (with the exception of the 56-60 kD component). Study of association-dissociation of GBP protein subunits by high performance liquid chromatography confirmed the hypothesis on the oligomeric structure of glutamate receptors which are made up of low molecular weight glycoprotein-lipid subunits and which form ionic channels by way of repeated association. Despite the similarity of antigen determinants in the active center of glutamate receptors from human and rat brain, it was assumed that the stoichiometry of structural organization of receptor subunits isolated from different sources is different. The functional role of structural complexity of human brain glutamate receptors is discussed.

Age- and gender-related regional variations of human brain cortical thickness, complexity, and gradient in the third decade.

PubMed

Creze, Maud; Versheure, Leslie; Besson, Pierre; Sauvage, Chloe; Leclerc, Xavier; Jissendi-Tchofo, Patrice

2014-06-01

Brain functional and cytoarchitectural maturation continue until adulthood, but little is known about the evolution of the regional pattern of cortical thickness (CT), complexity (CC), and intensity or gradient (CG) in young adults. We attempted to detect global and regional age- and gender-related variations of brain CT, CC, and CG, in 28 healthy young adults (19-33 years) using a three-dimensional T1 -weighted magnetic resonance imaging sequence and surface-based methods. Whole brain interindividual variations of CT and CG were similar to that in the literature. As a new finding, age- and gender-related variations significantly affected brain complexity (P < 0.01) on posterior cingulate and middle temporal cortices (age), and the fronto-orbital cortex (gender), all in the right hemisphere. Regions of interest analyses showed age and gender significant interaction (P < 0.05) on the temporopolar, inferior, and middle temporal-entorrhinal cortices bilaterally, as well as left inferior parietal. In addition, we found significant inverse correlations between CT and CC and between CT and CG over the whole brain and markedly in precentral and occipital areas. Our findings differ in details from previous reports and may correlate with late brain maturation and learning plasticity in young adults' brain in the third decade. Copyright © 2013 Wiley Periodicals, Inc.

Epigenetic and gene expression changes in the adolescent brain: What have we learned from animal models?

PubMed

Mychasiuk, Richelle; Metz, Gerlinde A S

2016-11-01

Adolescence is defined as the gradual period of transition between childhood and adulthood that is characterized by significant brain maturation, growth spurts, sexual maturation, and heightened social interaction. Although originally believed to be a uniquely human aspect of development, rodent and non-human primates demonstrate maturational patterns that distinctly support an adolescent stage. As epigenetic processes are essential for development and differentiation, but also transpire in mature cells in response to environmental influences, they are an important aspect of adolescent brain maturation. The purpose of this review article was to examine epigenetic programming in animal models of brain maturation during adolescence. The discussion focuses on animal models to examine three main concepts; epigenetic processes involved in normal adolescent brain maturation, the influence of fetal programming on adolescent brain development and the epigenome, and finally, postnatal experiences such as exercise and drugs that modify epigenetic processes important for adolescent brain maturation. This corollary emphasizes the utility of animal models to further our understanding of complex processes such as epigenetic regulation and brain development. Copyright © 2016 Elsevier Ltd. All rights reserved.

Cortical representations of communication sounds.

PubMed

Heiser, Marc A; Cheung, Steven W

2008-10-01

This review summarizes recent research into cortical processing of vocalizations in animals and humans. There has been a resurgent interest in this topic accompanied by an increased number of studies using animal models with complex vocalizations and new methods in human brain imaging. Recent results from such studies are discussed. Experiments have begun to reveal the bilateral cortical fields involved in communication sound processing and the transformations of neural representations that occur among those fields. Advances have also been made in understanding the neuronal basis of interaction between developmental exposures and behavioral experiences with vocalization perception. Exposure to sounds during the developmental period produces large effects on brain responses, as do a variety of specific trained tasks in adults. Studies have also uncovered a neural link between the motor production of vocalizations and the representation of vocalizations in cortex. Parallel experiments in humans and animals are answering important questions about vocalization processing in the central nervous system. This dual approach promises to reveal microscopic, mesoscopic, and macroscopic principles of large-scale dynamic interactions between brain regions that underlie the complex phenomenon of vocalization perception. Such advances will yield a greater understanding of the causes, consequences, and treatment of disorders related to speech processing.

Resting state brain networks in the prairie vole.

PubMed

Ortiz, Juan J; Portillo, Wendy; Paredes, Raul G; Young, Larry J; Alcauter, Sarael

2018-01-19

Resting state functional magnetic resonance imaging (rsfMRI) has shown the hierarchical organization of the human brain into large-scale complex networks, referred as resting state networks. This technique has turned into a promising translational research tool after the finding of similar resting state networks in non-human primates, rodents and other animal models of great value for neuroscience. Here, we demonstrate and characterize the presence of resting states networks in Microtus ochrogaster, the prairie vole, an extraordinary animal model to study complex human-like social behavior, with potential implications for the research of normal social development, addiction and neuropsychiatric disorders. Independent component analysis of rsfMRI data from isoflurane-anestethized prairie voles resulted in cortical and subcortical networks, including primary motor and sensory networks, but also included putative salience and default mode networks. We further discuss how future research could help to close the gap between the properties of the large scale functional organization and the underlying neurobiology of several aspects of social cognition. These results contribute to the evidence of preserved resting state brain networks across species and provide the foundations to explore the use of rsfMRI in the prairie vole for basic and translational research.

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.

Key cognitive preconditions for the evolution of language.

PubMed

Donald, Merlin

2017-02-01

Languages are socially constructed systems of expression, generated interactively in social networks, which can be assimilated by the individual brain as it develops. Languages co-evolved with culture, reflecting the changing complexity of human culture as it acquired the properties of a distributed cognitive system. Two key preconditions set the stage for the evolution of such cultures: a very general ability to rehearse and refine skills (evident early in hominin evolution in toolmaking), and the emergence of material culture as an external (to the brain) memory record that could retain and accumulate knowledge across generations. The ability to practice and rehearse skill provided immediate survival-related benefits in that it expanded the physical powers of early hominins, but the same adaptation also provided the imaginative substrate for a system of "mimetic" expression, such as found in ritual and pantomime, and in proto-words, which performed an expressive function somewhat like the home signs of deaf non-signers. The hominid brain continued to adapt to the increasing importance and complexity of culture as human interactions with material culture became more complex; above all, this entailed a gradual expansion in the integrative systems of the brain, especially those involved in the metacognitive supervision of self-performances. This supported a style of embodied mimetic imagination that improved the coordination of shared activities such as fire tending, but also in rituals and reciprocal mimetic games. The time-depth of this mimetic adaptation, and its role in both the construction and acquisition of languages, explains the importance of mimetic expression in the media, religion, and politics. Spoken language evolved out of voco-mimesis, and emerged long after the more basic abilities needed to refine skill and share intentions, probably coinciding with the common ancestor of sapient humans. Self-monitoring and self-supervised practice were necessary preconditions for lexical invention, and as these abilities evolved further, communicative skills extended to more abstract and complex aspects of the communication environments-that is, the "cognitive ecologies"-being generated by human groups. The hominin brain adapted continuously to the need to assimilate language and its many cognitive byproducts by expanding many of its higher integrative systems, a process that seems to have accelerated and peaked in the past half million years.

A gallium(III) Schiff base-curcumin complex that binds to amyloid-β plaques.

PubMed

Lange, Jaclyn L; Hayne, David J; Roselt, Peter; McLean, Catriona A; White, Jonathan M; Donnelly, Paul S

2016-09-01

Gallium-68 is a positron-emitting isotope that can be used in positron-emission tomography imaging agents. Alzheimer's disease is associated with the formation of plaques in the brain primarily comprised of aggregates of a 42 amino acid protein called amyloid-β. With the goal of synthesising charge neutral, low molecular weight, lipophilic gallium complexes with the potential to cross the blood-brain barrier and bind to Aβ plaques we have used an ancillary tetradentate N 2 O 2 Schiff base ligand and the β-diketone curcumin as a bidentate ligand to give a six-coordinate Ga 3+ complex. The tetradentate Schiff base ligand adopts the cis-β configuration with deprotonated curcumin acting as a bidentate ligand. The complex binds to amyloid-β plaques in human brain tissue and it is possible that extension of this chemistry to positron-emitting gallium-68 could provide useful imaging agents for Alzheimer's disease. Copyright © 2016 Elsevier Inc. All rights reserved.

Principal component analysis of the cytokine and chemokine response to human traumatic brain injury.

PubMed

Helmy, Adel; Antoniades, Chrystalina A; Guilfoyle, Mathew R; Carpenter, Keri L H; Hutchinson, Peter J

2012-01-01

There is a growing realisation that neuro-inflammation plays a fundamental role in the pathology of Traumatic Brain Injury (TBI). This has led to the search for biomarkers that reflect these underlying inflammatory processes using techniques such as cerebral microdialysis. The interpretation of such biomarker data has been limited by the statistical methods used. When analysing data of this sort the multiple putative interactions between mediators need to be considered as well as the timing of production and high degree of statistical co-variance in levels of these mediators. Here we present a cytokine and chemokine dataset from human brain following human traumatic brain injury and use principal component analysis and partial least squares discriminant analysis to demonstrate the pattern of production following TBI, distinct phases of the humoral inflammatory response and the differing patterns of response in brain and in peripheral blood. This technique has the added advantage of making no assumptions about the Relative Recovery (RR) of microdialysis derived parameters. Taken together these techniques can be used in complex microdialysis datasets to summarise the data succinctly and generate hypotheses for future study.

Prospective Design of Anti‐Transferrin Receptor Bispecific Antibodies for Optimal Delivery into the Human Brain

PubMed Central

Kanodia, JS; Gadkar, K; Bumbaca, D; Zhang, Y; Tong, RK; Luk, W; Hoyte, K; Lu, Y; Wildsmith, KR; Couch, JA; Watts, RJ; Dennis, MS; Ernst, JA; Scearce‐Levie, K; Atwal, JK; Joseph, S

2016-01-01

Anti‐transferrin receptor (TfR)‐based bispecific antibodies have shown promise for boosting antibody uptake in the brain. Nevertheless, there are limited data on the molecular properties, including affinity required for successful development of TfR‐based therapeutics. A complex nonmonotonic relationship exists between affinity of the anti‐TfR arm and brain uptake at therapeutically relevant doses. However, the quantitative nature of this relationship and its translatability to humans is heretofore unexplored. Therefore, we developed a mechanistic pharmacokinetic‐pharmacodynamic (PK‐PD) model for bispecific anti‐TfR/BACE1 antibodies that accounts for antibody‐TfR interactions at the blood‐brain barrier (BBB) as well as the pharmacodynamic (PD) effect of anti‐BACE1 arm. The calibrated model correctly predicted the optimal anti‐TfR affinity required to maximize brain exposure of therapeutic antibodies in the cynomolgus monkey and was scaled to predict the optimal affinity of anti‐TfR bispecifics in humans. Thus, this model provides a framework for testing critical translational predictions for anti‐TfR bispecific antibodies, including choice of candidate molecule for clinical development. PMID:27299941

Gut Microbes and the Brain: Paradigm Shift in Neuroscience

PubMed Central

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

2014-01-01

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

Rewiring the Corporate Brain: Using the New Science To Rethink How We Structure and Lead Organizations.

ERIC Educational Resources Information Center

Zohar, Danah

This book relates the radically new sciences of the 20th century--quantum mechanics, chaos theory, and complexity theory--to organizational problems and challenges facing corporate leaders. The book draws on the science of the human brain, with its three different kinds of neural structures--mental, emotional, and spiritual--to illustrate how to…

The role of sleep in human declarative memory consolidation.

PubMed

Alger, Sara E; Chambers, Alexis M; Cunningham, Tony; Payne, Jessica D

2015-01-01

Through a variety of methods, researchers have begun unraveling the mystery of why humans spend one-third of their lives asleep. Though sleep likely serves multiple functions, it has become clear that the sleeping brain offers an ideal environment for solidifying newly learned information in the brain. Sleep , which comprises a complex collection of brain states, supports the consolidation of many different types of information. It not only promotes learning and memory stabilization, but also memory reorganization that can lead to various forms of insightful behavior. As this chapter will describe, research provides ample support for these crucial cognitive functions of sleep . Focusing on the declarative memory system in humans, we review the literature regarding the benefits of sleep for both neutral and emotionally salient declarative memory. Finally, we discuss the literature regarding the impact of sleep on emotion regulation.

Dolphin social intelligence: complex alliance relationships in bottlenose dolphins and a consideration of selective environments for extreme brain size evolution in mammals.

PubMed

Connor, Richard C

2007-04-29

Bottlenose dolphins in Shark Bay, Australia, live in a large, unbounded society with a fission-fusion grouping pattern. Potential cognitive demands include the need to develop social strategies involving the recognition of a large number of individuals and their relationships with others. Patterns of alliance affiliation among males may be more complex than are currently known for any non-human, with individuals participating in 2-3 levels of shifting alliances. Males mediate alliance relationships with gentle contact behaviours such as petting, but synchrony also plays an important role in affiliative interactions. In general, selection for social intelligence in the context of shifting alliances will depend on the extent to which there are strategic options and risk. Extreme brain size evolution may have occurred more than once in the toothed whales, reaching peaks in the dolphin family and the sperm whale. All three 'peaks' of large brain size evolution in mammals (odontocetes, humans and elephants) shared a common selective environment: extreme mutual dependence based on external threats from predators or conspecific groups. In this context, social competition, and consequently selection for greater cognitive abilities and large brain size, was intense.

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

Emin, David, E-mail: emin@unm.edu; Akhtari, Massoud; Ellingson, B. M.

We analyze the transient-dc and frequency-dependent electrical conductivities between blocking electrodes. We extend this analysis to measurements of ions’ transport in freshly excised bulk samples of human brain tissue whose complex cellular structure produces blockages. The associated ionic charge-carrier density and diffusivity are consistent with local values for sodium cations determined non-invasively in brain tissue by MRI (NMR) and diffusion-MRI (spin-echo NMR). The characteristic separation between blockages, about 450 microns, is very much shorter than that found for sodium-doped gel proxies for brain tissue, >1 cm.

The evolution of the neocortex in mammals: intrinsic and extrinsic contributions to the cortical phenotype.

PubMed

Karlen, Sarah J; Krubitzer, Leah

2006-01-01

The neocortex is that portion of the brain that is involved in volitional motor control, perception, cognition and a number of other complex behaviours exhibited by mammals, including humans. Indeed, the increase in the size of the cortical sheet and cortical field number is one of the hallmarks of human brain evolution. Fossil records and comparative studies of the neocortex indicate that early mammalian neocortices were composed of only a few parts or cortical fields, and that in some lineages such as primates, the neocortex expanded dramatically. More significantly, the number of cortical fields increased and the connectivity between cortical fields became more complex. While we do not know the exact transformation between this type of increase in cortical field number and connectivity; and the emergence of complex behaviours like those mentioned above, we know that species that have large neocorticies with multiple parts generally have more complex behaviours, both overt and covert. Although a number of inroads have been made into understanding how neurons in the neocortex respond to a variety of stimuli, the micro and macro circuitry of particular neocortical fields, and the molecular developmental events that construct current organization, very little is known about how more cortical fields are added in evolution. In particular, we do not know the rules of change, nor the constraints imposed on evolving nervous systems that dictate the particular phenotype that will ultimately emerge. One reason why these issues are unresolved is that the brain is a compromise between existing genetic constraints and the need to adapt. Thus, the functions that the brain generates are absolutely imperfect, although functionally optimized. This makes it very difficult to determine the rules of construction, to generate viable computational models of brain evolution, and to predict the direction of changes that may occur over time. Despite these obstacles, it is still possible to study the evolution of the neocortex. One way is to study the products of the evolutionary process--extant mammal brains-and to make inferences about the process. The second way to study brain evolution is to examine the developmental mechanisms that give rise to complex brains. We have begun to test our theories regarding cortical evolution, generated from comparative studies, by 'tweaking' in a developing nervous system what we believe is naturally being modified in evolution. Our goals are to identify the constraints imposed on the evolving neocortex, to disentangle the genetic and activity dependent mechanisms that give rise to complex brains, and ultimately to produce a cortical phenotype that is consistent with what would naturally occur in evolution.

Evolution of complexity in the zebrafish synapse proteome

PubMed Central

Bayés, Àlex; Collins, Mark O.; Reig-Viader, Rita; Gou, Gemma; Goulding, David; Izquierdo, Abril; Choudhary, Jyoti S.; Emes, Richard D.; Grant, Seth G. N.

2017-01-01

The proteome of human brain synapses is highly complex and is mutated in over 130 diseases. This complexity arose from two whole-genome duplications early in the vertebrate lineage. Zebrafish are used in modelling human diseases; however, its synapse proteome is uncharacterized, and whether the teleost-specific genome duplication (TSGD) influenced complexity is unknown. We report the characterization of the proteomes and ultrastructure of central synapses in zebrafish and analyse the importance of the TSGD. While the TSGD increases overall synapse proteome complexity, the postsynaptic density (PSD) proteome of zebrafish has lower complexity than mammals. A highly conserved set of ∼1,000 proteins is shared across vertebrates. PSD ultrastructural features are also conserved. Lineage-specific proteome differences indicate that vertebrate species evolved distinct synapse types and functions. The data sets are a resource for a wide range of studies and have important implications for the use of zebrafish in modelling human synaptic diseases. PMID:28252024

From embodied mind to embodied robotics: humanities and system theoretical aspects.

PubMed

Mainzer, Klaus

2009-01-01

After an introduction (1) the article analyzes the evolution of the embodied mind (2), the innovation of embodied robotics (3), and finally discusses conclusions of embodied robotics for human responsibility (4). Considering the evolution of the embodied mind (2), we start with an introduction of complex systems and nonlinear dynamics (2.1), apply this approach to neural self-organization (2.2), distinguish degrees of complexity of the brain (2.3), explain the emergence of cognitive states by complex systems dynamics (2.4), and discuss criteria for modeling the brain as complex nonlinear system (2.5). The innovation of embodied robotics (3) is a challenge of future technology. We start with the distinction of symbolic and embodied AI (3.1) and explain embodied robots as dynamical systems (3.2). Self-organization needs self-control of technical systems (3.3). Cellular neural networks (CNN) are an example of self-organizing technical systems offering new avenues for neurobionics (3.4). In general, technical neural networks support different kinds of learning robots (3.5). Finally, embodied robotics aim at the development of cognitive and conscious robots (3.6).

Common genetic variants influence human subcortical brain structures.

PubMed

Hibar, Derrek P; Stein, Jason L; Renteria, Miguel E; Arias-Vasquez, Alejandro; Desrivières, Sylvane; Jahanshad, Neda; Toro, Roberto; Wittfeld, Katharina; Abramovic, Lucija; Andersson, Micael; Aribisala, Benjamin S; Armstrong, Nicola J; Bernard, Manon; Bohlken, Marc M; Boks, Marco P; Bralten, Janita; Brown, Andrew A; Chakravarty, M Mallar; Chen, Qiang; Ching, Christopher R K; Cuellar-Partida, Gabriel; den Braber, Anouk; Giddaluru, Sudheer; Goldman, Aaron L; Grimm, Oliver; Guadalupe, Tulio; Hass, Johanna; Woldehawariat, Girma; Holmes, Avram J; Hoogman, Martine; Janowitz, Deborah; Jia, Tianye; Kim, Sungeun; Klein, Marieke; Kraemer, Bernd; Lee, Phil H; Olde Loohuis, Loes M; Luciano, Michelle; Macare, Christine; Mather, Karen A; Mattheisen, Manuel; Milaneschi, Yuri; Nho, Kwangsik; Papmeyer, Martina; Ramasamy, Adaikalavan; Risacher, Shannon L; Roiz-Santiañez, Roberto; Rose, Emma J; Salami, Alireza; Sämann, Philipp G; Schmaal, Lianne; Schork, Andrew J; Shin, Jean; Strike, Lachlan T; Teumer, Alexander; van Donkelaar, Marjolein M J; van Eijk, Kristel R; Walters, Raymond K; Westlye, Lars T; Whelan, Christopher D; Winkler, Anderson M; Zwiers, Marcel P; Alhusaini, Saud; Athanasiu, Lavinia; Ehrlich, Stefan; Hakobjan, Marina M H; Hartberg, Cecilie B; Haukvik, Unn K; Heister, Angelien J G A M; Hoehn, David; Kasperaviciute, Dalia; Liewald, David C M; Lopez, Lorna M; Makkinje, Remco R R; Matarin, Mar; Naber, Marlies A M; McKay, D Reese; Needham, Margaret; Nugent, Allison C; Pütz, Benno; Royle, Natalie A; Shen, Li; Sprooten, Emma; Trabzuni, Daniah; van der Marel, Saskia S L; van Hulzen, Kimm J E; Walton, Esther; Wolf, Christiane; Almasy, Laura; Ames, David; Arepalli, Sampath; Assareh, Amelia A; Bastin, Mark E; Brodaty, Henry; Bulayeva, Kazima B; Carless, Melanie A; Cichon, Sven; Corvin, Aiden; Curran, Joanne E; Czisch, Michael; de Zubicaray, Greig I; Dillman, Allissa; Duggirala, Ravi; Dyer, Thomas D; Erk, Susanne; Fedko, Iryna O; Ferrucci, Luigi; Foroud, Tatiana M; Fox, Peter T; Fukunaga, Masaki; Gibbs, J Raphael; Göring, Harald H H; Green, Robert C; Guelfi, Sebastian; Hansell, Narelle K; Hartman, Catharina A; Hegenscheid, Katrin; Heinz, Andreas; Hernandez, Dena G; Heslenfeld, Dirk J; Hoekstra, Pieter J; Holsboer, Florian; Homuth, Georg; Hottenga, Jouke-Jan; Ikeda, Masashi; Jack, Clifford R; Jenkinson, Mark; Johnson, Robert; Kanai, Ryota; Keil, Maria; Kent, Jack W; Kochunov, Peter; Kwok, John B; Lawrie, Stephen M; Liu, Xinmin; Longo, Dan L; McMahon, Katie L; Meisenzahl, Eva; Melle, Ingrid; Mohnke, Sebastian; Montgomery, Grant W; Mostert, Jeanette C; Mühleisen, Thomas W; Nalls, Michael A; Nichols, Thomas E; Nilsson, Lars G; Nöthen, Markus M; Ohi, Kazutaka; Olvera, Rene L; Perez-Iglesias, Rocio; Pike, G Bruce; Potkin, Steven G; Reinvang, Ivar; Reppermund, Simone; Rietschel, Marcella; Romanczuk-Seiferth, Nina; Rosen, Glenn D; Rujescu, Dan; Schnell, Knut; Schofield, Peter R; Smith, Colin; Steen, Vidar M; Sussmann, Jessika E; Thalamuthu, Anbupalam; Toga, Arthur W; Traynor, Bryan J; Troncoso, Juan; Turner, Jessica A; Valdés Hernández, Maria C; van 't Ent, Dennis; van der Brug, Marcel; van der Wee, Nic J A; van Tol, Marie-Jose; Veltman, Dick J; Wassink, Thomas H; Westman, Eric; Zielke, Ronald H; Zonderman, Alan B; Ashbrook, David G; Hager, Reinmar; Lu, Lu; McMahon, Francis J; Morris, Derek W; Williams, Robert W; Brunner, Han G; Buckner, Randy L; Buitelaar, Jan K; Cahn, Wiepke; Calhoun, Vince D; Cavalleri, Gianpiero L; Crespo-Facorro, Benedicto; Dale, Anders M; Davies, Gareth E; Delanty, Norman; Depondt, Chantal; Djurovic, Srdjan; Drevets, Wayne C; Espeseth, Thomas; Gollub, Randy L; Ho, Beng-Choon; Hoffmann, Wolfgang; Hosten, Norbert; Kahn, René S; Le Hellard, Stephanie; Meyer-Lindenberg, Andreas; Müller-Myhsok, Bertram; Nauck, Matthias; Nyberg, Lars; Pandolfo, Massimo; Penninx, Brenda W J H; Roffman, Joshua L; Sisodiya, Sanjay M; Smoller, Jordan W; van Bokhoven, Hans; van Haren, Neeltje E M; Völzke, Henry; Walter, Henrik; Weiner, Michael W; Wen, Wei; White, Tonya; Agartz, Ingrid; Andreassen, Ole A; Blangero, John; Boomsma, Dorret I; Brouwer, Rachel M; Cannon, Dara M; Cookson, Mark R; de Geus, Eco J C; Deary, Ian J; Donohoe, Gary; Fernández, Guillén; Fisher, Simon E; Francks, Clyde; Glahn, David C; Grabe, Hans J; Gruber, Oliver; Hardy, John; Hashimoto, Ryota; Hulshoff Pol, Hilleke E; Jönsson, Erik G; Kloszewska, Iwona; Lovestone, Simon; Mattay, Venkata S; Mecocci, Patrizia; McDonald, Colm; McIntosh, Andrew M; Ophoff, Roel A; Paus, Tomas; Pausova, Zdenka; Ryten, Mina; Sachdev, Perminder S; Saykin, Andrew J; Simmons, Andy; Singleton, Andrew; Soininen, Hilkka; Wardlaw, Joanna M; Weale, Michael E; Weinberger, Daniel R; Adams, Hieab H H; Launer, Lenore J; Seiler, Stephan; Schmidt, Reinhold; Chauhan, Ganesh; Satizabal, Claudia L; Becker, James T; Yanek, Lisa; van der Lee, Sven J; Ebling, Maritza; Fischl, Bruce; Longstreth, W T; Greve, Douglas; Schmidt, Helena; Nyquist, Paul; Vinke, Louis N; van Duijn, Cornelia M; Xue, Luting; Mazoyer, Bernard; Bis, Joshua C; Gudnason, Vilmundur; Seshadri, Sudha; Ikram, M Arfan; Martin, Nicholas G; Wright, Margaret J; Schumann, Gunter; Franke, Barbara; Thompson, Paul M; Medland, Sarah E

2015-04-09

The highly complex structure of the human brain is strongly shaped by genetic influences. Subcortical brain regions form circuits with cortical areas to coordinate movement, learning, memory and motivation, and altered circuits can lead to abnormal behaviour and disease. To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts. We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume and intracranial volume. These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08 × 10(-33); 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport. Identification of these genetic variants provides insight into the causes of variability in human brain development, and may help to determine mechanisms of neuropsychiatric dysfunction.

Non-coding-regulatory regions of human brain genes delineated by bacterial artificial chromosome knock-in mice.

PubMed

Schmouth, Jean-François; Castellarin, Mauro; Laprise, Stéphanie; Banks, Kathleen G; Bonaguro, Russell J; McInerny, Simone C; Borretta, Lisa; Amirabbasi, Mahsa; Korecki, Andrea J; Portales-Casamar, Elodie; Wilson, Gary; Dreolini, Lisa; Jones, Steven J M; Wasserman, Wyeth W; Goldowitz, Daniel; Holt, Robert A; Simpson, Elizabeth M

2013-10-14

The next big challenge in human genetics is understanding the 98% of the genome that comprises non-coding DNA. Hidden in this DNA are sequences critical for gene regulation, and new experimental strategies are needed to understand the functional role of gene-regulation sequences in health and disease. In this study, we build upon our HuGX ('high-throughput human genes on the X chromosome') strategy to expand our understanding of human gene regulation in vivo. In all, ten human genes known to express in therapeutically important brain regions were chosen for study. For eight of these genes, human bacterial artificial chromosome clones were identified, retrofitted with a reporter, knocked single-copy into the Hprt locus in mouse embryonic stem cells, and mouse strains derived. Five of these human genes expressed in mouse, and all expressed in the adult brain region for which they were chosen. This defined the boundaries of the genomic DNA sufficient for brain expression, and refined our knowledge regarding the complexity of gene regulation. We also characterized for the first time the expression of human MAOA and NR2F2, two genes for which the mouse homologs have been extensively studied in the central nervous system (CNS), and AMOTL1 and NOV, for which roles in CNS have been unclear. We have demonstrated the use of the HuGX strategy to functionally delineate non-coding-regulatory regions of therapeutically important human brain genes. Our results also show that a careful investigation, using publicly available resources and bioinformatics, can lead to accurate predictions of gene expression.

Distribution of the branched-chain α-ketoacid dehydrogenase complex E1α subunit and glutamate dehydrogenase in the human brain and their role in neuro-metabolism.

PubMed

Hull, Jonathon; Usmari Moraes, Marcela; Brookes, Emma; Love, Seth; Conway, Myra E

2018-01-01

Glutamate is the major excitatory neurotransmitter of the central nervous system, with the branched-chain amino acids (BCAAs) acting as key nitrogen donors for de novo glutamate synthesis. Despite the importance of these major metabolites, their metabolic pathway in the human brain is still not well characterised. The metabolic pathways that influence the metabolism of BCAAs have been well characterised in rat models. However, the expression of key proteins such as the branched-chain α-ketoacid dehydrogenase (BCKD) complex and glutamate dehydrogenase isozymes (GDH) in the human brain is still not well characterised. We have used specific antibodies to these proteins to analyse their distribution within the human brain and report, for the first time, that the E1α subunit of the BCKD is located in both neurons and vascular endothelial cells. We also demonstrate that GDH is localised to astrocytes, although vascular immunolabelling does occur. The labelling of GDH was most intense in astrocytes adjacent to the hippocampus, in keeping with glutamatergic neurotransmission in this region. GDH was also present in astrocyte processes abutting vascular endothelial cells. Previously, we demonstrated that the branched-chain aminotransferase (hBCAT) proteins were most abundant in vascular cells (hBCATm) and neurons (hBCATc). Present findings are further evidence that BCAAs are metabolised within both the vasculature and neurons in the human brain. We suggest that GDH, hBCAT and the BCKD proteins operate in conjunction with astrocytic glutamate transporters and glutamine synthetase to regulate the availability of glutamate. This has important implications given that the dysregulation of glutamate metabolism, leading to glutamate excitotoxicity, is an important contributor to the pathogenesis of several neurodegenerative conditions such as Alzheimer's disease. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

Human area MT+ shows load-dependent activation during working memory maintenance with continuously morphing stimulation.

PubMed

Galashan, Daniela; Fehr, Thorsten; Kreiter, Andreas K; Herrmann, Manfred

2014-07-11

Initially, human area MT+ was considered a visual area solely processing motion information but further research has shown that it is also involved in various different cognitive operations, such as working memory tasks requiring motion-related information to be maintained or cognitive tasks with implied or expected motion.In the present fMRI study in humans, we focused on MT+ modulation during working memory maintenance using a dynamic shape-tracking working memory task with no motion-related working memory content. Working memory load was systematically varied using complex and simple stimulus material and parametrically increasing retention periods. Activation patterns for the difference between retention of complex and simple memorized stimuli were examined in order to preclude that the reported effects are caused by differences in retrieval. Conjunction analysis over all delay durations for the maintenance of complex versus simple stimuli demonstrated a wide-spread activation pattern. Percent signal change (PSC) in area MT+ revealed a pattern with higher values for the maintenance of complex shapes compared to the retention of a simple circle and with higher values for increasing delay durations. The present data extend previous knowledge by demonstrating that visual area MT+ presents a brain activity pattern usually found in brain regions that are actively involved in working memory maintenance.

Quantitative validation of a nonlinear histology-MRI coregistration method using Generalized Q-sampling Imaging in complex human cortical white matter

PubMed Central

Gangolli, Mihika; Holleran, Laurena; Kim, Joong Hee; Stein, Thor D.; Alvarez, Victor; McKee, Ann C.; Brody, David L.

2017-01-01

Advanced diffusion MRI methods have recently been proposed for detection of pathologies such as traumatic axonal injury and chronic traumatic encephalopathy which commonly affect complex cortical brain regions. However, radiological-pathological correlations in human brain tissue that detail the relationship between the multi-component diffusion signal and underlying pathology are lacking. We present a nonlinear voxel based two dimensional coregistration method that is useful for matching diffusion signals to quantitative metrics of high resolution histological images. When validated in ex vivo human cortical tissue at a 250 × 250 × 500 micron spatial resolution, the method proved robust in correlations between generalized q-sampling imaging and histologically based white matter fiber orientations, with r = 0.94 for the primary fiber direction and r = 0.88 for secondary fiber direction in each voxel. Importantly, however, the correlation was substantially worse with reduced spatial resolution or with fiber orientations derived using a diffusion tensor model. Furthermore, we have detailed a quantitative histological metric of white matter fiber integrity termed power coherence capable of distinguishing between architecturally complex but intact white matter from disrupted white matter regions. These methods may allow for more sensitive and specific radiological-pathological correlations of neurodegenerative diseases affecting complex gray and white matter. PMID:28365421

Humans use compression heuristics to improve the recall of social networks.

PubMed

Brashears, Matthew E

2013-01-01

The ability of primates, including humans, to maintain large social networks appears to depend on the ratio of the neocortex to the rest of the brain. However, observed human network size frequently exceeds predictions based on this ratio (e.g., "Dunbar's Number"), implying that human networks are too large to be cognitively managed. Here I show that humans adaptively use compression heuristics to allow larger amounts of social information to be stored in the same brain volume. I find that human adults can remember larger numbers of relationships in greater detail when a network exhibits triadic closure and kin labels than when it does not. These findings help to explain how humans manage large and complex social networks with finite cognitive resources and suggest that many of the unusual properties of human social networks are rooted in the strategies necessary to cope with cognitive limitations.

Neuro-impressions: interpreting the nature of human creativity

PubMed Central

Siler, Todd Lael

2012-01-01

Understanding the creative process is essential for realizing human potential. Over the past four decades, the author has explored this subject through his brain-inspired drawings, paintings, symbolic sculptures, and experimental art installations that present myriad impressions of human creativity. These impressionistic artworks interpret rather than illustrate the complexities of the creative process. They draw insights from empirical studies that correlate how human beings create, learn, remember, innovate, and communicate. In addition to offering fresh aesthetic experiences, this metaphorical art raises fundamental questions concerning the deep connections between the brain and its creations. The author describes his artworks as embodiments of everyday observations about the neuropsychology of creativity, and its all-purpose applications for stimulating and accelerating innovation. PMID:23091455

Fractals in the neurosciences, Part II: clinical applications and future perspectives.

PubMed

Di Ieva, Antonio; Esteban, Francisco J; Grizzi, Fabio; Klonowski, Wlodzimierz; Martín-Landrove, Miguel

2015-02-01

It has been ascertained that the human brain is a complex system studied at multiple scales, from neurons and microcircuits to macronetworks. The brain is characterized by a hierarchical organization that gives rise to its highly topological and functional complexity. Over the last decades, fractal geometry has been shown as a universal tool for the analysis and quantification of the geometric complexity of natural objects, including the brain. The fractal dimension has been identified as a quantitative parameter for the evaluation of the roughness of neural structures, the estimation of time series, and the description of patterns, thus able to discriminate different states of the brain in its entire physiopathological spectrum. Fractal-based computational analyses have been applied to the neurosciences, particularly in the field of clinical neurosciences including neuroimaging and neuroradiology, neurology and neurosurgery, psychiatry and psychology, and neuro-oncology and neuropathology. After a review of the basic concepts of fractal analysis and its main applications to the basic neurosciences in part I of this series, here, we review the main applications of fractals to the clinical neurosciences for a holistic approach towards a fractal geometry model of the brain. © The Author(s) 2013.

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.

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

Study of the neural dynamics for understanding communication in terms of complex hetero systems.

PubMed

Tsuda, Ichiro; Yamaguchi, Yoko; Hashimoto, Takashi; Okuda, Jiro; Kawasaki, Masahiro; Nagasaka, Yasuo

2015-01-01

The purpose of the research project was to establish a new research area named "neural information science for communication" by elucidating its neural mechanism. The research was performed in collaboration with applied mathematicians in complex-systems science and experimental researchers in neuroscience. The project included measurements of brain activity during communication with or without languages and analyses performed with the help of extended theories for dynamical systems and stochastic systems. The communication paradigm was extended to the interactions between human and human, human and animal, human and robot, human and materials, and even animal and animal. Copyright © 2014 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

Comparative psychology and the great apes - Their competence in learning, language, and numbers

NASA Technical Reports Server (NTRS)

Rumbaugh, Duane M.

1990-01-01

An overview of comparative studies conducted for the past three decades is presented. These studies have led to the establishment of the Language Research Center that provides facilities for research into questions of primate behavior and cognition. Several experiments conducted among chimpanzees are discussed and comparative analyses with the lesser apes, monkeys, and humans are offered. Among the primates, brain complexity varies widely and the evidence is strong that encephalization and enhanced brain complexity facilitate the learning of concepts, the transfer of learning to an advantage, and mediational and observational learning.

The storytelling brain. Commentary on "On social attribution: implications of recent cognitive neuroscience research for race, law, and politics".

PubMed

Nigam, Sanjay K

2012-09-01

The well-established techniques of the professional storyteller not only have the potential to model complex "truth" but also to dig deeply into that complexity, thereby perhaps getting closer to that truth. This applies not only to fiction, but also to medicine and even science. Compelling storytelling ability may have conferred an evolutionary survival advantage and, if so, is likely represented in the neural circuitry of the human brain. Functional imaging will likely point to a neuroanatomical basis for compelling storytelling ability; this will presumably reflect underlying cellular and molecular mechanisms.

EEG-based research on brain functional networks in cognition.

PubMed

Wang, Niannian; Zhang, Li; Liu, Guozhong

2015-01-01

Recently, exploring the cognitive functions of the brain by establishing a network model to understand the working mechanism of the brain has become a popular research topic in the field of neuroscience. In this study, electroencephalography (EEG) was used to collect data from subjects given four different mathematical cognitive tasks: recite numbers clockwise and counter-clockwise, and letters clockwise and counter-clockwise to build a complex brain function network (BFN). By studying the connectivity features and parameters of those brain functional networks, it was found that the average clustering coefficient is much larger than its corresponding random network and the average shortest path length is similar to the corresponding random networks, which clearly shows the characteristics of the small-world network. The brain regions stimulated during the experiment are consistent with traditional cognitive science regarding learning, memory, comprehension, and other rational judgment results. The new method of complex networking involves studying the mathematical cognitive process of reciting, providing an effective research foundation for exploring the relationship between brain cognition and human learning skills and memory. This could help detect memory deficits early in young and mentally handicapped children, and help scientists understand the causes of cognitive brain disorders.

Moral Enhancement Using Non-invasive Brain Stimulation

PubMed Central

Darby, R. Ryan; Pascual-Leone, Alvaro

2017-01-01

Biomedical enhancement refers to the use of biomedical interventions to improve capacities beyond normal, rather than to treat deficiencies due to diseases. Enhancement can target physical or cognitive capacities, but also complex human behaviors such as morality. However, the complexity of normal moral behavior makes it unlikely that morality is a single capacity that can be deficient or enhanced. Instead, our central hypothesis will be that moral behavior results from multiple, interacting cognitive-affective networks in the brain. First, we will test this hypothesis by reviewing evidence for modulation of moral behavior using non-invasive brain stimulation. Next, we will discuss how this evidence affects ethical issues related to the use of moral enhancement. We end with the conclusion that while brain stimulation has the potential to alter moral behavior, such alteration is unlikely to improve moral behavior in all situations, and may even lead to less morally desirable behavior in some instances. PMID:28275345

Brain imaging in the context of food perception and eating.

PubMed

Hollmann, Maurice; Pleger, Burkhard; Villringer, Arno; Horstmann, Annette

2013-02-01

Eating behavior depends heavily on brain function. In recent years, brain imaging has proved to be a powerful tool to elucidate brain function and brain structure in the context of eating. In this review, we summarize recent findings in the fast growing body of literature in the field and provide an overview of technical aspects as well as the basic brain mechanisms identified with imaging. Furthermore, we highlight findings linking neural processing of eating-related stimuli with obesity. The consumption of food is based on a complex interplay between homeostatic and hedonic mechanisms. Several hormones influence brain activity to regulate food intake and interact with the brain's reward circuitry, which is partly mediated by dopamine signaling. Additionally, it was shown that food stimuli trigger cognitive control mechanisms that incorporate internal goals into food choice. The brain mechanisms observed in this context are strongly influenced by genetic factors, sex and personality traits. Overall, a complex picture arises from brain-imaging findings, because a multitude of factors influence human food choice. Although several key mechanisms have been identified, there is no comprehensive model that is able to explain the behavioral observations to date. Especially a careful characterization of patients according to genotypes and phenotypes could help to better understand the current and future findings in neuroimaging studies.

Network Theory of Human Decision Making

DTIC Science & Technology

2012-06-14

must share the same complexity as the brain. This explains why music can be interpreted as the mirror of the brain [3]. According to [11] a...origin and that phenomenon of neural entrainment has the same origin, with a close connection with the phenomenon of cooperation-induced...renewal critical events, Central European Journal of Physics, 7, 421-431 (2009). [3] D. Adams, P. Grigolini, “ Music , New Aesthetic and

Memory and Imagination: The Paschal Triduum Teaching How to Live and How to Die

ERIC Educational Resources Information Center

Eschenauer, Donna

2012-01-01

Memory and imagination, complex activities of the brain, act as the cornerstone for ritual prayer. These brain functions ground us in hope and aid in our discovery of what it means to be human at a deep level. This article explores the ritual of the Paschal Triduum, the Roman Catholic Church's highest expression of faith. It interprets the Triduum…

The effects of cholesterol on learning and memory.

PubMed

Schreurs, Bernard G

2010-07-01

Cholesterol is vital to normal brain function including learning and memory but that involvement is as complex as the synthesis, metabolism and excretion of cholesterol itself. Dietary cholesterol influences learning tasks from water maze to fear conditioning even though cholesterol does not cross the blood brain barrier. Excess cholesterol has many consequences including peripheral pathology that can signal brain via cholesterol metabolites, pro-inflammatory mediators and antioxidant processes. Manipulations of cholesterol within the central nervous system through genetic, pharmacological, or metabolic means circumvent the blood brain barrier and affect learning and memory but often in animals already otherwise compromised. The human literature is no less complex. Cholesterol reduction using statins improves memory in some cases but not others. There is also controversy over statin use to alleviate memory problems in Alzheimer's disease. Correlations of cholesterol and cognitive function are mixed and association studies find some genetic polymorphisms are related to cognitive function but others are not. In sum, the field is in flux with a number of seemingly contradictory results and many complexities. Nevertheless, understanding cholesterol effects on learning and memory is too important to ignore.

Uncovering genes for cognitive (dys)function and predisposition for alcoholism spectrum disorders: A review of human brain oscillations as effective endophenotypes

PubMed Central

Rangaswamy, Madhavi; Porjesz, Bernice

2010-01-01

Brain oscillations provide a rich source of potentially useful endophenotypes (intermediate phenotypes) for psychiatric genetics, as they represent important correlates of human information processing and are associated with fundamental processes from perception to cognition. These oscillations are highly heritable, are modulated by genes controlling neurotransmitters in the brain, and provide links to associative and integrative brain functions. These endophenotypes represent traits that are less complex and more proximal to gene function than either diagnostic labels or traditional cognitive measures, providing a powerful strategy in searching for genes in psychiatric disorders. These intermediate phenotypes identify both affected and unaffected members of an affected family, including offspring at risk, providing a more direct connection with underlying biological vulnerability. Our group has utilized heritable neurophysiological features (i.e., brain oscillations) as endophenotypes, making it possible to identify susceptibility genes that may be difficult to detect with diagnosis alone. We have discussed our findings of significant linkage and association between brain oscillations and genes in GABAergic, cholinergic and glutamatergic systems (GABRA2, CHRM2, and GRM8). We have also shown that some oscillatory indices from both resting and active cognitive states have revealed a common subset of genetic foci that are shared with the diagnosis of alcoholism and related disorders. Implications of our findings have been discussed in the context of physiological and pharmacological studies on receptor function. These findings underscore the utility of quantitative neurophysiological endophenotypes in the study of the genetics of brain function and the genetic diathesis underlying complex psychiatric disorders. PMID:18634760

Uncovering genes for cognitive (dys)function and predisposition for alcoholism spectrum disorders: a review of human brain oscillations as effective endophenotypes.

PubMed

Rangaswamy, Madhavi; Porjesz, Bernice

2008-10-15

Brain oscillations provide a rich source of potentially useful endophenotypes (intermediate phenotypes) for psychiatric genetics, as they represent important correlates of human information processing and are associated with fundamental processes from perception to cognition. These oscillations are highly heritable, are modulated by genes controlling neurotransmitters in the brain, and provide links to associative and integrative brain functions. These endophenotypes represent traits that are less complex and more proximal to gene function than either diagnostic labels or traditional cognitive measures, providing a powerful strategy in searching for genes in psychiatric disorders. These intermediate phenotypes identify both affected and unaffected members of an affected family, including offspring at risk, providing a more direct connection with underlying biological vulnerability. Our group has utilized heritable neurophysiological features (i.e., brain oscillations) as endophenotypes, making it possible to identify susceptibility genes that may be difficult to detect with diagnosis alone. We have discussed our findings of significant linkage and association between brain oscillations and genes in GABAergic, cholinergic and glutamatergic systems (GABRA2, CHRM2, and GRM8). We have also shown that some oscillatory indices from both resting and active cognitive states have revealed a common subset of genetic foci that are shared with the diagnosis of alcoholism and related disorders. Implications of our findings have been discussed in the context of physiological and pharmacological studies on receptor function. These findings underscore the utility of quantitative neurophysiological endophenotypes in the study of the genetics of brain function and the genetic diathesis underlying complex psychiatric disorders.

Age-associated changes in rich-club organisation in autistic and neurotypical human brains

PubMed Central

Watanabe, Takamitsu; Rees, Geraint

2015-01-01

Macroscopic structural networks in the human brain have a rich-club architecture comprising both highly inter-connected central regions and sparsely connected peripheral regions. Recent studies show that disruption of this functionally efficient organisation is associated with several psychiatric disorders. However, despite increasing attention to this network property, whether age-associated changes in rich-club organisation occur during human adolescence remains unclear. Here, analysing a publicly shared diffusion tensor imaging dataset, we found that, during adolescence, brains of typically developing (TD) individuals showed increases in rich-club organisation and inferred network functionality, whereas individuals with autism spectrum disorders (ASD) did not. These differences between TD and ASD groups were statistically significant for both structural and functional properties. Moreover, this typical age-related changes in rich-club organisation were characterised by progressive involvement of the right anterior insula. In contrast, in ASD individuals, did not show typical increases in grey matter volume, and this relative anatomical immaturity was correlated with the severity of ASD social symptoms. These results provide evidence that rich-club architecture is one of the bases of functionally efficient brain networks underpinning complex cognitive functions in adult human brains. Furthermore, our findings suggest that immature rich-club organisation might be associated with some neurodevelopmental disorders. PMID:26537477

Artistic creativity, style and brain disorders.

PubMed

Bogousslavsky, Julien

2005-01-01

The production of novel, motivated or useful material defines creativity, which appears to be one of the higher, specific, human brain functions. While creativity can express itself in virtually any domain, art might particularly well illustrate how creativity may be modulated by the normal or pathological brain. Evidence emphasizes global brain functioning in artistic creativity and output, but critical steps which link perception processing to execution of a work, such as extraction-abstraction, as well as major developments of non-esthetic values attached to art also underline complex activation and inhibition processes mainly localized in the frontal lobe. Neurological diseases in artists provide a unique opportunity to study brain-creativity relationships, in particular through the stylistic changes which may develop after brain lesion. (c) 2005 S. Karger AG, Basel

Oxytocin and Social Motivation

PubMed Central

Gordon, Ilanit; Martin, Carina; Feldman, Ruth; Leckman, James F.

2011-01-01

Humans are fundamentally social creatures who are ‘motivated’ to be with others. In this review we examine the role of oxytocin (OT) as it relates to social motivation. OT is synthesized in the brain and throughout the body, including in the heart, thymus, gastrointestinal tract, as well as reproductive organs. The distribution of the OT receptor (OTR) system in both the brain and periphery is even more far-reaching and its expression is subject to changes over the course of development. OTR expression is also sensitive to changes in the external environment and the internal somatic world. The OT system functions as an important element within a complex, developmentally sensitive biobehavioral system. Other elements include sensory inputs, the salience, reward, and threat detection pathways, the hypothalamic-pituitary-gonadal axis, and the hypothalamic-pituitary-adrenal stress response axis. Despite an ever expanding scientific literature, key unresolved questions remain concerning the interplay of the central and peripheral components of this complex biobehavioral system that dynamically engages the brain and the body as humans interact with social partners over the course of development. PMID:21984889

Brain entropy and human intelligence: A resting-state fMRI study

PubMed Central

Calderone, Daniel; Morales, Leah J.

