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.

The Major Histocompatibility Complex and Autism Spectrum Disorder

PubMed Central

Needleman, Leigh A.; McAllister, A. Kimberley

2015-01-01

Autism spectrum disorder (ASD) is a complex disorder that appears to be caused by interactions between genetic changes and environmental insults during early development. A wide range of factors have been linked to the onset of ASD, but recently both genetic associations and environmental factors point to a central role for immune- related genes and immune responses to environmental stimuli. Specifically, many of the proteins encoded by the major histocompatibility complex (MHC) play a vital role in the formation, refinement, maintenance, and plasticity of the brain. Manipulations of levels of MHC molecules have illustrated how disrupted MHC signaling can significantly alter brain connectivity and function. Thus, an emerging hypothesis in our field is that disruptions in MHC expression in the developing brain caused by mutations and/or immune dysregulation may contribute to the altered brain connectivity and function characteristic of ASD. This review provides an overview of the structure and function of the three classes of MHC molecules in the immune system, healthy brain, and their possible involvement in ASD. PMID:22760919

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.

Atypical Brain Activation during Simple & Complex Levels of Processing in Adult ADHD: An fMRI Study

ERIC Educational Resources Information Center

Hale, T. Sigi; Bookheimer, Susan; McGough, James J.; Phillips, Joseph M.; McCracken, James T.

2007-01-01

Objective: Executive dysfunction in ADHD is well supported. However, recent studies suggest that more fundamental impairments may be contributing. We assessed brain function in adults with ADHD during simple and complex forms of processing. Method: We used functional magnetic resonance imaging with forward and backward digit spans to investigate…

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

Optical Imaging and Control of Neurons

NASA Astrophysics Data System (ADS)

Song, Yoon-Kyu

Although remarkable progress has been made in our understanding of the function, organization, and development of the brain by various approaches of modern science and technology, how the brain performs its marvelous function remains unsolved or incompletely understood. This is mainly attributed to the insufficient capability of currently available research tools and conceptual frameworks to deal with enormous complexity of the brain. Hence, in the last couple of decades, a significant effort has been made to crack the complexity of brain by utilizing research tools from diverse scientific areas. The research tools include the optical neurotechnology which incorporates the exquisite characteristics of optics, such as multi-parallel access and non-invasiveness, in sensing and stimulating the excitable membrane of a neuron, the basic functional unit of the brain. This chapter is aimed to serve as a short introduction to the optical neurotechnology for those who wish to use optical techniques as one of their brain research tools.

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).

Decreased Complexity in Alzheimer's Disease: Resting-State fMRI Evidence of Brain Entropy Mapping.

PubMed

Wang, Bin; Niu, Yan; Miao, Liwen; Cao, Rui; Yan, Pengfei; Guo, Hao; Li, Dandan; Guo, Yuxiang; Yan, Tianyi; Wu, Jinglong; Xiang, Jie; Zhang, Hui

2017-01-01

Alzheimer's disease (AD) is a frequently observed, irreversible brain function disorder among elderly individuals. Resting-state functional magnetic resonance imaging (rs-fMRI) has been introduced as an alternative approach to assessing brain functional abnormalities in AD patients. However, alterations in the brain rs-fMRI signal complexities in mild cognitive impairment (MCI) and AD patients remain unclear. Here, we described the novel application of permutation entropy (PE) to investigate the abnormal complexity of rs-fMRI signals in MCI and AD patients. The rs-fMRI signals of 30 normal controls (NCs), 33 early MCI (EMCI), 32 late MCI (LMCI), and 29 AD patients were obtained from the Alzheimer's disease Neuroimaging Initiative (ADNI) database. After preprocessing, whole-brain entropy maps of the four groups were extracted and subjected to Gaussian smoothing. We performed a one-way analysis of variance (ANOVA) on the brain entropy maps of the four groups. The results after adjusting for age and sex differences together revealed that the patients with AD exhibited lower complexity than did the MCI and NC controls. We found five clusters that exhibited significant differences and were distributed primarily in the occipital, frontal, and temporal lobes. The average PE of the five clusters exhibited a decreasing trend from MCI to AD. The AD group exhibited the least complexity. Additionally, the average PE of the five clusters was significantly positively correlated with the Mini-Mental State Examination (MMSE) scores and significantly negatively correlated with Functional Assessment Questionnaire (FAQ) scores and global Clinical Dementia Rating (CDR) scores in the patient groups. Significant correlations were also found between the PE and regional homogeneity (ReHo) in the patient groups. These results indicated that declines in PE might be related to changes in regional functional homogeneity in AD. These findings suggested that complexity analyses using PE in rs-fMRI signals can provide important information about the fMRI characteristics of cognitive impairments in MCI and AD.

Decreased Complexity in Alzheimer's Disease: Resting-State fMRI Evidence of Brain Entropy Mapping

PubMed Central

Wang, Bin; Niu, Yan; Miao, Liwen; Cao, Rui; Yan, Pengfei; Guo, Hao; Li, Dandan; Guo, Yuxiang; Yan, Tianyi; Wu, Jinglong; Xiang, Jie; Zhang, Hui

2017-01-01

Alzheimer's disease (AD) is a frequently observed, irreversible brain function disorder among elderly individuals. Resting-state functional magnetic resonance imaging (rs-fMRI) has been introduced as an alternative approach to assessing brain functional abnormalities in AD patients. However, alterations in the brain rs-fMRI signal complexities in mild cognitive impairment (MCI) and AD patients remain unclear. Here, we described the novel application of permutation entropy (PE) to investigate the abnormal complexity of rs-fMRI signals in MCI and AD patients. The rs-fMRI signals of 30 normal controls (NCs), 33 early MCI (EMCI), 32 late MCI (LMCI), and 29 AD patients were obtained from the Alzheimer's disease Neuroimaging Initiative (ADNI) database. After preprocessing, whole-brain entropy maps of the four groups were extracted and subjected to Gaussian smoothing. We performed a one-way analysis of variance (ANOVA) on the brain entropy maps of the four groups. The results after adjusting for age and sex differences together revealed that the patients with AD exhibited lower complexity than did the MCI and NC controls. We found five clusters that exhibited significant differences and were distributed primarily in the occipital, frontal, and temporal lobes. The average PE of the five clusters exhibited a decreasing trend from MCI to AD. The AD group exhibited the least complexity. Additionally, the average PE of the five clusters was significantly positively correlated with the Mini-Mental State Examination (MMSE) scores and significantly negatively correlated with Functional Assessment Questionnaire (FAQ) scores and global Clinical Dementia Rating (CDR) scores in the patient groups. Significant correlations were also found between the PE and regional homogeneity (ReHo) in the patient groups. These results indicated that declines in PE might be related to changes in regional functional homogeneity in AD. These findings suggested that complexity analyses using PE in rs-fMRI signals can provide important information about the fMRI characteristics of cognitive impairments in MCI and AD. PMID:29209199

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

Build-a-Brain Project: Students Design and Model the Brain of an Imaginary Animal

ERIC Educational Resources Information Center

Demetrikopoulos, Melissa K.; Pecore, John; Rose, Jordan D.; Fobbs, Archibald J., Jr.; Johnson, John I.; Carruth, Laura L.

2006-01-01

The brain is a truly fascinating structure! It controls the body and allows everyone to think, learn, speak, move, feel, remember, and experience emotions. Although the brain is a single organ, it is very complex and has several regions, each having a specific function. These functionally diverse regions work together to allow for coordination of…

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.

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

PubMed Central

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

2015-01-01

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

Functional Magnetic Resonance Imaging

ERIC Educational Resources Information Center

Voos, Avery; Pelphrey, Kevin

2013-01-01

Functional magnetic resonance imaging (fMRI), with its excellent spatial resolution and ability to visualize networks of neuroanatomical structures involved in complex information processing, has become the dominant technique for the study of brain function and its development. The accessibility of in-vivo pediatric brain-imaging techniques…

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

ERIC Educational Resources Information Center

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

2009-01-01

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

Mind Operational Semantics and Brain Operational Architectonics: A Putative Correspondence

PubMed Central

Benedetti, Giulio; Marchetti, Giorgio; Fingelkurts, Alexander A; Fingelkurts, Andrew A

2010-01-01

Despite allowing for the unprecedented visualization of brain functional activity, modern neurobiological techniques have not yet been able to provide satisfactory answers to important questions about the relationship between brain and mind. The aim of this paper is to show how two different but complementary approaches, Mind Operational Semantics (OS) and Brain Operational Architectonics (OA), can help bridge the gap between a specific kind of mental activity—the higher-order reflective thought or linguistic thought—and brain. The fundamental notion that allows the two different approaches to be jointly used under a common framework is that of operation. According to OS, which is based on introspection and linguistic data, the meanings of words can be analyzed in terms of elemental mental operations (EOMC), amongst which those of attention play a key role. Linguistic thought is made possible by special kinds of elements, which OS calls “correlators”, which have the function of tying together the other elements of thought, which OS calls “correlata” (a "correlational network” that is, a sentence, is so formed). Therefore, OS conceives of linguistic thought as a hierarchy of operations of increasing complexity. Likewise, according to OA, which is based on the joint analysis of cognitive and electromagnetic data (EEG and MEG), every conscious phenomenon is brought to existence by the joint operations of many functional and transient neuronal assemblies in the brain. According to OA, the functioning of the brain is always operational (made up of operations), and its structure is characterized by a hierarchy of operations of increasing complexity: single neurons, single assemblies of neurons, synchronized neuronal assemblies or Operational Modules (OM), integrated or complex OMs. The authors put forward the hypothesis that the whole level of OS’s description (EOMC, correlators, and correlational networks) corresponds to the level of OMs (or set of them) of different complexity within OA’s theory: EOMC could correspond to simple OMs, correlators to complex OMs and the correlational network to a set of simple and complex OMs. Finally, a set of experiments is proposed to verify the putative correspondence between OS and OA and prove the existence of an integrated continuum between brain and mind. PMID:21113277

Evidence-based guideline update: determining brain death in adults: report of the Quality Standards Subcommittee of the American Academy of Neurology.

PubMed

Wijdicks, Eelco F M; Varelas, Panayiotis N; Gronseth, Gary S; Greer, David M

2010-06-08

To provide an update of the 1995 American Academy of Neurology guideline with regard to the following questions: Are there patients who fulfill the clinical criteria of brain death who recover neurologic function? What is an adequate observation period to ensure that cessation of neurologic function is permanent? Are complex motor movements that falsely suggest retained brain function sometimes observed in brain death? What is the comparative safety of techniques for determining apnea? Are there new ancillary tests that accurately identify patients with brain death? A systematic literature search was conducted and included a review of MEDLINE and EMBASE from January 1996 to May 2009. Studies were limited to adults. In adults, there are no published reports of recovery of neurologic function after a diagnosis of brain death using the criteria reviewed in the 1995 American Academy of Neurology practice parameter. Complex-spontaneous motor movements and false-positive triggering of the ventilator may occur in patients who are brain dead. There is insufficient evidence to determine the minimally acceptable observation period to ensure that neurologic functions have ceased irreversibly. Apneic oxygenation diffusion to determine apnea is safe, but there is insufficient evidence to determine the comparative safety of techniques used for apnea testing. There is insufficient evidence to determine if newer ancillary tests accurately confirm the cessation of function of the entire brain.

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 permutation testing framework to compare groups of brain networks.

PubMed

Simpson, Sean L; Lyday, Robert G; Hayasaka, Satoru; Marsh, Anthony P; Laurienti, Paul J

2013-01-01

Brain network analyses have moved to the forefront of neuroimaging research over the last decade. However, methods for statistically comparing groups of networks have lagged behind. These comparisons have great appeal for researchers interested in gaining further insight into complex brain function and how it changes across different mental states and disease conditions. Current comparison approaches generally either rely on a summary metric or on mass-univariate nodal or edge-based comparisons that ignore the inherent topological properties of the network, yielding little power and failing to make network level comparisons. Gleaning deeper insights into normal and abnormal changes in complex brain function demands methods that take advantage of the wealth of data present in an entire brain network. Here we propose a permutation testing framework that allows comparing groups of networks while incorporating topological features inherent in each individual network. We validate our approach using simulated data with known group differences. We then apply the method to functional brain networks derived from fMRI data.

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.

Brain evolution and development: adaptation, allometry and constraint

PubMed Central

Barton, Robert A.

2016-01-01

Phenotypic traits are products of two processes: evolution and development. But how do these processes combine to produce integrated phenotypes? Comparative studies identify consistent patterns of covariation, or allometries, between brain and body size, and between brain components, indicating the presence of significant constraints limiting independent evolution of separate parts. These constraints are poorly understood, but in principle could be either developmental or functional. The developmental constraints hypothesis suggests that individual components (brain and body size, or individual brain components) tend to evolve together because natural selection operates on relatively simple developmental mechanisms that affect the growth of all parts in a concerted manner. The functional constraints hypothesis suggests that correlated change reflects the action of selection on distributed functional systems connecting the different sub-components, predicting more complex patterns of mosaic change at the level of the functional systems and more complex genetic and developmental mechanisms. These hypotheses are not mutually exclusive but make different predictions. We review recent genetic and neurodevelopmental evidence, concluding that functional rather than developmental constraints are the main cause of the observed patterns. PMID:27629025

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

ERIC Educational Resources Information Center

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

2010-01-01

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

Longitudinal Dynamics of 3-Dimensional Components of Selfhood After Severe Traumatic Brain Injury: A qEEG Case Study.

PubMed

Fingelkurts, Andrew A; Fingelkurts, Alexander A

2017-09-01

In this report, we describe the case of a patient who sustained extremely severe traumatic brain damage with diffuse axonal injury in a traffic accident and whose recovery was monitored during 6 years. Specifically, we were interested in the recovery dynamics of 3-dimensional components of selfhood (a 3-dimensional construct model for the complex experiential selfhood has been recently proposed based on the empirical findings on the functional-topographical specialization of 3 operational modules of brain functional network responsible for the self-consciousness processing) derived from the electroencephalographic (EEG) signal. The analysis revealed progressive (though not monotonous) restoration of EEG functional connectivity of 3 modules of brain functional network responsible for the self-consciousness processing, which was also paralleled by the clinically significant functional recovery. We propose that restoration of normal integrity of the operational modules of the self-referential brain network may underlie the positive dynamics of 3 aspects of selfhood and provide a neurobiological mechanism for their recovery. The results are discussed in the context of recent experimental studies that support this inference. Studies of ongoing recovery after severe brain injury utilizing knowledge about each separate aspect of complex selfhood will likely help to develop more efficient and targeted rehabilitation programs for patients with brain trauma.

The function of neurocognitive networks. Comment on “Understanding brain networks and brain organization” by Pessoa

NASA Astrophysics Data System (ADS)

Bressler, Steven L.

2014-09-01

Pessoa [5] has performed a valuable service by reviewing the extant literature on brain networks and making a number of interesting proposals about their cognitive function. The term function is at the core of understanding the brain networks of cognition, or neurocognitive networks (NCNs) [1]. The great Russian neuropsychologist, Luria [4], defined brain function as the common task executed by a distributed brain network of complex dynamic structures united by the demands of cognition. Casting Luria in a modern light, we can say that function emerges from the interactions of brain regions in NCNs as they dynamically self-organize according to cognitive demands. Pessoa rightly details the mapping between brain function and structure, emphasizing both its pluripotency (one structure having multiple functions) and degeneracy (many structures having the same function). However, he fails to consider the potential importance of a one-to-one mapping between NCNs and function. If NCNs are uniquely composed of specific collections of brain areas, then each NCN has a unique function determined by that composition.

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

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

PubMed

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

2015-03-01

Complex systems are described according to two central dimensions: (a) the randomness of their output, quantified via entropy; and (b) their complexity, which reflects the organization of a system's generators. Whereas some approaches hold that complexity can be reduced to uncertainty or entropy, an axiom of complexity science is that signals with very high or very low entropy are generated by relatively non-complex systems, while complex systems typically generate outputs with entropy peaking between these two extremes. In understanding their environment, individuals would benefit from coding for both input entropy and complexity; entropy indexes uncertainty and can inform probabilistic coding strategies, whereas complexity reflects a concise and abstract representation of the underlying environmental configuration, which can serve independent purposes, e.g., as a template for generalization and rapid comparisons between environments. Using functional neuroimaging, we demonstrate that, in response to passively processed auditory inputs, functional integration patterns in the human brain track both the entropy and complexity of the auditory signal. Connectivity between several brain regions scaled monotonically with input entropy, suggesting sensitivity to uncertainty, whereas connectivity between other regions tracked entropy in a convex manner consistent with sensitivity to input complexity. These findings suggest that the human brain simultaneously tracks the uncertainty of sensory data and effectively models their environmental generators. Copyright © 2014. Published by Elsevier Inc.

A trade-off between local and distributed information processing associated with remote episodic versus semantic memory.

PubMed

Heisz, Jennifer J; Vakorin, Vasily; Ross, Bernhard; Levine, Brian; McIntosh, Anthony R

2014-01-01

Episodic memory and semantic memory produce very different subjective experiences yet rely on overlapping networks of brain regions for processing. Traditional approaches for characterizing functional brain networks emphasize static states of function and thus are blind to the dynamic information processing within and across brain regions. This study used information theoretic measures of entropy to quantify changes in the complexity of the brain's response as measured by magnetoencephalography while participants listened to audio recordings describing past personal episodic and general semantic events. Personal episodic recordings evoked richer subjective mnemonic experiences and more complex brain responses than general semantic recordings. Critically, we observed a trade-off between the relative contribution of local versus distributed entropy, such that personal episodic recordings produced relatively more local entropy whereas general semantic recordings produced relatively more distributed entropy. Changes in the relative contributions of local and distributed entropy to the total complexity of the system provides a potential mechanism that allows the same network of brain regions to represent cognitive information as either specific episodes or more general semantic knowledge.

Vision's Brain.

ERIC Educational Resources Information Center

Miller, Julie Ann

1978-01-01

The functional architecture of the primary visual cortex has been explored by monitoring the responses of individual brain cells to visual stimuli. A combination of anatomical and physiological techniques reveals groups of functionally related cells, juxtaposed and superimposed, in a sometimes complex, but presumably efficient, structure. (BB)

Rehabilitation of executive functioning in patients with frontal lobe brain damage with goal management training.

PubMed

Levine, Brian; Schweizer, Tom A; O'Connor, Charlene; Turner, Gary; Gillingham, Susan; Stuss, Donald T; Manly, Tom; Robertson, Ian H

2011-01-01

Executive functioning deficits due to brain disease affecting frontal lobe functions cause significant real-life disability, yet solid evidence in support of executive functioning interventions is lacking. Goal Management Training (GMT), an executive functioning intervention that draws upon theories concerning goal processing and sustained attention, has received empirical support in studies of patients with traumatic brain injury, normal aging, and case studies. GMT promotes a mindful approach to complex real-life tasks that pose problems for patients with executive functioning deficits, with a main goal of periodically stopping ongoing behavior to monitor and adjust goals. In this controlled trial, an expanded version of GMT was compared to an alternative intervention, Brain Health Workshop that was matched to GMT on non-specific characteristics that can affect intervention outcome. Participants included 19 individuals in the chronic phase of recovery from brain disease (predominantly stroke) affecting frontal lobe function. Outcome data indicated specific effects of GMT on the Sustained Attention to Response Task as well as the Tower Test, a visuospatial problem-solving measure that reflected far transfer of training effects. There were no significant effects on self-report questionnaires, likely owing to the complexity of these measures in this heterogeneous patient sample. Overall, these data support the efficacy of GMT in the rehabilitation of executive functioning deficits.

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

PubMed Central

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

2016-01-01

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. PMID:26708753

Maturation of the auditory t-complex brain response across adolescence.

PubMed

Mahajan, Yatin; McArthur, Genevieve

2013-02-01

Adolescence is a time of great change in the brain in terms of structure and function. It is possible to track the development of neural function across adolescence using auditory event-related potentials (ERPs). This study tested if the brain's functional processing of sound changed across adolescence. We measured passive auditory t-complex peaks to pure tones and consonant-vowel (CV) syllables in 90 children and adolescents aged 10-18 years, as well as 10 adults. Across adolescence, Na amplitude increased to tones and speech at the right, but not left, temporal site. Ta amplitude decreased at the right temporal site for tones, and at both sites for speech. The Tb remained constant at both sites. The Na and Ta appeared to mature later in the right than left hemisphere. The t-complex peaks Na and Tb exhibited left lateralization and Ta showed right lateralization. Thus, the functional processing of sound continued to develop across adolescence and into adulthood. Crown Copyright © 2012. Published by Elsevier Ltd. All rights reserved.

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.

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.

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.

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.

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

Self-averaging in complex brain neuron signals

NASA Astrophysics Data System (ADS)

Bershadskii, A.; Dremencov, E.; Fukayama, D.; Yadid, G.

2002-12-01

Nonlinear statistical properties of Ventral Tegmental Area (VTA) of limbic brain are studied in vivo. VTA plays key role in generation of pleasure and in development of psychological drug addiction. It is shown that spiking time-series of the VTA dopaminergic neurons exhibit long-range correlations with self-averaging behavior. This specific VTA phenomenon has no relation to VTA rewarding function. Last result reveals complex role of VTA in limbic brain.

Connectome analysis for pre-operative brain mapping in neurosurgery

PubMed Central

Hart, Michael G.; Price, Stephen J.; Suckling, John

2016-01-01

Abstract Object: Brain mapping has entered a new era focusing on complex network connectivity. Central to this is the search for the connectome or the brains ‘wiring diagram’. Graph theory analysis of the connectome allows understanding of the importance of regions to network function, and the consequences of their impairment or excision. Our goal was to apply connectome analysis in patients with brain tumours to characterise overall network topology and individual patterns of connectivity alterations. Methods: Resting-state functional MRI data were acquired using multi-echo, echo planar imaging pre-operatively from five participants each with a right temporal–parietal–occipital glioblastoma. Complex networks analysis was initiated by parcellating the brain into anatomically regions amongst which connections were identified by retaining the most significant correlations between the respective wavelet decomposed time-series. Results: Key characteristics of complex networks described in healthy controls were preserved in these patients, including ubiquitous small world organization. An exponentially truncated power law fit to the degree distribution predicted findings of general network robustness to injury but with a core of hubs exhibiting disproportionate vulnerability. Tumours produced a consistent reduction in local and long-range connectivity with distinct patterns of connection loss depending on lesion location. Conclusions: Connectome analysis is a feasible and novel approach to brain mapping in individual patients with brain tumours. Applications to pre-surgical planning include identifying regions critical to network function that should be preserved and visualising connections at risk from tumour resection. In the future one could use such data to model functional plasticity and recovery of cognitive deficits. PMID:27447756

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.

Multilayer modeling and analysis of human brain networks

PubMed Central

2017-01-01

Abstract Understanding how the human brain is structured, and how its architecture is related to function, is of paramount importance for a variety of applications, including but not limited to new ways to prevent, deal with, and cure brain diseases, such as Alzheimer’s or Parkinson’s, and psychiatric disorders, such as schizophrenia. The recent advances in structural and functional neuroimaging, together with the increasing attitude toward interdisciplinary approaches involving computer science, mathematics, and physics, are fostering interesting results from computational neuroscience that are quite often based on the analysis of complex network representation of the human brain. In recent years, this representation experienced a theoretical and computational revolution that is breaching neuroscience, allowing us to cope with the increasing complexity of the human brain across multiple scales and in multiple dimensions and to model structural and functional connectivity from new perspectives, often combined with each other. In this work, we will review the main achievements obtained from interdisciplinary research based on magnetic resonance imaging and establish de facto, the birth of multilayer network analysis and modeling of the human brain. PMID:28327916

Neurodevelopment and executive function in autism.

PubMed

O'Hearn, Kirsten; Asato, Miya; Ordaz, Sarah; Luna, Beatriz

2008-01-01

Autism is a neurodevelopmental disorder characterized by social and communication deficits, and repetitive behavior. Studies investigating the integrity of brain systems in autism suggest a wide range of gray and white matter abnormalities that are present early in life and change with development. These abnormalities predominantly affect association areas and undermine functional integration. Executive function, which has a protracted development into adolescence and reflects the integration of complex widely distributed brain function, is also affected in autism. Evidence from studies probing response inhibition and working memory indicate impairments in these core components of executive function, as well as compensatory mechanisms that permit normative function in autism. Studies also demonstrate age-related improvements in executive function from childhood to adolescence in autism, indicating the presence of plasticity and suggesting a prolonged window for effective treatment. Despite developmental gains, mature executive functioning is limited in autism, reflecting abnormalities in wide-spread brain networks that may lead to impaired processing of complex information across all domains.

Whole-brain functional hypoconnectivity as an endophenotype of autism in adolescents

PubMed Central

Moseley, R.L.; Ypma, R.J.F.; Holt, R.J.; Floris, D.; Chura, L.R.; Spencer, M.D.; Baron-Cohen, S.; Suckling, J.; Bullmore, E.; Rubinov, M.

2015-01-01

Endophenotypes are heritable and quantifiable markers that may assist in the identification of the complex genetic underpinnings of psychiatric conditions. Here we examined global hypoconnectivity as an endophenotype of autism spectrum conditions (ASCs). We studied well-matched groups of adolescent males with autism, genetically-related siblings of individuals with autism, and typically-developing control participants. We parcellated the brain into 258 regions and used complex-network analysis to detect a robust hypoconnectivity endophenotype in our participant group. We observed that whole-brain functional connectivity was highest in controls, intermediate in siblings, and lowest in ASC, in task and rest conditions. We identified additional, local endophenotype effects in specific networks including the visual processing and default mode networks. Our analyses are the first to show that whole-brain functional hypoconnectivity is an endophenotype of autism in adolescence, and may thus underlie the heritable similarities seen in adolescents with ASC and their relatives. PMID:26413477

The Insula: A ‘Hub of Activity’ in Migraine

PubMed Central

Borsook, David; Veggeberg, Rosanna; Erpelding, Nathalie; Borra, Ronald; Linnman, Clas; Burstein, Rami; Becerra, Lino

2017-01-01

The insula, a ‘cortical hub’ buried within the lateral sulcus, is involved in a number of processes including goal-directed cognition, conscious awareness, autonomic regulation, interoception and somatosensation. While some of these processes are well known in the clinical presentation of migraine (i.e., autonomic and somatosensory alterations), other more complex behaviors in migraine, such as conscious awareness and error detection, are less well described. Since the insula processes and relays afferent inputs from brain areas involved in these functions to areas involved in higher cortical function such as frontal, temporal and parietal regions, it may be implicated as a brain region that translates the signals of altered internal milieu in migraine, along with other chronic pain conditions, through the insula into complex behaviors. Here we review how the insula function and structure is altered in migraine. As a brain region of a number of brain functions, it may serve as a model to study new potential clinical perspectives for migraine treatment. PMID:26290446

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.

Videogame training strategy-induced change in brain function during a complex visuomotor task.

PubMed

Lee, Hyunkyu; Voss, Michelle W; Prakash, Ruchika Shaurya; Boot, Walter R; Vo, Loan T K; Basak, Chandramallika; Vanpatter, Matt; Gratton, Gabriele; Fabiani, Monica; Kramer, Arthur F

2012-07-01

Although changes in brain function induced by cognitive training have been examined, functional plasticity associated with specific training strategies is still relatively unexplored. In this study, we examined changes in brain function during a complex visuomotor task following training using the Space Fortress video game. To assess brain function, participants completed functional magnetic resonance imaging (fMRI) before and after 30 h of training with one of two training regimens: Hybrid Variable-Priority Training (HVT), with a focus on improving specific skills and managing task priority, or Full Emphasis Training (FET), in which participants simply practiced the game to obtain the highest overall score. Control participants received only 6 h of FET. Compared to FET, HVT learners reached higher performance on the game and showed less brain activation in areas related to visuo-spatial attention and goal-directed movement after training. Compared to the control group, HVT exhibited less brain activation in right dorsolateral prefrontal cortex (DLPFC), coupled with greater performance improvement. Region-of-interest analysis revealed that the reduction in brain activation was correlated with improved performance on the task. This study sheds light on the neurobiological mechanisms of improved learning from directed training (HVT) over non-directed training (FET), which is related to visuo-spatial attention and goal-directed motor planning, while separating the practice-based benefit, which is related to executive control and rule management. Copyright © 2012 Elsevier B.V. All rights reserved.

Enlarging the scope: grasping brain complexity

PubMed Central

Tognoli, Emmanuelle; Kelso, J. A. Scott

2014-01-01

To further advance our understanding of the brain, new concepts and theories are needed. In particular, the ability of the brain to create information flows must be reconciled with its propensity for synchronization and mass action. The theoretical and empirical framework of Coordination Dynamics, a key aspect of which is metastability, are presented as a starting point to study the interplay of integrative and segregative tendencies that are expressed in space and time during the normal course of brain and behavioral function. Some recent shifts in perspective are emphasized, that may ultimately lead to a better understanding of brain complexity. PMID:25009476

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

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 ...

Pathophysiological implications of neurovascular P450 in brain disorders

PubMed Central

Ghosh, Chaitali; Hossain, Mohammed; Solanki, Jesal; Dadas, Aaron; Marchi, Nicola; Janigro, Damir

2016-01-01

Over the past decades, the significance of cytochrome P450 (CYP) enzymes has expanded beyond their role as peripheral drug metabolizers in the liver and gut. CYP enzymes are also functionally active at the neurovascular interface. CYP expression is modulated by disease states, impacting cellular functions, detoxification, and reactivity to toxic stimuli and brain drug biotransformation. Unveiling the physiological and molecular complexity of brain P450 enzymes will improve our understanding of the mechanisms underlying brain drug availability, pharmacological efficacy, and neurotoxic adverse effects from pharmacotherapy targeting brain disorders. PMID:27312874

Rehabilitation of Executive Functioning in Patients with Frontal Lobe Brain Damage with Goal Management Training

PubMed Central

Levine, Brian; Schweizer, Tom A.; O'Connor, Charlene; Turner, Gary; Gillingham, Susan; Stuss, Donald T.; Manly, Tom; Robertson, Ian H.

2011-01-01

Executive functioning deficits due to brain disease affecting frontal lobe functions cause significant real-life disability, yet solid evidence in support of executive functioning interventions is lacking. Goal Management Training (GMT), an executive functioning intervention that draws upon theories concerning goal processing and sustained attention, has received empirical support in studies of patients with traumatic brain injury, normal aging, and case studies. GMT promotes a mindful approach to complex real-life tasks that pose problems for patients with executive functioning deficits, with a main goal of periodically stopping ongoing behavior to monitor and adjust goals. In this controlled trial, an expanded version of GMT was compared to an alternative intervention, Brain Health Workshop that was matched to GMT on non-specific characteristics that can affect intervention outcome. Participants included 19 individuals in the chronic phase of recovery from brain disease (predominantly stroke) affecting frontal lobe function. Outcome data indicated specific effects of GMT on the Sustained Attention to Response Task as well as the Tower Test, a visuospatial problem-solving measure that reflected far transfer of training effects. There were no significant effects on self-report questionnaires, likely owing to the complexity of these measures in this heterogeneous patient sample. Overall, these data support the efficacy of GMT in the rehabilitation of executive functioning deficits. PMID:21369362

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

Untangling Brain-Wide Dynamics in Consciousness by Cross-Embedding

PubMed Central

Tajima, Satohiro; Yanagawa, Toru; Fujii, Naotaka; Toyoizumi, Taro

2015-01-01

Brain-wide interactions generating complex neural dynamics are considered crucial for emergent cognitive functions. However, the irreducible nature of nonlinear and high-dimensional dynamical interactions challenges conventional reductionist approaches. We introduce a model-free method, based on embedding theorems in nonlinear state-space reconstruction, that permits a simultaneous characterization of complexity in local dynamics, directed interactions between brain areas, and how the complexity is produced by the interactions. We demonstrate this method in large-scale electrophysiological recordings from awake and anesthetized monkeys. The cross-embedding method captures structured interaction underlying cortex-wide dynamics that may be missed by conventional correlation-based analysis, demonstrating a critical role of time-series analysis in characterizing brain state. The method reveals a consciousness-related hierarchy of cortical areas, where dynamical complexity increases along with cross-area information flow. These findings demonstrate the advantages of the cross-embedding method in deciphering large-scale and heterogeneous neuronal systems, suggesting a crucial contribution by sensory-frontoparietal interactions to the emergence of complex brain dynamics during consciousness. PMID:26584045

Intrinsic protective mechanisms of the neuron-glia network against glioma invasion.

PubMed

Iwadate, Yasuo; Fukuda, Kazumasa; Matsutani, Tomoo; Saeki, Naokatsu

2016-04-01

Gliomas arising in the brain parenchyma infiltrate into the surrounding brain and break down established complex neuron-glia networks. However, mounting evidence suggests that initially the network microenvironment of the adult central nervous system (CNS) is innately non-permissive to glioma cell invasion. The main players are inhibitory molecules in CNS myelin, as well as proteoglycans associated with astrocytes. Neural stem cells, and neurons themselves, possess inhibitory functions against neighboring tumor cells. These mechanisms have evolved to protect the established neuron-glia network, which is necessary for brain function. Greater insight into the interaction between glioma cells and the surrounding neuron-glia network is crucial for developing new therapies for treating these devastating tumors while preserving the important and complex neural functions of patients. Copyright © 2015 Elsevier Ltd. All rights reserved.

Segregation and persistence of form in the lateral occipital complex.

PubMed

Ferber, Susanne; Humphrey, G Keith; Vilis, Tutis

2005-01-01

While the lateral occipital complex (LOC) has been shown to be implicated in object recognition, it is unclear whether this brain area is responsive to low-level stimulus-driven features or high-level representational processes. We used scrambled shape-from-motion displays to disambiguate the presence of contours from figure-ground segregation and to measure the strength of the binding process for shapes without contours. We found persisting brain activation in the LOC for scrambled displays after the motion stopped indicating that this brain area subserves and maintains figure-ground segregation processes, a low-level function in the object processing hierarchy. In our second experiment, we found that the figure-ground segregation process has some form of spatial constancy indicating top-down influences. The persisting activation after the motion stops suggests an intermediate role in object recognition processes for this brain area and might provide further evidence for the idea that the lateral occipital complex subserves mnemonic functions mediating between iconic and short-term memory.

The anatomical problem posed by brain complexity and size: a potential solution.

PubMed

DeFelipe, Javier

2015-01-01

Over the years the field of neuroanatomy has evolved considerably but unraveling the extraordinary structural and functional complexity of the brain seems to be an unattainable goal, partly due to the fact that it is only possible to obtain an imprecise connection matrix of the brain. The reasons why reaching such a goal appears almost impossible to date is discussed here, together with suggestions of how we could overcome this anatomical problem by establishing new methodologies to study the brain and by promoting interdisciplinary collaboration. Generating a realistic computational model seems to be the solution rather than attempting to fully reconstruct the whole brain or a particular brain region.

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

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.

Resting and Task-Modulated High-Frequency Brain Rhythms Measured by Scalp Encephalography in Infants with Tuberous Sclerosis Complex

ERIC Educational Resources Information Center

Stamoulis, Catherine; Vogel-Farley, Vanessa; Degregorio, Geneva; Jeste, Shafali S.; Nelson, Charles A.

2015-01-01

The electrophysiological correlates of cognitive deficits in tuberous sclerosis complex (TSC) are not well understood, and modulations of neural dynamics by neuroanatomical abnormalities that characterize the disorder remain elusive. Neural oscillations (rhythms) are a fundamental aspect of brain function, and have dominant frequencies in a wide…

Training in Goal-Oriented Attentional Self-Regulation Improves Executive Functioning in Veterans with Chronic TBI.

PubMed

Novakovic-Agopian, Tatjana; Kornblith, Erica S; Abrams, Gary; Burciaga-Rosales, Joaquin; Loya, Fred; D'Esposito, Mark; Chen, Anthony J-W

2018-05-02

Deficits in executive control functions are some of the most common and disabling consequences of both military and civilian brain injury. However, effective interventions are scant. The goal of this study was to assess whether cognitive rehabilitation training that was successfully applied in chronic civilian brain injury would be effective for military Veterans with TBI. In a prior study, participants with chronic acquired brain injury significantly improved after training in goal-oriented attentional self-regulation (GOALS) on measures of attention/executive function, functional task performance, and goal-directed control over neural processing on fMRI. The objective of this study was to assess effects of GOALS training in Veterans with chronic TBI. 33 Veterans with chronic TBI and executive difficulties in their daily life completed either five weeks of manualized Goal-Oriented Attentional Self-Regulation (GOALS) training or Brain-Health Education (BHE) matched in time and intensity. Evaluator-blinded assessments at baseline and post training included neuropsychological and complex functional task performance and self-report measures of emotional regulation. After GOALS, but not BHE training, participants significantly improved from baseline on primary outcome measures of: Overall Complex Attention/Executive Function composite neuropsychological performance score [F = 7.10, p =.01; partial 2 = .19], and on overall complex functional task performance (Goal Processing Scale Overall Performance) [F=6.92, p=.01, partial 2 =.20]. Additionally, post-GOALS participants indicated significant improvement on emotional regulation self-report measures [POMS Confusion Score F=6.05, p=.02, partial2=.20]. Training in attentional self-regulation applied to participant defined goals may improve cognitive functioning in Veterans with chronic TBI. Attention regulation training may not only impact executive control functioning in real world complex tasks, but may also improve emotional regulation and functioning. Implications for treatment of Veterans with TBI are discussed.

Detecting Brain State Changes via Fiber-Centered Functional Connectivity Analysis

PubMed Central

Li, Xiang; Lim, Chulwoo; Li, Kaiming; Guo, Lei; Liu, Tianming

2013-01-01

Diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) have been widely used to study structural and functional brain connectivity in recent years. A common assumption used in many previous functional brain connectivity studies is the temporal stationarity. However, accumulating literature evidence has suggested that functional brain connectivity is under temporal dynamic changes in different time scales. In this paper, a novel and intuitive approach is proposed to model and detect dynamic changes of functional brain states based on multimodal fMRI/DTI data. The basic idea is that functional connectivity patterns of all fiber-connected cortical voxels are concatenated into a descriptive functional feature vector to represent the brain’s state, and the temporal change points of brain states are decided by detecting the abrupt changes of the functional vector patterns via the sliding window approach. Our extensive experimental results have shown that meaningful brain state change points can be detected in task-based fMRI/DTI, resting state fMRI/DTI, and natural stimulus fMRI/DTI data sets. Particularly, the detected change points of functional brain states in task-based fMRI corresponded well to the external stimulus paradigm administered to the participating subjects, thus partially validating the proposed brain state change detection approach. The work in this paper provides novel perspective on the dynamic behaviors of functional brain connectivity and offers a starting point for future elucidation of the complex patterns of functional brain interactions and dynamics. PMID:22941508

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...

Caffeine restores regional brain activation in acute hypoglycaemia in healthy volunteers.

PubMed

Rosenthal, M J; Smith, D; Yaguez, L; Giampietro, V; Kerr, D; Bullmore, E; Brammer, M; Williams, S C R; Amiel, S A

2007-07-01

Caffeine enhances counterregulatory responses to acute hypoglycaemia. Our aim was to explore its effects on cortical function, which are not known at present. Regional brain activation during performance of the four-choice reaction time (4CRT) at different levels of complexity was measured using functional magnetic resonance imaging (fMRI) at euglycaemia (5 mmol/l) and hypoglycaemia (2.6 mmol/l) in the presence and absence of caffeine in six healthy right-handed men. During hypoglycaemia, caffeine enhanced adrenaline responses to hypoglycaemia (2.5 +/- 0.7 nmol/l to 4.0 +/- 1.0 nmol/l, P = 0.01) and restored the brain activation response to the non-cued 4CRT, the linear increases in regional brain activation associated with increased task complexity and the ability to respond to a cue that were lost in hypoglycaemia alone. Caffeine can sustain regional brain activation patterns lost in acute hypoglycaemia, with some restoration of cortical function and enhanced adrenaline responsiveness. A methodology has been established that may help in the development of therapies to protect against severe hypoglycaemia in insulin therapy for patients with diabetes and problematic hypoglycaemia.

Hierarchical organization of functional connectivity in the mouse brain: a complex network approach.

PubMed

Bardella, Giampiero; Bifone, Angelo; Gabrielli, Andrea; Gozzi, Alessandro; Squartini, Tiziano

2016-08-18

This paper represents a contribution to the study of the brain functional connectivity from the perspective of complex networks theory. More specifically, we apply graph theoretical analyses to provide evidence of the modular structure of the mouse brain and to shed light on its hierarchical organization. We propose a novel percolation analysis and we apply our approach to the analysis of a resting-state functional MRI data set from 41 mice. This approach reveals a robust hierarchical structure of modules persistent across different subjects. Importantly, we test this approach against a statistical benchmark (or null model) which constrains only the distributions of empirical correlations. Our results unambiguously show that the hierarchical character of the mouse brain modular structure is not trivially encoded into this lower-order constraint. Finally, we investigate the modular structure of the mouse brain by computing the Minimal Spanning Forest, a technique that identifies subnetworks characterized by the strongest internal correlations. This approach represents a faster alternative to other community detection methods and provides a means to rank modules on the basis of the strength of their internal edges.

Hierarchical organization of functional connectivity in the mouse brain: a complex network approach

NASA Astrophysics Data System (ADS)

Bardella, Giampiero; Bifone, Angelo; Gabrielli, Andrea; Gozzi, Alessandro; Squartini, Tiziano

2016-08-01

This paper represents a contribution to the study of the brain functional connectivity from the perspective of complex networks theory. More specifically, we apply graph theoretical analyses to provide evidence of the modular structure of the mouse brain and to shed light on its hierarchical organization. We propose a novel percolation analysis and we apply our approach to the analysis of a resting-state functional MRI data set from 41 mice. This approach reveals a robust hierarchical structure of modules persistent across different subjects. Importantly, we test this approach against a statistical benchmark (or null model) which constrains only the distributions of empirical correlations. Our results unambiguously show that the hierarchical character of the mouse brain modular structure is not trivially encoded into this lower-order constraint. Finally, we investigate the modular structure of the mouse brain by computing the Minimal Spanning Forest, a technique that identifies subnetworks characterized by the strongest internal correlations. This approach represents a faster alternative to other community detection methods and provides a means to rank modules on the basis of the strength of their internal edges.

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

Down syndrome's brain dynamics: analysis of fractality in resting state.

PubMed

Hemmati, Sahel; Ahmadlou, Mehran; Gharib, Masoud; Vameghi, Roshanak; Sajedi, Firoozeh

2013-08-01

To the best knowledge of the authors there is no study on nonlinear brain dynamics of down syndrome (DS) patients, whereas brain is a highly complex and nonlinear system. In this study, fractal dimension of EEG, as a key characteristic of brain dynamics, showing irregularity and complexity of brain dynamics, was used for evaluation of the dynamical changes in the DS brain. The results showed higher fractality of the DS brain in almost all regions compared to the normal brain, which indicates less centrality and higher irregular or random functioning of the DS brain regions. Also, laterality analysis of the frontal lobe showed that the normal brain had a right frontal laterality of complexity whereas the DS brain had an inverse pattern (left frontal laterality). Furthermore, the high accuracy of 95.8 % obtained by enhanced probabilistic neural network classifier showed the potential of nonlinear dynamic analysis of the brain for diagnosis of DS patients. Moreover, the results showed that the higher EEG fractality in DS is associated with the higher fractality in the low frequencies (delta and theta), in broad regions of the brain, and the high frequencies (beta and gamma), majorly in the frontal regions.

Disrupted Brain Functional Organization in Epilepsy Revealed by Graph Theory Analysis.

PubMed

Song, Jie; Nair, Veena A; Gaggl, Wolfgang; Prabhakaran, Vivek

2015-06-01

The human brain is a complex and dynamic system that can be modeled as a large-scale brain network to better understand the reorganizational changes secondary to epilepsy. In this study, we developed a brain functional network model using graph theory methods applied to resting-state fMRI data acquired from a group of epilepsy patients and age- and gender-matched healthy controls. A brain functional network model was constructed based on resting-state functional connectivity. A minimum spanning tree combined with proportional thresholding approach was used to obtain sparse connectivity matrices for each subject, which formed the basis of brain networks. We examined the brain reorganizational changes in epilepsy thoroughly at the level of the whole brain, the functional network, and individual brain regions. At the whole-brain level, local efficiency was significantly decreased in epilepsy patients compared with the healthy controls. However, global efficiency was significantly increased in epilepsy due to increased number of functional connections between networks (although weakly connected). At the functional network level, there were significant proportions of newly formed connections between the default mode network and other networks and between the subcortical network and other networks. There was a significant proportion of decreasing connections between the cingulo-opercular task control network and other networks. Individual brain regions from different functional networks, however, showed a distinct pattern of reorganizational changes in epilepsy. These findings suggest that epilepsy alters brain efficiency in a consistent pattern at the whole-brain level, yet alters brain functional networks and individual brain regions differently.

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.

How does the brain process music?

PubMed

Warren, Jason

2008-02-01

The organisation of the musical brain is a major focus of interest in contemporary neuroscience. This reflects the increasing sophistication of tools (especially imaging techniques) to examine brain anatomy and function in health and disease, and the recognition that music provides unique insights into a number of aspects of nonverbal brain function. The emerging picture is complex but coherent, and moves beyond older ideas of music as the province of a single brain area or hemisphere to the concept of music as a 'whole-brain' phenomenon. Music engages a distributed set of cortical modules that process different perceptual, cognitive and emotional components with varying selectivity. 'Why' rather than 'how' the brain processes music is a key challenge for the future.

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…

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.

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.

Complex vestibular macular anatomical relationships need a synthetic approach

NASA Technical Reports Server (NTRS)

Ross, M. D.

2001-01-01

Mammalian vestibular maculae are anatomically organized for complex parallel processing of linear acceleration information. Anatomical findings in rat maculae are provided in order to underscore this complexity, which is little understood functionally. This report emphasizes that a synthetic approach is critical to understanding how maculae function and the kind of information they conduct to the brain.

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

Brain signal complexity rises with repetition suppression in visual learning.

PubMed

Lafontaine, Marc Philippe; Lacourse, Karine; Lina, Jean-Marc; McIntosh, Anthony R; Gosselin, Frédéric; Théoret, Hugo; Lippé, Sarah

2016-06-21

Neuronal activity associated with visual processing of an unfamiliar face gradually diminishes when it is viewed repeatedly. This process, known as repetition suppression (RS), is involved in the acquisition of familiarity. Current models suggest that RS results from interactions between visual information processing areas located in the occipito-temporal cortex and higher order areas, such as the dorsolateral prefrontal cortex (DLPFC). Brain signal complexity, which reflects information dynamics of cortical networks, has been shown to increase as unfamiliar faces become familiar. However, the complementarity of RS and increases in brain signal complexity have yet to be demonstrated within the same measurements. We hypothesized that RS and brain signal complexity increase occur simultaneously during learning of unfamiliar faces. Further, we expected alteration of DLPFC function by transcranial direct current stimulation (tDCS) to modulate RS and brain signal complexity over the occipito-temporal cortex. Participants underwent three tDCS conditions in random order: right anodal/left cathodal, right cathodal/left anodal and sham. Following tDCS, participants learned unfamiliar faces, while an electroencephalogram (EEG) was recorded. Results revealed RS over occipito-temporal electrode sites during learning, reflected by a decrease in signal energy, a measure of amplitude. Simultaneously, as signal energy decreased, brain signal complexity, as estimated with multiscale entropy (MSE), increased. In addition, prefrontal tDCS modulated brain signal complexity over the right occipito-temporal cortex during the first presentation of faces. These results suggest that although RS may reflect a brain mechanism essential to learning, complementary processes reflected by increases in brain signal complexity, may be instrumental in the acquisition of novel visual information. Such processes likely involve long-range coordinated activity between prefrontal and lower order visual areas. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

Mitochondrial Complex 1 Activity Measured by Spectrophotometry Is Reduced across All Brain Regions in Ageing and More Specifically in Neurodegeneration.

PubMed

Pollard, Amelia Kate; Craig, Emma Louise; Chakrabarti, Lisa

2016-01-01

Mitochondrial function, in particular complex 1 of the electron transport chain (ETC), has been shown to decrease during normal ageing and in neurodegenerative disease. However, there is some debate concerning which area of the brain has the greatest complex 1 activity. It is important to identify the pattern of activity in order to be able to gauge the effect of age or disease related changes. We determined complex 1 activity spectrophotometrically in the cortex, brainstem and cerebellum of middle aged mice (70-71 weeks), a cerebellar ataxic neurodegeneration model (pcd5J) and young wild type controls. We share our updated protocol on the measurements of complex1 activity and find that mitochondrial fractions isolated from frozen tissues can be measured for robust activity. We show that complex 1 activity is clearly highest in the cortex when compared with brainstem and cerebellum (p<0.003). Cerebellum and brainstem mitochondria exhibit similar levels of complex 1 activity in wild type brains. In the aged brain we see similar levels of complex 1 activity in all three-brain regions. The specific activity of complex 1 measured in the aged cortex is significantly decreased when compared with controls (p<0.0001). Both the cerebellum and brainstem mitochondria also show significantly reduced activity with ageing (p<0.05). The mouse model of ataxia predictably has a lower complex 1 activity in the cerebellum, and although reductions are measured in the cortex and brain stem, the remaining activity is higher than in the aged brains. We present clear evidence that complex 1 activity decreases across the brain with age and much more specifically in the cerebellum of the pcd5j mouse. Mitochondrial impairment can be a region specific phenomenon in disease, but in ageing appears to affect the entire brain, abolishing the pattern of higher activity in cortical regions.

Causal effect of disconnection lesions on interhemispheric functional connectivity in rhesus monkeys

PubMed Central

O’Reilly, Jill X.; Croxson, Paula L.; Jbabdi, Saad; Sallet, Jerome; Noonan, MaryAnn P.; Mars, Rogier B.; Browning, Philip G.F.; Wilson, Charles R. E.; Mitchell, Anna S.; Miller, Karla L.; Rushworth, Matthew F. S.; Baxter, Mark G.

2013-01-01

In the absence of external stimuli or task demands, correlations in spontaneous brain activity (functional connectivity) reflect patterns of anatomical connectivity. Hence, resting-state functional connectivity has been used as a proxy measure for structural connectivity and as a biomarker for brain changes in disease. To relate changes in functional connectivity to physiological changes in the brain, it is important to understand how correlations in functional connectivity depend on the physical integrity of brain tissue. The causal nature of this relationship has been called into question by patient data suggesting that decreased structural connectivity does not necessarily lead to decreased functional connectivity. Here we provide evidence for a causal but complex relationship between structural connectivity and functional connectivity: we tested interhemispheric functional connectivity before and after corpus callosum section in rhesus monkeys. We found that forebrain commissurotomy severely reduced interhemispheric functional connectivity, but surprisingly, this effect was greatly mitigated if the anterior commissure was left intact. Furthermore, intact structural connections increased their functional connectivity in line with the hypothesis that the inputs to each node are normalized. We conclude that functional connectivity is likely driven by corticocortical white matter connections but with complex network interactions such that a near-normal pattern of functional connectivity can be maintained by just a few indirect structural connections. These surprising results highlight the importance of network-level interactions in functional connectivity and may cast light on various paradoxical findings concerning changes in functional connectivity in disease states. PMID:23924609

The Topographical Mapping in Drosophila Central Complex Network and Its Signal Routing

PubMed Central

Chang, Po-Yen; Su, Ta-Shun; Shih, Chi-Tin; Lo, Chung-Chuan

2017-01-01

Neural networks regulate brain functions by routing signals. Therefore, investigating the detailed organization of a neural circuit at the cellular levels is a crucial step toward understanding the neural mechanisms of brain functions. To study how a complicated neural circuit is organized, we analyzed recently published data on the neural circuit of the Drosophila central complex, a brain structure associated with a variety of functions including sensory integration and coordination of locomotion. We discovered that, except for a small number of “atypical” neuron types, the network structure formed by the identified 194 neuron types can be described by only a few simple mathematical rules. Specifically, the topological mapping formed by these neurons can be reconstructed by applying a generation matrix on a small set of initial neurons. By analyzing how information flows propagate with or without the atypical neurons, we found that while the general pattern of signal propagation in the central complex follows the simple topological mapping formed by the “typical” neurons, some atypical neurons can substantially re-route the signal pathways, implying specific roles of these neurons in sensory signal integration. The present study provides insights into the organization principle and signal integration in the central complex. PMID:28443014

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.

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.

Heart and brain interaction in patients with heart failure: overview and proposal for a taxonomy. A position paper from the Study Group on Heart and Brain Interaction of the Heart Failure Association.

PubMed

Doehner, Wolfram; Ural, Dilek; Haeusler, Karl Georg; Čelutkienė, Jelena; Bestetti, Reinaldo; Cavusoglu, Yuksel; Peña-Duque, Marco A; Glavas, Duska; Iacoviello, Massimo; Laufs, Ulrich; Alvear, Ricardo Marmol; Mbakwem, Amam; Piepoli, Massimo F; Rosen, Stuart D; Tsivgoulis, Georgios; Vitale, Cristiana; Yilmaz, M Birhan; Anker, Stefan D; Filippatos, Gerasimos; Seferovic, Petar; Coats, Andrew J S; Ruschitzka, Frank

2018-02-01

Heart failure (HF) is a complex clinical syndrome with multiple interactions between the failing myocardium and cerebral (dys-)functions. Bi-directional feedback interactions between the heart and the brain are inherent in the pathophysiology of HF: (i) the impaired cardiac function affects cerebral structure and functional capacity, and (ii) neuronal signals impact on the cardiovascular continuum. These interactions contribute to the symptomatic presentation of HF patients and affect many co-morbidities of HF. Moreover, neuro-cardiac feedback signals significantly promote aggravation and further progression of HF and are causal in the poor prognosis of HF. The diversity and complexity of heart and brain interactions make it difficult to develop a comprehensive overview. In this paper a systematic approach is proposed to develop a comprehensive atlas of related conditions, signals and disease mechanisms of the interactions between the heart and the brain in HF. The proposed taxonomy is based on pathophysiological principles. Impaired perfusion of the brain may represent one major category, with acute (cardio-embolic) or chronic (haemodynamic failure) low perfusion being sub-categories with mostly different consequences (i.e. ischaemic stroke or cognitive impairment, respectively). Further categories include impairment of higher cortical function (mood, cognition), of brain stem function (sympathetic over-activation, neuro-cardiac reflexes). Treatment-related interactions could be categorized as medical, interventional and device-related interactions. Also interactions due to specific diseases are categorized. A methodical approach to categorize the interdependency of heart and brain may help to integrate individual research areas into an overall picture. © 2017 The Authors. European Journal of Heart Failure © 2017 European Society of Cardiology.

Regulation of the Adrenal Cortex Function During Stress

NASA Technical Reports Server (NTRS)

Soliman, K. F. A.

1978-01-01

A proposal to study the function of the adrenal gland in the rat during stress is presented. In the proposed project, three different phases of experimentation will be undertaken. The first phase includes establishment of the circadian rhythm of both brain amines and glucocoticoids, under normal conditions and under chronic and acute stressful conditions. The second phase includes the study of the pharmacokinetics of glucocorticoid binding under normal and stress conditions. The third phase includes brain uptake and binding under different experimental conditions. In the outlined experiments brain biogenic amines will be evaluated, adrenal functions will be measured and stress effect on those parameters will be studied. It is hoped that this investigation can explain some of the complex relationships between the brain neurotransmitter and adrenal function.

Graph theory analysis of complex brain networks: new concepts in brain mapping applied to neurosurgery.

PubMed

Hart, Michael G; Ypma, Rolf J F; Romero-Garcia, Rafael; Price, Stephen J; Suckling, John

2016-06-01

Neuroanatomy has entered a new era, culminating in the search for the connectome, otherwise known as the brain's wiring diagram. While this approach has led to landmark discoveries in neuroscience, potential neurosurgical applications and collaborations have been lagging. In this article, the authors describe the ideas and concepts behind the connectome and its analysis with graph theory. Following this they then describe how to form a connectome using resting state functional MRI data as an example. Next they highlight selected insights into healthy brain function that have been derived from connectome analysis and illustrate how studies into normal development, cognitive function, and the effects of synthetic lesioning can be relevant to neurosurgery. Finally, they provide a précis of early applications of the connectome and related techniques to traumatic brain injury, functional neurosurgery, and neurooncology.

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.

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.

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.

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.

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

Brain Modulyzer: Interactive Visual Analysis of Functional Brain Connectivity

DOE PAGES

Murugesan, Sugeerth; Bouchard, Kristopher; Brown, Jesse A.; ...

2016-05-09

Here, we present Brain Modulyzer, an interactive visual exploration tool for functional magnetic resonance imaging (fMRI) brain scans, aimed at analyzing the correlation between different brain regions when resting or when performing mental tasks. Brain Modulyzer combines multiple coordinated views—such as heat maps, node link diagrams, and anatomical views—using brushing and linking to provide an anatomical context for brain connectivity data. Integrating methods from graph theory and analysis, e.g., community detection and derived graph measures, makes it possible to explore the modular and hierarchical organization of functional brain networks. Providing immediate feedback by displaying analysis results instantaneously while changing parametersmore » gives neuroscientists a powerful means to comprehend complex brain structure more effectively and efficiently and supports forming hypotheses that can then be validated via statistical analysis. In order to demonstrate the utility of our tool, we also present two case studies—exploring progressive supranuclear palsy, as well as memory encoding and retrieval« less

Brain Modulyzer: Interactive Visual Analysis of Functional Brain Connectivity

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

Murugesan, Sugeerth; Bouchard, Kristopher; Brown, Jesse A.

Here, we present Brain Modulyzer, an interactive visual exploration tool for functional magnetic resonance imaging (fMRI) brain scans, aimed at analyzing the correlation between different brain regions when resting or when performing mental tasks. Brain Modulyzer combines multiple coordinated views—such as heat maps, node link diagrams, and anatomical views—using brushing and linking to provide an anatomical context for brain connectivity data. Integrating methods from graph theory and analysis, e.g., community detection and derived graph measures, makes it possible to explore the modular and hierarchical organization of functional brain networks. Providing immediate feedback by displaying analysis results instantaneously while changing parametersmore » gives neuroscientists a powerful means to comprehend complex brain structure more effectively and efficiently and supports forming hypotheses that can then be validated via statistical analysis. In order to demonstrate the utility of our tool, we also present two case studies—exploring progressive supranuclear palsy, as well as memory encoding and retrieval« less

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.

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.

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

PubMed

Başar, Erol; Karakaş, Sirel

2006-05-01

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

Visual cortical areas of the mouse: comparison of parcellation and network structure with primates

PubMed Central

Laramée, Marie-Eve; Boire, Denis

2015-01-01

Brains have evolved to optimize sensory processing. In primates, complex cognitive tasks must be executed and evolution led to the development of large brains with many cortical areas. Rodents do not accomplish cognitive tasks of the same level of complexity as primates and remain with small brains both in relative and absolute terms. But is a small brain necessarily a simple brain? In this review, several aspects of the visual cortical networks have been compared between rodents and primates. The visual system has been used as a model to evaluate the level of complexity of the cortical circuits at the anatomical and functional levels. The evolutionary constraints are first presented in order to appreciate the rules for the development of the brain and its underlying circuits. The organization of sensory pathways, with their parallel and cross-modal circuits, is also examined. Other features of brain networks, often considered as imposing constraints on the development of underlying circuitry, are also discussed and their effect on the complexity of the mouse and primate brain are inspected. In this review, we discuss the common features of cortical circuits in mice and primates and see how these can be useful in understanding visual processing in these animals. PMID:25620914

Visual cortical areas of the mouse: comparison of parcellation and network structure with primates.

PubMed

Laramée, Marie-Eve; Boire, Denis

2014-01-01

Brains have evolved to optimize sensory processing. In primates, complex cognitive tasks must be executed and evolution led to the development of large brains with many cortical areas. Rodents do not accomplish cognitive tasks of the same level of complexity as primates and remain with small brains both in relative and absolute terms. But is a small brain necessarily a simple brain? In this review, several aspects of the visual cortical networks have been compared between rodents and primates. The visual system has been used as a model to evaluate the level of complexity of the cortical circuits at the anatomical and functional levels. The evolutionary constraints are first presented in order to appreciate the rules for the development of the brain and its underlying circuits. The organization of sensory pathways, with their parallel and cross-modal circuits, is also examined. Other features of brain networks, often considered as imposing constraints on the development of underlying circuitry, are also discussed and their effect on the complexity of the mouse and primate brain are inspected. In this review, we discuss the common features of cortical circuits in mice and primates and see how these can be useful in understanding visual processing in these animals.

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

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

PubMed

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

2017-08-29

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

Development of a selective left-hemispheric fronto-temporal network for processing syntactic complexity in language comprehension.

PubMed

Xiao, Yaqiong; Friederici, Angela D; Margulies, Daniel S; Brauer, Jens

2016-03-01

The development of language comprehension abilities in childhood is closely related to the maturation of the brain, especially the ability to process syntactically complex sentences. Recent studies proposed that the fronto-temporal connection within left perisylvian regions, supporting the processing of syntactically complex sentences, is still immature at preschool age. In the current study, resting state functional magnetic resonance imaging data were acquired from typically developing 5-year-old children and adults to shed further light on the brain functional development. Children additionally performed a behavioral syntactic comprehension test outside the scanner. The amplitude of low-frequency fluctuations was analyzed in order to identify the functional correlation networks of language-relevant brain regions. Results showed an intrahemispheric correlation between left inferior frontal gyrus (IFG) and left posterior superior temporal sulcus (pSTS) in adults, whereas an interhemispheric correlation between left IFG and its right-hemispheric homolog was predominant in children. Correlation analysis between resting-state functional connectivity and sentence processing performance in 5-year-olds revealed that local connectivity within the left IFG is associated with competence of processing syntactically simple canonical sentences, while long-range connectivity between IFG and pSTS in left hemisphere is associated with competence of processing syntactically relatively more complex non-canonical sentences. The present developmental data suggest that a selective left fronto-temporal connectivity network for processing complex syntax is already in functional connection at the age of 5 years when measured in a non-task situation. The correlational findings provide new insight into the relationship between intrinsic functional connectivity and syntactic language abilities in preschool children. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Exploration and Modulation of Brain Network Interactions with Noninvasive Brain Stimulation in Combination with Neuroimaging

PubMed Central

Shafi, Mouhsin M.; Westover, M. Brandon; Fox, Michael D.; Pascual-Leone, Alvaro

2012-01-01

Much recent work in systems neuroscience has focused on how dynamic interactions between different cortical regions underlie complex brain functions such as motor coordination, language, and emotional regulation. Various studies using neuroimaging and neurophysiologic techniques have suggested that in many neuropsychiatric disorders, these dynamic brain networks are dysregulated. Here we review the utility of combined noninvasive brain stimulation and neuroimaging approaches towards greater understanding of dynamic brain networks in health and disease. Brain stimulation techniques, such as transcranial magnetic stimulation and transcranial direct current stimulation, use electromagnetic principles to noninvasively alter brain activity, and induce focal but also network effects beyond the stimulation site. When combined with brain imaging techniques such as functional MRI, PET and EEG, these brain stimulation techniques enable a causal assessment of the interaction between different network components, and their respective functional roles. The same techniques can also be applied to explore hypotheses regarding the changes in functional connectivity that occur during task performance and in various disease states such as stroke, depression and schizophrenia. Finally, in diseases characterized by pathologic alterations in either the excitability within a single region or in the activity of distributed networks, such techniques provide a potential mechanism to alter cortical network function and architectures in a beneficial manner. PMID:22429242

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

Alterations of motor performance and brain cortex mitochondrial function during ethanol hangover.

PubMed

Bustamante, Juanita; Karadayian, Analia G; Lores-Arnaiz, Silvia; Cutrera, Rodolfo A

2012-08-01

Ethanol has been known to affect various behavioral parameters in experimental animals, even several hours after ethanol (EtOH) is absent from blood circulation, in the period known as hangover. The aim of this study was to assess the effects of acute ethanol hangover on motor performance in association with the brain cortex energetic metabolism. Evaluation of motor performance and brain cortex mitochondrial function during alcohol hangover was performed in mice 6 hours after a high ethanol dose (hangover onset). Animals were injected i.p. either with saline (control group) or with ethanol (3.8 g/kg BW) (hangover group). Ethanol hangover group showed a bad motor performance compared with control animals (p < .05). Oxygen uptake in brain cortex mitochondria from hangover animals showed a 34% decrease in the respiratory control rate as compared with the control group. Mitochondrial complex activities were decreased being the complex I-III the less affected by the hangover condition; complex II-III was markedly decreased by ethanol hangover showing 50% less activity than controls. Complex IV was 42% decreased as compared with control animals. Hydrogen peroxide production was 51% increased in brain cortex mitochondria from the hangover group, as compared with the control animals. Quantification of the mitochondrial transmembrane potential indicated that ethanol injected animals presented 17% less ability to maintain the polarized condition as compared with controls. These results indicate that a clear decrease in proton motive force occurs in brain cortex mitochondria during hangover conditions. We can conclude that a decreased motor performance observed in the hangover group of animals could be associated with brain cortex mitochondrial dysfunction and the resulting impairment of its energetic metabolism. Copyright © 2012 Elsevier Inc. 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.

Multifunctional and Context-Dependent Control of Vocal Acoustics by Individual Muscles

PubMed Central

Srivastava, Kyle H.; Elemans, Coen P.H.

2015-01-01

The relationship between muscle activity and behavioral output determines how the brain controls and modifies complex skills. In vocal control, ensembles of muscles are used to precisely tune single acoustic parameters such as fundamental frequency and sound amplitude. If individual vocal muscles were dedicated to the control of single parameters, then the brain could control each parameter independently by modulating the appropriate muscle or muscles. Alternatively, if each muscle influenced multiple parameters, a more complex control strategy would be required to selectively modulate a single parameter. Additionally, it is unknown whether the function of single muscles is fixed or varies across different vocal gestures. A fixed relationship would allow the brain to use the same changes in muscle activation to, for example, increase the fundamental frequency of different vocal gestures, whereas a context-dependent scheme would require the brain to calculate different motor modifications in each case. We tested the hypothesis that single muscles control multiple acoustic parameters and that the function of single muscles varies across gestures using three complementary approaches. First, we recorded electromyographic data from vocal muscles in singing Bengalese finches. Second, we electrically perturbed the activity of single muscles during song. Third, we developed an ex vivo technique to analyze the biomechanical and acoustic consequences of single-muscle perturbations. We found that single muscles drive changes in multiple parameters and that the function of single muscles differs across vocal gestures, suggesting that the brain uses a complex, gesture-dependent control scheme to regulate vocal output. PMID:26490859

Impulsivity and the Modular Organization of Resting-State Neural Networks

PubMed Central

Davis, F. Caroline; Knodt, Annchen R.; Sporns, Olaf; Lahey, Benjamin B.; Zald, David H.; Brigidi, Bart D.; Hariri, Ahmad R.

2013-01-01

Impulsivity is a complex trait associated with a range of maladaptive behaviors, including many forms of psychopathology. Previous research has implicated multiple neural circuits and neurotransmitter systems in impulsive behavior, but the relationship between impulsivity and organization of whole-brain networks has not yet been explored. Using graph theory analyses, we characterized the relationship between impulsivity and the functional segregation (“modularity”) of the whole-brain network architecture derived from resting-state functional magnetic resonance imaging (fMRI) data. These analyses revealed remarkable differences in network organization across the impulsivity spectrum. Specifically, in highly impulsive individuals, regulatory structures including medial and lateral regions of the prefrontal cortex were isolated from subcortical structures associated with appetitive drive, whereas these brain areas clustered together within the same module in less impulsive individuals. Further exploration of the modular organization of whole-brain networks revealed novel shifts in the functional connectivity between visual, sensorimotor, cortical, and subcortical structures across the impulsivity spectrum. The current findings highlight the utility of graph theory analyses of resting-state fMRI data in furthering our understanding of the neurobiological architecture of complex behaviors. PMID:22645253

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

Artistic explorations of the brain

PubMed Central

Fetz, Eberhard E.

2012-01-01

The symbiotic relationships between art and the brain begin with the obvious fact that brain mechanisms underlie the creation and appreciation of art. Conversely, many spectacular images of neural structures have remarkable aesthetic appeal. But beyond its fascinating forms, the many functions performed by brain mechanisms provide a profound subject for aesthetic exploration. Complex interactions in the tangled neural networks in our brain miraculously generate coherent behavior and cognition. Neuroscientists tackle these phenomena with specialized methodologies that limit the scope of exposition and are comprehensible to an initiated minority. Artists can perform an end run around these limitations by representing the brain's remarkable functions in a manner that can communicate to a wide and receptive audience. This paper explores the ways that brain mechanisms can provide a largely untapped subject for artistic exploration. PMID:22347178

Implications of Right Brain Research on Curriculum Development.

ERIC Educational Resources Information Center

MacKinnon, Colin

The idea that the brain may be more complex and varied in the ways that it responds to and interprets information than is generally recognized suggests that both the left and right hemispheres are in need of total development. In discussing the development of curriculum that will bring into harmony the functions of both brain hemispheres, it is…

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

Electrophysiological Source Imaging: A Noninvasive Window to Brain Dynamics.

PubMed

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

2018-06-04

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

We should be using nonlinear indices when relating heart-rate dynamics to cognition and mood

PubMed Central

Young, Hayley; Benton, David

2015-01-01

Both heart rate (HR) and brain functioning involve the integrated output of a multitude of regulatory mechanisms, that are not quantified adequately by linear approximations such as means and standard deviations. It was therefore considered whether non-linear measures of HR complexity are more strongly associated with cognition and mood. Whilst resting, the inter-beat (R-R) time series of twenty-one males and twenty-four females were measured for five minutes. The data were summarised using time, frequency and nonlinear complexity measures. Attention, memory, reaction times, mood and cortisol levels were assessed. Nonlinear HR indices captured additional information, enabling a greater percentage of the variance in behaviour to be explained. On occasions non-linear indices were related to aspects for behaviour, for example focused attention and cortisol production, when time or frequency indices were not. These effects were sexually dimorphic with HR complexity being more strongly associated with the behaviour of females. It was concluded that nonlinear rather than linear methods of summarizing the HR times series offers a novel way of relating brain functioning and behaviour. It should be considered whether non-linear measures of HR complexity can be used as a biomarker of the integrated functioning of the brain. PMID:26565560

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.

Task-evoked brain functional magnetic susceptibility mapping by independent component analysis (χICA).

PubMed

Chen, Zikuan; Calhoun, Vince D

2016-03-01

Conventionally, independent component analysis (ICA) is performed on an fMRI magnitude dataset to analyze brain functional mapping (AICA). By solving the inverse problem of fMRI, we can reconstruct the brain magnetic susceptibility (χ) functional states. Upon the reconstructed χ dataspace, we propose an ICA-based brain functional χ mapping method (χICA) to extract task-evoked brain functional map. A complex division algorithm is applied to a timeseries of fMRI phase images to extract temporal phase changes (relative to an OFF-state snapshot). A computed inverse MRI (CIMRI) model is used to reconstruct a 4D brain χ response dataset. χICA is implemented by applying a spatial InfoMax ICA algorithm to the reconstructed 4D χ dataspace. With finger-tapping experiments on a 7T system, the χICA-extracted χ-depicted functional map is similar to the SPM-inferred functional χ map by a spatial correlation of 0.67 ± 0.05. In comparison, the AICA-extracted magnitude-depicted map is correlated with the SPM magnitude map by 0.81 ± 0.05. The understanding of the inferiority of χICA to AICA for task-evoked functional map is an ongoing research topic. For task-evoked brain functional mapping, we compare the data-driven ICA method with the task-correlated SPM method. In particular, we compare χICA with AICA for extracting task-correlated timecourses and functional maps. χICA can extract a χ-depicted task-evoked brain functional map from a reconstructed χ dataspace without the knowledge about brain hemodynamic responses. The χICA-extracted brain functional χ map reveals a bidirectional BOLD response pattern that is unavailable (or different) from AICA. Copyright © 2016 Elsevier B.V. All rights reserved.

Decreased prefrontal functional brain response during memory testing in women with Cushing's syndrome in remission.

PubMed

Ragnarsson, Oskar; Stomby, Andreas; Dahlqvist, Per; Evang, Johan A; Ryberg, Mats; Olsson, Tommy; Bollerslev, Jens; Nyberg, Lars; Johannsson, Gudmundur

2017-08-01

Neurocognitive dysfunction is an important feature of Cushing's syndrome (CS). Our hypothesis was that patients with CS in remission have decreased functional brain responses in the prefrontal cortex and hippocampus during memory testing. In this cross-sectional study we included 19 women previously treated for CS and 19 controls matched for age, gender, and education. The median remission time was 7 (IQR 6-10) years. Brain activity was studied with functional magnetic resonance imaging during episodic- and working-memory tasks. The primary regions of interest were the prefrontal cortex and the hippocampus. A voxel-wise comparison of functional brain responses in patients and controls was performed. During episodic-memory encoding, patients displayed lower functional brain responses in the left and right prefrontal gyrus (p<0.001) and in the right inferior occipital gyrus (p<0.001) compared with controls. There was a trend towards lower functional brain responses in the left posterior hippocampus in patients (p=0.05). During episodic-memory retrieval, the patients displayed lower functional brain responses in several brain areas with the most predominant difference in the right prefrontal cortex (p<0.001). During the working memory task, patients had lower response in the prefrontal cortices bilaterally (p<0.005). Patients, but not controls, had lower functional brain response during a more complex working memory task compared with a simpler one. In conclusion, women with CS in long-term remission have reduced functional brain responses during episodic and working memory testing. This observation extends previous findings showing long-term adverse effects of severe hypercortisolaemia on brain function. Copyright © 2017 Elsevier Ltd. All rights reserved.

Susceptibility-based functional brain mapping by 3D deconvolution of an MR-phase activation map.

PubMed

Chen, Zikuan; Liu, Jingyu; Calhoun, Vince D

2013-05-30

The underlying source of T2*-weighted magnetic resonance imaging (T2*MRI) for brain imaging is magnetic susceptibility (denoted by χ). T2*MRI outputs a complex-valued MR image consisting of magnitude and phase information. Recent research has shown that both the magnitude and the phase images are morphologically different from the source χ, primarily due to 3D convolution, and that the source χ can be reconstructed from complex MR images by computed inverse MRI (CIMRI). Thus, we can obtain a 4D χ dataset from a complex 4D MR dataset acquired from a brain functional MRI study by repeating CIMRI to reconstruct 3D χ volumes at each timepoint. Because the reconstructed χ is a more direct representation of neuronal activity than the MR image, we propose a method for χ-based functional brain mapping, which is numerically characterised by a temporal correlation map of χ responses to a stimulant task. Under the linear imaging conditions used for T2*MRI, we show that the χ activation map can be calculated from the MR phase map by CIMRI. We validate our approach using numerical simulations and Gd-phantom experiments. We also analyse real data from a finger-tapping visuomotor experiment and show that the χ-based functional mapping provides additional activation details (in the form of positive and negative correlation patterns) beyond those generated by conventional MR-magnitude-based mapping. Copyright © 2013 Elsevier B.V. All rights reserved.

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

Brain functional network abnormality extends beyond the sensorimotor network in brachial plexus injury patients.

PubMed

Feng, Jun-Tao; Liu, Han-Qiu; Hua, Xu-Yun; Gu, Yu-Dong; Xu, Jian-Guang; Xu, Wen-Dong

2016-12-01

Brachial plexus injury (BPI) is a type of severe peripheral nerve trauma that leads to central remodeling in the brain, as revealed by functional MRI analysis. However, previously reported remodeling is mostly restricted to sensorimotor areas of the brain. Whether this disturbance in the sensorimotor network leads to larger-scale functional remodeling remains unknown. We sought to explore the higher-level brain functional abnormality pattern of BPI patients from a large-scale network function connectivity dimension in 15 right-handed BPI patients. Resting-state functional MRI data were collected and analyzed using independent component analysis methods. Five components of interest were recognized and compared between patients and healthy subjects. Patients showed significantly altered brain local functional activities in the bilateral fronto-parietal network (FPN), sensorimotor network (SMN), and executive-control network (ECN) compared with healthy subjects. Moreover, functional connectivity between SMN and ECN were significantly less in patients compared with healthy subjects, and connectivity strength between ECN and SMN was negatively correlated with patients' residual function of the affected limb. Functional connectivity between SMN and right FPN were also significantly less than in controls, although connectivity between ECN and default mode network (DMN) was greater than in controls. These data suggested that brain functional disturbance in BPI patients extends beyond the sensorimotor network and cascades serial remodeling in the brain, which significantly correlates with residual hand function of the paralyzed limb. Furthermore, functional remodeling in these higher-level functional networks may lead to cognitive alterations in complex tasks.

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.

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.

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.

Microfluidic neurite guidance to study structure-function relationships in topologically-complex population-based neural networks.

PubMed

Honegger, Thibault; Thielen, Moritz I; Feizi, Soheil; Sanjana, Neville E; Voldman, Joel

2016-06-22

The central nervous system is a dense, layered, 3D interconnected network of populations of neurons, and thus recapitulating that complexity for in vitro CNS models requires methods that can create defined topologically-complex neuronal networks. Several three-dimensional patterning approaches have been developed but none have demonstrated the ability to control the connections between populations of neurons. Here we report a method using AC electrokinetic forces that can guide, accelerate, slow down and push up neurites in un-modified collagen scaffolds. We present a means to create in vitro neural networks of arbitrary complexity by using such forces to create 3D intersections of primary neuronal populations that are plated in a 2D plane. We report for the first time in vitro basic brain motifs that have been previously observed in vivo and show that their functional network is highly decorrelated to their structure. This platform can provide building blocks to reproduce in vitro the complexity of neural circuits and provide a minimalistic environment to study the structure-function relationship of the brain circuitry.

Microfluidic neurite guidance to study structure-function relationships in topologically-complex population-based neural networks

NASA Astrophysics Data System (ADS)

Honegger, Thibault; Thielen, Moritz I.; Feizi, Soheil; Sanjana, Neville E.; Voldman, Joel

2016-06-01

The central nervous system is a dense, layered, 3D interconnected network of populations of neurons, and thus recapitulating that complexity for in vitro CNS models requires methods that can create defined topologically-complex neuronal networks. Several three-dimensional patterning approaches have been developed but none have demonstrated the ability to control the connections between populations of neurons. Here we report a method using AC electrokinetic forces that can guide, accelerate, slow down and push up neurites in un-modified collagen scaffolds. We present a means to create in vitro neural networks of arbitrary complexity by using such forces to create 3D intersections of primary neuronal populations that are plated in a 2D plane. We report for the first time in vitro basic brain motifs that have been previously observed in vivo and show that their functional network is highly decorrelated to their structure. This platform can provide building blocks to reproduce in vitro the complexity of neural circuits and provide a minimalistic environment to study the structure-function relationship of the brain circuitry.