2018-01-01

Human intelligence comprises comprehension of and reasoning about an infinitely variable external environment. A brain capable of large variability in neural configurations, or states, will more easily understand and predict variable external events. Entropy measures the variety of configurations possible within a system, and recently the concept of brain entropy has been defined as the number of neural states a given brain can access. This study investigates the relationship between human intelligence and brain entropy, to determine whether neural variability as reflected in neuroimaging signals carries information about intellectual ability. We hypothesize that intelligence will be positively associated with entropy in a sample of 892 healthy adults, using resting-state fMRI. Intelligence is measured with the Shipley Vocabulary and WASI Matrix Reasoning tests. Brain entropy was positively associated with intelligence. This relation was most strongly observed in the prefrontal cortex, inferior temporal lobes, and cerebellum. This relationship between high brain entropy and high intelligence indicates an essential role for entropy in brain functioning. It demonstrates that access to variable neural states predicts complex behavioral performance, and specifically shows that entropy derived from neuroimaging signals at rest carries information about intellectual capacity. Future work in this area may elucidate the links between brain entropy in both resting and active states and various forms of intelligence. This insight has the potential to provide predictive information about adaptive behavior and to delineate the subdivisions and nature of intelligence based on entropic patterns. PMID:29432427

Brain entropy and human intelligence: A resting-state fMRI study.

PubMed

Saxe, Glenn N; Calderone, Daniel; Morales, Leah J

2018-01-01

Human intelligence comprises comprehension of and reasoning about an infinitely variable external environment. A brain capable of large variability in neural configurations, or states, will more easily understand and predict variable external events. Entropy measures the variety of configurations possible within a system, and recently the concept of brain entropy has been defined as the number of neural states a given brain can access. This study investigates the relationship between human intelligence and brain entropy, to determine whether neural variability as reflected in neuroimaging signals carries information about intellectual ability. We hypothesize that intelligence will be positively associated with entropy in a sample of 892 healthy adults, using resting-state fMRI. Intelligence is measured with the Shipley Vocabulary and WASI Matrix Reasoning tests. Brain entropy was positively associated with intelligence. This relation was most strongly observed in the prefrontal cortex, inferior temporal lobes, and cerebellum. This relationship between high brain entropy and high intelligence indicates an essential role for entropy in brain functioning. It demonstrates that access to variable neural states predicts complex behavioral performance, and specifically shows that entropy derived from neuroimaging signals at rest carries information about intellectual capacity. Future work in this area may elucidate the links between brain entropy in both resting and active states and various forms of intelligence. This insight has the potential to provide predictive information about adaptive behavior and to delineate the subdivisions and nature of intelligence based on entropic patterns.

Brain modularity controls the critical behavior of spontaneous activity.

PubMed

Russo, R; Herrmann, H J; de Arcangelis, L

2014-03-13

The human brain exhibits a complex structure made of scale-free highly connected modules loosely interconnected by weaker links to form a small-world network. These features appear in healthy patients whereas neurological diseases often modify this structure. An important open question concerns the role of brain modularity in sustaining the critical behaviour of spontaneous activity. Here we analyse the neuronal activity of a model, successful in reproducing on non-modular networks the scaling behaviour observed in experimental data, on a modular network implementing the main statistical features measured in human brain. We show that on a modular network, regardless the strength of the synaptic connections or the modular size and number, activity is never fully scale-free. Neuronal avalanches can invade different modules which results in an activity depression, hindering further avalanche propagation. Critical behaviour is solely recovered if inter-module connections are added, modifying the modular into a more random structure.

Complex network inference from P300 signals: Decoding brain state under visual stimulus for able-bodied and disabled subjects

NASA Astrophysics Data System (ADS)

Gao, Zhong-Ke; Cai, Qing; Dong, Na; Zhang, Shan-Shan; Bo, Yun; Zhang, Jie

2016-10-01

Distinguishing brain cognitive behavior underlying disabled and able-bodied subjects constitutes a challenging problem of significant importance. Complex network has established itself as a powerful tool for exploring functional brain networks, which sheds light on the inner workings of the human brain. Most existing works in constructing brain network focus on phase-synchronization measures between regional neural activities. In contrast, we propose a novel approach for inferring functional networks from P300 event-related potentials by integrating time and frequency domain information extracted from each channel signal, which we show to be efficient in subsequent pattern recognition. In particular, we construct brain network by regarding each channel signal as a node and determining the edges in terms of correlation of the extracted feature vectors. A six-choice P300 paradigm with six different images is used in testing our new approach, involving one able-bodied subject and three disabled subjects suffering from multiple sclerosis, cerebral palsy, traumatic brain and spinal-cord injury, respectively. We then exploit global efficiency, local efficiency and small-world indices from the derived brain networks to assess the network topological structure associated with different target images. The findings suggest that our method allows identifying brain cognitive behaviors related to visual stimulus between able-bodied and disabled subjects.

Evolution of brain-computer interfaces: going beyond classic motor physiology

PubMed Central

Leuthardt, Eric C.; Schalk, Gerwin; Roland, Jarod; Rouse, Adam; Moran, Daniel W.

2010-01-01

The notion that a computer can decode brain signals to infer the intentions of a human and then enact those intentions directly through a machine is becoming a realistic technical possibility. These types of devices are known as brain-computer interfaces (BCIs). The evolution of these neuroprosthetic technologies could have significant implications for patients with motor disabilities by enhancing their ability to interact and communicate with their environment. The cortical physiology most investigated and used for device control has been brain signals from the primary motor cortex. To date, this classic motor physiology has been an effective substrate for demonstrating the potential efficacy of BCI-based control. However, emerging research now stands to further enhance our understanding of the cortical physiology underpinning human intent and provide further signals for more complex brain-derived control. In this review, the authors report the current status of BCIs and detail the emerging research trends that stand to augment clinical applications in the future. PMID:19569892

Post-adolescent developmental changes in cortical complexity.

PubMed

Sandu, Anca-Larisa; Izard, Edouard; Specht, Karsten; Beneventi, Harald; Lundervold, Arvid; Ystad, Martin

2014-11-27

Post-adolescence is known to be a period of general maturation and development in the human brain. In brain imaging, volumetric and morphologic cortical grey-matter changes can easily be assessed, but the analysis of cortical complexity seems to have been broadly neglected for this age interval. Magnetic resonance imaging (MRI) was used to acquire structural brain images. The study involved 17 adolescents (mean age 14.1 ± 0.27, 11 girls) who were compared with 14 young adults (mean age 24.24 ± 2.76, 7 women) for measures of brain complexity (fractal dimension--FD), grey matter (GM) volume and surface-area of cortical ribbon. FD was calculated using box-counting and Minkowski-Bouligand methods; FD and GM volume were measured for the whole brain, each hemisphere and lobes: frontal, occipital, parietal and temporal. The results show that the adults have a lower cortical complexity than the adolescents, which was significant for whole brain, left and right hemisphere, frontal and parietal lobes for both genders; and only for males in left temporal lobe. The GM volume was smaller in men than in boys for almost all measurements, and smaller in women than in girls just for right parietal lobe. A significant Pearson correlation was found between FD and GM volume for whole brain and each hemisphere in both genders. The decrease of the GM surface-area was significant in post-adolescence for males, not for females. During post-adolescence there are common changes in cortical complexity in the same regions for both genders, but there are also gender specific changes in some cortical areas. The sex differences from different cortical measurements (FD, GM volume and surface-area of cortical ribbon) could suggest a maturation delay in specific brain regions for each gender in relation to the other and might be explained through the functional role of the corresponding regions reflected in gender difference of developed abilities.

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

PubMed Central

Tagliazucchi, Enzo; Sanjuán, Ana

2017-01-01

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

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

PubMed

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

2017-01-01

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

IgG and complement deposition and neuronal loss in cats and humans with epilepsy and voltage-gated potassium channel complex antibodies.

PubMed

Klang, Andrea; Schmidt, Peter; Kneissl, Sibylle; Bagó, Zoltán; Vincent, Angela; Lang, Bethan; Moloney, Teresa; Bien, Christian G; Halász, Péter; Bauer, Jan; Pákozdy, Akos

2014-05-01

Voltage-gated potassium channel complex (VGKC-complex) antibody (Ab) encephalitis is a well-recognized form of limbic encephalitis in humans, usually occurring in the absence of an underlying tumor. The patients have a subacute onset of seizures, magnetic resonance imaging findings suggestive of hippocampal inflammation, and high serum titers of Abs against proteins of the VGKC-complex, particularly leucine-rich, glioma-inactivated 1 (LGI1). Most patients are diagnosed promptly and recover substantially with immunotherapies; consequently, neuropathological data are limited. We have recently shown that feline complex partial cluster seizures with orofacial involvement (FEPSO) in cats can also be associated with Abs against VGKC-complexes/LGI1. Here we examined the brains of cats with FEPSO and compared the neuropathological findings with those in a human with VGKC-complex-Ab limbic encephalitis. Similar to humans, cats with VGKC-complex-Ab and FEPSO have hippocampal lesions with only moderate T-cell infiltrates but with marked IgG infiltration and complement C9neo deposition on hippocampal neurons, associated with neuronal loss. These findings provide further evidence that FEPSO is a feline form of VGKC-complex-Ab limbic encephalitis and provide a model for increasing understanding of the human disease.

Complex Trajectories of Brain Development in the Healthy Human Fetus.

PubMed

Andescavage, Nickie N; du Plessis, Adre; McCarter, Robert; Serag, Ahmed; Evangelou, Iordanis; Vezina, Gilbert; Robertson, Richard; Limperopoulos, Catherine

2017-11-01

This study characterizes global and hemispheric brain growth in healthy human fetuses during the second half of pregnancy using three-dimensional MRI techniques. We studied 166 healthy fetuses that underwent MRI between 18 and 39 completed weeks gestation. We created three-dimensional high-resolution reconstructions of the brain and calculated volumes for left and right cortical gray matter (CGM), fetal white matter (FWM), deep subcortical structures (DSS), and the cerebellum. We calculated the rate of growth for each tissue class according to gestational age and described patterns of hemispheric growth. Each brain region demonstrated major increases in volume during the second half of gestation, the most pronounced being the cerebellum (34-fold), followed by FWM (22-fold), CGM (21-fold), and DSS (10-fold). The left cerebellar hemisphere, CGM, and DSS had larger volumes early in gestation, but these equalized by term. It has been increasingly recognized that brain asymmetry evolves throughout the human life span. Advanced quantitative MRI provides noninvasive measurements of early structural asymmetry between the left and right fetal brain that may inform functional and behavioral laterality differences seen in children and young adulthood. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Computer-assisted mapping of immunoreactive mammalian gonadotropin-releasing hormone in adult human basal forebrain and amygdala.

PubMed

Stopa, E G; Koh, E T; Svendsen, C N; Rogers, W T; Schwaber, J S; King, J C

1991-06-01

Immunocytochemistry performed on 80-microns unembedded tissue sections was used to study the localization of GnRH-containing neurons and fibers in the basal forebrain and amygdala of six adult (four male, two female) human brains. Sections from one of the female brains were subjected to computer-assisted microscopic mapping to generate a three-dimensional analysis of immunoreactive structures. In all six brains examined, cell bodies were concentrated in the preoptic area and basal hypothalamus, but were also evident in the septal region, anterior olfactory area, and cortical and medial amygdaloid nuclei. GnRH-containing fibers were observed within the hypothalamus (predominantly infundibular region and preoptic area), septum, stria terminalis, ventral pallidum, dorsomedial thalamus, olfactory stria, and anterior olfactory area. Many fibers could also be seen coursing along the base of the brain between the hypothalamus and cortical and medial amygdaloid nuclei. The localization of GnRH-containing cells and fibers in several of these areas represents new observations in the human brain and suggests a role for the amygdaloid complex in the regulation of gonadotropin secretion. The comprehensive view provided by these data may be useful in the clinical application of novel transplantation strategies.

Orthotopic Patient-Derived Glioblastoma Xenografts in Mice.

PubMed

Xu, Zhongye; Kader, Michael; Sen, Rajeev; Placantonakis, Dimitris G

2018-01-01

Patient-derived xenografts (PDX) provide in vivo glioblastoma (GBM) models that recapitulate actual tumors. Orthotopic tumor xenografts within the mouse brain are obtained by injection of GBM stem-like cells derived from fresh surgical specimens. These xenografts reproduce GBM's histologic complexity and hallmark biological behaviors, such as brain invasion, angiogenesis, and resistance to therapy. This method has become essential for analyzing mechanisms of tumorigenesis and testing the therapeutic effect of candidate agents in the preclinical setting. Here, we describe a protocol for establishing orthotopic tumor xenografts in the mouse brain with human GBM cells.

Similarity-Based Fusion of MEG and fMRI Reveals Spatio-Temporal Dynamics in Human Cortex During Visual Object Recognition

PubMed Central

Cichy, Radoslaw Martin; Pantazis, Dimitrios; Oliva, Aude

2016-01-01

Every human cognitive function, such as visual object recognition, is realized in a complex spatio-temporal activity pattern in the brain. Current brain imaging techniques in isolation cannot resolve the brain's spatio-temporal dynamics, because they provide either high spatial or temporal resolution but not both. To overcome this limitation, we developed an integration approach that uses representational similarities to combine measurements of magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) to yield a spatially and temporally integrated characterization of neuronal activation. Applying this approach to 2 independent MEG–fMRI data sets, we observed that neural activity first emerged in the occipital pole at 50–80 ms, before spreading rapidly and progressively in the anterior direction along the ventral and dorsal visual streams. Further region-of-interest analyses established that dorsal and ventral regions showed MEG–fMRI correspondence in representations later than early visual cortex. Together, these results provide a novel and comprehensive, spatio-temporally resolved view of the rapid neural dynamics during the first few hundred milliseconds of object vision. They further demonstrate the feasibility of spatially unbiased representational similarity-based fusion of MEG and fMRI, promising new insights into how the brain computes complex cognitive functions. PMID:27235099

Gut microbes and the brain: paradigm shift in neuroscience.

PubMed

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

2014-11-12

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

Analysis of evoked deep brain connectivity.

PubMed

Klimeš, Petr; Janeček, Jiři; Jurák, Pavel; Halámek, Josef; Chládek, Han; Brázdil, Milan

2013-01-01

Establishing dependencies and connectivity among different structures in the human brain is an extremely complex issue. Methods that are often used for connectivity analysis are based on correlation mechanisms. Correlation methods can analyze changes in signal shape or instantaneous power level. Although recent studies imply that observation of results from both groups of methods together can disclose some of the basic functions and behavior of the human brain during mental activity and decision-making, there is no technique covering changes in the shape of signals along with changes in their power levels. We present a method using a time evaluation of the correlation along with a comparison of power levels in every available contact pair from intracranial electrodes placed in deep brain structures. Observing shape changes in signals after stimulation together with their power levels provides us with new information about signal character between different structures in the brain during task-related events - visual stimulation with motor response. The results for a subject with 95 intracerebral contacts used in this paper demonstrate a clear methodology capable of spatially analyzing connectivity among deep brain structures.

Neural Connectivity Patterns Underlying Symbolic Number Processing Indicate Mathematical Achievement in Children

ERIC Educational Resources Information Center

Park, Joonkoo; Li, Rosa; Brannon, Elizabeth M.

2014-01-01

In early childhood, humans learn culturally specific symbols for number that allow them entry into the world of complex numerical thinking. Yet little is known about how the brain supports the development of the uniquely human symbolic number system. Here, we use functional magnetic resonance imaging along with an effective connectivity analysis…

Linking neuronal brain activity to the glucose metabolism.

PubMed

Göbel, Britta; Oltmanns, Kerstin M; Chung, Matthias

2013-08-29

Energy homeostasis ensures the functionality of the entire organism. The human brain as a missing link in the global regulation of the complex whole body energy metabolism is subject to recent investigation. The goal of this study is to gain insight into the influence of neuronal brain activity on cerebral and peripheral energy metabolism. In particular, the tight link between brain energy supply and metabolic responses of the organism is of interest. We aim to identifying regulatory elements of the human brain in the whole body energy homeostasis. First, we introduce a general mathematical model describing the human whole body energy metabolism. It takes into account the two central roles of the brain in terms of energy metabolism. The brain is considered as energy consumer as well as regulatory instance. Secondly, we validate our mathematical model by experimental data. Cerebral high-energy phosphate content and peripheral glucose metabolism are measured in healthy men upon neuronal activation induced by transcranial direct current stimulation versus sham stimulation. By parameter estimation we identify model parameters that provide insight into underlying neurophysiological processes. Identified parameters reveal effects of neuronal activity on regulatory mechanisms of systemic glucose metabolism. Our examinations support the view that the brain increases its glucose supply upon neuronal activation. The results indicate that the brain supplies itself with energy according to its needs, and preeminence of cerebral energy supply is reflected. This mechanism ensures balanced cerebral energy homeostasis. The hypothesis of the central role of the brain in whole body energy homeostasis as active controller is supported.

Linking neuronal brain activity to the glucose metabolism

PubMed Central

2013-01-01

Background Energy homeostasis ensures the functionality of the entire organism. The human brain as a missing link in the global regulation of the complex whole body energy metabolism is subject to recent investigation. The goal of this study is to gain insight into the influence of neuronal brain activity on cerebral and peripheral energy metabolism. In particular, the tight link between brain energy supply and metabolic responses of the organism is of interest. We aim to identifying regulatory elements of the human brain in the whole body energy homeostasis. Methods First, we introduce a general mathematical model describing the human whole body energy metabolism. It takes into account the two central roles of the brain in terms of energy metabolism. The brain is considered as energy consumer as well as regulatory instance. Secondly, we validate our mathematical model by experimental data. Cerebral high-energy phosphate content and peripheral glucose metabolism are measured in healthy men upon neuronal activation induced by transcranial direct current stimulation versus sham stimulation. By parameter estimation we identify model parameters that provide insight into underlying neurophysiological processes. Identified parameters reveal effects of neuronal activity on regulatory mechanisms of systemic glucose metabolism. Results Our examinations support the view that the brain increases its glucose supply upon neuronal activation. The results indicate that the brain supplies itself with energy according to its needs, and preeminence of cerebral energy supply is reflected. This mechanism ensures balanced cerebral energy homeostasis. Conclusions The hypothesis of the central role of the brain in whole body energy homeostasis as active controller is supported. PMID:23988084

Structural covariance networks are coupled to expression of genes enriched in supragranular layers of the human cortex.

PubMed

Romero-Garcia, Rafael; Whitaker, Kirstie J; Váša, František; Seidlitz, Jakob; Shinn, Maxwell; Fonagy, Peter; Dolan, Raymond J; Jones, Peter B; Goodyer, Ian M; Bullmore, Edward T; Vértes, Petra E

2018-05-01

Complex network topology is characteristic of many biological systems, including anatomical and functional brain networks (connectomes). Here, we first constructed a structural covariance network from MRI measures of cortical thickness on 296 healthy volunteers, aged 14-24 years. Next, we designed a new algorithm for matching sample locations from the Allen Brain Atlas to the nodes of the SCN. Subsequently we used this to define, transcriptomic brain networks by estimating gene co-expression between pairs of cortical regions. Finally, we explored the hypothesis that transcriptional networks and structural MRI connectomes are coupled. A transcriptional brain network (TBN) and a structural covariance network (SCN) were correlated across connection weights and showed qualitatively similar complex topological properties: assortativity, small-worldness, modularity, and a rich-club. In both networks, the weight of an edge was inversely related to the anatomical (Euclidean) distance between regions. There were differences between networks in degree and distance distributions: the transcriptional network had a less fat-tailed degree distribution and a less positively skewed distance distribution than the SCN. However, cortical areas connected to each other within modules of the SCN had significantly higher levels of whole genome co-expression than expected by chance. Nodes connected in the SCN had especially high levels of expression and co-expression of a human supragranular enriched (HSE) gene set that has been specifically located to supragranular layers of human cerebral cortex and is known to be important for large-scale, long-distance cortico-cortical connectivity. This coupling of brain transcriptome and connectome topologies was largely but not entirely accounted for by the common constraint of physical distance on both networks. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Imaging brain development: the adolescent brain.

PubMed

Blakemore, Sarah-Jayne

2012-06-01

The past 15 years have seen a rapid expansion in the number of studies using neuroimaging techniques to investigate maturational changes in the human brain. In this paper, I review MRI studies on structural changes in the developing brain, and fMRI studies on functional changes in the social brain during adolescence. Both MRI and fMRI studies point to adolescence as a period of continued neural development. In the final section, I discuss a number of areas of research that are just beginning and may be the subject of developmental neuroimaging in the next twenty years. Future studies might focus on complex questions including the development of functional connectivity; how gender and puberty influence adolescent brain development; the effects of genes, environment and culture on the adolescent brain; development of the atypical adolescent brain; and implications for policy of the study of the adolescent brain. Copyright © 2011 Elsevier Inc. All rights reserved.

Fiber tracking of brain white matter based on graph theory.

PubMed

Lu, Meng

2015-01-01

Brain white matter tractography is reconstructed via diffusion-weighted magnetic resonance images. Due to the complex structure of brain white matter fiber bundles, fiber crossing and fiber branching are abundant in human brain. And regular methods with diffusion tensor imaging (DTI) can't accurately handle this problem. the biggest problems of the brain tractography. Therefore, this paper presented a novel brain white matter tractography method based on graph theory, so the fiber tracking between two voxels is transformed into locating the shortest path in a graph. Besides, the presented method uses Q-ball imaging (QBI) as the source data instead of DTI, because QBI can provide accurate information about multiple fiber crossing and branching in one voxel using orientation distribution function (ODF). Experiments showed that the presented method can accurately handle the problem of brain white matter fiber crossing and branching, and reconstruct brain tractograhpy both in phantom data and real brain data.

Network complexity as a measure of information processing across resting-state networks: evidence from the Human Connectome Project

PubMed Central

McDonough, Ian M.; Nashiro, Kaoru

2014-01-01

An emerging field of research focused on fluctuations in brain signals has provided evidence that the complexity of those signals, as measured by entropy, conveys important information about network dynamics (e.g., local and distributed processing). While much research has focused on how neural complexity differs in populations with different age groups or clinical disorders, substantially less research has focused on the basic understanding of neural complexity in populations with young and healthy brain states. The present study used resting-state fMRI data from the Human Connectome Project (Van Essen et al., 2013) to test the extent that neural complexity in the BOLD signal, as measured by multiscale entropy (1) would differ from random noise, (2) would differ between four major resting-state networks previously associated with higher-order cognition, and (3) would be associated with the strength and extent of functional connectivity—a complementary method of estimating information processing. We found that complexity in the BOLD signal exhibited different patterns of complexity from white, pink, and red noise and that neural complexity was differentially expressed between resting-state networks, including the default mode, cingulo-opercular, left and right frontoparietal networks. Lastly, neural complexity across all networks was negatively associated with functional connectivity at fine scales, but was positively associated with functional connectivity at coarse scales. The present study is the first to characterize neural complexity in BOLD signals at a high temporal resolution and across different networks and might help clarify the inconsistencies between neural complexity and functional connectivity, thus informing the mechanisms underlying neural complexity. PMID:24959130

Graph theoretical analysis of complex networks in the brain

PubMed Central

Stam, Cornelis J; Reijneveld, Jaap C

2007-01-01

Since the discovery of small-world and scale-free networks the study of complex systems from a network perspective has taken an enormous flight. In recent years many important properties of complex networks have been delineated. In particular, significant progress has been made in understanding the relationship between the structural properties of networks and the nature of dynamics taking place on these networks. For instance, the 'synchronizability' of complex networks of coupled oscillators can be determined by graph spectral analysis. These developments in the theory of complex networks have inspired new applications in the field of neuroscience. Graph analysis has been used in the study of models of neural networks, anatomical connectivity, and functional connectivity based upon fMRI, EEG and MEG. These studies suggest that the human brain can be modelled as a complex network, and may have a small-world structure both at the level of anatomical as well as functional connectivity. This small-world structure is hypothesized to reflect an optimal situation associated with rapid synchronization and information transfer, minimal wiring costs, as well as a balance between local processing and global integration. The topological structure of functional networks is probably restrained by genetic and anatomical factors, but can be modified during tasks. There is also increasing evidence that various types of brain disease such as Alzheimer's disease, schizophrenia, brain tumours and epilepsy may be associated with deviations of the functional network topology from the optimal small-world pattern. PMID:17908336

A network engineering perspective on probing and perturbing cognition with neurofeedback

PubMed Central

Khambhati, Ankit N.

2017-01-01

Network science and engineering provide a flexible and generalizable tool set to describe and manipulate complex systems characterized by heterogeneous interaction patterns among component parts. While classically applied to social systems, these tools have recently proven to be particularly useful in the study of the brain. In this review, we describe the nascent use of these tools to understand human cognition, and we discuss their utility in informing the meaningful and predictable perturbation of cognition in combination with the emerging capabilities of neurofeedback. To blend these disparate strands of research, we build on emerging conceptualizations of how the brain functions (as a complex network) and how we can develop and target interventions or modulations (as a form of network control). We close with an outline of current frontiers that bridge neurofeedback, connectomics, and network control theory to better understand human cognition. PMID:28445589

Neuroscience, moral reasoning, and the law.

PubMed

Knabb, Joshua J; Welsh, Robert K; Ziebell, Joseph G; Reimer, Kevin S

2009-01-01

Modern advancements in functional magnetic resonance imaging (fMRI) technology have given neuroscientists the opportunity to more fully appreciate the brain's contribution to human behavior and decision making. Morality and moral reasoning are relative newcomers to the growing literature on decision neuroscience. With recent attention given to the salience of moral factors (e.g. moral emotions, moral reasoning) in the process of decision making, neuroscientists have begun to offer helpful frameworks for understanding the interplay between the brain, morality, and human decision making. These frameworks are relatively unfamiliar to the community of forensic psychologists, despite the fact that they offer an improved understanding of judicial decision making from a biological perspective. This article presents a framework reviewing how event-feature-emotion complexes (EFEC) are relevant to jurors and understanding complex criminal behavior. Future directions regarding converging fields of neuroscience and legal decision making are considered. Copyright 2009 John Wiley & Sons, Ltd.

Encoding and Decoding Models in Cognitive Electrophysiology

PubMed Central

Holdgraf, Christopher R.; Rieger, Jochem W.; Micheli, Cristiano; Martin, Stephanie; Knight, Robert T.; Theunissen, Frederic E.

2017-01-01

Cognitive neuroscience has seen rapid growth in the size and complexity of data recorded from the human brain as well as in the computational tools available to analyze this data. This data explosion has resulted in an increased use of multivariate, model-based methods for asking neuroscience questions, allowing scientists to investigate multiple hypotheses with a single dataset, to use complex, time-varying stimuli, and to study the human brain under more naturalistic conditions. These tools come in the form of “Encoding” models, in which stimulus features are used to model brain activity, and “Decoding” models, in which neural features are used to generated a stimulus output. Here we review the current state of encoding and decoding models in cognitive electrophysiology and provide a practical guide toward conducting experiments and analyses in this emerging field. Our examples focus on using linear models in the study of human language and audition. We show how to calculate auditory receptive fields from natural sounds as well as how to decode neural recordings to predict speech. The paper aims to be a useful tutorial to these approaches, and a practical introduction to using machine learning and applied statistics to build models of neural activity. The data analytic approaches we discuss may also be applied to other sensory modalities, motor systems, and cognitive systems, and we cover some examples in these areas. In addition, a collection of Jupyter notebooks is publicly available as a complement to the material covered in this paper, providing code examples and tutorials for predictive modeling in python. The aim is to provide a practical understanding of predictive modeling of human brain data and to propose best-practices in conducting these analyses. PMID:29018336

A Comparative View of Face Perception

PubMed Central

Leopold, David A.; Rhodes, Gillian

2010-01-01

Face perception serves as the basis for much of human social exchange. Diverse information can be extracted about an individual from a single glance at their face, including their identity, emotional state, and direction of attention. Neuropsychological and fMRI experiments reveal a complex network of specialized areas in the human brain supporting these face-reading skills. Here we consider the evolutionary roots of human face perception by exploring the manner in which different animal species view and respond to faces. We focus on behavioral experiments collected from both primates and non-primates, assessing the types of information that animals are able to extract from the faces of their conspecifics, human experimenters, and natural predators. These experiments reveal that faces are an important category of visual stimuli for animals in all major vertebrate taxa, possibly reflecting the early emergence of neural specialization for faces in vertebrate evolution. At the same time, some aspects of facial perception are only evident in primates and a few other social mammals, and may therefore have evolved to suit the needs of complex social communication. Since the human brain likely utilizes both primitive and recently evolved neural specializations for the processing of faces, comparative studies may hold the key to understanding how these parallel circuits emerged during human evolution. PMID:20695655

A comparative view of face perception.

PubMed

Leopold, David A; Rhodes, Gillian

2010-08-01

Face perception serves as the basis for much of human social exchange. Diverse information can be extracted about an individual from a single glance at their face, including their identity, emotional state, and direction of attention. Neuropsychological and functional magnetic resonance imaging (fMRI) experiments reveal a complex network of specialized areas in the human brain supporting these face-reading skills. Here we consider the evolutionary roots of human face perception by exploring the manner in which different animal species view and respond to faces. We focus on behavioral experiments collected from both primates and nonprimates, assessing the types of information that animals are able to extract from the faces of their conspecifics, human experimenters, and natural predators. These experiments reveal that faces are an important category of visual stimuli for animals in all major vertebrate taxa, possibly reflecting the early emergence of neural specialization for faces in vertebrate evolution. At the same time, some aspects of facial perception are only evident in primates and a few other social mammals, and may therefore have evolved to suit the needs of complex social communication. Because the human brain likely utilizes both primitive and recently evolved neural specializations for the processing of faces, comparative studies may hold the key to understanding how these parallel circuits emerged during human evolution. 2010 APA, all rights reserved

High-resolution temporal and regional mapping of MAPT expression and splicing in human brain development.

PubMed

Hefti, Marco M; Farrell, Kurt; Kim, SoongHo; Bowles, Kathryn R; Fowkes, Mary E; Raj, Towfique; Crary, John F

2018-01-01

The microtubule associated protein tau plays a critical role in the pathogenesis of neurodegenerative disease. Recent studies suggest that tau also plays a role in disorders of neuronal connectivity, including epilepsy and post-traumatic stress disorder. Animal studies have shown that the MAPT gene, which codes for the tau protein, undergoes complex pre-mRNA alternative splicing to produce multiple isoforms during brain development. Human data, particularly on temporal and regional variation in tau splicing during development are however lacking. In this study, we present the first detailed examination of the temporal and regional sequence of MAPT alternative splicing in the developing human brain. We used a novel computational analysis of large transcriptomic datasets (total n = 502 patients), quantitative polymerase chain reaction (qPCR) and western blotting to examine tau expression and splicing in post-mortem human fetal, pediatric and adult brains. We found that MAPT exons 2 and 10 undergo abrupt shifts in expression during the perinatal period that are unique in the canonical human microtubule-associated protein family, while exon 3 showed small but significant temporal variation. Tau isoform expression may be a marker of neuronal maturation, temporally correlated with the onset of axonal growth. Immature brain regions such as the ganglionic eminence and rhombic lip had very low tau expression, but within more mature regions, there was little variation in tau expression or splicing. We thus demonstrate an abrupt, evolutionarily conserved shift in tau isoform expression during the human perinatal period that may be due to tau expression in maturing neurons. Alternative splicing of the MAPT pre-mRNA may play a vital role in normal brain development across multiple species and provides a basis for future investigations into the developmental and pathological functions of the tau protein.

AMPA-receptor specific biogenesis complexes control synaptic transmission and intellectual ability

PubMed Central

Brechet, Aline; Buchert, Rebecca; Schwenk, Jochen; Boudkkazi, Sami; Zolles, Gerd; Siquier-Pernet, Karine; Schaber, Irene; Bildl, Wolfgang; Saadi, Abdelkrim; Bole-Feysot, Christine; Nitschke, Patrick; Reis, Andre; Sticht, Heinrich; Al-Sanna’a, Nouriya; Rolfs, Arndt; Kulik, Akos; Schulte, Uwe; Colleaux, Laurence; Abou Jamra, Rami; Fakler, Bernd

2017-01-01

AMPA-type glutamate receptors (AMPARs), key elements in excitatory neurotransmission in the brain, are macromolecular complexes whose properties and cellular functions are determined by the co-assembled constituents of their proteome. Here we identify AMPAR complexes that transiently form in the endoplasmic reticulum (ER) and lack the core-subunits typical for AMPARs in the plasma membrane. Central components of these ER AMPARs are the proteome constituents FRRS1l (C9orf4) and CPT1c that specifically and cooperatively bind to the pore-forming GluA1-4 proteins of AMPARs. Bi-allelic mutations in the human FRRS1L gene are shown to cause severe intellectual disability with cognitive impairment, speech delay and epileptic activity. Virus-directed deletion or overexpression of FRRS1l strongly impact synaptic transmission in adult rat brain by decreasing or increasing the number of AMPARs in synapses and extra-synaptic sites. Our results provide insight into the early biogenesis of AMPARs and demonstrate its pronounced impact on synaptic transmission and brain function. PMID:28675162

Mutations in UNC80, Encoding Part of the UNC79-UNC80-NALCN Channel Complex, Cause Autosomal-Recessive Severe Infantile Encephalopathy.

PubMed

Shamseldin, Hanan E; Faqeih, Eissa; Alasmari, Ali; Zaki, Maha S; Gleeson, Joseph G; Alkuraya, Fowzan S

2016-01-07

Brain channelopathies represent a growing class of brain disorders that usually result in paroxysmal disorders, although their role in other neurological phenotypes, including the recently described NALCN-related infantile encephalopathy, is increasingly recognized. In three Saudi Arabian families and one Egyptian family all affected by a remarkably similar phenotype (infantile encephalopathy and largely normal brain MRI) to that of NALCN-related infantile encephalopathy, we identified a locus on 2q34 in which whole-exome sequencing revealed three, including two apparently loss-of-function, recessive mutations in UNC80. UNC80 encodes a large protein that is necessary for the stability and function of NALCN and for bridging NALCN to UNC79 to form a functional complex. Our results expand the clinical relevance of the UNC79-UNC80-NALCN channel complex. Copyright © 2016 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

A neurologist looks at mind and brain: "the enchanted loom".

PubMed

Hansotia, Phiroze

2003-10-01

For a long time, before we developed an appreciation of the neuroanatomy and neurophysiology of the brain, there was uncertainty as to the nature and source of the human mind. Philosophers linked the mind to mythical "humors" that controlled the human body, and others speculated that the mind was associated with "life-force" or soul. Few felt that there was a relation between the human mind and brain, but they had to wait for the Age of Enlightenment and scientific discovery in the 18th and 19th centuries to establish a clear association between the two. Three centuries ago Rene Descartes described the mind as an extracorporeal entity that was expressed through the pineal gland. Descartes was wrong about the pineal, but the debate he set off regarding the relationship between mind and brain rages on. This review looks at the history of speculation on the mind and the development of ideas that have led to our present understanding of this phenomenon. The basic anatomy and physiology of the brain is reviewed to help us understand the brain's association with the complex function we call mind. This is followed by a look at some syndromes that may result when part of the brain is damaged-the parietal lobe is arbitrarily selected as an example-and the resulting effect on the subject's mind. This assists us in understanding the association of mind and brain, and also to better understanding its components, behavior, function and dysfunction.

Gaining Insight of Fetal Brain Development with Diffusion MRI and Histology

PubMed Central

Huang, Hao; Vasung, Lana

2013-01-01

Human brain is extraordinarily complex and yet its origin is a simple tubular structure. Its development during the fetal period is characterized by a series of accurately organized events which underlie the mechanisms of dramatic structural changes during fetal development. Revealing detailed anatomy at different stages of human fetal brain development provides insight on understanding not only this highly ordered process, but also the neurobiological foundations of cognitive brain disorders such as mental retardation, autism, schizophrenia, bipolar and language impairment. Diffusion tensor imaging (DTI) and histology are complementary tools which are capable of delineating the fetal brain structures at both macroscopic and microscopic level. In this review, the structural development of the fetal brains has been characterized with DTI and histology. Major components of the fetal brain, including cortical plate, fetal white matter and cerebral wall layer between the ventricle and subplate, have been delineated with DTI and histology. Anisotropic metrics derived from DTI were used to quantify the microstructural changes during the dynamic process of human fetal cortical development and prenatal development of other animal models. Fetal white matter pathways have been traced with DTI-based tractography to reveal growth patterns of individual white matter tracts and corticocortical connectivity. These detailed anatomical accounts of the structural changes during fetal period may provide the clues of detecting developmental and cognitive brain disorders at their early stages. The anatomical information from DTI and histology may also provide reference standards for diagnostic radiology of premature newborns. PMID:23796901

A simpler primate brain: the visual system of the marmoset monkey

PubMed Central

Solomon, Samuel G.; Rosa, Marcello G. P.

2014-01-01

Humans are diurnal primates with high visual acuity at the center of gaze. Although primates share many similarities in the organization of their visual centers with other mammals, and even other species of vertebrates, their visual pathways also show unique features, particularly with respect to the organization of the cerebral cortex. Therefore, in order to understand some aspects of human visual function, we need to study non-human primate brains. Which species is the most appropriate model? Macaque monkeys, the most widely used non-human primates, are not an optimal choice in many practical respects. For example, much of the macaque cerebral cortex is buried within sulci, and is therefore inaccessible to many imaging techniques, and the postnatal development and lifespan of macaques are prohibitively long for many studies of brain maturation, plasticity, and aging. In these and several other respects the marmoset, a small New World monkey, represents a more appropriate choice. Here we review the visual pathways of the marmoset, highlighting recent work that brings these advantages into focus, and identify where additional work needs to be done to link marmoset brain organization to that of macaques and humans. We will argue that the marmoset monkey provides a good subject for studies of a complex visual system, which will likely allow an important bridge linking experiments in animal models to humans. PMID:25152716

Using the Optical Fractionator to Estimate Total Cell Numbers in the Normal and Abnormal Developing Human Forebrain.

PubMed

Larsen, Karen B

2017-01-01

Human fetal brain development is a complex process which is vulnerable to disruption at many stages. Although histogenesis is well-documented, only a few studies have quantified cell numbers across normal human fetal brain growth. Due to the present lack of normative data it is difficult to gauge abnormal development. Furthermore, many studies of brain cell numbers have employed biased counting methods, whereas innovations in stereology during the past 20-30 years enable reliable and efficient estimates of cell numbers. However, estimates of cell volumes and densities in fetal brain samples are unreliable due to unpredictable shrinking artifacts, and the fragility of the fetal brain requires particular care in handling and processing. The optical fractionator design offers a direct and robust estimate of total cell numbers in the fetal brain with a minimum of handling of the tissue. Bearing this in mind, we have used the optical fractionator to quantify the growth of total cell numbers as a function of fetal age. We discovered a two-phased development in total cell numbers in the human fetal forebrain consisting of an initial steep rise in total cell numbers between 13 and 20 weeks of gestation, followed by a slower linear phase extending from mid-gestation to 40 weeks of gestation. Furthermore, we have demonstrated a reduced total cell number in the forebrain in fetuses with Down syndome at midgestation and in intrauterine growth-restricted fetuses during the third trimester.

Parallel Computing for Brain Simulation.

PubMed

Pastur-Romay, L A; Porto-Pazos, A B; Cedron, F; Pazos, A

2017-01-01

The human brain is the most complex system in the known universe, it is therefore one of the greatest mysteries. It provides human beings with extraordinary abilities. However, until now it has not been understood yet how and why most of these abilities are produced. For decades, researchers have been trying to make computers reproduce these abilities, focusing on both understanding the nervous system and, on processing data in a more efficient way than before. Their aim is to make computers process information similarly to the brain. Important technological developments and vast multidisciplinary projects have allowed creating the first simulation with a number of neurons similar to that of a human brain. This paper presents an up-to-date review about the main research projects that are trying to simulate and/or emulate the human brain. They employ different types of computational models using parallel computing: digital models, analog models and hybrid models. This review includes the current applications of these works, as well as future trends. It is focused on various works that look for advanced progress in Neuroscience and still others which seek new discoveries in Computer Science (neuromorphic hardware, machine learning techniques). Their most outstanding characteristics are summarized and the latest advances and future plans are presented. In addition, this review points out the importance of considering not only neurons: Computational models of the brain should also include glial cells, given the proven importance of astrocytes in information processing. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Functional aspects of early brain development are preserved in tuberous sclerosis complex (TSC) epileptogenic lesions.

PubMed

Ruffolo, Gabriele; Iyer, Anand; Cifelli, Pierangelo; Roseti, Cristina; Mühlebner, Angelika; van Scheppingen, Jackelien; Scholl, Theresa; Hainfellner, Johannes A; Feucht, Martha; Krsek, Pavel; Zamecnik, Josef; Jansen, Floor E; Spliet, Wim G M; Limatola, Cristina; Aronica, Eleonora; Palma, Eleonora

2016-11-01

Tuberous sclerosis complex (TSC) is a rare multi-system genetic disease characterized by several neurological disorders, the most common of which is the refractory epilepsy caused by highly epileptogenic cortical lesions. Previous studies suggest an alteration of GABAergic and glutamatergic transmission in TSC brain indicating an unbalance of excitation/inhibition that can explain, at least in part, the high incidence of epilepsy in these patients. Here we investigate whether TSC cortical tissues could retain GABAA and AMPA receptors at early stages of human brain development thus contributing to the generation and recurrence of seizures. Given the limited availability of pediatric human brain specimens, we used the microtransplantation method of injecting Xenopus oocytes with membranes from TSC cortical tubers and control brain tissues. Moreover, qPCR was performed to investigate the expression of GABAA and AMPA receptor subunits (GABAA α1-5, β3, γ2, δ; GluA1, GluA2) and cation chloride co-transporters NKCC1 and KCC2. The evaluation of nine human cortical brain samples, from 15 gestation weeks to 15years old, showed a progressive shift towards more hyperpolarized GABAA reversal potential (EGABA). This shift was associated with a differential expression of the chloride cotransporters NKCC1 and KCC2. Furthermore, the GluA1/GluA2 mRNA ratio of expression paralleled the development process. On the contrary, in oocytes micro-transplanted with epileptic TSC tuber tissue from seven patients, neither the GABAA reversal potential nor the GluA1/GluA2 expression showed similar developmental changes. Our data indicate for the first time, that in the same cohort of TSC patients, the pattern of both GABAAR and GluA1/GluA2 functions retains features that are typical of an immature brain. These observations support the potential contribution of altered receptor function to the epileptic disorder of TSC and may suggest novel therapeutic approaches. Furthermore, our findings strengthen the novel hypothesis that other developmental brain diseases can share the same hallmarks of immaturity leading to intractable seizures. Copyright © 2016 Elsevier Inc. All rights reserved.

Foundations for a New Science of Learning

PubMed Central

Meltzoff, Andrew N.; Kuhl, Patricia K.; Movellan, Javier; Sejnowski, Terrence J.

2009-01-01

Human learning is distinguished by the range and complexity of skills that can be learned and the degree of abstraction that can be achieved compared to other species. Humans are also the only species that has developed formal ways to enhance learning: teachers, schools, and curricula. Human infants have an intense interest in people and their behavior, and possess powerful implicit learning mechanisms that are affected by social interaction. Neuroscientists are beginning to understand the brain mechanisms underlying learning and how shared brain systems for perception and action support social learning. Machine learning algorithms are being developed that allow robots and computers to learn autonomously. New insights from many different fields are converging to create a new science of learning that may transform educational practices. PMID:19608908

Assessing Relevance of External Cognitive Measures.

PubMed

Cairó, Osvaldo

2017-01-01

The arrival of modern brain imaging technologies has provided new opportunities for examining the biological essence of human intelligence as well as the relationship between brain size and cognition. Thanks to these advances, we can now state that the relationship between brain size and intelligence has never been well understood. This view is supported by findings showing that cognition is correlated more with brain tissues than sheer brain size. The complexity of cellular and molecular organization of neural connections actually determines the computational capacity of the brain. In this review article, we determine that while genotypes are responsible for defining the theoretical limits of intelligence, what is primarily responsible for determining whether those limits are reached or exceeded is experience (environmental influence). Therefore, we contend that the gene-environment interplay defines the intelligent quotient of an individual.

Plasticity of the aging brain: new directions in cognitive neuroscience.

PubMed

Gutchess, Angela

2014-10-31

Cognitive neuroscience has revealed aging of the human brain to be rich in reorganization and change. Neuroimaging results have recast our framework around cognitive aging from one of decline to one emphasizing plasticity. Current methods use neurostimulation approaches to manipulate brain function, providing a direct test of the ways that the brain differently contributes to task performance for younger and older adults. Emerging research into emotional, social, and motivational domains provides some evidence for preservation with age, suggesting potential avenues of plasticity, alongside additional evidence for reorganization. Thus, we begin to see that aging of the brain, amidst interrelated behavioral and biological changes, is as complex and idiosyncratic as the brain itself, qualitatively changing over the life span. Copyright © 2014, American Association for the Advancement of Science.

Genetics of human hydrocephalus

PubMed Central

Williams, Michael A.; Rigamonti, Daniele

2006-01-01

Human hydrocephalus is a common medical condition that is characterized by abnormalities in the flow or resorption of cerebrospinal fluid (CSF), resulting in ventricular dilatation. Human hydrocephalus can be classified into two clinical forms, congenital and acquired. Hydrocephalus is one of the complex and multifactorial neurological disorders. A growing body of evidence indicates that genetic factors play a major role in the pathogenesis of hydrocephalus. An understanding of the genetic components and mechanism of this complex disorder may offer us significant insights into the molecular etiology of impaired brain development and an accumulation of the cerebrospinal fluid in cerebral compartments during the pathogenesis of hydrocephalus. Genetic studies in animal models have started to open the way for understanding the underlying pathology of hydrocephalus. At least 43 mutants/loci linked to hereditary hydrocephalus have been identified in animal models and humans. Up to date, 9 genes associated with hydrocephalus have been identified in animal models. In contrast, only one such gene has been identified in humans. Most of known hydrocephalus gene products are the important cytokines, growth factors or related molecules in the cellular signal pathways during early brain development. The current molecular genetic evidence from animal models indicate that in the early development stage, impaired and abnormal brain development caused by abnormal cellular signaling and functioning, all these cellular and developmental events would eventually lead to the congenital hydrocephalus. Owing to our very primitive knowledge of the genetics and molecular pathogenesis of human hydrocephalus, it is difficult to evaluate whether data gained from animal models can be extrapolated to humans. Initiation of a large population genetics study in humans will certainly provide invaluable information about the molecular and cellular etiology and the developmental mechanisms of human hydrocephalus. This review summarizes the recent findings on this issue among human and animal models, especially with reference to the molecular genetics, pathological, physiological and cellular studies, and identifies future research directions. PMID:16773266

Natural world physical, brain operational, and mind phenomenal space-time

NASA Astrophysics Data System (ADS)

Fingelkurts, Andrew A.; Fingelkurts, Alexander A.; Neves, Carlos F. H.

2010-06-01

Concepts of space and time are widely developed in physics. However, there is a considerable lack of biologically plausible theoretical frameworks that can demonstrate how space and time dimensions are implemented in the activity of the most complex life-system - the brain with a mind. Brain activity is organized both temporally and spatially, thus representing space-time in the brain. Critical analysis of recent research on the space-time organization of the brain's activity pointed to the existence of so-called operational space-time in the brain. This space-time is limited to the execution of brain operations of differing complexity. During each such brain operation a particular short-term spatio-temporal pattern of integrated activity of different brain areas emerges within related operational space-time. At the same time, to have a fully functional human brain one needs to have a subjective mental experience. Current research on the subjective mental experience offers detailed analysis of space-time organization of the mind. According to this research, subjective mental experience (subjective virtual world) has definitive spatial and temporal properties similar to many physical phenomena. Based on systematic review of the propositions and tenets of brain and mind space-time descriptions, our aim in this review essay is to explore the relations between the two. To be precise, we would like to discuss the hypothesis that via the brain operational space-time the mind subjective space-time is connected to otherwise distant physical space-time reality.

Computational modeling of blast wave interaction with a human body and assessment of traumatic brain injury

NASA Astrophysics Data System (ADS)

Tan, X. G.; Przekwas, A. J.; Gupta, R. K.

2017-11-01

The modeling of human body biomechanics resulting from blast exposure poses great challenges because of the complex geometry and the substantial material heterogeneity. We developed a detailed human body finite element model representing both the geometry and the materials realistically. The model includes the detailed head (face, skull, brain and spinal cord), the neck, the skeleton, air cavities (lungs) and the tissues. Hence, it can be used to properly model the stress wave propagation in the human body subjected to blast loading. The blast loading on the human was generated from a simulated C4 explosion. We used the highly scalable solvers in the multi-physics code CoBi for both the blast simulation and the human body biomechanics. The meshes generated for these simulations are of good quality so that relatively large time-step sizes can be used without resorting to artificial time scaling treatments. The coupled gas dynamics and biomechanics solutions were validated against the shock tube test data. The human body models were used to conduct parametric simulations to find the biomechanical response and the brain injury mechanism due to blasts impacting the human body. Under the same blast loading condition, we showed the importance of inclusion of the whole body.

Comparative analyses of the neuron numbers and volumes of the amygdaloid complex in old and new world primates.

PubMed

Carlo, C N; Stefanacci, L; Semendeferi, K; Stevens, C F

2010-04-15

The amygdaloid complex (AC), a key component of the limbic system, is a brain region critical for the detection and interpretation of emotionally salient information. Therefore, changes in its structure and function are likely to provide correlates of mood and emotion disorders, diseases that afflict a large portion of the human population. Previous gross comparisons of the AC in control and diseased individuals have, however, mainly failed to discover these expected correlations with diseases. We have characterized AC nuclei in different nonhuman primate species to establish a baseline for more refined comparisons between the normal and the diseased amygdala. AC nuclei volume and neuron number in 19 subdivisions are reported from 13 Old and New World primate brains, spanning five primate species, and compared with corresponding data from humans. Analysis of the four largest AC nuclei revealed that volume and neuron number of one component, the central nucleus, has a negative allometric relationship with total amygdala volume and neuron number, which is in contrast with the isometric relationship found in the other AC nuclei (for both neuron number and volume). Neuron density decreases across all four nuclei according to a single power law with an exponent of about minus one-half. Because we have included quantitative comparisons with great apes and humans, our conclusions apply to human brains, and our scaling laws can potentially be used to study the anatomical correlates of the amygdala in disorders involving pathological emotion processing. (c) 2009 Wiley-Liss, Inc.

Physical biology of human brain development.

PubMed

Budday, Silvia; Steinmann, Paul; Kuhl, Ellen

2015-01-01

Neurodevelopment is a complex, dynamic process that involves a precisely orchestrated sequence of genetic, environmental, biochemical, and physical events. Developmental biology and genetics have shaped our understanding of the molecular and cellular mechanisms during neurodevelopment. Recent studies suggest that physical forces play a central role in translating these cellular mechanisms into the complex surface morphology of the human brain. However, the precise impact of neuronal differentiation, migration, and connection on the physical forces during cortical folding remains unknown. Here we review the cellular mechanisms of neurodevelopment with a view toward surface morphogenesis, pattern selection, and evolution of shape. We revisit cortical folding as the instability problem of constrained differential growth in a multi-layered system. To identify the contributing factors of differential growth, we map out the timeline of neurodevelopment in humans and highlight the cellular events associated with extreme radial and tangential expansion. We demonstrate how computational modeling of differential growth can bridge the scales-from phenomena on the cellular level toward form and function on the organ level-to make quantitative, personalized predictions. Physics-based models can quantify cortical stresses, identify critical folding conditions, rationalize pattern selection, and predict gyral wavelengths and gyrification indices. We illustrate that physical forces can explain cortical malformations as emergent properties of developmental disorders. Combining biology and physics holds promise to advance our understanding of human brain development and enable early diagnostics of cortical malformations with the ultimate goal to improve treatment of neurodevelopmental disorders including epilepsy, autism spectrum disorders, and schizophrenia.

Fast assembling of neuron fragments in serial 3D sections.

PubMed

Chen, Hanbo; Iascone, Daniel Maxim; da Costa, Nuno Maçarico; Lein, Ed S; Liu, Tianming; Peng, Hanchuan

2017-09-01

Reconstructing neurons from 3D image-stacks of serial sections of thick brain tissue is very time-consuming and often becomes a bottleneck in high-throughput brain mapping projects. We developed NeuronStitcher, a software suite for stitching non-overlapping neuron fragments reconstructed in serial 3D image sections. With its efficient algorithm and user-friendly interface, NeuronStitcher has been used successfully to reconstruct very large and complex human and mouse neurons.

Control of cognition and adaptive behavior by the GLP/G9a epigenetic suppressor complex

PubMed Central

Schaefer, Anne; Sampath, Srihari C.; Intrator, Adam; Min, Alice; Gertler, Tracy S.; Surmeier, D. James; Tarakhovsky, Alexander; Greengard, Paul

2009-01-01

SUMMARY The genetic basis of cognition and behavioral adaptation to the environment remains poorly understood. Here we demonstrate that the histone methyltransferase complex GLP/G9a controls cognition and adaptive responses in a region-specific fashion in the adult brain. Using conditional mutagenesis in mice, we show that postnatal, neuron-specific deficiency of GLP/G9a leads to de-repression of numerous non-neuronal and neuron progenitor genes in adult neurons. This transcriptional alteration is associated with complex behavioral abnormalities, including defects in learning, motivation and environmental adaptation. The behavioral changes triggered by GLP/G9a deficiency are similar to key symptoms of the human 9q34 mental retardation syndrome that is associated with structural alterations of the GLP gene. The likely causal role of GLP/G9a in mental retardation in mice and humans suggests a key role for the GLP/G9a controlled histone H3K9 di-methylation in regulation of brain function through maintenance of the transcriptional homeostasis in adult neurons. PMID:20005824

Redox proteomics and the dynamic molecular landscape of the aging brain.

PubMed

Perluigi, Marzia; Swomley, Aaron M; Butterfield, D Allan

2014-01-01

It is well established that the risk to develop neurodegenerative disorders increases with chronological aging. Accumulating studies contributed to characterize the age-dependent changes either at gene and protein expression level which, taken together, show that aging of the human brain results from the combination of the normal decline of multiple biological functions with environmental factors that contribute to defining disease risk of late-life brain disorders. Finding the "way out" of the labyrinth of such complex molecular interactions may help to fill the gap between "normal" brain aging and development of age-dependent diseases. To this purpose, proteomics studies are a powerful tool to better understand where to set the boundary line of healthy aging and age-related disease by analyzing the variation of protein expression levels and the major post translational modifications that determine "protein" physio/pathological fate. Increasing attention has been focused on oxidative modifications due to the crucial role of oxidative stress in aging, in addition to the fact that this type of modification is irreversible and may alter protein function. Redox proteomics studies contributed to decipher the complexity of brain aging by identifying the proteins that were increasingly oxidized and eventually dysfunctional as a function of age. The purpose of this review is to summarize the most important findings obtained by applying proteomics approaches to murine models of aging with also a brief overview of some human studies, in particular those related to dementia. Copyright © 2014. Published by Elsevier B.V.

Granular computing with multiple granular layers for brain big data processing.

PubMed

Wang, Guoyin; Xu, Ji

2014-12-01

Big data is the term for a collection of datasets so huge and complex that it becomes difficult to be processed using on-hand theoretical models and technique tools. Brain big data is one of the most typical, important big data collected using powerful equipments of functional magnetic resonance imaging, multichannel electroencephalography, magnetoencephalography, Positron emission tomography, near infrared spectroscopic imaging, as well as other various devices. Granular computing with multiple granular layers, referred to as multi-granular computing (MGrC) for short hereafter, is an emerging computing paradigm of information processing, which simulates the multi-granular intelligent thinking model of human brain. It concerns the processing of complex information entities called information granules, which arise in the process of data abstraction and derivation of information and even knowledge from data. This paper analyzes three basic mechanisms of MGrC, namely granularity optimization, granularity conversion, and multi-granularity joint computation, and discusses the potential of introducing MGrC into intelligent processing of brain big data.

View-Independent Working Memory Representations of Artificial Shapes in Prefrontal and Posterior Regions of the Human Brain.

PubMed

Christophel, Thomas B; Allefeld, Carsten; Endisch, Christian; Haynes, John-Dylan

2018-06-01

Traditional views of visual working memory postulate that memorized contents are stored in dorsolateral prefrontal cortex using an adaptive and flexible code. In contrast, recent studies proposed that contents are maintained by posterior brain areas using codes akin to perceptual representations. An important question is whether this reflects a difference in the level of abstraction between posterior and prefrontal representations. Here, we investigated whether neural representations of visual working memory contents are view-independent, as indicated by rotation-invariance. Using functional magnetic resonance imaging and multivariate pattern analyses, we show that when subjects memorize complex shapes, both posterior and frontal brain regions maintain the memorized contents using a rotation-invariant code. Importantly, we found the representations in frontal cortex to be localized to the frontal eye fields rather than dorsolateral prefrontal cortices. Thus, our results give evidence for the view-independent storage of complex shapes in distributed representations across posterior and frontal brain regions.

The Potential of Using Brain Images for Authentication

PubMed Central

Zhou, Zongtan; Shen, Hui; Hu, Dewen

2014-01-01

Biometric recognition (also known as biometrics) refers to the automated recognition of individuals based on their biological or behavioral traits. Examples of biometric traits include fingerprint, palmprint, iris, and face. The brain is the most important and complex organ in the human body. Can it be used as a biometric trait? In this study, we analyze the uniqueness of the brain and try to use the brain for identity authentication. The proposed brain-based verification system operates in two stages: gray matter extraction and gray matter matching. A modified brain segmentation algorithm is implemented for extracting gray matter from an input brain image. Then, an alignment-based matching algorithm is developed for brain matching. Experimental results on two data sets show that the proposed brain recognition system meets the high accuracy requirement of identity authentication. Though currently the acquisition of the brain is still time consuming and expensive, brain images are highly unique and have the potential possibility for authentication in view of pattern recognition. PMID:25126604

The potential of using brain images for authentication.

PubMed

Chen, Fanglin; Zhou, Zongtan; Shen, Hui; Hu, Dewen

2014-01-01

Biometric recognition (also known as biometrics) refers to the automated recognition of individuals based on their biological or behavioral traits. Examples of biometric traits include fingerprint, palmprint, iris, and face. The brain is the most important and complex organ in the human body. Can it be used as a biometric trait? In this study, we analyze the uniqueness of the brain and try to use the brain for identity authentication. The proposed brain-based verification system operates in two stages: gray matter extraction and gray matter matching. A modified brain segmentation algorithm is implemented for extracting gray matter from an input brain image. Then, an alignment-based matching algorithm is developed for brain matching. Experimental results on two data sets show that the proposed brain recognition system meets the high accuracy requirement of identity authentication. Though currently the acquisition of the brain is still time consuming and expensive, brain images are highly unique and have the potential possibility for authentication in view of pattern recognition.

Deficits of long-term memory in ecstasy users are related to cognitive complexity of the task.

PubMed

Brown, John; McKone, Elinor; Ward, Jeff

2010-03-01

Despite animal evidence that methylenedioxymethamphetamine (ecstasy) causes lasting damage in brain regions related to long-term memory, results regarding human memory performance have been variable. This variability may reflect the cognitive complexity of the memory tasks. However, previous studies have tested only a limited range of cognitive complexity. Furthermore, comparisons across different studies are made difficult by regional variations in ecstasy composition and patterns of use. The objective of this study is to evaluate ecstasy-related deficits in human verbal memory over a wide range of cognitive complexity using subjects drawn from a single geographical population. Ecstasy users were compared to non-drug using controls on verbal tasks with low cognitive complexity (stem completion), moderate cognitive complexity (stem-cued recall and word list learning) and high cognitive complexity (California Verbal Learning Test, Verbal Paired Associates and a novel Verbal Triplet Associates test). Where significant differences were found, both groups were also compared to cannabis users. More cognitively complex memory tasks were associated with clearer ecstasy-related deficits than low complexity tasks. In the most cognitively demanding task, ecstasy-related deficits remained even after multiple learning opportunities, whereas the performance of cannabis users approached that of non-drug using controls. Ecstasy users also had weaker deliberate strategy use than both non-drug and cannabis controls. Results were consistent with the proposal that ecstasy-related memory deficits are more reliable on tasks with greater cognitive complexity. This could arise either because such tasks require a greater contribution from the frontal lobe or because they require greater interaction between multiple brain regions.

Towards Tunable Consensus Clustering for Studying Functional Brain Connectivity During Affective Processing.

PubMed

Liu, Chao; Abu-Jamous, Basel; Brattico, Elvira; Nandi, Asoke K

2017-03-01

In the past decades, neuroimaging of humans has gained a position of status within neuroscience, and data-driven approaches and functional connectivity analyses of functional magnetic resonance imaging (fMRI) data are increasingly favored to depict the complex architecture of human brains. However, the reliability of these findings is jeopardized by too many analysis methods and sometimes too few samples used, which leads to discord among researchers. We propose a tunable consensus clustering paradigm that aims at overcoming the clustering methods selection problem as well as reliability issues in neuroimaging by means of first applying several analysis methods (three in this study) on multiple datasets and then integrating the clustering results. To validate the method, we applied it to a complex fMRI experiment involving affective processing of hundreds of music clips. We found that brain structures related to visual, reward, and auditory processing have intrinsic spatial patterns of coherent neuroactivity during affective processing. The comparisons between the results obtained from our method and those from each individual clustering algorithm demonstrate that our paradigm has notable advantages over traditional single clustering algorithms in being able to evidence robust connectivity patterns even with complex neuroimaging data involving a variety of stimuli and affective evaluations of them. The consensus clustering method is implemented in the R package "UNCLES" available on http://cran.r-project.org/web/packages/UNCLES/index.html .

Human hippocampus associates information in memory

PubMed Central

Henke, Katharina; Weber, Bruno; Kneifel, Stefan; Wieser, Heinz Gregor; Buck, Alfred

1999-01-01

The hippocampal formation, one of the most complex and vulnerable brain structures, is recognized as a crucial brain area subserving human long-term memory. Yet, its specific functions in memory are controversial. Recent experimental results suggest that the hippocampal contribution to human memory is limited to episodic memory, novelty detection, semantic (deep) processing of information, and spatial memory. We measured the regional cerebral blood flow by positron-emission tomography while healthy volunteers learned pairs of words with different learning strategies. These led to different forms of learning, allowing us to test the degree to which they challenge hippocampal function. Neither novelty detection nor depth of processing activated the hippocampal formation as much as semantically associating the primarily unrelated words in memory. This is compelling evidence for another function of the human hippocampal formation in memory: establishing semantic associations. PMID:10318979

The neural bases for valuing social equality.

PubMed

Aoki, Ryuta; Yomogida, Yukihito; Matsumoto, Kenji

2015-01-01

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

Behavioural and neurophysiological evidence for face identity and face emotion processing in animals

PubMed Central

Tate, Andrew J; Fischer, Hanno; Leigh, Andrea E; Kendrick, Keith M

2006-01-01

Visual cues from faces provide important social information relating to individual identity, sexual attraction and emotional state. Behavioural and neurophysiological studies on both monkeys and sheep have shown that specialized skills and neural systems for processing these complex cues to guide behaviour have evolved in a number of mammals and are not present exclusively in humans. Indeed, there are remarkable similarities in the ways that faces are processed by the brain in humans and other mammalian species. While human studies with brain imaging and gross neurophysiological recording approaches have revealed global aspects of the face-processing network, they cannot investigate how information is encoded by specific neural networks. Single neuron electrophysiological recording approaches in both monkeys and sheep have, however, provided some insights into the neural encoding principles involved and, particularly, the presence of a remarkable degree of high-level encoding even at the level of a specific face. Recent developments that allow simultaneous recordings to be made from many hundreds of individual neurons are also beginning to reveal evidence for global aspects of a population-based code. This review will summarize what we have learned so far from these animal-based studies about the way the mammalian brain processes the faces and the emotions they can communicate, as well as associated capacities such as how identity and emotion cues are dissociated and how face imagery might be generated. It will also try to highlight what questions and advances in knowledge still challenge us in order to provide a complete understanding of just how brain networks perform this complex and important social recognition task. PMID:17118930

High-definition fiber tractography of the human brain: neuroanatomical validation and neurosurgical applications.

PubMed

Fernandez-Miranda, Juan C; Pathak, Sudhir; Engh, Johnathan; Jarbo, Kevin; Verstynen, Timothy; Yeh, Fang-Cheng; Wang, Yibao; Mintz, Arlan; Boada, Fernando; Schneider, Walter; Friedlander, Robert

2012-08-01

High-definition fiber tracking (HDFT) is a novel combination of processing, reconstruction, and tractography methods that can track white matter fibers from cortex, through complex fiber crossings, to cortical and subcortical targets with subvoxel resolution. To perform neuroanatomical validation of HDFT and to investigate its neurosurgical applications. Six neurologically healthy adults and 36 patients with brain lesions were studied. Diffusion spectrum imaging data were reconstructed with a Generalized Q-Ball Imaging approach. Fiber dissection studies were performed in 20 human brains, and selected dissection results were compared with tractography. HDFT provides accurate replication of known neuroanatomical features such as the gyral and sulcal folding patterns, the characteristic shape of the claustrum, the segmentation of the thalamic nuclei, the decussation of the superior cerebellar peduncle, the multiple fiber crossing at the centrum semiovale, the complex angulation of the optic radiations, the terminal arborization of the arcuate tract, and the cortical segmentation of the dorsal Broca area. From a clinical perspective, we show that HDFT provides accurate structural connectivity studies in patients with intracerebral lesions, allowing qualitative and quantitative white matter damage assessment, aiding in understanding lesional patterns of white matter structural injury, and facilitating innovative neurosurgical applications. High-grade gliomas produce significant disruption of fibers, and low-grade gliomas cause fiber displacement. Cavernomas cause both displacement and disruption of fibers. Our HDFT approach provides an accurate reconstruction of white matter fiber tracts with unprecedented detail in both the normal and pathological human brain. Further studies to validate the clinical findings are needed.

Behavioural and neurophysiological evidence for face identity and face emotion processing in animals.

PubMed

Tate, Andrew J; Fischer, Hanno; Leigh, Andrea E; Kendrick, Keith M

2006-12-29

Visual cues from faces provide important social information relating to individual identity, sexual attraction and emotional state. Behavioural and neurophysiological studies on both monkeys and sheep have shown that specialized skills and neural systems for processing these complex cues to guide behaviour have evolved in a number of mammals and are not present exclusively in humans. Indeed, there are remarkable similarities in the ways that faces are processed by the brain in humans and other mammalian species. While human studies with brain imaging and gross neurophysiological recording approaches have revealed global aspects of the face-processing network, they cannot investigate how information is encoded by specific neural networks. Single neuron electrophysiological recording approaches in both monkeys and sheep have, however, provided some insights into the neural encoding principles involved and, particularly, the presence of a remarkable degree of high-level encoding even at the level of a specific face. Recent developments that allow simultaneous recordings to be made from many hundreds of individual neurons are also beginning to reveal evidence for global aspects of a population-based code. This review will summarize what we have learned so far from these animal-based studies about the way the mammalian brain processes the faces and the emotions they can communicate, as well as associated capacities such as how identity and emotion cues are dissociated and how face imagery might be generated. It will also try to highlight what questions and advances in knowledge still challenge us in order to provide a complete understanding of just how brain networks perform this complex and important social recognition task.

Multimodal communication in animals, humans and robots: an introduction to perspectives in brain-inspired informatics.

PubMed

Wermter, S; Page, M; Knowles, M; Gallese, V; Pulvermüller, F; Taylor, J

2009-03-01

Recent years have seen convergence in research on brain mechanisms and neurocomputational approaches, culminating in the creation of a new generation of robots whose artificial "brains" respect neuroscience principles and whose "cognitive" systems venture into higher cognitive domains such as planning and action sequencing, complex object and concept processing, and language. The present article gives an overview of selected projects in this general multidisciplinary field. The work reviewed centres on research funded by the EU in the context of the New and Emergent Science and Technology, NEST, funding scheme highlighting the topic "What it means to be human". Examples of such projects include learning by imitation (Edici project), examining the origin of human rule-based reasoning (Far), studying the neural origins of language (Neurocom), exploring the evolutionary origins of the human mind (Pkb140404), researching into verbal and non-verbal communication (Refcom), using and interpreting signs (Sedsu), characterising human language by structural complexity (Chlasc), and representing abstract concepts (Abstract). Each of the communication-centred research projects revealed individual insights; however, there had been little overall analysis of results and hypotheses. In the Specific Support Action Nestcom, we proposed to analyse some NEST projects focusing on the central question "What it means to communicate" and to review, understand and integrate the results of previous communication-related research, in order to develop and communicate multimodal experimental hypotheses for investigation by future projects. The present special issue includes a range of papers on the interplay between neuroinformatics, brain science and robotics in the general area of higher cognitive functions and multimodal communication. These papers extend talks given at the NESTCOM workshops, at ICANN (http://www.his.sunderland.ac.uk/nestcom/workshop/icann.html) in Porto and at the first meeting of the Federation of the European Societies of Neuropsychology in Edinburgh in 2008 (http://www.his.sunderland.ac.uk/nestcom/workshop/esn.html). We hope that the collection will give a vivid insight into current trends in the field.

Effects of tramadol, clonazepam, and their combination on brain mitochondrial complexes.

PubMed

Mohamed, Tarek Mostafa; Ghaffar, Hamdy M Abdel; El Husseiny, Rabee M R

2015-12-01

The present study is an unsubstantiated qualitative assessment of the abused drugs-tramadol and clonazepam. The aim of this study is to evaluate whether the effects of tramadol, clonazepam, and their combination on mitochondrial electron transport chain (ETC) complexes were influential at therapeutic or at progressively increasing doses. The study comprised of a total of 70 healthy male rats, aged 3 months. According to the drug intake regimen, animals were divided into seven groups: control, tramadol therapeutic, clonazepam therapeutic, combination therapeutic, tramadol abuse, clonazepam abuse, and combination abuse group. At the end of the experiment, brain mitochondrial ETC complexes (I, II, III, and IV) were evaluated. Histopathological examinations were also performed on brain tissues. The results showed that groups that received tramadol (therapeutic and abuse) suffered from weight loss. Tramadol abuse group and combination abuse group showed significant decrease in the activities of I, III, and IV complexes but not in the activity of complex II. In conclusion, tramadol but not clonazepam has been found to partially inhibit the activities of respiratory chain complexes I, III, and IV but not the activity of complex II and such inhibition occurred only at doses that exceeded the maximum recommended adult human daily therapeutic doses. This result explains the clinical and histopathological effects of tramadol, such as seizures and red neurons (marker for apoptosis), respectively. © The Author(s) 2012.

Regulatory consequences of neuronal ELAV-like protein binding to coding and non-coding RNAs in human brain

PubMed Central

Scheckel, Claudia; Drapeau, Elodie; Frias, Maria A; Park, Christopher Y; Fak, John; Zucker-Scharff, Ilana; Kou, Yan; Haroutunian, Vahram; Ma'ayan, Avi

2016-01-01

Neuronal ELAV-like (nELAVL) RNA binding proteins have been linked to numerous neurological disorders. We performed crosslinking-immunoprecipitation and RNAseq on human brain, and identified nELAVL binding sites on 8681 transcripts. Using knockout mice and RNAi in human neuroblastoma cells, we showed that nELAVL intronic and 3' UTR binding regulates human RNA splicing and abundance. We validated hundreds of nELAVL targets among which were important neuronal and disease-associated transcripts, including Alzheimer's disease (AD) transcripts. We therefore investigated RNA regulation in AD brain, and observed differential splicing of 150 transcripts, which in some cases correlated with differential nELAVL binding. Unexpectedly, the most significant change of nELAVL binding was evident on non-coding Y RNAs. nELAVL/Y RNA complexes were specifically remodeled in AD and after acute UV stress in neuroblastoma cells. We propose that the increased nELAVL/Y RNA association during stress may lead to nELAVL sequestration, redistribution of nELAVL target binding, and altered neuronal RNA splicing. DOI: http://dx.doi.org/10.7554/eLife.10421.001 PMID:26894958

Intra-Blood-Brain Barrier Synthesis of Human Immunodeficiency Virus Antigen and Antibody in Humans and Chimpanzees

NASA Astrophysics Data System (ADS)

Goudsmit, Jaap; Epstein, Leon G.; Paul, Deborah A.; van der Helm, Hayo J.; Dawson, George J.; Asher, David M.; Yanagihara, Richard; Wolff, Axel V.; Gibbs, Clarence J.; Carleton Gajdusek, D.

1987-06-01

The presence of human immunodeficiency virus (HIV) antigens in cerebrospinal fluid (CSF) was associated with progressive encephalopathy in adult and pediatric patients with acquired immunodeficiency syndrome (AIDS). HIV antigen was detected in CSF from 6 of 7 AIDS patients with progressive encephalopathy. By contrast, HIV antigen, whether free or complexed, was detected in CSF from only 1 of 18 HIV antibody seropositive patients without progressive encephalopathy and from 0 of 8 experimentally infected chimpanzees without clinical signs. Intra-blood-brain barrier synthesis of HIV-specific antibody was demonstrated in the majority of patients with AIDS (9/12) or at risk for AIDS (8/13) as well as in the experimentally infected chimpanzees, indicating HIV-specific B-cell reactivity in the brain without apparent neurological signs. In 6 of 11 patients with HIV infection, antibodies synthesized in the central nervous system were directed against HIV envelope proteins. Active viral expression appears to be necessary for both the immunodeficiency and progressive encephalopathy associated with HIV infection.

Protecting peer review: correspondence chronology and ethical analysis regarding Logothetis vs. Shmuel and Leopold.

PubMed

Fox, Peter T; Bullmore, Ed; Bandettini, Peter A; Lancaster, Jack L

2009-02-01

Editors of scientific journals are ethically bound to provide a fair and impartial peer-review process and to protect the rights of contributing authors to publish research results. If, however, a dispute arises among investigators regarding data ownership and the right to publish, the ethical responsibilities of journal editors become more complex. The editors of Human Brain Mapping recently had the unusual experience of learning of an ongoing dispute regarding data-access rights pertaining to a manuscript already accepted for publication. Herein the editors describe the nature of the dispute, the steps taken to explore and resolve the conflict, and discuss the ethical principles that govern such circumstances. Drawing on this experience and with the goal of avoiding future controversies, the editors have formulated a Data Rights Policy and a Data Rights Procedure for Human Brain Mapping. Human Brain Mapping adopts this policy effective immediately and respectfully suggests that other journals consider adopting this or similar policies.

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.

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.

Network integrity of the parental brain in infancy supports the development of children's social competencies.

PubMed

Abraham, Eyal; Hendler, Talma; Zagoory-Sharon, Orna; Feldman, Ruth

2016-11-01

The cross-generational transmission of mammalian sociality, initiated by the parent's postpartum brain plasticity and species-typical behavior that buttress offspring's socialization, has not been studied in humans. In this longitudinal study, we measured brain response of 45 primary-caregiving parents to their infant's stimuli, observed parent-infant interactions, and assayed parental oxytocin (OT). Intra- and inter-network connectivity were computed in three main networks of the human parental brain: core limbic, embodied simulation and mentalizing. During preschool, two key child social competencies were observed: emotion regulation and socialization. Parent's network integrity in infancy predicted preschoolers' social outcomes, with subcortical and cortical network integrity foreshadowing simple evolutionary-based regulatory tactics vs complex self-regulatory strategies and advanced socialization. Parent-infant synchrony mediated the links between connectivity of the parent's embodied simulation network and preschoolers' ability to use cognitive/executive emotion regulation strategies, highlighting the inherently dyadic nature of this network and its long-term effects on tuning young to social life. Parent's inter-network core limbic-embodied simulation connectivity predicted children's OT as moderated by parental OT. Findings challenge solipsistic neuroscience perspectives by demonstrating how the parent-offspring interface enables the brain of one human to profoundly impact long-term adaptation of another. © The Author (2016). Published by Oxford University Press.

Cell fusion in the brain: two cells forward, one cell back.

PubMed

Kemp, Kevin; Wilkins, Alastair; Scolding, Neil

2014-11-01

Adult stem cell populations, notably those which reside in the bone marrow, have been shown to contribute to several neuronal cell types in the rodent and human brain. The observation that circulating bone marrow cells can migrate into the central nervous system and fuse with, in particular, cerebellar Purkinje cells has suggested, at least in part, a potential mechanism behind this process. Experimentally, the incidence of cell fusion in the brain is enhanced with age, radiation exposure, inflammation, chemotherapeutic drugs and even selective damage to the neurons themselves. The presence of cell fusion, shown by detection of increased bi-nucleated neurons, has also been described in a variety of human central nervous system diseases, including both multiple sclerosis and Alzheimer's disease. Accumulating evidence is therefore raising new questions into the biological significance of cell fusion, with the possibility that it represents an important means of cell-mediated neuroprotection or rescue of highly complex neurons that cannot be replaced in adult life. Here, we discuss the evidence behind this phenomenon in the rodent and human brain, with a focus on the subsequent research investigating the physiological mechanisms of cell fusion underlying this process. We also highlight how these studies offer new insights into endogenous neuronal repair, opening new exciting avenues for potential therapeutic interventions against neurodegeneration and brain injury.

Network integrity of the parental brain in infancy supports the development of children’s social competencies

PubMed Central

Abraham, Eyal; Hendler, Talma; Zagoory-Sharon, Orna

2016-01-01

The cross-generational transmission of mammalian sociality, initiated by the parent’s postpartum brain plasticity and species-typical behavior that buttress offspring’s socialization, has not been studied in humans. In this longitudinal study, we measured brain response of 45 primary-caregiving parents to their infant’s stimuli, observed parent–infant interactions, and assayed parental oxytocin (OT). Intra- and inter-network connectivity were computed in three main networks of the human parental brain: core limbic, embodied simulation and mentalizing. During preschool, two key child social competencies were observed: emotion regulation and socialization. Parent’s network integrity in infancy predicted preschoolers’ social outcomes, with subcortical and cortical network integrity foreshadowing simple evolutionary-based regulatory tactics vs complex self-regulatory strategies and advanced socialization. Parent–infant synchrony mediated the links between connectivity of the parent’s embodied simulation network and preschoolers' ability to use cognitive/executive emotion regulation strategies, highlighting the inherently dyadic nature of this network and its long-term effects on tuning young to social life. Parent’s inter-network core limbic-embodied simulation connectivity predicted children’s OT as moderated by parental OT. Findings challenge solipsistic neuroscience perspectives by demonstrating how the parent–offspring interface enables the brain of one human to profoundly impact long-term adaptation of another. PMID:27369068

Extracting morphologies from third harmonic generation images of structurally normal human brain tissue.

PubMed

Zhang, Zhiqing; Kuzmin, Nikolay V; Groot, Marie Louise; de Munck, Jan C

2017-06-01

The morphologies contained in 3D third harmonic generation (THG) images of human brain tissue can report on the pathological state of the tissue. However, the complexity of THG brain images makes the usage of modern image processing tools, especially those of image filtering, segmentation and validation, to extract this information challenging. We developed a salient edge-enhancing model of anisotropic diffusion for image filtering, based on higher order statistics. We split the intrinsic 3-phase segmentation problem into two 2-phase segmentation problems, each of which we solved with a dedicated model, active contour weighted by prior extreme. We applied the novel proposed algorithms to THG images of structurally normal ex-vivo human brain tissue, revealing key tissue components-brain cells, microvessels and neuropil, enabling statistical characterization of these components. Comprehensive comparison to manually delineated ground truth validated the proposed algorithms. Quantitative comparison to second harmonic generation/auto-fluorescence images, acquired simultaneously from the same tissue area, confirmed the correctness of the main THG features detected. The software and test datasets are available from the authors. z.zhang@vu.nl. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Exponential evolution: implications for intelligent extraterrestrial life.

PubMed

Russell, D A

1983-01-01

Some measures of biologic complexity, including maximal levels of brain development, are exponential functions of time through intervals of 10(6) to 10(9) yrs. Biological interactions apparently stimulate evolution but physical conditions determine the time required to achieve a given level of complexity. Trends in brain evolution suggest that other organisms could attain human levels within approximately 10(7) yrs. The number (N) and longevity (L) terms in appropriate modifications of the Drake Equation, together with trends in the evolution of biological complexity on Earth, could provide rough estimates of the prevalence of life forms at specified levels of complexity within the Galaxy. If life occurs throughout the cosmos, exponential evolutionary processes imply that higher intelligence will soon (10(9) yrs) become more prevalent than it now is. Changes in the physical universe become less rapid as time increases from the Big Bang. Changes in biological complexity may be most rapid at such later times. This lends a unique and symmetrical importance to early and late universal times.

Genetic Markers of Human Evolution Are Enriched in Schizophrenia.

PubMed

Srinivasan, Saurabh; Bettella, Francesco; Mattingsdal, Morten; Wang, Yunpeng; Witoelar, Aree; Schork, Andrew J; Thompson, Wesley K; Zuber, Verena; Winsvold, Bendik S; Zwart, John-Anker; Collier, David A; Desikan, Rahul S; Melle, Ingrid; Werge, Thomas; Dale, Anders M; Djurovic, Srdjan; Andreassen, Ole A

2016-08-15

Why schizophrenia has accompanied humans throughout our history despite its negative effect on fitness remains an evolutionary enigma. It is proposed that schizophrenia is a by-product of the complex evolution of the human brain and a compromise for humans' language, creative thinking, and cognitive abilities. We analyzed recent large genome-wide association studies of schizophrenia and a range of other human phenotypes (anthropometric measures, cardiovascular disease risk factors, immune-mediated diseases) using a statistical framework that draws on polygenic architecture and ancillary information on genetic variants. We used information from the evolutionary proxy measure called the Neanderthal selective sweep (NSS) score. Gene loci associated with schizophrenia are significantly (p = 7.30 × 10(-9)) more prevalent in genomic regions that are likely to have undergone recent positive selection in humans (i.e., with a low NSS score). Variants in brain-related genes with a low NSS score confer significantly higher susceptibility than variants in other brain-related genes. The enrichment is strongest for schizophrenia, but we cannot rule out enrichment for other phenotypes. The false discovery rate conditional on the evolutionary proxy points to 27 candidate schizophrenia susceptibility loci, 12 of which are associated with schizophrenia and other psychiatric disorders or linked to brain development. Our results suggest that there is a polygenic overlap between schizophrenia and NSS score, a marker of human evolution, which is in line with the hypothesis that the persistence of schizophrenia is related to the evolutionary process of becoming human. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Fluid and flexible minds: Intelligence reflects synchrony in the brain’s intrinsic network architecture

PubMed Central

Ferguson, Michael A.; Anderson, Jeffrey S.; Spreng, R. Nathan

2017-01-01

Human intelligence has been conceptualized as a complex system of dissociable cognitive processes, yet studies investigating the neural basis of intelligence have typically emphasized the contributions of discrete brain regions or, more recently, of specific networks of functionally connected regions. Here we take a broader, systems perspective in order to investigate whether intelligence is an emergent property of synchrony within the brain’s intrinsic network architecture. Using a large sample of resting-state fMRI and cognitive data (n = 830), we report that the synchrony of functional interactions within and across distributed brain networks reliably predicts fluid and flexible intellectual functioning. By adopting a whole-brain, systems-level approach, we were able to reliably predict individual differences in human intelligence by characterizing features of the brain’s intrinsic network architecture. These findings hold promise for the eventual development of neural markers to predict changes in intellectual function that are associated with neurodevelopment, normal aging, and brain disease.

The evolutionary dynamics of language.

PubMed

Steels, Luc; Szathmáry, Eörs

2018-02-01

The well-established framework of evolutionary dynamics can be applied to the fascinating open problems how human brains are able to acquire and adapt language and how languages change in a population. Schemas for handling grammatical constructions are the replicating unit. They emerge and multiply with variation in the brains of individuals and undergo selection based on their contribution to needed expressive power, communicative success and the reduction of cognitive effort. Adopting this perspective has two major benefits. (i) It makes a bridge to neurobiological models of the brain that have also adopted an evolutionary dynamics point of view, thus opening a new horizon for studying how human brains achieve the remarkably complex competence for language. And (ii) it suggests a new foundation for studying cultural language change as an evolutionary dynamics process. The paper sketches this novel perspective, provides references to empirical data and computational experiments, and points to open problems. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

The neuroscience of observing consciousness & mirror neurons in therapeutic hypnosis.

PubMed

Rossi, Ernest L; Rossi, Kathryn L

2006-04-01

Neuroscience documents the activity of "mirror neurons" in the human brain as a mechanism whereby we experience empathy and recognize the intentions of others by observing their behavior and automatically matching their brain activity. This neural basis of empathy finds support in research on dysfunctions in the mirror systems of humans with autism and fMRI research on normal subjects designed to assess intentionality, emotions, and complex cognition. Such empathy research now appears to be consistent with the historical and research literature on hypnotic induction, rapport, and many of the classical phenomena of suggestion. A preliminary outline of how mirror neurons may function as a rapport zone mediating between observing consciousness, the gene expression/protein synthesis cycle, and brain plasticity in therapeutic hypnosis and psychosomatic medicine is proposed. Brain plasticity is generalized in the theory, research, and practice of utilizing mirror neurons as an explanatory framework in developing and training new skill sets for facilitating an activity-dependent approach to creative problem solving, mind-body healing, and rehabilitation with therapeutic hypnosis.

Performance analysis of unsupervised optimal fuzzy clustering algorithm for MRI brain tumor segmentation.

PubMed

Blessy, S A Praylin Selva; Sulochana, C Helen

2015-01-01

Segmentation of brain tumor from Magnetic Resonance Imaging (MRI) becomes very complicated due to the structural complexities of human brain and the presence of intensity inhomogeneities. To propose a method that effectively segments brain tumor from MR images and to evaluate the performance of unsupervised optimal fuzzy clustering (UOFC) algorithm for segmentation of brain tumor from MR images. Segmentation is done by preprocessing the MR image to standardize intensity inhomogeneities followed by feature extraction, feature fusion and clustering. Different validation measures are used to evaluate the performance of the proposed method using different clustering algorithms. The proposed method using UOFC algorithm produces high sensitivity (96%) and low specificity (4%) compared to other clustering methods. Validation results clearly show that the proposed method with UOFC algorithm effectively segments brain tumor from MR images.

Assessing Relevance of External Cognitive Measures

PubMed Central

Cairó, Osvaldo

2017-01-01

The arrival of modern brain imaging technologies has provided new opportunities for examining the biological essence of human intelligence as well as the relationship between brain size and cognition. Thanks to these advances, we can now state that the relationship between brain size and intelligence has never been well understood. This view is supported by findings showing that cognition is correlated more with brain tissues than sheer brain size. The complexity of cellular and molecular organization of neural connections actually determines the computational capacity of the brain. In this review article, we determine that while genotypes are responsible for defining the theoretical limits of intelligence, what is primarily responsible for determining whether those limits are reached or exceeded is experience (environmental influence). Therefore, we contend that the gene-environment interplay defines the intelligent quotient of an individual. PMID:28270753

Automatic Brain Portion Segmentation From Magnetic Resonance Images of Head Scans Using Gray Scale Transformation and Morphological Operations.

PubMed

Somasundaram, Karuppanagounder; Ezhilarasan, Kamalanathan

2015-01-01

To develop an automatic skull stripping method for magnetic resonance imaging (MRI) of human head scans. The proposed method is based on gray scale transformation and morphological operations. The proposed method has been tested with 20 volumes of normal T1-weighted images taken from Internet Brain Segmentation Repository. Experimental results show that the proposed method gives better results than the popular skull stripping methods Brain Extraction Tool and Brain Surface Extractor. The average value of Jaccard and Dice coefficients are 0.93 and 0.962 respectively. In this article, we have proposed a novel skull stripping method using intensity transformation and morphological operations. This is a low computational complexity method but gives competitive or better results than that of the popular skull stripping methods Brain Surface Extractor and Brain Extraction Tool.

Quantitative complexity analysis in multi-channel intracranial EEG recordings form epilepsy brains

PubMed Central

Liu, Chang-Chia; Pardalos, Panos M.; Chaovalitwongse, W. Art; Shiau, Deng-Shan; Ghacibeh, Georges; Suharitdamrong, Wichai; Sackellares, J. Chris

2008-01-01

Epilepsy is a brain disorder characterized clinically by temporary but recurrent disturbances of brain function that may or may not be associated with destruction or loss of consciousness and abnormal behavior. Human brain is composed of more than 10 to the power 10 neurons, each of which receives electrical impulses known as action potentials from others neurons via synapses and sends electrical impulses via a sing output line to a similar (the axon) number of neurons. When neuronal networks are active, they produced a change in voltage potential, which can be captured by an electroencephalogram (EEG). The EEG recordings represent the time series that match up to neurological activity as a function of time. By analyzing the EEG recordings, we sought to evaluate the degree of underlining dynamical complexity prior to progression of seizure onset. Through the utilization of the dynamical measurements, it is possible to classify the state of the brain according to the underlying dynamical properties of EEG recordings. The results from two patients with temporal lobe epilepsy (TLE), the degree of complexity start converging to lower value prior to the epileptic seizures was observed from epileptic regions as well as non-epileptic regions. The dynamical measurements appear to reflect the changes of EEG’s dynamical structure. We suggest that the nonlinear dynamical analysis can provide a useful information for detecting relative changes in brain dynamics, which cannot be detected by conventional linear analysis. PMID:19079790

Benefits of agomelatine in behavioral, neurochemical and blood brain barrier alterations in prenatal valproic acid induced autism spectrum disorder.

PubMed

Kumar, Hariom; Sharma, B M; Sharma, Bhupesh

2015-12-01

Valproic acid administration during gestational period causes behavior and biochemical deficits similar to those observed in humans with autism spectrum disorder. Although worldwide prevalence of autism spectrum disorder has been increased continuously, therapeutic agents to ameliorate the social impairment are very limited. The present study has been structured to investigate the therapeutic potential of melatonin receptor agonist, agomelatine in prenatal valproic acid (Pre-VPA) induced autism spectrum disorder in animals. Pre-VPA has produced reduction in social interaction (three chamber social behavior apparatus), spontaneous alteration (Y-Maze), exploratory activity (Hole board test), intestinal motility, serotonin levels (prefrontal cortex and ileum) and prefrontal cortex mitochondrial complex activity (complex I, II, IV). Furthermore, Pre-VPA has increased locomotor activity (actophotometer), anxiety, brain oxidative stress (thiobarbituric acid reactive species, glutathione, and catalase), nitrosative stress (nitrite/nitrate), inflammation (brain and ileum myeloperoxidase activity), calcium levels and blood brain barrier leakage in animals. Treatment with agomelatine has significantly attenuated Pre-VPA induced reduction in social interaction, spontaneous alteration, exploratory activity intestinal motility, serotonin levels and prefrontal cortex mitochondrial complex activity. Furthermore, agomelatine also attenuated Pre-VPA induced increase in locomotion, anxiety, brain oxidative stress, nitrosative stress, inflammation, calcium levels and blood brain barrier leakage. It is concluded that, Pre-VPA has induced autism spectrum disorder, which was attenuated by agomelatine. Agomelatine has shown ameliorative effect on behavioral, neurochemical and blood brain barrier alteration in Pre-VPA exposed animals. Thus melatonin receptor agonists may provide beneficial therapeutic strategy for managing autism spectrum disorder. Copyright © 2015 Elsevier Ltd. All rights reserved.

Gaining insight of fetal brain development with diffusion MRI and histology.

PubMed

Huang, Hao; Vasung, Lana

2014-02-01

Human brain is extraordinarily complex and yet its origin is a simple tubular structure. Its development during the fetal period is characterized by a series of accurately organized events which underlie the mechanisms of dramatic structural changes during fetal development. Revealing detailed anatomy at different stages of human fetal brain development provides insight on understanding not only this highly ordered process, but also the neurobiological foundations of cognitive brain disorders such as mental retardation, autism, schizophrenia, bipolar and language impairment. Diffusion tensor imaging (DTI) and histology are complementary tools which are capable of delineating the fetal brain structures at both macroscopic and microscopic levels. In this review, the structural development of the fetal brains has been characterized with DTI and histology. Major components of the fetal brain, including cortical plate, fetal white matter and cerebral wall layer between the ventricle and subplate, have been delineated with DTI and histology. Anisotropic metrics derived from DTI were used to quantify the microstructural changes during the dynamic process of human fetal cortical development and prenatal development of other animal models. Fetal white matter pathways have been traced with DTI-based tractography to reveal growth patterns of individual white matter tracts and corticocortical connectivity. These detailed anatomical accounts of the structural changes during fetal period may provide the clues of detecting developmental and cognitive brain disorders at their early stages. The anatomical information from DTI and histology may also provide reference standards for diagnostic radiology of premature newborns. Copyright © 2013 ISDN. Published by Elsevier Ltd. All rights reserved.

Speech as a breakthrough signaling resource in the cognitive evolution of biological complex adaptive systems.

PubMed

Mattei, Tobias A

2014-12-01

In self-adapting dynamical systems, a significant improvement in the signaling flow among agents constitutes one of the most powerful triggering events for the emergence of new complex behaviors. Ackermann and colleagues' comprehensive phylogenetic analysis of the brain structures involved in acoustic communication provides further evidence of the essential role which speech, as a breakthrough signaling resource, has played in the evolutionary development of human cognition viewed from the standpoint of complex adaptive system analysis.

Structural brain aging and speech production: a surface-based brain morphometry study.

PubMed

Tremblay, Pascale; Deschamps, Isabelle

2016-07-01

While there has been a growing number of studies examining the neurofunctional correlates of speech production over the past decade, the neurostructural correlates of this immensely important human behaviour remain less well understood, despite the fact that previous studies have established links between brain structure and behaviour, including speech and language. In the present study, we thus examined, for the first time, the relationship between surface-based cortical thickness (CT) and three different behavioural indexes of sublexical speech production: response duration, reaction times and articulatory accuracy, in healthy young and older adults during the production of simple and complex meaningless sequences of syllables (e.g., /pa-pa-pa/ vs. /pa-ta-ka/). The results show that each behavioural speech measure was sensitive to the complexity of the sequences, as indicated by slower reaction times, longer response durations and decreased articulatory accuracy in both groups for the complex sequences. Older adults produced longer speech responses, particularly during the production of complex sequence. Unique age-independent and age-dependent relationships between brain structure and each of these behavioural measures were found in several cortical and subcortical regions known for their involvement in speech production, including the bilateral anterior insula, the left primary motor area, the rostral supramarginal gyrus, the right inferior frontal sulcus, the bilateral putamen and caudate, and in some region less typically associated with speech production, such as the posterior cingulate cortex.

Spectral properties of the temporal evolution of brain network structure.

PubMed

Wang, Rong; Zhang, Zhen-Zhen; Ma, Jun; Yang, Yong; Lin, Pan; Wu, Ying

2015-12-01

The temporal evolution properties of the brain network are crucial for complex brain processes. In this paper, we investigate the differences in the dynamic brain network during resting and visual stimulation states in a task-positive subnetwork, task-negative subnetwork, and whole-brain network. The dynamic brain network is first constructed from human functional magnetic resonance imaging data based on the sliding window method, and then the eigenvalues corresponding to the network are calculated. We use eigenvalue analysis to analyze the global properties of eigenvalues and the random matrix theory (RMT) method to measure the local properties. For global properties, the shifting of the eigenvalue distribution and the decrease in the largest eigenvalue are linked to visual stimulation in all networks. For local properties, the short-range correlation in eigenvalues as measured by the nearest neighbor spacing distribution is not always sensitive to visual stimulation. However, the long-range correlation in eigenvalues as evaluated by spectral rigidity and number variance not only predicts the universal behavior of the dynamic brain network but also suggests non-consistent changes in different networks. These results demonstrate that the dynamic brain network is more random for the task-positive subnetwork and whole-brain network under visual stimulation but is more regular for the task-negative subnetwork. Our findings provide deeper insight into the importance of spectral properties in the functional brain network, especially the incomparable role of RMT in revealing the intrinsic properties of complex systems.

Spectral properties of the temporal evolution of brain network structure

NASA Astrophysics Data System (ADS)

Wang, Rong; Zhang, Zhen-Zhen; Ma, Jun; Yang, Yong; Lin, Pan; Wu, Ying

2015-12-01

The temporal evolution properties of the brain network are crucial for complex brain processes. In this paper, we investigate the differences in the dynamic brain network during resting and visual stimulation states in a task-positive subnetwork, task-negative subnetwork, and whole-brain network. The dynamic brain network is first constructed from human functional magnetic resonance imaging data based on the sliding window method, and then the eigenvalues corresponding to the network are calculated. We use eigenvalue analysis to analyze the global properties of eigenvalues and the random matrix theory (RMT) method to measure the local properties. For global properties, the shifting of the eigenvalue distribution and the decrease in the largest eigenvalue are linked to visual stimulation in all networks. For local properties, the short-range correlation in eigenvalues as measured by the nearest neighbor spacing distribution is not always sensitive to visual stimulation. However, the long-range correlation in eigenvalues as evaluated by spectral rigidity and number variance not only predicts the universal behavior of the dynamic brain network but also suggests non-consistent changes in different networks. These results demonstrate that the dynamic brain network is more random for the task-positive subnetwork and whole-brain network under visual stimulation but is more regular for the task-negative subnetwork. Our findings provide deeper insight into the importance of spectral properties in the functional brain network, especially the incomparable role of RMT in revealing the intrinsic properties of complex systems.