Homological scaffolds of brain functional networks

PubMed Central

Petri, G.; Expert, P.; Turkheimer, F.; Carhart-Harris, R.; Nutt, D.; Hellyer, P. J.; Vaccarino, F.

2014-01-01

Networks, as efficient representations of complex systems, have appealed to scientists for a long time and now permeate many areas of science, including neuroimaging (Bullmore and Sporns 2009 Nat. Rev. Neurosci. 10, 186–198. (doi:10.1038/nrn2618)). Traditionally, the structure of complex networks has been studied through their statistical properties and metrics concerned with node and link properties, e.g. degree-distribution, node centrality and modularity. Here, we study the characteristics of functional brain networks at the mesoscopic level from a novel perspective that highlights the role of inhomogeneities in the fabric of functional connections. This can be done by focusing on the features of a set of topological objects—homological cycles—associated with the weighted functional network. We leverage the detected topological information to define the homological scaffolds, a new set of objects designed to represent compactly the homological features of the correlation network and simultaneously make their homological properties amenable to networks theoretical methods. As a proof of principle, we apply these tools to compare resting-state functional brain activity in 15 healthy volunteers after intravenous infusion of placebo and psilocybin—the main psychoactive component of magic mushrooms. The results show that the homological structure of the brain's functional patterns undergoes a dramatic change post-psilocybin, characterized by the appearance of many transient structures of low stability and of a small number of persistent ones that are not observed in the case of placebo. PMID:25401177

Neuroscience in its context. Neuroscience and psychology in the work of Wilhelm Wundt.

PubMed

Ziche, P

1999-01-01

Wilhelm Wundt (1832-1920), the first to establish an Institute devoted exclusively to psychological research in Germany, started his career as a (neuro)physiologist. He gradually turned into a psychologist in the 1860's and 1870's, at a time when neuroscience had to deal with the problem of giving an adequate physiological interpretation of the data accumulated by neuroanatomy. Neither the functional interpretation of brain morphology, nor the options provided by the reflex model seemed acceptable to Wundt. In his Physiological Psychology, first published in 1874, Wundt adds another aspect to this discussion by showing that psychology may help, and indeed is required, to clarify some of the most controversial problems in brain research. He thus became a key figure in neuroscience's struggle to locate itself within the various research traditions. The following theses will be argued for: 1. Wundt's turn to psychology resulted from his view that the methodological basis of physiological brain research of the time was unsatisfactory. 2. Psychology, in its attempt to solve these problems, implied a new conception of an interaction between experimental and theoretical brain research. 3. Wundt tried to demonstrate the necessity of psychological considerations for experimental brain research. These points are discussed with reference to Wundt's treatment of the localization of functions in the brain. According to Wundt, psychology can show, by analyzing the complex structure of intellect and will, that mental phenomena can be realized in the brain only in the form of complex interations of the elements of the brain. The results of the psychological considerations imply that a strict localizations cannot be correct; but they are also turned against the conception of a complete functional equivalence of the various parts of the cortext. For Wundt, a reconstruction of brain processes cannot start with neurones, but only with patterns of a functional organization of brain activity. Wundt accordingly proposes a functional interpretation on the level of the physiology of nervous tissue as well as for the over-all organization of the brain.

A review of structural and functional brain networks: small world and atlas.

PubMed

Yao, Zhijun; Hu, Bin; Xie, Yuanwei; Moore, Philip; Zheng, Jiaxiang

2015-03-01

Brain networks can be divided into two categories: structural and functional networks. Many studies of neuroscience have reported that the complex brain networks are characterized by small-world or scale-free properties. The identification of nodes is the key factor in studying the properties of networks on the macro-, micro- or mesoscale in both structural and functional networks. In the study of brain networks, nodes are always determined by atlases. Therefore, the selection of atlases is critical, and appropriate atlases are helpful to combine the analyses of structural and functional networks. Currently, some problems still exist in the establishment or usage of atlases, which are often caused by the segmentation or the parcellation of the brain. We suggest that quantification of brain networks might be affected by the selection of atlases to a large extent. In the process of building atlases, the influences of single subjects and groups should be balanced. In this article, we focused on the effects of atlases on the analysis of brain networks and the improved divisions based on the tractography or connectivity in the parcellation of atlases.

Non-invasive Brain Stimulation: Probing Intracortical Circuits and Improving Cognition in the Aging Brain

PubMed Central

Gomes-Osman, Joyce; Indahlastari, Aprinda; Fried, Peter J.; Cabral, Danylo L. F.; Rice, Jordyn; Nissim, Nicole R.; Aksu, Serkan; McLaren, Molly E.; Woods, Adam J.

2018-01-01

The impact of cognitive aging on brain function and structure is complex, and the relationship between aging-related structural changes and cognitive function are not fully understood. Physiological and pathological changes to the aging brain are highly variable, making it difficult to estimate a cognitive trajectory with which to monitor the conversion to cognitive decline. Beyond the information on the structural and functional consequences of cognitive aging gained from brain imaging and neuropsychological studies, non-invasive brain stimulation techniques such as transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) can enable stimulation of the human brain in vivo, offering useful insights into the functional integrity of intracortical circuits using electrophysiology and neuromodulation. TMS measurements can be used to identify and monitor changes in cortical reactivity, the integrity of inhibitory and excitatory intracortical circuits, the mechanisms of long-term potentiation (LTP)/depression-like plasticity and central cholinergic function. Repetitive TMS and tDCS can be used to modulate neuronal excitability and enhance cortical function, and thus offer a potential means to slow or reverse cognitive decline. This review will summarize and critically appraise relevant literature regarding the use of TMS and tDCS to probe cortical areas affected by the aging brain, and as potential therapeutic tools to improve cognitive function in the aging population. Challenges arising from intra-individual differences, limited reproducibility, and methodological differences will be discussed.

Big words, halved brains and small worlds: complex brain networks of figurative language comprehension.

PubMed

Arzouan, Yossi; Solomon, Sorin; Faust, Miriam; Goldstein, Abraham

2011-04-27

Language comprehension is a complex task that involves a wide network of brain regions. We used topological measures to qualify and quantify the functional connectivity of the networks used under various comprehension conditions. To that aim we developed a technique to represent functional networks based on EEG recordings, taking advantage of their excellent time resolution in order to capture the fast processes that occur during language comprehension. Networks were created by searching for a specific causal relation between areas, the negative feedback loop, which is ubiquitous in many systems. This method is a simple way to construct directed graphs using event-related activity, which can then be analyzed topologically. Brain activity was recorded while subjects read expressions of various types and indicated whether they found them meaningful. Slightly different functional networks were obtained for event-related activity evoked by each expression type. The differences reflect the special contribution of specific regions in each condition and the balance of hemispheric activity involved in comprehending different types of expressions and are consistent with the literature in the field. Our results indicate that representing event-related brain activity as a network using a simple temporal relation, such as the negative feedback loop, to indicate directional connectivity is a viable option for investigation which also derives new information about aspects not reflected in the classical methods for investigating brain activity.

Glial-Specific Functions of Microcephaly Protein WDR62 and Interaction with the Mitotic Kinase AURKA Are Essential for Drosophila Brain Growth.

PubMed

Lim, Nicholas R; Shohayeb, Belal; Zaytseva, Olga; Mitchell, Naomi; Millard, S Sean; Ng, Dominic C H; Quinn, Leonie M

2017-07-11

The second most commonly mutated gene in primary microcephaly (MCPH) patients is wd40-repeat protein 62 (wdr62), but the relative contribution of WDR62 function to the growth of major brain lineages is unknown. Here, we use Drosophila models to dissect lineage-specific WDR62 function(s). Interestingly, although neural stem cell (neuroblast)-specific depletion of WDR62 significantly decreased neuroblast number, brain size was unchanged. In contrast, glial lineage-specific WDR62 depletion significantly decreased brain volume. Moreover, loss of function in glia not only decreased the glial population but also non-autonomously caused neuroblast loss. We further demonstrated that WDR62 controls brain growth through lineage-specific interactions with master mitotic signaling kinase, AURKA. Depletion of AURKA in neuroblasts drives brain overgrowth, which was suppressed by WDR62 co-depletion. In contrast, glial-specific depletion of AURKA significantly decreased brain volume, which was further decreased by WDR62 co-depletion. Thus, dissecting relative contributions of MCPH factors to individual neural lineages will be critical for understanding complex diseases such as microcephaly. Crown Copyright © 2017. Published by Elsevier Inc. All rights reserved.

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…

Large-Scale Network Analysis of Whole-Brain Resting-State Functional Connectivity in Spinal Cord Injury: A Comparative Study.

PubMed

Kaushal, Mayank; Oni-Orisan, Akinwunmi; Chen, Gang; Li, Wenjun; Leschke, Jack; Ward, Doug; Kalinosky, Benjamin; Budde, Matthew; Schmit, Brian; Li, Shi-Jiang; Muqeet, Vaishnavi; Kurpad, Shekar

2017-09-01

Network analysis based on graph theory depicts the brain as a complex network that allows inspection of overall brain connectivity pattern and calculation of quantifiable network metrics. To date, large-scale network analysis has not been applied to resting-state functional networks in complete spinal cord injury (SCI) patients. To characterize modular reorganization of whole brain into constituent nodes and compare network metrics between SCI and control subjects, fifteen subjects with chronic complete cervical SCI and 15 neurologically intact controls were scanned. The data were preprocessed followed by parcellation of the brain into 116 regions of interest (ROI). Correlation analysis was performed between every ROI pair to construct connectivity matrices and ROIs were categorized into distinct modules. Subsequently, local efficiency (LE) and global efficiency (GE) network metrics were calculated at incremental cost thresholds. The application of a modularity algorithm organized the whole-brain resting-state functional network of the SCI and the control subjects into nine and seven modules, respectively. The individual modules differed across groups in terms of the number and the composition of constituent nodes. LE demonstrated statistically significant decrease at multiple cost levels in SCI subjects. GE did not differ significantly between the two groups. The demonstration of modular architecture in both groups highlights the applicability of large-scale network analysis in studying complex brain networks. Comparing modules across groups revealed differences in number and membership of constituent nodes, indicating modular reorganization due to neural plasticity.

The Vertebrate Brain, Evidence of Its Modular Organization and Operating System: Insights into the Brain's Basic Units of Structure, Function, and Operation and How They Influence Neuronal Signaling and Behavior.

PubMed

Baslow, Morris H

2011-01-01

The human brain is a complex organ made up of neurons and several other cell types, and whose role is processing information for use in eliciting behaviors. However, the composition of its repeating cellular units for both structure and function are unresolved. Based on recent descriptions of the brain's physiological "operating system", a function of the tri-cellular metabolism of N-acetylaspartate (NAA) and N-acetylaspartylglutamate (NAAG) for supply of energy, and on the nature of "neuronal words and languages" for intercellular communication, insights into the brain's modular structural and functional units have been gained. In this article, it is proposed that the basic structural unit in brain is defined by its physiological operating system, and that it consists of a single neuron, and one or more astrocytes, oligodendrocytes, and vascular system endothelial cells. It is also proposed that the basic functional unit in the brain is defined by how neurons communicate, and consists of two neurons and their interconnecting dendritic-synaptic-dendritic field. Since a functional unit is composed of two neurons, it requires two structural units to form a functional unit. Thus, the brain can be envisioned as being made up of the three-dimensional stacking and intertwining of myriad structural units which results not only in its gross structure, but also in producing a uniform distribution of binary functional units. Since the physiological NAA-NAAG operating system for supply of energy is repeated in every structural unit, it is positioned to control global brain function.

Functional brain networks in Alzheimer's disease: EEG analysis based on limited penetrable visibility graph and phase space method

NASA Astrophysics Data System (ADS)

Wang, Jiang; Yang, Chen; Wang, Ruofan; Yu, Haitao; Cao, Yibin; Liu, Jing

2016-10-01

In this paper, EEG series are applied to construct functional connections with the correlation between different regions in order to investigate the nonlinear characteristic and the cognitive function of the brain with Alzheimer's disease (AD). First, limited penetrable visibility graph (LPVG) and phase space method map single EEG series into networks, and investigate the underlying chaotic system dynamics of AD brain. Topological properties of the networks are extracted, such as average path length and clustering coefficient. It is found that the network topology of AD in several local brain regions are different from that of the control group with no statistically significant difference existing all over the brain. Furthermore, in order to detect the abnormality of AD brain as a whole, functional connections among different brain regions are reconstructed based on similarity of clustering coefficient sequence (CCSS) of EEG series in the four frequency bands (delta, theta, alpha, and beta), which exhibit obvious small-world properties. Graph analysis demonstrates that for both methodologies, the functional connections between regions of AD brain decrease, particularly in the alpha frequency band. AD causes the graph index complexity of the functional network decreased, the small-world properties weakened, and the vulnerability increased. The obtained results show that the brain functional network constructed by LPVG and phase space method might be more effective to distinguish AD from the normal control than the analysis of single series, which is helpful for revealing the underlying pathological mechanism of the disease.

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.

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

Structural bases for neurophysiological investigations of amygdaloid complex of the brain

NASA Astrophysics Data System (ADS)

Kalimullina, Liliya B.; Kalkamanov, Kh. A.; Akhmadeev, Azat V.; Zakharov, Vadim P.; Sharafullin, Ildus F.

2015-11-01

Amygdala (Am) as a part of limbic system of the brain defines such important functions as adaptive behavior of animals, formation of emotions and memory, regulation of endocrine and visceral functions. We worked out, with the help of mathematic modelling of the pattern recognition theory, principles for organization of neurophysiological and neuromorphological studies of Am nuclei, which take into account the existing heterogeneity of its formations and optimize, to a great extent, the protocol for carrying out of such investigations. The given scheme of studies of Am’s structural-functional organization at its highly-informative sections can be used as a guide for precise placement of electrodes’, cannulae’s and microsensors into particular Am nucleus in the brain with the registration not only the nucleus itself, but also its extensions. This information is also important for defining the number of slices covering specific Am nuclei which must be investigated to reveal the physiological role of a particular part of amygdaloid complex.

Default network connectivity decodes brain states with simulated microgravity.

PubMed

Zeng, Ling-Li; Liao, Yang; Zhou, Zongtan; Shen, Hui; Liu, Yadong; Liu, Xufeng; Hu, Dewen

2016-04-01

With great progress of space navigation technology, it becomes possible to travel beyond Earth's gravity. So far, it remains unclear whether the human brain can function normally within an environment of microgravity and confinement. Particularly, it is a challenge to figure out some neuroimaging-based markers for rapid screening diagnosis of disrupted brain function in microgravity environment. In this study, a 7-day -6° head down tilt bed rest experiment was used to simulate the microgravity, and twenty healthy male participants underwent resting-state functional magnetic resonance imaging scans at baseline and after the simulated microgravity experiment. We used a multivariate pattern analysis approach to distinguish the brain states with simulated microgravity from normal gravity based on the functional connectivity within the default network, resulting in an accuracy of no less than 85 % via cross-validation. Moreover, most discriminative functional connections were mainly located between the limbic system and cortical areas and were enhanced after simulated microgravity, implying a self-adaption or compensatory enhancement to fulfill the need of complex demand in spatial navigation and motor control functions in microgravity environment. Overall, the findings suggest that the brain states in microgravity are likely different from those in normal gravity and that brain connectome could act as a biomarker to indicate the brain state in microgravity.

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

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

Directionality analysis on functional magnetic resonance imaging during motor task using Granger causality.

PubMed

Anwar, A R; Muthalib, M; Perrey, S; Galka, A; Granert, O; Wolff, S; Deuschl, G; Raethjen, J; Heute, U; Muthuraman, M

2012-01-01

Directionality analysis of signals originating from different parts of brain during motor tasks has gained a lot of interest. Since brain activity can be recorded over time, methods of time series analysis can be applied to medical time series as well. Granger Causality is a method to find a causal relationship between time series. Such causality can be referred to as a directional connection and is not necessarily bidirectional. The aim of this study is to differentiate between different motor tasks on the basis of activation maps and also to understand the nature of connections present between different parts of the brain. In this paper, three different motor tasks (finger tapping, simple finger sequencing, and complex finger sequencing) are analyzed. Time series for each task were extracted from functional magnetic resonance imaging (fMRI) data, which have a very good spatial resolution and can look into the sub-cortical regions of the brain. Activation maps based on fMRI images show that, in case of complex finger sequencing, most parts of the brain are active, unlike finger tapping during which only limited regions show activity. Directionality analysis on time series extracted from contralateral motor cortex (CMC), supplementary motor area (SMA), and cerebellum (CER) show bidirectional connections between these parts of the brain. In case of simple finger sequencing and complex finger sequencing, the strongest connections originate from SMA and CMC, while connections originating from CER in either direction are the weakest ones in magnitude during all paradigms.

Intracellular Transport and Kinesin Superfamily Proteins: Structure, Function and Dynamics

NASA Astrophysics Data System (ADS)

Hirokawa, N.; Takemura, R.

Using various molecular cell biological and molecular genetic approaches, we identified kinesin superfamily proteins (KIFs) and characterized their significant functions in intracellular transport, which is fundamental for cellular morphogenesis, functioning, and survival. We showed that KIFs not only transport various membranous organelles, proteins complexes and mRNAs fundamental for cellular functions but also play significant roles in higher brain functions such as memory and learning, determination of important developmental processes such as left-right asymmetry formation and brain wiring. We also elucidated that KIFs recognize and bind to their specific cargoes using scaffolding or adaptor protein complexes. Concerning the mechanism of motility, we discovered the simplest unique monomeric motor KIF1A and determined by molecular biophysics, cryoelectron microscopy and X-ray crystallography that KIF1A can move on a microtubule processively as a monomer by biased Brownian motion and by hydolyzing ATP.

INVESTIGATING DIFFERENCES IN BRAIN FUNCTIONAL NETWORKS USING HIERARCHICAL COVARIATE-ADJUSTED INDEPENDENT COMPONENT ANALYSIS.

PubMed

Shi, Ran; Guo, Ying

2016-12-01

Human brains perform tasks via complex functional networks consisting of separated brain regions. A popular approach to characterize brain functional networks in fMRI studies is independent component analysis (ICA), which is a powerful method to reconstruct latent source signals from their linear mixtures. In many fMRI studies, an important goal is to investigate how brain functional networks change according to specific clinical and demographic variabilities. Existing ICA methods, however, cannot directly incorporate covariate effects in ICA decomposition. Heuristic post-ICA analysis to address this need can be inaccurate and inefficient. In this paper, we propose a hierarchical covariate-adjusted ICA (hc-ICA) model that provides a formal statistical framework for estimating covariate effects and testing differences between brain functional networks. Our method provides a more reliable and powerful statistical tool for evaluating group differences in brain functional networks while appropriately controlling for potential confounding factors. We present an analytically tractable EM algorithm to obtain maximum likelihood estimates of our model. We also develop a subspace-based approximate EM that runs significantly faster while retaining high accuracy. To test the differences in functional networks, we introduce a voxel-wise approximate inference procedure which eliminates the need of computationally expensive covariance matrix estimation and inversion. We demonstrate the advantages of our methods over the existing method via simulation studies. We apply our method to an fMRI study to investigate differences in brain functional networks associated with post-traumatic stress disorder (PTSD).

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.

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.

Brain architecture and social complexity in modern and ancient birds.

PubMed

Burish, Mark J; Kueh, Hao Yuan; Wang, Samuel S-H

2004-01-01

Vertebrate brains vary tremendously in size, but differences in form are more subtle. To bring out functional contrasts that are independent of absolute size, we have normalized brain component sizes to whole brain volume. The set of such volume fractions is the cerebrotype of a species. Using this approach in mammals we previously identified specific associations between cerebrotype and behavioral specializations. Among primates, cerebrotypes are linked principally to enlargement of the cerebral cortex and are associated with increases in the complexity of social structure. Here we extend this analysis to include a second major vertebrate group, the birds. In birds the telencephalic volume fraction is strongly correlated with social complexity. This correlation accounts for almost half of the observed variation in telencephalic size, more than any other behavioral specialization examined, including the ability to learn song. A prominent exception to this pattern is owls, which are not social but still have very large forebrains. Interpolating the overall correlation for Archaeopteryx, an ancient bird, suggests that its social complexity was likely to have been on a par with modern domesticated chickens. Telencephalic volume fraction outperforms residuals-based measures of brain size at separating birds by social structure. Telencephalic volume fraction may be an anatomical substrate for social complexity, and perhaps cognitive ability, that can be generalized across a range of vertebrate brains, including dinosaurs. Copyright 2004 S. Karger AG, Basel

Nutritional Factors Affecting Adult Neurogenesis and Cognitive Function

USDA-ARS?s Scientific Manuscript database

Adult neurogenesis, a complex process by which stem cells in the hippocampal brain region differentiate and proliferate into new neurons and other resident brain cells, is known to be affected by many intrinsic and extrinsic factors, including diet. Neurogenesis plays a critical role in neural plas...

Global loss of acetylcholinesterase activity with mitochondrial complexes inhibition and inflammation in brain of hypercholesterolemic mice.

PubMed

Paul, Rajib; Borah, Anupom

2017-12-20

There exists an intricate relationship between hypercholesterolemia (elevated plasma cholesterol) and brain functions. The present study aims to understand the impact of hypercholesterolemia on pathological consequences in mouse brain. A chronic mouse model of hypercholesterolemia was induced by giving high-cholesterol diet for 12 weeks. The hypercholesterolemic mice developed cognitive impairment as evident from object recognition memory test. Cholesterol accumulation was observed in four discrete brain regions, such as cortex, striatum, hippocampus and substantia nigra along with significantly damaged blood-brain barrier by hypercholesterolemia. The crucial finding is the loss of acetylcholinesterase activity with mitochondrial dysfunction globally in the brain of hypercholesterolemic mice, which is related to the levels of cholesterol. Moreover, the levels of hydroxyl radical were elevated in the regions of brain where the activity of mitochondrial complexes was found to be reduced. Intriguingly, elevations of inflammatory stress markers in the cholesterol-rich brain regions were observed. As cognitive impairment, diminished brain acetylcholinesterase activity, mitochondrial dysfunctions, and inflammation are the prima facie pathologies of neurodegenerative diseases, the findings impose hypercholesterolemia as potential risk factor towards brain dysfunction.

Brain Signature Characterizing the Body-Brain-Mind Axis of Transsexuals

PubMed Central

Chao, Hsiang-Tai; Tu, Pei-Chi; Li, Cheng-Ta; Cheng, Chou-Ming; Su, Tung-Ping; Lee, Ying-Chiao; Hsieh, Jen-Chuen

2013-01-01

Individuals with gender identity disorder (GID), who are commonly referred to as transsexuals (TXs), are afflicted by negative psychosocial stressors. Central to the psychological complex of TXs is the conviction of belonging to the opposite sex. Neuroanatomical and functional brain imaging studies have demonstrated that the GID is associated with brain alterations. In this study, we found that TXs identify, when viewing male-female couples in erotic or non-erotic (“neutral”) interactions, with the couple member of the desired gender in both situations. By means of functional magnetic resonance imaging, we found that the TXs, as opposed to controls (CONs), displayed an increased functional connectivity between the ventral tegmental area, which is associated with dimorphic genital representation, and anterior cingulate cortex subregions, which play a key role in social exclusion, conflict monitoring and punishment adjustment. The neural connectivity pattern suggests a brain signature of the psychosocial distress for the gender-sex incongruity of TXs. PMID:23923023

Remodeling Functional Connectivity in Multiple Sclerosis: A Challenging Therapeutic Approach.

PubMed

Stampanoni Bassi, Mario; Gilio, Luana; Buttari, Fabio; Maffei, Pierpaolo; Marfia, Girolama A; Restivo, Domenico A; Centonze, Diego; Iezzi, Ennio

2017-01-01

Neurons in the central nervous system are organized in functional units interconnected to form complex networks. Acute and chronic brain damage disrupts brain connectivity producing neurological signs and/or symptoms. In several neurological diseases, particularly in Multiple Sclerosis (MS), structural imaging studies cannot always demonstrate a clear association between lesion site and clinical disability, originating the "clinico-radiological paradox." The discrepancy between structural damage and disability can be explained by a complex network perspective. Both brain networks architecture and synaptic plasticity may play important roles in modulating brain networks efficiency after brain damage. In particular, long-term potentiation (LTP) may occur in surviving neurons to compensate network disconnection. In MS, inflammatory cytokines dramatically interfere with synaptic transmission and plasticity. Importantly, in addition to acute and chronic structural damage, inflammation could contribute to reduce brain networks efficiency in MS leading to worse clinical recovery after a relapse and worse disease progression. These evidence suggest that removing inflammation should represent the main therapeutic target in MS; moreover, as synaptic plasticity is particularly altered by inflammation, specific strategies aimed at promoting LTP mechanisms could be effective for enhancing clinical recovery. Modulation of plasticity with different non-invasive brain stimulation (NIBS) techniques has been used to promote recovery of MS symptoms. Better knowledge of features inducing brain disconnection in MS is crucial to design specific strategies to promote recovery and use NIBS with an increasingly tailored approach.

Implantable fiber-optic interface for parallel multisite long-term optical dynamic brain interrogation in freely moving mice

PubMed Central

Doronina-Amitonova, L. V.; Fedotov, I. V.; Ivashkina, O. I.; Zots, M. A.; Fedotov, A. B.; Anokhin, K. V.; Zheltikov, A. M.

2013-01-01

Seeing the big picture of functional responses within large neural networks in a freely functioning brain is crucial for understanding the cellular mechanisms behind the higher nervous activity, including the most complex brain functions, such as cognition and memory. As a breakthrough toward meeting this challenge, implantable fiber-optic interfaces integrating advanced optogenetic technologies and cutting-edge fiber-optic solutions have been demonstrated, enabling a long-term optogenetic manipulation of neural circuits in freely moving mice. Here, we show that a specifically designed implantable fiber-optic interface provides a powerful tool for parallel long-term optical interrogation of distinctly separate, functionally different sites in the brain of freely moving mice. This interface allows the same groups of neurons lying deeply in the brain of a freely behaving mouse to be reproducibly accessed and optically interrogated over many weeks, providing a long-term dynamic detection of genome activity in response to a broad variety of pharmacological and physiological stimuli. PMID:24253232

Implantable fiber-optic interface for parallel multisite long-term optical dynamic brain interrogation in freely moving mice

NASA Astrophysics Data System (ADS)

Doronina-Amitonova, L. V.; Fedotov, I. V.; Ivashkina, O. I.; Zots, M. A.; Fedotov, A. B.; Anokhin, K. V.; Zheltikov, A. M.

2013-11-01

Seeing the big picture of functional responses within large neural networks in a freely functioning brain is crucial for understanding the cellular mechanisms behind the higher nervous activity, including the most complex brain functions, such as cognition and memory. As a breakthrough toward meeting this challenge, implantable fiber-optic interfaces integrating advanced optogenetic technologies and cutting-edge fiber-optic solutions have been demonstrated, enabling a long-term optogenetic manipulation of neural circuits in freely moving mice. Here, we show that a specifically designed implantable fiber-optic interface provides a powerful tool for parallel long-term optical interrogation of distinctly separate, functionally different sites in the brain of freely moving mice. This interface allows the same groups of neurons lying deeply in the brain of a freely behaving mouse to be reproducibly accessed and optically interrogated over many weeks, providing a long-term dynamic detection of genome activity in response to a broad variety of pharmacological and physiological stimuli.

Structure and function of complex brain networks

PubMed Central

Sporns, Olaf

2013-01-01

An increasing number of theoretical and empirical studies approach the function of the human brain from a network perspective. The analysis of brain networks is made feasible by the development of new imaging acquisition methods as well as new tools from graph theory and dynamical systems. This review surveys some of these methodological advances and summarizes recent findings on the architecture of structural and functional brain networks. Studies of the structural connectome reveal several modules or network communities that are interlinked by hub regions mediating communication processes between modules. Recent network analyses have shown that network hubs form a densely linked collective called a “rich club,” centrally positioned for attracting and dispersing signal traffic. In parallel, recordings of resting and task-evoked neural activity have revealed distinct resting-state networks that contribute to functions in distinct cognitive domains. Network methods are increasingly applied in a clinical context, and their promise for elucidating neural substrates of brain and mental disorders is discussed. PMID:24174898

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.

Finding the imposter: brain connectivity of lesions causing delusional misidentifications.

PubMed

Darby, R Ryan; Laganiere, Simon; Pascual-Leone, Alvaro; Prasad, Sashank; Fox, Michael D

2017-02-01

SEE MCKAY AND FURL DOI101093/AWW323 FOR A SCIENTIFIC COMMENTARY ON THIS ARTICLE: Focal brain injury can sometimes lead to bizarre symptoms, such as the delusion that a family member has been replaced by an imposter (Capgras syndrome). How a single brain lesion could cause such a complex disorder is unclear, leading many to speculate that concurrent delirium, psychiatric disease, dementia, or a second lesion is required. Here we instead propose that Capgras and other delusional misidentification syndromes arise from single lesions at unique locations within the human brain connectome. This hypothesis is motivated by evidence that symptoms emerge from sites functionally connected to a lesion location, not just the lesion location itself. First, 17 cases of lesion-induced delusional misidentifications were identified and lesion locations were mapped to a common brain atlas. Second, lesion network mapping was used to identify brain regions functionally connected to the lesion locations. Third, regions involved in familiarity perception and belief evaluation, two processes thought to be abnormal in delusional misidentifications, were identified using meta-analyses of previous functional magnetic resonance imaging studies. We found that all 17 lesion locations were functionally connected to the left retrosplenial cortex, the region most activated in functional magnetic resonance imaging studies of familiarity. Similarly, 16 of 17 lesion locations were functionally connected to the right frontal cortex, the region most activated in functional magnetic resonance imaging studies of expectation violation, a component of belief evaluation. This connectivity pattern was highly specific for delusional misidentifications compared to four other lesion-induced neurological syndromes (P < 0.0001). Finally, 15 lesions causing other types of delusions were connected to expectation violation (P < 0.0001) but not familiarity regions, demonstrating specificity for delusion content. Our results provide potential neuroanatomical correlates for impaired familiarity perception and belief evaluation in patients with delusional misidentifications. More generally, we demonstrate a mechanism by which a single lesion can cause a complex neuropsychiatric syndrome based on that lesion's unique pattern of functional connectivity, without the need for pre-existing or hidden pathology. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Fractality of sensations and the brain health: the theory linking neurodegenerative disorder with distortion of spatial and temporal scale-invariance and fractal complexity of the visible world

PubMed Central

Zueva, Marina V.

2015-01-01

The theory that ties normal functioning and pathology of the brain and visual system with the spatial–temporal structure of the visual and other sensory stimuli is described for the first time in the present study. The deficit of fractal complexity of environmental influences can lead to the distortion of fractal complexity in the visual pathways of the brain and abnormalities of development or aging. The use of fractal light stimuli and fractal stimuli of other modalities can help to restore the functions of the brain, particularly in the elderly and in patients with neurodegenerative disorders or amblyopia. Non-linear dynamics of these physiological processes have a strong base of evidence, which is seen in the impaired fractal regulation of rhythmic activity in aged and diseased brains. From birth to old age, we live in a non-linear world, in which objects and processes with the properties of fractality and non-linearity surround us. Against this background, the evolution of man took place and all periods of life unfolded. Works of art created by man may also have fractal properties. The positive influence of music on cognitive functions is well-known. Insufficiency of sensory experience is believed to play a crucial role in the pathogenesis of amblyopia and age-dependent diseases. The brain is very plastic in its early development, and the plasticity decreases throughout life. However, several studies showed the possibility to reactivate the adult’s neuroplasticity in a variety of ways. We propose that a non-linear structure of sensory information on many spatial and temporal scales is crucial to the brain health and fractal regulation of physiological rhythms. Theoretical substantiation of the author’s theory is presented. Possible applications and the future research that can experimentally confirm or refute the theoretical concept are considered. PMID:26236232

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

PubMed

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

2011-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Laser technique for anatomical-functional study of the medial prefrontal cortex of the brain

NASA Astrophysics Data System (ADS)

Sanchez-Huerta, Laura; Hernandez, Adan; Ayala, Griselda; Marroquin, Javier; Silva, Adriana B.; Khotiaintsev, Konstantin S.; Svirid, Vladimir A.; Flores, Gonzalo; Khotiaintsev, Sergei N.

1999-05-01

The brain represents one of the most complex systems that we know yet. In its study, non-destructive methods -- in particular, behavioral studies play an important role. By alteration of brain functioning (e.g. by pharmacological means) and observation of consequent behavior changes an important information on brain organization and functioning is obtained. For inducing local alterations, permanent brain lesions are employed. However, for correct results this technique has to be quasi-non-destructive, i.e. not to affect the normal brain function. Hence, the lesions should be very small, accurate and applied precisely over the structure (e.g. the brain nucleus) of interest. These specifications are difficult to meet with the existing techniques for brain lesions -- specifically, neurotoxical, mechanical and electrical means because they result in too extensive damage. In this paper, we present new laser technique for quasi-non- destructive anatomical-functional mapping in vivo of the medial prefrontal cortex (MPFC) of the rat. The technique is based on producing of small-size, well-controlled laser- induced lesions over some areas of the MPFC. The anesthetized animals are subjected to stereotactic surgery and certain points of the MPFC are exposed the confined radiation of the 10 W cw CO2 laser. Subsequent behavioral changes observed in neonatal and adult animals as well as histological data prove effectiveness of this technology for anatomical- functional studies of the brain by areas, and as a treatment method for some pathologies.

Multimodal Brain Imaging in Autism Spectrum Disorder and the Promise of Twin Research

ERIC Educational Resources Information Center

Mevel, Katell; Fransson, Peter; Bölte, Sven

2015-01-01

Current evidence suggests the phenotype of autism spectrum disorder to be driven by a complex interaction of genetic and environmental factors impacting onto brain maturation, synaptic function, and cortical networks. However, findings are heterogeneous, and the exact neurobiological pathways of autism spectrum disorder still remain poorly…

The Characterization of Brain Behavior Relationships via Cognitive Neuroinformatic Approaches

ERIC Educational Resources Information Center

Kalar, Donald James, II

2009-01-01

The scope, breadth, and volume of data characterizing our current understanding of how the brain functions is growing at an increasingly rapid pace. What is more, theories are becoming increasing complex and nuanced, integrating knowledge from multiple previously independent sources of scientific inquiry. The research described within this…

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

The Vertebrate Brain, Evidence of Its Modular Organization and Operating System: Insights into the Brain's Basic Units of Structure, Function, and Operation and How They Influence Neuronal Signaling and Behavior

PubMed Central

Baslow, Morris H.

2011-01-01

The human brain is a complex organ made up of neurons and several other cell types, and whose role is processing information for use in eliciting behaviors. However, the composition of its repeating cellular units for both structure and function are unresolved. Based on recent descriptions of the brain's physiological “operating system”, a function of the tri-cellular metabolism of N-acetylaspartate (NAA) and N-acetylaspartylglutamate (NAAG) for supply of energy, and on the nature of “neuronal words and languages” for intercellular communication, insights into the brain's modular structural and functional units have been gained. In this article, it is proposed that the basic structural unit in brain is defined by its physiological operating system, and that it consists of a single neuron, and one or more astrocytes, oligodendrocytes, and vascular system endothelial cells. It is also proposed that the basic functional unit in the brain is defined by how neurons communicate, and consists of two neurons and their interconnecting dendritic–synaptic–dendritic field. Since a functional unit is composed of two neurons, it requires two structural units to form a functional unit. Thus, the brain can be envisioned as being made up of the three-dimensional stacking and intertwining of myriad structural units which results not only in its gross structure, but also in producing a uniform distribution of binary functional units. Since the physiological NAA–NAAG operating system for supply of energy is repeated in every structural unit, it is positioned to control global brain function. PMID:21720525

Towards systemic theories in biological psychiatry.

PubMed

Bender, W; Albus, M; Möller, H-J; Tretter, F

2006-02-01

Although still rather controversial, empirical data on the neurobiology of schizophrenia have reached a degree of complexity that makes it hard to obtain a coherent picture of the malfunctions of the brain in schizophrenia. Theoretical neuropsychiatry should therefore use the tools of theoretical sciences like cybernetics, informatics, computational neuroscience or systems science. The methodology of systems science permits the modeling of complex dynamic nonlinear systems. Such procedures might help us to understand brain functions and the disorders and actions of psychiatric drugs better.

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

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.

The role of lateral habenula-dorsal raphe nucleus circuits in higher brain functions and psychiatric illness.

PubMed

Zhao, Hua; Zhang, Bei-Lin; Yang, Shao-Jun; Rusak, Benjamin

2015-01-15

Serotonergic neurons in the dorsal raphe nucleus (DRN) play an important role in regulation of many physiological functions. The lateral nucleus of the habenular complex (LHb) is closely connected to the DRN both morphologically and functionally. The LHb is a key regulator of the activity of DRN serotonergic neurons, and it also receives reciprocal input from the DRN. The LHb is also a major way-station that receives limbic system input via the stria medullaris and provides output to the DRN and thereby indirectly connects a number of other brain regions to the DRN. The complex interactions of the LHb and DRN contribute to the regulation of numerous important behavioral and physiological mechanisms, including those regulating cognition, reward, pain sensitivity and patterns of sleep and waking. Disruption of these functions is characteristic of major psychiatric illnesses, so there has been a great deal of interest in how disturbed LHb-DRN interactions may contribute to the symptoms of these illnesses. This review summarizes recent research related to the roles of the LHb-DRN system in regulation of higher brain functions and the possible role of disturbed LHb-DRN function in the pathogenesis of psychiatric disorders, especially depression. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

Cliques of Neurons Bound into Cavities Provide a Missing Link between Structure and Function.

PubMed

Reimann, Michael W; Nolte, Max; Scolamiero, Martina; Turner, Katharine; Perin, Rodrigo; Chindemi, Giuseppe; Dłotko, Paweł; Levi, Ran; Hess, Kathryn; Markram, Henry

2017-01-01

The lack of a formal link between neural network structure and its emergent function has hampered our understanding of how the brain processes information. We have now come closer to describing such a link by taking the direction of synaptic transmission into account, constructing graphs of a network that reflect the direction of information flow, and analyzing these directed graphs using algebraic topology. Applying this approach to a local network of neurons in the neocortex revealed a remarkably intricate and previously unseen topology of synaptic connectivity. The synaptic network contains an abundance of cliques of neurons bound into cavities that guide the emergence of correlated activity. In response to stimuli, correlated activity binds synaptically connected neurons into functional cliques and cavities that evolve in a stereotypical sequence toward peak complexity. We propose that the brain processes stimuli by forming increasingly complex functional cliques and cavities.