Reconsidering the evolution of brain, cognition, and behavior in birds and mammals

PubMed Central

Willemet, Romain

2013-01-01

Despite decades of research, some of the most basic issues concerning the extraordinarily complex brains and behavior of birds and mammals, such as the factors responsible for the diversity of brain size and composition, are still unclear. This is partly due to a number of conceptual and methodological issues. Determining species and group differences in brain composition requires accounting for the presence of taxon-cerebrotypes and the use of precise statistical methods. The role of allometry in determining brain variables should be revised. In particular, bird and mammalian brains appear to have evolved in response to a variety of selective pressures influencing both brain size and composition. “Brain” and “cognition” are indeed meta-variables, made up of the variables that are ecologically relevant and evolutionarily selected. External indicators of species differences in cognition and behavior are limited by the complexity of these differences. Indeed, behavioral differences between species and individuals are caused by cognitive and affective components. Although intra-species variability forms the basis of species evolution, some of the mechanisms underlying individual differences in brain and behavior appear to differ from those between species. While many issues have persisted over the years because of a lack of appropriate data or methods to test them; several fallacies, particularly those related to the human brain, reflect scientists' preconceptions. The theoretical framework on the evolution of brain, cognition, and behavior in birds and mammals should be reconsidered with these biases in mind. PMID:23847570

Profiling nonhuman intelligence: An exercise in developing unbiased tools for describing other "types" of intelligence on earth

NASA Astrophysics Data System (ADS)

Herzing, Denise L.

2014-02-01

Intelligence has historically been studied by comparing nonhuman cognitive and language abilities with human abilities. Primate-like species, which show human-like anatomy and share evolutionary lineage, have been the most studied. However, when comparing animals of non-primate origins our abilities to profile the potential for intelligence remains inadequate. Historically our measures for nonhuman intelligence have included a variety of tools: (1) physical measurements - brain to body ratio, brain structure/convolution/neural density, presence of artifacts and physical tools, (2) observational and sensory measurements - sensory signals, complexity of signals, cross-modal abilities, social complexity, (3) data mining - information theory, signal/noise, pattern recognition, (4) experimentation - memory, cognition, language comprehension/use, theory of mind, (5) direct interfaces - one way and two way interfaces with primates, dolphins, birds and (6) accidental interactions - human/animal symbiosis, cross-species enculturation. Because humans tend to focus on "human-like" attributes and measures and scientists are often unwilling to consider other "types" of intelligence that may not be human equated, our abilities to profile "types" of intelligence that differ on a variety of scales is weak. Just as biologists stretch their definitions of life to look at extremophiles in unusual conditions, so must we stretch our descriptions of types of minds and begin profiling, rather than equating, other life forms we may encounter.

Information properties of morphologically complex words modulate brain activity during word reading.

PubMed

Hakala, Tero; Hultén, Annika; Lehtonen, Minna; Lagus, Krista; Salmelin, Riitta

2018-06-01

Neuroimaging studies of the reading process point to functionally distinct stages in word recognition. Yet, current understanding of the operations linked to those various stages is mainly descriptive in nature. Approaches developed in the field of computational linguistics may offer a more quantitative approach for understanding brain dynamics. Our aim was to evaluate whether a statistical model of morphology, with well-defined computational principles, can capture the neural dynamics of reading, using the concept of surprisal from information theory as the common measure. The Morfessor model, created for unsupervised discovery of morphemes, is based on the minimum description length principle and attempts to find optimal units of representation for complex words. In a word recognition task, we correlated brain responses to word surprisal values derived from Morfessor and from other psycholinguistic variables that have been linked with various levels of linguistic abstraction. The magnetoencephalography data analysis focused on spatially, temporally and functionally distinct components of cortical activation observed in reading tasks. The early occipital and occipito-temporal responses were correlated with parameters relating to visual complexity and orthographic properties, whereas the later bilateral superior temporal activation was correlated with whole-word based and morphological models. The results show that the word processing costs estimated by the statistical Morfessor model are relevant for brain dynamics of reading during late processing stages. © 2018 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Revealing pathologies in the liquid crystalline structures of the brain by polarimetric studies (Presentation Recording)

NASA Astrophysics Data System (ADS)

Bakhshetyan, Karen; Melkonyan, Gurgen G.; Galstian, Tigran V.; Saghatelyan, Armen

2015-10-01

Natural or "self" alignment of molecular complexes in living tissue represents many similarities with liquid crystals (LC), which are anisotropic liquids. The orientational characteristics of those complexes may be related to many important functional parameters and their study may reveal important pathologies. The know-how, accumulated thanks to the study of LC materials, may thus be used to this end. One of the traditionally used methods, to characterize those materials, is the polarized light imaging (PLI) that allows for label-free analysis of anisotropic structures in the brain tissue and can be used, for example, for the analysis of myelinated fiber bundles. In the current work, we first attempted to apply the PLI on the mouse histological brain sections to create a map of anisotropic structures using cross-polarizer transmission light. Then we implemented the PLI for comparative study of histological sections of human postmortem brain samples under normal and pathological conditions, such as Parkinson's disease (PD). Imaging the coronal, sagittal and horizontal sections of mouse brain allowed us to create a false color-coded fiber orientation map under polarized light. In human brain datasets for both control and PD groups we measured the pixel intensities in myelin-rich subregions of internal capsule and normalized these to non-myelinated background signal from putamen and caudate nucleus. Quantification of intensities revealed a statistically significant reduction of fiber intensity of PD compared to control subjects (2.801 +/- 0.303 and 3.724 +/- 0.07 respectively; *p < 0.05). Our study confirms the validity of PLI method for visualizing myelinated axonal fibers. This relatively simple technique can become a promising tool for study of neurodegenerative diseases where labeling-free imaging is an important benefit.

Differential Effects of Structural Modifications on the Competition of Chalcones for the PIB Amyloid Imaging Ligand-Binding Site in Alzheimer's Disease Brain and Synthetic Aβ Fibrils.

PubMed

Fosso, Marina Y; McCarty, Katie; Head, Elizabeth; Garneau-Tsodikova, Sylvie; LeVine, Harry

2016-02-17

Alzheimer's disease (AD) is a complex brain disorder that still remains ill defined. In order to understand the significance of binding of different clinical in vivo imaging ligands to the polymorphic pathological features of AD brain, the molecular characteristics of the ligand interacting with its specific binding site need to be defined. Herein, we observed that tritiated Pittsburgh Compound B ((3)H-PIB) can be displaced from synthetic Aβ(1-40) and Aβ(1-42) fibrils and from the PIB binding complex purified from human AD brain (ADPBC) by molecules containing a chalcone structural scaffold. We evaluated how substitution on the chalcone scaffold alters its ability to displace (3)H-PIB from the synthetic fibrils and ADPBC. By comparing unsubstituted core chalcone scaffolds along with the effects of bromine and methyl substitution at various positions, we found that attaching a hydroxyl group on the ring adjacent to the carbonyl group (ring I) of the parent member of the chalcone family generally improved the binding affinity of chalcones toward ADPBC and synthetic fibrils F40 and F42. Furthermore, any substitution on ring I at the ortho-position of the carbonyl group greatly decreases the binding affinity of the chalcones, potentially as a result of steric hindrance. Together with the finding that neither our chalcones nor PIB interact with the Congo Red/X-34 binding site, these molecules provide new tools to selectively probe the PIB binding site that is found in human AD brain, but not in brains of AD pathology animal models. Our chalcone derivatives also provide important information on the effects of fibril polymorphism on ligand binding.

Increased 5S rRNA oxidation in Alzheimer's disease.

PubMed

Ding, Qunxing; Zhu, Haiyan; Zhang, Bing; Soriano, Augusto; Burns, Roxanne; Markesbery, William R

2012-01-01

It is widely accepted that oxidative stress is involved in neurodegenerative disorders such as Alzheimer's disease (AD). Ribosomal RNA (rRNA) is one of the most abundant molecules in most cells and is affected by oxidative stress in the human brain. Previous data have indicated that total rRNA levels were decreased in the brains of subjects with AD and mild cognitive impairment concomitant with an increase in rRNA oxidation. In addition, level of 5S rRNA, one of the essential components of the ribosome complex, was significantly lower in the inferior parietal lobule (IP) brain area of subjects with AD compared with control subjects. To further evaluate the alteration of 5S rRNA in neurodegenerative human brains, multiple brain regions from both AD and age-matched control subjects were used in this study, including IP, superior and middle temporal gyro, temporal pole, and cerebellum. Different molecular pools including 5S rRNA integrated into ribosome complexes, free 5S rRNA, cytoplasmic 5S rRNA, and nuclear 5S rRNA were studied. Free 5S rRNA levels were significantly decreased in the temporal pole region of AD subjects and the oxidation of ribosome-integrated and free 5S rRNA was significantly increased in multiple brain regions in AD subjects compared with controls. Moreover, a greater amount of oxidized 5S rRNA was detected in the cytoplasm and nucleus of AD subjects compared with controls. These results suggest that the increased oxidation of 5S rRNA, especially the oxidation of free 5S rRNA, may be involved in the neurodegeneration observed in AD.

Dynamic reconfiguration of frontal brain networks during executive cognition in humans

PubMed Central

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

2015-01-01

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

Predicting novel histopathological microlesions in human epileptic brain through transcriptional clustering.

PubMed

Dachet, Fabien; Bagla, Shruti; Keren-Aviram, Gal; Morton, Andrew; Balan, Karina; Saadat, Laleh; Valyi-Nagy, Tibor; Kupsky, William; Song, Fei; Dratz, Edward; Loeb, Jeffrey A

2015-02-01

Although epilepsy is associated with a variety of abnormalities, exactly why some brain regions produce seizures and others do not is not known. We developed a method to identify cellular changes in human epileptic neocortex using transcriptional clustering. A paired analysis of high and low spiking tissues recorded in vivo from 15 patients predicted 11 cell-specific changes together with their 'cellular interactome'. These predictions were validated histologically revealing millimetre-sized 'microlesions' together with a global increase in vascularity and microglia. Microlesions were easily identified in deeper cortical layers using the neuronal marker NeuN, showed a marked reduction in neuronal processes, and were associated with nearby activation of MAPK/CREB signalling, a marker of epileptic activity, in superficial layers. Microlesions constitute a common, undiscovered layer-specific abnormality of neuronal connectivity in human neocortex that may be responsible for many 'non-lesional' forms of epilepsy. The transcriptional clustering approach used here could be applied more broadly to predict cellular differences in other brain and complex tissue disorders. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Methodological Problems on the Way to Integrative Human Neuroscience.

PubMed

Kotchoubey, Boris; Tretter, Felix; Braun, Hans A; Buchheim, Thomas; Draguhn, Andreas; Fuchs, Thomas; Hasler, Felix; Hastedt, Heiner; Hinterberger, Thilo; Northoff, Georg; Rentschler, Ingo; Schleim, Stephan; Sellmaier, Stephan; Tebartz Van Elst, Ludger; Tschacher, Wolfgang

2016-01-01

Neuroscience is a multidisciplinary effort to understand the structures and functions of the brain and brain-mind relations. This effort results in an increasing amount of data, generated by sophisticated technologies. However, these data enhance our descriptive knowledge , rather than improve our understanding of brain functions. This is caused by methodological gaps both within and between subdisciplines constituting neuroscience, and the atomistic approach that limits the study of macro- and mesoscopic issues. Whole-brain measurement technologies do not resolve these issues, but rather aggravate them by the complexity problem. The present article is devoted to methodological and epistemic problems that obstruct the development of human neuroscience. We neither discuss ontological questions (e.g., the nature of the mind) nor review data, except when it is necessary to demonstrate a methodological issue. As regards intradisciplinary methodological problems, we concentrate on those within neurobiology (e.g., the gap between electrical and chemical approaches to neurophysiological processes) and psychology (missing theoretical concepts). As regards interdisciplinary problems, we suggest that core disciplines of neuroscience can be integrated using systemic concepts that also entail human-environment relations. We emphasize the necessity of a meta-discussion that should entail a closer cooperation with philosophy as a discipline of systematic reflection. The atomistic reduction should be complemented by the explicit consideration of the embodiedness of the brain and the embeddedness of humans. The discussion is aimed at the development of an explicit methodology of integrative human neuroscience , which will not only link different fields and levels, but also help in understanding clinical phenomena.

Methodological Problems on the Way to Integrative Human Neuroscience

PubMed Central

Kotchoubey, Boris; Tretter, Felix; Braun, Hans A.; Buchheim, Thomas; Draguhn, Andreas; Fuchs, Thomas; Hasler, Felix; Hastedt, Heiner; Hinterberger, Thilo; Northoff, Georg; Rentschler, Ingo; Schleim, Stephan; Sellmaier, Stephan; Tebartz Van Elst, Ludger; Tschacher, Wolfgang

2016-01-01

Neuroscience is a multidisciplinary effort to understand the structures and functions of the brain and brain-mind relations. This effort results in an increasing amount of data, generated by sophisticated technologies. However, these data enhance our descriptive knowledge, rather than improve our understanding of brain functions. This is caused by methodological gaps both within and between subdisciplines constituting neuroscience, and the atomistic approach that limits the study of macro- and mesoscopic issues. Whole-brain measurement technologies do not resolve these issues, but rather aggravate them by the complexity problem. The present article is devoted to methodological and epistemic problems that obstruct the development of human neuroscience. We neither discuss ontological questions (e.g., the nature of the mind) nor review data, except when it is necessary to demonstrate a methodological issue. As regards intradisciplinary methodological problems, we concentrate on those within neurobiology (e.g., the gap between electrical and chemical approaches to neurophysiological processes) and psychology (missing theoretical concepts). As regards interdisciplinary problems, we suggest that core disciplines of neuroscience can be integrated using systemic concepts that also entail human-environment relations. We emphasize the necessity of a meta-discussion that should entail a closer cooperation with philosophy as a discipline of systematic reflection. The atomistic reduction should be complemented by the explicit consideration of the embodiedness of the brain and the embeddedness of humans. The discussion is aimed at the development of an explicit methodology of integrative human neuroscience, which will not only link different fields and levels, but also help in understanding clinical phenomena. PMID:27965548

Perturbation of Brain Oscillations after Ischemic Stroke: A Potential Biomarker for Post-Stroke Function and Therapy

PubMed Central

Rabiller, Gratianne; He, Ji-Wei; Nishijima, Yasuo; Wong, Aaron; Liu, Jialing

2015-01-01

Brain waves resonate from the generators of electrical current and propagate across brain regions with oscillation frequencies ranging from 0.05 to 500 Hz. The commonly observed oscillatory waves recorded by an electroencephalogram (EEG) in normal adult humans can be grouped into five main categories according to the frequency and amplitude, namely δ (1–4 Hz, 20–200 μV), θ (4–8 Hz, 10 μV), α (8–12 Hz, 20–200 μV), β (12–30 Hz, 5–10 μV), and γ (30–80 Hz, low amplitude). Emerging evidence from experimental and human studies suggests that groups of function and behavior seem to be specifically associated with the presence of each oscillation band, although the complex relationship between oscillation frequency and function, as well as the interaction between brain oscillations, are far from clear. Changes of brain oscillation patterns have long been implicated in the diseases of the central nervous system including ischemic stroke, in which the reduction of cerebral blood flow as well as the progression of tissue damage have direct spatiotemporal effects on the power of several oscillatory bands and their interactions. This review summarizes the current knowledge in behavior and function associated with each brain oscillation, and also in the specific changes in brain electrical activities that correspond to the molecular events and functional alterations observed after experimental and human stroke. We provide the basis of the generations of brain oscillations and potential cellular and molecular mechanisms underlying stroke-induced perturbation. We will also discuss the implications of using brain oscillation patterns as biomarkers for the prediction of stroke outcome and therapeutic efficacy. PMID:26516838

Dunbar's number: group size and brain physiology in humans reexamined.

PubMed

de Ruiter, Jan; Weston, Gavin; Lyon, Stephen M

2011-01-01

Popular academic ideas linking physiological adaptations to social behaviors are spreading disconcertingly into wider societal contexts. In this article, we note our skepticism with one particularly popular—in our view, problematic—supposed causal correlation between neocortex size and social group size. The resulting Dunbar's Number, as it has come to be called, has been statistically tested against observed group size in different primate species. Although there may be reason to doubt the Dunbar's Number hypothesis among nonhuman primate species, we restrict ourselves here to the application of such an explanatory hypothesis to human, culture-manipulating populations. Human information process management, we argue, cannot be understood as a simple product of brain physiology. Cross-cultural comparison of not only group size but also relationship-reckoning systems like kinship terminologies suggests that although neocortices are undoubtedly crucial to human behavior, they cannot be given such primacy in explaining complex group composition, formation, or management.

A mathematical model of a recombinant humanized anti-cocaine monoclonal antibody's effects on cocaine pharmacokinetics in mice.

PubMed

Wetzel, Hanna N; Zhang, Tongli; Norman, Andrew B

2017-09-01

A recombinant humanized anti-cocaine monoclonal antibody (mAb), h2E2, is at an advanced stage of pre-clinical development as an immunotherapy for cocaine abuse. It is hypothesized that h2E2 binds to and sequesters cocaine in the blood. A three-compartment model of the effects of h2E2 on cocaine's distribution was constructed. The model assumes that h2E2 binds to cocaine and that the h2E2-cocaine complex does not enter the brain but distributes between the central and peripheral compartments. Free cocaine is eliminated from both the central and peripheral compartments, and h2E2 and the h2E2-cocaine complex are eliminated from the central compartment only. This model was tested against a new dataset measuring cocaine concentrations in the brain and plasma over 1h in the presence and absence of h2E2. The mAb significantly increased plasma cocaine concentrations with a concomitant significant decrease in brain concentration. Plasma concentrations declined over the 1-hour sampling period in both groups. With a set of parameters within reasonable physiological ranges, the three-compartment model was able to qualitatively and quantitatively simulate the increased plasma concentration in the presence of the antibody and the decreased peak brain concentration in the presence of antibody. Importantly, the model explained the decline in plasma concentrations over time as distribution of the cocaine-h2E2 complex into a peripheral compartment. This model will facilitate the targeting of ideal mAb PK/PD properties thus accelerating the identification of lead candidate anti-drug mAbs. Copyright © 2017 Elsevier Inc. All rights reserved.

Calmodulin Methyltransferase Is Required for Growth, Muscle Strength, Somatosensory Development and Brain Function

PubMed Central

Haziza, Sitvanit; Magnani, Roberta; Lan, Dima; Keinan, Omer; Saada, Ann; Hershkovitz, Eli; Yanay, Nurit; Cohen, Yoram; Nevo, Yoram; Houtz, Robert L.; Sheffield, Val C.; Golan, Hava; Parvari, Ruti

2015-01-01

Calmodulin lysine methyl transferase (CaM KMT) is ubiquitously expressed and highly conserved from plants to vertebrates. CaM is frequently trimethylated at Lys-115, however, the role of CaM methylation in vertebrates has not been studied. CaM KMT was found to be homozygously deleted in the 2P21 deletion syndrome that includes 4 genes. These patients present with cystinuria, severe intellectual disabilities, hypotonia, mitochondrial disease and facial dysmorphism. Two siblings with deletion of three of the genes included in the 2P21 deletion syndrome presented with cystinuria, hypotonia, a mild/moderate mental retardation and a respiratory chain complex IV deficiency. To be able to attribute the functional significance of the methylation of CaM in the mouse and the contribution of CaM KMT to the clinical presentation of the 2p21deletion patients, we produced a mouse model lacking only CaM KMT with deletion borders as in the human 2p21deletion syndrome. No compensatory activity for CaM methylation was found. Impairment of complexes I and IV, and less significantly III, of the mitochondrial respiratory chain was more pronounced in the brain than in muscle. CaM KMT is essential for normal body growth and somatosensory development, as well as for the proper functioning of the adult mouse brain. Developmental delay was demonstrated for somatosensory function and for complex behavior, which involved both basal motor function and motivation. The mutant mice also had deficits in motor learning, complex coordination and learning of aversive stimuli. The mouse model contributes to the evaluation of the role of methylated CaM. CaM methylation appears to have a role in growth, muscle strength, somatosensory development and brain function. The current study has clinical implications for human patients. Patients presenting slow growth and muscle weakness that could result from a mitochondrial impairment and mental retardation should be considered for sequence analysis of the CaM KMT gene. PMID:26247364

Calmodulin Methyltransferase Is Required for Growth, Muscle Strength, Somatosensory Development and Brain Function.

PubMed

Haziza, Sitvanit; Magnani, Roberta; Lan, Dima; Keinan, Omer; Saada, Ann; Hershkovitz, Eli; Yanay, Nurit; Cohen, Yoram; Nevo, Yoram; Houtz, Robert L; Sheffield, Val C; Golan, Hava; Parvari, Ruti

2015-08-01

Calmodulin lysine methyl transferase (CaM KMT) is ubiquitously expressed and highly conserved from plants to vertebrates. CaM is frequently trimethylated at Lys-115, however, the role of CaM methylation in vertebrates has not been studied. CaM KMT was found to be homozygously deleted in the 2P21 deletion syndrome that includes 4 genes. These patients present with cystinuria, severe intellectual disabilities, hypotonia, mitochondrial disease and facial dysmorphism. Two siblings with deletion of three of the genes included in the 2P21 deletion syndrome presented with cystinuria, hypotonia, a mild/moderate mental retardation and a respiratory chain complex IV deficiency. To be able to attribute the functional significance of the methylation of CaM in the mouse and the contribution of CaM KMT to the clinical presentation of the 2p21deletion patients, we produced a mouse model lacking only CaM KMT with deletion borders as in the human 2p21deletion syndrome. No compensatory activity for CaM methylation was found. Impairment of complexes I and IV, and less significantly III, of the mitochondrial respiratory chain was more pronounced in the brain than in muscle. CaM KMT is essential for normal body growth and somatosensory development, as well as for the proper functioning of the adult mouse brain. Developmental delay was demonstrated for somatosensory function and for complex behavior, which involved both basal motor function and motivation. The mutant mice also had deficits in motor learning, complex coordination and learning of aversive stimuli. The mouse model contributes to the evaluation of the role of methylated CaM. CaM methylation appears to have a role in growth, muscle strength, somatosensory development and brain function. The current study has clinical implications for human patients. Patients presenting slow growth and muscle weakness that could result from a mitochondrial impairment and mental retardation should be considered for sequence analysis of the CaM KMT gene.

Big data, open science and the brain: lessons learned from genomics.

PubMed

Choudhury, Suparna; Fishman, Jennifer R; McGowan, Michelle L; Juengst, Eric T

2014-01-01

The BRAIN Initiative aims to break new ground in the scale and speed of data collection in neuroscience, requiring tools to handle data in the magnitude of yottabytes (10(24)). The scale, investment and organization of it are being compared to the Human Genome Project (HGP), which has exemplified "big science" for biology. In line with the trend towards Big Data in genomic research, the promise of the BRAIN Initiative, as well as the European Human Brain Project, rests on the possibility to amass vast quantities of data to model the complex interactions between the brain and behavior and inform the diagnosis and prevention of neurological disorders and psychiatric disease. Advocates of this "data driven" paradigm in neuroscience argue that harnessing the large quantities of data generated across laboratories worldwide has numerous methodological, ethical and economic advantages, but it requires the neuroscience community to adopt a culture of data sharing and open access to benefit from them. In this article, we examine the rationale for data sharing among advocates and briefly exemplify these in terms of new "open neuroscience" projects. Then, drawing on the frequently invoked model of data sharing in genomics, we go on to demonstrate the complexities of data sharing, shedding light on the sociological and ethical challenges within the realms of institutions, researchers and participants, namely dilemmas around public/private interests in data, (lack of) motivation to share in the academic community, and potential loss of participant anonymity. Our paper serves to highlight some foreseeable tensions around data sharing relevant to the emergent "open neuroscience" movement.

Virtual Neurorobotics (VNR) to Accelerate Development of Plausible Neuromorphic Brain Architectures.

PubMed

Goodman, Philip H; Buntha, Sermsak; Zou, Quan; Dascalu, Sergiu-Mihai

2007-01-01

Traditional research in artificial intelligence and machine learning has viewed the brain as a specially adapted information-processing system. More recently the field of social robotics has been advanced to capture the important dynamics of human cognition and interaction. An overarching societal goal of this research is to incorporate the resultant knowledge about intelligence into technology for prosthetic, assistive, security, and decision support applications. However, despite many decades of investment in learning and classification systems, this paradigm has yet to yield truly "intelligent" systems. For this reason, many investigators are now attempting to incorporate more realistic neuromorphic properties into machine learning systems, encouraged by over two decades of neuroscience research that has provided parameters that characterize the brain's interdependent genomic, proteomic, metabolomic, anatomic, and electrophysiological networks. Given the complexity of neural systems, developing tenable models to capture the essence of natural intelligence for real-time application requires that we discriminate features underlying information processing and intrinsic motivation from those reflecting biological constraints (such as maintaining structural integrity and transporting metabolic products). We propose herein a conceptual framework and an iterative method of virtual neurorobotics (VNR) intended to rapidly forward-engineer and test progressively more complex putative neuromorphic brain prototypes for their ability to support intrinsically intelligent, intentional interaction with humans. The VNR system is based on the viewpoint that a truly intelligent system must be driven by emotion rather than programmed tasking, incorporating intrinsic motivation and intentionality. We report pilot results of a closed-loop, real-time interactive VNR system with a spiking neural brain, and provide a video demonstration as online supplemental material.

Brain banks as key part of biochemical and molecular studies on cerebral cortex involvement in Parkinson's disease.

PubMed

Ravid, Rivka; Ferrer, Isidro

2012-04-01

Exciting developments in basic and clinical neuroscience and recent progress in the field of Parkinson's disease (PD) are partly a result of the availability of human specimens obtained through brain banks. These banks have optimized the methodological, managerial and organizational procedures; standard operating procedures; and ethical, legal and social issues, including the code of conduct for 21st Century brain banking and novel protocols. The present minireview focuses on current brain banking organization and management, as well as the likely future direction of the brain banking field. We emphasize the potentials and pitfalls when using high-quality specimens of the human central nervous system for advancing PD research. PD is a generalized disease in which α-synuclein is not a unique component but, instead, is only one of the players accounting for the complex impairment of biochemical/molecular processes involved in metabolic pathways. This is particularly important in the cerebral cortex, where altered cognition has a complex neurochemical substrate. Mitochondria and energy metabolism impairment, abnormal RNA, microRNA, protein synthesis, post-translational protein modifications and alterations in the lipid composition of membranes and lipid rafts are part of these complementary factors. We have to be alert to the possible pitfalls of each specimen and its suitability for a particular study. Not all samples qualify for the study of DNA, RNA, proteins, post-translational modifications, lipids and metabolomes, although the use of carefully selected samples and appropriate methods minimizes pitfalls and errors and guarantees high-quality reserach. © 2012 The Authors Journal compilation © 2012 FEBS.

Side population in human glioblastoma is non-tumorigenic and characterizes brain endothelial cells

PubMed Central

Golebiewska, Anna; Bougnaud, Sébastien; Stieber, Daniel; Brons, Nicolaas H. C.; Vallar, Laurent; Hertel, Frank; Klink, Barbara; Schröck, Evelin; Bjerkvig, Rolf

2013-01-01

The identification and significance of cancer stem-like cells in malignant gliomas remains controversial. It has been proposed that cancer stem-like cells display increased drug resistance, through the expression of ATP-binding cassette transporters that detoxify cells by effluxing exogenous compounds. Here, we investigated the ‘side population’ phenotype based on efflux properties of ATP-binding cassette transporters in freshly isolated human glioblastoma samples and intracranial xenografts derived thereof. Using fluorescence in situ hybridization analysis on sorted cells obtained from glioblastoma biopsies, as well as human tumour xenografts developed in immunodeficient enhanced green fluorescence protein-expressing mice that allow an unequivocal tumour-stroma discrimination, we show that side population cells in human glioblastoma are non-neoplastic and exclusively stroma-derived. Tumour cells were consistently devoid of efflux properties regardless of their genetic background, tumour ploidy or stem cell associated marker expression. Using multi-parameter flow cytometry we identified the stromal side population in human glioblastoma to be brain-derived endothelial cells with a minor contribution of astrocytes. In contrast with their foetal counterpart, neural stem/progenitor cells in the adult brain did not display the side population phenotype. Of note, we show that CD133-positive cells often associated with cancer stem-like cells in glioblastoma biopsies, do not represent a homogenous cell population and include CD31-positive endothelial cells. Interestingly, treatment of brain tumours with the anti-angiogenic agent bevacizumab reduced total vessel density, but did not affect the efflux properties of endothelial cells. In conclusion our findings contribute to an unbiased identification of cancer stem-like cells and stromal cells in brain neoplasms, and provide novel insight into the complex issue of drug delivery to the brain. Since efflux properties of endothelial cells are likely to compromise drug availability, transiently targeting ATP-binding cassette transporters may be a valuable therapeutic strategy to improve treatment effects in brain tumours. PMID:23460667

SELECTIVE CHANGES IN BRAIN PROTEIN KINASE C ISOFORMS FOLLOWING DEVELOPMENTAL EXPOSURE TO A PCB MIXTURE.

EPA Science Inventory

Introduction
Polychlorinated biphenyls (PCBs) offer a unique model to understand the major issues related to complex environmental mixtures. These environmental pollutants are ubiquitous, persistent, bioaccumulate in human body through the food chain, and exist as mixtures of ...

Automatic delineation and 3D visualization of the human ventricular system using probabilistic neural networks

NASA Astrophysics Data System (ADS)

Hatfield, Fraser N.; Dehmeshki, Jamshid

1998-09-01

Neurosurgery is an extremely specialized area of medical practice, requiring many years of training. It has been suggested that virtual reality models of the complex structures within the brain may aid in the training of neurosurgeons as well as playing an important role in the preparation for surgery. This paper focuses on the application of a probabilistic neural network to the automatic segmentation of the ventricles from magnetic resonance images of the brain, and their three dimensional visualization.

Targeting Cancer Protein Profiles with Split-Enzyme Reporter Fragments to Achieve Chemical Resolution for Molecular Imaging

DTIC Science & Technology

2013-08-01

We next tested the utility of the construct to accumulate in tumors expressing EGFR using an orthotopic mouse model for brain tumors. Glioma cells...filament tumor marker, identified implanted cells within the orthotopic mouse model which were of human origin, i.e. Gli36Δ5 cells, and demonstrated that...forward into in vivo animal tumor model studies. • In vivo imaging of EGFR targeted-complex in orthotopic mouse model of brain tumor. • Ex vivo validation

Rehabilitation of Visual and Perceptual Dysfunction after Severe Traumatic Brain Injury

DTIC Science & Technology

2014-05-01

Aguilar C, Hall-Haro C. Decay of prism aftereffects under passive and active conditions. Cogn Brain Res. 2004;20:92-97. 13. Kornheiser A. Adaptation...17. Huxlin KR, Martin T, Kelly K, et al. Perceptual relearning of complex visual motion after V1 damage in humans. J Neurosci . 2009;29:3981-3991...questionnaires. Restor Neurol Neurosci . 2004;22:399-420. 19. Peli E, Bowers AR, Mandel AJ, Higgins K, Goldstein RB, Bobrow L. Design of driving simulator

Two possible driving forces supporting the evolution of animal communication. Comment on "Towards a Computational Comparative Neuroprimatology: Framing the language-ready brain" by Michael A. Arbib

NASA Astrophysics Data System (ADS)

Moulin-Frier, Clément; Verschure, Paul F. M. J.

2016-03-01

In the target paper [1], M.A. Arbib proposes a quite exhaustive review of the (often computational) models developed during the last decades that support his detailed scenario on language evolution (the Mirror System Hypothesis, MSH). The approach considers that language evolved from a mirror system for grasping already present in LCA-m (the last common ancestor of macaques and humans), to a simple imitation system for grasping present in LCA-c (the last common ancestor of chimpanzees and humans), to a complex imitation system for grasping that developed in the hominid line since that ancestor. MSH considers that this complex imitation system is a key evolutionary step for a language-ready brain, providing all the required elements for an open-ended gestural communication system. The transition from the gestural (bracchio-manual and visual) to the vocal (articulatory and auditory) domain is supposed to be a less important evolutionary step.

A network engineering perspective on probing and perturbing cognition with neurofeedback.

PubMed

Bassett, Danielle S; Khambhati, Ankit N

2017-05-01

Network science and engineering provide a flexible and generalizable tool set to describe and manipulate complex systems characterized by heterogeneous interaction patterns among component parts. While classically applied to social systems, these tools have recently proven to be particularly useful in the study of the brain. In this review, we describe the nascent use of these tools to understand human cognition, and we discuss their utility in informing the meaningful and predictable perturbation of cognition in combination with the emerging capabilities of neurofeedback. To blend these disparate strands of research, we build on emerging conceptualizations of how the brain functions (as a complex network) and how we can develop and target interventions or modulations (as a form of network control). We close with an outline of current frontiers that bridge neurofeedback, connectomics, and network control theory to better understand human cognition. © 2017 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals Inc. on behalf of The New York Academy of Sciences.

Structural and molecular interrogation of intact biological systems

PubMed Central

Chung, Kwanghun; Wallace, Jenelle; Kim, Sung-Yon; Kalyanasundaram, Sandhiya; Andalman, Aaron S.; Davidson, Thomas J.; Mirzabekov, Julie J.; Zalocusky, Kelly A.; Mattis, Joanna; Denisin, Aleksandra K.; Pak, Sally; Bernstein, Hannah; Ramakrishnan, Charu; Grosenick, Logan; Gradinaru, Viviana; Deisseroth, Karl

2014-01-01

Obtaining high-resolution information from a complex system, while maintaining the global perspective needed to understand system function, represents a key challenge in biology. Here we address this challenge with a method (termed CLARITY) for the transformation of intact tissue into a nanoporous hydrogel-hybridized form (crosslinked to a three-dimensional network of hydrophilic polymers) that is fully assembled but optically transparent and macromolecule-permeable. Using mouse brains, we show intact-tissue imaging of long-range projections, local circuit wiring, cellular relationships, subcellular structures, protein complexes, nucleic acids and neurotransmitters. CLARITY also enables intact-tissue in situ hybridization, immunohistochemistry with multiple rounds of staining and de-staining in non-sectioned tissue, and antibody labelling throughout the intact adult mouse brain. Finally, we show that CLARITY enables fine structural analysis of clinical samples, including non-sectioned human tissue from a neuropsychiatric-disease setting, establishing a path for the transmutation of human tissue into a stable, intact and accessible form suitable for probing structural and molecular underpinnings of physiological function and disease. PMID:23575631

[Neurophysiological Foundations and Practical Realizations of the Brain-Machine Interfaces the Technology in Neurological Rehabilitation].

PubMed

Kaplan, A Ya

2016-01-01

Technology brain-computer interface (BCI) based on the registration and interpretation of EEG has recently become one of the most popular developments in neuroscience and psychophysiology. This is due not only to the intended future use of these technologies in many areas of practical human activity, but also to the fact that IMC--is a completely new paradigm in psychophysiology, allowing test hypotheses about the possibilities of the human brain to the development of skills of interaction with the outside world without the mediation of the motor system, i.e. only with the help of voluntary modulation of EEG generators. This paper examines the theoretical and experimental basis, the current state and prospects of development of training, communicational and assisting complexes based on BCI to control them without muscular effort on the basis of mental commands detected in the EEG of patients with severely impaired speech and motor system.

Neuroscience and education.

PubMed

Goswami, Usha

2004-03-01

Neuroscience is a relatively new discipline encompassing neurology, psychology and biology. It has made great strides in the last 100 years, during which many aspects of the physiology, biochemistry, pharmacology and structure of the vertebrate brain have been understood. Understanding of some of the basic perceptual, cognitive, attentional, emotional and mnemonic functions is also making progress, particularly since the advent of the cognitive neurosciences, which focus specifically on understanding higher level processes of cognition via imaging technology. Neuroimaging has enabled scientists to study the human brain at work in vivo, deepening our understanding of the very complex processes underpinning speech and language, thinking and reasoning, reading and mathematics. It seems timely, therefore, to consider how we might implement our increased understanding of brain development and brain function to explore educational questions.

Evolution and genomics of the human brain.

PubMed

Rosales-Reynoso, M A; Juárez-Vázquez, C I; Barros-Núñez, P

2018-05-01

Most living beings are able to perform actions that can be considered intelligent or, at the very least, the result of an appropriate reaction to changing circumstances in their environment. However, the intelligence or intellectual processes of humans are vastly superior to those achieved by all other species. The adult human brain is a highly complex organ weighing approximately 1500g, which accounts for only 2% of the total body weight but consumes an amount of energy equal to that required by all skeletal muscle at rest. Although the human brain displays a typical primate structure, it can be identified by its specific distinguishing features. The process of evolution and humanisation of the Homo sapiens brain resulted in a unique and distinct organ with the largest relative volume of any animal species. It also permitted structural reorganization of tissues and circuits in specific segments and regions. These steps explain the remarkable cognitive abilities of modern humans compared not only with other species in our genus, but also with older members of our own species. Brain evolution required the coexistence of two adaptation mechanisms. The first involves genetic changes that occur at the species level, and the second occurs at the individual level and involves changes in chromatin organisation or epigenetic changes. The genetic mechanisms include: a) genetic changes in coding regions that lead to changes in the sequence and activity of existing proteins; b) duplication and deletion of previously existing genes; c) changes in gene expression through changes in the regulatory sequences of different genes; and d) synthesis of non-coding RNAs. Lastly, this review describes some of the main documented chromosomal differences between humans and great apes. These differences have also contributed to the evolution and humanisation process of the H. sapiens brain. Copyright © 2014 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.

DCS-SVM: a novel semi-automated method for human brain MR image segmentation.

PubMed

Ahmadvand, Ali; Daliri, Mohammad Reza; Hajiali, Mohammadtaghi

2017-11-27

In this paper, a novel method is proposed which appropriately segments magnetic resonance (MR) brain images into three main tissues. This paper proposes an extension of our previous work in which we suggested a combination of multiple classifiers (CMC)-based methods named dynamic classifier selection-dynamic local training local Tanimoto index (DCS-DLTLTI) for MR brain image segmentation into three main cerebral tissues. This idea is used here and a novel method is developed that tries to use more complex and accurate classifiers like support vector machine (SVM) in the ensemble. This work is challenging because the CMC-based methods are time consuming, especially on huge datasets like three-dimensional (3D) brain MR images. Moreover, SVM is a powerful method that is used for modeling datasets with complex feature space, but it also has huge computational cost for big datasets, especially those with strong interclass variability problems and with more than two classes such as 3D brain images; therefore, we cannot use SVM in DCS-DLTLTI. Therefore, we propose a novel approach named "DCS-SVM" to use SVM in DCS-DLTLTI to improve the accuracy of segmentation results. The proposed method is applied on well-known datasets of the Internet Brain Segmentation Repository (IBSR) and promising results are obtained.

How environment and genes shape the adolescent brain.

PubMed

Paus, Tomáš

2013-07-01

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

Variations in brain defects result from cellular mosaicism in the activation of heat shock signalling.

PubMed

Ishii, Seiji; Torii, Masaaki; Son, Alexander I; Rajendraprasad, Meenu; Morozov, Yury M; Kawasawa, Yuka Imamura; Salzberg, Anna C; Fujimoto, Mitsuaki; Brennand, Kristen; Nakai, Akira; Mezger, Valerie; Gage, Fred H; Rakic, Pasko; Hashimoto-Torii, Kazue

2017-05-02

Repetitive prenatal exposure to identical or similar doses of harmful agents results in highly variable and unpredictable negative effects on fetal brain development ranging in severity from high to little or none. However, the molecular and cellular basis of this variability is not well understood. This study reports that exposure of mouse and human embryonic brain tissues to equal doses of harmful chemicals, such as ethanol, activates the primary stress response transcription factor heat shock factor 1 (Hsf1) in a highly variable and stochastic manner. While Hsf1 is essential for protecting the embryonic brain from environmental stress, excessive activation impairs critical developmental events such as neuronal migration. Our results suggest that mosaic activation of Hsf1 within the embryonic brain in response to prenatal environmental stress exposure may contribute to the resulting generation of phenotypic variations observed in complex congenital brain disorders.

A peptide for targeted, systemic delivery of imaging and therapeutic compounds into acute brain injuries

NASA Astrophysics Data System (ADS)

Mann, Aman P.; Scodeller, Pablo; Hussain, Sazid; Joo, Jinmyoung; Kwon, Ester; Braun, Gary B.; Mölder, Tarmo; She, Zhi-Gang; Kotamraju, Venkata Ramana; Ranscht, Barbara; Krajewski, Stan; Teesalu, Tambet; Bhatia, Sangeeta; Sailor, Michael J.; Ruoslahti, Erkki

2016-06-01

Traumatic brain injury (TBI) is a major health and socio-economic problem, but no pharmacological agent is currently approved for the treatment of acute TBI. Thus, there is a great need for advances in this field. Here, we describe a short peptide (sequence CAQK) identified by in vivo phage display screening in mice with acute brain injury. The CAQK peptide selectively binds to injured mouse and human brain, and systemically injected CAQK specifically homes to sites of brain injury in mouse models. The CAQK target is a proteoglycan complex upregulated in brain injuries. Coupling to CAQK increased injury site accumulation of systemically administered molecules ranging from a drug-sized molecule to nanoparticles. CAQK-coated nanoparticles containing silencing oligonucleotides provided the first evidence of gene silencing in injured brain parenchyma by systemically administered siRNA. These findings present an effective targeting strategy for the delivery of therapeutics in clinical management of acute brain injuries.

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.

Evolution of Siglec-11 and Siglec-16 Genes in Hominins

PubMed Central

Wang, Xiaoxia; Mitra, Nivedita; Cruz, Pedro; Deng, Liwen; Varki, Nissi; Angata, Takashi; Green, Eric D.; Mullikin, Jim; Hayakawa, Toshiyuki; Varki, Ajit

2012-01-01

We previously reported a human-specific gene conversion of SIGLEC11 by an adjacent paralogous pseudogene (SIGLEC16P), generating a uniquely human form of the Siglec-11 protein, which is expressed in the human brain. Here, we show that Siglec-11 is expressed exclusively in microglia in all human brains studied—a finding of potential relevance to brain evolution, as microglia modulate neuronal survival, and Siglec-11 recruits SHP-1, a tyrosine phosphatase that modulates microglial biology. Following the recent finding of a functional SIGLEC16 allele in human populations, further analysis of the human SIGLEC11 and SIGLEC16/P sequences revealed an unusual series of gene conversion events between two loci. Two tandem and likely simultaneous gene conversions occurred from SIGLEC16P to SIGLEC11 with a potentially deleterious intervening short segment happening to be excluded. One of the conversion events also changed the 5′ untranslated sequence, altering predicted transcription factor binding sites. Both of the gene conversions have been dated to ∼1–1.2 Ma, after the emergence of the genus Homo, but prior to the emergence of the common ancestor of Denisovans and modern humans about 800,000 years ago, thus suggesting involvement in later stages of hominin brain evolution. In keeping with this, recombinant soluble Siglec-11 binds ligands in the human brain. We also address a second-round more recent gene conversion from SIGLEC11 to SIGLEC16, with the latter showing an allele frequency of ∼0.1–0.3 in a worldwide population study. Initial pseudogenization of SIGLEC16 was estimated to occur at least 3 Ma, which thus preceded the gene conversion of SIGLEC11 by SIGLEC16P. As gene conversion usually disrupts the converted gene, the fact that ORFs of hSIGLEC11 and hSIGLEC16 have been maintained after an unusual series of very complex gene conversion events suggests that these events may have been subject to hominin-specific selection forces. PMID:22383531

Levels of detail analysis of microwave scattering from human head models for brain stroke detection

PubMed Central

2017-01-01

In this paper, we have presented a microwave scattering analysis from multiple human head models. This study incorporates different levels of detail in the human head models and its effect on microwave scattering phenomenon. Two levels of detail are taken into account; (i) Simplified ellipse shaped head model (ii) Anatomically realistic head model, implemented using 2-D geometry. In addition, heterogenic and frequency-dispersive behavior of the brain tissues has also been incorporated in our head models. It is identified during this study that the microwave scattering phenomenon changes significantly once the complexity of head model is increased by incorporating more details using magnetic resonance imaging database. It is also found out that the microwave scattering results match in both types of head model (i.e., geometrically simple and anatomically realistic), once the measurements are made in the structurally simplified regions. However, the results diverge considerably in the complex areas of brain due to the arbitrary shape interface of tissue layers in the anatomically realistic head model. After incorporating various levels of detail, the solution of subject microwave scattering problem and the measurement of transmitted and backscattered signals were obtained using finite element method. Mesh convergence analysis was also performed to achieve error free results with a minimum number of mesh elements and a lesser degree of freedom in the fast computational time. The results were promising and the E-Field values converged for both simple and complex geometrical models. However, the E-Field difference between both types of head model at the same reference point differentiated a lot in terms of magnitude. At complex location, a high difference value of 0.04236 V/m was measured compared to the simple location, where it turned out to be 0.00197 V/m. This study also contributes to provide a comparison analysis between the direct and iterative solvers so as to find out the solution of subject microwave scattering problem in a minimum computational time along with memory resources requirement. It is seen from this study that the microwave imaging may effectively be utilized for the detection, localization and differentiation of different types of brain stroke. The simulation results verified that the microwave imaging can be efficiently exploited to study the significant contrast between electric field values of the normal and abnormal brain tissues for the investigation of brain anomalies. In the end, a specific absorption rate analysis was carried out to compare the ionizing effects of microwave signals to different types of head model using a factor of safety for brain tissues. It is also suggested after careful study of various inversion methods in practice for microwave head imaging, that the contrast source inversion method may be more suitable and computationally efficient for such problems. PMID:29177115

Defining functional SMA and pre-SMA subregions in human MFC using resting state fMRI: functional connectivity-based parcellation method.

PubMed

Kim, Jae-Hun; Lee, Jong-Min; Jo, Hang Joon; Kim, Sook Hui; Lee, Jung Hee; Kim, Sung Tae; Seo, Sang Won; Cox, Robert W; Na, Duk L; Kim, Sun I; Saad, Ziad S

2010-02-01

Noninvasive parcellation of the human cerebral cortex is an important goal for understanding and examining brain functions. Recently, the patterns of anatomical connections using diffusion tensor imaging (DTI) have been used to parcellate brain regions. Here, we present a noninvasive parcellation approach that uses "functional fingerprints" obtained by correlation measures on resting state functional magnetic resonance imaging (fMRI) data to parcellate brain regions. In other terms, brain regions are parcellated based on the similarity of their connection--as reflected by correlation during resting state--to the whole brain. The proposed method was used to parcellate the medial frontal cortex (MFC) into supplementary motor areas (SMA) and pre-SMA subregions. In agreement with anatomical landmark-based parcellation, we find that functional fingerprint clustering of the MFC results in anterior and posterior clusters. The probabilistic maps from 12 subjects showed that the anterior cluster is mainly located rostral to the vertical commissure anterior (VCA) line, whereas the posterior cluster is mainly located caudal to VCA line, suggesting the homologues of pre-SMA and SMA. The functional connections from the putative pre-SMA cluster were connected to brain regions which are responsible for complex/cognitive motor control, whereas those from the putative SMA cluster were connected to brain regions which are related to the simple motor control. These findings demonstrate the feasibility of the functional connectivity-based parcellation of the human cerebral cortex using resting state fMRI. Copyright (c) 2009 Elsevier Inc. All rights reserved.

The Role of Brain Inflammation in Epileptogenesis in TSC

DTIC Science & Technology

2014-07-01

human temporal lobe epilepsy . Neurobiol Dis 2008;29:142-160. 5. Ravizza T, Noe F, Zardoni D, Vaghi V, Sifringer M, Vezzani A. Interleukin...of epilepsy , as well as in human tissue obtained from epilepsy patients, such as with mesial temporal sclerosis. Different types of inflammatory...14. ABSTRACT Epilepsy is a common, disabling problem in patients with tuberous sclerosis complex (TSC) and is usually intractable to available

Mapping of Human FOXP2 Enhancers Reveals Complex Regulation.

PubMed

Becker, Martin; Devanna, Paolo; Fisher, Simon E; Vernes, Sonja C

2018-01-01

Mutations of the FOXP2 gene cause a severe speech and language disorder, providing a molecular window into the neurobiology of language. Individuals with FOXP2 mutations have structural and functional alterations affecting brain circuits that overlap with sites of FOXP2 expression, including regions of the cortex, striatum, and cerebellum. FOXP2 displays complex patterns of expression in the brain, as well as in non-neuronal tissues, suggesting that sophisticated regulatory mechanisms control its spatio-temporal expression. However, to date, little is known about the regulation of FOXP2 or the genomic elements that control its expression. Using chromatin conformation capture (3C), we mapped the human FOXP2 locus to identify putative enhancer regions that engage in long-range interactions with the promoter of this gene. We demonstrate the ability of the identified enhancer regions to drive gene expression. We also show regulation of the FOXP2 promoter and enhancer regions by candidate regulators - FOXP family and TBR1 transcription factors. These data point to regulatory elements that may contribute to the temporal- or tissue-specific expression patterns of human FOXP2 . Understanding the upstream regulatory pathways controlling FOXP2 expression will bring new insight into the molecular networks contributing to human language and related disorders.