Optical Imaging of Targeted β-Galactosidase in Brain Tumors to Detect EGFR Levels

PubMed Central

Broome, Ann-Marie; Ramamurthy, Gopal; Lavik, Kari; Liggett, Alexander; Kinstlinger, Ian; Basilion, James

2015-01-01

A current limitation in molecular imaging is that it often requires genetic manipulation of cancer cells for noninvasive imaging. Other methods to detect tumor cells in vivo using exogenously delivered and functionally active reporters, such as β-gal, are required. We report the development of a platform system for linking β-gal to any number of different ligands or antibodies for in vivo targeting to tissue or cells, without the requirement for genetic engineering of the target cells prior to imaging. Our studies demonstrate significant uptake in vitro and in vivo of an EGFR-targeted β-gal complex. We were then able to image orthotopic brain tumor accumulation and localization of the targeted enzyme when a fluorophore was added to the complex, as well as validate the internalization of the intravenously administered β-gal reporter complex ex vivo. After fluorescence imaging localized the β-gal complexes to the brain tumor, we topically applied a bioluminescent β-gal substrate to serial sections of the brain to evaluate the delivery and integrity of the enzyme. Finally, robust bioluminescence of the EGFR-targeted β-gal complex was captured within the tumor during noninvasive in vivo imaging. PMID:25775241

Optical imaging of targeted β-galactosidase in brain tumors to detect EGFR levels.

PubMed

Broome, Ann-Marie; Ramamurthy, Gopal; Lavik, Kari; Liggett, Alexander; Kinstlinger, Ian; Basilion, James

2015-04-15

A current limitation in molecular imaging is that it often requires genetic manipulation of cancer cells for noninvasive imaging. Other methods to detect tumor cells in vivo using exogenously delivered and functionally active reporters, such as β-gal, are required. We report the development of a platform system for linking β-gal to any number of different ligands or antibodies for in vivo targeting to tissue or cells, without the requirement for genetic engineering of the target cells prior to imaging. Our studies demonstrate significant uptake in vitro and in vivo of an EGFR-targeted β-gal complex. We were then able to image orthotopic brain tumor accumulation and localization of the targeted enzyme when a fluorophore was added to the complex, as well as validate the internalization of the intravenously administered β-gal reporter complex ex vivo. After fluorescence imaging localized the β-gal complexes to the brain tumor, we topically applied a bioluminescent β-gal substrate to serial sections of the brain to evaluate the delivery and integrity of the enzyme. Finally, robust bioluminescence of the EGFR-targeted β-gal complex was captured within the tumor during noninvasive in vivo imaging.

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

PubMed Central

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

2016-01-01

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

Thinking, Walking, Talking: Integratory Motor and Cognitive Brain Function

PubMed Central

Leisman, Gerry; Moustafa, Ahmed A.; Shafir, Tal

2016-01-01

In this article, we argue that motor and cognitive processes are functionally related and most likely share a similar evolutionary history. This is supported by clinical and neural data showing that some brain regions integrate both motor and cognitive functions. In addition, we also argue that cognitive processes coincide with complex motor output. Further, we also review data that support the converse notion that motor processes can contribute to cognitive function, as found by many rehabilitation and aerobic exercise training programs. Support is provided for motor and cognitive processes possessing dynamic bidirectional influences on each other. PMID:27252937

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.

Changes in functional connectivity within the fronto-temporal brain network induced by regular and irregular Russian verb production

PubMed Central

Kireev, Maxim; Slioussar, Natalia; Korotkov, Alexander D.; Chernigovskaya, Tatiana V.; Medvedev, Svyatoslav V.

2015-01-01

Functional connectivity between brain areas involved in the processing of complex language forms remains largely unexplored. Contributing to the debate about neural mechanisms underlying regular and irregular inflectional morphology processing in the mental lexicon, we conducted an fMRI experiment in which participants generated forms from different types of Russian verbs and nouns as well as from nonce stimuli. The data were subjected to a whole brain voxel-wise analysis of context dependent changes in functional connectivity [the so-called psychophysiological interaction (PPI) analysis]. Unlike previously reported subtractive results that reveal functional segregation between brain areas, PPI provides complementary information showing how these areas are functionally integrated in a particular task. To date, PPI evidence on inflectional morphology has been scarce and only available for inflectionally impoverished English verbs in a same-different judgment task. Using PPI here in conjunction with a production task in an inflectionally rich language, we found that functional connectivity between the left inferior frontal gyrus (LIFG) and bilateral superior temporal gyri (STG) was significantly greater for regular real verbs than for irregular ones. Furthermore, we observed a significant positive covariance between the number of mistakes in irregular real verb trials and the increase in functional connectivity between the LIFG and the right anterior cingulate cortex in these trails, as compared to regular ones. Our results therefore allow for dissociation between regularity and processing difficulty effects. These results, on the one hand, shed new light on the functional interplay within the LIFG-bilateral STG language-related network and, on the other hand, call for partial reconsideration of some of the previous findings while stressing the role of functional temporo-frontal connectivity in complex morphological processes. PMID:25741262

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.

Measures for brain connectivity analysis: nodes centrality and their invariant patterns

NASA Astrophysics Data System (ADS)

da Silva, Laysa Mayra Uchôa; Baltazar, Carlos Arruda; Silva, Camila Aquemi; Ribeiro, Mauricio Watanabe; de Aratanha, Maria Adelia Albano; Deolindo, Camila Sardeto; Rodrigues, Abner Cardoso; Machado, Birajara Soares

2017-07-01

The high dynamical complexity of the brain is related to its small-world topology, which enable both segregated and integrated information processing capabilities. Several measures of connectivity estimation have already been employed to characterize functional brain networks from multivariate electrophysiological data. However, understanding the properties of each measure that lead to a better description of the real topology and capture the complex phenomena present in the brain remains challenging. In this work we compared four nonlinear connectivity measures and show that each method characterizes distinct features of brain interactions. The results suggest an invariance of global network parameters from different behavioral states and that more complete description may be reached considering local features, independently of the connectivity measure employed. Our findings also point to future perspectives in connectivity studies that combine distinct and complementary dependence measures in assembling higher dimensions manifolds.

From the Bottom-Up: Chemotherapy and Gut-Brain Axis Dysregulation.

PubMed

Bajic, Juliana E; Johnston, Ian N; Howarth, Gordon S; Hutchinson, Mark R

2018-01-01

The central nervous system and gastrointestinal tract form the primary targets of chemotherapy-induced toxicities. Symptoms associated with damage to these regions have been clinically termed chemotherapy-induced cognitive impairment and mucositis. Whilst extensive literature outlines the complex etiology of each pathology, to date neither chemotherapy-induced side-effect has considered the potential impact of one on the pathogenesis of the other disorder. This is surprising considering the close bidirectional relationship shared between each organ; the gut-brain axis. There are complex multiple pathways linking the gut to the brain and vice versa in both normal physiological function and disease. For instance, psychological and social factors influence motility and digestive function, symptom perception, and behaviors associated with illness and pathological outcomes. On the other hand, visceral pain affects central nociception pathways, mood and behavior. Recent interest highlights the influence of functional gut disorders, such as inflammatory bowel diseases and irritable bowel syndrome in the development of central comorbidities. Gut-brain axis dysfunction and microbiota dysbiosis have served as key portals in understanding the potential mechanisms associated with these functional gut disorders and their effects on cognition. In this review we will present the role gut-brain axis dysregulation plays in the chemotherapy setting, highlighting peripheral-to-central immune signaling mechanisms and their contribution to neuroimmunological changes associated with chemotherapy exposure. Here, we hypothesize that dysregulation of the gut-brain axis plays a major role in the intestinal, psychological and neurological complications following chemotherapy. We pay particular attention to evidence surrounding microbiota dysbiosis, the role of intestinal permeability, damage to nerves of the enteric and peripheral nervous systems and vagal and humoral mediated changes.

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

PubMed

Simonyan, Kristina; Fuertinger, Stefan

2015-04-01

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

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.

Regulation of Drosophila Brain Wiring by Neuropil Interactions via a Slit-Robo-RPTP Signaling Complex.

PubMed

Oliva, Carlos; Soldano, Alessia; Mora, Natalia; De Geest, Natalie; Claeys, Annelies; Erfurth, Maria-Luise; Sierralta, Jimena; Ramaekers, Ariane; Dascenco, Dan; Ejsmont, Radoslaw K; Schmucker, Dietmar; Sanchez-Soriano, Natalia; Hassan, Bassem A

2016-10-24

The axonal wiring molecule Slit and its Round-About (Robo) receptors are conserved regulators of nerve cord patterning. Robo receptors also contribute to wiring brain circuits. Whether molecular mechanisms regulating these signals are modified to fit more complex brain wiring processes is unclear. We investigated the role of Slit and Robo receptors in wiring Drosophila higher-order brain circuits and identified differences in the cellular and molecular mechanisms of Robo/Slit function. First, we find that signaling by Robo receptors in the brain is regulated by the Receptor Protein Tyrosine Phosphatase RPTP69d. RPTP69d increases membrane availability of Robo3 without affecting its phosphorylation state. Second, we detect no midline localization of Slit during brain development. Instead, Slit is enriched in the mushroom body, a neuronal structure covering large areas of the brain. Thus, a divergent molecular mechanism regulates neuronal circuit wiring in the Drosophila brain, partly in response to signals from the mushroom body. Copyright © 2016 The Authors. Published by 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.

Whole-brain analytic measures of network communication reveal increased structure-function correlation in right temporal lobe epilepsy.

PubMed

Wirsich, Jonathan; Perry, Alistair; Ridley, Ben; Proix, Timothée; Golos, Mathieu; Bénar, Christian; Ranjeva, Jean-Philippe; Bartolomei, Fabrice; Breakspear, Michael; Jirsa, Viktor; Guye, Maxime

2016-01-01

The in vivo structure-function relationship is key to understanding brain network reorganization due to pathologies. This relationship is likely to be particularly complex in brain network diseases such as temporal lobe epilepsy, in which disturbed large-scale systems are involved in both transient electrical events and long-lasting functional and structural impairments. Herein, we estimated this relationship by analyzing the correlation between structural connectivity and functional connectivity in terms of analytical network communication parameters. As such, we targeted the gradual topological structure-function reorganization caused by the pathology not only at the whole brain scale but also both in core and peripheral regions of the brain. We acquired diffusion (dMRI) and resting-state fMRI (rsfMRI) data in seven right-lateralized TLE (rTLE) patients and fourteen healthy controls and analyzed the structure-function relationship by using analytical network communication metrics derived from the structural connectome. In rTLE patients, we found a widespread hypercorrelated functional network. Network communication analysis revealed greater unspecific branching of the shortest path (search information) in the structural connectome and a higher global correlation between the structural and functional connectivity for the patient group. We also found evidence for a preserved structural rich-club in the patient group. In sum, global augmentation of structure-function correlation might be linked to a smaller functional repertoire in rTLE patients, while sparing the central core of the brain which may represent a pathway that facilitates the spread of seizures.

Evaluation of a Computer-Based Revision Prompting Intervention for Undergraduate Writers with Acquired Brain Injury

ERIC Educational Resources Information Center

Ledbetter, Alexander K.

2017-01-01

People with acquired brain injury (ABI) present with impairments in working memory and executive functions, and these cognitive deficits contribute to difficulty self-regulating the production of expository writing. Cognitive processes involved in carrying out complex writing tasks include planning, generating text, and reviewing or revising text…

LONI visualization environment.

PubMed

Dinov, Ivo D; Valentino, Daniel; Shin, Bae Cheol; Konstantinidis, Fotios; Hu, Guogang; MacKenzie-Graham, Allan; Lee, Erh-Fang; Shattuck, David; Ma, Jeff; Schwartz, Craig; Toga, Arthur W

2006-06-01

Over the past decade, the use of informatics to solve complex neuroscientific problems has increased dramatically. Many of these research endeavors involve examining large amounts of imaging, behavioral, genetic, neurobiological, and neuropsychiatric data. Superimposing, processing, visualizing, or interpreting such a complex cohort of datasets frequently becomes a challenge. We developed a new software environment that allows investigators to integrate multimodal imaging data, hierarchical brain ontology systems, on-line genetic and phylogenic databases, and 3D virtual data reconstruction models. The Laboratory of Neuro Imaging visualization environment (LONI Viz) consists of the following components: a sectional viewer for imaging data, an interactive 3D display for surface and volume rendering of imaging data, a brain ontology viewer, and an external database query system. The synchronization of all components according to stereotaxic coordinates, region name, hierarchical ontology, and genetic labels is achieved via a comprehensive BrainMapper functionality, which directly maps between position, structure name, database, and functional connectivity information. This environment is freely available, portable, and extensible, and may prove very useful for neurobiologists, neurogenetisists, brain mappers, and for other clinical, pedagogical, and research endeavors.

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

PubMed

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

2018-03-10

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

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.

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

Oxytocin effects on complex brain networks are moderated by experiences of maternal love withdrawal.

PubMed

Riem, Madelon M E; van IJzendoorn, Marinus H; Tops, Mattie; Boksem, Maarten A S; Rombouts, Serge A R B; Bakermans-Kranenburg, Marian J

2013-10-01

The neuropeptide oxytocin has been implicated in a variety of social processes. However, recent studies indicate that oxytocin does not enhance prosocial behavior in all people in all circumstances. Here, we investigate effects of intranasal oxytocin administration on intrinsic functional brain connectivity with resting state functional magnetic resonance imaging. Participants were 42 women who received a nasal spray containing either 16 IU of oxytocin or a placebo and reported how often their mother used love withdrawal as a disciplinary strategy involving withholding love and affection after a failure or misbehavior. We found that oxytocin changes functional connectivity between the posterior cingulate cortex (PCC) and the brainstem. In the oxytocin group there was a positive connectivity between these regions, whereas the placebo group showed negative connectivity. In addition, oxytocin induced functional connectivity changes between the PCC, the cerebellum and the postcentral gyrus, but only for those participants who experienced low levels of maternal love withdrawal. We speculate that oxytocin enhances prosocial behavior by influencing complex brain networks involved in self-referential processing and affectionate touch, most prominently in individuals with supportive family backgrounds. Copyright © 2013 Elsevier B.V. and ECNP. All rights reserved.

Can nutraceuticals prevent Alzheimer's disease? Potential therapeutic role of a formulation containing shilajit and complex B vitamins.

PubMed

Carrasco-Gallardo, Carlos; Farías, Gonzalo A; Fuentes, Patricio; Crespo, Fernando; Maccioni, Ricardo B

2012-11-01

Alzheimer's disease (AD) is a brain disorder displaying a prevalence and impact in constant expansion. This expansive and epidemic behavior is concerning medical and public opinion while focusing efforts on its prevention and treatment. One important strategy to prevent this brain impairment is based on dietary changes and nutritional supplements, functional foods and nutraceuticals. In this review we discuss the potential contributions of shilajit and complex B vitamins to AD prevention. We analyze the status of biological studies and present data of a clinical trial developed in patients with mild AD. Studies suggest that shilajit and its active principle fulvic acid, as well as a formula of shilajit with B complex vitamins, emerge as novel nutraceutical with potential uses against this brain disorder. Copyright © 2012 IMSS. Published by Elsevier Inc. All rights reserved.

A decade of imaging surgeons' brain function (part II): A systematic review of applications for technical and nontechnical skills assessment.

PubMed

Modi, Hemel Narendra; Singh, Harsimrat; Yang, Guang-Zhong; Darzi, Ara; Leff, Daniel Richard

2017-11-01

Functional neuroimaging technologies enable assessment of operator brain function and can deepen our understanding of skills learning, ergonomic optima, and cognitive processes in surgeons. Although there has been a critical mass of data detailing surgeons' brain function, this literature has not been reviewed systematically. A systematic search of original neuroimaging studies assessing surgeons' brain function and published up until November 2016 was conducted using Medline, Embase, and PsycINFO databases. Twenty-seven studies fulfilled the inclusion criteria, including 3 feasibility studies, 14 studies exploring the neural correlates of technical skill acquisition, and the remainder investigating brain function in the context of intraoperative decision-making (n = 1), neurofeedback training (n = 1), robot-assisted technology (n = 5), and surgical teaching (n = 3). Early stages of learning open surgical tasks (knot-tying) are characterized by prefrontal cortical activation, which subsequently attenuates with deliberate practice. However, with complex laparoscopic skills (intracorporeal suturing), prefrontal cortical engagement requires substantial training, and attenuation occurs over a longer time course, after years of refinement. Neurofeedback and interventions that improve neural efficiency may enhance technical performance and skills learning. Imaging surgeons' brain function has identified neural signatures of expertise that might help inform objective assessment and selection processes. Interventions that improve neural efficiency may target skill-specific brain regions and augment surgical performance. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

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.

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.

Finding the imposter: brain connectivity of lesions causing delusional misidentifications

PubMed Central

Darby, R Ryan; Laganiere, Simon; Pascual-Leone, Alvaro; Prasad, Sashank; Fox, Michael D

2017-01-01

Abstract See McKay and Furl (doi:10.1093/aww323) for a scientific commentary on this article. Focal brain injury can sometimes lead to bizarre symptoms, such as the delusion that a family member has been replaced by an imposter (Capgras syndrome). How a single brain lesion could cause such a complex disorder is unclear, leading many to speculate that concurrent delirium, psychiatric disease, dementia, or a second lesion is required. Here we instead propose that Capgras and other delusional misidentification syndromes arise from single lesions at unique locations within the human brain connectome. This hypothesis is motivated by evidence that symptoms emerge from sites functionally connected to a lesion location, not just the lesion location itself. First, 17 cases of lesion-induced delusional misidentifications were identified and lesion locations were mapped to a common brain atlas. Second, lesion network mapping was used to identify brain regions functionally connected to the lesion locations. Third, regions involved in familiarity perception and belief evaluation, two processes thought to be abnormal in delusional misidentifications, were identified using meta-analyses of previous functional magnetic resonance imaging studies. We found that all 17 lesion locations were functionally connected to the left retrosplenial cortex, the region most activated in functional magnetic resonance imaging studies of familiarity. Similarly, 16 of 17 lesion locations were functionally connected to the right frontal cortex, the region most activated in functional magnetic resonance imaging studies of expectation violation, a component of belief evaluation. This connectivity pattern was highly specific for delusional misidentifications compared to four other lesion-induced neurological syndromes (P < 0.0001). Finally, 15 lesions causing other types of delusions were connected to expectation violation (P < 0.0001) but not familiarity regions, demonstrating specificity for delusion content. Our results provide potential neuroanatomical correlates for impaired familiarity perception and belief evaluation in patients with delusional misidentifications. More generally, we demonstrate a mechanism by which a single lesion can cause a complex neuropsychiatric syndrome based on that lesion’s unique pattern of functional connectivity, without the need for pre-existing or hidden pathology. PMID:28082298

Characterization and classification of zebrafish brain morphology mutants

PubMed Central

Lowery, Laura Anne; De Rienzo, Gianluca; Gutzman, Jennifer H.; Sive, Hazel

2010-01-01

The mechanisms by which the vertebrate brain achieves its three-dimensional structure are clearly complex, requiring the functions of many genes. Using the zebrafish as a model, we have begun to define genes required for brain morphogenesis, including brain ventricle formation, by studying 16 mutants previously identified as having embryonic brain morphology defects. We report the phenotypic characterization of these mutants at several time-points, using brain ventricle dye injection, imaging, and immunohistochemistry with neuronal markers. Most of these mutants display early phenotypes, affecting initial brain shaping, while others show later phenotypes, affecting brain ventricle expansion. In the early phenotype group, we further define four phenotypic classes and corresponding functions required for brain morphogenesis. Although we did not use known genotypes for this classification, basing it solely on phenotypes, many mutants with defects in functionally related genes clustered in a single class. In particular, class 1 mutants show midline separation defects, corresponding to epithelial junction defects; class 2 mutants show reduced brain ventricle size; class 3 mutants show midbrain-hindbrain abnormalities, corresponding to basement membrane defects; and class 4 mutants show absence of ventricle lumen inflation, corresponding to defective ion pumping. Later brain ventricle expansion requires the extracellular matrix, cardiovascular circulation, and transcription/splicing-dependent events. We suggest that these mutants define processes likely to be used during brain morphogenesis throughout the vertebrates. PMID:19051268

The multisensory brain and its ability to learn music.

PubMed

Zimmerman, Emily; Lahav, Amir

2012-04-01

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

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.

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

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.

Co-activation patterns in resting-state fMRI signals.

PubMed

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

2018-02-08

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

The social network-network: size is predicted by brain structure and function in the amygdala and paralimbic regions

PubMed Central

Von Der Heide, Rebecca; Vyas, Govinda

2014-01-01

The social brain hypothesis proposes that the large size of the primate neocortex evolved to support complex and demanding social interactions. Accordingly, recent studies have reported correlations between the size of an individual’s social network and the density of gray matter (GM) in regions of the brain implicated in social cognition. However, the reported relationships between GM density and social group size are somewhat inconsistent with studies reporting correlations in different brain regions. One factor that might account for these discrepancies is the use of different measures of social network size (SNS). This study used several measures of SNS to assess the relationships SNS and GM density. The second goal of this study was to test the relationship between social network measures and functional brain activity. Participants performed a social closeness task using photos of their friends and unknown people. Across the VBM and functional magnetic resonance imaging analyses, individual differences in SNS were consistently related to structural and functional differences in three regions: the left amygdala, right amygdala and the right entorhinal/ventral anterior temporal cortex. PMID:24493846

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.

Forthergillian Lecture. Imaging human brain function.

PubMed

Frackowiak, R S

The non-invasive brain scanning techniques introduced a quarter of a century ago have become crucial for diagnosis in clinical neurology. They have also been used to investigate brain function and have provided information about normal activity and pathogenesis. They have been used to investigate functional specialization in the brain and how specialized areas communicate to generate complex integrated functions such as speech, memory, the emotions and so on. The phenomenon of brain plasticity is poorly understood and yet clinical neurologists are aware, from everyday observations, that spontaneous recovery from brain lesions is common. An improved understanding of the mechanisms of recovery may generate new therapeutic strategies and indicate ways of modulating mechanisms that promote plastic compensation for loss of function. The main methods used to investigate these issues are positron emission tomography and magnetic resonance imaging (M.R.I.). M.R.I. is also used to map brain structure. The techniques of functional brain mapping and computational morphometrics depend on high performance scanners and a validated set of analytic statistical procedures that generate reproducible data and meaningful inferences from brain scanning data. The motor system presents a good paradigm to illustrate advances made by scanning towards an understanding of plasticity at the level of brain areas. The normal motor system is organized in a nested hierarchy. Recovery from paralysis caused by internal capsule strokes involves functional reorganization manifesting itself as changed patterns of activity in the component brain areas of the normal motor system. The pattern of plastic modification depends in part on patterns of residual or disturbed connectivity after brain injury. Therapeutic manipulations in patients with Parkinson's disease using deep brain stimulation, dopaminergic agents or fetal mesencephalic transplantation provide a means to examine mechanisms underpinning plastic change. Other models of plastic change, such as normal visuospatial learning or re-establishing speech comprehension after cochlear implantation in the deaf illustrate how patterns of brain function adapt over time. Limitations of the scanning techniques and prospects for the future are discussed in relation to new developments in the neuroimaging field.

Mapping the brain correlates of borderline personality disorder: A functional neuroimaging meta-analysis of resting state studies.

PubMed

Visintin, Eleonora; De Panfilis, Chiara; Amore, Mario; Balestrieri, Matteo; Wolf, Robert Christian; Sambataro, Fabio

2016-11-01

Altered intrinsic function of the brain has been implicated in Borderline Personality Disorder (BPD). Nonetheless, imaging studies have yielded inconsistent alterations of brain function. To investigate the neural activity at rest in BPD, we conducted a set of meta-analyses of brain imaging studies performed at rest. A total of seven functional imaging studies (152 patients with BPD and 147 control subjects) were combined using whole-brain Signed Differential Mapping meta-analyses. Furthermore, two conjunction meta-analyses of neural activity at rest were also performed: with neural activity changes during emotional processing, and with structural differences, respectively. We found altered neural activity in the regions of the default mode network (DMN) in BPD. Within the regions of the midline core DMN, patients with BPD showed greater activity in the anterior as well as in the posterior midline hubs relative to controls. Conversely, in the regions of the dorsal DMN they showed reduced activity compared to controls in the right lateral temporal complex and bilaterally in the orbitofrontal cortex. Increased activity in the precuneus was observed both at rest and during emotional processing. Reduced neural activity at rest in lateral temporal complex was associated with smaller volume of this area. Heterogeneity across imaging studies. Altered activity in the regions of the midline core as well as of the dorsal subsystem of the DMN may reflect difficulties with interpersonal and affective regulation in BPD. These findings suggest that changes in spontaneous neural activity could underlie core symptoms in BPD. Copyright © 2016 Elsevier B.V. All rights reserved.

Metabolic alterations in developing brain after injury – knowns and unknowns

PubMed Central

McKenna, Mary C.; Scafidi, Susanna; Robertson, Courtney L.

2016-01-01

Brain development is a highly orchestrated complex process. The developing brain utilizes many substrates including glucose, ketone bodies, lactate, fatty acids and amino acids for energy, cell division and the biosynthesis of nucleotides, proteins and lipids. Metabolism is crucial to provide energy for all cellular processes required for brain development and function including ATP formation, synaptogenesis, synthesis, release and uptake of neurotransmitters, maintaining ionic gradients and redox status, and myelination. The rapidly growing population of infants and children with neurodevelopmental and cognitive impairments and life-long disability resulting from developmental brain injury is a significant public health concern. Brain injury in infants and children can have devastating effects because the injury is superimposed on the high metabolic demands of the developing brain. Acute injury in the pediatric brain can derail, halt or lead to dysregulation of the complex and highly regulated normal developmental processes. This paper provides a brief review of metabolism in developing brain and alterations found clinically and in animal models of developmental brain injury. The metabolic changes observed in three major categories of injury that can result in life-long cognitive and neurological disabilities, including neonatal hypoxia-ischemia, pediatric traumatic brain injury, and brain injury secondary to prematurity are reviewed. PMID:26148530

Age-dependent changes at the blood-brain barrier. A Comparative structural and functional study in young adult and middle aged rats.

PubMed

Bors, Luca; Tóth, Kinga; Tóth, Estilla Zsófia; Bajza, Ágnes; Csorba, Attila; Szigeti, Krisztián; Máthé, Domokos; Perlaki, Gábor; Orsi, Gergely; Tóth, Gábor K; Erdő, Franciska

2018-05-01

Decreased beta-amyloid clearance in Alzheimer's disease and increased blood-brain barrier permeability in aged subjects have been reported in several articles. However, morphological and functional characterization of blood-brain barrier and its membrane transporter activity have not been described in physiological aging yet. The aim of our study was to explore the structural changes in the brain microvessels and possible functional alterations of P-glycoprotein at the blood-brain barrier with aging. Our approach included MR imaging for anatomical orientation in middle aged rats, electronmicroscopy and immunohistochemistry to analyse the alterations at cellular level, dual or triple-probe microdialysis and SPECT to test P-glycoprotein functionality in young and middle aged rats. Our results indicate that the thickness of basal lamina increases, the number of tight junctions decreases and the size of astrocyte endfeet extends with advanced age. On the basis of microdialysis and SPECT results the P-gp function is reduced in old rats. With our multiparametric approach a complex regulation can be suggested which includes elements leading to increased permeability of blood-brain barrier by enhanced paracellular and transcellular transport, and factors working against it. To verify the role of P-gp pumps in brain aging further studies are warranted. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

The Drosophila blood-brain barrier: development and function of a glial endothelium.

PubMed

Limmer, Stefanie; Weiler, Astrid; Volkenhoff, Anne; Babatz, Felix; Klämbt, Christian

2014-01-01

The efficacy of neuronal function requires a well-balanced extracellular ion homeostasis and a steady supply with nutrients and metabolites. Therefore, all organisms equipped with a complex nervous system developed a so-called blood-brain barrier, protecting it from an uncontrolled entry of solutes, metabolites or pathogens. In higher vertebrates, this diffusion barrier is established by polarized endothelial cells that form extensive tight junctions, whereas in lower vertebrates and invertebrates the blood-brain barrier is exclusively formed by glial cells. Here, we review the development and function of the glial blood-brain barrier of Drosophila melanogaster. In the Drosophila nervous system, at least seven morphologically distinct glial cell classes can be distinguished. Two of these glial classes form the blood-brain barrier. Perineurial glial cells participate in nutrient uptake and establish a first diffusion barrier. The subperineurial glial (SPG) cells form septate junctions, which block paracellular diffusion and thus seal the nervous system from the hemolymph. We summarize the molecular basis of septate junction formation and address the different transport systems expressed by the blood-brain barrier forming glial cells.

Molecular Imaging Provides Novel Insights on Estrogen Receptor Activity in Mouse Brain

PubMed Central

Stell, Alessia; Belcredito, Silvia; Ciana, Paolo; Maggi, Adriana

2009-01-01

Estrogen receptors have long been known to be expressed in several brain areas in addition to those directly involved in the control of reproductive functions. Investigations in humans and in animal models suggest a strong influence of estrogens on limbic and motor functions, yet the complexity and heterogeneity of neural tissue have limited our approaches to the full understanding of estrogen activity in the central nervous system. The aim of this study was to examine the transcriptional activity of estrogen receptors in the brain of male and female mice. Exploiting the ERE-Luc reporter mouse, we set up a novel, bioluminescence-based technique to study brain estrogen receptor transcriptional activity. Here we show, for the first time, that estrogen receptors are similarly active in male and female brains and that the estrous cycle affects estrogen receptor activity in regions of the central nervous system not known to be associated with reproductive functions. Because of its reproducibility and sensitivity, this novel bioluminescence application candidates as an innovative methodology for the study and development of drugs targeting brain estrogen receptors. PMID:19123998

Molecular imaging provides novel insights on estrogen receptor activity in mouse brain.

PubMed

Stell, Alessia; Belcredito, Silvia; Ciana, Paolo; Maggi, Adriana

2008-01-01

Estrogen receptors have long been known to be expressed in several brain areas in addition to those directly involved in the control of reproductive functions. Investigations in humans and in animal models suggest a strong influence of estrogens on limbic and motor functions, yet the complexity and heterogeneity of neural tissue have limited our approaches to the full understanding of estrogen activity in the central nervous system. The aim of this study was to examine the transcriptional activity of estrogen receptors in the brain of male and female mice. Exploiting the ERE-Luc reporter mouse, we set up a novel, bioluminescence-based technique to study brain estrogen receptor transcriptional activity. Here we show, for the first time, that estrogen receptors are similarly active in male and female brains and that the estrous cycle affects estrogen receptor activity in regions of the central nervous system not known to be associated with reproductive functions. Because of its reproducibility and sensitivity, this novel bioluminescence application stands as a candidate as an innovative methodology for the study and development of drugs targeting brain estrogen receptors.

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

Molecular, Cellular and Functional Effects of Radiation-Induced Brain Injury: A Review

PubMed Central

Balentova, Sona; Adamkov, Marian

2015-01-01

Radiation therapy is the most effective non-surgical treatment of primary brain tumors and metastases. Preclinical studies have provided valuable insights into pathogenesis of radiation-induced injury to the central nervous system. Radiation-induced brain injury can damage neuronal, glial and vascular compartments of the brain and may lead to molecular, cellular and functional changes. Given its central role in memory and adult neurogenesis, the majority of studies have focused on the hippocampus. These findings suggested that hippocampal avoidance in cranial radiotherapy prevents radiation-induced cognitive impairment of patients. However, multiple rodent studies have shown that this problem is more complex. As the radiation-induced cognitive impairment reflects hippocampal and non-hippocampal compartments, it is of critical importance to investigate molecular, cellular and functional modifications in various brain regions as well as their integration at clinically relevant doses and schedules. We here provide a literature overview, including our previously published results, in order to support the translation of preclinical findings to clinical practice, and improve the physical and mental status of patients with brain tumors. PMID:26610477

Roadmap on neurophotonics

NASA Astrophysics Data System (ADS)

Cho, Yong Ku; Zheng, Guoan; Augustine, George J.; Hochbaum, Daniel; Cohen, Adam; Knöpfel, Thomas; Pisanello, Ferruccio; Pavone, Francesco S.; Vellekoop, Ivo M.; Booth, Martin J.; Hu, Song; Zhu, Jiang; Chen, Zhongping; Hoshi, Yoko

2016-09-01

Mechanistic understanding of how the brain gives rise to complex behavioral and cognitive functions is one of science’s grand challenges. The technical challenges that we face as we attempt to gain a systems-level understanding of the brain are manifold. The brain’s structural complexity requires us to push the limit of imaging resolution and depth, while being able to cover large areas, resulting in enormous data acquisition and processing needs. Furthermore, it is necessary to detect functional activities and ‘map’ them onto the structural features. The functional activity occurs at multiple levels, using electrical and chemical signals. Certain electrical signals are only decipherable with sub-millisecond timescale resolution, while other modes of signals occur in minutes to hours. For these reasons, there is a wide consensus that new tools are necessary to undertake this daunting task. Optical techniques, due to their versatile and scalable nature, have great potentials to answer these challenges. Optical microscopy can now image beyond the diffraction limit, record multiple types of brain activity, and trace structural features across large areas of tissue. Genetically encoded molecular tools opened doors to controlling and detecting neural activity using light in specific cell types within the intact brain. Novel sample preparation methods that reduce light scattering have been developed, allowing whole brain imaging in rodent models. Adaptive optical methods have the potential to resolve images from deep brain regions. In this roadmap article, we showcase a few major advances in this area, survey the current challenges, and identify potential future needs that may be used as a guideline for the next steps to be taken.

Roadmap on neurophotonics

PubMed Central

Cho, Yong Ku; Zheng, Guoan; Augustine, George J; Hochbaum, Daniel; Cohen, Adam; Knöpfel, Thomas; Pisanello, Ferruccio; Pavone, Francesco S; Vellekoop, Ivo M; Booth, Martin J; Hu, Song; Zhu, Jiang; Chen, Zhongping; Hoshi, Yoko

2017-01-01

Mechanistic understanding of how the brain gives rise to complex behavioral and cognitive functions is one of science’s grand challenges. The technical challenges that we face as we attempt to gain a systems-level understanding of the brain are manifold. The brain’s structural complexity requires us to push the limit of imaging resolution and depth, while being able to cover large areas, resulting in enormous data acquisition and processing needs. Furthermore, it is necessary to detect functional activities and ‘map’ them onto the structural features. The functional activity occurs at multiple levels, using electrical and chemical signals. Certain electrical signals are only decipherable with sub-millisecond timescale resolution, while other modes of signals occur in minutes to hours. For these reasons, there is a wide consensus that new tools are necessary to undertake this daunting task. Optical techniques, due to their versatile and scalable nature, have great potentials to answer these challenges. Optical microscopy can now image beyond the diffraction limit, record multiple types of brain activity, and trace structural features across large areas of tissue. Genetically encoded molecular tools opened doors to controlling and detecting neural activity using light in specific cell types within the intact brain. Novel sample preparation methods that reduce light scattering have been developed, allowing whole brain imaging in rodent models. Adaptive optical methods have the potential to resolve images from deep brain regions. In this roadmap article, we showcase a few major advances in this area, survey the current challenges, and identify potential future needs that may be used as a guideline for the next steps to be taken. PMID:28386392

Graph-based network analysis of resting-state functional MRI.

PubMed

Wang, Jinhui; Zuo, Xinian; He, Yong

2010-01-01

In the past decade, resting-state functional MRI (R-fMRI) measures of brain activity have attracted considerable attention. Based on changes in the blood oxygen level-dependent signal, R-fMRI offers a novel way to assess the brain's spontaneous or intrinsic (i.e., task-free) activity with both high spatial and temporal resolutions. The properties of both the intra- and inter-regional connectivity of resting-state brain activity have been well documented, promoting our understanding of the brain as a complex network. Specifically, the topological organization of brain networks has been recently studied with graph theory. In this review, we will summarize the recent advances in graph-based brain network analyses of R-fMRI signals, both in typical and atypical populations. Application of these approaches to R-fMRI data has demonstrated non-trivial topological properties of functional networks in the human brain. Among these is the knowledge that the brain's intrinsic activity is organized as a small-world, highly efficient network, with significant modularity and highly connected hub regions. These network properties have also been found to change throughout normal development, aging, and in various pathological conditions. The literature reviewed here suggests that graph-based network analyses are capable of uncovering system-level changes associated with different processes in the resting brain, which could provide novel insights into the understanding of the underlying physiological mechanisms of brain function. We also highlight several potential research topics in the future.

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.

Cocaine-Induced Neurodevelopmental Deficits and Underlying Mechanisms

PubMed Central

Martin, Melissa M.; Graham, Devon L.; McCarthy, Deirdre M.; Bhide, Pradeep G.; Stanwood, Gregg D.

2017-01-01

Exposure to drugs early in life has complex and long-lasting implications for brain structure and function. This review summarizes work to date on the immediate and long-term effects of prenatal exposure to cocaine. In utero cocaine exposure produces disruptions in brain monoamines, particularly dopamine, during sensitive periods of brain development, and leads to permanent changes in specific brain circuits, molecules, and behavior. Here, we integrate clinical studies and significance with mechanistic preclinical studies, to define our current knowledge base and identify gaps for future investigation. PMID:27345015

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.

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.

Sculpting the Intrinsic Modular Organization of Spontaneous Brain Activity by Art.

PubMed

Lin, Chia-Shu; Liu, Yong; Huang, Wei-Yuan; Lu, Chia-Feng; Teng, Shin; Ju, Tzong-Ching; He, Yong; Wu, Yu-Te; Jiang, Tianzi; Hsieh, Jen-Chuen

2013-01-01

Artistic training is a complex learning that requires the meticulous orchestration of sophisticated polysensory, motor, cognitive, and emotional elements of mental capacity to harvest an aesthetic creation. In this study, we investigated the architecture of the resting-state functional connectivity networks from professional painters, dancers and pianists. Using a graph-based network analysis, we focused on the art-related changes of modular organization and functional hubs in the resting-state functional connectivity network. We report that the brain architecture of artists consists of a hierarchical modular organization where art-unique and artistic form-specific brain states collectively mirror the mind states of virtuosos. We show that even in the resting state, this type of extraordinary and long-lasting training can macroscopically imprint a neural network system of spontaneous activity in which the related brain regions become functionally and topologically modularized in both domain-general and domain-specific manners. The attuned modularity reflects a resilient plasticity nurtured by long-term experience.

The effect of the COMT val(158)met polymorphism on neural correlates of semantic verbal fluency.

PubMed

Krug, Axel; Markov, Valentin; Sheldrick, Abigail; Krach, Sören; Jansen, Andreas; Zerres, Klaus; Eggermann, Thomas; Stöcker, Tony; Shah, N Jon; Kircher, Tilo

2009-12-01

Variation in the val(158)met polymorphism of the COMT gene has been found to be associated with cognitive performance. In functional neuroimaging studies, this dysfunction has been linked to signal changes in prefrontal areas. Given the complex modulation and functional heterogeneity of frontal lobe systems, further specification of COMT gene-related phenotypes differing in prefrontally mediated cognitive performance are of major interest. Eighty healthy individuals (54 men, 26 women; mean age 23.3 years) performed an overt semantic verbal fluency task while brain activation was measured with functional magnetic resonance imaging (fMRI). COMT val(158)met genotype was determined and correlated with brain activation measured with fMRI during the task. Although there were no differences in performance, brain activation in the left inferior frontal gyrus [Brodmann area 10] was positively correlated with the number of val alleles in the COMT gene. COMT val(158)met status modulates brain activation during the language production on a semantic level in an area related to executive functions.