Mapping of Human FOXP2 Enhancers Reveals Complex Regulation

PubMed Central

Becker, Martin; Devanna, Paolo; Fisher, Simon E.; Vernes, Sonja C.

2018-01-01

Mutations of the FOXP2 gene cause a severe speech and language disorder, providing a molecular window into the neurobiology of language. Individuals with FOXP2 mutations have structural and functional alterations affecting brain circuits that overlap with sites of FOXP2 expression, including regions of the cortex, striatum, and cerebellum. FOXP2 displays complex patterns of expression in the brain, as well as in non-neuronal tissues, suggesting that sophisticated regulatory mechanisms control its spatio-temporal expression. However, to date, little is known about the regulation of FOXP2 or the genomic elements that control its expression. Using chromatin conformation capture (3C), we mapped the human FOXP2 locus to identify putative enhancer regions that engage in long-range interactions with the promoter of this gene. We demonstrate the ability of the identified enhancer regions to drive gene expression. We also show regulation of the FOXP2 promoter and enhancer regions by candidate regulators – FOXP family and TBR1 transcription factors. These data point to regulatory elements that may contribute to the temporal- or tissue-specific expression patterns of human FOXP2. Understanding the upstream regulatory pathways controlling FOXP2 expression will bring new insight into the molecular networks contributing to human language and related disorders. PMID:29515369

A Neurology of the Conservative-Liberal Dimension of Political Ideology.

PubMed

Mendez, Mario F

2017-01-01

Differences in political ideology are a major source of human disagreement and conflict. There is increasing evidence that neurobiological mechanisms mediate individual differences in political ideology through effects on a conservative-liberal axis. This review summarizes personality, evolutionary and genetic, cognitive, neuroimaging, and neurological studies of conservatism-liberalism and discusses how they might affect political ideology. What emerges from this highly variable literature is evidence for a normal right-sided "conservative-complex" involving structures sensitive to negativity bias, threat, disgust, and avoidance. This conservative-complex may be damaged with brain disease, sometimes leading to a pathological "liberal shift" or a reduced tendency to conservatism in political ideology. Although not deterministic, these findings recommend further research on politics and the brain.

Joint explorative analysis of neuroreceptor subsystems in the human brain: application to receptor-transporter correlation using PET data.

PubMed

Cselényi, Zsolt; Lundberg, Johan; Halldin, Christer; Farde, Lars; Gulyás, Balázs

2004-10-01

Positron emission tomography (PET) has proved to be a highly successful technique in the qualitative and quantitative exploration of the human brain's neurotransmitter-receptor systems. In recent years, the number of PET radioligands, targeted to different neuroreceptor systems of the human brain, has increased considerably. This development paves the way for a simultaneous analysis of different receptor systems and subsystems in the same individual. The detailed exploration of the versatility of neuroreceptor systems requires novel technical approaches, capable of operating on huge parametric image datasets. An initial step of such explorative data processing and analysis should be the development of novel exploratory data-mining tools to gain insight into the "structure" of complex multi-individual, multi-receptor data sets. For practical reasons, a possible and feasible starting point of multi-receptor research can be the analysis of the pre- and post-synaptic binding sites of the same neurotransmitter. In the present study, we propose an unsupervised, unbiased data-mining tool for this task and demonstrate its usefulness by using quantitative receptor maps, obtained with positron emission tomography, from five healthy subjects on (pre-synaptic) serotonin transporters (5-HTT or SERT) and (post-synaptic) 5-HT(1A) receptors. Major components of the proposed technique include the projection of the input receptor maps to a feature space, the quasi-clustering and classification of projected data (neighbourhood formation), trans-individual analysis of neighbourhood properties (trajectory analysis), and the back-projection of the results of trajectory analysis to normal space (creation of multi-receptor maps). The resulting multi-receptor maps suggest that complex relationships and tendencies in the relationship between pre- and post-synaptic transporter-receptor systems can be revealed and classified by using this method. As an example, we demonstrate the regional correlation of the serotonin transporter-receptor systems. These parameter-specific multi-receptor maps can usefully guide the researchers in their endeavour to formulate models of multi-receptor interactions and changes in the human brain.

Spatial transcriptomic survey of human embryonic cerebral cortex by single-cell RNA-seq analysis.

PubMed

Fan, Xiaoying; Dong, Ji; Zhong, Suijuan; Wei, Yuan; Wu, Qian; Yan, Liying; Yong, Jun; Sun, Le; Wang, Xiaoye; Zhao, Yangyu; Wang, Wei; Yan, Jie; Wang, Xiaoqun; Qiao, Jie; Tang, Fuchou

2018-06-04

The cellular complexity of human brain development has been intensively investigated, although a regional characterization of the entire human cerebral cortex based on single-cell transcriptome analysis has not been reported. Here, we performed RNA-seq on over 4,000 individual cells from 22 brain regions of human mid-gestation embryos. We identified 29 cell sub-clusters, which showed different proportions in each region and the pons showed especially high percentage of astrocytes. Embryonic neurons were not as diverse as adult neurons, although they possessed important features of their destinies in adults. Neuron development was unsynchronized in the cerebral cortex, as dorsal regions appeared to be more mature than ventral regions at this stage. Region-specific genes were comprehensively identified in each neuronal sub-cluster, and a large proportion of these genes were neural disease related. Our results present a systematic landscape of the regionalized gene expression and neuron maturation of the human cerebral cortex.

The BRAIN Initiative: developing technology to catalyse neuroscience discovery.

PubMed

Jorgenson, Lyric A; Newsome, William T; Anderson, David J; Bargmann, Cornelia I; Brown, Emery N; Deisseroth, Karl; Donoghue, John P; Hudson, Kathy L; Ling, Geoffrey S F; MacLeish, Peter R; Marder, Eve; Normann, Richard A; Sanes, Joshua R; Schnitzer, Mark J; Sejnowski, Terrence J; Tank, David W; Tsien, Roger Y; Ugurbil, Kamil; Wingfield, John C

2015-05-19

The evolution of the field of neuroscience has been propelled by the advent of novel technological capabilities, and the pace at which these capabilities are being developed has accelerated dramatically in the past decade. Capitalizing on this momentum, the United States launched the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative to develop and apply new tools and technologies for revolutionizing our understanding of the brain. In this article, we review the scientific vision for this initiative set forth by the National Institutes of Health and discuss its implications for the future of neuroscience research. Particular emphasis is given to its potential impact on the mapping and study of neural circuits, and how this knowledge will transform our understanding of the complexity of the human brain and its diverse array of behaviours, perceptions, thoughts and emotions.

Hierarchical functional modularity in the resting-state human brain.

PubMed

Ferrarini, Luca; Veer, Ilya M; Baerends, Evelinda; van Tol, Marie-José; Renken, Remco J; van der Wee, Nic J A; Veltman, Dirk J; Aleman, André; Zitman, Frans G; Penninx, Brenda W J H; van Buchem, Mark A; Reiber, Johan H C; Rombouts, Serge A R B; Milles, Julien

2009-07-01

Functional magnetic resonance imaging (fMRI) studies have shown that anatomically distinct brain regions are functionally connected during the resting state. Basic topological properties in the brain functional connectivity (BFC) map have highlighted the BFC's small-world topology. Modularity, a more advanced topological property, has been hypothesized to be evolutionary advantageous, contributing to adaptive aspects of anatomical and functional brain connectivity. However, current definitions of modularity for complex networks focus on nonoverlapping clusters, and are seriously limited by disregarding inclusive relationships. Therefore, BFC's modularity has been mainly qualitatively investigated. Here, we introduce a new definition of modularity, based on a recently improved clustering measurement, which overcomes limitations of previous definitions, and apply it to the study of BFC in resting state fMRI of 53 healthy subjects. Results show hierarchical functional modularity in the brain. Copyright 2009 Wiley-Liss, Inc

The BRAIN Initiative: developing technology to catalyse neuroscience discovery

PubMed Central

Jorgenson, Lyric A.; Newsome, William T.; Anderson, David J.; Bargmann, Cornelia I.; Brown, Emery N.; Deisseroth, Karl; Donoghue, John P.; Hudson, Kathy L.; Ling, Geoffrey S. F.; MacLeish, Peter R.; Marder, Eve; Normann, Richard A.; Sanes, Joshua R.; Schnitzer, Mark J.; Sejnowski, Terrence J.; Tank, David W.; Tsien, Roger Y.; Ugurbil, Kamil; Wingfield, John C.

2015-01-01

The evolution of the field of neuroscience has been propelled by the advent of novel technological capabilities, and the pace at which these capabilities are being developed has accelerated dramatically in the past decade. Capitalizing on this momentum, the United States launched the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative to develop and apply new tools and technologies for revolutionizing our understanding of the brain. In this article, we review the scientific vision for this initiative set forth by the National Institutes of Health and discuss its implications for the future of neuroscience research. Particular emphasis is given to its potential impact on the mapping and study of neural circuits, and how this knowledge will transform our understanding of the complexity of the human brain and its diverse array of behaviours, perceptions, thoughts and emotions. PMID:25823863

Quantitative imaging of brain energy metabolisms and neuroenergetics using in vivo X-nuclear 2H, 17O and 31P MRS at ultra-high field.

PubMed

Zhu, Xiao-Hong; Lu, Ming; Chen, Wei

2018-07-01

Brain energy metabolism relies predominantly on glucose and oxygen utilization to generate biochemical energy in the form of adenosine triphosphate (ATP). ATP is essential for maintaining basal electrophysiological activities in a resting brain and supporting evoked neuronal activity under an activated state. Studying complex neuroenergetic processes in the brain requires sophisticated neuroimaging techniques enabling noninvasive and quantitative assessment of cerebral energy metabolisms and quantification of metabolic rates. Recent state-of-the-art in vivo X-nuclear MRS techniques, including 2 H, 17 O and 31 P MRS have shown promise, especially at ultra-high fields, in the quest for understanding neuroenergetics and brain function using preclinical models and in human subjects under healthy and diseased conditions. Copyright © 2018 Elsevier Inc. All rights reserved.

A designed recombinant fusion protein for targeted delivery of siRNA to the mouse brain.

PubMed

Haroon, Mohamed Mohamed; Dar, Ghulam Hassan; Jeyalakshmi, Durga; Venkatraman, Uthra; Saba, Kamal; Rangaraj, Nandini; Patel, Anant Bahadur; Gopal, Vijaya

2016-04-28

RNA interference represents a novel therapeutic approach to modulate several neurodegenerative disease-related genes. However, exogenous delivery of siRNA restricts their transport into different tissues and specifically into the brain mainly due to its large size and the presence of the blood-brain barrier (BBB). To overcome these challenges, we developed here a strategy wherein a peptide known to target specific gangliosides was fused to a double-stranded RNA binding protein to deliver siRNA to the brain parenchyma. The designed fusion protein designated as TARBP-BTP consists of a double-stranded RNA-binding domain (dsRBD) of human Trans Activation response element (TAR) RNA Binding Protein (TARBP2) fused to a brain targeting peptide that binds to monosialoganglioside GM1. Conformation-specific binding of TARBP2 domain to siRNA led to the formation of homogenous serum-stable complex with targeting potential. Further, uptake of the complex in Neuro-2a, IMR32 and HepG2 cells analyzed by confocal microscopy and fluorescence activated cell sorting, revealed selective requirement of GM1 for entry. Remarkably, systemic delivery of the fluorescently labeled complex (TARBP-BTP:siRNA) in ΑβPP-PS1 mouse model of Alzheimer's disease (AD) led to distinctive localization in the cerebral hemisphere. Further, the delivery of siRNA mediated by TARBP-BTP led to significant knockdown of BACE1 in the brain, in both ΑβPP-PS1 mice and wild type C57BL/6. The study establishes the growing importance of fusion proteins in delivering therapeutic siRNA to brain tissues. Copyright © 2016 Elsevier B.V. All rights reserved.

Multiscale neural connectivity during human sensory processing in the brain

NASA Astrophysics Data System (ADS)

Maksimenko, Vladimir A.; Runnova, Anastasia E.; Frolov, Nikita S.; Makarov, Vladimir V.; Nedaivozov, Vladimir; Koronovskii, Alexey A.; Pisarchik, Alexander; Hramov, Alexander E.

2018-05-01

Stimulus-related brain activity is considered using wavelet-based analysis of neural interactions between occipital and parietal brain areas in alpha (8-12 Hz) and beta (15-30 Hz) frequency bands. We show that human sensory processing related to the visual stimuli perception induces brain response resulted in different ways of parieto-occipital interactions in these bands. In the alpha frequency band the parieto-occipital neuronal network is characterized by homogeneous increase of the interaction between all interconnected areas both within occipital and parietal lobes and between them. In the beta frequency band the occipital lobe starts to play a leading role in the dynamics of the occipital-parietal network: The perception of visual stimuli excites the visual center in the occipital area and then, due to the increase of parieto-occipital interactions, such excitation is transferred to the parietal area, where the attentional center takes place. In the case when stimuli are characterized by a high degree of ambiguity, we find greater increase of the interaction between interconnected areas in the parietal lobe due to the increase of human attention. Based on revealed mechanisms, we describe the complex response of the parieto-occipital brain neuronal network during the perception and primary processing of the visual stimuli. The results can serve as an essential complement to the existing theory of neural aspects of visual stimuli processing.

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.

Expression of mRNAs encoding ARPP-16/19, ARPP-21, and DARPP-32 in human brain tissue.

PubMed

Brené, S; Lindefors, N; Ehrlich, M; Taubes, T; Horiuchi, A; Kopp, J; Hall, H; Sedvall, G; Greengard, P; Persson, H

1994-03-01

In this study we have isolated and sequenced human cDNAs for the phosphoproteins DARPP-32, ARPP-21, and ARPP-16/19, and have compared these sequences to previously characterized bovine and rat cDNAs. In situ hybridization and Northern blot analysis with the human cDNA probes were used to study the expression of mRNAs encoding ARPP-16/19, ARPP-21, and DARPP-32 in human postmortem brain tissue. In situ hybridization was performed using horizontal whole hemisphere sections. Five representative levels of the brain ranging from 71 mm to 104 mm ventral to vertex were examined. All three probes showed distinct hybridization patterns in the caudate nucleus, putamen, nucleus accumbens, and the amygdaloid complex. For ARPP-16/19 mRNA, a hybridization signal comparable to the signal in caudate nucleus, putamen, and nucleus accumbens was also detected in the neocortex. ARPP-21 and DARPP-32 mRNA, on the other hand, were present in lower levels in neocortical regions. DARPP-32 mRNA was abundant in the cerebellar cortex at the level of the Purkinje cell layer. High levels of ARPP-16/19 and ARPP-21 mRNA were also found in the cerebellar cortex, where they were confined to deeper layers. The present result demonstrate that mRNAs for the three phosphoproteins are expressed in overlapping, but also distinct, areas of the human brain that in many cases coincide with previously described distribution of the dopamine D1 receptor.

Complex biomarker discovery in neuroimaging data: Finding a needle in a haystack☆

PubMed Central

Atluri, Gowtham; Padmanabhan, Kanchana; Fang, Gang; Steinbach, Michael; Petrella, Jeffrey R.; Lim, Kelvin; MacDonald, Angus; Samatova, Nagiza F.; Doraiswamy, P. Murali; Kumar, Vipin

2013-01-01

Neuropsychiatric disorders such as schizophrenia, bipolar disorder and Alzheimer's disease are major public health problems. However, despite decades of research, we currently have no validated prognostic or diagnostic tests that can be applied at an individual patient level. Many neuropsychiatric diseases are due to a combination of alterations that occur in a human brain rather than the result of localized lesions. While there is hope that newer imaging technologies such as functional and anatomic connectivity MRI or molecular imaging may offer breakthroughs, the single biomarkers that are discovered using these datasets are limited by their inability to capture the heterogeneity and complexity of most multifactorial brain disorders. Recently, complex biomarkers have been explored to address this limitation using neuroimaging data. In this manuscript we consider the nature of complex biomarkers being investigated in the recent literature and present techniques to find such biomarkers that have been developed in related areas of data mining, statistics, machine learning and bioinformatics. PMID:24179856

Basal ganglia systems in ritualistic social displays: reptiles and humans; function and illness.

PubMed

Baxter, Lewis R

2003-08-01

Complex, situation-specific territorial maintenance routines are similar across living terrestrial vertebrates (=amniotes). Decades ago, Paul MacLean et al., at the Laboratory of Brain Evolution and Behavior of the National Institute of Mental Health, postulated that these are evolutionarily conserved behaviors whose expression is mediated by the similarly conserved amniote basal ganglia and related brain systems (BG systems). Therefore, they undertook studies in nonhuman primates and in small social lizards (the common green anole, Anolis carolinensis) to examine this idea. MacLean et al. also postulated that when BG systems misfunction in humans, behavioral abnormalities result, some of them under the rubric of psychiatric illnesses. Obsessive-compulsive disorder (OCD) was singled out as one likely candidate. In the last dozen years, functional brain imaging studies of OCD patients have validated the contention that this is, in fact, a condition involving dysfunctioning BG systems. Inspired by the MacLean group's original investigations, my colleagues and I have now applied related functional imaging techniques in naturalistic experiments using Anolis to better understand BG systems' roles in the mediation of complex behavioral routines in healthy amniotes. Here, I will review this functional imaging work in primates (man, and a little in monkey) and in lizards. I believe the literature not only supports MacLean et al.'s contentions about BG systems and behavior in general, but also validates Paul MacLean's life-long contention that human behavioral medicine can profit from a broad comparative approach.

Pushing spatial and temporal resolution for functional and diffusion MRI in the Human Connectome Project

PubMed Central

Uğurbil, Kamil; Xu, Junqian; Auerbach, Edward J.; Moeller, Steen; Vu, An; Duarte-Carvajalino, Julio M.; Lenglet, Christophe; Wu, Xiaoping; Schmitter, Sebastian; Van de Moortele, Pierre Francois; Strupp, John; Sapiro, Guillermo; De Martino, Federico; Wang, Dingxin; Harel, Noam; Garwood, Michael; Chen, Liyong; Feinberg, David A.; Smith, Stephen M.; Miller, Karla L.; Sotiropoulos, Stamatios N; Jbabdi, Saad; Andersson, Jesper L; Behrens, Timothy EJ; Glasser, Matthew F.; Van Essen, David; Yacoub, Essa

2013-01-01

The human connectome project (HCP) relies primarily on three complementary magnetic resonance (MR) methods. These are: 1) resting state functional MR imaging (rfMRI) which uses correlations in the temporal fluctuations in an fMRI time series to deduce ‘functional connectivity’; 2) diffusion imaging (dMRI), which provides the input for tractography algorithms used for the reconstruction of the complex axonal fiber architecture; and 3) task based fMRI (tfMRI), which is employed to identify functional parcellation in the human brain in order to assist analyses of data obtained with the first two methods. We describe technical improvements and optimization of these methods as well as instrumental choices that impact speed of acquisition of fMRI and dMRI images at 3 Tesla, leading to whole brain coverage with 2 mm isotropic resolution in 0.7 second for fMRI, and 1.25 mm isotropic resolution dMRI data for tractography analysis with three-fold reduction in total data acquisition time. Ongoing technical developments and optimization for acquisition of similar data at 7 Tesla magnetic field are also presented, targeting higher resolution, specificity of functional imaging signals, mitigation of the inhomogeneous radio frequency (RF) fields and power deposition. Results demonstrate that overall, these approaches represent a significant advance in MR imaging of the human brain to investigate brain function and structure. PMID:23702417

Analysis of dual tree M-band wavelet transform based features for brain image classification.

PubMed

Ayalapogu, Ratna Raju; Pabboju, Suresh; Ramisetty, Rajeswara Rao

2018-04-29

The most complex organ in the human body is the brain. The unrestrained growth of cells in the brain is called a brain tumor. The cause of a brain tumor is still unknown and the survival rate is lower than other types of cancers. Hence, early detection is very important for proper treatment. In this study, an efficient computer-aided diagnosis (CAD) system is presented for brain image classification by analyzing MRI of the brain. At first, the MRI brain images of normal and abnormal categories are modeled by using the statistical features of dual tree m-band wavelet transform (DTMBWT). A maximum margin classifier, support vector machine (SVM) is then used for the classification and validated with k-fold approach. Results show that the system provides promising results on a repository of molecular brain neoplasia data (REMBRANDT) with 97.5% accuracy using 4 th level statistical features of DTMBWT. Viewing the experimental results, we conclude that the system gives a satisfactory performance for the brain image classification. © 2018 International Society for Magnetic Resonance in Medicine.

Sleep Deprivation Impairs the Human Central and Peripheral Nervous System Discrimination of Social Threat

PubMed Central

Goldstein-Piekarski, Andrea N.; Greer, Stephanie M.; Saletin, Jared M.

2015-01-01

Facial expressions represent one of the most salient cues in our environment. They communicate the affective state and intent of an individual and, if interpreted correctly, adaptively influence the behavior of others in return. Processing of such affective stimuli is known to require reciprocal signaling between central viscerosensory brain regions and peripheral-autonomic body systems, culminating in accurate emotion discrimination. Despite emerging links between sleep and affective regulation, the impact of sleep loss on the discrimination of complex social emotions within and between the CNS and PNS remains unknown. Here, we demonstrate in humans that sleep deprivation impairs both viscerosensory brain (anterior insula, anterior cingulate cortex, amygdala) and autonomic-cardiac discrimination of threatening from affiliative facial cues. Moreover, sleep deprivation significantly degrades the normally reciprocal associations between these central and peripheral emotion-signaling systems, most prominent at the level of cardiac-amygdala coupling. In addition, REM sleep physiology across the sleep-rested night significantly predicts the next-day success of emotional discrimination within this viscerosensory network across individuals, suggesting a role for REM sleep in affective brain recalibration. Together, these findings establish that sleep deprivation compromises the faithful signaling of, and the “embodied” reciprocity between, viscerosensory brain and peripheral autonomic body processing of complex social signals. Such impairments hold ecological relevance in professional contexts in which the need for accurate interpretation of social cues is paramount yet insufficient sleep is pervasive. PMID:26180190

Sleep Deprivation Impairs the Human Central and Peripheral Nervous System Discrimination of Social Threat.

PubMed

Goldstein-Piekarski, Andrea N; Greer, Stephanie M; Saletin, Jared M; Walker, Matthew P

2015-07-15

Facial expressions represent one of the most salient cues in our environment. They communicate the affective state and intent of an individual and, if interpreted correctly, adaptively influence the behavior of others in return. Processing of such affective stimuli is known to require reciprocal signaling between central viscerosensory brain regions and peripheral-autonomic body systems, culminating in accurate emotion discrimination. Despite emerging links between sleep and affective regulation, the impact of sleep loss on the discrimination of complex social emotions within and between the CNS and PNS remains unknown. Here, we demonstrate in humans that sleep deprivation impairs both viscerosensory brain (anterior insula, anterior cingulate cortex, amygdala) and autonomic-cardiac discrimination of threatening from affiliative facial cues. Moreover, sleep deprivation significantly degrades the normally reciprocal associations between these central and peripheral emotion-signaling systems, most prominent at the level of cardiac-amygdala coupling. In addition, REM sleep physiology across the sleep-rested night significantly predicts the next-day success of emotional discrimination within this viscerosensory network across individuals, suggesting a role for REM sleep in affective brain recalibration. Together, these findings establish that sleep deprivation compromises the faithful signaling of, and the "embodied" reciprocity between, viscerosensory brain and peripheral autonomic body processing of complex social signals. Such impairments hold ecological relevance in professional contexts in which the need for accurate interpretation of social cues is paramount yet insufficient sleep is pervasive. Copyright © 2015 the authors 0270-6474/15/3510135-11$15.00/0.

The Agent Brain: A Review of Non-invasive Brain Stimulation Studies on Sensing Agency.

PubMed

Crivelli, Davide; Balconi, Michela

2017-01-01

According to philosophy of mind and neuroscientific models, the sense of agency can be defined as the sense that I am the one that is generating an action and causing its effects. Such ability to sense ourselves as causal agents is critical for the definition of intentional behavior and is a primary root for human interaction skills. The present mini-review aims at discussing evidences from non-invasive brain stimulation (NIBS) studies targeting functional correlates of different aspects of agency and evidences on the way stimulation techniques affect such core feature of human subjective experience. Clinical and brain imaging studies helped in defining a neural network mediating agency-related processes, which includes the dorsolateral prefrontal cortex (dlPFC), the cingulate cortex (CC), the supplementary and pre-supplementary motor areas (SMA and pre-SMA), the posterior parietal cortex (PPC) and its inferior regions and the cerebellum. However, while the plurality of those structures mirrors the complexity of the phenomenon, their actual roles with respect to different components of the experience of agency have been primarily explored via correlational techniques, without a clear evidence about their causal significance with respect to the integration of sensorimotor information, intentionalization, and action monitoring processes. Therefore, insights into the specific causal role of different cortical structures can be specified by using NIBS techniques, in order to provide improved understanding into the bases of our ability vs. inability to properly act in complex social contexts.

Continuous monitoring of brain dynamics with functional near infrared spectroscopy as a tool for neuroergonomic research: empirical examples and a technological development

PubMed Central

Ayaz, Hasan; Onaral, Banu; Izzetoglu, Kurtulus; Shewokis, Patricia A.; McKendrick, Ryan; Parasuraman, Raja

2013-01-01

Functional near infrared spectroscopy (fNIRS) is a non-invasive, safe, and portable optical neuroimaging method that can be used to assess brain dynamics during skill acquisition and performance of complex work and everyday tasks. In this paper we describe neuroergonomic studies that illustrate the use of fNIRS in the examination of training-related brain dynamics and human performance assessment. We describe results of studies investigating cognitive workload in air traffic controllers, acquisition of dual verbal-spatial working memory skill, and development of expertise in piloting unmanned vehicles. These studies used conventional fNIRS devices in which the participants were tethered to the device while seated at a workstation. Consistent with the aims of mobile brain imaging (MoBI), we also describe a compact and battery-operated wireless fNIRS system that performs with similar accuracy as other established fNIRS devices. Our results indicate that both wired and wireless fNIRS systems allow for the examination of brain function in naturalistic settings, and thus are suitable for reliable human performance monitoring and training assessment. PMID:24385959

A speed limit for evolution.

PubMed

Worden, R P

1995-09-07

An upper bound on the speed of evolution is derived. The bound concerns the amount of genetic information which is expressed in observable ways in various aspects of the phenotype. The genetic information expressed in some part of the phenotype of a species cannot increase faster than a given rate, determined by the selection pressure on that part. This rate is typically a small fraction of a bit per generation. Total expressed genetic information cannot increase faster than a species-specific rate--typically a few bits per generation. These bounds apply to all aspects of the phenotype, but are particularly relevant to cognition. As brains are highly complex, we expect large amounts of expressed genetic information in the brain--of the order of 100 kilobytes--yet evolutionary changes in brain genetic information are only a fraction of a bit per generation. This has important consequences for cognitive evolution. The limit implies that the human brain differs from the chimpanzee brain by at most 5 kilobytes of genetic design information. This is not enough to define a Language Acquisition Device, unless it depends heavily on pre-existing primate symbolic cognition. Subject to the evolutionary speed limit, in changing environments a simple, modular brain architecture is fitter than more complex ones. This encourages us to look for simplicity in brain design, rather than expecting the brain to be a patchwork of ad hoc adaptations. The limit implies that pure species selection is not an important mechanism of evolutionary change.

Task-Related Edge Density (TED)—A New Method for Revealing Dynamic Network Formation in fMRI Data of the Human Brain

PubMed Central

Lohmann, Gabriele; Stelzer, Johannes; Zuber, Verena; Buschmann, Tilo; Margulies, Daniel; Bartels, Andreas; Scheffler, Klaus

2016-01-01

The formation of transient networks in response to external stimuli or as a reflection of internal cognitive processes is a hallmark of human brain function. However, its identification in fMRI data of the human brain is notoriously difficult. Here we propose a new method of fMRI data analysis that tackles this problem by considering large-scale, task-related synchronisation networks. Networks consist of nodes and edges connecting them, where nodes correspond to voxels in fMRI data, and the weight of an edge is determined via task-related changes in dynamic synchronisation between their respective times series. Based on these definitions, we developed a new data analysis algorithm that identifies edges that show differing levels of synchrony between two distinct task conditions and that occur in dense packs with similar characteristics. Hence, we call this approach “Task-related Edge Density” (TED). TED proved to be a very strong marker for dynamic network formation that easily lends itself to statistical analysis using large scale statistical inference. A major advantage of TED compared to other methods is that it does not depend on any specific hemodynamic response model, and it also does not require a presegmentation of the data for dimensionality reduction as it can handle large networks consisting of tens of thousands of voxels. We applied TED to fMRI data of a fingertapping and an emotion processing task provided by the Human Connectome Project. TED revealed network-based involvement of a large number of brain areas that evaded detection using traditional GLM-based analysis. We show that our proposed method provides an entirely new window into the immense complexity of human brain function. PMID:27341204

Task-Related Edge Density (TED)-A New Method for Revealing Dynamic Network Formation in fMRI Data of the Human Brain.

PubMed

Lohmann, Gabriele; Stelzer, Johannes; Zuber, Verena; Buschmann, Tilo; Margulies, Daniel; Bartels, Andreas; Scheffler, Klaus

2016-01-01

The formation of transient networks in response to external stimuli or as a reflection of internal cognitive processes is a hallmark of human brain function. However, its identification in fMRI data of the human brain is notoriously difficult. Here we propose a new method of fMRI data analysis that tackles this problem by considering large-scale, task-related synchronisation networks. Networks consist of nodes and edges connecting them, where nodes correspond to voxels in fMRI data, and the weight of an edge is determined via task-related changes in dynamic synchronisation between their respective times series. Based on these definitions, we developed a new data analysis algorithm that identifies edges that show differing levels of synchrony between two distinct task conditions and that occur in dense packs with similar characteristics. Hence, we call this approach "Task-related Edge Density" (TED). TED proved to be a very strong marker for dynamic network formation that easily lends itself to statistical analysis using large scale statistical inference. A major advantage of TED compared to other methods is that it does not depend on any specific hemodynamic response model, and it also does not require a presegmentation of the data for dimensionality reduction as it can handle large networks consisting of tens of thousands of voxels. We applied TED to fMRI data of a fingertapping and an emotion processing task provided by the Human Connectome Project. TED revealed network-based involvement of a large number of brain areas that evaded detection using traditional GLM-based analysis. We show that our proposed method provides an entirely new window into the immense complexity of human brain function.

The enchanted loom. [Book on evolution of intelligence

NASA Technical Reports Server (NTRS)

Jastrow, R.

1981-01-01

The evolution of intelligence began with the movement of Crossopterygian fish onto land. The eventual appearance of large dinosaurs eliminated all but the smallest of mammalian creatures, with the survivors forced to move only nocturnally, when enhanced olfactory and aural faculties were favored and involved a larger grey matter/body mass ratio than possessed by the dinosaurs. Additionally, the mammals made comparisons between the inputs of various senses, implying the presence of significant memory capacity and an ability to abstract survival information. More complex behavior occurred with the advent of tree dwellers (forward-looking eyes), hands, color vision, and the ability to grip and manipulate objects. An extra pound of brain evolved in the human skull in less than a million years. The neural processes that can lead to an action by a creature with a brain are mimicked by the basic AND and OR gates in computers, which are rapidly approaching the circuit density of the human brain. It is suggested that humans will eventually produce computers of higher intelligence than people possess, and computer spacecraft, alive in an electronic sense, will travel outward to explore the universe.

Hypnosis and imaging of the living human brain.

PubMed

Landry, Mathieu; Raz, Amir

2015-01-01

Over more than two decades, studies using imaging techniques of the living human brain have begun to explore the neural correlates of hypnosis. The collective findings provide a gripping, albeit preliminary, account of the underlying neurobiological mechanisms involved in hypnotic phenomena. While substantial advances lend support to different hypotheses pertaining to hypnotic modulation of attention, control, and monitoring processes, the complex interactions among the many mediating variables largely hinder our ability to isolate robust commonalities across studies. The present account presents a critical integrative synthesis of neuroimaging studies targeting hypnosis as a function of suggestion. Specifically, hypnotic induction without task-specific suggestion is examined, as well as suggestions concerning sensation and perception, memory, and ideomotor response. The importance of carefully designed experiments is highlighted to better tease apart the neural correlates that subserve hypnotic phenomena. Moreover, converging findings intimate that hypnotic suggestions seem to induce specific neural patterns. These observations propose that suggestions may have the ability to target focal brain networks. Drawing on evidence spanning several technological modalities, neuroimaging studies of hypnosis pave the road to a more scientific understanding of a dramatic, yet largely evasive, domain of human behavior.

HDAC6 Brain Mapping with [ 18 F]Bavarostat Enabled by a Ru-Mediated Deoxyfluorination

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

Strebl, Martin G.; Campbell, Arthur J.; Zhao, Wen -Ning

Histone deacetylase 6 (HDAC6) function and dysregulation have been implicated in the etiology of certain cancers and more recently in central nervous system (CNS) disorders including Rett syndrome, Alzheimer’s and Parkinson’s diseases, and major depressive disorder. HDAC6-selective inhibitors have therapeutic potential, but in the CNS drug space the development of highly brain penetrant HDAC inhibitors has been a persistent challenge. Moreover, no tool exists to directly characterize HDAC6 and its related biology in the living human brain. Here, we report a highly brain penetrant HDAC6 inhibitor, Bavarostat, that exhibits excellent HDAC6 selectivity (>80-fold over all other Zn-containing HDAC paralogues), modulatesmore » tubulin acetylation selectively over histone acetylation, and has excellent brain penetrance. We further demonstrate that Bavarostat can be radiolabeled with 18F by deoxyfluorination through in situ formation of a ruthenium π-complex of the corresponding phenol precursor: the only method currently suitable for synthesis of [ 18F]Bavarostat. In conclusion, by using [ 18F]Bavarostat in a series of rodent and nonhuman primate imaging experiments, we demonstrate its utility for mapping HDAC6 in the living brain, which sets the stage for first-in-human neurochemical imaging of this important target.« less

HDAC6 Brain Mapping with [ 18 F]Bavarostat Enabled by a Ru-Mediated Deoxyfluorination

DOE PAGES

Strebl, Martin G.; Campbell, Arthur J.; Zhao, Wen -Ning; ...

2017-09-06

Histone deacetylase 6 (HDAC6) function and dysregulation have been implicated in the etiology of certain cancers and more recently in central nervous system (CNS) disorders including Rett syndrome, Alzheimer’s and Parkinson’s diseases, and major depressive disorder. HDAC6-selective inhibitors have therapeutic potential, but in the CNS drug space the development of highly brain penetrant HDAC inhibitors has been a persistent challenge. Moreover, no tool exists to directly characterize HDAC6 and its related biology in the living human brain. Here, we report a highly brain penetrant HDAC6 inhibitor, Bavarostat, that exhibits excellent HDAC6 selectivity (>80-fold over all other Zn-containing HDAC paralogues), modulatesmore » tubulin acetylation selectively over histone acetylation, and has excellent brain penetrance. We further demonstrate that Bavarostat can be radiolabeled with 18F by deoxyfluorination through in situ formation of a ruthenium π-complex of the corresponding phenol precursor: the only method currently suitable for synthesis of [ 18F]Bavarostat. In conclusion, by using [ 18F]Bavarostat in a series of rodent and nonhuman primate imaging experiments, we demonstrate its utility for mapping HDAC6 in the living brain, which sets the stage for first-in-human neurochemical imaging of this important target.« less

Neuromodulation: Selected approaches and challenges

PubMed Central

Parpura, Vladimir; Silva, Gabriel A.; Tass, Peter A.; Bennet, Kevin E.; Meyyappan, Meyya; Koehne, Jessica; Lee, Kendall H.; Andrews, Russell J.

2012-01-01

The brain operates through complex interactions in the flow of information and signal processing within neural networks. The “wiring” of such networks, being neuronal or glial, can physically and/or functionally go rogue in various pathological states. Neuromodulation, as a multidisciplinary venture, attempts to correct such faulty nets. In this review, selected approaches and challenges in neuromoduation are discussed. The use of water-dispersible carbon nanotubes have proven effective in modulation of neurite outgrowth in culture as well as in aiding regeneration after spinal cord injury in vivo. Studying neural circuits using computational biology and analytical engineering approaches brings to light geometrical mapping of dynamics within neural networks, much needed information for stimulation interventions in medical practice. Indeed, sophisticated desynchronization approaches used for brain stimulation have been successful in coaxing “misfiring” neuronal circuits to resume productive firing patterns in various human disorders. Devices have been developed for the real time measurement of various neurotransmitters as well as electrical activity in the human brain during electrical deep brain stimulation. Such devices can establish the dynamics of electrochemical changes in the brain during stimulation. With increasing application of nanomaterials in devices for electrical and chemical recording and stimulating in the brain, the era of cellular, and even intracellular, precision neuromodulation will soon be upon us. PMID:23190025

Parametric fMRI analysis of visual encoding in the human medial temporal lobe.

PubMed

Rombouts, S A; Scheltens, P; Machielson, W C; Barkhof, F; Hoogenraad, F G; Veltman, D J; Valk, J; Witter, M P

1999-01-01

A number of functional brain imaging studies indicate that the medial temporal lobe system is crucially involved in encoding new information into memory. However, most studies were based on differences in brain activity between encoding of familiar vs. novel stimuli. To further study the underlying cognitive processes, we applied a parametric design of encoding. Seven healthy subjects were instructed to encode complex color pictures into memory. Stimuli were presented in a parametric fashion at different rates, thus representing different loads of encoding. Functional magnetic resonance imaging (fMRI) was used to assess changes in brain activation. To determine the number of pictures successfully stored into memory, recognition scores were determined afterwards. During encoding, brain activation occurred in the medial temporal lobe, comparable to the results obtained by others. Increasing the encoding load resulted in an increase in the number of successfully stored items. This was reflected in a significant increase in brain activation in the left lingual gyrus, in the left and right parahippocampal gyrus, and in the right inferior frontal gyrus. This study shows that fMRI can detect changes in brain activation during variation of one aspect of higher cognitive tasks. Further, it strongly supports the notion that the human medial temporal lobe is involved in encoding novel visual information into memory.

Can modular psychological concepts like affect and emotion be assigned to a distinct subset of regional neural circuits?. Comment on "The quartet theory of human emotions: An integrative and neurofunctional model" by S. Koelsch et al.

NASA Astrophysics Data System (ADS)

Fehr, Thorsten; Herrmann, Manfred

2015-06-01

The proposed Quartet Theory of Human Emotions by Koelsch and co-workers [11] adumbrates evidence from various scientific sources to integrate and assign the psychological concepts of 'affect' and 'emotion' to four brain circuits or to four neuronal core systems for affect-processing in the brain. The authors differentiate between affect and emotion and assign several facultative, or to say modular, psychological domains and principles of information processing, such as learning and memory, antecedents of affective activity, emotion satiation, cognitive complexity, subjective quality feelings, degree of conscious appraisal, to different affect systems. Furthermore, they relate orbito-frontal brain structures to moral affects as uniquely human, and the hippocampus to attachment-related affects. An additional feature of the theory describes 'emotional effector-systems' for motor-related processes (e.g., emotion-related actions), physiological arousal, attention and memory that are assumed to be cross-linked with the four proposed affect systems. Thus, higher principles of emotional information processing, but also modular affect-related issues, such as moral and attachment related affects, are thought to be handled by these four different physiological sub-systems that are on the other side assumed to be highly interwoven at both physiological and functional levels. The authors also state that the proposed sub-systems have many features in common, such as the selection and modulation of biological processes related to behaviour, perception, attention and memory. The latter aspect challenges an ongoing discussion about the mind-body problem: To which degree do the proposed sub-systems 'sufficiently' cover the processing of complex modular or facultative emotional/affective and/or cognitive phenomena? There are current models and scientific positions that almost completely reject the idea that modular psychological phenomena are handled by a distinct selection of regional brain systems or neural modules, but rather suggest highly complex and cross-linked neural networks individually shaped by livelong learning and experience [e.g., 6,7,10,13]. This holds in particular true for complex emotional phenomena such as aggression or empathy in social interaction [8,13]. It thus remains questionable, whether - beyond primary sensory and motor-processing - a small number of modular sub-systems sufficiently cover the organisation of specific phenomenological and social features of perception and behaviour [7,10].

A model for brain life history evolution.

PubMed

González-Forero, Mauricio; Faulwasser, Timm; Lehmann, Laurent

2017-03-01

Complex cognition and relatively large brains are distributed across various taxa, and many primarily verbal hypotheses exist to explain such diversity. Yet, mathematical approaches formalizing verbal hypotheses would help deepen the understanding of brain and cognition evolution. With this aim, we combine elements of life history and metabolic theories to formulate a metabolically explicit mathematical model for brain life history evolution. We assume that some of the brain's energetic expense is due to production (learning) and maintenance (memory) of energy-extraction skills (or cognitive abilities, knowledge, information, etc.). We also assume that individuals use such skills to extract energy from the environment, and can allocate this energy to grow and maintain the body, including brain and reproductive tissues. The model can be used to ask what fraction of growth energy should be allocated at each age, given natural selection, to growing brain and other tissues under various biological settings. We apply the model to find uninvadable allocation strategies under a baseline setting ("me vs nature"), namely when energy-extraction challenges are environmentally determined and are overcome individually but possibly with maternal help, and use modern-human data to estimate model's parameter values. The resulting uninvadable strategies yield predictions for brain and body mass throughout ontogeny and for the ages at maturity, adulthood, and brain growth arrest. We find that: (1) a me-vs-nature setting is enough to generate adult brain and body mass of ancient human scale and a sequence of childhood, adolescence, and adulthood stages; (2) large brains are favored by intermediately challenging environments, moderately effective skills, and metabolically expensive memory; and (3) adult skill is proportional to brain mass when metabolic costs of memory saturate the brain metabolic rate allocated to skills.

Task complexity, posture, age, sex: which is the main factor influencing manual laterality in captive Cercocebus torquatus torquatus?

PubMed

Laurence, Agathe; Wallez, Catherine; Blois-Heulin, Catherine

2011-09-01

Behavioural asymmetries reflect brain asymmetry in nonhuman primates (NHP) as in humans. By investigating manual laterality, researchers can study the evolution of brain hemisphere specialisation. Three dominant theories aim to establish an evolutionary scenario. The most recent theory relates different levels of manual laterality to task complexity. Our investigation aimed to evaluate the importance of two extrinsic factors (posture and the need for manual coordination) and two intrinsic factors (age and sex) on the expression of manual laterality by red-capped mangabeys. We observed 19 captive-born mangabeys, in spontaneous situations and under experimental conditions (seven experimental tasks varying in complexity). No directionality was observed in hand preference at the group level whatever the task. But our data revealed an effect of task complexity: more subjects were lateralised than not lateralised for the bipedal task and for the three most complex tasks. Finally, we evidenced an age and a sex effect. We compare our results with data for several other primate species and discuss them in the light of different manual laterality theories.

Complexity measures of music

NASA Astrophysics Data System (ADS)

Pease, April; Mahmoodi, Korosh; West, Bruce J.

2018-03-01

We present a technique to search for the presence of crucial events in music, based on the analysis of the music volume. Earlier work on this issue was based on the assumption that crucial events correspond to the change of music notes, with the interesting result that the complexity index of the crucial events is mu ~ 2, which is the same inverse power-law index of the dynamics of the brain. The search technique analyzes music volume and confirms the results of the earlier work, thereby contributing to the explanation as to why the brain is sensitive to music, through the phenomenon of complexity matching. Complexity matching has recently been interpreted as the transfer of multifractality from one complex network to another. For this reason we also examine the mulifractality of music, with the observation that the multifractal spectrum of a computer performance is significantly narrower than the multifractal spectrum of a human performance of the same musical score. We conjecture that although crucial events are demonstrably important for information transmission, they alone are not suficient to define musicality, which is more adequately measured by the multifractality spectrum.

The Missing Link: Context Loss in Online Databases

ERIC Educational Resources Information Center

Mi, Jia; Nesta, Frederick

2005-01-01

Full-text databases do not allow for the complexity of the interaction of the human eye and brain with printed matter. As a result, both content and context may be lost. The authors propose additional indexing fields that would maintain the content and context of print in electronic formats.

Culturally Appropriate Education: Insights from Educational Neuroscience

ERIC Educational Resources Information Center

Zhou, Jiaxian; Fischer, Kurt W.

2013-01-01

Culturally appropriate education focuses on educational competence needed in a global world and respect for different world views of learners and teachers from different cultural contexts. The relationship between gene, brain, and culture is complex and dynamical. Cultural experience and learning sculpts the anatomy and function of the human brain…

Neuroscience, Education and Mental Health

ERIC Educational Resources Information Center

Arboccó de los Heros, Manuel

2016-01-01

The following article presents a series of investigations, reflections, and quotes about neuroscience, education, and psychology. Each area is specialized in some matters but at some point they share territory and mutually benefit one another, and help us to increasingly understand the complex world of learning, the brain, and human behavior. We…

Neurophysiological Factors in Human Information Processing Capacity

ERIC Educational Resources Information Center

Ramsey, Nick F.; Jansma, J. M.; Jager, G.; Van Raalten, T.; Kahn, R. S.

2004-01-01

What determines how well an individual can manage the complexity of information processing demands when several tasks have to be executed simultaneously? Various theoretical frameworks address the mechanisms of information processing and the changes that take place when processes become automated, and brain regions involved in various types of…

Asymmetry of the Brain: Development and Implications.

PubMed

Duboc, Véronique; Dufourcq, Pascale; Blader, Patrick; Roussigné, Myriam

2015-01-01

Although the left and right hemispheres of our brains develop with a high degree of symmetry at both the anatomical and functional levels, it has become clear that subtle structural differences exist between the two sides and that each is dominant in processing specific cognitive tasks. As the result of evolutionary conservation or convergence, lateralization of the brain is found in both vertebrates and invertebrates, suggesting that it provides significant fitness for animal life. This widespread feature of hemispheric specialization has allowed the emergence of model systems to study its development and, in some cases, to link anatomical asymmetries to brain function and behavior. Here, we present some of what is known about brain asymmetry in humans and model organisms as well as what is known about the impact of environmental and genetic factors on brain asymmetry development. We specifically highlight the progress made in understanding the development of epithalamic asymmetries in zebrafish and how this model provides an exciting opportunity to address brain asymmetry at different levels of complexity.

Alkaline Ceramidase 3 Deficiency Results in Purkinje Cell Degeneration and Cerebellar Ataxia Due to Dyshomeostasis of Sphingolipids in the Brain

PubMed Central

Preston, Chet; Wang, Louis; Yi, Jae Kyo; Lin, Chih-Li; Sun, Wei; Spyropoulos, Demetri D.; Rhee, Soyoung; Li, Mingsong; Zhou, Jie; Ge, Shaoyu; Zhang, Guofeng; Snider, Ashley J.; Hannun, Yusuf A.; Obeid, Lina M.; Mao, Cungui

2015-01-01

Dyshomeostasis of both ceramides and sphingosine-1-phosphate (S1P) in the brain has been implicated in aging-associated neurodegenerative disorders in humans. However, mechanisms that maintain the homeostasis of these bioactive sphingolipids in the brain remain unclear. Mouse alkaline ceramidase 3 (Acer3), which preferentially catalyzes the hydrolysis of C18:1-ceramide, a major unsaturated long-chain ceramide species in the brain, is upregulated with age in the mouse brain. Acer3 knockout causes an age-dependent accumulation of various ceramides and C18:1-monohexosylceramide and abolishes the age-related increase in the levels of sphingosine and S1P in the brain; thereby resulting in Purkinje cell degeneration in the cerebellum and deficits in motor coordination and balance. Our results indicate that Acer3 plays critically protective roles in controlling the homeostasis of various sphingolipids, including ceramides, sphingosine, S1P, and certain complex sphingolipids in the brain and protects Purkinje cells from premature degeneration. PMID:26474409

A chronological expression profile of gene activity during embryonic mouse brain development.

PubMed

Goggolidou, P; Soneji, S; Powles-Glover, N; Williams, D; Sethi, S; Baban, D; Simon, M M; Ragoussis, I; Norris, D P

2013-12-01

The brain is a functionally complex organ, the patterning and development of which are key to adult health. To help elucidate the genetic networks underlying mammalian brain patterning, we conducted detailed transcriptional profiling during embryonic development of the mouse brain. A total of 2,400 genes were identified as showing differential expression between three developmental stages. Analysis of the data identified nine gene clusters to demonstrate analogous expression profiles. A significant group of novel genes of as yet undiscovered biological function were detected as being potentially relevant to brain development and function, in addition to genes that have previously identified roles in the brain. Furthermore, analysis for genes that display asymmetric expression between the left and right brain hemispheres during development revealed 35 genes as putatively asymmetric from a combined data set. Our data constitute a valuable new resource for neuroscience and neurodevelopment, exposing possible functional associations between genes, including novel loci, and encouraging their further investigation in human neurological and behavioural disorders.