Sculpting the Intrinsic Modular Organization of Spontaneous Brain Activity by Art

PubMed Central

Lin, Chia-Shu; Liu, Yong; Huang, Wei-Yuan; Lu, Chia-Feng; Teng, Shin; Ju, Tzong-Ching; He, Yong; Wu, Yu-Te; Jiang, Tianzi; Hsieh, Jen-Chuen

2013-01-01

Artistic training is a complex learning that requires the meticulous orchestration of sophisticated polysensory, motor, cognitive, and emotional elements of mental capacity to harvest an aesthetic creation. In this study, we investigated the architecture of the resting-state functional connectivity networks from professional painters, dancers and pianists. Using a graph-based network analysis, we focused on the art-related changes of modular organization and functional hubs in the resting-state functional connectivity network. We report that the brain architecture of artists consists of a hierarchical modular organization where art-unique and artistic form-specific brain states collectively mirror the mind states of virtuosos. We show that even in the resting state, this type of extraordinary and long-lasting training can macroscopically imprint a neural network system of spontaneous activity in which the related brain regions become functionally and topologically modularized in both domain-general and domain-specific manners. The attuned modularity reflects a resilient plasticity nurtured by long-term experience. PMID:23840527

Variation in brain anatomy in frogs and its possible bearing on their locomotor ecology.

PubMed

Manzano, Adriana S; Herrel, Anthony; Fabre, Anne-Claire; Abdala, Virginia

2017-07-01

Despite the long-standing interest in the evolution of the brain, relatively little is known about variation in brain anatomy in frogs. Yet, frogs are ecologically diverse and, as such, variation in brain anatomy linked to differences in lifestyle or locomotor behavior can be expected. Here we present a comparative morphological study focusing on the macro- and micro-anatomy of the six regions of the brain and its choroid plexus: the olfactory bulbs, the telencephalon, the diencephalon, the mesencephalon, the rhombencephalon, and the cerebellum. We also report on the comparative anatomy of the plexus brachialis responsible for the innervation of the forelimbs. It is commonly thought that amphibians have a simplified brain organization, associated with their supposedly limited behavioral complexity and reduced motor skills. We compare frogs with different ecologies that also use their limbs in different contexts and for other functions. Our results show that brain morphology is more complex and more variable than typically assumed. Moreover, variation in brain morphology among species appears related to locomotor behavior as suggested by our quantitative analyses. Thus we propose that brain morphology may be related to the locomotor mode, at least in the frogs included in our analysis. © 2017 Anatomical Society.

Reduced cognitive function, increased blood-brain-barrier transport and inflammatory responses, and altered brain metabolites in LDLr -/-and C57BL/6 mice fed a western diet

PubMed Central

Lee, Linda L.; Puchowicz, Michelle; Golub, Mari S.; Befroy, Douglas E.; Wilson, Dennis W.; Anderson, Steven; Cline, Gary; Bini, Jason; Borkowski, Kamil; Knotts, Trina A.; Rutledge, John C.

2018-01-01

Recent work suggests that diet affects brain metabolism thereby impacting cognitive function. Our objective was to determine if a western diet altered brain metabolism, increased blood-brain barrier (BBB) transport and inflammation, and induced cognitive impairment in C57BL/6 (WT) mice and low-density lipoprotein receptor null (LDLr -/-) mice, a model of hyperlipidemia and cognitive decline. We show that a western diet and LDLr -/- moderately influence cognitive processes as assessed by Y-maze and radial arm water maze. Also, western diet significantly increased BBB transport, as well as microvessel factor VIII in LDLr -/- and microglia IBA1 staining in WT, both indicators of activation and neuroinflammation. Interestingly, LDLr -/- mice had a significant increase in 18F- fluorodeoxyglucose uptake irrespective of diet and brain 1H-magnetic resonance spectroscopy showed increased lactate and lipid moieties. Metabolic assessments of whole mouse brain by GC/MS and LC/MS/MS showed that a western diet altered brain TCA cycle and β-oxidation intermediates, levels of amino acids, and complex lipid levels and elevated proinflammatory lipid mediators. Our study reveals that the western diet has multiple impacts on brain metabolism, physiology, and altered cognitive function that likely manifest via multiple cellular pathways. PMID:29444171

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.

Tracing Activity Across the Whole Brain Neural Network with Optogenetic Functional Magnetic Resonance Imaging

PubMed Central

Lee, Jin Hyung

2011-01-01

Despite the overwhelming need, there has been a relatively large gap in our ability to trace network level activity across the brain. The complex dense wiring of the brain makes it extremely challenging to understand cell-type specific activity and their communication beyond a few synapses. Recent development of the optogenetic functional magnetic resonance imaging (ofMRI) provides a new impetus for the study of brain circuits by enabling causal tracing of activities arising from defined cell types and firing patterns across the whole brain. Brain circuit elements can be selectively triggered based on their genetic identity, cell body location, and/or their axonal projection target with temporal precision while the resulting network response is monitored non-invasively with unprecedented spatial and temporal accuracy. With further studies including technological innovations to bring ofMRI to its full potential, ofMRI is expected to play an important role in our system-level understanding of the brain circuit mechanism. PMID:22046160

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

Long-Term Memory Shapes the Primary Olfactory Center of an Insect Brain

ERIC Educational Resources Information Center

Hourcade, Benoit; Perisse, Emmanuel; Devaud, Jean-Marc; Sandoz, Jean-Christophe

2009-01-01

The storage of stable memories is generally considered to rely on changes in the functional properties and/or the synaptic connectivity of neural networks. However, these changes are not easily tractable given the complexity of the learning procedures and brain circuits studied. Such a search can be narrowed down by studying memories of specific…

The Neuroanatomy of Autism Spectrum Disorder: An Overview of Structural Neuroimaging Findings and Their Translatability to the Clinical Setting

ERIC Educational Resources Information Center

Ecker, Christine

2017-01-01

Autism spectrum disorder is a complex neurodevelopmental disorder, which is accompanied by differences in brain anatomy, functioning and brain connectivity. Due to its neurodevelopmental character, and the large phenotypic heterogeneity among individuals on the autism spectrum, the neurobiology of autism spectrum disorder is inherently difficult…

Research Review: Constraining Heterogeneity--The Social Brain and Its Development in Autism Spectrum Disorder

ERIC Educational Resources Information Center

Pelphrey, Kevin A.; Shultz, Sarah; Hudac, Caitlin M.; Vander Wyk, Brent C.

2011-01-01

The expression of autism spectrum disorder (ASD) is highly heterogeneous, owing to the complex interactions between genes, the brain, and behavior throughout development. Here we present a model of ASD that implicates an early and initial failure to develop the specialized functions of one or more of the set of neuroanatomical structures involved…

Phase Transitions: In the Brain, Socio-­Dramatic Play and Meaningful Early Learning

ERIC Educational Resources Information Center

Fromberg, Doris Pronin

2017-01-01

There are similar, non-linear complex dynamical systems that underlie the epigenetic development of young children. This paper discusses the confluence of research on brain functions; a body or research that informs the characteristics of young children's play and imagination; and the ways in which young children acquire fresh perceptions and…

Anomalous Development of Brain Structure and Function in Spina Bifida Myelomeningocele

ERIC Educational Resources Information Center

Juranek, Jenifer; Salman, Michael S.

2010-01-01

Spina bifida myelomeningocele (SBM) is a specific type of neural tube defect whereby the open neural tube at the level of the spinal cord alters brain development during early stages of gestation. Some structural anomalies are virtually unique to individuals with SBM, including a complex pattern of cerebellar dysplasia known as the Chiari II…

Narrative Skill in Children with Early Unilateral Brain Injury: A Possible Limit to Functional Plasticity

ERIC Educational Resources Information Center

Demir, Ozlem Ece; Levine, Susan C.; Goldin-Meadow, Susan

2010-01-01

Children with pre- or perinatal brain injury (PL) exhibit marked plasticity for language learning. Previous work has focused mostly on the emergence of earlier-developing skills, such as vocabulary and syntax. Here we ask whether this plasticity for earlier-developing aspects of language extends to more complex, later-developing language functions…

Reduction of brain mitochondrial β-oxidation impairs complex I and V in chronic alcohol intake: the underlying mechanism for neurodegeneration.

PubMed

Haorah, James; Rump, Travis J; Xiong, Huangui

2013-01-01

Neuropathy and neurocognitive deficits are common among chronic alcohol users, which are believed to be associated with mitochondrial dysfunction in the brain. The specific type of brain mitochondrial respiratory chain complexes (mRCC) that are adversely affected by alcohol abuse has not been studied. Thus, we examined the alterations of mRCC in freshly isolated mitochondria from mice brain that were pair-fed the ethanol (4% v/v) and control liquid diets for 7-8 weeks. We observed that alcohol intake severely reduced the levels of complex I and V. A reduction in complex I was associated with a decrease in carnitine palmitoyltransferase 1 (cPT1) and cPT2 levels. The mitochondrial outer (cPT1) and inner (cPT2) membrane transporter enzymes are specialized in acylation of fatty acid from outer to inner membrane of mitochondria for ATP production. Thus, our results showed that alterations of cPT1 and cPT2 paralleled a decrease β-oxidation of palmitate and ATP production, suggesting that impairment of substrate entry step (complex I function) can cause a negative impact on ATP production (complex V function). Disruption of cPT1/cPT2 was accompanied by an increase in cytochrome C leakage, while reduction of complex I and V paralleled a decrease in depolarization of mitochondrial membrane potential (ΔΨ, monitored by JC-1 fluorescence) and ATP production in alcohol intake. We noted that acetyl-L-carnitine (ALC, a cofactor of cPT1 and cPT2) prevented the adverse effects of alcohol while coenzyme Q10 (CoQ10) was not very effective against alcohol insults. These results suggest that understanding the molecular, biochemical, and signaling mechanisms of the CNS mitochondrial β-oxidation such as ALC can mitigate alcohol related neurological disorders.

Effect of complex aerobic physical exercise on PSD-95 in the hippocampus and on cognitive function in juvenile mice

NASA Astrophysics Data System (ADS)

Satriani, W. H.; Redjeki, S.; Kartinah, N. T.

2017-08-01

Increased neuroplasticity induced by complex aerobic physical exercise is associated with improved cognitive function in adult mice. Increased cognitive function is assumed to be based on increased synapse formation. One of the regions of the brain that is important in cognitive function is the hippocampus, which plays a role in memory formation. Post synaptic density-95 (PSD-95) is an adhesion protein of the post-synaptic density scaffolding that is essential to synaptic stabilization. As we age, the PSD-95 molecule matures the synapses needed for the formation of the basic circuitry of the nervous system in the brain. However, during the growth period, synapse elimination is higher than its formation. This study aims to determine whether complex aerobic exercise can improve cognitive function and PSD-95 levels in the hippocampus of juvenile mice during their growth stage. The mice performed complex aerobic exercise starting at five weeks of age and continuing for seven weeks with a gradual increase of 8 m/min. At eight weeks it was increased to 10 m/min. The exercise was done for five days of each week. The subjects of the study were tested for cognition one week before being sacrificed (at 12 weeks). The PSD-95 in the hippocampus was measured with ELISA. The results showed that there was a significant difference in cognitive function, where p < 0.05, between the group that was given complex aerobic exercise and a control group that did not. However, the PSD-95 levels did not differ significantly between the two groups. The results of this study indicate that early complex aerobic exercise can improve cognitive ability in adulthood but does not increase the levels of PSD-95 in adults.

Functional magnetic resonance imaging reflects changes in brain functioning with sedation.

PubMed

Starbuck, Victoria N; Kay, Gary G; Platenberg, R. Craig; Lin, Chin-Shoou; Zielinski, Brandon A

2000-12-01

Functional magnetic resonance imaging (fMRI) studies have demonstrated localized brain activation during cognitive tasks. Brain activation increases with task complexity and decreases with familiarity. This study investigates how sleepiness alters the relationship between brain activation and task familiarity. We hypothesize that sleepiness prevents the reduction in activation associated with practice. Twenty-nine individuals rated their sleepiness using the Stanford Sleepiness Scale before fMRI. During imaging, subjects performed the Paced Auditory Serial Addition Test, a continuous mental arithmetic task. A positive correlation was observed between self-rated sleepiness and frontal brain activation. Fourteen subjects participated in phase 2. Sleepiness was induced by evening dosing with chlorpheniramine (CP) (8 mg or 12 mg) and terfenadine (60 mg) in the morning for 3 days before the second fMRI scan. The Multiple Sleep Latency Test (MSLT) was also performed. Results revealed a significant increase in fMRI activation in proportion to the dose of CP. In contrast, for all subjects receiving placebo there was a reduction in brain activation. MSLT revealed significant daytime sleepiness for subjects receiving CP. These findings suggest that sleepiness interferes with efficiency of brain functioning. The sleepy or sedated brain shows increased oxygen utilization during performance of a familiar cognitive task. Thus, the beneficial effect of prior task exposure is lost under conditions of sedation. Copyright 2000 John Wiley & Sons, Ltd.

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

Brain State Differentiation and Behavioral Inflexibility in Autism†

PubMed Central

Uddin, Lucina Q.; Supekar, Kaustubh; Lynch, Charles J.; Cheng, Katherine M.; Odriozola, Paola; Barth, Maria E.; Phillips, Jennifer; Feinstein, Carl; Abrams, Daniel A.; Menon, Vinod

2015-01-01

Autism spectrum disorders (ASDs) are characterized by social impairments alongside cognitive and behavioral inflexibility. While social deficits in ASDs have extensively been characterized, the neurobiological basis of inflexibility and its relation to core clinical symptoms of the disorder are unknown. We acquired functional neuroimaging data from 2 cohorts, each consisting of 17 children with ASDs and 17 age- and IQ-matched typically developing (TD) children, during stimulus-evoked brain states involving performance of social attention and numerical problem solving tasks, as well as during intrinsic, resting brain states. Effective connectivity between key nodes of the salience network, default mode network, and central executive network was used to obtain indices of functional organization across evoked and intrinsic brain states. In both cohorts examined, a machine learning algorithm was able to discriminate intrinsic (resting) and evoked (task) functional brain network configurations more accurately in TD children than in children with ASD. Brain state discriminability was related to severity of restricted and repetitive behaviors, indicating that weak modulation of brain states may contribute to behavioral inflexibility in ASD. These findings provide novel evidence for a potential link between neurophysiological inflexibility and core symptoms of this complex neurodevelopmental disorder. PMID:25073720

The Interface between Neuroscience and Neuro-Psychoanalysis: Focus on Brain Connectivity

PubMed Central

Salone, Anatolia; Di Giacinto, Alessandra; Lai, Carlo; De Berardis, Domenico; Iasevoli, Felice; Fornaro, Michele; De Risio, Luisa; Santacroce, Rita; Martinotti, Giovanni; Giannantonio, Massimo Di

2016-01-01

Over the past 20 years, the advent of advanced techniques has significantly enhanced our knowledge on the brain. Yet, our understanding of the physiological and pathological functioning of the mind is still far from being exhaustive. Both the localizationist and the reductionist neuroscientific approaches to psychiatric disorders have proven to be largely unsatisfactory and are outdated. Accruing evidence suggests that psychoanalysis can engage the neurosciences in a productive and mutually enriching dialogue that may further our understanding of psychiatric disorders. In particular, advances in brain connectivity research have provided evidence supporting the convergence of neuroscientific findings and psychoanalysis and helped characterize the circuitry and mechanisms that underlie higher brain functions. In the present paper we discuss how knowledge on brain connectivity can impact neuropsychoanalysis, with a particular focus on schizophrenia. Brain connectivity studies in schizophrenic patients indicate complex alterations in brain functioning and circuitry, with particular emphasis on the role of cortical midline structures (CMS) and the default mode network (DMN). These networks seem to represent neural correlates of psychodynamic concepts central to the understanding of schizophrenia and of core psychopathological alterations of this disorder (i.e., ego disturbances and impaired primary process thinking). PMID:26869904

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.

An integrated modelling framework for neural circuits with multiple neuromodulators.

PubMed

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

2017-01-01

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

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

PubMed Central

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

2018-01-01

Abstract 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. PMID:29524274

An integrated modelling framework for neural circuits with multiple neuromodulators

PubMed Central

Vemana, Vinith

2017-01-01

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

Brain Distribution and Modulation of Neuronal Excitability by Indicaxanthin From Opuntia Ficus Indica Administered at Nutritionally-Relevant Amounts

PubMed Central

Gambino, Giuditta; Allegra, Mario; Sardo, Pierangelo; Attanzio, Alessandro; Tesoriere, Luisa; Livrea, Maria A.; Ferraro, Giuseppe; Carletti, Fabio

2018-01-01

Several studies have recently investigated the role of nutraceuticals in complex pathophysiological processes such as oxidative damages, inflammatory conditions and excitotoxicity. In this regard, the effects of nutraceuticals on basic functions of neuronal cells, such as excitability, are still poorly investigated. For this reason, the possible modulation of neuronal excitability by phytochemicals (PhC) could represent an interesting field of research given that excitotoxicity phenomena are involved in neurodegenerative alterations leading, for example, to Alzheimer’s disease. The present study was focused on indicaxanthin from Opuntia ficus indica, a bioactive betalain pigment, with a proven antioxidant and anti-inflammatory potential, previously found to cross blood-brain barrier (BBB) and to modulate the bioelectric activity of hippocampal neurons. On this basis, we aimed at detecting the specific brain areas where indicaxanthin localizes after oral administration at dietary-achievable amounts and highlighting eventual local effects on the excitability of single neuronal units. HPLC analysis of brain tissue 1 h after ingestion of 2 μmol/kg indicaxanthin indicated that the phytochemical accumulates in cortex, hippocampus, diencephalon, brainstem and cerebellum, but not in the striato-pallidal complex. Then, electrophysiological recordings, applying the microiontophoretic technique, were carried out with different amounts of indicaxanthin (0.34, 0.17, 0.085 ng/neuron) to assess whether indicaxanthin influenced the neuronal firing rate. The data showed that the bioelectric activity of neurons belonging to different brain areas was modulated after local injection of indicaxanthin, mainly with dose-related responses. A predominating inhibitory effect was observed, suggesting a possible novel beneficial effect of indicaxanthin in reducing cell excitability. These findings can constitute a new rationale for exploring biological mechanisms through which PhC could modulate neuronal function with a relapse on complex cognitive brain process and related neurodegenerative conditions. PMID:29867444

Avalanches and generalized memory associativity in a network model for conscious and unconscious mental functioning

NASA Astrophysics Data System (ADS)

Siddiqui, Maheen; Wedemann, Roseli S.; Jensen, Henrik Jeldtoft

2018-01-01

We explore statistical characteristics of avalanches associated with the dynamics of a complex-network model, where two modules corresponding to sensorial and symbolic memories interact, representing unconscious and conscious mental processes. The model illustrates Freud's ideas regarding the neuroses and that consciousness is related with symbolic and linguistic memory activity in the brain. It incorporates the Stariolo-Tsallis generalization of the Boltzmann Machine in order to model memory retrieval and associativity. In the present work, we define and measure avalanche size distributions during memory retrieval, in order to gain insight regarding basic aspects of the functioning of these complex networks. The avalanche sizes defined for our model should be related to the time consumed and also to the size of the neuronal region which is activated, during memory retrieval. This allows the qualitative comparison of the behaviour of the distribution of cluster sizes, obtained during fMRI measurements of the propagation of signals in the brain, with the distribution of avalanche sizes obtained in our simulation experiments. This comparison corroborates the indication that the Nonextensive Statistical Mechanics formalism may indeed be more well suited to model the complex networks which constitute brain and mental structure.

Chimera states in brain networks: Empirical neural vs. modular fractal connectivity

NASA Astrophysics Data System (ADS)

Chouzouris, Teresa; Omelchenko, Iryna; Zakharova, Anna; Hlinka, Jaroslav; Jiruska, Premysl; Schöll, Eckehard

2018-04-01

Complex spatiotemporal patterns, called chimera states, consist of coexisting coherent and incoherent domains and can be observed in networks of coupled oscillators. The interplay of synchrony and asynchrony in complex brain networks is an important aspect in studies of both the brain function and disease. We analyse the collective dynamics of FitzHugh-Nagumo neurons in complex networks motivated by its potential application to epileptology and epilepsy surgery. We compare two topologies: an empirical structural neural connectivity derived from diffusion-weighted magnetic resonance imaging and a mathematically constructed network with modular fractal connectivity. We analyse the properties of chimeras and partially synchronized states and obtain regions of their stability in the parameter planes. Furthermore, we qualitatively simulate the dynamics of epileptic seizures and study the influence of the removal of nodes on the network synchronizability, which can be useful for applications to epileptic surgery.

Attention-deficit hyperactivity disorder (ADHD) and tuberous sclerosis complex.

PubMed

D'Agati, Elisa; Moavero, Romina; Cerminara, Caterina; Curatolo, Paolo

2009-10-01

The neurobiological basis of attention-deficit hyperactivity disorder (ADHD) in tuberous sclerosis complex is still largely unknown. Cortical tubers may disrupt several brain networks that control different types of attention. Frontal lobe dysfunction due to seizures or epileptiform electroencephalographic discharges may perturb the development of brain systems that underpin attentional and hyperactive functions during a critical early stage of brain maturation. Comorbidity of attention-deficit hyperactivity disorder (ADHD) with mental retardation and autism spectrum disorders is frequent in children with tuberous sclerosis. Attention-deficit hyperactivity disorder (ADHD) may also reflect a direct effect of the abnormal genetic program. Treatment of children with tuberous sclerosis complex with combined symptoms of attention-deficit hyperactivity disorder (ADHD) and epilepsy may represent a challenge for clinicians, because antiepileptic therapy and drugs used to treat attention-deficit hyperactivity disorder (ADHD) may aggravate the clinical picture of each other.

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.

Emotional Complexity and the Neural Representation of Emotion in Motion

PubMed Central

Barnard, Philip J.; Lawrence, Andrew D.

2011-01-01

According to theories of emotional complexity, individuals low in emotional complexity encode and represent emotions in visceral or action-oriented terms, whereas individuals high in emotional complexity encode and represent emotions in a differentiated way, using multiple emotion concepts. During functional magnetic resonance imaging, participants viewed valenced animated scenarios of simple ball-like figures attending either to social or spatial aspects of the interactions. Participant’s emotional complexity was assessed using the Levels of Emotional Awareness Scale. We found a distributed set of brain regions previously implicated in processing emotion from facial, vocal and bodily cues, in processing social intentions, and in emotional response, were sensitive to emotion conveyed by motion alone. Attention to social meaning amplified the influence of emotion in a subset of these regions. Critically, increased emotional complexity correlated with enhanced processing in a left temporal polar region implicated in detailed semantic knowledge; with a diminished effect of social attention; and with increased differentiation of brain activity between films of differing valence. Decreased emotional complexity was associated with increased activity in regions of pre-motor cortex. Thus, neural coding of emotion in semantic vs action systems varies as a function of emotional complexity, helping reconcile puzzling inconsistencies in neuropsychological investigations of emotion recognition. PMID:20207691

From Hippocampus to Whole-Brain: The Role of Integrative Processing in Episodic Memory Retrieval

PubMed Central

Geib, Benjamin R.; Stanley, Matthew L.; Dennis, Nancy A.; Woldorff, Marty G.; Cabeza, Roberto

2017-01-01

Multivariate functional connectivity analyses of neuroimaging data have revealed the importance of complex, distributed interactions between disparate yet interdependent brain regions. Recent work has shown that topological properties of functional brain networks are associated with individual and group differences in cognitive performance, including in episodic memory. After constructing functional whole-brain networks derived from an event-related fMRI study of memory retrieval, we examined differences in functional brain network architecture between forgotten and remembered words. This study yielded three main findings. First, graph theory analyses showed that successfully remembering compared to forgetting was associated with significant changes in the connectivity profile of the left hippocampus and a corresponding increase in efficient communication with the rest of the brain. Second, bivariate functional connectivity analyses indicated stronger interactions between the left hippocampus and a retrieval assembly for remembered versus forgotten items. This assembly included the left precuneus, left caudate, bilateral supramarginal gyrus, and the bilateral dorsolateral superior frontal gyrus. Integrative properties of the retrieval assembly were greater for remembered than forgotten items. Third, whole-brain modularity analyses revealed that successful memory retrieval was marginally significantly associated with a less segregated modular architecture in the network. The magnitude of the decreases in modularity between remembered and forgotten conditions was related to memory performance. These findings indicate that increases in integrative properties at the nodal, retrieval assembly, and whole-brain topological levels facilitate memory retrieval, while also underscoring the potential of multivariate brain connectivity approaches for providing valuable new insights into the neural bases of memory processes. PMID:28112460

Dietary Tocotrienol/γ-Cyclodextrin Complex Increases Mitochondrial Membrane Potential and ATP Concentrations in the Brains of Aged Mice

PubMed Central

Schloesser, Anke; Esatbeyoglu, Tuba; Piegholdt, Stefanie; Dose, Janina; Ikuta, Naoko; Okamoto, Hinako; Ishida, Yoshiyuki; Terao, Keiji; Matsugo, Seiichi; Rimbach, Gerald

2015-01-01

Brain aging is accompanied by a decrease in mitochondrial function. In vitro studies suggest that tocotrienols, including γ- and δ-tocotrienol (T3), may exhibit neuroprotective properties. However, little is known about the effect of dietary T3 on mitochondrial function in vivo. In this study, we monitored the effect of a dietary T3/γ-cyclodextrin complex (T3CD) on mitochondrial membrane potential and ATP levels in the brain of 21-month-old mice. Mice were fed either a control diet or a diet enriched with T3CD providing 100 mg T3 per kg diet for 6 months. Dietary T3CD significantly increased mitochondrial membrane potential and ATP levels compared to those of controls. The increase in MMP and ATP due to dietary T3CD was accompanied by an increase in the protein levels of the mitochondrial transcription factor A (TFAM). Furthermore, dietary T3CD slightly increased the mRNA levels of superoxide dismutase, γ-glutamyl cysteinyl synthetase, and heme oxygenase 1 in the brain. Overall, the present data suggest that T3CD increases TFAM, mitochondrial membrane potential, and ATP synthesis in the brains of aged mice. PMID:26301044

Enhancement of cognitive and neural functions through complex reasoning training: evidence from normal and clinical populations

PubMed Central

Chapman, Sandra B.; Mudar, Raksha A.

2014-01-01

Public awareness of cognitive health is fairly recent compared to physical health. Growing evidence suggests that cognitive training offers promise in augmenting cognitive brain performance in normal and clinical populations. Targeting higher-order cognitive functions, such as reasoning in particular, may promote generalized cognitive changes necessary for supporting the complexities of daily life. This data-driven perspective highlights cognitive and brain changes measured in randomized clinical trials that trained gist reasoning strategies in populations ranging from teenagers to healthy older adults, individuals with brain injury to those at-risk for Alzheimer's disease. The evidence presented across studies support the potential for Gist reasoning training to strengthen cognitive performance in trained and untrained domains and to engage more efficient communication across widespread neural networks that support higher-order cognition. The meaningful benefits of Gist training provide compelling motivation to examine optimal dose for sustained benefits as well as to explore additive benefits of meditation, physical exercise, and/or improved sleep in future studies. PMID:24808834

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.

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.

Advances in Electrophysiological Research

PubMed Central

Kamarajan, Chella; Porjesz, Bernice

2015-01-01

Electrophysiological measures of brain function are effective tools to understand neurocognitive phenomena and sensitive indicators of pathophysiological processes associated with various clinical conditions, including alcoholism. Individuals with alcohol use disorder (AUD) and their high-risk offspring have consistently shown dysfunction in several electrophysiological measures in resting state (i.e., electroencephalogram) and during cognitive tasks (i.e., event-related potentials and event-related oscillations). Researchers have recently developed sophisticated signal-processing techniques to characterize different aspects of brain dynamics, which can aid in identifying the neural mechanisms underlying alcoholism and other related complex disorders. These quantitative measures of brain function also have been successfully used as endophenotypes to identify and help understand genes associated with AUD and related disorders. Translational research also is examining how brain electrophysiological measures potentially can be applied to diagnosis, prevention, and treatment. PMID:26259089

Resting state fMRI entropy probes complexity of brain activity in adults with ADHD.

PubMed

Sokunbi, Moses O; Fung, Wilson; Sawlani, Vijay; Choppin, Sabine; Linden, David E J; Thome, Johannes

2013-12-30

In patients with attention deficit hyperactivity disorder (ADHD), quantitative neuroimaging techniques have revealed abnormalities in various brain regions, including the frontal cortex, striatum, cerebellum, and occipital cortex. Nonlinear signal processing techniques such as sample entropy have been used to probe the regularity of brain magnetoencephalography signals in patients with ADHD. In the present study, we extend this technique to analyse the complex output patterns of the 4 dimensional resting state functional magnetic resonance imaging signals in adult patients with ADHD. After adjusting for the effect of age, we found whole brain entropy differences (P=0.002) between groups and negative correlation (r=-0.45) between symptom scores and mean whole brain entropy values, indicating lower complexity in patients. In the regional analysis, patients showed reduced entropy in frontal and occipital regions bilaterally and a significant negative correlation between the symptom scores and the entropy maps at a family-wise error corrected cluster level of P<0.05 (P=0.001, initial threshold). Our findings support the hypothesis of abnormal frontal-striatal-cerebellar circuits in ADHD and the suggestion that sample entropy is a useful tool in revealing abnormalities in the brain dynamics of patients with psychiatric disorders. © 2013 Elsevier Ireland Ltd. All rights reserved.

Cannabidiol improves brain and liver function in a fulminant hepatic failure-induced model of hepatic encephalopathy in mice

PubMed Central

Avraham, Y; Grigoriadis, NC; Poutahidis, T; Vorobiev, L; Magen, I; Ilan, Y; Mechoulam, R; Berry, EM

2011-01-01

BACKGROUND AND PURPOSE Hepatic encephalopathy is a neuropsychiatric disorder of complex pathogenesis caused by acute or chronic liver failure. We investigated the effects of cannabidiol, a non-psychoactive constituent of Cannabis sativa with anti-inflammatory properties that activates the 5-hydroxytryptamine receptor 5-HT1A, on brain and liver functions in a model of hepatic encephalopathy associated with fulminant hepatic failure induced in mice by thioacetamide. EXPERIMENTAL APPROACH Female Sabra mice were injected with either saline or thioacetamide and were treated with either vehicle or cannabidiol. Neurological and motor functions were evaluated 2 and 3 days, respectively, after induction of hepatic failure, after which brains and livers were removed for histopathological analysis and blood was drawn for analysis of plasma liver enzymes. In a separate group of animals, cognitive function was tested after 8 days and brain 5-HT levels were measured 12 days after induction of hepatic failure. KEY RESULTS Neurological and cognitive functions were severely impaired in thioacetamide-treated mice and were restored by cannabidiol. Similarly, decreased motor activity in thioacetamide-treated mice was partially restored by cannabidiol. Increased plasma levels of ammonia, bilirubin and liver enzymes, as well as enhanced 5-HT levels in thioacetamide-treated mice were normalized following cannabidiol administration. Likewise, astrogliosis in the brains of thioacetamide-treated mice was moderated after cannabidiol treatment. CONCLUSIONS AND IMPLICATIONS Cannabidiol restores liver function, normalizes 5-HT levels and improves brain pathology in accordance with normalization of brain function. Therefore, the effects of cannabidiol may result from a combination of its actions in the liver and brain. PMID:21182490

Cannabidiol improves brain and liver function in a fulminant hepatic failure-induced model of hepatic encephalopathy in mice.

PubMed

Avraham, Y; Grigoriadis, Nc; Poutahidis, T; Vorobiev, L; Magen, I; Ilan, Y; Mechoulam, R; Berry, Em

2011-04-01

Hepatic encephalopathy is a neuropsychiatric disorder of complex pathogenesis caused by acute or chronic liver failure. We investigated the effects of cannabidiol, a non-psychoactive constituent of Cannabis sativa with anti-inflammatory properties that activates the 5-hydroxytryptamine receptor 5-HT(1A) , on brain and liver functions in a model of hepatic encephalopathy associated with fulminant hepatic failure induced in mice by thioacetamide. Female Sabra mice were injected with either saline or thioacetamide and were treated with either vehicle or cannabidiol. Neurological and motor functions were evaluated 2 and 3 days, respectively, after induction of hepatic failure, after which brains and livers were removed for histopathological analysis and blood was drawn for analysis of plasma liver enzymes. In a separate group of animals, cognitive function was tested after 8 days and brain 5-HT levels were measured 12 days after induction of hepatic failure. Neurological and cognitive functions were severely impaired in thioacetamide-treated mice and were restored by cannabidiol. Similarly, decreased motor activity in thioacetamide-treated mice was partially restored by cannabidiol. Increased plasma levels of ammonia, bilirubin and liver enzymes, as well as enhanced 5-HT levels in thioacetamide-treated mice were normalized following cannabidiol administration. Likewise, astrogliosis in the brains of thioacetamide-treated mice was moderated after cannabidiol treatment. Cannabidiol restores liver function, normalizes 5-HT levels and improves brain pathology in accordance with normalization of brain function. Therefore, the effects of cannabidiol may result from a combination of its actions in the liver and brain. © 2011 The Authors. British Journal of Pharmacology © 2011 The British Pharmacological Society.

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 .

Fractal dimension brain morphometry: a novel approach to quantify white matter in traumatic brain injury.

PubMed

Rajagopalan, Venkateswaran; Das, Abhijit; Zhang, Luduan; Hillary, Frank; Wylie, Glenn R; Yue, Guang H

2018-06-16

Traumatic brain injury (TBI) is the main cause of disability in people younger than 35 in the United States. The mechanisms of TBI are complex resulting in both focal and diffuse brain damage. Fractal dimension (FD) is a measure that can characterize morphometric complexity and variability of brain structure especially white matter (WM) structure and may provide novel insights into the injuries evident following TBI. FD-based brain morphometry may provide information on WM structural changes after TBI that is more sensitive to subtle structural changes post injury compared to conventional MRI measurements. Anatomical and diffusion tensor imaging (DTI) data were obtained using a 3 T MRI scanner in subjects with moderate to severe TBI and in healthy controls (HC). Whole brain WM volume, grey matter volume, cortical thickness, cortical area, FD and DTI metrics were evaluated globally and for the left and right hemispheres separately. A neuropsychological test battery sensitive to cognitive impairment associated with traumatic brain injury was performed. TBI group showed lower structural complexity (FD) bilaterally (p < 0.05). No significant difference in either grey matter volume, cortical thickness or cortical area was observed in any of the brain regions between TBI and healthy controls. No significant differences in whole brain WM volume or DTI metrics between TBI and HC groups were observed. Behavioral data analysis revealed that WM FD accounted for a significant amount of variance in executive functioning and processing speed beyond demographic and DTI variables. FD therefore, may serve as a sensitive marker of injury and may play a role in outcome prediction in TBI.

[Peculiarities of cerebral structures functioning in adolescents with achondroplasia].

PubMed

Skripnikov, A A; Dolganova, T I; Aranovich, A M

2013-01-01

Complex neurophysiological examination (rheoencephalography, electroencephalography) was carried out in 12 adolescents 12 to 18 years old in order to reveal the peculiarities of cerebral structures functioning in adolescents with achondroplasia. Some deviations from the normal values were found out: reduced blood filling of the brain vessels in the pools of a. carotis interna and a. vertebralis, rheoencephalographic signs of intracranial hypertension of mild degree and brain cycling characterized by moderate and significant amplitude increase, presence of pathological types (delta-, theta-) of the rhythmics and the reduction of the physiological ones (alpha-, beta-). At the same time the peculiarities of rheoencephalographic indices were observed while functional testings (hypercapnia, hyperoxia). Brain cycling differed from normal values by weaker response to the weight-bearing, mainly in alpha- and beta-ranges.

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.

Network neuroscience

PubMed Central

Bassett, Danielle S; Sporns, Olaf

2017-01-01

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

Brain abnormalities in antisocial individuals: implications for the law.

PubMed

Yang, Yaling; Glenn, Andrea L; Raine, Adrian

2008-01-01

With the increasing popularity in the use of brain imaging on antisocial individuals, an increasing number of brain imaging studies have revealed structural and functional impairments in antisocial, psychopathic, and violent individuals. This review summarizes key findings from brain imaging studies on antisocial/aggressive behavior. Key regions commonly found to be impaired in antisocial populations include the prefrontal cortex (particularly orbitofrontal and dorsolateral prefrontal cortex), superior temporal gyrus, amygdala-hippocampal complex, and anterior cingulate cortex. Key functions of these regions are reviewed to provide a better understanding on how deficits in these regions may predispose to antisocial behavior. Objections to the use of imaging findings in a legal context are outlined, and alternative perspectives raised. It is argued that brain dysfunction is a risk factor for antisocial behavior and that it is likely that imaging will play an increasing (albeit limited) role in legal decision-making. (c) 2008 John Wiley & Sons, Ltd.

The Sea Slug, Pleurobranchaea californica: A Signpost Species in the Evolution of Complex Nervous Systems and Behavior.

PubMed

Gillette, Rhanor; Brown, Jeffrey W

2015-12-01

How and why did complex brain and behavior evolve? Clues emerge from comparative studies of animals with simpler morphology, nervous system, and behavioral economics. The brains of vertebrates, arthropods, and some annelids have highly derived executive structures and function that control downstream, central pattern generators (CPGs) for locomotion, behavioral choice, and reproduction. For the vertebrates, these structures-cortex, basal ganglia, and hypothalamus-integrate topographically mapped sensory inputs with motivation and memory to transmit complex motor commands to relay stations controlling CPG outputs. Similar computations occur in the central complex and mushroom bodies of the arthropods, and in mammals these interactions structure subjective thought and socially based valuations. The simplest model systems available for comparison are opisthobranch molluscs, which have avoided selective pressure for complex bodies, brain, and behavior through potent chemical defenses. In particular, in the sea-slug Pleurobranchaea californica the functions of vertebrates' olfactory bulb and pallium are performed in the peripheral nervous system (PNS) of the chemotactile oral veil. Functions of hypothalamus and basal ganglia are combined in Pleurobranchaea's feeding motor network. The actions of basal ganglia on downstream locomotor regions and spinal CPGs are analogous to Pleurobranchaea's feeding network actions on CPGs for agonist and antagonist behaviors. The nervous systems of opisthobranch and pulmonate gastropods may conserve or reflect relations of the ancestral urbilaterian. Parallels and contrasts in neuronal circuits for action selection in Pleurobranchaea and vertebrates suggest how a basic set of decision circuitry was built upon in evolving segmentation, articulated skeletons, sociality, and highly invested reproductive strategies. They suggest (1) an origin of olfactory bulb and pallium from head-region PNS; (2) modularization of an ancestral feeding network into discrete but interacting executive modules for incentive comparison and decision (basal ganglia), and homeostatic functions (hypothalamus); (3) modification of a multifunctional premotor network for turns and locomotion, and its downstream targets for mid-brain and hind-brain motor areas and spinal CPGs; (4) condensation of a distributed serotonergic network for arousal into the raphe nuclei, with superimposed control by a peptidergic hypothalamic network mediating appetite and arousal; (5) centralization and condensation of the dopaminergic sensory afferents of the PNS, and/or the disperse dopaminergic elements of central CPGs, into the brain nuclei mediating valuation, reward, and motor arousal; and (6) the urbilaterian possessed the basic circuit relations integrating sensation, internal state, and learning for cost-benefit approach-avoidance decisions. © The Author 2015. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

Understanding emotion with brain networks.

PubMed

Pessoa, Luiz

2018-02-01

Emotional processing appears to be interlocked with perception, cognition, motivation, and action. These interactions are supported by the brain's large-scale non-modular anatomical and functional architectures. An important component of this organization involves characterizing the brain in terms of networks. Two aspects of brain networks are discussed: brain networks should be considered as inherently overlapping (not disjoint) and dynamic (not static). Recent work on multivariate pattern analysis shows that affective dimensions can be detected in the activity of distributed neural systems that span cortical and subcortical regions. More broadly, the paper considers how we should think of causation in complex systems like the brain, so as to inform the relationship between emotion and other mental aspects, such as cognition.

From hippocampus to whole-brain: The role of integrative processing in episodic memory retrieval.

PubMed

Geib, Benjamin R; Stanley, Matthew L; Dennis, Nancy A; Woldorff, Marty G; Cabeza, Roberto

2017-04-01

Multivariate functional connectivity analyses of neuroimaging data have revealed the importance of complex, distributed interactions between disparate yet interdependent brain regions. Recent work has shown that topological properties of functional brain networks are associated with individual and group differences in cognitive performance, including in episodic memory. After constructing functional whole-brain networks derived from an event-related fMRI study of memory retrieval, we examined differences in functional brain network architecture between forgotten and remembered words. This study yielded three main findings. First, graph theory analyses showed that successfully remembering compared to forgetting was associated with significant changes in the connectivity profile of the left hippocampus and a corresponding increase in efficient communication with the rest of the brain. Second, bivariate functional connectivity analyses indicated stronger interactions between the left hippocampus and a retrieval assembly for remembered versus forgotten items. This assembly included the left precuneus, left caudate, bilateral supramarginal gyrus, and the bilateral dorsolateral superior frontal gyrus. Integrative properties of the retrieval assembly were greater for remembered than forgotten items. Third, whole-brain modularity analyses revealed that successful memory retrieval was marginally significantly associated with a less segregated modular architecture in the network. The magnitude of the decreases in modularity between remembered and forgotten conditions was related to memory performance. These findings indicate that increases in integrative properties at the nodal, retrieval assembly, and whole-brain topological levels facilitate memory retrieval, while also underscoring the potential of multivariate brain connectivity approaches for providing valuable new insights into the neural bases of memory processes. Hum Brain Mapp 38:2242-2259, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Plasticity of brain wave network interactions and evolution across physiologic states

PubMed Central

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

2015-01-01

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

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.

RMND5 from Xenopus laevis is an E3 ubiquitin-ligase and functions in early embryonic forebrain development.

PubMed

Pfirrmann, Thorsten; Villavicencio-Lorini, Pablo; Subudhi, Abinash K; Menssen, Ruth; Wolf, Dieter H; Hollemann, Thomas

2015-01-01

In Saccharomyces cerevisiae the Gid-complex functions as an ubiquitin-ligase complex that regulates the metabolic switch between glycolysis and gluconeogenesis. In higher organisms six conserved Gid proteins form the CTLH protein-complex with unknown function. Here we show that Rmnd5, the Gid2 orthologue from Xenopus laevis, is an ubiquitin-ligase embedded in a high molecular weight complex. Expression of rmnd5 is strongest in neuronal ectoderm, prospective brain, eyes and ciliated cells of the skin and its suppression results in malformations of the fore- and midbrain. We therefore suggest that Xenopus laevis Rmnd5, as a subunit of the CTLH complex, is a ubiquitin-ligase targeting an unknown factor for polyubiquitination and subsequent proteasomal degradation for proper fore- and midbrain development.

Changes of several brain receptor complexes in the cerebral cortex of patients with Alzheimer disease: probable new potential pharmaceutical targets.

PubMed

Falsafi, Soheil Keihan; Roßner, Steffen; Ghafari, Maryam; Groessl, Michael; Morawski, Markus; Gerner, Christopher; Lubec, Gert

2014-01-01

Although Alzheimer disease (AD) has been linked to defects in major brain receptors, studies thus far have been limited to the determination of receptor subunits or specific ligand binding studies. However, the availability of current technology enables the determination and quantification of brain receptor complexes. Thus, we examined levels of native receptor complexes in the brains of patients with AD. Cortical tissue was obtained from control subjects (n = 12 females and 12 males) and patients with AD (n = 12 females and 12 males) within a 3-h postmortem time period. The tissues were kept frozen until further biochemical analyses. Membrane proteins were extracted and subsequently enriched by ultracentrifugation using a sucrose gradient. Membrane proteins were then electrophoresed onto native gels and immunoblotted using antibodies against individual brain receptors. We found that the levels were comparable for complexes containing GluR2, GluR3 and GluR4 as well as 5-HT1A. Moreover, the levels of complexes containing muscarinic AChR M1, NR1 and GluR1 were significantly increased in male patients with AD. Nicotinic AChRs 4 and 7 as well as dopaminergic receptors D1 and D2 were also increased in males and females with AD. These findings reveal a pattern of altered receptor complex levels that may contribute to the deterioration of the concerted activity of these receptors and thus result in cognitive deficits observed in patients with AD. It should be emphasised that receptor complexes function as working units rather than individual subunits. Thus, the receptor deficits identified may be relevant for the design of experimental therapies. Therefore, specific pharmacological modulation of these receptors is within the pharmaceutical repertoire.

A Complex Interplay of Vitamin B1 and B6 Metabolism with Cognition, Brain Structure, and Functional Connectivity in Older Adults.

PubMed

Jannusch, Kai; Jockwitz, Christiane; Bidmon, Hans-Jürgen; Moebus, Susanne; Amunts, Katrin; Caspers, Svenja

2017-01-01

Aging is associated with brain atrophy, functional brain network reorganization and decline of cognitive performance, albeit characterized by high interindividual variability. Among environmental influencing factors accounting for this variability, nutrition and particularly vitamin supply is thought to play an important role. While evidence exists that supplementation of vitamins B6 and B1 might be beneficial for cognition and brain structure, at least in deficient states and neurodegenerative diseases, little is known about this relation during healthy aging and in relation to reorganization of functional brain networks. We thus assessed the relation between blood levels of vitamins B1 and B6 and cognitive performance, cortical folding, and functional resting-state connectivity in a large sample of older adults ( N > 600; age: 55-85 years), drawn from the population-based 1000BRAINS study. In addition to blood sampling, subjects underwent structural and functional resting-state neuroimaging as well as extensive neuropsychological testing in the domains of executive functions, (working) memory, attention, and language. Brain regions showing changes in the local gyrification index as calculated using FreeSurfer in relation to vitamin levels were used for subsequent seed-based resting-state functional connectivity analysis. For B6, a positive correlation with local cortical folding was found throughout the brain, while only slight changes in functional connectivity were observed. Contrarily, for B1, a negative correlation with cortical folding as well as problem solving and visuo-spatial working memory performance was found, which was accompanied by pronounced increases of interhemispheric and decreases of intrahemispheric functional connectivity. While the effects for B6 expand previous knowledge on beneficial effects of B6 supplementation on brain structure, they also showed that additional effects on cognition might not be recognizable in healthy older subjects with normal B6 blood levels. The cortical atrophy and pronounced functional reorganization associated with B1, contrarily, was more in line with the theory of a disturbed B1 metabolism in older adults, leading to B1 utilization deficits, and thus, an effective B1 deficiency in the brain, despite normal to high-normal blood levels.

A Complex Interplay of Vitamin B1 and B6 Metabolism with Cognition, Brain Structure, and Functional Connectivity in Older Adults

PubMed Central

Jannusch, Kai; Jockwitz, Christiane; Bidmon, Hans-Jürgen; Moebus, Susanne; Amunts, Katrin; Caspers, Svenja

2017-01-01

Aging is associated with brain atrophy, functional brain network reorganization and decline of cognitive performance, albeit characterized by high interindividual variability. Among environmental influencing factors accounting for this variability, nutrition and particularly vitamin supply is thought to play an important role. While evidence exists that supplementation of vitamins B6 and B1 might be beneficial for cognition and brain structure, at least in deficient states and neurodegenerative diseases, little is known about this relation during healthy aging and in relation to reorganization of functional brain networks. We thus assessed the relation between blood levels of vitamins B1 and B6 and cognitive performance, cortical folding, and functional resting-state connectivity in a large sample of older adults (N > 600; age: 55–85 years), drawn from the population-based 1000BRAINS study. In addition to blood sampling, subjects underwent structural and functional resting-state neuroimaging as well as extensive neuropsychological testing in the domains of executive functions, (working) memory, attention, and language. Brain regions showing changes in the local gyrification index as calculated using FreeSurfer in relation to vitamin levels were used for subsequent seed-based resting-state functional connectivity analysis. For B6, a positive correlation with local cortical folding was found throughout the brain, while only slight changes in functional connectivity were observed. Contrarily, for B1, a negative correlation with cortical folding as well as problem solving and visuo-spatial working memory performance was found, which was accompanied by pronounced increases of interhemispheric and decreases of intrahemispheric functional connectivity. While the effects for B6 expand previous knowledge on beneficial effects of B6 supplementation on brain structure, they also showed that additional effects on cognition might not be recognizable in healthy older subjects with normal B6 blood levels. The cortical atrophy and pronounced functional reorganization associated with B1, contrarily, was more in line with the theory of a disturbed B1 metabolism in older adults, leading to B1 utilization deficits, and thus, an effective B1 deficiency in the brain, despite normal to high-normal blood levels. PMID:29163003

The blood-brain barrier: an engineering perspective

PubMed Central

Wong, Andrew D.; Ye, Mao; Levy, Amanda F.; Rothstein, Jeffrey D.; Bergles, Dwight E.; Searson, Peter C.

2013-01-01

It has been more than 100 years since Paul Ehrlich reported that various water-soluble dyes injected into the circulation did not enter the brain. Since Ehrlich's first experiments, only a small number of molecules, such as alcohol and caffeine have been found to cross the blood-brain barrier, and this selective permeability remains the major roadblock to treatment of many central nervous system diseases. At the same time, many central nervous system diseases are associated with disruption of the blood-brain barrier that can lead to changes in permeability, modulation of immune cell transport, and trafficking of pathogens into the brain. Therefore, advances in our understanding of the structure and function of the blood-brain barrier are key to developing effective treatments for a wide range of central nervous system diseases. Over the past 10 years it has become recognized that the blood-brain barrier is a complex, dynamic system that involves biomechanical and biochemical signaling between the vascular system and the brain. Here we reconstruct the structure, function, and transport properties of the blood-brain barrier from an engineering perspective. New insight into the physics of the blood-brain barrier could ultimately lead to clinical advances in the treatment of central nervous system diseases. PMID:24009582

Unlocking the Secrets of Brain Signals (4K)

ScienceCinema

None

2018-06-21

Scientists have for the first time determined, at atomic-scale resolution, the 3-D structure of a protein complex that provides the ultrafast trigger for chemicals messages sent between nerve cells in our brains. The discovery, which provides a new understanding of the molecular machinery driving brain function, builds on decades of research at Stanford University, the Stanford School of Medicine and SLAC National Accelerator Laboratory was made possible by SLAC’s Linac Coherent Light Source, an ultrabright X-ray laser.

Unlocking the Secrets of Brain Signals (4K)

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

None

2015-08-17

Scientists have for the first time determined, at atomic-scale resolution, the 3-D structure of a protein complex that provides the ultrafast trigger for chemicals messages sent between nerve cells in our brains. The discovery, which provides a new understanding of the molecular machinery driving brain function, builds on decades of research at Stanford University, the Stanford School of Medicine and SLAC National Accelerator Laboratory was made possible by SLAC’s Linac Coherent Light Source, an ultrabright X-ray laser.

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

Colour processing in complex environments: insights from the visual system of bees

PubMed Central

Dyer, Adrian G.; Paulk, Angelique C.; Reser, David H.

2011-01-01

Colour vision enables animals to detect and discriminate differences in chromatic cues independent of brightness. How the bee visual system manages this task is of interest for understanding information processing in miniaturized systems, as well as the relationship between bee pollinators and flowering plants. Bees can quickly discriminate dissimilar colours, but can also slowly learn to discriminate very similar colours, raising the question as to how the visual system can support this, or whether it is simply a learning and memory operation. We discuss the detailed neuroanatomical layout of the brain, identify probable brain areas for colour processing, and suggest that there may be multiple systems in the bee brain that mediate either coarse or fine colour discrimination ability in a manner dependent upon individual experience. These multiple colour pathways have been identified along both functional and anatomical lines in the bee brain, providing us with some insights into how the brain may operate to support complex colour discrimination behaviours. PMID:21147796

A comprehensive neuropsychological mapping battery for functional magnetic resonance imaging.

PubMed

Karakas, Sirel; Baran, Zeynel; Ceylan, Arzu Ozkan; Tileylioglu, Emre; Tali, Turgut; Karakas, Hakki Muammer

2013-11-01

Existing batteries for FMRI do not precisely meet the criteria for comprehensive mapping of cognitive functions within minimum data acquisition times using standard scanners and head coils. The goal was to develop a battery of neuropsychological paradigms for FMRI that can also be used in other brain imaging techniques and behavioural research. Participants were 61 healthy, young adult volunteers (48 females and 13 males, mean age: 22.25 ± 3.39 years) from the university community. The battery included 8 paradigms for basic (visual, auditory, sensory-motor, emotional arousal) and complex (language, working memory, inhibition/interference control, learning) cognitive functions. Imaging was performed using standard functional imaging capabilities (1.5-T MR scanner, standard head coil). Structural and functional data series were analysed using Brain Voyager QX2.9 and Statistical Parametric Mapping-8. For basic processes, activation centres for individuals were within a distance of 3-11 mm of the group centres of the target regions and for complex cognitive processes, between 7 mm and 15 mm. Based on fixed-effect and random-effects analyses, the distance between the activation centres was 0-4 mm. There was spatial variability between individual cases; however, as shown by the distances between the centres found with fixed-effect and random-effects analyses, the coordinates for individual cases can be used to represent those of the group. The findings show that the neuropsychological brain mapping battery described here can be used in basic science studies that investigate the relationship of the brain to the mind and also as functional localiser in clinical studies for diagnosis, follow-up and pre-surgical mapping. © 2013.

The impact of symptomatic mild traumatic brain injury on complex everyday activities and the link with alterations in cerebral functioning: Exploratory case studies.

PubMed

Bottari, Carolina; Gosselin, Nadia; Chen, Jen-Kai; Ptito, Alain

2017-07-01

The objective of the study was to explore the neurophysiological correlates of altered functional independence using functional magnetic resonance imaging (fMRI) and event-related potentials (ERP) after a mild traumatic brain injury (mTBI). The participants consisted of three individuals with symptomatic mTBI (3.9 ± 3.6 months post-mTBI) and 12 healthy controls. The main measures used were the Instrumental Activities of Daily Living (IADL) Profile observation-based assessment; a visual externally ordered working memory task combined to event-related potentials (ERP) and fMRI recordings; neuropsychological tests; post-concussion symptoms questionnaires; and the Activities of Daily Living (ADL) Profile interview. Compared to normal controls, all three patients had difficulty with a real-world complex budgeting activity due to deficits in planning, ineffective strategy use and/or a prolonged time to detect and correct errors. Reduced activations in the right mid-dorsolateral prefrontal cortex on fMRI as well as abnormal frontal or parietal components of the ERP occurred alongside these deficits. Results of this exploratory study suggest that reduced independence in complex everyday activities in symptomatic mTBI may be at least partly explained by a decrease in brain activation in the prefrontal cortex, abnormal ERP, or slower reaction times on working memory tasks. The study presents an initial attempt at combining research in neuroscience with ecological real-world evaluation research to further our understanding of the difficulties in complex everyday activities experienced by individuals with mTBI.

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

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.

Functional brain imaging and bioacoustics in the Bottlenose dolphins, Tursiops truncatus

NASA Astrophysics Data System (ADS)

Ridgway, Sam; Finneran, James; Carder, Donald; van Bonn, William; Smith, Cynthia; Houser, Dorian; Mattrey, Robert; Hoh, Carl

2003-10-01

The dolphin brain is the central processing computer for a complex and effective underwater echolocation and communication system. Until now, it has not been possible to study or diagnose disorders of the dolphin brain employing modern functional imaging methods like those used in human medicine. Our most recent studies employ established methods such as behavioral tasks, physiological observations, and computed tomography (CT) and, for the first time, single photon emission computed tomography (SPECT), and positron emission tomography (PET). Trained dolphins slide out of their enclosure on to a mat and are transported by trainers and veterinarians to the laboratory for injection of a ligand. Following ligand injection, brief experiments include trained vocal responses to acoustic, visual, or tactile stimuli. We have used the ligand technetium (Tc-99m) biscisate (Neurolite) to image circulatory flow by SPECT. Fluro-deoxy-d-glucose (18-F-FDG) has been employed to image brain metabolism with PET. Veterinarians carefully monitored dolphins during and after the procedure. Through these methods, we have demonstrated that functional imaging can be employed safely and productively with dolphins to obtain valuable information on brain structure and function for medical and research purposes. Hemispheric differences and variations in flow and metabolism in different brain areas will be shown.

Stress, Anxiety, and Immunomodulation: A Pharmacological Analysis.

PubMed

Ray, A; Gulati, K; Rai, N

2017-01-01

Stress and stressful events are common occurrences in our daily lives and such aversive situations bring about complex changes in the biological system. Such stress responses influence the brain and behavior, neuroendocrine and immune systems, and these responses orchestrate to increase or decrease the ability of the organism to cope with such stressors. The brain via expression of complex behavioral paradigms controls peripheral responses to stress and a bidirectional link exists in the modulation of stress effects. Anxiety is a common neurobehavioral correlate of a variety of stressors, and both acute and chronic stress exposure could precipitate anxiety disorders. Psychoneuroimmunology involves interactions between the brain and the immune system, and it is now being increasingly recognized that the immune system could contribute to the neurobehavioral responses to stress. Studies have shown that the brain and its complex neurotransmitter networks could influence immune function, and there could be a possible link between anxiogenesis and immunomodulation during stress. Physiological and pharmacological data have highlighted this concept, and the present review gives an overview of the relationship between stress, anxiety, and immune responsiveness. © 2017 Elsevier Inc. All rights reserved.

Progesterone Receptors: Form and Function in Brain

PubMed Central

Brinton, Roberta Diaz; Thompson, Richard F.; Foy, Michael R.; Baudry, Michel; Wang, JunMing; Finch, Caleb E; Morgan, Todd E.; Stanczyk, Frank Z.; Pike, Christian J.; Nilsen, Jon

2008-01-01

Emerging data indicate that progesterone has multiple non-reproductive functions in the central nervous system to regulate cognition, mood, inflammation, mitochondrial function, neurogenesis and regeneration, myelination and recovery from traumatic brain injury. Progesterone-regulated neural responses are mediated by an array of progesterone receptors (PR) that include the classic nuclear PRA and PRB receptors and splice variants of each, the seven transmembrane domain 7TMPRβ and the membrane-associated 25-Dx PR (PGRMC1). These PRs induce classic regulation of gene expression while also transducing signaling cascades that originate at the cell membrane and ultimately activate transcription factors. Remarkably, PRs are broadly expressed throughout the brain and can be detected in every neural cell type. The distribution of PRs beyond hypothalamic borders, suggests a much broader role of progesterone in regulating neural function. Despite the large body of evidence regarding progesterone regulation of reproductive behaviors and estrogen-inducible responses as well as effects of progesterone metabolite neurosteroids, much remains to be discovered regarding the functional outcomes resulting from activation of the complex array of PRs in brain by gonadally and / or glial derived progesterone. Moreover, the impact of clinically used progestogens and developing selective PR modulators for targeted outcomes in brain is a critical avenue of investigation as the non-reproductive functions of PRs have far-reaching implications for hormone therapy to maintain neurological health and function throughout menopausal aging. PMID:18374402

Candidate gene screen in the red flour beetle Tribolium reveals six3 as ancient regulator of anterior median head and central complex development.

PubMed

Posnien, Nico; Koniszewski, Nikolaus Dieter Bernhard; Hein, Hendrikje Jeannette; Bucher, Gregor

2011-12-01

Several highly conserved genes play a role in anterior neural plate patterning of vertebrates and in head and brain patterning of insects. However, head involution in Drosophila has impeded a systematic identification of genes required for insect head formation. Therefore, we use the red flour beetle Tribolium castaneum in order to comprehensively test the function of orthologs of vertebrate neural plate patterning genes for a function in insect head development. RNAi analysis reveals that most of these genes are indeed required for insect head capsule patterning, and we also identified several genes that had not been implicated in this process before. Furthermore, we show that Tc-six3/optix acts upstream of Tc-wingless, Tc-orthodenticle1, and Tc-eyeless to control anterior median development. Finally, we demonstrate that Tc-six3/optix is the first gene known to be required for the embryonic formation of the central complex, a midline-spanning brain part connected to the neuroendocrine pars intercerebralis. These functions are very likely conserved among bilaterians since vertebrate six3 is required for neuroendocrine and median brain development with certain mutations leading to holoprosencephaly.

Candidate Gene Screen in the Red Flour Beetle Tribolium Reveals Six3 as Ancient Regulator of Anterior Median Head and Central Complex Development

PubMed Central

Hein, Hendrikje Jeannette; Bucher, Gregor

2011-01-01

Several highly conserved genes play a role in anterior neural plate patterning of vertebrates and in head and brain patterning of insects. However, head involution in Drosophila has impeded a systematic identification of genes required for insect head formation. Therefore, we use the red flour beetle Tribolium castaneum in order to comprehensively test the function of orthologs of vertebrate neural plate patterning genes for a function in insect head development. RNAi analysis reveals that most of these genes are indeed required for insect head capsule patterning, and we also identified several genes that had not been implicated in this process before. Furthermore, we show that Tc-six3/optix acts upstream of Tc-wingless, Tc-orthodenticle1, and Tc-eyeless to control anterior median development. Finally, we demonstrate that Tc-six3/optix is the first gene known to be required for the embryonic formation of the central complex, a midline-spanning brain part connected to the neuroendocrine pars intercerebralis. These functions are very likely conserved among bilaterians since vertebrate six3 is required for neuroendocrine and median brain development with certain mutations leading to holoprosencephaly. PMID:22216011

Neural stem cells and neuro/gliogenesis in the central nervous system: understanding the structural and functional plasticity of the developing, mature, and diseased brain.

PubMed

Yamaguchi, Masahiro; Seki, Tatsunori; Imayoshi, Itaru; Tamamaki, Nobuaki; Hayashi, Yoshitaka; Tatebayashi, Yoshitaka; Hitoshi, Seiji

2016-05-01

Neurons and glia in the central nervous system (CNS) originate from neural stem cells (NSCs). Knowledge of the mechanisms of neuro/gliogenesis from NSCs is fundamental to our understanding of how complex brain architecture and function develop. NSCs are present not only in the developing brain but also in the mature brain in adults. Adult neurogenesis likely provides remarkable plasticity to the mature brain. In addition, recent progress in basic research in mental disorders suggests an etiological link with impaired neuro/gliogenesis in particular brain regions. Here, we review the recent progress and discuss future directions in stem cell and neuro/gliogenesis biology by introducing several topics presented at a joint meeting of the Japanese Association of Anatomists and the Physiological Society of Japan in 2015. Collectively, these topics indicated that neuro/gliogenesis from NSCs is a common event occurring in many brain regions at various ages in animals. Given that significant structural and functional changes in cells and neural networks are accompanied by neuro/gliogenesis from NSCs and the integration of newly generated cells into the network, stem cell and neuro/gliogenesis biology provides a good platform from which to develop an integrated understanding of the structural and functional plasticity that underlies the development of the CNS, its remodeling in adulthood, and the recovery from diseases that affect it.

Topodynamics of metastable brains

NASA Astrophysics Data System (ADS)

Tozzi, Arturo; Peters, James F.; Fingelkurts, Andrew A.; Fingelkurts, Alexander A.; Marijuán, Pedro C.

2017-07-01

The brain displays both the anatomical features of a vast amount of interconnected topological mappings as well as the functional features of a nonlinear, metastable system at the edge of chaos, equipped with a phase space where mental random walks tend towards lower energetic basins. Nevertheless, with the exception of some advanced neuro-anatomic descriptions and present-day connectomic research, very few studies have been addressing the topological path of a brain embedded or embodied in its external and internal environment. Herein, by using new formal tools derived from algebraic topology, we provide an account of the metastable brain, based on the neuro-scientific model of Operational Architectonics of brain-mind functioning. We introduce a ;topodynamic; description that shows how the relationships among the countless intertwined spatio-temporal levels of brain functioning can be assessed in terms of projections and mappings that take place on abstract structures, equipped with different dimensions, curvatures and energetic constraints. Such a topodynamical approach, apart from providing a biologically plausible model of brain function that can be operationalized, is also able to tackle the issue of a long-standing dichotomy: it throws indeed a bridge between the subjective, immediate datum of the naïve complex of sensations and mentations and the objective, quantitative, data extracted from experimental neuro-scientific procedures. Importantly, it opens the door to a series of new predictions and future directions of advancement for neuroscientific research.

Functional interactions of HIV-infection and methamphetamine dependence during motor programming.

PubMed

Archibald, Sarah L; Jacobson, Mark W; Fennema-Notestine, Christine; Ogasawara, Miki; Woods, Steven P; Letendre, Scott; Grant, Igor; Jernigan, Terry L

2012-04-30

Methamphetamine (METH) dependence is frequently comorbid with HIV infection and both have been linked to alterations of brain structure and function. In a previous study, we showed that the brain volume loss characteristic of HIV infection contrasts with METH-related volume increases in striatum and parietal cortex, suggesting distinct neurobiological responses to HIV and METH (Jernigan et al., 2005). Functional magnetic resonance imaging (fMRI) has the potential to reveal functional interactions between the effects of HIV and METH. In the present study, 50 participants were studied in four groups: an HIV+ group, a recently METH-dependent group, a dually affected group, and a group of unaffected community comparison subjects. An fMRI paradigm consisting of motor sequencing tasks of varying levels of complexity was administered to examine blood oxygenation level dependent (BOLD) changes. Within all groups, activity increased significantly with increasing task complexity in large clusters within sensorimotor and parietal cortex, basal ganglia, cerebellum, and cingulate. The task complexity effect was regressed on HIV status, METH status, and the HIV×METH interaction term in a simultaneous multiple regression. HIV was associated with less complexity-related activation in striatum, whereas METH was associated with less complexity-related activation in parietal regions. Significant interaction effects were observed in both cortical and subcortical regions; and, contrary to expectations, the complexity-related activation was less aberrant in dually affected than in single risk participants, in spite of comparable levels of neurocognitive impairment among the clinical groups. Thus, HIV and METH dependence, perhaps through their effects on dopaminergic systems, may have opposing functional effects on neural circuits involved in motor programming. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Neuropsychological Investigation of Motor Impairments in Autism

PubMed Central

Duffield, Tyler; Trontel, Haley; Bigler, Erin D.; Froehlich, Alyson; Prigge, Molly B.; Travers, Brittany; Green, Ryan R.; Cariello, Annahir N.; Cooperrider, Jason; Nielsen, Jared; Alexander, Andrew; Anderson, Jeffrey; Fletcher, P. Thomas; Lange, Nicholas; Zielinski, Brandon; Lainhart, Janet

2013-01-01

It is unclear how standardized neuropsychological measures of motor function relate to brain volumes of motor regions in autism spectrum disorder (ASD). An all male sample composed of 59 ASD and 30 controls (ages 5–33 years) completed three measures of motor function: strength of grip (SOG), finger tapping test (FTT), and grooved peg-board test (GPT). Likewise, all participants underwent magnetic resonance imaging with region of interest (ROI) volumes obtained to include the following regions: motor cortex (pre-central gyrus), somatosensory cortex (post-central gyrus), thalamus, basal ganglia, cerebellum and caudal middle frontal gyrus. These traditional neuropsychological measures of motor function are assumed to differ in motor complexity with GPT requiring the most followed by FTT and SOG. Performance by ASD participants on the GPT and FTT differed significantly from controls, with the largest effect size differences observed on the more complex GPT task. Differences on the SOG task between the two groups were non-significant. Since more complex motor tasks tap more complex networks, poorer GPT performance by those with ASD may reflect less efficient motor networks. There was no gross pathology observed in classic motor areas of the brain in ASD, as region of interest (ROI) volumes did not differ, but FTT was negatively related to motor cortex volume in ASD. The results suggest a hierarchical motor disruption in ASD, with difficulties evident only in more complex tasks as well as a potential anomalous size-function relation in motor cortex in ASD. PMID:23985036

Effect of Error Augmentation on Brain Activation and Motor Learning of a Complex Locomotor Task

PubMed Central

Marchal-Crespo, Laura; Michels, Lars; Jaeger, Lukas; López-Olóriz, Jorge; Riener, Robert

2017-01-01

Up to date, the functional gains obtained after robot-aided gait rehabilitation training are limited. Error augmenting strategies have a great potential to enhance motor learning of simple motor tasks. However, little is known about the effect of these error modulating strategies on complex tasks, such as relearning to walk after a neurologic accident. Additionally, neuroimaging evaluation of brain regions involved in learning processes could provide valuable information on behavioral outcomes. We investigated the effect of robotic training strategies that augment errors—error amplification and random force disturbance—and training without perturbations on brain activation and motor learning of a complex locomotor task. Thirty-four healthy subjects performed the experiment with a robotic stepper (MARCOS) in a 1.5 T MR scanner. The task consisted in tracking a Lissajous figure presented on a display by coordinating the legs in a gait-like movement pattern. Behavioral results showed that training without perturbations enhanced motor learning in initially less skilled subjects, while error amplification benefited better-skilled subjects. Training with error amplification, however, hampered transfer of learning. Randomly disturbing forces induced learning and promoted transfer in all subjects, probably because the unexpected forces increased subjects' attention. Functional MRI revealed main effects of training strategy and skill level during training. A main effect of training strategy was seen in brain regions typically associated with motor control and learning, such as, the basal ganglia, cerebellum, intraparietal sulcus, and angular gyrus. Especially, random disturbance and no perturbation lead to stronger brain activation in similar brain regions than error amplification. Skill-level related effects were observed in the IPS, in parts of the superior parietal lobe (SPL), i.e., precuneus, and temporal cortex. These neuroimaging findings indicate that gait-like motor learning depends on interplay between subcortical, cerebellar, and fronto-parietal brain regions. An interesting observation was the low activation observed in the brain's reward system after training with error amplification compared to training without perturbations. Our results suggest that to enhance learning of a locomotor task, errors should be augmented based on subjects' skill level. The impacts of these strategies on motor learning, brain activation, and motivation in neurological patients need further investigation. PMID:29021739

Brain volumes predict neurodevelopment in adolescents after surgery for congenital heart disease.

PubMed

von Rhein, Michael; Buchmann, Andreas; Hagmann, Cornelia; Huber, Reto; Klaver, Peter; Knirsch, Walter; Latal, Beatrice

2014-01-01

Patients with complex congenital heart disease are at risk for neurodevelopmental impairments. Evidence suggests that brain maturation can be delayed and pre- and postoperative brain injury may occur, and there is limited information on the long-term effect of congenital heart disease on brain development and function in adolescent patients. At a mean age of 13.8 years, 39 adolescent survivors of childhood cardiopulmonary bypass surgery with no structural brain lesions evident through conventional cerebral magnetic resonance imaging and 32 healthy control subjects underwent extensive neurodevelopmental assessment and cerebral magnetic resonance imaging. Cerebral scans were analysed quantitatively using surface-based and voxel-based morphometry. Compared with control subjects, patients had lower total brain (P = 0.003), white matter (P = 0.004) and cortical grey matter (P = 0.005) volumes, whereas cerebrospinal fluid volumes were not different. Regional brain volume reduction ranged from 5.3% (cortical grey matter) to 11% (corpus callosum). Adolescents with cyanotic heart disease showed more brain volume loss than those with acyanotic heart disease, particularly in the white matter, thalami, hippocampi and corpus callosum (all P-values < 0.05). Brain volume reduction correlated significantly with cognitive, motor and executive functions (grey matter: P < 0.05, white matter: P < 0.01). Our findings suggest that there are long-lasting cerebral changes in adolescent survivors of cardiopulmonary bypass surgery for congenital heart disease and that these changes are associated with functional outcome.

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.

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

Emotional Prosody Processing in Epilepsy: Some Insights on Brain Reorganization.

PubMed

Alba-Ferrara, Lucy; Kochen, Silvia; Hausmann, Markus

2018-01-01

Drug resistant epilepsy is one of the most complex, multifactorial and polygenic neurological syndrome. Besides its dynamicity and variability, it still provides us with a model to study brain-behavior relationship, giving cues on the anatomy and functional representation of brain function. Given that onset zone of focal epileptic seizures often affects different anatomical areas, cortical but limited to one hemisphere, this condition also let us study the functional differences of the left and right cerebral hemispheres. One lateralized function in the human brain is emotional prosody, and it can be a useful ictal sign offering hints on the location of the epileptogenic zone. Besides its importance for effective communication, prosody is not considered an eloquent domain, making resective surgery on its neural correlates feasible. We performed an Electronic databases search (Medline and PsychINFO) from inception to July 2017 for studies about prosody in epilepsy. The search terms included "epilepsy," "seizure," "emotional prosody," and "vocal affect." This review focus on emotional prosody processing in epilepsy as it can give hints regarding plastic functional changes following seizures (preoperatively), resection (post operatively), and also as an ictal sign enabling the assessment of dynamic brain networks. Moreover, it is argued that such reorganization can help to preserve the expression and reception of emotional prosody as a central skill to develop appropriate social interactions.

The "silent" imprint of musical training.

PubMed

Klein, Carina; Liem, Franziskus; Hänggi, Jürgen; Elmer, Stefan; Jäncke, Lutz

2016-02-01

Playing a musical instrument at a professional level is a complex multimodal task requiring information integration between different brain regions supporting auditory, somatosensory, motor, and cognitive functions. These kinds of task-specific activations are known to have a profound influence on both the functional and structural architecture of the human brain. However, until now, it is widely unknown whether this specific imprint of musical practice can still be detected during rest when no musical instrument is used. Therefore, we applied high-density electroencephalography and evaluated whole-brain functional connectivity as well as small-world topologies (i.e., node degree) during resting state in a sample of 15 professional musicians and 15 nonmusicians. As expected, musicians demonstrate increased intra- and interhemispheric functional connectivity between those brain regions that are typically involved in music perception and production, such as the auditory, the sensorimotor, and prefrontal cortex as well as Broca's area. In addition, mean connectivity within this specific network was positively related to musical skill and the total number of training hours. Thus, we conclude that musical training distinctively shapes intrinsic functional network characteristics in such a manner that its signature can still be detected during a task-free condition. Hum Brain Mapp 37:536-546, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Temporal fractal analysis of the rs-BOLD signal identifies brain abnormalities in autism spectrum disorder.

PubMed

Dona, Olga; Hall, Geoffrey B; Noseworthy, Michael D

2017-01-01

Brain connectivity in autism spectrum disorders (ASD) has proven difficult to characterize due to the heterogeneous nature of the spectrum. Connectivity in the brain occurs in a complex, multilevel and multi-temporal manner, driving the fluctuations observed in local oxygen demand. These fluctuations can be characterized as fractals, as they auto-correlate at different time scales. In this study, we propose a model-free complexity analysis based on the fractal dimension of the rs-BOLD signal, acquired with magnetic resonance imaging. The fractal dimension can be interpreted as measure of signal complexity and connectivity. Previous studies have suggested that reduction in signal complexity can be associated with disease. Therefore, we hypothesized that a detectable difference in rs-BOLD signal complexity could be observed between ASD patients and Controls. Anatomical and functional data from fifty-five subjects with ASD (12.7 ± 2.4 y/o) and 55 age-matched (14.1 ± 3.1 y/o) healthy controls were accessed through the NITRC database and the ABIDE project. Subjects were scanned using a 3T GE Signa MRI and a 32-channel RF-coil. Axial FSPGR-3D images were used to prescribe rs-BOLD (TE/TR = 30/2000ms) where 300 time points were acquired. Motion correction was performed on the functional data and anatomical and functional images were aligned and spatially warped to the N27 standard brain atlas. Fractal analysis, performed on a grey matter mask, was done by estimating the Hurst exponent in the frequency domain using a power spectral density approach and refining the estimation in the time domain with de-trended fluctuation analysis and signal summation conversion methods. Voxel-wise fractal dimension (FD) was calculated for every subject in the control group and in the ASD group to create ROI-based Z-scores for the ASD patients. Voxel-wise validation of FD normality across controls was confirmed, and non-Gaussian voxels were eliminated from subsequent analysis. To maintain a 95% confidence level, only regions where Z-score values were at least 2 standard deviations away from the mean (i.e. where |Z| > 2.0) were included in the analysis. We found that the main regions, where signal complexity significantly decreased among ASD patients, were the amygdala (p = 0.001), the vermis (p = 0.02), the basal ganglia (p = 0.01) and the hippocampus (p = 0.02). No regions reported significant increase in signal complexity in this study. Our findings were correlated with ADIR and ADOS assessment tools, reporting the highest correlation with the ADOS metrics. Brain connectivity is best modeled as a complex system. Therefore, a measure of complexity as the fractal dimension of fluctuations in brain oxygen demand and utilization could provide important information about connectivity issues in ASD. Moreover, this technique can be used in the characterization of a single subject, with respect to controls, without the need for group analysis. Our novel approach provides an ideal avenue for personalized diagnostics, thus providing unique patient specific assessment that could help in individualizing treatments.

Decreased functional connectivity in schizophrenia: The relationship between social functioning, social cognition and graph theoretical network measures.

PubMed

Erdeniz, Burak; Serin, Emin; İbadi, Yelda; Taş, Cumhur

2017-12-30

Schizophrenia is a complex disorder in which abnormalities in brain connectivity and social functioning play a central role. The aim of this study is to explore small-world network properties, and understand their relationship with social functioning and social cognition in the context of schizophrenia, by testing functional connectivity differences in network properties and its relation to clinical behavioral measures. Resting-state fMRI time series data were acquired from 23 patients diagnosed with schizophrenia and 23 healthy volunteers. The results revealed that patients with schizophrenia show significantly decreased connectivity between a range of brain regions, particularly involving connections among the right orbitofrontal cortex, bilateral putamen and left amygdala. Furthermore, topological properties of functional brain networks in patients with schizophrenia were characterized by reduced path length compared to healthy controls; however, no significant difference was found for clustering coefficient, local efficiency or global efficiency. Additionally, we found that nodal efficiency of the amygdala and the putamen were significantly correlated with the independence-performance subscale of social functioning scale (SFC), and Reading the Mind in the Eyes test; however, the correlations do not survive correction for multiple comparison. The current results help to clarify the relationship between social functioning deficits and topological brain measures in schizophrenia. Copyright © 2017 Elsevier B.V. All rights reserved.