Foundations for a new science of learning.

PubMed

Meltzoff, Andrew N; Kuhl, Patricia K; Movellan, Javier; Sejnowski, Terrence J

2009-07-17

Human learning is distinguished by the range and complexity of skills that can be learned and the degree of abstraction that can be achieved compared with those of other species. Homo sapiens is also the only species that has developed formal ways to enhance learning: teachers, schools, and curricula. Human infants have an intense interest in people and their behavior and possess powerful implicit learning mechanisms that are affected by social interaction. Neuroscientists are beginning to understand the brain mechanisms underlying learning and how shared brain systems for perception and action support social learning. Machine learning algorithms are being developed that allow robots and computers to learn autonomously. New insights from many different fields are converging to create a new science of learning that may transform educational practices.

Pro-necrotic Activity of Cationic Mastoparan Peptides in Human Glioblastoma Multiforme Cells Via Membranolytic Action.

PubMed

da Silva, Annielle Mendes Brito; Silva-Gonçalves, Laíz Costa; Oliveira, Fernando Augusto; Arcisio-Miranda, Manoel

2018-07-01

Glioblastoma multiforme is the most common and lethal malignant brain tumor. Because of its complexity and heterogeneity, this tumor has become resistant to conventional therapies and the available treatment produces multiple side effects. Here, using multiple experimental approaches, we demonstrate that three mastoparan peptides-Polybia-MP1, Mastoparan X, and HR1-from solitary wasp venom exhibit potent anticancer activity toward human glioblastoma multiforme cells. Importantly, the antiglioblastoma action of mastoparan peptides occurs by membranolytic activity, leading to necrosis. Our data also suggest a direct relation between mastoparan membranolytic potency and the presence of negatively charged phospholipids like phosphatidylserine. Collectively, these data may warrant additional studies for mastoparan peptides as new agents for the treatment of glioblastoma multiforme brain tumor.

Localization of mRNA for CHRNA7 in human fetal brain.

PubMed

Agulhon, C; Abitbol, M; Bertrand, D; Malafosse, A

1999-08-02

The aim of this study was to determine the regional distribution in situ of the mRNA for the alpha 7 subunit of the neuronal nicotinic acetylcholine receptor in human fetal brain. We found high levels of alpha 7 gene expression in nuclei that receive sensory information, such as those of the neocortex and hippocampus, the thalamic nuclei, the reticular thalamic nucleus, the pontine nuclei and the superior olive complex. These data support a possible regulatory function for alpha 7-containing receptors in sensory processing, which may be involved in the pathological physiology of schizophrenia and autism. Early alpha 7 gene expression is also consistent with a morphogenetic role for alpha 7 receptors in central nervous system development.

Common genetic variants influence human subcortical brain structures

PubMed Central

Hibar, Derrek P.; Stein, Jason L.; Renteria, Miguel E.; Arias-Vasquez, Alejandro; Desrivières, Sylvane; Jahanshad, Neda; Toro, Roberto; Wittfeld, Katharina; Abramovic, Lucija; Andersson, Micael; Aribisala, Benjamin S.; Armstrong, Nicola J.; Bernard, Manon; Bohlken, Marc M.; Boks, Marco P.; Bralten, Janita; Brown, Andrew A.; Chakravarty, M. Mallar; Chen, Qiang; Ching, Christopher R. K.; Cuellar-Partida, Gabriel; den Braber, Anouk; Giddaluru, Sudheer; Goldman, Aaron L.; Grimm, Oliver; Guadalupe, Tulio; Hass, Johanna; Woldehawariat, Girma; Holmes, Avram J.; Hoogman, Martine; Janowitz, Deborah; Jia, Tianye; Kim, Sungeun; Klein, Marieke; Kraemer, Bernd; Lee, Phil H.; Olde Loohuis, Loes M.; Luciano, Michelle; Macare, Christine; Mather, Karen A.; Mattheisen, Manuel; Milaneschi, Yuri; Nho, Kwangsik; Papmeyer, Martina; Ramasamy, Adaikalavan; Risacher, Shannon L.; Roiz-Santiañez, Roberto; Rose, Emma J.; Salami, Alireza; Sämann, Philipp G.; Schmaal, Lianne; Schork, Andrew J.; Shin, Jean; Strike, Lachlan T.; Teumer, Alexander; van Donkelaar, Marjolein M. J.; van Eijk, Kristel R.; Walters, Raymond K.; Westlye, Lars T.; Whelan, Christopher D.; Winkler, Anderson M.; Zwiers, Marcel P.; Alhusaini, Saud; Athanasiu, Lavinia; Ehrlich, Stefan; Hakobjan, Marina M. H.; Hartberg, Cecilie B.; Haukvik, Unn K.; Heister, Angelien J. G. A. M.; Hoehn, David; Kasperaviciute, Dalia; Liewald, David C. M.; Lopez, Lorna M.; Makkinje, Remco R. R.; Matarin, Mar; Naber, Marlies A. M.; McKay, D. Reese; Needham, Margaret; Nugent, Allison C.; Pütz, Benno; Royle, Natalie A.; Shen, Li; Sprooten, Emma; Trabzuni, Daniah; van der Marel, Saskia S. L.; van Hulzen, Kimm J. E.; Walton, Esther; Wolf, Christiane; Almasy, Laura; Ames, David; Arepalli, Sampath; Assareh, Amelia A.; Bastin, Mark E.; Brodaty, Henry; Bulayeva, Kazima B.; Carless, Melanie A.; Cichon, Sven; Corvin, Aiden; Curran, Joanne E.; Czisch, Michael; de Zubicaray, Greig I.; Dillman, Allissa; Duggirala, Ravi; Dyer, Thomas D.; Erk, Susanne; Fedko, Iryna O.; Ferrucci, Luigi; Foroud, Tatiana M.; Fox, Peter T.; Fukunaga, Masaki; Gibbs, J. Raphael; Göring, Harald H. H.; Green, Robert C.; Guelfi, Sebastian; Hansell, Narelle K.; Hartman, Catharina A.; Hegenscheid, Katrin; Heinz, Andreas; Hernandez, Dena G.; Heslenfeld, Dirk J.; Hoekstra, Pieter J.; Holsboer, Florian; Homuth, Georg; Hottenga, Jouke-Jan; Ikeda, Masashi; Jack, Clifford R.; Jenkinson, Mark; Johnson, Robert; Kanai, Ryota; Keil, Maria; Kent, Jack W.; Kochunov, Peter; Kwok, John B.; Lawrie, Stephen M.; Liu, Xinmin; Longo, Dan L.; McMahon, Katie L.; Meisenzahl, Eva; Melle, Ingrid; Mohnke, Sebastian; Montgomery, Grant W.; Mostert, Jeanette C.; Mühleisen, Thomas W.; Nalls, Michael A.; Nichols, Thomas E.; Nilsson, Lars G.; Nöthen, Markus M.; Ohi, Kazutaka; Olvera, Rene L.; Perez-Iglesias, Rocio; Pike, G. Bruce; Potkin, Steven G.; Reinvang, Ivar; Reppermund, Simone; Rietschel, Marcella; Romanczuk-Seiferth, Nina; Rosen, Glenn D.; Rujescu, Dan; Schnell, Knut; Schofield, Peter R.; Smith, Colin; Steen, Vidar M.; Sussmann, Jessika E.; Thalamuthu, Anbupalam; Toga, Arthur W.; Traynor, Bryan J.; Troncoso, Juan; Turner, Jessica A.; Valdés Hernández, Maria C.; van ’t Ent, Dennis; van der Brug, Marcel; van der Wee, Nic J. A.; van Tol, Marie-Jose; Veltman, Dick J.; Wassink, Thomas H.; Westman, Eric; Zielke, Ronald H.; Zonderman, Alan B.; Ashbrook, David G.; Hager, Reinmar; Lu, Lu; McMahon, Francis J.; Morris, Derek W.; Williams, Robert W.; Brunner, Han G.; Buckner, Randy L.; Buitelaar, Jan K.; Cahn, Wiepke; Calhoun, Vince D.; Cavalleri, Gianpiero L.; Crespo-Facorro, Benedicto; Dale, Anders M.; Davies, Gareth E.; Delanty, Norman; Depondt, Chantal; Djurovic, Srdjan; Drevets, Wayne C.; Espeseth, Thomas; Gollub, Randy L.; Ho, Beng-Choon; Hoffmann, Wolfgang; Hosten, Norbert; Kahn, René S.; Le Hellard, Stephanie; Meyer-Lindenberg, Andreas; Müller-Myhsok, Bertram; Nauck, Matthias; Nyberg, Lars; Pandolfo, Massimo; Penninx, Brenda W. J. H.; Roffman, Joshua L.; Sisodiya, Sanjay M.; Smoller, Jordan W.; van Bokhoven, Hans; van Haren, Neeltje E. M.; Völzke, Henry; Walter, Henrik; Weiner, Michael W.; Wen, Wei; White, Tonya; Agartz, Ingrid; Andreassen, Ole A.; Blangero, John; Boomsma, Dorret I.; Brouwer, Rachel M.; Cannon, Dara M.; Cookson, Mark R.; de Geus, Eco J. C.; Deary, Ian J.; Donohoe, Gary; Fernández, Guillén; Fisher, Simon E.; Francks, Clyde; Glahn, David C.; Grabe, Hans J.; Gruber, Oliver; Hardy, John; Hashimoto, Ryota; Hulshoff Pol, Hilleke E.; Jönsson, Erik G.; Kloszewska, Iwona; Lovestone, Simon; Mattay, Venkata S.; Mecocci, Patrizia; McDonald, Colm; McIntosh, Andrew M.; Ophoff, Roel A.; Paus, Tomas; Pausova, Zdenka; Ryten, Mina; Sachdev, Perminder S.; Saykin, Andrew J.; Simmons, Andy; Singleton, Andrew; Soininen, Hilkka; Wardlaw, Joanna M.; Weale, Michael E.; Weinberger, Daniel R.; Adams, Hieab H. H.; Launer, Lenore J.; Seiler, Stephan; Schmidt, Reinhold; Chauhan, Ganesh; Satizabal, Claudia L.; Becker, James T.; Yanek, Lisa; van der Lee, Sven J.; Ebling, Maritza; Fischl, Bruce; Longstreth, W. T.; Greve, Douglas; Schmidt, Helena; Nyquist, Paul; Vinke, Louis N.; van Duijn, Cornelia M.; Xue, Luting; Mazoyer, Bernard; Bis, Joshua C.; Gudnason, Vilmundur; Seshadri, Sudha; Ikram, M. Arfan; Martin, Nicholas G.; Wright, Margaret J.; Schumann, Gunter; Franke, Barbara; Thompson, Paul M.; Medland, Sarah E.

2015-01-01

The highly complex structure of the human brain is strongly shaped by genetic influences1. Subcortical brain regions form circuits with cortical areas to coordinate movement2, learning, memory3 and motivation4, and altered circuits can lead to abnormal behaviour and disease2. To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts. We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume5 and intracranial volume6. These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08 × 10−33; 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport. Identification of these genetic variants provides insight into the causes of variability inhuman brain development, and may help to determine mechanisms of neuropsychiatric dysfunction. PMID:25607358

Investigating Neuromagnetic Brain Responses against Chromatic Flickering Stimuli by Wavelet Entropies

PubMed Central

Bhagat, Mayank; Bhushan, Chitresh; Saha, Goutam; Shimjo, Shinsuke; Watanabe, Katsumi; Bhattacharya, Joydeep

2009-01-01

Background Photosensitive epilepsy is a type of reflexive epilepsy triggered by various visual stimuli including colourful ones. Despite the ubiquitous presence of colorful displays, brain responses against different colour combinations are not properly studied. Methodology/Principal Findings Here, we studied the photosensitivity of the human brain against three types of chromatic flickering stimuli by recording neuromagnetic brain responses (magnetoencephalogram, MEG) from nine adult controls, an unmedicated patient, a medicated patient, and two controls age-matched with patients. Dynamical complexities of MEG signals were investigated by a family of wavelet entropies. Wavelet entropy is a newly proposed measure to characterize large scale brain responses, which quantifies the degree of order/disorder associated with a multi-frequency signal response. In particular, we found that as compared to the unmedicated patient, controls showed significantly larger wavelet entropy values. We also found that Renyi entropy is the most powerful feature for the participant classification. Finally, we also demonstrated the effect of combinational chromatic sensitivity on the underlying order/disorder in MEG signals. Conclusions/Significance Our results suggest that when perturbed by potentially epileptic-triggering stimulus, healthy human brain manages to maintain a non-deterministic, possibly nonlinear state, with high degree of disorder, but an epileptic brain represents a highly ordered state which making it prone to hyper-excitation. Further, certain colour combination was found to be more threatening than other combinations. PMID:19779630

Investigating neuromagnetic brain responses against chromatic flickering stimuli by wavelet entropies.

PubMed

Bhagat, Mayank; Bhushan, Chitresh; Saha, Goutam; Shimjo, Shinsuke; Watanabe, Katsumi; Bhattacharya, Joydeep

2009-09-25

Photosensitive epilepsy is a type of reflexive epilepsy triggered by various visual stimuli including colourful ones. Despite the ubiquitous presence of colorful displays, brain responses against different colour combinations are not properly studied. Here, we studied the photosensitivity of the human brain against three types of chromatic flickering stimuli by recording neuromagnetic brain responses (magnetoencephalogram, MEG) from nine adult controls, an unmedicated patient, a medicated patient, and two controls age-matched with patients. Dynamical complexities of MEG signals were investigated by a family of wavelet entropies. Wavelet entropy is a newly proposed measure to characterize large scale brain responses, which quantifies the degree of order/disorder associated with a multi-frequency signal response. In particular, we found that as compared to the unmedicated patient, controls showed significantly larger wavelet entropy values. We also found that Renyi entropy is the most powerful feature for the participant classification. Finally, we also demonstrated the effect of combinational chromatic sensitivity on the underlying order/disorder in MEG signals. Our results suggest that when perturbed by potentially epileptic-triggering stimulus, healthy human brain manages to maintain a non-deterministic, possibly nonlinear state, with high degree of disorder, but an epileptic brain represents a highly ordered state which making it prone to hyper-excitation. Further, certain colour combination was found to be more threatening than other combinations.

Evolution of human brain functions: the functional structure of human consciousness.

PubMed

Cloninger, C Robert

2009-11-01

The functional structure of self-aware consciousness in human beings is described based on the evolution of human brain functions. Prior work on heritable temperament and character traits is extended to account for the quantum-like and holographic properties (i.e. parts elicit wholes) of self-aware consciousness. Cladistic analysis is used to identify the succession of ancestors leading to human beings. The functional capacities that emerge along this lineage of ancestors are described. The ecological context in which each cladogenesis occurred is described to illustrate the shifting balance of evolution as a complex adaptive system. Comparative neuroanatomy is reviewed to identify the brain structures and networks that emerged coincident with the emergent brain functions. Individual differences in human temperament traits were well developed in the common ancestor shared by reptiles and humans. Neocortical development in mammals proceeded in five major transitions: from early reptiles to early mammals, early primates, simians, early Homo, and modern Homo sapiens. These transitions provide the foundation for human self-awareness related to sexuality, materiality, emotionality, intellectuality, and spirituality, respectively. The functional structure of human self-aware consciousness is concerned with the regulation of five planes of being: sexuality, materiality, emotionality, intellectuality, and spirituality. Each plane elaborates neocortical functions organized around one of the five special senses. The interactions among these five planes gives rise to a 5 x 5 matrix of subplanes, which are functions that coarsely describe the focus of neocortical regulation. Each of these 25 neocortical functions regulates each of five basic motives or drives that can be measured as temperaments or basic emotions related to fear, anger, disgust, surprise, and happiness/sadness. The resulting 5 x 5 x 5 matrix of human characteristics provides a general and testable model of the functional structure of human consciousness that includes personality, physicality, emotionality, cognition, and spirituality in a unified developmental framework.

Advances in the Neuroscience of Intelligence: from Brain Connectivity to Brain Perturbation.

PubMed

Santarnecchi, Emiliano; Rossi, Simone

2016-12-06

Our view is that intelligence, as expression of the complexity of the human brain and of its evolutionary path, represents an intriguing example of "system level brain plasticity": tangible proofs of this assertion lie in the strong links intelligence has with vital brain capacities as information processing (i.e., pure, rough capacity to transfer information in an efficient way), resilience (i.e., the ability to cope with loss of efficiency and/or loss of physical elements in a network) and adaptability (i.e., being able to efficiently rearrange its dynamics in response to environmental demands). Current evidence supporting this view move from theoretical models correlating intelligence and individual response to systematic "lesions" of brain connectivity, as well as from the field of Noninvasive Brain Stimulation (NiBS). Perturbation-based approaches based on techniques as transcranial magnetic stimulation (TMS) and transcranial alternating current stimulation (tACS), are opening new in vivo scenarios which could allow to disclose more causal relationship between intelligence and brain plasticity, overcoming the limitations of brain-behavior correlational evidence.

Regional anatomy of the pedunculopontine nucleus: relevance for deep brain stimulation.

PubMed

Fournier-Gosselin, Marie-Pierre; Lipsman, Nir; Saint-Cyr, Jean A; Hamani, Clement; Lozano, Andres M

2013-09-01

The pedunculopontine nucleus (PPN) is currently being investigated as a potential deep brain stimulation target to improve gait and posture in Parkinson's disease. This review examines the complex anatomy of the PPN region and suggests a functional mapping of the surrounding nuclei and fiber tracts that may serve as a guide to a more accurate placement of electrodes while avoiding potentially adverse effects. The relationships of the PPN were examined in different human brain atlases. Schematic representations of those structures in the vicinity of the PPN were generated and correlated with their potential stimulation effects. By providing a functional map and representative schematics of the PPN region, we hope to optimize the placement of deep brain stimulation electrodes, thereby maximizing safety and clinical efficacy. © 2013 International Parkinson and Movement Disorder Society.

A model for brain life history evolution

PubMed Central

Lehmann, Laurent

2017-01-01

Complex cognition and relatively large brains are distributed across various taxa, and many primarily verbal hypotheses exist to explain such diversity. Yet, mathematical approaches formalizing verbal hypotheses would help deepen the understanding of brain and cognition evolution. With this aim, we combine elements of life history and metabolic theories to formulate a metabolically explicit mathematical model for brain life history evolution. We assume that some of the brain’s energetic expense is due to production (learning) and maintenance (memory) of energy-extraction skills (or cognitive abilities, knowledge, information, etc.). We also assume that individuals use such skills to extract energy from the environment, and can allocate this energy to grow and maintain the body, including brain and reproductive tissues. The model can be used to ask what fraction of growth energy should be allocated at each age, given natural selection, to growing brain and other tissues under various biological settings. We apply the model to find uninvadable allocation strategies under a baseline setting (“me vs nature”), namely when energy-extraction challenges are environmentally determined and are overcome individually but possibly with maternal help, and use modern-human data to estimate model’s parameter values. The resulting uninvadable strategies yield predictions for brain and body mass throughout ontogeny and for the ages at maturity, adulthood, and brain growth arrest. We find that: (1) a me-vs-nature setting is enough to generate adult brain and body mass of ancient human scale and a sequence of childhood, adolescence, and adulthood stages; (2) large brains are favored by intermediately challenging environments, moderately effective skills, and metabolically expensive memory; and (3) adult skill is proportional to brain mass when metabolic costs of memory saturate the brain metabolic rate allocated to skills. PMID:28278153

A novel technique for phase synchrony measurement from the complex motor imaginary potential of combined body and limb action

NASA Astrophysics Data System (ADS)

Zhou, Zhong-xing; Wan, Bai-kun; Ming, Dong; Qi, Hong-zhi

2010-08-01

In this study, we proposed and evaluated the use of the empirical mode decomposition (EMD) technique combined with phase synchronization analysis to investigate the human brain synchrony of the supplementary motor area (SMA) and primary motor area (M1) during complex motor imagination of combined body and limb action. We separated the EEG data of the SMA and M1 into intrinsic mode functions (IMFs) using the EMD method and determined the characteristic IMFs by power spectral density (PSD) analysis. Thereafter, the instantaneous phases of the characteristic IMFs were obtained by the Hilbert transformation, and the single-trial phase-locking value (PLV) features for brain synchrony measurement between the SMA and M1 were investigated separately. The classification performance suggests that the proposed approach is effective for phase synchronization analysis and is promising for the application of a brain-computer interface in motor nerve reconstruction of the lower limbs.

A Proteomics Analysis of the Effects of Chronic Hemiparetic Stroke on Troponin T Expression in Human Vastus Lateralis

PubMed Central

Rabek, Jeffrey P.; Hafer-Macko, Charlene E.; Amaning, James K.; DeFord, James H.; Dimayuga, Vincent L.; Madsen, Mark A.; Macko, Richard F.

2009-01-01

Stroke disability is attributed to upper motor neuron deficits resulting from ischemic brain injury. We have developed proteome maps of the Vastus lateralis to examine the effects of ischemic brain injury on paretic skeletal muscle myofilament proteins. Proteomics analyses from seven hemiparetic stroke patients have detected a decrease of three troponin T isoforms in the paretic muscle suggesting that myosin–actin interactions may be attenuated. We propose that ischemic brain injury may prevent troponin T participation in complex formation thereby affecting the protein interactions associated with excitation–contraction coupling. We have also detected a novel skeletal troponin T isoform that has a C-terminal variation. Our data suggest that the decreased slow troponin T isoform pools in the paretic limb may contribute to the gait deficit after stroke. The complexity of the neurological deficit on Vastus lateralis is suggested by the multiple changes in proteins detected by our proteomics mapping. PMID:19447848

Neuronal chronometry of target detection: fusion of hemodynamic and event-related potential data.

PubMed

Calhoun, V D; Adali, T; Pearlson, G D; Kiehl, K A

2006-04-01

Event-related potential (ERP) studies of the brain's response to infrequent, target (oddball) stimuli elicit a sequence of physiological events, the most prominent and well studied being a complex, the P300 (or P3) peaking approximately 300 ms post-stimulus for simple stimuli and slightly later for more complex stimuli. Localization of the neural generators of the human oddball response remains challenging due to the lack of a single imaging technique with good spatial and temporal resolution. Here, we use independent component analyses to fuse ERP and fMRI modalities in order to examine the dynamics of the auditory oddball response with high spatiotemporal resolution across the entire brain. Initial activations in auditory and motor planning regions are followed by auditory association cortex and motor execution regions. The P3 response is associated with brainstem, temporal lobe, and medial frontal activity and finally a late temporal lobe "evaluative" response. We show that fusing imaging modalities with different advantages can provide new information about the brain.

Arterial Spin Labeling: a one-stop-shop for measurement of brain perfusion in the clinical settings.

PubMed

Golay, Xavier; Petersen, Esben T; Zimine, Ivan; Lim, Tchoyoson C C

2007-01-01

Arterial Spin Labeling (ASL) has opened a unique window into the human brain function and perfusion physiology. Altogether fast and of intrinsic high spatial resolution, ASL is a technique very appealing not only for the diagnosis of vascular diseases, but also in basic neuroscience for the follow-up of small perfusion changes occurring during brain activation. However, due to limited signal-to-noise ratio and complex flow kinetics, ASL is one of the more challenging disciplines within magnetic resonance imaging. In this paper, the theoretical background and main implementations of ASL are revisited. In particular, the different uses of ASL, the pitfalls and possibilities are described and illustrated using clinical cases.

The consequences of fetal growth restriction on brain structure and neurodevelopmental outcome.

PubMed

Miller, Suzanne L; Huppi, Petra S; Mallard, Carina

2016-02-15

Fetal growth restriction (FGR) is a significant complication of pregnancy describing a fetus that does not grow to full potential due to pathological compromise. FGR affects 3-9% of pregnancies in high-income countries, and is a leading cause of perinatal mortality and morbidity. Placental insufficiency is the principal cause of FGR, resulting in chronic fetal hypoxia. This hypoxia induces a fetal adaptive response of cardiac output redistribution to favour vital organs, including the brain, and is in consequence called brain sparing. Despite this, it is now apparent that brain sparing does not ensure normal brain development in growth-restricted fetuses. In this review we have brought together available evidence from human and experimental animal studies to describe the complex changes in brain structure and function that occur as a consequence of FGR. In both humans and animals, neurodevelopmental outcomes are influenced by the timing of the onset of FGR, the severity of FGR, and gestational age at delivery. FGR is broadly associated with reduced total brain volume and altered cortical volume and structure, decreased total number of cells and myelination deficits. Brain connectivity is also impaired, evidenced by neuronal migration deficits, reduced dendritic processes, and less efficient networks with decreased long-range connections. Subsequent to these structural alterations, short- and long-term functional consequences have been described in school children who had FGR, most commonly including problems in motor skills, cognition, memory and neuropsychological dysfunctions. © 2015 The Authors. The Journal of Physiology © 2015 The Physiological Society.

DJ-1 is a redox sensitive adapter protein for high molecular weight complexes involved in regulation of catecholamine homeostasis

PubMed Central

Piston, Dominik; Alvarez-Erviti, Lydia; Bansal, Vikas; Gargano, Daniela; Yao, Zhi; Szabadkai, Gyorgy; Odell, Mark; Puno, M Rhyan; Björkblom, Benny; Maple-Grødem, Jodi; Breuer, Peter; Kaut, Oliver; Larsen, Jan Petter; Bonn, Stefan; Møller, Simon Geir; Wüllner, Ullrich; Schapira, Anthony H V

2017-01-01

Abstract DJ-1 is an oxidation sensitive protein encoded by the PARK7 gene. Mutations in PARK7 are a rare cause of familial recessive Parkinson’s disease (PD), but growing evidence suggests involvement of DJ-1 in idiopathic PD. The key clinical features of PD, rigidity and bradykinesia, result from neurotransmitter imbalance, particularly the catecholamines dopamine (DA) and noradrenaline. We report in human brain and human SH-SY5Y neuroblastoma cell lines that DJ-1 predominantly forms high molecular weight (HMW) complexes that included RNA metabolism proteins hnRNPA1 and PABP1 and the glycolysis enzyme GAPDH. In cell culture models the oxidation status of DJ-1 determined the specific complex composition. RNA sequencing indicated that oxidative changes to DJ-1 were concomitant with changes in mRNA transcripts mainly involved in catecholamine metabolism. Importantly, loss of DJ-1 function upon knock down (KD) or expression of the PD associated form L166P resulted in the absence of HMW DJ-1 complexes. In the KD model, the absence of DJ-1 complexes was accompanied by impairment in catecholamine homeostasis, with significant increases in intracellular DA and noraderenaline levels. These changes in catecholamines could be rescued by re-expression of DJ-1. This catecholamine imbalance may contribute to the particular vulnerability of dopaminergic and noradrenergic neurons to neurodegeneration in PARK7-related PD. Notably, oxidised DJ-1 was significantly decreased in idiopathic PD brain, suggesting altered complex function may also play a role in the more common sporadic form of the disease. PMID:29016861

Neuroelectrical Decomposition of Spontaneous Brain Activity Measured with Functional Magnetic Resonance Imaging

PubMed Central

Liu, Zhongming; de Zwart, Jacco A.; Chang, Catie; Duan, Qi; van Gelderen, Peter; Duyn, Jeff H.

2014-01-01

Spontaneous activity in the human brain occurs in complex spatiotemporal patterns that may reflect functionally specialized neural networks. Here, we propose a subspace analysis method to elucidate large-scale networks by the joint analysis of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data. The new approach is based on the notion that the neuroelectrical activity underlying the fMRI signal may have EEG spectral features that report on regional neuronal dynamics and interregional interactions. Applying this approach to resting healthy adults, we indeed found characteristic spectral signatures in the EEG correlates of spontaneous fMRI signals at individual brain regions as well as the temporal synchronization among widely distributed regions. These spectral signatures not only allowed us to parcel the brain into clusters that resembled the brain's established functional subdivision, but also offered important clues for disentangling the involvement of individual regions in fMRI network activity. PMID:23796947

Niels Stensen: a 17th century scientist with a modern view of brain organization.

PubMed

Parent, André

2013-07-01

In 1665 the Danish scholar Niels Stensen (1638-1686) reached Paris, where he pronounced a discourse on brain anatomy that was to orient neuroscientists for years to come. In his lecture, Stensen rejected ancient speculations about animal spirits and criticized René Descartes and his followers who, despite a poor knowledge of brain anatomy, elaborated complex models to explain the multifaceted function of what he considered the principal organ of the human mind. He advocated the need for studying the brain through a comparative, developmental and pathological convergent approach and called for appropriate dissection methods and accurate illustrations. His own careful anatomical studies permitted him to precisely depict many brain structures. After pioneering works in paleontology and geology, he devoted himself to theology. In 1677 Stensen converted from Lutheranism to Catholicism and, while working relentlessly as a bishop and apostolic vicar in Northern Europe, he died in self-imposed poverty at age 48.

The NSW Brain Tissue Resource Centre: Banking for Alcohol and Major Neuropsychiatric Disorders Research

PubMed Central

Sutherland, G.T.; Sheedy, D.; Stevens, J.; McCrossin, T.; Smith, C.C.; van Roijen, M.; Kril, J.J.

2016-01-01

The New South Wales Brain Tissue Resource Centre (NSWBTRC) at the University of Sydney (Australia) is an established human brain bank providing tissue to the neuroscience research community for investigations on alcohol-related brain damage and major psychiatric illnesses such as schizophrenia. The NSWBTRC relies on wide community engagement to encourage those with and without neuropsychiatric illness to consent to donation through its allied research programs. The subsequent provision of high-quality samples relies on standardized operational protocols, associated clinical data, quality control measures, integrated information systems, robust infrastructure, and governance. These processes are continually augmented to complement the changes in internal and external governance as well as the complexity and diversity of advanced investigation techniques. This report provides an overview of the dynamic process of brain banking and discusses the challenges of meeting the future needs of researchers, including synchronicity with other disease-focus collections. PMID:27139235

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.

Approximating high angular resolution apparent diffusion coefficient profiles using spherical harmonics under BiGaussian assumption

NASA Astrophysics Data System (ADS)

Cao, Ning; Liang, Xuwei; Zhuang, Qi; Zhang, Jun

2009-02-01

Magnetic Resonance Imaging (MRI) techniques have achieved much importance in providing visual and quantitative information of human body. Diffusion MRI is the only non-invasive tool to obtain information of the neural fiber networks of the human brain. The traditional Diffusion Tensor Imaging (DTI) is only capable of characterizing Gaussian diffusion. High Angular Resolution Diffusion Imaging (HARDI) extends its ability to model more complex diffusion processes. Spherical harmonic series truncated to a certain degree is used in recent studies to describe the measured non-Gaussian Apparent Diffusion Coefficient (ADC) profile. In this study, we use the sampling theorem on band-limited spherical harmonics to choose a suitable degree to truncate the spherical harmonic series in the sense of Signal-to-Noise Ratio (SNR), and use Monte Carlo integration to compute the spherical harmonic transform of human brain data obtained from icosahedral schema.

The Neuropathology of Obesity: Insights from Human Disease

PubMed Central

Lee, Edward B.; Mattson, Mark P.

2013-01-01

Obesity, a pathologic state defined by excess adipose tissue, is a significant public health problem as it affects a large proportion of individuals and is linked with increased risk for numerous chronic diseases. Obesity is the result of fundamental changes associated with modern society including overnutrition and sedentary lifestyles. Proper energy homeostasis is dependent on normal brain function as the master metabolic regulator which integrates peripheral signals, modulates autonomic outflow and controls feeding behavior. Therefore, many human brain diseases are associated with obesity. This review explores the neuropathology of obesity by examining brain diseases which either cause or are influenced by obesity. First, several genetic and acquired brain diseases are discussed as a means to understand the central regulation of peripheral metabolism. These diseases range from monogenetic causes of obesity (leptin deficiency, MC4R deficiency, Bardet-Biedl syndrome and others) to complex neurodevelopmental disorders (Prader-Willi syndrome and Sim1 deficiency) and neurodegenerative conditions (frontotemporal dementia and Gourmand’s syndrome) and serve to highlight the central regulatory mechanisms which have evolved to maintain energy homeostasis. Next, to examine the effect of obesity on the brain, chronic neuropathologic conditions (epilepsy, multiple sclerosis and Alzheimer’s disease) are discussed as examples of obesity leading to maladaptive processes which exacerbate chronic disease. Thus obesity is associated with multiple pathways including abnormal metabolism, altered hormonal signaling and increased inflammation which act in concert to promote downstream neuropathology. Finally, the effect of anti-obesity interventions is discussed in terms of brain structure and function. Together, understanding human diseases and anti-obesity interventions leads to insights into the bidirectional interaction between peripheral metabolism and central brain function, highlighting the need for continued clinicopathologic and mechanistic studies of the neuropathology of obesity. PMID:24096619

Resolving Structural Variability in Network Models and the Brain

PubMed Central

Klimm, Florian; Bassett, Danielle S.; Carlson, Jean M.; Mucha, Peter J.

2014-01-01

Large-scale white matter pathways crisscrossing the cortex create a complex pattern of connectivity that underlies human cognitive function. Generative mechanisms for this architecture have been difficult to identify in part because little is known in general about mechanistic drivers of structured networks. Here we contrast network properties derived from diffusion spectrum imaging data of the human brain with 13 synthetic network models chosen to probe the roles of physical network embedding and temporal network growth. We characterize both the empirical and synthetic networks using familiar graph metrics, but presented here in a more complete statistical form, as scatter plots and distributions, to reveal the full range of variability of each measure across scales in the network. We focus specifically on the degree distribution, degree assortativity, hierarchy, topological Rentian scaling, and topological fractal scaling—in addition to several summary statistics, including the mean clustering coefficient, the shortest path-length, and the network diameter. The models are investigated in a progressive, branching sequence, aimed at capturing different elements thought to be important in the brain, and range from simple random and regular networks, to models that incorporate specific growth rules and constraints. We find that synthetic models that constrain the network nodes to be physically embedded in anatomical brain regions tend to produce distributions that are most similar to the corresponding measurements for the brain. We also find that network models hardcoded to display one network property (e.g., assortativity) do not in general simultaneously display a second (e.g., hierarchy). This relative independence of network properties suggests that multiple neurobiological mechanisms might be at play in the development of human brain network architecture. Together, the network models that we develop and employ provide a potentially useful starting point for the statistical inference of brain network structure from neuroimaging data. PMID:24675546

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.

Haptic contents of a movie dynamically engage the spectator's sensorimotor cortex.

PubMed

Lankinen, Kaisu; Smeds, Eero; Tikka, Pia; Pihko, Elina; Hari, Riitta; Koskinen, Miika

2016-11-01

Observation of another person's actions and feelings activates brain areas that support similar functions in the observer, thereby facilitating inferences about the other's mental and bodily states. In real life, events eliciting this kind of vicarious brain activations are intermingled with other complex, ever-changing stimuli in the environment. One practical approach to study the neural underpinnings of real-life vicarious perception is to image brain activity during movie viewing. Here the goal was to find out how observed haptic events in a silent movie would affect the spectator's sensorimotor cortex. The functional state of the sensorimotor cortex was monitored by analyzing, in 16 healthy subjects, magnetoencephalographic (MEG) responses to tactile finger stimuli that were presented once per second throughout the session. Using canonical correlation analysis and spatial filtering, consistent single-trial responses across subjects were uncovered, and their waveform changes throughout the movie were quantified. The long-latency (85-175 ms) parts of the responses were modulated in concordance with the participants' average moment-by-moment ratings of own engagement in the haptic content of the movie (correlation r = 0.49; ratings collected after the MEG session). The results, obtained by using novel signal-analysis approaches, demonstrate that the functional state of the human sensorimotor cortex fluctuates in a fine-grained manner even during passive observation of temporally varying haptic events. Hum Brain Mapp 37:4061-4068, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Convergent Differential Regulation of Parvalbumin in the Brains of Vocal Learners

PubMed Central

Hara, Erina; Rivas, Miriam V.; Ward, James M.; Okanoya, Kazuo; Jarvis, Erich D.

2012-01-01

Spoken language and learned song are complex communication behaviors found in only a few species, including humans and three groups of distantly related birds – songbirds, parrots, and hummingbirds. Despite their large phylogenetic distances, these vocal learners show convergent behaviors and associated brain pathways for vocal communication. However, it is not clear whether this behavioral and anatomical convergence is associated with molecular convergence. Here we used oligo microarrays to screen for genes differentially regulated in brain nuclei necessary for producing learned vocalizations relative to adjacent brain areas that control other behaviors in avian vocal learners versus vocal non-learners. A top candidate gene in our screen was a calcium-binding protein, parvalbumin (PV). In situ hybridization verification revealed that PV was expressed significantly higher throughout the song motor pathway, including brainstem vocal motor neurons relative to the surrounding brain regions of all distantly related avian vocal learners. This differential expression was specific to PV and vocal learners, as it was not found in avian vocal non-learners nor for control genes in learners and non-learners. Similar to the vocal learning birds, higher PV up-regulation was found in the brainstem tongue motor neurons used for speech production in humans relative to a non-human primate, macaques. These results suggest repeated convergent evolution of differential PV up-regulation in the brains of vocal learners separated by more than 65–300 million years from a common ancestor and that the specialized behaviors of learned song and speech may require extra calcium buffering and signaling. PMID:22238614

Animal models of cerebral ischemia

NASA Astrophysics Data System (ADS)

Khodanovich, M. Yu.; Kisel, A. A.

2015-11-01

Cerebral ischemia remains one of the most frequent causes of death and disability worldwide. Animal models are necessary to understand complex molecular mechanisms of brain damage as well as for the development of new therapies for stroke. This review considers a certain range of animal models of cerebral ischemia, including several types of focal and global ischemia. Since animal models vary in specificity for the human disease which they reproduce, the complexity of surgery, infarct size, reliability of reproduction for statistical analysis, and adequate models need to be chosen according to the aim of a study. The reproduction of a particular animal model needs to be evaluated using appropriate tools, including the behavioral assessment of injury and non-invasive and post-mortem control of brain damage. These problems also have been summarized in the review.

The HSPB8-BAG3 chaperone complex is upregulated in astrocytes in the human brain affected by protein aggregation diseases.

PubMed

Seidel, K; Vinet, J; Dunnen, W F A den; Brunt, E R; Meister, M; Boncoraglio, A; Zijlstra, M P; Boddeke, H W G M; Rüb, U; Kampinga, H H; Carra, S

2012-02-01

HSPB8 is a small heat shock protein that forms a complex with the co-chaperone BAG3. Overexpression of the HSPB8-BAG3 complex in cells stimulates autophagy and facilitates the clearance of mutated aggregation-prone proteins, whose accumulation is a hallmark of many neurodegenerative disorders. HSPB8-BAG3 could thus play a protective role in protein aggregation diseases and might be specifically upregulated in response to aggregate-prone protein-mediated toxicity. Here we analysed HSPB8-BAG3 expression levels in post-mortem human brain tissue from patients suffering of the following protein conformation disorders: Alzheimer's disease, Parkinson's disease, Huntington's disease and spinocerebellar ataxia type 3 (SCA3). Western blotting and immunohistochemistry techniques were used to analyse HSPB8 and BAG3 expression levels in fibroblasts from SCA3 patients and post-mortem brain tissues, respectively. In all diseases investigated, we observed a strong upregulation of HSPB8 and a moderate upregulation of BAG3 specifically in astrocytes in the cerebral areas affected by neuronal damage and degeneration. Intriguingly, no significant change in the HSPB8-BAG3 expression levels was observed within neurones, irrespective of their localization or of the presence of proteinaceous aggregates. We propose that the upregulation of HSPB8 and BAG3 may enhance the ability of astrocytes to clear aggregated proteins released from neurones and cellular debris, maintain the local tissue homeostasis and/or participate in the cytoskeletal remodelling that astrocytes undergo during astrogliosis. © 2011 The Authors. Neuropathology and Applied Neurobiology © 2011 British Neuropathological Society.

Network science and the human brain: Using graph theory to understand the brain and one of its hubs, the amygdala, in health and disease.

PubMed

Mears, David; Pollard, Harvey B

2016-06-01

Over the past 15 years, the emerging field of network science has revealed the key features of brain networks, which include small-world topology, the presence of highly connected hubs, and hierarchical modularity. The value of network studies of the brain is underscored by the range of network alterations that have been identified in neurological and psychiatric disorders, including epilepsy, depression, Alzheimer's disease, schizophrenia, and many others. Here we briefly summarize the concepts of graph theory that are used to quantify network properties and describe common experimental approaches for analysis of brain networks of structural and functional connectivity. These range from tract tracing to functional magnetic resonance imaging, diffusion tensor imaging, electroencephalography, and magnetoencephalography. We then summarize the major findings from the application of graph theory to nervous systems ranging from Caenorhabditis elegans to more complex primate brains, including man. Focusing, then, on studies involving the amygdala, a brain region that has attracted intense interest as a center for emotional processing, fear, and motivation, we discuss the features of the amygdala in brain networks for fear conditioning and emotional perception. Finally, to highlight the utility of graph theory for studying dysfunction of the amygdala in mental illness, we review data with regard to changes in the hub properties of the amygdala in brain networks of patients with depression. We suggest that network studies of the human brain may serve to focus attention on regions and connections that act as principal drivers and controllers of brain function in health and disease. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

Extracting the inclination angle of nerve fibers within the human brain with 3D-PLI independent of system properties

NASA Astrophysics Data System (ADS)

Reckfort, Julia; Wiese, Hendrik; Dohmen, Melanie; Grässel, David; Pietrzyk, Uwe; Zilles, Karl; Amunts, Katrin; Axer, Markus

2013-09-01

The neuroimaging technique 3D-polarized light imaging (3D-PLI) has opened up new avenues to study the complex nerve fiber architecture of the human brain at sub-millimeter spatial resolution. This polarimetry technique is applicable to histological sections of postmortem brains utilizing the birefringence of nerve fibers caused by the regular arrangement of lipids and proteins in the myelin sheaths surrounding axons. 3D-PLI provides a three-dimensional description of the anatomical wiring scheme defined by the in-section direction angle and the out-of-section inclination angle. To date, 3D-PLI is the only available method that allows bridging the microscopic and the macroscopic description of the fiber architecture of the human brain. Here we introduce a new approach to retrieve the inclination angle of the fibers independently of the properties of the used polarimeters. This is relevant because the image resolution and the signal transmission inuence the measured birefringent signal (retardation) significantly. The image resolution was determined using the USAF- 1951 testchart applying the Rayleigh criterion. The signal transmission was measured by elliptical polarizers applying the Michelson contrast and histological slices of the optic tract of a postmortem brain. Based on these results, a modified retardation-inclination transfer function was proposed to extract the fiber inclination. The comparison of the actual and the inclination angles calculated with the theoretically proposed and the modified transfer function revealed a significant improvement in the extraction of the fiber inclinations.

It ain't what you do (it's the way that you do it).

PubMed

Aitken, Kenneth John

2013-08-01

Knowledge of the complexity of human communication comes from three main sources - (i) studies of the linguistics and neuropsychology of dysfunction after brain injury; (ii) studies of the development of social communication in infancy, and its dysfunction in developmental psychopathologies; and (iii) the evolutionary history of human communicative interaction. Together, these suggest the need for a broad, integrated theory of communication of which language forms a small but critical component.

How to perfect a chocolate soufflé and other important problems.

PubMed

Behrens, Timothy E J; Jocham, Gerhard

2011-07-28

When learning to achieve a goal through a complex series of actions, humans often group several actions into a subroutine and evaluate whether the subroutine achieved a specific subgoal. A new study reports brain responses consistent with such "hierarchical reinforcement learning." Copyright © 2011 Elsevier Inc. All rights reserved.

Virtual Cerebral Ventricular System: An MR-Based Three-Dimensional Computer Model

ERIC Educational Resources Information Center

Adams, Christina M.; Wilson, Timothy D.

2011-01-01

The inherent spatial complexity of the human cerebral ventricular system, coupled with its deep position within the brain, poses a problem for conceptualizing its anatomy. Cadaveric dissection, while considered the gold standard of anatomical learning, may be inadequate for learning the anatomy of the cerebral ventricular system; even with…

Experiential Learning in Rodents: Past Experience Enables Rapid Learning and Localized Encoding in Hippocampus

ERIC Educational Resources Information Center

Cox, Conor D.; Palmer, Linda C.; Pham, Danielle T.; Trieu, Brian H.; Gall, Christine M.; Lynch, Gary

2017-01-01

Humans routinely use past experience with complexity to deal with novel, challenging circumstances. This fundamental aspect of real-world behavior has received surprisingly little attention in animal studies, and the underlying brain mechanisms are unknown. The present experiments tested for transfer from past experience in rats and then used…

Drosophila as an In Vivo Model for Human Neurodegenerative Disease

PubMed Central

McGurk, Leeanne; Berson, Amit; Bonini, Nancy M.

2015-01-01

With the increase in the ageing population, neurodegenerative disease is devastating to families and poses a huge burden on society. The brain and spinal cord are extraordinarily complex: they consist of a highly organized network of neuronal and support cells that communicate in a highly specialized manner. One approach to tackling problems of such complexity is to address the scientific questions in simpler, yet analogous, systems. The fruit fly, Drosophila melanogaster, has been proven tremendously valuable as a model organism, enabling many major discoveries in neuroscientific disease research. The plethora of genetic tools available in Drosophila allows for exquisite targeted manipulation of the genome. Due to its relatively short lifespan, complex questions of brain function can be addressed more rapidly than in other model organisms, such as the mouse. Here we discuss features of the fly as a model for human neurodegenerative disease. There are many distinct fly models for a range of neurodegenerative diseases; we focus on select studies from models of polyglutamine disease and amyotrophic lateral sclerosis that illustrate the type and range of insights that can be gleaned. In discussion of these models, we underscore strengths of the fly in providing understanding into mechanisms and pathways, as a foundation for translational and therapeutic research. PMID:26447127

Drosophila as an In Vivo Model for Human Neurodegenerative Disease.

PubMed

McGurk, Leeanne; Berson, Amit; Bonini, Nancy M

2015-10-01

With the increase in the ageing population, neurodegenerative disease is devastating to families and poses a huge burden on society. The brain and spinal cord are extraordinarily complex: they consist of a highly organized network of neuronal and support cells that communicate in a highly specialized manner. One approach to tackling problems of such complexity is to address the scientific questions in simpler, yet analogous, systems. The fruit fly, Drosophila melanogaster, has been proven tremendously valuable as a model organism, enabling many major discoveries in neuroscientific disease research. The plethora of genetic tools available in Drosophila allows for exquisite targeted manipulation of the genome. Due to its relatively short lifespan, complex questions of brain function can be addressed more rapidly than in other model organisms, such as the mouse. Here we discuss features of the fly as a model for human neurodegenerative disease. There are many distinct fly models for a range of neurodegenerative diseases; we focus on select studies from models of polyglutamine disease and amyotrophic lateral sclerosis that illustrate the type and range of insights that can be gleaned. In discussion of these models, we underscore strengths of the fly in providing understanding into mechanisms and pathways, as a foundation for translational and therapeutic research. Copyright © 2015 by the Genetics Society of America.

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

PubMed

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

2018-06-25

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

Episodic Memory Retrieval Benefits from a Less Modular Brain Network Organization

PubMed Central

2017-01-01

Most complex cognitive tasks require the coordinated interplay of multiple brain networks, but the act of retrieving an episodic memory may place especially heavy demands for communication between the frontoparietal control network (FPCN) and the default mode network (DMN), two networks that do not strongly interact with one another in many task contexts. We applied graph theoretical analysis to task-related fMRI functional connectivity data from 20 human participants and found that global brain modularity—a measure of network segregation—is markedly reduced during episodic memory retrieval relative to closely matched analogical reasoning and visuospatial perception tasks. Individual differences in modularity were correlated with memory task performance, such that lower modularity levels were associated with a lower false alarm rate. Moreover, the FPCN and DMN showed significantly elevated coupling with each other during the memory task, which correlated with the global reduction in brain modularity. Both networks also strengthened their functional connectivity with the hippocampus during the memory task. Together, these results provide a novel demonstration that reduced modularity is conducive to effective episodic retrieval, which requires close collaboration between goal-directed control processes supported by the FPCN and internally oriented self-referential processing supported by the DMN. SIGNIFICANCE STATEMENT Modularity, an index of the degree to which nodes of a complex system are organized into discrete communities, has emerged as an important construct in the characterization of brain connectivity dynamics. We provide novel evidence that the modularity of the human brain is reduced when individuals engage in episodic memory retrieval, relative to other cognitive tasks, and that this state of lower modularity is associated with improved memory performance. We propose a neural systems mechanism for this finding where the nodes of the frontoparietal control network and default mode network strengthen their interaction with one another during episodic retrieval. Such across-network communication likely facilitates effective access to internally generated representations of past event knowledge. PMID:28242796

Episodic Memory Retrieval Benefits from a Less Modular Brain Network Organization.