Embryonic blood-cerebrospinal fluid barrier formation and function

PubMed Central

Bueno, David; Parvas, Maryam; Hermelo, Ismaïl; Garcia-Fernàndez, Jordi

2014-01-01

During embryonic development and adult life, brain cavities and ventricles are filled with cerebrospinal fluid (CSF). CSF has attracted interest as an active signaling medium that regulates brain development, homeostasis and disease. CSF is a complex protein-rich fluid containing growth factors and signaling molecules that regulate multiple cell functions in the central nervous system (CNS). The composition and substance concentrations of CSF are tightly controlled. In recent years, it has been demonstrated that embryonic CSF (eCSF) has a key function as a fluid pathway for delivering diffusible signals to the developing brain, thus contributing to the proliferation, differentiation and survival of neural progenitor cells, and to the expansion and patterning of the brain. From fetal stages through to adult life, CSF is primarily produced by the choroid plexus. The development and functional activities of the choroid plexus and other blood–brain barrier (BBB) systems in adults and fetuses have been extensively analyzed. However, eCSF production and control of its homeostasis in embryos, from the closure of the anterior neuropore when the brain cavities become physiologically sealed, to the formation of the functional fetal choroid plexus, has not been studied in as much depth and remains open to debate. This review brings together the existing literature, some of which is based on experiments conducted by our research group, concerning the formation and function of a temporary embryonic blood–CSF barrier in the context of the crucial roles played by the molecules in eCSF. PMID:25389383

Cannabis use and memory brain function in adolescent boys: a cross-sectional multicenter functional magnetic resonance imaging study.

PubMed

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

2010-06-01

Early-onset cannabis use has been associated with later use/abuse, mental health problems (psychosis, depression), and abnormal development of cognition and brain function. During adolescence, ongoing neurodevelopmental maturation and experience shape the neural circuitry underlying complex cognitive functions such as memory and executive control. Prefrontal and temporal regions are critically involved in these functions. Maturational processes leave these brain areas prone to the potentially harmful effects of cannabis use. We performed a two-site (United States and The Netherlands; pooled data) functional magnetic resonance imaging (MRI) study with a cross-sectional design, investigating the effects of adolescent cannabis use on working memory (WM) and associative memory (AM) brain function in 21 abstinent but frequent cannabis-using boys (13-19) years of age and compared them with 24 nonusing peers. Brain activity during WM was assessed before and after rule-based learning (automatization). AM was assessed using a pictorial hippocampal-dependent memory task. Cannabis users performed normally on both memory tasks. During WM assessment, cannabis users showed excessive activity in prefrontal regions when a task was novel, whereas automatization of the task reduced activity to the same level in users and controls. No effect of cannabis use on AM-related brain function was found. In adolescent cannabis users, the WM system was overactive during a novel task, suggesting functional compensation. Inefficient WM recruitment was not related to a failure in automatization but became evident when processing continuously changing information. The results seem to confirm the vulnerability of still developing frontal lobe functioning for early-onset cannabis use. 2010 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

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

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.

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

Patterns of recovery and change in verbal and nonverbal functions in a case of crossed aphasia: implications for models of functional brain lateralization and localization.

PubMed

Trojano, L; Balbi, P; Russo, G; Elefante, R

1994-05-01

We present a 2-year verbal and nonverbal follow-up of a crossed aphasic patient. The patient had suffered from widespread ischemic damage in the area of right middle cerebral artery, with a parieto-temporal lesion. Three months postonset he showed classical Wernicke's aphasia associated with oral, limb and constructional apraxia and left hemineglect. However, follow-up findings showed a complex, dynamic pattern entirely consistent with cognitive models of language and nonlanguage abilities. Current models of functional brain lateralizations could not satisfactorily account for such longitudinal, fine-grain observations.

Development of the blood-brain barrier: a historical point of view.

PubMed

Ribatti, Domenico; Nico, Beatrice; Crivellato, Enrico; Artico, Marco

2006-01-01

Although there has been considerable controversy since the observation by Ehrlich more than 100 years ago that the brain did not take up dyes from the vascular system, the concept of an endothelial blood-brain barrier (BBB) was confirmed by the unequivocal demonstration that the passage of molecules from blood to brain and vice versa was prevented by endothelial tight junctions (TJs). There are three major functions implicated in the term "BBB": protection of the brain from the blood milieu, selective transport, and metabolism or modification of blood- or brain-borne substances. The BBB phenotype develops under the influence of associated brain cells, especially astrocytic glia, and consists of complex TJs and a number of specific transport and enzyme systems that regulate molecular traffic across the endothelial cells. The development of the BBB is a complex process that leads to endothelial cells with unique permeability characteristics due to high electrical resistance and the expression of specific transporters and metabolic pathways. This review article summarizes the historical background underlying our current knowledge of the cellular and molecular mechanisms involved in the development and maintenance of the BBB. (c) 2006 Wiley-Liss, Inc.

Protective Mechanism of STAT3-siRNA on Cerebral Ischemia Injury

NASA Astrophysics Data System (ADS)

He, Jinting; Yang, Le; Liang, Wenzhao

2018-01-01

Nerve cells in ischemic brain injury will occur a series of complex signal transduction pathway changes and produce the corresponding biological function, thus affecting the central nervous system functionally different cells in the ischemic brain injury metabolism, division, Differentiation and death process, while changes in signal pathways also play an important role in the repair process of the post-ischemic nervous system. JAK/STAT pathway and vascular lesions have some relevance, but its exact mechanism after cerebral ischemia is not yet fully understood. This study is intended to further explore the JAK / STAT pathway in the functional site of STAT3 in neuronal ischemia Hypoxic injury and related molecular mechanisms, targeting these targets design intervention strategies to block the signal pathway, in order to provide a theoretical basis for the treatment of ischemic brain damage in this pathway.

The efficacy and safety of extended-release methylphenidate following traumatic brain injury: a randomised controlled pilot study.

PubMed

Dymowski, Alicia R; Ponsford, Jennie L; Owens, Jacqueline A; Olver, John H; Ponsford, Michael; Willmott, Catherine

2017-06-01

To investigate the feasibility, safety and efficacy of extended-release methylphenidate in enhancing processing speed, complex attentional functioning and everyday attentional behaviour after traumatic brain injury. Seven week randomised, placebo-controlled, double-blind, parallel pilot study. Inpatient and outpatient Acquired Brain Injury Rehabilitation Program. Eleven individuals with reduced processing speed and/or attention deficits following complicated mild to severe traumatic brain injury. Participants were allocated using a blocked randomisation schedule to receive daily extended-release methylphenidate (Ritalin ® LA at a dose of 0.6 mg/kg) or placebo (lactose) in identical capsules. Tests of processing speed and complex attention, and ratings of everyday attentional behaviour were completed at baseline, week 7 (on-drug), week 8 (off-drug) and 9 months follow-up. Vital signs and side effects were monitored from baseline to week 8. Three percent ( n = 11) of individuals screened participated (mean post-traumatic amnesia duration = 63.80 days, SD = 45.15). Results were analysed for six and four individuals on methylphenidate and placebo, respectively. Groups did not differ on attentional test performance or relative/therapist ratings of everyday attentional behaviour. One methylphenidate participant withdrew due to difficulty sleeping. Methylphenidate was associated with trends towards increased blood pressure and reported anxiety. Methylphenidate was not associated with enhanced processing speed, attentional functioning or everyday attentional behaviour after traumatic brain injury. Alternative treatments for attention deficits after traumatic brain injury should be explored given the limited feasibility of methylphenidate in this population.

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

PubMed Central

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

2007-01-01

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

Avocado Oil Improves Mitochondrial Function and Decreases Oxidative Stress in Brain of Diabetic Rats.

PubMed

Ortiz-Avila, Omar; Esquivel-Martínez, Mauricio; Olmos-Orizaba, Berenice Eridani; Saavedra-Molina, Alfredo; Rodriguez-Orozco, Alain R; Cortés-Rojo, Christian

2015-01-01

Diabetic encephalopathy is a diabetic complication related to the metabolic alterations featuring diabetes. Diabetes is characterized by increased lipid peroxidation, altered glutathione redox status, exacerbated levels of ROS, and mitochondrial dysfunction. Although the pathophysiology of diabetic encephalopathy remains to be clarified, oxidative stress and mitochondrial dysfunction play a crucial role in the pathogenesis of chronic diabetic complications. Taking this into consideration, the aim of this work was to evaluate the effects of 90-day avocado oil intake in brain mitochondrial function and oxidative status in streptozotocin-induced diabetic rats (STZ rats). Avocado oil improves brain mitochondrial function in diabetic rats preventing impairment of mitochondrial respiration and mitochondrial membrane potential (ΔΨ m ), besides increasing complex III activity. Avocado oil also decreased ROS levels and lipid peroxidation and improved the GSH/GSSG ratio as well. These results demonstrate that avocado oil supplementation prevents brain mitochondrial dysfunction induced by diabetes in association with decreased oxidative stress.

Evidence for a distributed hierarchy of action representation in the brain

PubMed Central

Grafton, Scott T.; de C. Hamilton, Antonia F.

2007-01-01

Complex human behavior is organized around temporally distal outcomes. Behavioral studies based on tasks such as normal prehension, multi-step object use and imitation establish the existence of relative hierarchies of motor control. The retrieval errors in apraxia also support the notion of a hierarchical model for representing action in the brain. In this review, three functional brain imaging studies of action observation using the method of repetition suppression are used to identify a putative neural architecture that supports action understanding at the level of kinematics, object centered goals and ultimately, motor outcomes. These results, based on observation, may match a similar functional anatomic hierarchy for action planning and execution. If this is true, then the findings support a functional anatomic model that is distributed across a set of interconnected brain areas that are differentially recruited for different aspects of goal oriented behavior, rather than a homogeneous mirror neuron system for organizing and understanding all behavior. PMID:17706312

Developing Brain Vital Signs: Initial Framework for Monitoring Brain Function Changes Over Time

PubMed Central

Ghosh Hajra, Sujoy; Liu, Careesa C.; Song, Xiaowei; Fickling, Shaun; Liu, Luke E.; Pawlowski, Gabriela; Jorgensen, Janelle K.; Smith, Aynsley M.; Schnaider-Beeri, Michal; Van Den Broek, Rudi; Rizzotti, Rowena; Fisher, Kirk; D'Arcy, Ryan C. N.

2016-01-01

Clinical assessment of brain function relies heavily on indirect behavior-based tests. Unfortunately, behavior-based assessments are subjective and therefore susceptible to several confounding factors. Event-related brain potentials (ERPs), derived from electroencephalography (EEG), are often used to provide objective, physiological measures of brain function. Historically, ERPs have been characterized extensively within research settings, with limited but growing clinical applications. Over the past 20 years, we have developed clinical ERP applications for the evaluation of functional status following serious injury and/or disease. This work has identified an important gap: the need for a clinically accessible framework to evaluate ERP measures. Crucially, this enables baseline measures before brain dysfunction occurs, and might enable the routine collection of brain function metrics in the future much like blood pressure measures today. Here, we propose such a framework for extracting specific ERPs as potential “brain vital signs.” This framework enabled the translation/transformation of complex ERP data into accessible metrics of brain function for wider clinical utilization. To formalize the framework, three essential ERPs were selected as initial indicators: (1) the auditory N100 (Auditory sensation); (2) the auditory oddball P300 (Basic attention); and (3) the auditory speech processing N400 (Cognitive processing). First step validation was conducted on healthy younger and older adults (age range: 22–82 years). Results confirmed specific ERPs at the individual level (86.81–98.96%), verified predictable age-related differences (P300 latency delays in older adults, p < 0.05), and demonstrated successful linear transformation into the proposed brain vital sign (BVS) framework (basic attention latency sub-component of BVS framework reflects delays in older adults, p < 0.05). The findings represent an initial critical step in developing, extracting, and characterizing ERPs as vital signs, critical for subsequent evaluation of dysfunction in conditions like concussion and/or dementia. PMID:27242415

Brain networks governing the golf swing in professional golfers.

PubMed

Kim, Jin Hyun; Han, Joung Kyue; Kim, Bung-Nyun; Han, Doug Hyun

2015-01-01

Golf, as with most complex motor skills, requires multiple different brain functions, including attention, motor planning, coordination, calculation of timing, and emotional control. In this study we assessed the correlation between swing components and brain connectivity from the cerebellum to the cerebrum. Ten female golf players and 10 age-matched female controls were recruited. In order to determine swing consistency among participants, the standard deviation (SD) of the mean swing speed time and the SD of the mean swing angle were assessed over 30 swings. Functional brain connectivity was assessed by resting state functional MRI. Pro-golfers showed greater positive left cerebellum connectivity to the occipital lobe, temporal lobe, parietal lobe and both frontal lobes compared to controls. The SD of play scores was positively correlated with the SD of the impact angle. Constant swing speed and back swing angle in professional golfers were associated with functional connectivity (FC) between the cerebellum and parietal and frontal lobes. In addition, the constant impact angle in professional golfers was associated with improved golf scores and additional FC of the thalamus.

The hippocampal response to psychosocial stress varies with salivary uric acid level

PubMed Central

Goodman, Adam M.; Wheelock, Muriah D.; Harnett, Nathaniel G.; Mrug, Sylvie; Granger, Douglas A.; Knight, David C.

2016-01-01

Uric acid is a naturally occurring, endogenous compound that impacts mental health. In particular, uric acid levels are associated with emotion-related psychopathology (e.g., anxiety and depression). Therefore, understanding uric acid’s impact on the brain would provide valuable new knowledge regarding neural mechanisms that mediate the relationship between uric acid and mental health. Brain regions including the prefrontal cortex, amygdala, and hippocampus underlie stress reactivity and emotion regulation. Thus, uric acid may impact emotion by modifying the function of these brain regions. The present study used functional magnetic resonance imaging (fMRI) during a psychosocial stress task to investigate the relationship between baseline uric acid levels (in saliva) and brain function. Results demonstrate that activity within the bilateral hippocampal complex varied with uric acid concentrations. Specifically, activity within the hippocampus and surrounding cortex increased as a function of uric acid level. The current findings suggest that uric acid levels modulate stress-related hippocampal activity. Given that the hippocampus has been implicated in emotion regulation during psychosocial stress, the present findings offer a potential mechanism by which uric acid impacts mental health. PMID:27725214

Nutritional Factors Affecting Adult Neurogenesis and Cognitive Function.

PubMed

Poulose, Shibu M; Miller, Marshall G; Scott, Tammy; Shukitt-Hale, Barbara

2017-11-01

Adult neurogenesis, a complex process by which stem cells in the hippocampal brain region differentiate and proliferate into new neurons and other resident brain cells, is known to be affected by many intrinsic and extrinsic factors, including diet. Neurogenesis plays a critical role in neural plasticity, brain homeostasis, and maintenance in the central nervous system and is a crucial factor in preserving the cognitive function and repair of damaged brain cells affected by aging and brain disorders. Intrinsic factors such as aging, neuroinflammation, oxidative stress, and brain injury, as well as lifestyle factors such as high-fat and high-sugar diets and alcohol and opioid addiction, negatively affect adult neurogenesis. Conversely, many dietary components such as curcumin, resveratrol, blueberry polyphenols, sulforaphane, salvionic acid, polyunsaturated fatty acids (PUFAs), and diets enriched with polyphenols and PUFAs, as well as caloric restriction, physical exercise, and learning, have been shown to induce neurogenesis in adult brains. Although many of the underlying mechanisms by which nutrients and dietary factors affect adult neurogenesis have yet to be determined, nutritional approaches provide promising prospects to stimulate adult neurogenesis and combat neurodegenerative diseases and cognitive decline. In this review, we summarize the evidence supporting the role of nutritional factors in modifying adult neurogenesis and their potential to preserve cognitive function during aging. © 2017 American Society for Nutrition.

The use of magnetic resonance imaging for studying female sexual function: A review.

PubMed

Vaccaro, Christine M

2015-04-01

Many would agree that there are two quintessential sexual organs in the female: the clitoris and the brain. Using non-invasive techniques of magnetic resonance imaging (MRI), investigators have gained insight into the mental and physical factors involved in female sexual function. Since only the external clitoral glans is easily accessible for direct measurement, the complete anatomy of the clitoris (including the internal components-paired corpora, crura, and bulbs) has only recently been described, with MRI providing the most sensitive way of distinguishing among the various soft tissue planes. Average sizes of clitoral structures and average distances between the clitoral complex and other pelvic landmarks have been measured. These measurements have been correlated with female sexual function: a longer distance between the clitoral complex and the vaginal lumen correlates with poorer sexual function, consistent with prior imaging studies. However, whether clitoral size influences function is debatable, so further studies are needed. Physiological investigations have demonstrated that female arousal disorder is unlikely to be due to inadequate genital engorgement. Some consider the brain to be the ultimate sexual organ, and several recent studies have used functional MRI (fMRI) to reveal sexual excitability in the brain. The normal sexual response requires deactivation of the frontal lobe and activation of the instinctual limbic system of the midbrain. As MR technology continues to improve, the mysteries of female sexuality will be further unraveled. © 2015 Wiley Periodicals, Inc.

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…

A functional neuroimaging review of obesity, appetitive hormones and ingestive behavior.

PubMed

Burger, Kyle S; Berner, Laura A

2014-09-01

Adequate energy intake is vital for the survival of humans and is regulated by complex homeostatic and hedonic mechanisms. Supported by functional MRI (fMRI) studies that consistently demonstrate differences in brain response as a function of weight status during exposure to appetizing food stimuli, it has been posited that hedonically driven food intake contributes to weight gain and obesity maintenance. These food reward theories of obesity are reliant on the notion that the aberrant brain response to food stimuli relates directly to ingestive behavior, specifically, excess food intake. Importantly, functioning of homeostatic neuroendocrine regulators of food intake, such as leptin and ghrelin, are impacted by weight status. Thus, data from studies that evaluate the effect on weight status on brain response to food may be a result of differences in neuroendocrine functioning and/or behavior. In the present review, we examine the influence of weight and weight change, exogenous administration of appetitive hormones, and ingestive behavior on BOLD response to food stimuli. Published by Elsevier Inc.

Assessing dynamics, spatial scale, and uncertainty in task-related brain network analyses

PubMed Central

Stephen, Emily P.; Lepage, Kyle Q.; Eden, Uri T.; Brunner, Peter; Schalk, Gerwin; Brumberg, Jonathan S.; Guenther, Frank H.; Kramer, Mark A.

2014-01-01

The brain is a complex network of interconnected elements, whose interactions evolve dynamically in time to cooperatively perform specific functions. A common technique to probe these interactions involves multi-sensor recordings of brain activity during a repeated task. Many techniques exist to characterize the resulting task-related activity, including establishing functional networks, which represent the statistical associations between brain areas. Although functional network inference is commonly employed to analyze neural time series data, techniques to assess the uncertainty—both in the functional network edges and the corresponding aggregate measures of network topology—are lacking. To address this, we describe a statistically principled approach for computing uncertainty in functional networks and aggregate network measures in task-related data. The approach is based on a resampling procedure that utilizes the trial structure common in experimental recordings. We show in simulations that this approach successfully identifies functional networks and associated measures of confidence emergent during a task in a variety of scenarios, including dynamically evolving networks. In addition, we describe a principled technique for establishing functional networks based on predetermined regions of interest using canonical correlation. Doing so provides additional robustness to the functional network inference. Finally, we illustrate the use of these methods on example invasive brain voltage recordings collected during an overt speech task. The general strategy described here—appropriate for static and dynamic network inference and different statistical measures of coupling—permits the evaluation of confidence in network measures in a variety of settings common to neuroscience. PMID:24678295

Assessing dynamics, spatial scale, and uncertainty in task-related brain network analyses.

PubMed

Stephen, Emily P; Lepage, Kyle Q; Eden, Uri T; Brunner, Peter; Schalk, Gerwin; Brumberg, Jonathan S; Guenther, Frank H; Kramer, Mark A

2014-01-01

The brain is a complex network of interconnected elements, whose interactions evolve dynamically in time to cooperatively perform specific functions. A common technique to probe these interactions involves multi-sensor recordings of brain activity during a repeated task. Many techniques exist to characterize the resulting task-related activity, including establishing functional networks, which represent the statistical associations between brain areas. Although functional network inference is commonly employed to analyze neural time series data, techniques to assess the uncertainty-both in the functional network edges and the corresponding aggregate measures of network topology-are lacking. To address this, we describe a statistically principled approach for computing uncertainty in functional networks and aggregate network measures in task-related data. The approach is based on a resampling procedure that utilizes the trial structure common in experimental recordings. We show in simulations that this approach successfully identifies functional networks and associated measures of confidence emergent during a task in a variety of scenarios, including dynamically evolving networks. In addition, we describe a principled technique for establishing functional networks based on predetermined regions of interest using canonical correlation. Doing so provides additional robustness to the functional network inference. Finally, we illustrate the use of these methods on example invasive brain voltage recordings collected during an overt speech task. The general strategy described here-appropriate for static and dynamic network inference and different statistical measures of coupling-permits the evaluation of confidence in network measures in a variety of settings common to neuroscience.

The modulation of brain functional connectivity with manual acupuncture in healthy subjects: An electroencephalograph case study

NASA Astrophysics Data System (ADS)

Yi, Guo-Sheng; Wang, Jiang; Han, Chun-Xiao; Deng, Bin; Wei, Xi-Le; Li, Nuo

2013-02-01

Manual acupuncture is widely used for pain relief and stress control. Previous studies on acupuncture have shown its modulatory effects on the functional connectivity associated with one or a few preselected brain regions. To investigate how manual acupuncture modulates the organization of functional networks at a whole-brain level, we acupuncture at ST36 of a right leg to obtain electroencephalograph (EEG) signals. By coherence estimation, we determine the synchronizations between all pairwise combinations of EEG channels in three acupuncture states. The resulting synchronization matrices are converted into functional networks by applying a threshold, and the clustering coefficients and path lengths are computed as a function of threshold. The results show that acupuncture can increase functional connections and synchronizations between different brain areas. For a wide range of thresholds, the clustering coefficient during acupuncture and post-acupuncture period is higher than that during the pre-acupuncture control period, whereas the characteristic path length is shorter. We provide further support for the presence of “small-world" network characteristics in functional networks by using acupuncture. These preliminary results highlight the beneficial modulations of functional connectivity by manual acupuncture, which could contribute to the understanding of the effects of acupuncture on the entire brain, as well as the neurophysiological mechanisms underlying acupuncture. Moreover, the proposed method may be a useful approach to the further investigation of the complexity of patterns of interrelations between EEG channels.

Age-related changes in the ease of dynamical transitions in human brain activity.

PubMed

Ezaki, Takahiro; Sakaki, Michiko; Watanabe, Takamitsu; Masuda, Naoki

2018-06-01

Executive functions, a set of cognitive processes that enable flexible behavioral control, are known to decay with aging. Because such complex mental functions are considered to rely on the dynamic coordination of functionally different neural systems, the age-related decline in executive functions should be underpinned by alteration of large-scale neural dynamics. However, the effects of age on brain dynamics have not been firmly formulated. Here, we investigate such age-related changes in brain dynamics by applying "energy landscape analysis" to publicly available functional magnetic resonance imaging data from healthy younger and older human adults. We quantified the ease of dynamical transitions between different major patterns of brain activity, and estimated it for the default mode network (DMN) and the cingulo-opercular network (CON) separately. We found that the two age groups shared qualitatively the same trajectories of brain dynamics in both the DMN and CON. However, in both of networks, the ease of transitions was significantly smaller in the older than the younger group. Moreover, the ease of transitions was associated with the performance in executive function tasks in a doubly dissociated manner: for the younger adults, the ability of executive functions was mainly correlated with the ease of transitions in the CON, whereas that for the older adults was specifically associated with the ease of transitions in the DMN. These results provide direct biological evidence for age-related changes in macroscopic brain dynamics and suggest that such neural dynamics play key roles when individuals carry out cognitively demanding tasks. © 2018 Wiley Periodicals, Inc.

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

Fluid dynamics vascular theory of brain and inner-ear function in traumatic brain injury: a translational hypothesis for diagnosis and treatment.

PubMed

Shulman, Abraham; Strashun, Arnold M

2009-01-01

It is hypothesized that in all traumatic brain injury (TBI) patients with a clinical history of closed or penetrating head injury, the initial head trauma is associated with a vibratory sensation and noise exposure, with resultant alteration in vascular supply to the structures and contents of the fluid compartments of brain and ear (i.e., the fluid dynamics vascular theory of brain-inner-ear function [FDVTBE]). The primary etiology-head trauma-results in an initial fluctuation, interference, or interaction in the normal fluid dynamics between brain and labyrinth of the inner ear, with a resultant clinical diversity of complaints varying in time of onset and severity. Normal function of the brain and ear is a reflection of a normal state of homeostasis between the fluid compartments in the brain of cerebrospinal fluid and perilymph-endolymph in the labyrinth of the ear. The normal homeostasis in the structures and contents between the two fluid compartment systems--intracerebral and intralabyrinthine--is controlled by mechanisms involved in the maintenance of normal pressures, water and electrolyte content, and neurotransmitter activities. The initial pathophysiology (a reflection of an alteration in the vascular supply to the brain-ear) is hypothesized to be an initial acute inflammatory response, persistence of which results in ischemia and an irreversible alteration in the involved neural substrates of brain-ear. Clinically, a chronic multisymptom complex becomes manifest. The multisymptom complex, individual for each TBI patient regardless of the diagnostic TBI category (i.e., mild, moderate, or severe), initially reflects processes of inflammation and ischemia which, in brain, result in brain volume loss identified as neurodegeneration and hydrocephalus ex vacuo or an alteration in cerebrospinal fluid production (i.e., pseudotumor cerebri) and, in ear, secondary endolymphatic hydrops with associated cochleovestibular complaints of hearing loss, tinnitus, vertigo, ear blockage, and hyperacusis. The FDVTBE integrates and translates a neurovascular hypothesis for Alzheimer's disease to TBI. This study presents an FDVTBE hypothesis of TBI to explain the clinical association of head trauma (TBI) and central nervous system neurodegeneration with multisensory complaints, highlighted by and focusing on cochleovestibular complaints. A clinical case report, previously published for demonstration of the cerebrovascular medical significance of a particular type of tinnitus, and evidence-based basic science and clinical medicine are cited to provide objective evidence in support and demonstration of the FDVTBE.

Streptococcus agalactiae impairs cerebral bioenergetics in experimentally infected silver catfish.

PubMed

Baldissera, Matheus D; Souza, Carine F; Parmeggiani, Belisa S; Santos, Roberto C V; Leipnitz, Guilhian; Moreira, Karen L S; da Rocha, Maria Izabel U M; da Veiga, Marcelo L; Baldisserotto, Bernardo

2017-10-01

It is becoming evident that bacterial infectious diseases affect brain energy metabolism, where alterations of enzymatic complexes of the mitochondrial respiratory chain and creatine kinase (CK) lead to an impairment of cerebral bioenergetics which contribute to disease pathogenesis in the central nervous system (CNS). Based on this evidence, the aim of this study was to evaluate whether alterations in the activity of complex IV of the respiratory chain and CK contribute to impairment of cerebral bioenergetics during Streptococcus agalactiae infection in silver catfish (Rhamdia quelen). The activity of complex IV of the respiratory chain in brain increased, while the CK activity decreased in infected animals compared to uninfected animals. Brain histopathology revealed inflammatory demyelination, gliosis of the brain and intercellular edema in infected animals. Based on this evidence, S. agalactiae infection causes an impairment in cerebral bioenergetics through the augmentation of complex IV activity, which may be considered an adaptive response to maintain proper functioning of the electron respiratory chain, as well as to ensure ongoing electron flow through the electron transport chain. Moreover, inhibition of cerebral CK activity contributes to lower availability of ATP, contributing to impairment of cerebral energy homeostasis. In summary, these alterations contribute to disease pathogenesis linked to the CNS. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

Brain dynamics in ASD during movie-watching show idiosyncratic functional integration and segregation.

PubMed

Bolton, Thomas A W; Jochaut, Delphine; Giraud, Anne-Lise; Van De Ville, Dimitri

2018-06-01

To refine our understanding of autism spectrum disorders (ASD), studies of the brain in dynamic, multimodal and ecological experimental settings are required. One way to achieve this is to compare the neural responses of ASD and typically developing (TD) individuals when viewing a naturalistic movie, but the temporal complexity of the stimulus hampers this task, and the presence of intrinsic functional connectivity (FC) may overshadow movie-driven fluctuations. Here, we detected inter-subject functional correlation (ISFC) transients to disentangle movie-induced functional changes from underlying resting-state activity while probing FC dynamically. When considering the number of significant ISFC excursions triggered by the movie across the brain, connections between remote functional modules were more heterogeneously engaged in the ASD population. Dynamically tracking the temporal profiles of those ISFC changes and tying them to specific movie subparts, this idiosyncrasy in ASD responses was then shown to involve functional integration and segregation mechanisms such as response inhibition, background suppression, or multisensory integration, while low-level visual processing was spared. Through the application of a new framework for the study of dynamic experimental paradigms, our results reveal a temporally localized idiosyncrasy in ASD responses, specific to short-lived episodes of long-range functional interplays. © 2018 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

HBpF-proBDNF: A New Tool for the Analysis of Pro-Brain Derived Neurotrophic Factor Receptor Signaling and Cell Biology.

PubMed

Gaub, Perrine; de Léon, Andrès; Gibon, Julien; Soubannier, Vincent; Dorval, Geneviève; Séguéla, Philippe; Barker, Philip A

2016-01-01

Neurotrophins activate intracellular signaling pathways necessary for neuronal survival, growth and apoptosis. The most abundant neurotrophin in the adult brain, brain-derived neurotrophic factor (BDNF), is first synthesized as a proBDNF precursor and recent studies have demonstrated that proBDNF can be secreted and that it functions as a ligand for a receptor complex containing p75NTR and sortilin. Activation of proBDNF receptors mediates growth cone collapse, reduces synaptic activity, and facilitates developmental apoptosis of motoneurons but the precise signaling cascades have been difficult to discern. To address this, we have engineered, expressed and purified HBpF-proBDNF, an expression construct containing a 6X-HIS tag, a biotin acceptor peptide (BAP) sequence, a PreScission™ Protease cleavage site and a FLAG-tag attached to the N-terminal part of murine proBDNF. Intact HBpF-proBDNF has activities indistinguishable from its wild-type counterpart and can be used to purify proBDNF signaling complexes or to monitor proBDNF endocytosis and retrograde transport. HBpF-proBDNF will be useful for characterizing proBDNF signaling complexes and for deciphering the role of proBDNF in neuronal development, synapse function and neurodegenerative disease.

Understanding neuromotor strategy during functional upper extremity tasks using symbolic dynamics.

PubMed

Nathan, Dominic E; Guastello, Stephen J; Prost, Robert W; Jeutter, Dean C

2012-01-01

The ability to model and quantify brain activation patterns that pertain to natural neuromotor strategy of the upper extremities during functional task performance is critical to the development of therapeutic interventions such as neuroprosthetic devices. The mechanisms of information flow, activation sequence and patterns, and the interaction between anatomical regions of the brain that are specific to movement planning, intention and execution of voluntary upper extremity motor tasks were investigated here. This paper presents a novel method using symbolic dynamics (orbital decomposition) and nonlinear dynamic tools of entropy, self-organization and chaos to describe the underlying structure of activation shifts in regions of the brain that are involved with the cognitive aspects of functional upper extremity task performance. Several questions were addressed: (a) How is it possible to distinguish deterministic or causal patterns of activity in brain fMRI from those that are really random or non-contributory to the neuromotor control process? (b) Can the complexity of activation patterns over time be quantified? (c) What are the optimal ways of organizing fMRI data to preserve patterns of activation, activation levels, and extract meaningful temporal patterns as they evolve over time? Analysis was performed using data from a custom developed time resolved fMRI paradigm involving human subjects (N=18) who performed functional upper extremity motor tasks with varying time delays between the onset of intention and onset of actual movements. The results indicate that there is structure in the data that can be quantified through entropy and dimensional complexity metrics and statistical inference, and furthermore, orbital decomposition is sensitive in capturing the transition of states that correlate with the cognitive aspects of functional task performance.

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.

Computational physics of the mind

NASA Astrophysics Data System (ADS)

Duch, Włodzisław

1996-08-01

In the XIX century and earlier physicists such as Newton, Mayer, Hooke, Helmholtz and Mach were actively engaged in the research on psychophysics, trying to relate psychological sensations to intensities of physical stimuli. Computational physics allows to simulate complex neural processes giving a chance to answer not only the original psychophysical questions but also to create models of the mind. In this paper several approaches relevant to modeling of the mind are outlined. Since direct modeling of the brain functions is rather limited due to the complexity of such models a number of approximations is introduced. The path from the brain, or computational neurosciences, to the mind, or cognitive sciences, is sketched, with emphasis on higher cognitive functions such as memory and consciousness. No fundamental problems in understanding of the mind seem to arise. From a computational point of view realistic models require massively parallel architectures.

The yin and yang of sleep and attention

PubMed Central

Kirszenblat, Leonie; van Swinderen, Bruno

2015-01-01

Sleep is not a single state, but a complex set of brain processes that supports a number of physiological needs. Sleep deprivation is known to affect attention in many animals, suggesting that a key function of sleep is to regulate attention. Conversely, tasks that require more attention drive sleep need and sleep intensity. Attention involves the ability to filter incoming stimuli based on their relative salience, and this is likely to require coordinated synaptic activity across the brain. This capacity may have only become possible with the evolution of related neural mechanisms that support two key sleep functions: stimulus suppression and synaptic plasticity. We argue here that sleep and attention may have co-evolved as brain states that regulate each other. PMID:26602764

Physiology and molecular biology of barrier mechanisms in the fetal and neonatal brain.

PubMed

Saunders, Norman R; Dziegielewska, Katarzyna M; Møllgård, Kjeld; Habgood, Mark D

2018-05-17

Properties of the local internal environment of the adult brain are tightly controlled providing a stable milieu essential for its normal function. The mechanisms involved in this complex control are structural, molecular and physiological (influx and efflux transporters) frequently referred to as the "blood-brain barrier". These mechanisms include regulation of ion levels in brain interstitial fluid essential for normal neuronal function, supply of nutrients, removal of metabolic products and prevention of entry or elimination of toxic agents. A key feature is cerebrospinal fluid secretion and turnover. This is much less during development, allowing greater accumulation of permeating molecules. The overall effect of these mechanisms is to tightly control the exchange of molecules into and out of the brain. This review presents experimental evidence currently available on the status of these mechanisms in developing brain. It has been frequently stated for over nearly a century that the blood-brain barrier is not present or at least is functionally deficient in the embryo, fetus and newborn. We suggest the alternative hypothesis that the barrier mechanisms in developing brain are likely to be appropriately matched to each stage of its development. The contributions of different barrier mechanisms, such as changes in constituents of cerebrospinal fluid in relation to specific features of brain development, for example neurogenesis, are only beginning to be studied. The evidence on this previously neglected aspect of brain barrier function is outlined. We also suggest future directions this field could follow with special emphasis on potential applications in a clinical setting. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

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.

Planning and Realization of Complex Intentions in Traumatic Brain Injury and Normal Aging

ERIC Educational Resources Information Center

Kliegel, Matthias; Eschen, Anne; Thone-Otto, Angelika I. T.

2004-01-01

The realization of delayed intentions (i.e., prospective memory) is a highly complex process composed of four phases: intention formation, retention, re-instantiation, and execution. The aim of this study was to investigate if executive functioning impairments are related to problems in the formation, re-instantiation, and execution of a delayed…

State-dependencies of learning across brain scales

PubMed Central

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

2015-01-01

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

Brain Network Analysis from High-Resolution EEG Signals

NASA Astrophysics Data System (ADS)

de Vico Fallani, Fabrizio; Babiloni, Fabio

Over the last decade, there has been a growing interest in the detection of the functional connectivity in the brain from different neuroelectromagnetic and hemodynamic signals recorded by several neuro-imaging devices such as the functional Magnetic Resonance Imaging (fMRI) scanner, electroencephalography (EEG) and magnetoencephalography (MEG) apparatus. Many methods have been proposed and discussed in the literature with the aim of estimating the functional relationships among different cerebral structures. However, the necessity of an objective comprehension of the network composed by the functional links of different brain regions is assuming an essential role in the Neuroscience. Consequently, there is a wide interest in the development and validation of mathematical tools that are appropriate to spot significant features that could describe concisely the structure of the estimated cerebral networks. The extraction of salient characteristics from brain connectivity patterns is an open challenging topic, since often the estimated cerebral networks have a relative large size and complex structure. Recently, it was realized that the functional connectivity networks estimated from actual brain-imaging technologies (MEG, fMRI and EEG) can be analyzed by means of the graph theory. Since a graph is a mathematical representation of a network, which is essentially reduced to nodes and connections between them, the use of a theoretical graph approach seems relevant and useful as firstly demonstrated on a set of anatomical brain networks. In those studies, the authors have employed two characteristic measures, the average shortest path L and the clustering index C, to extract respectively the global and local properties of the network structure. They have found that anatomical brain networks exhibit many local connections (i.e. a high C) and few random long distance connections (i.e. a low L). These values identify a particular model that interpolate between a regular lattice and a random structure. Such a model has been designated as "small-world" network in analogy with the concept of the small-world phenomenon observed more than 30 years ago in social systems. In a similar way, many types of functional brain networks have been analyzed according to this mathematical approach. In particular, several studies based on different imaging techniques (fMRI, MEG and EEG) have found that the estimated functional networks showed small-world characteristics. In the functional brain connectivity context, these properties have been demonstrated to reflect an optimal architecture for the information processing and propagation among the involved cerebral structures. However, the performance of cognitive and motor tasks as well as the presence of neural diseases has been demonstrated to affect such a small-world topology, as revealed by the significant changes of L and C. Moreover, some functional brain networks have been mostly found to be very unlike the random graphs in their degree-distribution, which gives information about the allocation of the functional links within the connectivity pattern. It was demonstrated that the degree distributions of these networks follow a power-law trend. For this reason those networks are called "scale-free". They still exhibit the small-world phenomenon but tend to contain few nodes that act as highly connected "hubs". Scale-free networks are known to show resistance to failure, facility of synchronization and fast signal processing. Hence, it would be important to see whether the scaling properties of the functional brain networks are altered under various pathologies or experimental tasks. The present Chapter proposes a theoretical graph approach in order to evaluate the functional connectivity patterns obtained from high-resolution EEG signals. In this way, the "Brain Network Analysis" (in analogy with the Social Network Analysis that has emerged as a key technique in modern sociology) represents an effective methodology improving the comprehension of the complex interactions in the brain.

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.

Discovery of new candidate genes related to brain development using protein interaction information.

PubMed

Chen, Lei; Chu, Chen; Kong, Xiangyin; Huang, Tao; Cai, Yu-Dong

2015-01-01

Human brain development is a dramatic process composed of a series of complex and fine-tuned spatiotemporal gene expressions. A good comprehension of this process can assist us in developing the potential of our brain. However, we have only limited knowledge about the genes and gene functions that are involved in this biological process. Therefore, a substantial demand remains to discover new brain development-related genes and identify their biological functions. In this study, we aimed to discover new brain-development related genes by building a computational method. We referred to a series of computational methods used to discover new disease-related genes and developed a similar method. In this method, the shortest path algorithm was executed on a weighted graph that was constructed using protein-protein interactions. New candidate genes fell on at least one of the shortest paths connecting two known genes that are related to brain development. A randomization test was then adopted to filter positive discoveries. Of the final identified genes, several have been reported to be associated with brain development, indicating the effectiveness of the method, whereas several of the others may have potential roles in brain development.