PubMed

Westphal, Andrew J; Wang, Siliang; Rissman, Jesse

2017-03-29

Most complex cognitive tasks require the coordinated interplay of multiple brain networks, but the act of retrieving an episodic memory may place especially heavy demands for communication between the frontoparietal control network (FPCN) and the default mode network (DMN), two networks that do not strongly interact with one another in many task contexts. We applied graph theoretical analysis to task-related fMRI functional connectivity data from 20 human participants and found that global brain modularity-a measure of network segregation-is markedly reduced during episodic memory retrieval relative to closely matched analogical reasoning and visuospatial perception tasks. Individual differences in modularity were correlated with memory task performance, such that lower modularity levels were associated with a lower false alarm rate. Moreover, the FPCN and DMN showed significantly elevated coupling with each other during the memory task, which correlated with the global reduction in brain modularity. Both networks also strengthened their functional connectivity with the hippocampus during the memory task. Together, these results provide a novel demonstration that reduced modularity is conducive to effective episodic retrieval, which requires close collaboration between goal-directed control processes supported by the FPCN and internally oriented self-referential processing supported by the DMN. SIGNIFICANCE STATEMENT Modularity, an index of the degree to which nodes of a complex system are organized into discrete communities, has emerged as an important construct in the characterization of brain connectivity dynamics. We provide novel evidence that the modularity of the human brain is reduced when individuals engage in episodic memory retrieval, relative to other cognitive tasks, and that this state of lower modularity is associated with improved memory performance. We propose a neural systems mechanism for this finding where the nodes of the frontoparietal control network and default mode network strengthen their interaction with one another during episodic retrieval. Such across-network communication likely facilitates effective access to internally generated representations of past event knowledge. Copyright © 2017 the authors 0270-6474/17/373523-09$15.00/0.

Reading wild minds: A computational assay of Theory of Mind sophistication across seven primate species

PubMed Central

Devaine, Marie; San-Galli, Aurore; Trapanese, Cinzia; Bardino, Giulia; Hano, Christelle; Saint Jalme, Michel; Bouret, Sebastien

2017-01-01

Theory of Mind (ToM), i.e. the ability to understand others' mental states, endows humans with highly adaptive social skills such as teaching or deceiving. Candidate evolutionary explanations have been proposed for the unique sophistication of human ToM among primates. For example, the Machiavellian intelligence hypothesis states that the increasing complexity of social networks may have induced a demand for sophisticated ToM. This type of scenario ignores neurocognitive constraints that may eventually be crucial limiting factors for ToM evolution. In contradistinction, the cognitive scaffolding hypothesis asserts that a species' opportunity to develop sophisticated ToM is mostly determined by its general cognitive capacity (on which ToM is scaffolded). However, the actual relationships between ToM sophistication and either brain volume (a proxy for general cognitive capacity) or social group size (a proxy for social network complexity) are unclear. Here, we let 39 individuals sampled from seven non-human primate species (lemurs, macaques, mangabeys, orangutans, gorillas and chimpanzees) engage in simple dyadic games against artificial ToM players (via a familiar human caregiver). Using computational analyses of primates' choice sequences, we found that the probability of exhibiting a ToM-compatible learning style is mainly driven by species' brain volume (rather than by social group size). Moreover, primates' social cognitive sophistication culminates in a precursor form of ToM, which still falls short of human fully-developed ToM abilities. PMID:29112973

Reading wild minds: A computational assay of Theory of Mind sophistication across seven primate species.

PubMed

Devaine, Marie; San-Galli, Aurore; Trapanese, Cinzia; Bardino, Giulia; Hano, Christelle; Saint Jalme, Michel; Bouret, Sebastien; Masi, Shelly; Daunizeau, Jean

2017-11-01

Theory of Mind (ToM), i.e. the ability to understand others' mental states, endows humans with highly adaptive social skills such as teaching or deceiving. Candidate evolutionary explanations have been proposed for the unique sophistication of human ToM among primates. For example, the Machiavellian intelligence hypothesis states that the increasing complexity of social networks may have induced a demand for sophisticated ToM. This type of scenario ignores neurocognitive constraints that may eventually be crucial limiting factors for ToM evolution. In contradistinction, the cognitive scaffolding hypothesis asserts that a species' opportunity to develop sophisticated ToM is mostly determined by its general cognitive capacity (on which ToM is scaffolded). However, the actual relationships between ToM sophistication and either brain volume (a proxy for general cognitive capacity) or social group size (a proxy for social network complexity) are unclear. Here, we let 39 individuals sampled from seven non-human primate species (lemurs, macaques, mangabeys, orangutans, gorillas and chimpanzees) engage in simple dyadic games against artificial ToM players (via a familiar human caregiver). Using computational analyses of primates' choice sequences, we found that the probability of exhibiting a ToM-compatible learning style is mainly driven by species' brain volume (rather than by social group size). Moreover, primates' social cognitive sophistication culminates in a precursor form of ToM, which still falls short of human fully-developed ToM abilities.

Structure Expression and Function of kynurenine Aminotransferases in Human and Rodent Brains

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

Q Han; T Cai; D Tagle

Kynurenine aminotransferases (KATs) catalyze the synthesis of kynurenic acid (KYNA), an endogenous antagonist of N-methyl-D: -aspartate and alpha 7-nicotinic acetylcholine receptors. Abnormal KYNA levels in human brains are implicated in the pathophysiology of schizophrenia, Alzheimer's disease, and other neurological disorders. Four KATs have been reported in mammalian brains, KAT I/glutamine transaminase K/cysteine conjugate beta-lyase 1, KAT II/aminoadipate aminotransferase, KAT III/cysteine conjugate beta-lyase 2, and KAT IV/glutamic-oxaloacetic transaminase 2/mitochondrial aspartate aminotransferase. KAT II has a striking tertiary structure in N-terminal part and forms a new subgroup in fold type I aminotransferases, which has been classified as subgroup Iepsilon. Knowledge regarding KATsmore » is vast and complex; therefore, this review is focused on recent important progress of their gene characterization, physiological and biochemical function, and structural properties. The biochemical differences of four KATs, specific enzyme activity assays, and the structural insights into the mechanism of catalysis and inhibition of these enzymes are discussed.« less

Immoral behaviour following brain damage: A review.

PubMed

Roberts, Stefanie; Henry, Julie D; Molenberghs, Pascal

2018-04-16

Despite the apparent sociability of human kind, immoral behaviour is ever present in society. The term 'immoral behaviour' represents a complex array of conduct, ranging from insensitivity to topics of conversation through to violent assault and murder. To better understand the neuroscience of immoral behaviour, this review investigates two clinical populations that commonly present with changes in moral behaviour - behavioural-variant frontotemporal dementia and acquired brain injuries. Based on evidence from these groups, it is argued that rather than a single underlying cause, immoral behaviour can result from three distinct types of cognitive failure: (1) problems understanding others; (2) difficulties controlling behaviour; or (3) deficits in the capacity to make appropriate emotional contributions. Each of these failures is associated with damage to different brain regions. A more nuanced approach to the neuroscience of immoral behaviour has important implications for our understanding of immoral behaviour in a wide range of clinical groups, as well as human society more broadly. © 2018 The British Psychological Society.

‘My Virtual Dream’: Collective Neurofeedback in an Immersive Art Environment

PubMed Central

Kovacevic, Natasha; Ritter, Petra; Tays, William; Moreno, Sylvain; McIntosh, Anthony Randal

2015-01-01

While human brains are specialized for complex and variable real world tasks, most neuroscience studies reduce environmental complexity, which limits the range of behaviours that can be explored. Motivated to overcome this limitation, we conducted a large-scale experiment with electroencephalography (EEG) based brain-computer interface (BCI) technology as part of an immersive multi-media science-art installation. Data from 523 participants were collected in a single night. The exploratory experiment was designed as a collective computer game where players manipulated mental states of relaxation and concentration with neurofeedback targeting modulation of relative spectral power in alpha and beta frequency ranges. Besides validating robust time-of-night effects, gender differences and distinct spectral power patterns for the two mental states, our results also show differences in neurofeedback learning outcome. The unusually large sample size allowed us to detect unprecedented speed of learning changes in the power spectrum (~ 1 min). Moreover, we found that participants' baseline brain activity predicted subsequent neurofeedback beta training, indicating state-dependent learning. Besides revealing these training effects, which are relevant for BCI applications, our results validate a novel platform engaging art and science and fostering the understanding of brains under natural conditions. PMID:26154513

The brain ages optimally to model its environment: evidence from sensory learning over the adult lifespan.

PubMed

Moran, Rosalyn J; Symmonds, Mkael; Dolan, Raymond J; Friston, Karl J

2014-01-01

The aging brain shows a progressive loss of neuropil, which is accompanied by subtle changes in neuronal plasticity, sensory learning and memory. Neurophysiologically, aging attenuates evoked responses--including the mismatch negativity (MMN). This is accompanied by a shift in cortical responsivity from sensory (posterior) regions to executive (anterior) regions, which has been interpreted as a compensatory response for cognitive decline. Theoretical neurobiology offers a simpler explanation for all of these effects--from a Bayesian perspective, as the brain is progressively optimized to model its world, its complexity will decrease. A corollary of this complexity reduction is an attenuation of Bayesian updating or sensory learning. Here we confirmed this hypothesis using magnetoencephalographic recordings of the mismatch negativity elicited in a large cohort of human subjects, in their third to ninth decade. Employing dynamic causal modeling to assay the synaptic mechanisms underlying these non-invasive recordings, we found a selective age-related attenuation of synaptic connectivity changes that underpin rapid sensory learning. In contrast, baseline synaptic connectivity strengths were consistently strong over the decades. Our findings suggest that the lifetime accrual of sensory experience optimizes functional brain architectures to enable efficient and generalizable predictions of the world.

Compact continuum brain model for human electroencephalogram

NASA Astrophysics Data System (ADS)

Kim, J. W.; Shin, H.-B.; Robinson, P. A.

2007-12-01

A low-dimensional, compact brain model has recently been developed based on physiologically based mean-field continuum formulation of electric activity of the brain. The essential feature of the new compact model is a second order time-delayed differential equation that has physiologically plausible terms, such as rapid corticocortical feedback and delayed feedback via extracortical pathways. Due to its compact form, the model facilitates insight into complex brain dynamics via standard linear and nonlinear techniques. The model successfully reproduces many features of previous models and experiments. For example, experimentally observed typical rhythms of electroencephalogram (EEG) signals are reproduced in a physiologically plausible parameter region. In the nonlinear regime, onsets of seizures, which often develop into limit cycles, are illustrated by modulating model parameters. It is also shown that a hysteresis can occur when the system has multiple attractors. As a further illustration of this approach, power spectra of the model are fitted to those of sleep EEGs of two subjects (one with apnea, the other with narcolepsy). The model parameters obtained from the fittings show good matches with previous literature. Our results suggest that the compact model can provide a theoretical basis for analyzing complex EEG signals.

The Future of Psychology: Connecting Mind to Brain

PubMed Central

Barrett, Lisa Feldman

2009-01-01

Psychological states such as thoughts and feelings are real. Brain states are real. The problem is that the two are not real in the same way, creating the mind–brain correspondence problem. In this article, I present a possible solution to this problem that involves two suggestions. First, complex psychological states such as emotion and cognition an be thought of as constructed events that can be causally reduced to a set of more basic, psychologically primitive ingredients that are more clearly respected by the brain. Second, complex psychological categories like emotion and cognition are the phenomena that require explanation in psychology, and, therefore, they cannot be abandoned by science. Describing the content and structure of these categories is a necessary and valuable scientific activity. Physical concepts are free creations of the human mind, and are not, however it may seem, uniquely determined by the external world.—Einstein & Infeld (1938, p. 33) The cardinal passions of our life, anger, love, fear, hate, hope, and the most comprehensive divisions of our intellectual activity, to remember, expect, think, know, dream (and he goes on to say, feel) are the only facts of a subjective order…—James (1890, p. 195) PMID:19844601

Fetal functional imaging portrays heterogeneous development of emerging human brain networks

PubMed Central

Jakab, András; Schwartz, Ernst; Kasprian, Gregor; Gruber, Gerlinde M.; Prayer, Daniela; Schöpf, Veronika; Langs, Georg

2014-01-01

The functional connectivity architecture of the adult human brain enables complex cognitive processes, and exhibits a remarkably complex structure shared across individuals. We are only beginning to understand its heterogeneous structure, ranging from a strongly hierarchical organization in sensorimotor areas to widely distributed networks in areas such as the parieto-frontal cortex. Our study relied on the functional magnetic resonance imaging (fMRI) data of 32 fetuses with no detectable morphological abnormalities. After adapting functional magnetic resonance acquisition, motion correction, and nuisance signal reduction procedures of resting-state functional data analysis to fetuses, we extracted neural activity information for major cortical and subcortical structures. Resting fMRI networks were observed for increasing regional functional connectivity from 21st to 38th gestational weeks (GWs) with a network-based statistical inference approach. The overall connectivity network, short range, and interhemispheric connections showed sigmoid expansion curve peaking at the 26–29 GW. In contrast, long-range connections exhibited linear increase with no periods of peaking development. Region-specific increase of functional signal synchrony followed a sequence of occipital (peak: 24.8 GW), temporal (peak: 26 GW), frontal (peak: 26.4 GW), and parietal expansion (peak: 27.5 GW). We successfully adapted functional neuroimaging and image post-processing approaches to correlate macroscopical scale activations in the fetal brain with gestational age. This in vivo study reflects the fact that the mid-fetal period hosts events that cause the architecture of the brain circuitry to mature, which presumably manifests in increasing strength of intra- and interhemispheric functional macro connectivity. PMID:25374531

Fetal functional imaging portrays heterogeneous development of emerging human brain networks.

PubMed

Jakab, András; Schwartz, Ernst; Kasprian, Gregor; Gruber, Gerlinde M; Prayer, Daniela; Schöpf, Veronika; Langs, Georg

2014-01-01

The functional connectivity architecture of the adult human brain enables complex cognitive processes, and exhibits a remarkably complex structure shared across individuals. We are only beginning to understand its heterogeneous structure, ranging from a strongly hierarchical organization in sensorimotor areas to widely distributed networks in areas such as the parieto-frontal cortex. Our study relied on the functional magnetic resonance imaging (fMRI) data of 32 fetuses with no detectable morphological abnormalities. After adapting functional magnetic resonance acquisition, motion correction, and nuisance signal reduction procedures of resting-state functional data analysis to fetuses, we extracted neural activity information for major cortical and subcortical structures. Resting fMRI networks were observed for increasing regional functional connectivity from 21st to 38th gestational weeks (GWs) with a network-based statistical inference approach. The overall connectivity network, short range, and interhemispheric connections showed sigmoid expansion curve peaking at the 26-29 GW. In contrast, long-range connections exhibited linear increase with no periods of peaking development. Region-specific increase of functional signal synchrony followed a sequence of occipital (peak: 24.8 GW), temporal (peak: 26 GW), frontal (peak: 26.4 GW), and parietal expansion (peak: 27.5 GW). We successfully adapted functional neuroimaging and image post-processing approaches to correlate macroscopical scale activations in the fetal brain with gestational age. This in vivo study reflects the fact that the mid-fetal period hosts events that cause the architecture of the brain circuitry to mature, which presumably manifests in increasing strength of intra- and interhemispheric functional macro connectivity.

Causes of metabolic syndrome and obesity-related co-morbidities Part 1: A composite unifying theory review of human-specific co-adaptations to brain energy consumption

PubMed Central

2014-01-01

One line summary Metabolic syndrome and obesity-related co-morbidities are largely explained by co-adaptations to the energy use of the large human brain in the cortico-limbic-striatal and NRF2 systems. The medical, research and general community is unable to effect significantly decreased rates of central obesity and related type II diabetes mellitus (TIIDM), cardiovascular disease (CVD) and cancer. All conditions seem to be linked by the concept of the metabolic syndrome (MetS), but the underlying causes are not known. MetS markers may have been mistaken for causes, thus many treatments are destined to be suboptimal. The current paper aims to critique current paradigms, give explanations for their persistence, and to return to first principles in an attempt to determine and clarify likely causes of MetS and obesity related comorbidities. A wide literature has been mined, study concepts analysed and the basics of human evolution and new biochemistry reviewed. A plausible, multifaceted composite unifying theory is formulated. The basis of the theory is that the proportionately large, energy-demanding human brain may have driven co-adaptive mechanisms to provide, or conserve, energy for the brain. A ‘dual system’ is proposed. 1) The enlarged, complex cortico-limbic-striatal system increases dietary energy by developing strong neural self-reward/motivation pathways for the acquisition of energy dense food, and (2) the nuclear factor-erythroid 2-related factor 2 (NRF2) cellular protection system amplifies antioxidant, antitoxicant and repair activity by employing plant chemicals, becoming highly energy efficient in humans. The still-evolving, complex human cortico-limbic-striatal system generates strong behavioural drives for energy dense food procurement, including motivating agricultural technologies and social system development. Addiction to such foods, leading to neglect of nutritious but less appetizing ‘common or garden’ food, appears to have occurred. Insufficient consumption of food micronutrients prevents optimal human NRF2 function. Inefficient oxidation of excess energy forces central and non-adipose cells to store excess toxic lipid. Oxidative stress and metabolic inflammation, or metaflammation, allow susceptibility to infectious, degenerative atherosclerotic cardiovascular, autoimmune, neurodegenerative and dysplastic diseases. Other relevant human-specific co-adaptations are examined, and encompass the unusual ability to store fat, certain vitamin pathways, the generalised but flexible intestine and microbiota, and slow development and longevity. This theory has significant past and future corollaries, which are explored in a separate article by McGill, A-T, in Archives of Public Health, 72: 31. PMID:25708524

Vulnerability of complex networks

NASA Astrophysics Data System (ADS)

Mishkovski, Igor; Biey, Mario; Kocarev, Ljupco

2011-01-01

We consider normalized average edge betweenness of a network as a metric of network vulnerability. We suggest that normalized average edge betweenness together with is relative difference when certain number of nodes and/or edges are removed from the network is a measure of network vulnerability, called vulnerability index. Vulnerability index is calculated for four synthetic networks: Erdős-Rényi (ER) random networks, Barabási-Albert (BA) model of scale-free networks, Watts-Strogatz (WS) model of small-world networks, and geometric random networks. Real-world networks for which vulnerability index is calculated include: two human brain networks, three urban networks, one collaboration network, and two power grid networks. We find that WS model of small-world networks and biological networks (human brain networks) are the most robust networks among all networks studied in the paper.

Between brains, bodies and things: tectonoetic awareness and the extended self.

PubMed

Malafouris, Lambros

2008-06-12

This paper presents the possible outline of a framework that will enable the incorporation of material culture into the study of the human self. To this end, I introduce the notions of extended self and tectonoetic awareness. Focusing on the complex interactions between brains, bodies and things and drawing a number of different and usually unconnected threads of evidence from archaeology, philosophy and neuroscience together, I present a view of selfhood as an extended and distributed phenomenon that is enacted across the skin barrier and which thus comprises both neural and extra-neural resources. Finally, I use the example of a gold Mycenaean signet ring to explore how a piece of inanimate matter can be seen (sometimes) as a constitutive and efficacious part of the human self-system.

Heterogeneous fractionation profiles of meta-analytic coactivation networks.

PubMed

Laird, Angela R; Riedel, Michael C; Okoe, Mershack; Jianu, Radu; Ray, Kimberly L; Eickhoff, Simon B; Smith, Stephen M; Fox, Peter T; Sutherland, Matthew T

2017-04-01

Computational cognitive neuroimaging approaches can be leveraged to characterize the hierarchical organization of distributed, functionally specialized networks in the human brain. To this end, we performed large-scale mining across the BrainMap database of coordinate-based activation locations from over 10,000 task-based experiments. Meta-analytic coactivation networks were identified by jointly applying independent component analysis (ICA) and meta-analytic connectivity modeling (MACM) across a wide range of model orders (i.e., d=20-300). We then iteratively computed pairwise correlation coefficients for consecutive model orders to compare spatial network topologies, ultimately yielding fractionation profiles delineating how "parent" functional brain systems decompose into constituent "child" sub-networks. Fractionation profiles differed dramatically across canonical networks: some exhibited complex and extensive fractionation into a large number of sub-networks across the full range of model orders, whereas others exhibited little to no decomposition as model order increased. Hierarchical clustering was applied to evaluate this heterogeneity, yielding three distinct groups of network fractionation profiles: high, moderate, and low fractionation. BrainMap-based functional decoding of resultant coactivation networks revealed a multi-domain association regardless of fractionation complexity. Rather than emphasize a cognitive-motor-perceptual gradient, these outcomes suggest the importance of inter-lobar connectivity in functional brain organization. We conclude that high fractionation networks are complex and comprised of many constituent sub-networks reflecting long-range, inter-lobar connectivity, particularly in fronto-parietal regions. In contrast, low fractionation networks may reflect persistent and stable networks that are more internally coherent and exhibit reduced inter-lobar communication. Copyright © 2017 Elsevier Inc. All rights reserved.

Heterogeneous fractionation profiles of meta-analytic coactivation networks

PubMed Central

Laird, Angela R.; Riedel, Michael C.; Okoe, Mershack; Jianu, Radu; Ray, Kimberly L.; Eickhoff, Simon B.; Smith, Stephen M.; Fox, Peter T.; Sutherland, Matthew T.

2017-01-01

Computational cognitive neuroimaging approaches can be leveraged to characterize the hierarchical organization of distributed, functionally specialized networks in the human brain. To this end, we performed large-scale mining across the BrainMap database of coordinate-based activation locations from over 10,000 task-based experiments. Meta-analytic coactivation networks were identified by jointly applying independent component analysis (ICA) and meta-analytic connectivity modeling (MACM) across a wide range of model orders (i.e., d = 20 to 300). We then iteratively computed pairwise correlation coefficients for consecutive model orders to compare spatial network topologies, ultimately yielding fractionation profiles delineating how “parent” functional brain systems decompose into constituent “child” sub-networks. Fractionation profiles differed dramatically across canonical networks: some exhibited complex and extensive fractionation into a large number of sub-networks across the full range of model orders, whereas others exhibited little to no decomposition as model order increased. Hierarchical clustering was applied to evaluate this heterogeneity, yielding three distinct groups of network fractionation profiles: high, moderate, and low fractionation. BrainMap-based functional decoding of resultant coactivation networks revealed a multi-domain association regardless of fractionation complexity. Rather than emphasize a cognitive-motor-perceptual gradient, these outcomes suggest the importance of inter-lobar connectivity in functional brain organization. We conclude that high fractionation networks are complex and comprised of many constituent sub-networks reflecting long-range, inter-lobar connectivity, particularly in fronto-parietal regions. In contrast, low fractionation networks may reflect persistent and stable networks that are more internally coherent and exhibit reduced inter-lobar communication. PMID:28222386

A quantitative magnetic resonance histology atlas of postnatal rat brain development with regional estimates of growth and variability.

PubMed

Calabrese, Evan; Badea, Alexandra; Watson, Charles; Johnson, G Allan

2013-05-01

There has been growing interest in the role of postnatal brain development in the etiology of several neurologic diseases. The rat has long been recognized as a powerful model system for studying neuropathology and the safety of pharmacologic treatments. However, the complex spatiotemporal changes that occur during rat neurodevelopment remain to be elucidated. This work establishes the first magnetic resonance histology (MRH) atlas of the developing rat brain, with an emphasis on quantitation. The atlas comprises five specimens at each of nine time points, imaged with eight distinct MR contrasts and segmented into 26 developmentally defined brain regions. The atlas was used to establish a timeline of morphometric changes and variability throughout neurodevelopment and represents a quantitative database of rat neurodevelopment for characterizing rat models of human neurologic disease. Published by Elsevier Inc.

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

Reward-based hypertension control by a synthetic brain-dopamine interface.

PubMed

Rössger, Katrin; Charpin-El Hamri, Ghislaine; Fussenegger, Martin

2013-11-05

Synthetic biology has significantly advanced the design of synthetic trigger-controlled devices that can reprogram mammalian cells to interface with complex metabolic activities. In the brain, the neurotransmitter dopamine coordinates communication with target neurons via a set of dopamine receptors that control behavior associated with reward-driven learning. This dopamine transmission has recently been suggested to increase central sympathetic outflow, resulting in plasma dopamine levels that correlate with corresponding brain activities. By functionally rewiring the human dopamine receptor D1 (DRD1) via the second messenger cyclic adenosine monophosphate (cAMP) to synthetic promoters containing cAMP response element-binding protein 1(CREB1)-specific cAMP-responsive operator modules, we have designed a synthetic dopamine-sensitive transcription controller that reversibly fine-tunes specific target gene expression at physiologically relevant brain-derived plasma dopamine levels. Following implantation of circuit-transgenic human cell lines insulated by semipermeable immunoprotective microcontainers into mice, the designer device interfaced with dopamine-specific brain activities and produced a systemic expression response when the animal's reward system was stimulated by food, sexual arousal, or addictive drugs. Reward-triggered brain activities were able to remotely program peripheral therapeutic implants to produce sufficient amounts of the atrial natriuretic peptide, which reduced the blood pressure of hypertensive mice to the normal physiologic range. Seamless control of therapeutic transgenes by subconscious behavior may provide opportunities for treatment strategies of the future.

Resolving anatomical and functional structure in human brain organization: identifying mesoscale organization in weighted network representations.

PubMed

Lohse, Christian; Bassett, Danielle S; Lim, Kelvin O; Carlson, Jean M

2014-10-01

Human brain anatomy and function display a combination of modular and hierarchical organization, suggesting the importance of both cohesive structures and variable resolutions in the facilitation of healthy cognitive processes. However, tools to simultaneously probe these features of brain architecture require further development. We propose and apply a set of methods to extract cohesive structures in network representations of brain connectivity using multi-resolution techniques. We employ a combination of soft thresholding, windowed thresholding, and resolution in community detection, that enable us to identify and isolate structures associated with different weights. One such mesoscale structure is bipartivity, which quantifies the extent to which the brain is divided into two partitions with high connectivity between partitions and low connectivity within partitions. A second, complementary mesoscale structure is modularity, which quantifies the extent to which the brain is divided into multiple communities with strong connectivity within each community and weak connectivity between communities. Our methods lead to multi-resolution curves of these network diagnostics over a range of spatial, geometric, and structural scales. For statistical comparison, we contrast our results with those obtained for several benchmark null models. Our work demonstrates that multi-resolution diagnostic curves capture complex organizational profiles in weighted graphs. We apply these methods to the identification of resolution-specific characteristics of healthy weighted graph architecture and altered connectivity profiles in psychiatric disease.

Regulating with imagery and the complexity of basic emotions. Comment on "The quartet theory of human emotions: An integrative and neurofunctional model" by S. Koelsch et al.

NASA Astrophysics Data System (ADS)

Meyer, Marcel; Kuchinke, Lars

2015-06-01

Literature, music and the arts have long attested to the complexity of human emotions. Hitherto, psychological and biological theories of emotions have largely neglected this rich heritage. In their review Koelsch and colleagues [1] have embarked upon the pioneering endeavour of integrating the diverse perspectives in emotion research. Noting that the focus of prior neurobiological theories relies mainly on animal studies, the authors sought to complement this body of research with a model of complex ("moral") emotions in humans (henceforth: complex emotions). According to this novel framework, there are four main interacting affective centres in the brain. Each centre is associated with a dominant affective function, such as ascending activation (brainstem), pain/pleasure (diencephalon), attachment-related affects (hippocampus) or moral emotions and unconscious cognitive appraisal (orbitofrontal cortex). Furthermore, language is ascribed a key role in (a) the communication of subjective feeling (reconfiguration) and (b) in the conscious regulation of emotions (by means of logic and rational thought).

Manganese-Enhanced Magnetic Resonance Imaging Reflects Brain Pathology During Progressive HIV-1 Infection of Humanized Mice.

PubMed

Bade, Aditya N; Gorantla, Santhi; Dash, Prasanta K; Makarov, Edward; Sajja, Balasrinivasa R; Poluektova, Larisa Y; Luo, Jiangtao; Gendelman, Howard E; Boska, Michael D; Liu, Yutong

2016-07-01

Progressive human immunodeficiency viral (HIV) infection commonly leads to a constellation of cognitive, motor, and behavioral impairments. These are collectively termed HIV-associated neurocognitive disorders (HAND). While antiretroviral therapy (ART) reduces HAND severity, it does not affect disease prevalence. Despite decades of research, there remain no biomarkers for HAND and all potential comorbid conditions must first be excluded for a diagnosis to be made. To this end, we now report that manganese (Mn(2+))-enhanced magnetic resonance imaging (MEMRI) can reflect brain region-specific HIV-1-induced neuropathology in chronically virus-infected NOD/scid-IL-2Rγc(null) humanized mice. MEMRI diagnostics mirrors the abilities of Mn(2+) to enter and accumulate in affected neurons during disease. T1 relaxivity and its weighted signal intensity are proportional to Mn(2+) activities in neurons. In 16-week virus-infected humanized mice, altered MEMRI signal enhancement was easily observed in affected brain regions. These included, but were not limited to, the hippocampus, amygdala, thalamus, globus pallidus, caudoputamen, substantia nigra, and cerebellum. MEMRI signal was coordinated with levels of HIV-1 infection, neuroinflammation (astro- and micro-gliosis), and neuronal injury. MEMRI accurately demonstrates the complexities of HIV-1-associated neuropathology in rodents that reflects, in measure, the clinical manifestations of neuroAIDS as it is seen in a human host.

Hemispheric Asymmetry of Visual Scene Processing in the Human Brain: Evidence from Repetition Priming and Intrinsic Activity

PubMed Central

Kahn, Itamar; Wig, Gagan S.; Schacter, Daniel L.

2012-01-01

Asymmetrical specialization of cognitive processes across the cerebral hemispheres is a hallmark of healthy brain development and an important evolutionary trait underlying higher cognition in humans. While previous research, including studies of priming, divided visual field presentation, and split-brain patients, demonstrates a general pattern of right/left asymmetry of form-specific versus form-abstract visual processing, little is known about brain organization underlying this dissociation. Here, using repetition priming of complex visual scenes and high-resolution functional magnetic resonance imaging (MRI), we demonstrate asymmetrical form specificity of visual processing between the right and left hemispheres within a region known to be critical for processing of visual spatial scenes (parahippocampal place area [PPA]). Next, we use resting-state functional connectivity MRI analyses to demonstrate that this functional asymmetry is associated with differential intrinsic activity correlations of the right versus left PPA with regions critically involved in perceptual versus conceptual processing, respectively. Our results demonstrate that the PPA comprises lateralized subregions across the cerebral hemispheres that are engaged in functionally dissociable yet complementary components of visual scene analysis. Furthermore, this functional asymmetry is associated with differential intrinsic functional connectivity of the PPA with distinct brain areas known to mediate dissociable cognitive processes. PMID:21968568

Hemispheric asymmetry of visual scene processing in the human brain: evidence from repetition priming and intrinsic activity.

PubMed

Stevens, W Dale; Kahn, Itamar; Wig, Gagan S; Schacter, Daniel L

2012-08-01

Asymmetrical specialization of cognitive processes across the cerebral hemispheres is a hallmark of healthy brain development and an important evolutionary trait underlying higher cognition in humans. While previous research, including studies of priming, divided visual field presentation, and split-brain patients, demonstrates a general pattern of right/left asymmetry of form-specific versus form-abstract visual processing, little is known about brain organization underlying this dissociation. Here, using repetition priming of complex visual scenes and high-resolution functional magnetic resonance imaging (MRI), we demonstrate asymmetrical form specificity of visual processing between the right and left hemispheres within a region known to be critical for processing of visual spatial scenes (parahippocampal place area [PPA]). Next, we use resting-state functional connectivity MRI analyses to demonstrate that this functional asymmetry is associated with differential intrinsic activity correlations of the right versus left PPA with regions critically involved in perceptual versus conceptual processing, respectively. Our results demonstrate that the PPA comprises lateralized subregions across the cerebral hemispheres that are engaged in functionally dissociable yet complementary components of visual scene analysis. Furthermore, this functional asymmetry is associated with differential intrinsic functional connectivity of the PPA with distinct brain areas known to mediate dissociable cognitive processes.

The sleeping brain as a complex system.

PubMed

Olbrich, Eckehard; Achermann, Peter; Wennekers, Thomas

2011-10-13

'Complexity science' is a rapidly developing research direction with applications in a multitude of fields that study complex systems consisting of a number of nonlinear elements with interesting dynamics and mutual interactions. This Theme Issue 'The complexity of sleep' aims at fostering the application of complexity science to sleep research, because the brain in its different sleep stages adopts different global states that express distinct activity patterns in large and complex networks of neural circuits. This introduction discusses the contributions collected in the present Theme Issue. We highlight the potential and challenges of a complex systems approach to develop an understanding of the brain in general and the sleeping brain in particular. Basically, we focus on two topics: the complex networks approach to understand the changes in the functional connectivity of the brain during sleep, and the complex dynamics of sleep, including sleep regulation. We hope that this Theme Issue will stimulate and intensify the interdisciplinary communication to advance our understanding of the complex dynamics of the brain that underlies sleep and consciousness.

Detailed spatiotemporal brain mapping of chromatic vision combining high-resolution VEP with fMRI and retinotopy.

PubMed

Pitzalis, Sabrina; Strappini, Francesca; Bultrini, Alessandro; Di Russo, Francesco

2018-03-13

Neuroimaging studies have identified so far, several color-sensitive visual areas in the human brain, and the temporal dynamics of these activities have been separately investigated using the visual-evoked potentials (VEPs). In the present study, we combined electrophysiological and neuroimaging methods to determine a detailed spatiotemporal profile of chromatic VEP and to localize its neural generators. The accuracy of the present co-registration study was obtained by combining standard fMRI data with retinotopic and motion mapping data at the individual level. We found a sequence of occipito activities more complex than that typically reported for chromatic VEPs, including feed-forward and reentrant feedback. Results showed that chromatic human perception arises by the combined activity of at the least five parieto-occipital areas including V1, LOC, V8/VO, and the motion-sensitive dorsal region MT+. However, the contribution of V1 and V8/VO seems dominant because the re-entrant activity in these areas was present more than once (twice in V8/VO and thrice in V1). This feedforward and feedback chromatic processing appears delayed compared with the luminance processing. Associating VEPs and neuroimaging measures, we showed for the first time a complex spatiotemporal pattern of activity, confirming that chromatic stimuli produce intricate interactions of many different brain dorsal and ventral areas. © 2018 Wiley Periodicals, Inc.

Effect of head motion on MRI B0 field distribution.

PubMed

Liu, Jiaen; de Zwart, Jacco A; van Gelderen, Peter; Murphy-Boesch, Joseph; Duyn, Jeff H

2018-05-16

To identify and characterize the sources of B 0 field changes due to head motion, to reduce motion sensitivity in human brain MRI. B 0 fields were measured in 5 healthy human volunteers at various head poses. After measurement of the total field, the field originating from the subject was calculated by subtracting the external field generated by the magnet and shims. A subject-specific susceptibility model was created to quantify the contribution of the head and torso. The spatial complexity of the field changes was analyzed using spherical harmonic expansion. Minor head pose changes can cause substantial and spatially complex field changes in the brain. For rotations and translations of approximately 5 º and 5 mm, respectively, at 7 T, the field change that is associated with the subject's magnetization generates a standard deviation (SD) of about 10 Hz over the brain. The stationary torso contributes to this subject-associated field change significantly with a SD of about 5 Hz. The subject-associated change leads to image-corrupting phase errors in multi-shot T2*-weighted acquisitions. The B 0 field changes arising from head motion are problematic for multishot T2*-weighted imaging. Characterization of the underlying sources provides new insights into mitigation strategies, which may benefit from individualized predictive field models in addition to real-time field monitoring and correction strategies. © 2018 International Society for Magnetic Resonance in Medicine.

Planning Ahead: Object-Directed Sequential Actions Decoded from Human Frontoparietal and Occipitotemporal Networks

PubMed Central

Gallivan, Jason P.; Johnsrude, Ingrid S.; Randall Flanagan, J.

2016-01-01

Object-manipulation tasks (e.g., drinking from a cup) typically involve sequencing together a series of distinct motor acts (e.g., reaching toward, grasping, lifting, and transporting the cup) in order to accomplish some overarching goal (e.g., quenching thirst). Although several studies in humans have investigated the neural mechanisms supporting the planning of visually guided movements directed toward objects (such as reaching or pointing), only a handful have examined how manipulatory sequences of actions—those that occur after an object has been grasped—are planned and represented in the brain. Here, using event-related functional MRI and pattern decoding methods, we investigated the neural basis of real-object manipulation using a delayed-movement task in which participants first prepared and then executed different object-directed action sequences that varied either in their complexity or final spatial goals. Consistent with previous reports of preparatory brain activity in non-human primates, we found that activity patterns in several frontoparietal areas reliably predicted entire action sequences in advance of movement. Notably, we found that similar sequence-related information could also be decoded from pre-movement signals in object- and body-selective occipitotemporal cortex (OTC). These findings suggest that both frontoparietal and occipitotemporal circuits are engaged in transforming object-related information into complex, goal-directed movements. PMID:25576538

Outer brain barriers in rat and human development

PubMed Central

Brøchner, Christian B.; Holst, Camilla B.; Møllgård, Kjeld

2015-01-01

Complex barriers at the brain's surface, particularly in development, are poorly defined. In the adult, arachnoid blood-cerebrospinal fluid (CSF) barrier separates the fenestrated dural vessels from the CSF by means of a cell layer joined by tight junctions. Outer CSF-brain barrier provides diffusion restriction between brain and subarachnoid CSF through an initial radial glial end feet layer covered with a pial surface layer. To further characterize these interfaces we examined embryonic rat brains from E10 to P0 and forebrains from human embryos and fetuses (6–21st weeks post-conception) and adults using immunohistochemistry and confocal microscopy. Antibodies against claudin-11, BLBP, collagen 1, SSEA-4, MAP2, YKL-40, and its receptor IL-13Rα2 and EAAT1 were used to describe morphological characteristics and functional aspects of the outer brain barriers. Claudin-11 was a reliable marker of the arachnoid blood-CSF barrier. Collagen 1 delineated the subarachnoid space and stained pial surface layer. BLBP defined radial glial end feet layer and SSEA-4 and YKL-40 were present in both leptomeningeal cells and end feet layer, which transformed into glial limitans. IL-13Rα2 and EAAT1 were present in the end feet layer illustrating transporter/receptor presence in the outer CSF-brain barrier. MAP2 immunostaining in adult brain outlined the lower border of glia limitans; remnants of end feet were YKL-40 positive in some areas. We propose that outer brain barriers are composed of at least 3 interfaces: blood-CSF barrier across arachnoid barrier cell layer, blood-CSF barrier across pial microvessels, and outer CSF-brain barrier comprising glial end feet layer/pial surface layer. PMID:25852456

Outer brain barriers in rat and human development.

PubMed

Brøchner, Christian B; Holst, Camilla B; Møllgård, Kjeld

2015-01-01

Complex barriers at the brain's surface, particularly in development, are poorly defined. In the adult, arachnoid blood-cerebrospinal fluid (CSF) barrier separates the fenestrated dural vessels from the CSF by means of a cell layer joined by tight junctions. Outer CSF-brain barrier provides diffusion restriction between brain and subarachnoid CSF through an initial radial glial end feet layer covered with a pial surface layer. To further characterize these interfaces we examined embryonic rat brains from E10 to P0 and forebrains from human embryos and fetuses (6-21st weeks post-conception) and adults using immunohistochemistry and confocal microscopy. Antibodies against claudin-11, BLBP, collagen 1, SSEA-4, MAP2, YKL-40, and its receptor IL-13Rα2 and EAAT1 were used to describe morphological characteristics and functional aspects of the outer brain barriers. Claudin-11 was a reliable marker of the arachnoid blood-CSF barrier. Collagen 1 delineated the subarachnoid space and stained pial surface layer. BLBP defined radial glial end feet layer and SSEA-4 and YKL-40 were present in both leptomeningeal cells and end feet layer, which transformed into glial limitans. IL-13Rα2 and EAAT1 were present in the end feet layer illustrating transporter/receptor presence in the outer CSF-brain barrier. MAP2 immunostaining in adult brain outlined the lower border of glia limitans; remnants of end feet were YKL-40 positive in some areas. We propose that outer brain barriers are composed of at least 3 interfaces: blood-CSF barrier across arachnoid barrier cell layer, blood-CSF barrier across pial microvessels, and outer CSF-brain barrier comprising glial end feet layer/pial surface layer.

From monkey-like action recognition to human language: an evolutionary framework for neurolinguistics.

PubMed

Arbib, Michael A

2005-04-01

The article analyzes the neural and functional grounding of language skills as well as their emergence in hominid evolution, hypothesizing stages leading from abilities known to exist in monkeys and apes and presumed to exist in our hominid ancestors right through to modern spoken and signed languages. The starting point is the observation that both premotor area F5 in monkeys and Broca's area in humans contain a "mirror system" active for both execution and observation of manual actions, and that F5 and Broca's area are homologous brain regions. This grounded the mirror system hypothesis of Rizzolatti and Arbib (1998) which offers the mirror system for grasping as a key neural "missing link" between the abilities of our nonhuman ancestors of 20 million years ago and modern human language, with manual gestures rather than a system for vocal communication providing the initial seed for this evolutionary process. The present article, however, goes "beyond the mirror" to offer hypotheses on evolutionary changes within and outside the mirror systems which may have occurred to equip Homo sapiens with a language-ready brain. Crucial to the early stages of this progression is the mirror system for grasping and its extension to permit imitation. Imitation is seen as evolving via a so-called simple system such as that found in chimpanzees (which allows imitation of complex "object-oriented" sequences but only as the result of extensive practice) to a so-called complex system found in humans (which allows rapid imitation even of complex sequences, under appropriate conditions) which supports pantomime. This is hypothesized to have provided the substrate for the development of protosign, a combinatorially open repertoire of manual gestures, which then provides the scaffolding for the emergence of protospeech (which thus owes little to nonhuman vocalizations), with protosign and protospeech then developing in an expanding spiral. It is argued that these stages involve biological evolution of both brain and body. By contrast, it is argued that the progression from protosign and protospeech to languages with full-blown syntax and compositional semantics was a historical phenomenon in the development of Homo sapiens, involving few if any further biological changes.

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

Myelination, oligodendrocytes, and serious mental illness.

PubMed

Haroutunian, V; Katsel, P; Roussos, P; Davis, K L; Altshuler, L L; Bartzokis, G

2014-11-01

Historically, the human brain has been conceptually segregated from the periphery and further dichotomized into gray matter (GM) and white matter (WM) based on the whitish appearance of the exceptionally high lipid content of the myelin sheaths encasing neuronal axons. These simplistic dichotomies were unfortunately extended to conceptually segregate neurons from glia, cognition from behavior, and have been codified in the separation of clinical and scientific fields into medicine, psychiatry, neurology, pathology, etc. The discrete classifications have helped obscure the importance of continual dynamic communication between all brain cell types (neurons, astrocytes, microglia, oligodendrocytes, and precursor (NG2) cells) as well as between brain and periphery through multiple signaling systems. The signaling systems range from neurotransmitters to insulin, angiotensin, and multiple kinases such a glycogen synthase kinase 3 (GSK-3) that together help integrate metabolism, inflammation, and myelination processes and orchestrate the development, plasticity, maintenance, and repair that continually optimize function of neural networks. A more comprehensive, evolution-based, systems biology approach that integrates brain, body, and environmental interactions may ultimately prove more fruitful in elucidating the complexities of human brain function. The historic focus on neurons/GM is rebalanced herein by highlighting the importance of a systems-level understanding of the interdependent age-related shifts in both central and peripheral homeostatic mechanisms that can lead to remarkably prevalent and devastating neuropsychiatric diseases. Herein we highlight the role of glia, especially the most recently evolved oligodendrocytes and the myelin they produce, in achieving and maintaining optimal brain function. The human brain undergoes exceptionally protracted and pervasive myelination (even throughout its GM) and can thus achieve and maintain the rapid conduction and synchronous timing of neural networks on which optimal function depends. The continuum of increasing myelin vulnerability resulting from the human brain's protracted myelination underlies underappreciated communalities between different disease phenotypes ranging from developmental ones such as schizophrenia (SZ) and bipolar disorder (BD) to degenerative ones such as Alzheimer's disease (AD). These shared vulnerabilities also expose significant yet underexplored opportunities for novel treatment and prevention approaches that have the potential to considerably reduce the tremendous burden of neuropsychiatric disease. © 2014 Wiley Periodicals, Inc.

Nonlocal atlas-guided multi-channel forest learning for human brain labeling

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

Ma, Guangkai; Gao, Yaozong; Wu, Guorong

Purpose: It is important for many quantitative brain studies to label meaningful anatomical regions in MR brain images. However, due to high complexity of brain structures and ambiguous boundaries between different anatomical regions, the anatomical labeling of MR brain images is still quite a challenging task. In many existing label fusion methods, appearance information is widely used. However, since local anatomy in the human brain is often complex, the appearance information alone is limited in characterizing each image point, especially for identifying the same anatomical structure across different subjects. Recent progress in computer vision suggests that the context features canmore » be very useful in identifying an object from a complex scene. In light of this, the authors propose a novel learning-based label fusion method by using both low-level appearance features (computed from the target image) and high-level context features (computed from warped atlases or tentative labeling maps of the target image). Methods: In particular, the authors employ a multi-channel random forest to learn the nonlinear relationship between these hybrid features and target labels (i.e., corresponding to certain anatomical structures). Specifically, at each of the iterations, the random forest will output tentative labeling maps of the target image, from which the authors compute spatial label context features and then use in combination with original appearance features of the target image to refine the labeling. Moreover, to accommodate the high inter-subject variations, the authors further extend their learning-based label fusion to a multi-atlas scenario, i.e., they train a random forest for each atlas and then obtain the final labeling result according to the consensus of results from all atlases. Results: The authors have comprehensively evaluated their method on both public LONI-LBPA40 and IXI datasets. To quantitatively evaluate the labeling accuracy, the authors use the dice similarity coefficient to measure the overlap degree. Their method achieves average overlaps of 82.56% on 54 regions of interest (ROIs) and 79.78% on 80 ROIs, respectively, which significantly outperform the baseline method (random forests), with the average overlaps of 72.48% on 54 ROIs and 72.09% on 80 ROIs, respectively. Conclusions: The proposed methods have achieved the highest labeling accuracy, compared to several state-of-the-art methods in the literature.« less

Nonlocal atlas-guided multi-channel forest learning for human brain labeling

PubMed Central

Ma, Guangkai; Gao, Yaozong; Wu, Guorong; Wu, Ligang; Shen, Dinggang

2016-01-01

Purpose: It is important for many quantitative brain studies to label meaningful anatomical regions in MR brain images. However, due to high complexity of brain structures and ambiguous boundaries between different anatomical regions, the anatomical labeling of MR brain images is still quite a challenging task. In many existing label fusion methods, appearance information is widely used. However, since local anatomy in the human brain is often complex, the appearance information alone is limited in characterizing each image point, especially for identifying the same anatomical structure across different subjects. Recent progress in computer vision suggests that the context features can be very useful in identifying an object from a complex scene. In light of this, the authors propose a novel learning-based label fusion method by using both low-level appearance features (computed from the target image) and high-level context features (computed from warped atlases or tentative labeling maps of the target image). Methods: In particular, the authors employ a multi-channel random forest to learn the nonlinear relationship between these hybrid features and target labels (i.e., corresponding to certain anatomical structures). Specifically, at each of the iterations, the random forest will output tentative labeling maps of the target image, from which the authors compute spatial label context features and then use in combination with original appearance features of the target image to refine the labeling. Moreover, to accommodate the high inter-subject variations, the authors further extend their learning-based label fusion to a multi-atlas scenario, i.e., they train a random forest for each atlas and then obtain the final labeling result according to the consensus of results from all atlases. Results: The authors have comprehensively evaluated their method on both public LONI_LBPA40 and IXI datasets. To quantitatively evaluate the labeling accuracy, the authors use the dice similarity coefficient to measure the overlap degree. Their method achieves average overlaps of 82.56% on 54 regions of interest (ROIs) and 79.78% on 80 ROIs, respectively, which significantly outperform the baseline method (random forests), with the average overlaps of 72.48% on 54 ROIs and 72.09% on 80 ROIs, respectively. Conclusions: The proposed methods have achieved the highest labeling accuracy, compared to several state-of-the-art methods in the literature. PMID:26843260

Neural codes of seeing architectural styles

PubMed Central

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

2017-01-01

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

Obesity and insulin resistance are associated with reduced activity in core memory regions of the brain.

PubMed

Cheke, Lucy G; Bonnici, Heidi M; Clayton, Nicola S; Simons, Jon S

2017-02-01

Increasing research in animals and humans suggests that obesity may be associated with learning and memory deficits, and in particular with reductions in episodic memory. Rodent models have implicated the hippocampus in obesity-related memory impairments, but the neural mechanisms underlying episodic memory deficits in obese humans remain undetermined. In the present study, lean and obese human participants were scanned using fMRI while completing a What-Where-When episodic memory test (the "Treasure-Hunt Task") that assessed the ability to remember integrated item, spatial, and temporal details of previously encoded complex events. In lean participants, the Treasure-Hunt task elicited significant activity in regions of the brain known to be important for recollecting episodic memories, such as the hippocampus, angular gyrus, and dorsolateral prefrontal cortex. Both obesity and insulin resistance were associated with significantly reduced functional activity throughout the core recollection network. These findings indicate that obesity is associated with reduced functional activity in core brain areas supporting episodic memory and that insulin resistance may be a key player in this association. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Neural codes of seeing architectural styles.

PubMed

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

2017-01-10

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

Origin of hyperbolicity in brain-to-brain coordination networks

NASA Astrophysics Data System (ADS)

Tadić, Bosiljka; Andjelković, Miroslav; Šuvakov, Milovan

2018-02-01

Hyperbolicity or negative curvature of complex networks is the intrinsic geometric proximity of nodes in the graph metric space, which implies an improved network function. Here, we investigate hidden combinatorial geometries in brain-to-brain coordination networks arising through social communications. The networks originate from correlations among EEG signals previously recorded during spoken communications comprising of 14 individuals with 24 speaker-listener pairs. We find that the corresponding networks are delta-hyperbolic with delta_max=1 and the graph diameter D=3 in each brain. While the emergent hyperbolicity in the two-brain networks satisfies delta_max/D/2 < 1 and can be attributed to the topology of the subgraph formed around the cross-brains linking channels. We identify these subgraphs in each studied two-brain network and decompose their structure into simple geometric descriptors (triangles, tetrahedra and cliques of higher orders) that contribute to hyperbolicity. Considering topologies that exceed two separate brain networks as a measure of coordination synergy between the brains, we identify different neuronal correlation patterns ranging from weak coordination to super-brain structure. These topology features are in qualitative agreement with the listener’s self-reported ratings of own experience and quality of the speaker, suggesting that studies of the cross-brain connector networks can reveal new insight into the neural mechanisms underlying human social behavior.

ApoE and Sex Bias in Cerebrovascular Aging of Men and Mice

PubMed Central

Finch, Caleb E.; Shams, Sara

2016-01-01

Alzheimer disease (AD) research has mainly focused on neurodegenerative processes associated with the classic neuropathologic markers of senile plaques and neurofibrillary tangles. Additionally, cerebrovascular contributions to dementia are increasingly recognized, particularly from cerebral small vessel disease (SVD). Remarkably, in AD brains, the ApoE ε4 allele shows male excess for cerebral microbleeds (CMB), a marker of SVD, which is opposite to the female excess of plaques and tangles. Mouse transgenic models add further complexities to sex-ApoE ε4 allele interactions, with female excess of CMBs and brain amyloid. We conclude that brain aging and AD pathogenesis cannot be understood in humans without addressing major gaps in the extent of sex differences in cerebrovascular pathology. PMID:27546867

Social Distance Evaluation in Human Parietal Cortex

PubMed Central

Yamakawa, Yoshinori; Kanai, Ryota; Matsumura, Michikazu; Naito, Eiichi

2009-01-01

Across cultures, social relationships are often thought of, described, and acted out in terms of physical space (e.g. “close friends” “high lord”). Does this cognitive mapping of social concepts arise from shared brain resources for processing social and physical relationships? Using fMRI, we found that the tasks of evaluating social compatibility and of evaluating physical distances engage a common brain substrate in the parietal cortex. The present study shows the possibility of an analytic brain mechanism to process and represent complex networks of social relationships. Given parietal cortex's known role in constructing egocentric maps of physical space, our present findings may help to explain the linguistic, psychological and behavioural links between social and physical space. PMID:19204791

Voxelwise Spectral Diffusional Connectivity and its Applications to Alzheimer’s Disease and Intelligence Prediction

PubMed Central

Li, Junning; Jin, Yan; Shi, Yonggang; Dinov, Ivo D.; Wang, Danny J.; Toga, Arthur W.; Thompson, Paul M.

2014-01-01

Human brain connectivity can be studied using graph theory. Many connectivity studies parcellate the brain into regions and count fibres extracted between them. The resulting network analyses require validation of the tractography, as well as region and parameter selection. Here we investigate whole brain connectivity from a different perspective. We propose a mathematical formulation based on studying the eigenvalues of the Laplacian matrix of the diffusion tensor field at the voxel level. This voxelwise matrix has over a million parameters, but we derive the Kirchhoff complexity and eigen-spectrum through elegant mathematical theorems, without heavy computation. We use these novel measures to accurately estimate the voxelwise connectivity in multiple biomedical applications such as Alzheimer’s disease and intelligence prediction. PMID:24505723

Sulci segmentation using geometric active contours

NASA Astrophysics Data System (ADS)

Torkaman, Mahsa; Zhu, Liangjia; Karasev, Peter; Tannenbaum, Allen

2017-02-01

Sulci are groove-like regions lying in the depth of the cerebral cortex between gyri, which together, form a folded appearance in human and mammalian brains. Sulci play an important role in the structural analysis of the brain, morphometry (i.e., the measurement of brain structures), anatomical labeling and landmark-based registration.1 Moreover, sulcal morphological changes are related to cortical thickness, whose measurement may provide useful information for studying variety of psychiatric disorders. Manually extracting sulci requires complying with complex protocols, which make the procedure both tedious and error prone.2 In this paper, we describe an automatic procedure, employing geometric active contours, which extract the sulci. Sulcal boundaries are obtained by minimizing a certain energy functional whose minimum is attained at the boundary of the given sulci.

Methodological considerations in conducting an olfactory fMRI study.

PubMed

Vedaei, Faezeh; Fakhri, Mohammad; Harirchian, Mohammad Hossein; Firouznia, Kavous; Lotfi, Yones; Ali Oghabian, Mohammad

2013-01-01

The sense of smell is a complex chemosensory processing in human and animals that allows them to connect with the environment as one of their chief sensory systems. In the field of functional brain imaging, many studies have focused on locating brain regions that are involved during olfactory processing. Despite wealth of literature about brain network in different olfactory tasks, there is a paucity of data regarding task design. Moreover, considering importance of olfactory tasks for patients with variety of neurological diseases, special contemplations should be addressed for patients. In this article, we review current olfaction tasks for behavioral studies and functional neuroimaging assessments, as well as technical principles regarding utilization of these tasks in functional magnetic resonance imaging studies.

Rich-club organization of the newborn human brain

PubMed Central

Ball, Gareth; Aljabar, Paul; Zebari, Sally; Tusor, Nora; Arichi, Tomoki; Merchant, Nazakat; Robinson, Emma C.; Ogundipe, Enitan; Rueckert, Daniel; Edwards, A. David; Counsell, Serena J.

2014-01-01

Combining diffusion magnetic resonance imaging and network analysis in the adult human brain has identified a set of highly connected cortical hubs that form a “rich club”—a high-cost, high-capacity backbone thought to enable efficient network communication. Rich-club architecture appears to be a persistent feature of the mature mammalian brain, but it is not known when this structure emerges during human development. In this longitudinal study we chart the emergence of structural organization in mid to late gestation. We demonstrate that a rich club of interconnected cortical hubs is already present by 30 wk gestation. Subsequently, until the time of normal birth, the principal development is a proliferation of connections between core hubs and the rest of the brain. We also consider the impact of environmental factors on early network development, and compare term-born neonates to preterm infants at term-equivalent age. Though rich-club organization remains intact following premature birth, we reveal significant disruptions in both in cortical–subcortical connectivity and short-distance corticocortical connections. Rich club organization is present well before the normal time of birth and may provide the fundamental structural architecture for the subsequent emergence of complex neurological functions. Premature exposure to the extrauterine environment is associated with altered network architecture and reduced network capacity, which may in part account for the high prevalence of cognitive problems in preterm infants. PMID:24799693

Rich club network analysis shows distinct patterns of disruption in frontotemporal dementia and Alzheimer’s disease

PubMed Central

Daianu, Madelaine; Jahanshad, Neda; Villalon-Reina, Julio E.; Mendez, Mario F.; Bartzokis, George; Jimenez, Elvira E.; Joshi, Aditi; Barsuglia, Joseph; Thompson, Paul M.

2015-01-01

Diffusion imaging and brain connectivity analyses can reveal the underlying organizational patterns of the human brain, described as complex networks of densely interlinked regions. Here, we analyzed 1.5-Tesla whole-brain diffusion-weighted images from 64 participants – 15 patients with behavioral variant frontotemporal (bvFTD) dementia, 19 with early-onset Alzheimer’s disease (EOAD), and 30 healthy elderly controls. Based on whole-brain tractography, we reconstructed structural brain connectivity networks to map connections between cortical regions. We examined how bvFTD and EOAD disrupt the weighted ‘rich club’ – a network property where high-degree network nodes are more interconnected than expected by chance. bvFTD disrupts both the nodal and global organization of the network in both low- and high-degree regions of the brain. EOAD targets the global connectivity of the brain, mainly affecting the fiber density of high-degree (highly connected) regions that form the rich club network. These rich club analyses suggest distinct patterns of disruptions among different forms of dementia. PMID:26161050

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

PubMed Central

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

2017-01-01

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

Intra- and inter-brain synchronization during musical improvisation on the guitar.

PubMed

Müller, Viktor; Sänger, Johanna; Lindenberger, Ulman

2013-01-01

Humans interact with the environment through sensory and motor acts. Some of these interactions require synchronization among two or more individuals. Multiple-trial designs, which we have used in past work to study interbrain synchronization in the course of joint action, constrain the range of observable interactions. To overcome the limitations of multiple-trial designs, we conducted single-trial analyses of electroencephalography (EEG) signals recorded from eight pairs of guitarists engaged in musical improvisation. We identified hyper-brain networks based on a complex interplay of different frequencies. The intra-brain connections primarily involved higher frequencies (e.g., beta), whereas inter-brain connections primarily operated at lower frequencies (e.g., delta and theta). The topology of hyper-brain networks was frequency-dependent, with a tendency to become more regular at higher frequencies. We also found hyper-brain modules that included nodes (i.e., EEG electrodes) from both brains. Some of the observed network properties were related to musical roles during improvisation. Our findings replicate and extend earlier work and point to mechanisms that enable individuals to engage in temporally coordinated joint action.

Intra- and Inter-Brain Synchronization during Musical Improvisation on the Guitar

PubMed Central

Müller, Viktor; Sänger, Johanna; Lindenberger, Ulman

2013-01-01

Humans interact with the environment through sensory and motor acts. Some of these interactions require synchronization among two or more individuals. Multiple-trial designs, which we have used in past work to study interbrain synchronization in the course of joint action, constrain the range of observable interactions. To overcome the limitations of multiple-trial designs, we conducted single-trial analyses of electroencephalography (EEG) signals recorded from eight pairs of guitarists engaged in musical improvisation. We identified hyper-brain networks based on a complex interplay of different frequencies. The intra-brain connections primarily involved higher frequencies (e.g., beta), whereas inter-brain connections primarily operated at lower frequencies (e.g., delta and theta). The topology of hyper-brain networks was frequency-dependent, with a tendency to become more regular at higher frequencies. We also found hyper-brain modules that included nodes (i.e., EEG electrodes) from both brains. Some of the observed network properties were related to musical roles during improvisation. Our findings replicate and extend earlier work and point to mechanisms that enable individuals to engage in temporally coordinated joint action. PMID:24040094

Canonical TGF-β Signaling Negatively Regulates Neuronal Morphogenesis through TGIF/Smad Complex-Mediated CRMP2 Suppression.

PubMed

Nakashima, Hideyuki; Tsujimura, Keita; Irie, Koichiro; Ishizu, Masataka; Pan, Miao; Kameda, Tomonori; Nakashima, Kinichi

2018-05-16

Functional neuronal connectivity requires proper neuronal morphogenesis and its dysregulation causes neurodevelopmental diseases. Transforming growth factor-β (TGF-β) family cytokines play pivotal roles in development, but little is known about their contribution to morphological development of neurons. Here we show that the Smad-dependent canonical signaling of TGF-β family cytokines negatively regulates neuronal morphogenesis during brain development. Mechanistically, activated Smads form a complex with transcriptional repressor TG-interacting factor (TGIF), and downregulate the expression of a neuronal polarity regulator, collapsin response mediator protein 2. We also demonstrate that TGF-β family signaling inhibits neurite elongation of human induced pluripotent stem cell-derived neurons. Furthermore, the expression of TGF-β receptor 1, Smad4, or TGIF, which have mutations found in patients with neurodevelopmental disorders, disrupted neuronal morphogenesis in both mouse (male and female) and human (female) neurons. Together, these findings suggest that the regulation of neuronal morphogenesis by an evolutionarily conserved function of TGF-β signaling is involved in the pathogenesis of neurodevelopmental diseases. SIGNIFICANCE STATEMENT Canonical transforming growth factor-β (TGF-β) signaling plays a crucial role in multiple organ development, including brain, and mutations in components of the signaling pathway associated with several human developmental disorders. In this study, we found that Smads/TG-interacting factor-dependent canonical TGF-β signaling regulates neuronal morphogenesis through the suppression of collapsin response mediator protein-2 (CRMP2) expression during brain development, and that function of this signaling is evolutionarily conserved in the mammalian brain. Mutations in canonical TGF-β signaling factors identified in patients with neurodevelopmental disorders disrupt the morphological development of neurons. Thus, our results suggest that proper control of TGF-β/Smads/CRMP2 signaling pathways is critical for the precise execution of neuronal morphogenesis, whose impairment eventually results in neurodevelopmental disorders. Copyright © 2018 the authors 0270-6474/18/384791-20$15.00/0.

Natural lecithin promotes neural network complexity and activity

PubMed Central

Latifi, Shahrzad; Tamayol, Ali; Habibey, Rouhollah; Sabzevari, Reza; Kahn, Cyril; Geny, David; Eftekharpour, Eftekhar; Annabi, Nasim; Blau, Axel; Linder, Michel; Arab-Tehrany, Elmira

2016-01-01

Phospholipids in the brain cell membranes contain different polyunsaturated fatty acids (PUFAs), which are critical to nervous system function and structure. In particular, brain function critically depends on the uptake of the so-called “essential” fatty acids such as omega-3 (n-3) and omega-6 (n-6) PUFAs that cannot be readily synthesized by the human body. We extracted natural lecithin rich in various PUFAs from a marine source and transformed it into nanoliposomes. These nanoliposomes increased neurite outgrowth, network complexity and neural activity of cortical rat neurons in vitro. We also observed an upregulation of synapsin I (SYN1), which supports the positive role of lecithin in synaptogenesis, synaptic development and maturation. These findings suggest that lecithin nanoliposomes enhance neuronal development, which may have an impact on devising new lecithin delivery strategies for therapeutic applications. PMID:27228907

Natural lecithin promotes neural network complexity and activity.

PubMed

Latifi, Shahrzad; Tamayol, Ali; Habibey, Rouhollah; Sabzevari, Reza; Kahn, Cyril; Geny, David; Eftekharpour, Eftekhar; Annabi, Nasim; Blau, Axel; Linder, Michel; Arab-Tehrany, Elmira

2016-05-27

Phospholipids in the brain cell membranes contain different polyunsaturated fatty acids (PUFAs), which are critical to nervous system function and structure. In particular, brain function critically depends on the uptake of the so-called "essential" fatty acids such as omega-3 (n-3) and omega-6 (n-6) PUFAs that cannot be readily synthesized by the human body. We extracted natural lecithin rich in various PUFAs from a marine source and transformed it into nanoliposomes. These nanoliposomes increased neurite outgrowth, network complexity and neural activity of cortical rat neurons in vitro. We also observed an upregulation of synapsin I (SYN1), which supports the positive role of lecithin in synaptogenesis, synaptic development and maturation. These findings suggest that lecithin nanoliposomes enhance neuronal development, which may have an impact on devising new lecithin delivery strategies for therapeutic applications.

Complex and differential glial responses in Alzheimer's disease and ageing.

PubMed

Rodríguez, José J; Butt, Arthur M; Gardenal, Emanuela; Parpura, Vladimir; Verkhratsky, Alexei

2016-01-01

Glial cells and their association with neurones are fundamental for brain function. The emergence of complex neurone-glial networks assures rapid information transfer, creating a sophisticated circuitry where both types of neural cells work in concert, serving different activities. All glial cells, represented by astrocytes, oligodendrocytes, microglia and NG2-glia, are essential for brain homeostasis and defence. Thus, glia are key not only for normal central nervous system (CNS) function, but also to its dysfunction, being directly associated with all forms of neuropathological processes. Therefore, the progression and outcome of neurological and neurodegenerative diseases depend on glial reactions. In this review, we provide a concise account of recent data obtained from both human material and animal models demonstrating the pathological involvement of glia in neurodegenerative processes, including Alzheimer's disease (AD), as well as physiological ageing.

Protein analysis through Western blot of cells excised individually from human brain and muscle tissue

PubMed Central

Koob, A.O.; Bruns, L.; Prassler, C.; Masliah, E.; Klopstock, T.; Bender, A.

2016-01-01

Comparing protein levels from single cells in tissue has not been achieved through Western blot. Laser capture microdissection allows for the ability to excise single cells from sectioned tissue and compile an aggregate of cells in lysis buffer. In this study we analyzed proteins from cells excised individually from brain and muscle tissue through Western blot. After we excised individual neurons from the substantia nigra of the brain, the accumulated surface area of the individual cells was 120,000, 24,000, 360,000, 480,000, 600,000 μm2. We used an optimized Western blot protocol to probe for tyrosine hydroxylase in this cell pool. We also took 360,000 μm2 of astrocytes (1700 cells) and analyzed the specificity of the method. In muscle we were able to analyze the proteins of the five complexes of the electron transport chain through Western blot from 200 human cells. With this method, we demonstrate the ability to compare cell-specific protein levels in the brain and muscle and describe for the first time how to visualize proteins through Western blot from cells captured individually. PMID:22402104

Protein analysis through Western blot of cells excised individually from human brain and muscle tissue.

PubMed

Koob, A O; Bruns, L; Prassler, C; Masliah, E; Klopstock, T; Bender, A

2012-06-15

Comparing protein levels from single cells in tissue has not been achieved through Western blot. Laser capture microdissection allows for the ability to excise single cells from sectioned tissue and compile an aggregate of cells in lysis buffer. In this study we analyzed proteins from cells excised individually from brain and muscle tissue through Western blot. After we excised individual neurons from the substantia nigra of the brain, the accumulated surface area of the individual cells was 120,000, 24,000, 360,000, 480,000, 600,000 μm2. We used an optimized Western blot protocol to probe for tyrosine hydroxylase in this cell pool. We also took 360,000 μm2 of astrocytes (1700 cells) and analyzed the specificity of the method. In muscle we were able to analyze the proteins of the five complexes of the electron transport chain through Western blot from 200 human cells. With this method, we demonstrate the ability to compare cell-specific protein levels in the brain and muscle and describe for the first time how to visualize proteins through Western blot from cells captured individually. Copyright © 2012 Elsevier Inc. All rights reserved.

DICCCOL: Dense Individualized and Common Connectivity-Based Cortical Landmarks

PubMed Central

Zhu, Dajiang; Guo, Lei; Jiang, Xi; Zhang, Tuo; Zhang, Degang; Chen, Hanbo; Deng, Fan; Faraco, Carlos; Jin, Changfeng; Wee, Chong-Yaw; Yuan, Yixuan; Lv, Peili; Yin, Yan; Hu, Xiaolei; Duan, Lian; Hu, Xintao; Han, Junwei; Wang, Lihong; Shen, Dinggang; Miller, L Stephen

2013-01-01

Is there a common structural and functional cortical architecture that can be quantitatively encoded and precisely reproduced across individuals and populations? This question is still largely unanswered due to the vast complexity, variability, and nonlinearity of the cerebral cortex. Here, we hypothesize that the common cortical architecture can be effectively represented by group-wise consistent structural fiber connections and take a novel data-driven approach to explore the cortical architecture. We report a dense and consistent map of 358 cortical landmarks, named Dense Individualized and Common Connectivity–based Cortical Landmarks (DICCCOLs). Each DICCCOL is defined by group-wise consistent white-matter fiber connection patterns derived from diffusion tensor imaging (DTI) data. Our results have shown that these 358 landmarks are remarkably reproducible over more than one hundred human brains and possess accurate intrinsically established structural and functional cross-subject correspondences validated by large-scale functional magnetic resonance imaging data. In particular, these 358 cortical landmarks can be accurately and efficiently predicted in a new single brain with DTI data. Thus, this set of 358 DICCCOL landmarks comprehensively encodes the common structural and functional cortical architectures, providing opportunities for many applications in brain science including mapping human brain connectomes, as demonstrated in this work. PMID:22490548

LOGISMOS-B for primates: primate cortical surface reconstruction and thickness measurement

NASA Astrophysics Data System (ADS)

Oguz, Ipek; Styner, Martin; Sanchez, Mar; Shi, Yundi; Sonka, Milan

2015-03-01

Cortical thickness and surface area are important morphological measures with implications for many psychiatric and neurological conditions. Automated segmentation and reconstruction of the cortical surface from 3D MRI scans is challenging due to the variable anatomy of the cortex and its highly complex geometry. While many methods exist for this task in the context of the human brain, these methods are typically not readily applicable to the primate brain. We propose an innovative approach based on our recently proposed human cortical reconstruction algorithm, LOGISMOS-B, and the Laplace-based thickness measurement method. Quantitative evaluation of our approach was performed based on a dataset of T1- and T2-weighted MRI scans from 12-month-old macaques where labeling by our anatomical experts was used as independent standard. In this dataset, LOGISMOS-B has an average signed surface error of 0.01 +/- 0.03mm and an unsigned surface error of 0.42 +/- 0.03mm over the whole brain. Excluding the rather problematic temporal pole region further improves unsigned surface distance to 0.34 +/- 0.03mm. This high level of accuracy reached by our algorithm even in this challenging developmental dataset illustrates its robustness and its potential for primate brain studies.

Glutamate and Glutamine: A Review of In Vivo MRS in the Human Brain

PubMed Central

Ramadan, Saadallah; Lin, Alexander; Stanwell, Peter

2013-01-01

Our understanding of the roles that the amino acids glutamate (Glu) and glutamine (Gln) play in the mammalian central nervous system has increased rapidly in recent times. Many conditions are known to exhibit a disturbance in Glu-Gln equilibrium and the exact relationship between these changed conditions and these amino acids are not fully understood. This has led to increased interest in Glu/Gln quantitation in the human brain in an array of conditions (e.g. mental illness, tumor, neuro-degeneration) as well as in normal brain function. Accordingly, this review has been undertaken to describe the increasing number of in vivo techniques available to study Glu and Gln separately, or pooled as ‘Glx’. The present range of magnetic resonance spectroscopy (MRS) methods used to assess Glu and Gln, vary in approach, complexity and outcome, thus the focus of this review is on a description of MRS acquisition approaches, and an indication of relative utility of each technique rather than brain pathologies associated to Glu and/or Gln perturbation. Consequently, this review focuses particularly on (1) one-dimensional (1D) 1H MRS, (2) two-dimensional (2D) 1H MRS, and (3) 1D 13C MRS techniques. PMID:24123328

Replicating Human Hand Synergies Onto Robotic Hands: A Review on Software and Hardware Strategies.

PubMed

Salvietti, Gionata

2018-01-01

This review reports the principal solutions proposed in the literature to reduce the complexity of the control and of the design of robotic hands taking inspiration from the organization of the human brain. Several studies in neuroscience concerning the sensorimotor organization of the human hand proved that, despite the complexity of the hand, a few parameters can describe most of the variance in the patterns of configurations and movements. In other words, humans exploit a reduced set of parameters, known in the literature as synergies, to control their hands. In robotics, this dimensionality reduction can be achieved by coupling some of the degrees of freedom (DoFs) of the robotic hand, that results in a reduction of the needed inputs. Such coupling can be obtained at the software level, exploiting mapping algorithm to reproduce human hand organization, and at the hardware level, through either rigid or compliant physical couplings between the joints of the robotic hand. This paper reviews the main solutions proposed for both the approaches.

Interpretation of the Precision Matrix and Its Application in Estimating Sparse Brain Connectivity during Sleep Spindles from Human Electrocorticography Recordings

PubMed Central

Das, Anup; Sampson, Aaron L.; Lainscsek, Claudia; Muller, Lyle; Lin, Wutu; Doyle, John C.; Cash, Sydney S.; Halgren, Eric; Sejnowski, Terrence J.

2017-01-01

The correlation method from brain imaging has been used to estimate functional connectivity in the human brain. However, brain regions might show very high correlation even when the two regions are not directly connected due to the strong interaction of the two regions with common input from a third region. One previously proposed solution to this problem is to use a sparse regularized inverse covariance matrix or precision matrix (SRPM) assuming that the connectivity structure is sparse. This method yields partial correlations to measure strong direct interactions between pairs of regions while simultaneously removing the influence of the rest of the regions, thus identifying regions that are conditionally independent. To test our methods, we first demonstrated conditions under which the SRPM method could indeed find the true physical connection between a pair of nodes for a spring-mass example and an RC circuit example. The recovery of the connectivity structure using the SRPM method can be explained by energy models using the Boltzmann distribution. We then demonstrated the application of the SRPM method for estimating brain connectivity during stage 2 sleep spindles from human electrocorticography (ECoG) recordings using an 8 × 8 electrode array. The ECoG recordings that we analyzed were from a 32-year-old male patient with long-standing pharmaco-resistant left temporal lobe complex partial epilepsy. Sleep spindles were automatically detected using delay differential analysis and then analyzed with SRPM and the Louvain method for community detection. We found spatially localized brain networks within and between neighboring cortical areas during spindles, in contrast to the case when sleep spindles were not present. PMID:28095202

The cognitive neuroscience of ageing.

PubMed

Grady, Cheryl

2012-06-20

The availability of neuroimaging technology has spurred a marked increase in the human cognitive neuroscience literature, including the study of cognitive ageing. Although there is a growing consensus that the ageing brain retains considerable plasticity of function, currently measured primarily by means of functional MRI, it is less clear how age differences in brain activity relate to cognitive performance. The field is also hampered by the complexity of the ageing process itself and the large number of factors that are influenced by age. In this Review, current trends and unresolved issues in the cognitive neuroscience of ageing are discussed.

Moral judgments, emotions and the utilitarian brain.

PubMed

Moll, Jorge; de Oliveira-Souza, Ricardo

2007-08-01

The investigation of the neural and cognitive mechanisms underlying the moral mind is of paramount importance for understanding complex human behaviors, from altruism to antisocial acts. A new study on patients with prefrontal damage provides key insights on the neurobiology of moral judgment and raises new questions on the mechanisms by which reason and emotion contribute to moral cognition.

Selective Effects of Motor Expertise in Mental Body Rotation Tasks: Comparing Object-Based and Perspective Transformations

ERIC Educational Resources Information Center

Steggemann, Yvonne; Engbert, Kai; Weigelt, Matthias

2011-01-01

Brain imaging studies provide strong evidence for the involvement of the human mirror system during the observation of complex movements, depending on the individual's motor expertise. Here, we ask the question whether motor expertise not only affects perception while observing movements, but also benefits perception while solving mental rotation…

The Library and Human Memory Simulation Studies. Reports on File Organization Studies.

ERIC Educational Resources Information Center

Reilly, Kevin D.

This report describes digital computer simulation efforts in a study of memory systems for two important cases: that of the individual the brain; and that of society, the library. A neural system model is presented in which a complex system is produced by connecting simple hypothetical neurons whose states change under application of a…

The Role of Brain Inflammation in Epileptogenesis in TSC

DTIC Science & Technology

2013-07-01

and adaptive immunity during epileptogenesis and spontaneous seizures: evidence from experimental models and human temporal lobe epilepsy . Neurobiol...tissue obtained from epilepsy patients, such as with mesial temporal sclerosis. Different types of inflammatory mediators and pathways have been...13. SUPPLEMENTARY NOTES 14. ABSTRACT Epilepsy is a common, disabling problem in patients with tuberous sclerosis complex (TSC) and

Aberrant expression of long noncoding RNAs in autistic brain.

PubMed

Ziats, Mark N; Rennert, Owen M

2013-03-01

The autism spectrum disorders (ASD) have a significant hereditary component, but the implicated genetic loci are heterogeneous and complex. Consequently, there is a gap in understanding how diverse genomic aberrations all result in one clinical ASD phenotype. Gene expression studies from autism brain tissue have demonstrated that aberrantly expressed protein-coding genes may converge onto common molecular pathways, potentially reconciling the strong heritability and shared clinical phenotypes with the genomic heterogeneity of the disorder. However, the regulation of gene expression is extremely complex and governed by many mechanisms, including noncoding RNAs. Yet no study in ASD brain tissue has assessed for changes in regulatory long noncoding RNAs (lncRNAs), which represent a large proportion of the human transcriptome, and actively modulate mRNA expression. To assess if aberrant expression of lncRNAs may play a role in the molecular pathogenesis of ASD, we profiled over 33,000 annotated lncRNAs and 30,000 mRNA transcripts from postmortem brain tissue of autistic and control prefrontal cortex and cerebellum by microarray. We detected over 200 differentially expressed lncRNAs in ASD, which were enriched for genomic regions containing genes related to neurodevelopment and psychiatric disease. Additionally, comparison of differences in expression of mRNAs between prefrontal cortex and cerebellum within individual donors showed ASD brains had more transcriptional homogeneity. Moreover, this was also true of the lncRNA transcriptome. Our results suggest that further investigation of lncRNA expression in autistic brain may further elucidate the molecular pathogenesis of this disorder.

Interleukin 2 Activates Brain Microvascular Endothelial Cells Resulting in Destabilization of Adherens Junctions.

PubMed

Wylezinski, Lukasz S; Hawiger, Jacek

2016-10-28

The pleiotropic cytokine interleukin 2 (IL2) disrupts the blood-brain barrier and alters brain microcirculation, underlying vascular leak syndrome that complicates cancer immunotherapy with IL2. The microvascular effects of IL2 also play a role in the development of multiple sclerosis and other chronic neurological disorders. The mechanism of IL2-induced disruption of brain microcirculation has not been determined previously. We found that both human and murine brain microvascular endothelial cells express constituents of the IL2 receptor complex. Then we established that signaling through this receptor complex leads to activation of the transcription factor, nuclear factor κB, resulting in expression of proinflammatory interleukin 6 and monocyte chemoattractant protein 1. We also discovered that IL2 induces disruption of adherens junctions, concomitant with cytoskeletal reorganization, ultimately leading to increased endothelial cell permeability. IL2-induced phosphorylation of vascular endothelial cadherin (VE-cadherin), a constituent of adherens junctions, leads to dissociation of its stabilizing adaptor partners, p120-catenin and β-catenin. Increased phosphorylation of VE-cadherin was also accompanied by a reduction of Src homology 2 domain-containing protein-tyrosine phosphatase 2, known to maintain vascular barrier function. These results unravel the mechanism of deleterious effects induced by IL2 on brain microvascular endothelial cells and may inform the development of new measures to improve IL2 cancer immunotherapy, as well as treatments for autoimmune diseases affecting the central nervous system. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Anatomical and functional assemblies of brain BOLD oscillations

PubMed Central

Baria, Alexis T.; Baliki, Marwan N.; Parrish, Todd; Apkarian, A. Vania

2011-01-01

Brain oscillatory activity has long been thought to have spatial properties, the details of which are unresolved. Here we examine spatial organizational rules for the human brain oscillatory activity as measured by blood oxygen level-dependent (BOLD). Resting state BOLD signal was transformed into frequency space (Welch’s method), averaged across subjects, and its spatial distribution studied as a function of four frequency bands, spanning the full bandwidth of BOLD. The brain showed anatomically constrained distribution of power for each frequency band. This result was replicated on a repository dataset of 195 subjects. Next, we examined larger-scale organization by parceling the neocortex into regions approximating Brodmann Areas (BAs). This indicated that BAs of simple function/connectivity (unimodal), vs. complex properties (transmodal), are dominated by low frequency BOLD oscillations, and within the visual ventral stream we observe a graded shift of power to higher frequency bands for BAs further removed from the primary visual cortex (increased complexity), linking frequency properties of BOLD to hodology. Additionally, BOLD oscillation properties for the default mode network demonstrated that it is composed of distinct frequency dependent regions. When the same analysis was performed on a visual-motor task, frequency-dependent global and voxel-wise shifts in BOLD oscillations could be detected at brain sites mostly outside those identified with general linear modeling. Thus, analysis of BOLD oscillations in full bandwidth uncovers novel brain organizational rules, linking anatomical structures and functional networks to characteristic BOLD oscillations. The approach also identifies changes in brain intrinsic properties in relation to responses to external inputs. PMID:21613505

Python Executable Script for Estimating Two Effective Parameters to Individualize Brain-Computer Interfaces: Individual Alpha Frequency and Neurophysiological Predictor.

PubMed

Alonso-Valerdi, Luz María

2016-01-01

A brain-computer interface (BCI) aims to establish communication between the human brain and a computing system so as to enable the interaction between an individual and his environment without using the brain output pathways. Individuals control a BCI system by modulating their brain signals through mental tasks (e.g., motor imagery or mental calculation) or sensory stimulation (e.g., auditory, visual, or tactile). As users modulate their brain signals at different frequencies and at different levels, the appropriate characterization of those signals is necessary. The modulation of brain signals through mental tasks is furthermore a skill that requires training. Unfortunately, not all the users acquire such skill. A practical solution to this problem is to assess the user probability of controlling a BCI system. Another possible solution is to set the bandwidth of the brain oscillations, which is highly sensitive to the users' age, sex and anatomy. With this in mind, NeuroIndex, a Python executable script, estimates a neurophysiological prediction index and the individual alpha frequency (IAF) of the user in question. These two parameters are useful to characterize the user EEG signals, and decide how to go through the complex process of adapting the human brain and the computing system on the basis of previously proposed methods. NeuroIndeX is not only the implementation of those methods, but it also complements the methods each other and provides an alternative way to obtain the prediction parameter. However, an important limitation of this application is its dependency on the IAF value, and some results should be interpreted with caution. The script along with some electroencephalographic datasets are available on a GitHub repository in order to corroborate the functionality and usability of this application.

Python Executable Script for Estimating Two Effective Parameters to Individualize Brain-Computer Interfaces: Individual Alpha Frequency and Neurophysiological Predictor

PubMed Central

Alonso-Valerdi, Luz María

2016-01-01

A brain-computer interface (BCI) aims to establish communication between the human brain and a computing system so as to enable the interaction between an individual and his environment without using the brain output pathways. Individuals control a BCI system by modulating their brain signals through mental tasks (e.g., motor imagery or mental calculation) or sensory stimulation (e.g., auditory, visual, or tactile). As users modulate their brain signals at different frequencies and at different levels, the appropriate characterization of those signals is necessary. The modulation of brain signals through mental tasks is furthermore a skill that requires training. Unfortunately, not all the users acquire such skill. A practical solution to this problem is to assess the user probability of controlling a BCI system. Another possible solution is to set the bandwidth of the brain oscillations, which is highly sensitive to the users' age, sex and anatomy. With this in mind, NeuroIndex, a Python executable script, estimates a neurophysiological prediction index and the individual alpha frequency (IAF) of the user in question. These two parameters are useful to characterize the user EEG signals, and decide how to go through the complex process of adapting the human brain and the computing system on the basis of previously proposed methods. NeuroIndeX is not only the implementation of those methods, but it also complements the methods each other and provides an alternative way to obtain the prediction parameter. However, an important limitation of this application is its dependency on the IAF value, and some results should be interpreted with caution. The script along with some electroencephalographic datasets are available on a GitHub repository in order to corroborate the functionality and usability of this application. PMID:27445783

MicroRNA-153 Physiologically Inhibits Expression of Amyloid-β Precursor Protein in Cultured Human Fetal Brain Cells and Is Dysregulated in a Subset of Alzheimer Disease Patients*

PubMed Central

Long, Justin M.; Ray, Balmiki; Lahiri, Debomoy K.

2012-01-01

Regulation of amyloid-β (Aβ) precursor protein (APP) expression is complex. MicroRNAs (miRNAs) are expected to participate in the molecular network that controls this process. The composition of this network is, however, still undefined. Elucidating the complement of miRNAs that regulate APP expression should reveal novel drug targets capable of modulating Aβ production in AD. Here, we investigated the contribution of miR-153 to this regulatory network. A miR-153 target site within the APP 3′-untranslated region (3′-UTR) was predicted by several bioinformatic algorithms. We found that miR-153 significantly reduced reporter expression when co-transfected with an APP 3′-UTR reporter construct. Mutation of the predicted miR-153 target site eliminated this reporter response. miR-153 delivery in both HeLa cells and primary human fetal brain cultures significantly reduced APP expression. Delivery of a miR-153 antisense inhibitor to human fetal brain cultures significantly elevated APP expression. miR-153 delivery also reduced expression of the APP paralog APLP2. High functional redundancy between APP and APLP2 suggests that miR-153 may target biological pathways in which they both function. Interestingly, in a subset of human AD brain specimens with moderate AD pathology, miR-153 levels were reduced. This same subset also exhibited elevated APP levels relative to control specimens. Therefore, endogenous miR-153 inhibits expression of APP in human neurons by specifically interacting with the APP 3′-UTR. This regulatory interaction may have relevance to AD etiology, where low miR-153 levels may drive increased APP expression in a subset of AD patients. PMID:22733824

Human homologues of the bacterial heat-shock protein DnaJ are preferentially expressed in neurons.

PubMed Central

Cheetham, M E; Brion, J P; Anderton, B H

1992-01-01

The bacterial heat-shock protein DnaJ has been implicated in protein folding and protein complex dissociation. The DnaJ protein interacts with the prokaryotic analogue of Hsp70, DnaK, and accelerates the rate of ATP hydrolysis by DnaK. Several yeast homologues of DnaJ, with different proposed subcellular localizations and functions, have recently been isolated and are the only eukaryotic forms of DnaJ so far described. We have isolated cDNAs corresponding to two alternatively spliced transcripts of a novel human gene, HSJ1, which show sequence similarity to the bacterial DnaJ protein and the yeast homologues. The cDNA clones were isolated from a human brain-frontal-cortex expression library screened with a polyclonal antiserum raised to paired-helical-filament (PHF) proteins isolated from extracts of the brains of patients suffering from Alzheimer's disease. The similarity between the predicted human protein sequences and the bacterial and yeast proteins is highest at the N-termini, this region also shows a limited similarity to viral T-antigens and is a possible common motif involved in the interaction with DnaK/Hsp70. Northern-blot analysis has shown that human brain contains higher levels of mRNA for the DnaJ homologue than other tissues examined, and hybridization studies with riboprobes in situ show a restricted pattern of expression of the mRNA within the brain, with neuronal layers giving the strongest signal. These findings suggest that the DnaJ-DnaK (Hsp70) interaction is general to eukaryotes and, indeed, to higher organisms. Images Fig. 2. Fig. 3. Fig. 4. Fig. 5. PMID:1599432

The tissue-type plasminogen activator–plasminogen activator inhibitor 1 complex promotes neurovascular injury in brain trauma: evidence from mice and humans

PubMed Central

Sashindranath, Maithili; Sales, Eunice; Daglas, Maria; Freeman, Roxann; Samson, Andre L.; Cops, Elisa J.; Beckham, Simone; Galle, Adam; McLean, Catriona; Morganti-Kossmann, Cristina; Rosenfeld, Jeffrey V.; Madani, Rime; Vassalli, Jean-Dominique; Su, Enming J.; Lawrence, Daniel A.

2012-01-01

The neurovascular unit provides a dynamic interface between the circulation and central nervous system. Disruption of neurovascular integrity occurs in numerous brain pathologies including neurotrauma and ischaemic stroke. Tissue plasminogen activator is a serine protease that converts plasminogen to plasmin, a protease that dissolves blood clots. Besides its role in fibrinolysis, tissue plasminogen activator is abundantly expressed in the brain where it mediates extracellular proteolysis. However, proteolytically active tissue plasminogen activator also promotes neurovascular disruption after ischaemic stroke; the molecular mechanisms of this process are still unclear. Tissue plasminogen activator is naturally inhibited by serine protease inhibitors (serpins): plasminogen activator inhibitor-1, neuroserpin or protease nexin-1 that results in the formation of serpin:protease complexes. Proteases and serpin:protease complexes are cleared through high-affinity binding to low-density lipoprotein receptors, but their binding to these receptors can also transmit extracellular signals across the plasma membrane. The matrix metalloproteinases are the second major proteolytic system in the mammalian brain, and like tissue plasminogen activators are pivotal to neurological function but can also degrade structures of the neurovascular unit after injury. Herein, we show that tissue plasminogen activator potentiates neurovascular damage in a dose-dependent manner in a mouse model of neurotrauma. Surprisingly, inhibition of activity following administration of plasminogen activator inhibitor-1 significantly increased cerebrovascular permeability. This led to our finding that formation of complexes between tissue plasminogen activator and plasminogen activator inhibitor-1 in the brain parenchyma facilitates post-traumatic cerebrovascular damage. We demonstrate that following trauma, the complex binds to low-density lipoprotein receptors, triggering the induction of matrix metalloproteinase-3. Accordingly, pharmacological inhibition of matrix metalloproteinase-3 attenuates neurovascular permeability and improves neurological function in injured mice. Our results are clinically relevant, because concentrations of tissue plasminogen activator: plasminogen activator inhibitor-1 complex and matrix metalloproteinase-3 are significantly elevated in cerebrospinal fluid of trauma patients and correlate with neurological outcome. In a separate study, we found that matrix metalloproteinase-3 and albumin, a marker of cerebrovascular damage, were significantly increased in brain tissue of patients with neurotrauma. Perturbation of neurovascular homeostasis causing oedema, inflammation and cell death is an important cause of acute and long-term neurological dysfunction after trauma. A role for the tissue plasminogen activator–matrix metalloproteinase axis in promoting neurovascular disruption after neurotrauma has not been described thus far. Targeting tissue plasminogen activator: plasminogen activator inhibitor-1 complex signalling or downstream matrix metalloproteinase-3 induction may provide viable therapeutic strategies to reduce cerebrovascular permeability after neurotrauma. PMID:22822039

The Anatomical Distance of Functional Connections Predicts Brain Network Topology in Health and Schizophrenia

PubMed Central

Vértes, Petra E.; Stidd, Reva; Lalonde, François; Clasen, Liv; Rapoport, Judith; Giedd, Jay; Bullmore, Edward T.; Gogtay, Nitin

2013-01-01

The human brain is a topologically complex network embedded in anatomical space. Here, we systematically explored relationships between functional connectivity, complex network topology, and anatomical (Euclidean) distance between connected brain regions, in the resting-state functional magnetic resonance imaging brain networks of 20 healthy volunteers and 19 patients with childhood-onset schizophrenia (COS). Normal between-subject differences in average distance of connected edges in brain graphs were strongly associated with variation in topological properties of functional networks. In addition, a club or subset of connector hubs was identified, in lateral temporal, parietal, dorsal prefrontal, and medial prefrontal/cingulate cortical regions. In COS, there was reduced strength of functional connectivity over short distances especially, and therefore, global mean connection distance of thresholded graphs was significantly greater than normal. As predicted from relationships between spatial and topological properties of normal networks, this disorder-related proportional increase in connection distance was associated with reduced clustering and modularity and increased global efficiency of COS networks. Between-group differences in connection distance were localized specifically to connector hubs of multimodal association cortex. In relation to the neurodevelopmental pathogenesis of schizophrenia, we argue that the data are consistent with the interpretation that spatial and topological disturbances of functional network organization could arise from excessive “pruning” of short-distance functional connections in schizophrenia. PMID:22275481

The neurobiology of social environmental risk for schizophrenia: an evolving research field.

PubMed

Akdeniz, Ceren; Tost, Heike; Meyer-Lindenberg, Andreas

2014-04-01

Schizophrenia is a severe and complex brain disorder that usually manifests in early adulthood and disturbs a wide range of human functions. More than 100 years after its initial description, the pathophysiology of the disorder is still incompletely understood. Many epidemiological studies strongly suggest a complex interaction between genetic and environmental risk factors for the development of the disorder. While there is considerable evidence for a social environmental component of this risk, the links between adverse social factors and altered brain function have just come into focus. In the present review, we first summarize epidemiological evidence for the significance of social environmental risk factors, outline the role of altered social stress processing in mental illness, and review the latest experimental evidence for the neural correlates of social environmental risk for schizophrenia. The studies we have discussed in this review provide a selection of the current work in the field. We suggest that many of the social environmental risk factors may impact on perceived social stress and engage neural circuits in the brain whose functional and structural architecture undergoes detrimental change in response to prolonged exposure. We conclude that multidisciplinary approaches involving various fields and thoroughly constructed longitudinal designs are necessary to capture complex structure of social environmental risks.

Downregulation of the expression of mitochondrial electron transport complex genes in autism brains.

PubMed

Anitha, Ayyappan; Nakamura, Kazuhiko; Thanseem, Ismail; Matsuzaki, Hideo; Miyachi, Taishi; Tsujii, Masatsugu; Iwata, Yasuhide; Suzuki, Katsuaki; Sugiyama, Toshiro; Mori, Norio

2013-05-01

Mitochondrial dysfunction (MtD) and abnormal brain bioenergetics have been implicated in autism, suggesting possible candidate genes in the electron transport chain (ETC). We compared the expression of 84 ETC genes in the post-mortem brains of autism patients and controls. Brain tissues from the anterior cingulate gyrus, motor cortex, and thalamus of autism patients (n = 8) and controls (n = 10) were obtained from Autism Tissue Program, USA. Quantitative real-time PCR arrays were used to quantify gene expression. We observed reduced expression of several ETC genes in autism brains compared to controls. Eleven genes of Complex I, five genes each of Complex III and Complex IV, and seven genes of Complex V showed brain region-specific reduced expression in autism. ATP5A1 (Complex V), ATP5G3 (Complex V) and NDUFA5 (Complex I) showed consistently reduced expression in all the brain regions of autism patients. Upon silencing ATP5A1, the expression of mitogen-activated protein kinase 13 (MAPK13), a p38 MAPK responsive to stress stimuli, was upregulated in HEK 293 cells. This could have been induced by oxidative stress due to impaired ATP synthesis. We report new candidate genes involved in abnormal brain bioenergetics in autism, supporting the hypothesis that mitochondria, critical for neurodevelopment, may play a role in autism. © 2012 The Authors; Brain Pathology © 2012 International Society of Neuropathology.

Brain rhythms and neural syntax: implications for efficient coding of cognitive content and neuropsychiatric disease.

PubMed Central

Buzsáki, György; Watson, Brendon O.

2012-01-01

The perpetual activity of the cerebral cortex is largely supported by the variety of oscillations the brain generates, spanning a number of frequencies and anatomical locations, as well as behavioral correlates. First, we review findings from animal studies showing that most forms of brain rhythms are inhibition-based, producing rhythmic volleys of inhibitory inputs to principal cell populations, thereby providing alternating temporal windows of relatively reduced and enhanced excitability in neuronal networks. These inhibition-based mechanisms offer natural temporal frames to group or “chunk” neuronal activity into cell assemblies and sequences of assemblies, with more complex multi-oscillation interactions creating syntactical rules for the effective exchange of information among cortical networks. We then review recent studies in human psychiatric patients demonstrating a variety alterations in neural oscillations across all major psychiatric diseases, and suggest possible future research directions and treatment approaches based on the fundamental properties of brain rhythms. PMID:23393413

Nicotine Blocks Brain Estrogen Synthase (Aromatase): In Vivo Positron Emission Tomography Studies in Female Baboons

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

Biegon, A.; Biegon, A.; Kim, S.-W.

Cigarette smoking and nicotine have complex effects on human physiology and behavior, including some effects similar to those elicited by inhibition of aromatase, the last enzyme in estrogen biosynthesis. We report the first in vivo primate study to determine whether there is a direct effect of nicotine administration on brain aromatase. Brain aromatase availability was examined with positron emission tomography and the selective aromatase inhibitor [{sup 11}C]vorozole in six baboons before and after exposure to IV nicotine at .015 and .03 mg/kg. Nicotine administration produced significant, dose-dependent reductions in [{sup 11}C]vorozole binding. The amygdala and preoptic area showed the largestmore » reductions. Plasma levels of nicotine and its major metabolite cotinine were similar to those found in cigarette smokers. Nicotine interacts in vivo with primate brain aromatase in regions involved in mood, aggression, and sexual behavior.« less