The Virtual Brain Integrates Computational Modeling and Multimodal Neuroimaging

PubMed Central

Schirner, Michael; McIntosh, Anthony R.; Jirsa, Viktor K.

2013-01-01

Abstract Brain function is thought to emerge from the interactions among neuronal populations. Apart from traditional efforts to reproduce brain dynamics from the micro- to macroscopic scales, complementary approaches develop phenomenological models of lower complexity. Such macroscopic models typically generate only a few selected—ideally functionally relevant—aspects of the brain dynamics. Importantly, they often allow an understanding of the underlying mechanisms beyond computational reproduction. Adding detail to these models will widen their ability to reproduce a broader range of dynamic features of the brain. For instance, such models allow for the exploration of consequences of focal and distributed pathological changes in the system, enabling us to identify and develop approaches to counteract those unfavorable processes. Toward this end, The Virtual Brain (TVB) (www.thevirtualbrain.org), a neuroinformatics platform with a brain simulator that incorporates a range of neuronal models and dynamics at its core, has been developed. This integrated framework allows the model-based simulation, analysis, and inference of neurophysiological mechanisms over several brain scales that underlie the generation of macroscopic neuroimaging signals. In this article, we describe how TVB works, and we present the first proof of concept. PMID:23442172

Early Language Learning and Literacy: Neuroscience Implications for Education

PubMed Central

Kuhl, Patricia K.

2011-01-01

The last decade has produced an explosion in neuroscience research examining young children’s early processing of language that has implications for education. Noninvasive, safe functional brain measurements have now been proven feasible for use with children starting at birth. In the arena of language, the neural signatures of learning can be documented at a remarkably early point in development, and these early measures predict performance in children’s language and pre-reading abilities in the second, third, and fifth year of life, a finding with theoretical and educational import. There is evidence that children’s early mastery of language requires learning in a social context, and this finding also has important implications for education. Evidence relating socio-economic status (SES) to brain function for language suggests that SES should be considered a proxy for the opportunity to learn and that the complexity of language input is a significant factor in developing brain areas related to language. The data indicate that the opportunity to learn from complex stimuli and events are vital early in life, and that success in school begins in infancy. PMID:21892359

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.

Age differences in the motor control of speech: An fMRI study of healthy aging.

PubMed

Tremblay, Pascale; Sato, Marc; Deschamps, Isabelle

2017-05-01

Healthy aging is associated with a decline in cognitive, executive, and motor processes that are concomitant with changes in brain activation patterns, particularly at high complexity levels. While speech production relies on all these processes, and is known to decline with age, the mechanisms that underlie these changes remain poorly understood, despite the importance of communication on everyday life. In this cross-sectional group study, we investigated age differences in the neuromotor control of speech production by combining behavioral and functional magnetic resonance imaging (fMRI) data. Twenty-seven healthy adults underwent fMRI while performing a speech production task consisting in the articulation of nonwords of different sequential and motor complexity. Results demonstrate strong age differences in movement time (MT), with longer and more variable MT in older adults. The fMRI results revealed extensive age differences in the relationship between BOLD signal and MT, within and outside the sensorimotor system. Moreover, age differences were also found in relation to sequential complexity within the motor and attentional systems, reflecting both compensatory and de-differentiation mechanisms. At very high complexity level (high motor complexity and high sequence complexity), age differences were found in both MT data and BOLD response, which increased in several sensorimotor and executive control areas. Together, these results suggest that aging of motor and executive control mechanisms may contribute to age differences in speech production. These findings highlight the importance of studying functionally relevant behavior such as speech to understand the mechanisms of human brain aging. Hum Brain Mapp 38:2751-2771, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Recruitment of prefrontal-striatal circuit in response to skilled motor challenge.

PubMed

Guo, Yumei; Wang, Zhuo; Prathap, Sandhya; Holschneider, Daniel P

2017-12-13

A variety of physical fitness regimens have been shown to improve cognition, including executive function, yet our understanding of which parameters of motor training are important in optimizing outcomes remains limited. We used functional brain mapping to compare the ability of two motor challenges to acutely recruit the prefrontal-striatal circuit. The two motor tasks - walking in a complex running wheel with irregularly spaced rungs or walking in a running wheel with a smooth internal surface - differed only in the extent of skill required for their execution. Cerebral perfusion was mapped in rats by intravenous injection of [C]-iodoantipyrine during walking in either a motorized complex wheel or in a simple wheel. Regional cerebral blood flow (rCBF) was quantified by whole-brain autoradiography and analyzed in three-dimensional reconstructed brains by statistical parametric mapping and seed-based functional connectivity. Skilled or simple walking compared with rest, increased rCBF in regions of the motor circuit, somatosensory and visual cortex, as well as the hippocampus. Significantly greater rCBF increases were noted during skilled walking than for simple walking. Skilled walking, unlike simple walking or the resting condition, was associated with a significant positive functional connectivity in the prefrontal-striatal circuit (prelimbic cortex-dorsomedial striatum) and greater negative functional connectivity in the prefrontal-hippocampal circuit. Our findings suggest that the level of skill of a motor training task determines the extent of functional recruitment of the prefrontal-corticostriatal circuit, with implications for a new approach in neurorehabilitation that uses circuit-specific neuroplasticity to improve motor and cognitive functions.

Scanning fast and slow: current limitations of 3 Tesla functional MRI and future potential

NASA Astrophysics Data System (ADS)

Boubela, Roland N.; Kalcher, Klaudius; Nasel, Christian; Moser, Ewald

2014-02-01

Functional MRI at 3T has become a workhorse for the neurosciences, e.g., neurology, psychology, and psychiatry, enabling non-invasive investigation of brain function and connectivity. However, BOLD-based fMRI is a rather indirect measure of brain function, confounded by fluctuation related signals, e.g. head or brain motion, brain pulsation, blood flow, intermixed with susceptibility differences close or distant to the region of neuronal activity. Even though a plethora of preprocessing strategies have been published to address these confounds, their efficiency is still under discussion. In particular, physiological signal fluctuations closely related to brain supply may mask BOLD signal changes related to "true" neuronal activation. Here we explore recent technical and methodological advancements aimed at disentangling the various components, employing fast multiband vs. standard EPI, in combination with fast temporal ICA.Our preliminary results indicate that fast (TR< 0.5s) scanning may help to identify and eliminate physiologic components, increasing tSNR and functional contrast. In addition, biological variability can be studied and task performance better correlated to other measures. This should increase specificity and reliability in fMRI studies. Furthermore, physiological signal changes during scanning may then be recognized as a source of information rather than a nuisance. As we are currently still undersampling the complexity of the brain, even at a rather coarse macroscopic level, we should be very cautious in the interpretation of neuroscientific findings, in particular when comparing different groups (e.g., age, sex, medication, pathology, etc.). From a technical point of view our goal should be to sample brain activity at layer specific resolution with low TR, covering as much of the brain as possible without violating SAR limits. We hope to stimulate discussion towards a better understanding and a more quantitative use of fMRI.

The brain-tumor related protein podoplanin regulates synaptic plasticity and hippocampus-dependent learning and memory.

PubMed

Cicvaric, Ana; Yang, Jiaye; Krieger, Sigurd; Khan, Deeba; Kim, Eun-Jung; Dominguez-Rodriguez, Manuel; Cabatic, Maureen; Molz, Barbara; Acevedo Aguilar, Juan Pablo; Milicevic, Radoslav; Smani, Tarik; Breuss, Johannes M; Kerjaschki, Dontscho; Pollak, Daniela D; Uhrin, Pavel; Monje, Francisco J

2016-12-01

Podoplanin is a cell-surface glycoprotein constitutively expressed in the brain and implicated in human brain tumorigenesis. The intrinsic function of podoplanin in brain neurons remains however uncharacterized. Using an established podoplanin-knockout mouse model and electrophysiological, biochemical, and behavioral approaches, we investigated the brain neuronal role of podoplanin. Ex-vivo electrophysiology showed that podoplanin deletion impairs dentate gyrus synaptic strengthening. In vivo, podoplanin deletion selectively impaired hippocampus-dependent spatial learning and memory without affecting amygdala-dependent cued fear conditioning. In vitro, neuronal overexpression of podoplanin promoted synaptic activity and neuritic outgrowth whereas podoplanin-deficient neurons exhibited stunted outgrowth and lower levels of p-Ezrin, TrkA, and CREB in response to nerve growth factor (NGF). Surface Plasmon Resonance data further indicated a physical interaction between podoplanin and NGF. This work proposes podoplanin as a novel component of the neuronal machinery underlying neuritogenesis, synaptic plasticity, and hippocampus-dependent memory functions. The existence of a relevant cross-talk between podoplanin and the NGF/TrkA signaling pathway is also for the first time proposed here, thus providing a novel molecular complex as a target for future multidisciplinary studies of the brain function in the physiology and the pathology. Key messages Podoplanin, a protein linked to the promotion of human brain tumors, is required in vivo for proper hippocampus-dependent learning and memory functions. Deletion of podoplanin selectively impairs activity-dependent synaptic strengthening at the neurogenic dentate-gyrus and hampers neuritogenesis and phospho Ezrin, TrkA and CREB protein levels upon NGF stimulation. Surface plasmon resonance data indicates a physical interaction between podoplanin and NGF. On these grounds, a relevant cross-talk between podoplanin and NGF as well as a role for podoplanin in plasticity-related brain neuronal functions is here proposed.

Prolonged Delirium Secondary to Hypoxic-ischemic Encephalopathy Following Cardiac Arrest

PubMed Central

Yogaratnam, Jegan; Jacob, Rajesh; Naik, Sandeep; Magadi, Harish

2013-01-01

Hypoxic-ischemic brain injury encompasses a complex constellation of pathophysiological and cellular brain injury induced by hypoxia, ischemia, cytotoxicity, or combinations of these mechanisms and can result in poor outcomes including significant changes in personality and cognitive impairments in memory, cognition, and attention. We report a case of a male patient with normal premorbid functioning who developed prolonged delirium following hypoxic-ischemic brain insults subsequent to cardiac arrest. The case highlights the importance of adopting a multidisciplinary treatment approach involving the coordinated care of medical and nursing teams to optimise management of patients suffering from such a debilitating organic brain syndrome. PMID:23678354

Speech and language outcomes of very preterm infants.

PubMed

Vohr, Betty

2014-04-01

Speech and language impairments of both simple and complex language functions are common among former preterm infants. Risk factors include lower gestational age and increasing illness severity including severe brain injury. Even in the absence of brain injury, however, altered brain maturation and vulnerability imposed by premature entrance to the extrauterine environment is associated with brain structural and microstructural changes. These alterations are associated with language impairments with lasting effects in childhood and adolescence and increased needs for speech therapy and education supports. Studies are needed to investigate language interventions which begin in the neonatal intensive care unit. Copyright © 2013 Elsevier Ltd. All rights reserved.

Classifying social anxiety disorder using multivoxel pattern analyses of brain function and structure☆

PubMed Central

Frick, Andreas; Gingnell, Malin; Marquand, Andre F.; Howner, Katarina; Fischer, Håkan; Kristiansson, Marianne; Williams, Steven C.R.; Fredrikson, Mats; Furmark, Tomas

2014-01-01

Functional neuroimaging of social anxiety disorder (SAD) support altered neural activation to threat-provoking stimuli focally in the fear network, while structural differences are distributed over the temporal and frontal cortices as well as limbic structures. Previous neuroimaging studies have investigated the brain at the voxel level using mass-univariate methods which do not enable detection of more complex patterns of activity and structural alterations that may separate SAD from healthy individuals. Support vector machine (SVM) is a supervised machine learning method that capitalizes on brain activation and structural patterns to classify individuals. The aim of this study was to investigate if it is possible to discriminate SAD patients (n = 14) from healthy controls (n = 12) using SVM based on (1) functional magnetic resonance imaging during fearful face processing and (2) regional gray matter volume. Whole brain and region of interest (fear network) SVM analyses were performed for both modalities. For functional scans, significant classifications were obtained both at whole brain level and when restricting the analysis to the fear network while gray matter SVM analyses correctly classified participants only when using the whole brain search volume. These results support that SAD is characterized by aberrant neural activation to affective stimuli in the fear network, while disorder-related alterations in regional gray matter volume are more diffusely distributed over the whole brain. SVM may thus be useful for identifying imaging biomarkers of SAD. PMID:24239689

Approaching the biology of human parental attachment: brain imaging, oxytocin and coordinated assessments of mothers and fathers.

PubMed

Swain, J E; Kim, P; Spicer, J; Ho, S S; Dayton, C J; Elmadih, A; Abel, K M

2014-09-11

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 enables the formation of each individual's first social bonds and critically shapes development. 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. These include circuitry 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 during early parent-infant experiences. The function of these circuits is modifiable by current and early-life experiences, hormonal and other factors. Severe 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 given our current model. Developments in the understanding of the parental brain may have profound implications for long-term outcomes in families across risk, resilience and possible interventions. This article is part of a Special Issue entitled Oxytocin and Social Behav. Copyright © 2014 Elsevier B.V. All rights reserved.

A combinatorial optogenetic approach to medial habenula function

NASA Astrophysics Data System (ADS)

Turner, Eric E.; Hsu, Yun-Wei; Wang, Si; Morton, Glenn; Zeng, Hongkui

2013-03-01

The habenula is a brain region found in all vertebrate species. It consists of medial and lateral subnuclei which make complex descending connections to the brainstem. Although the medial habenula (MHb) and its projection, the fasciculus retroflexus (FR), have been recognized for decades, their function remains obscure. The small size of the MHb in rodents, and the cellular and molecular complexity of this region, have made it difficult to study the function of this region with high specificity. Here we describe a Cre-mediated genetic system for expressing the microbial opsin channelrhodopsin (ChR2) specifically in the dorsal (dMHb) and ventral (vMHb) medial habenula. Genetically targeted expression of ChR2 allows MHb neurons to be selectively activated with light in acute brain slices with electrophysiological readouts, and in vivo by means of custom-built fiber optic cannulas. These tools will allow highly specific studies of MHb circuitry and the role of the MHb in behaviors related to addiction and mood regulation.

Relating brain signal variability to knowledge representation.

PubMed

Heisz, Jennifer J; Shedden, Judith M; McIntosh, Anthony R

2012-11-15

We assessed the hypothesis that brain signal variability is a reflection of functional network reconfiguration during memory processing. In the present experiments, we use multiscale entropy to capture the variability of human electroencephalogram (EEG) while manipulating the knowledge representation associated with faces stored in memory. Across two experiments, we observed increased variability as a function of greater knowledge representation. In Experiment 1, individuals with greater familiarity for a group of famous faces displayed more brain signal variability. In Experiment 2, brain signal variability increased with learning after multiple experimental exposures to previously unfamiliar faces. The results demonstrate that variability increases with face familiarity; cognitive processes during the perception of familiar stimuli may engage a broader network of regions, which manifests as higher complexity/variability in spatial and temporal domains. In addition, effects of repetition suppression on brain signal variability were observed, and the pattern of results is consistent with a selectivity model of neural adaptation. Crown Copyright © 2012. Published by Elsevier Inc. All rights reserved.

How can we study reasoning in the brain?

PubMed Central

Papo, David

2015-01-01

The brain did not develop a dedicated device for reasoning. This fact bears dramatic consequences. While for perceptuo-motor functions neural activity is shaped by the input's statistical properties, and processing is carried out at high speed in hardwired spatially segregated modules, in reasoning, neural activity is driven by internal dynamics and processing times, stages, and functional brain geometry are largely unconstrained a priori. Here, it is shown that the complex properties of spontaneous activity, which can be ignored in a short-lived event-related world, become prominent at the long time scales of certain forms of reasoning. It is argued that the neural correlates of reasoning should in fact be defined in terms of non-trivial generic properties of spontaneous brain activity, and that this implies resorting to concepts, analytical tools, and ways of designing experiments that are as yet non-standard in cognitive neuroscience. The implications in terms of models of brain activity, shape of the neural correlates, methods of data analysis, observability of the phenomenon, and experimental designs are discussed. PMID:25964755

How can we study reasoning in the brain?

PubMed

Papo, David

2015-01-01

The brain did not develop a dedicated device for reasoning. This fact bears dramatic consequences. While for perceptuo-motor functions neural activity is shaped by the input's statistical properties, and processing is carried out at high speed in hardwired spatially segregated modules, in reasoning, neural activity is driven by internal dynamics and processing times, stages, and functional brain geometry are largely unconstrained a priori. Here, it is shown that the complex properties of spontaneous activity, which can be ignored in a short-lived event-related world, become prominent at the long time scales of certain forms of reasoning. It is argued that the neural correlates of reasoning should in fact be defined in terms of non-trivial generic properties of spontaneous brain activity, and that this implies resorting to concepts, analytical tools, and ways of designing experiments that are as yet non-standard in cognitive neuroscience. The implications in terms of models of brain activity, shape of the neural correlates, methods of data analysis, observability of the phenomenon, and experimental designs are discussed.

Functional neuroanatomy of disorders of consciousness.

PubMed

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

2014-01-01

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

The implications of brain connectivity in the neuropsychology of autism

PubMed Central

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

2014-01-01

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

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

PubMed Central

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

2010-01-01

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

Genomic distribution and possible functions of DNA hydroxymethylation in the brain.

PubMed

Wen, Lu; Tang, Fuchou

2014-11-01

DNA methylation (5-methylcytosine, 5mC) is involved in many cellular processes and emerges as an important epigenetic player in brain development and memory formation. The recent discovery that 5mC can be oxidized to 5-hydroxymethylcytosine (5hmC) by TET (Ten-Eleven-Translocation) proteins provides novel insights into the dynamic character of 5mC in the brain. The content of 5hmC is remarkably high in the brain, adding further complexity. In this review, we discuss how recent advances have improved our understanding of the possible biological roles of 5hmC and TET proteins in the brain. These advances attribute to various approaches, including the genome-wide approach to map 5hmC in different genomic contexts, the gene knockout/knockdown approach to elucidate the functions of TET proteins and 5hmC, and the biochemical approach to uncover potential 5hmC readers. Copyright © 2014 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.

Finer parcellation reveals detailed correlational structure of resting-state fMRI signals.

PubMed

Dornas, João V; Braun, Jochen

2018-01-15

Even in resting state, the human brain generates functional signals (fMRI) with complex correlational structure. To simplify this structure, it is common to parcellate a standard brain into coarse chunks. Finer parcellations are considered less reproducible and informative, due to anatomical and functional variability of individual brains. Grouping signals with similar local correlation profiles, restricted to each anatomical region (Tzourio-Mazoyer et al., 2002), we divide a standard brain into 758 'functional clusters' averaging 1.7cm 3 gray matter volume ('MD758' parcellation). We compare 758 'spatial clusters' of similar size ('S758'). 'Functional clusters' are spatially contiguous and cluster quality (integration and segregation of temporal variance) is far superior to 'spatial clusters', comparable to multi-modal parcellations of half the resolution (Craddock et al., 2012; Glasser et al., 2016). Moreover, 'functional clusters' capture many long-range functional correlations, with O(10 5 ) reproducibly correlated cluster pairs in different anatomical regions. The pattern of functional correlations closely mirrors long-range anatomical connectivity established by fibre tracking. MD758 is comparable to coarser parcellations (Craddock et al., 2012; Glasser et al., 2016) in terms of cluster quality, correlational structure (54% relative mutual entropy vs 60% and 61%), and sparseness (35% significant pairwise correlations vs 36% and 44%). We describe and evaluate a simple path to finer functional parcellations of the human brain. Detailed correlational structure is surprisingly consistent between individuals, opening new possibilities for comparing functional correlations between cognitive conditions, states of health, or pharmacological interventions. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Neuropeptide transmission in brain circuits

PubMed Central

van den Pol, Anthony N.

2014-01-01

Neuropeptides are found in many mammalian CNS neurons where they play key roles in modulating neuronal activity. In contrast to amino acid transmitter release at the synapse, neuropeptide release is not restricted to the synaptic specialization, and after release, a neuropeptide may diffuse some distance to exert its action through a G-protein coupled receptor. Some neuropeptides such as hypocretin/orexin are synthesized only in single regions of the brain, and the neurons releasing these peptides probably have similar functional roles. Other peptides such as neuropeptide Y (NPY) are synthesized throughout the brain, and neurons that synthesize the peptide in one region have no anatomical or functional connection with NPY neurons in other brain regions. Here, I review converging data revealing a complex interaction between slow-acting neuromodulator peptides and fast-acting amino acid transmitters in the control of energy homeostasis, drug addiction, mood and motivation, sleep-wake states, and neuroendocrine regulation. PMID:23040809

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

PubMed Central

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

2015-01-01

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

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).

13 reasons why the brain is susceptible to oxidative stress.

PubMed

Cobley, James Nathan; Fiorello, Maria Luisa; Bailey, Damian Miles

2018-05-01

The human brain consumes 20% of the total basal oxygen (O 2 ) budget to support ATP intensive neuronal activity. Without sufficient O 2 to support ATP demands, neuronal activity fails, such that, even transient ischemia is neurodegenerative. While the essentiality of O 2 to brain function is clear, how oxidative stress causes neurodegeneration is ambiguous. Ambiguity exists because many of the reasons why the brain is susceptible to oxidative stress remain obscure. Many are erroneously understood as the deleterious result of adventitious O 2 derived free radical and non-radical species generation. To understand how many reasons underpin oxidative stress, one must first re-cast free radical and non-radical species in a positive light because their deliberate generation enables the brain to achieve critical functions (e.g. synaptic plasticity) through redox signalling (i.e. positive functionality). Using free radicals and non-radical derivatives to signal sensitises the brain to oxidative stress when redox signalling goes awry (i.e. negative functionality). To advance mechanistic understanding, we rationalise 13 reasons why the brain is susceptible to oxidative stress. Key reasons include inter alia unsaturated lipid enrichment, mitochondria, calcium, glutamate, modest antioxidant defence, redox active transition metals and neurotransmitter auto-oxidation. We review RNA oxidation as an underappreciated cause of oxidative stress. The complex interplay between each reason dictates neuronal susceptibility to oxidative stress in a dynamic context and neural identity dependent manner. Our discourse sets the stage for investigators to interrogate the biochemical basis of oxidative stress in the brain in health and disease. Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.

Functional magnetic resonance imaging: basic principles and application in the neurosciences.

PubMed

Labbé Atenas, T; Ciampi Díaz, E; Cruz Quiroga, J P; Uribe Arancibia, S; Cárcamo Rodríguez, C

2018-03-12

Functional magnetic resonance imaging (fMRI) is an advanced tool for the study of brain functions in healthy subjects and in neuropsychiatric patients. This tool makes it possible to identify and locate specific phenomena related to neuronal metabolism and activity. Starting with the detection of changes in the blood supply to a region that participates in a function, more complex approaches have been developed to study the dynamics of neuronal networks. Studies examining the brain at rest or involved in different tasks have provided evidence related to the onset, development, and/or response to treatment in various diseases. The diversity of the possible artifacts associated with image registration as well as the complexity of the analytical experimental designs has generated abundant debate about the technique behind fMRI. This article aims to introduce readers to the fundamentals underlying fMRI, to explain how fMRI studies are interpreted, and to discuss fMRI's contributions to the study of the mechanisms underlying diverse diseases of the nervous system. Copyright © 2018 SERAM. Publicado por Elsevier España, S.L.U. All rights reserved.

Short-term Music Training Enhances Complex, Distributed Neural Communication during Music and Linguistic Tasks

PubMed Central

Carpentier, Sarah M.; Moreno, Sylvain; McIntosh, Anthony R.

2016-01-01

Musical training is frequently associated with benefits to linguistic abilities, and recent focus has been placed on possible benefits of bilingualism to lifelong executive functions; however, the neural mechanisms for such effects are unclear. The aim of this study was to gain better understanding of the whole-brain functional effects of music and second-language training that could support such previously observed cognitive transfer effects. We conducted a 28-day longitudinal study of monolingual English-speaking 4- to 6-year-old children randomly selected to receive daily music or French language training, excluding weekends. Children completed passive EEG music note and French vowel auditory oddball detection tasks before and after training. Brain signal complexity was measured on source waveforms at multiple temporal scales as an index of neural information processing and network communication load. Comparing pretraining with posttraining, musical training was associated with increased EEG complexity at coarse temporal scales during the music and French vowel tasks in widely distributed cortical regions. Conversely, very minimal decreases in complexity at fine scales and trends toward coarse-scale increases were displayed after French training during the tasks. Spectral analysis failed to distinguish between training types and found overall theta (3.5–7.5 Hz) power increases after all training forms, with spatially fewer decreases in power at higher frequencies (>10 Hz). These findings demonstrate that musical training increased diversity of brain network states to support domain-specific music skill acquisition and music-to-language transfer effects. PMID:27243611

Short-term Music Training Enhances Complex, Distributed Neural Communication during Music and Linguistic Tasks.

PubMed

Carpentier, Sarah M; Moreno, Sylvain; McIntosh, Anthony R

2016-10-01

Musical training is frequently associated with benefits to linguistic abilities, and recent focus has been placed on possible benefits of bilingualism to lifelong executive functions; however, the neural mechanisms for such effects are unclear. The aim of this study was to gain better understanding of the whole-brain functional effects of music and second-language training that could support such previously observed cognitive transfer effects. We conducted a 28-day longitudinal study of monolingual English-speaking 4- to 6-year-old children randomly selected to receive daily music or French language training, excluding weekends. Children completed passive EEG music note and French vowel auditory oddball detection tasks before and after training. Brain signal complexity was measured on source waveforms at multiple temporal scales as an index of neural information processing and network communication load. Comparing pretraining with posttraining, musical training was associated with increased EEG complexity at coarse temporal scales during the music and French vowel tasks in widely distributed cortical regions. Conversely, very minimal decreases in complexity at fine scales and trends toward coarse-scale increases were displayed after French training during the tasks. Spectral analysis failed to distinguish between training types and found overall theta (3.5-7.5 Hz) power increases after all training forms, with spatially fewer decreases in power at higher frequencies (>10 Hz). These findings demonstrate that musical training increased diversity of brain network states to support domain-specific music skill acquisition and music-to-language transfer effects.

The Specialization of Function: Cognitive and Neural Perspectives

PubMed Central

Mahon, Bradford Z.; Cantlon, Jessica F.

2014-01-01

A unifying theme that cuts across all research areas and techniques in the cognitive and brain sciences is whether there is specialization of function at levels of processing that are ‘abstracted away’ from sensory inputs and motor outputs. Any theory that articulates claims about specialization of function in the mind/brain confronts the following types of interrelated questions, each of which carries with it certain theoretical commitments. What methods are appropriate for decomposing complex cognitive and neural processes into their constituent parts? How do cognitive processes map onto neural processes, and at what resolution are they related? What types of conclusions can be drawn about the structure of mind from dissociations observed at the neural level, and vice versa? The contributions that form this Special Issue of Cognitive Neuropsychology represent recent reflections on these and other issues from leading researchers in different areas of the cognitive and brain sciences. PMID:22185234

A review on functional and structural brain connectivity in numerical cognition

PubMed Central

Moeller, Korbinian; Willmes, Klaus; Klein, Elise

2015-01-01

Only recently has the complex anatomo-functional system underlying numerical cognition become accessible to evaluation in the living brain. We identified 27 studies investigating brain connectivity in numerical cognition. Despite considerable heterogeneity regarding methodological approaches, populations investigated, and assessment procedures implemented, the results provided largely converging evidence regarding the underlying brain connectivity involved in numerical cognition. Analyses of both functional/effective as well as structural connectivity have consistently corroborated the assumption that numerical cognition is subserved by a fronto-parietal network including (intra)parietal as well as (pre)frontal cortex sites. Evaluation of structural connectivity has indicated the involvement of fronto-parietal association fibers encompassing the superior longitudinal fasciculus dorsally and the external capsule/extreme capsule system ventrally. Additionally, commissural fibers seem to connect the bilateral intraparietal sulci when number magnitude information is processed. Finally, the identification of projection fibers such as the superior corona radiata indicates connections between cortex and basal ganglia as well as the thalamus in numerical cognition. Studies on functional/effective connectivity further indicated a specific role of the hippocampus. These specifications of brain connectivity augment the triple-code model of number processing and calculation with respect to how gray matter areas associated with specific number-related representations may work together. PMID:26029075

Functional Brain Networks: Does the Choice of Dependency Estimator and Binarization Method Matter?

NASA Astrophysics Data System (ADS)

Jalili, Mahdi

2016-07-01

The human brain can be modelled as a complex networked structure with brain regions as individual nodes and their anatomical/functional links as edges. Functional brain networks are constructed by first extracting weighted connectivity matrices, and then binarizing them to minimize the noise level. Different methods have been used to estimate the dependency values between the nodes and to obtain a binary network from a weighted connectivity matrix. In this work we study topological properties of EEG-based functional networks in Alzheimer’s Disease (AD). To estimate the connectivity strength between two time series, we use Pearson correlation, coherence, phase order parameter and synchronization likelihood. In order to binarize the weighted connectivity matrices, we use Minimum Spanning Tree (MST), Minimum Connected Component (MCC), uniform threshold and density-preserving methods. We find that the detected AD-related abnormalities highly depend on the methods used for dependency estimation and binarization. Topological properties of networks constructed using coherence method and MCC binarization show more significant differences between AD and healthy subjects than the other methods. These results might explain contradictory results reported in the literature for network properties specific to AD symptoms. The analysis method should be seriously taken into account in the interpretation of network-based analysis of brain signals.

New levels of language processing complexity and organization revealed by granger causation.

PubMed

Gow, David W; Caplan, David N

2012-01-01

Granger causation analysis of high spatiotemporal resolution reconstructions of brain activation offers a new window on the dynamic interactions between brain areas that support language processing. Premised on the observation that causes both precede and uniquely predict their effects, this approach provides an intuitive, model-free means of identifying directed causal interactions in the brain. It requires the analysis of all non-redundant potentially interacting signals, and has shown that even "early" processes such as speech perception involve interactions of many areas in a strikingly large network that extends well beyond traditional left hemisphere perisylvian cortex that play out over hundreds of milliseconds. In this paper we describe this technique and review several general findings that reframe the way we think about language processing and brain function in general. These include the extent and complexity of language processing networks, the central role of interactive processing dynamics, the role of processing hubs where the input from many distinct brain regions are integrated, and the degree to which task requirements and stimulus properties influence processing dynamics and inform our understanding of "language-specific" localized processes.

Intrinsic brain networks normalize with treatment in pediatric complex regional pain syndrome

PubMed Central

Becerra, Lino; Sava, Simona; Simons, Laura E.; Drosos, Athena M.; Sethna, Navil; Berde, Charles; Lebel, Alyssa A.; Borsook, David

2014-01-01

Pediatric complex regional pain syndrome (P-CRPS) offers a unique model of chronic neuropathic pain as it either resolves spontaneously or through therapeutic interventions in most patients. Here we evaluated brain changes in well-characterized children and adolescents with P-CRPS by measuring resting state networks before and following a brief (median = 3 weeks) but intensive physical and psychological treatment program, and compared them to matched healthy controls. Differences in intrinsic brain networks were observed in P-CRPS compared to controls before treatment (disease state) with the most prominent differences in the fronto-parietal, salience, default mode, central executive, and sensorimotor networks. Following treatment, behavioral measures demonstrated a reduction of symptoms and improvement of physical state (pain levels and motor functioning). Correlation of network connectivities with spontaneous pain measures pre- and post-treatment indicated concomitant reductions in connectivity in salience, central executive, default mode and sensorimotor networks (treatment effects). These results suggest a rapid alteration in global brain networks with treatment and provide a venue to assess brain changes in CRPS pre- and post-treatment, and to evaluate therapeutic effects. PMID:25379449

Imaging Nicotine in Rat Brain Tissue by Use of Nanospray Desorption Electrospray Ionization Mass Spectrometry

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

Lanekoff, Ingela T.; Thomas, Mathew; Carson, James P.

Imaging mass spectrometry offers simultaneous detection of drugs, drug metabolites and endogenous substances in a single experiment. This is important when evaluating effects of a drug on a complex organ system such as the brain, where there is a need to understand how regional drug distribution impacts function. Nicotine is an addictive drug and its action in the brain is of high interest. Here we use nanospray desorption electrospray ionization, nano-DESI, imaging to discover the localization of nicotine in rat brain tissue after in vivo administration of nicotine. Nano-DESI is a new ambient technique that enables spatially-resolved analysis of tissuemore » samples without special sample pretreatment. We demonstrate high sensitivity of nano-DESI imaging that enables detection of only 0.7 fmole nicotine per pixel in the complex brain matrix. Furthermore, by adding deuterated nicotine to the solvent, we examined how matrix effects, ion suppression, and normalization affect the observed nicotine distribution. Finally, we provide preliminary results suggesting that nicotine localizes to the hippocampal substructure called dentate gyrus.« less

Inhibition of cystathionine-gamma-lyase leads to loss of glutathione and aggravation of mitochondrial dysfunction mediated by excitatory amino acid in the CNS.

PubMed

Diwakar, Latha; Ravindranath, Vijayalakshmi

2007-01-01

Oxidative stress has been implicated in the pathogenesis and progression of neurodegenerative disorders and antioxidants potentially have a major role in neuroprotection. Optimum levels of glutathione (gamma-glutamylcysteinyl glycine), an endogenous thiol antioxidant are required for the maintenance of the redox status of cells. Cystathionine gamma-lyase is the rate-limiting enzyme for the synthesis of cysteine from methionine and availability of cysteine is a critical factor in glutathione synthesis. In the present study, we have examined the role of cystathionine gamma-lyase in maintaining the redox homeostasis in brain, particularly with reference to mitochondrial function since the complex I of the electron transport chain is sensitive to redox perturbation. Inhibition of cystathionine gamma-lyase by l-propargylglycine caused loss of glutathione and decrease in complex I activity in the brain although the enzyme activity in mouse brain was 1% of the corresponding hepatic activity. We then examined the effect of this inhibition on the neurotoxicity mediated by the excitatory amino acid, l-beta-oxalyl amino-l-alanine, which is the causative factor of a type of motor neuron disease, neurolathyrism. l-beta-Oxalyl amino-l-alanine toxicity was exacerbated by l-propargylglycine measured as loss of complex I activity indicating the importance of cystathionine gamma-lyase in maintaining glutathione levels and in turn the mitochondrial function during excitotoxicity. Oxidative stress generated by l-beta-oxalyl amino-l-alanine itself inhibited cystathionine gamma-lyase, which could be prevented by prior treatment with thiol antioxidant. Thus, cystathionine gamma-lyase itself is susceptible to inactivation by oxidative stress and this can potentially exacerbate oxidant-induced damage. Cystathionine gamma-lyase is present in neuronal cells in human brain and its activity is several-fold higher compared to mouse brain. It could potentially play an important role in maintaining glutathione and protein thiol homeostasis in brain and hence afford neuroprotection.

A Selective Review of Simulated Driving Studies: Combining Naturalistic and Hybrid Paradigms, Analysis Approaches, and Future Directions

PubMed Central

Calhoun, V. D.; Pearlson, G. D.

2011-01-01

Naturalistic paradigms such as movie watching or simulated driving that mimic closely real-world complex activities are becoming more widely used in functional magnetic resonance imaging (fMRI) studies both because of their ability to robustly stimulate brain connectivity and the availability of analysis methods which are able to capitalize on connectivity within and among intrinsic brain networks identified both during a task and in resting fMRI data. In this paper we review over a decade of work from our group and others on the use of simulated driving paradigms to study both the healthy brain as well as the effects of acute alcohol administration on functional connectivity during such paradigms. We briefly review our initial work focused on the configuration of the driving simulator and the analysis strategies. We then describe in more detail several recent studies from our group including a hybrid study examining distracted driving and compare resulting data with those from a separate visual oddball task. The analysis of these data were performed primarily using a combination of group independent component analysis (ICA) and the general linear model (GLM) and in the various studies we highlight novel findings which result from an analysis of either 1) within-network connectivity, 2) inter-network connectivity, also called functional network connectivity, or 3) the degree to which the modulation of the various intrinsic networks were associated with the alcohol administration and the task context. Despite the fact that the behavioral effects of alcohol intoxication are relatively well known, there is still much to discover on how acute alcohol exposure modulates brain function in a selective manner, associated with behavioral alterations. Through the above studies, we have learned more regarding the impact of acute alcohol intoxication on organization of the brain’s intrinsic connectivity networks during performance of a complex, real-world cognitive operation. Lessons learned from the above studies have broader applicability to designing ecologically valid, complex, functional MRI cognitive paradigms and incorporating pharmacologic challenges into such studies. Overall, the use of hybrid driving studies is a particularly promising area of neuroscience investigation. PMID:21718791

Complex Actions of Estradiol-3-Sulfate in Late Gestation Fetal Brain

PubMed Central

Winikor, Jared; Schlaerth, Christine; Rabaglino, Maria Belen; Cousins, Roderick; Sutherland, Monique

2011-01-01

The most abundant form of estrogen circulating in fetal plasma is sulfo-conjugated estrogen; for example, estradiol-3-sulfate (E2SO4) is more highly abundant than estradiol (E2). The present study investigated the ontogeny of the deconjugating (steroid sulfatase [STS]) and conjugating (estrogen sulfotransferase [STF]) enzymes in ovine fetal brain and tested the hypothesis that treatment with E2SO4 would alter the expression of one or both enzymes. Steroid sulfatase was more highly expressed than STF, and both changed as a function of gestational age. Estradiol-3-sulfate infused intracerebroventricularly (icv) significantly increased plasma adrenocorticotropic hormone (ACTH) and cortisol concentrations. Plasma E2 and E2SO4 were increased, and brain expression of estrogen receptor α was decreased. The proteins STS and STF were up- and downregulated, respectively. Pituitary proopiomelanocortin (POMC) and follicle-stimulating hormone (FSH) and hypothalamic corticotrophin-releasing hormone (CRH) messenger RNA (mRNA) was decreased. We conclude that E2SO4 has complex actions on the fetal brain, which might involve deconjugation by STS, but that the net result of direct E2SO4 icv infusion is more complex than can be accounted for by infusion of E2 alone. PMID:21273638

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.

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

Realistic modeling of neurons and networks: towards brain simulation.

PubMed

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

2013-01-01

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

Realistic modeling of neurons and networks: towards brain simulation

PubMed Central

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

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

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.

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.

Electrical Neuroimaging of Music Processing Reveals Mid-Latency Changes with Level of Musical Expertise

PubMed Central

James, Clara E.; Oechslin, Mathias S.; Michel, Christoph M.; De Pretto, Michael

2017-01-01

This original research focused on the effect of musical training intensity on cerebral and behavioral processing of complex music using high-density event-related potential (ERP) approaches. Recently we have been able to show progressive changes with training in gray and white matter, and higher order brain functioning using (f)MRI [(functional) Magnetic Resonance Imaging], as well as changes in musical and general cognitive functioning. The current study investigated the same population of non-musicians, amateur pianists and expert pianists using spatio-temporal ERP analysis, by means of microstate analysis, and ERP source imaging. The stimuli consisted of complex musical compositions containing three levels of transgression of musical syntax at closure that participants appraised. ERP waveforms, microstates and underlying brain sources revealed gradual differences according to musical expertise in a 300–500 ms window after the onset of the terminal chords of the pieces. Within this time-window, processing seemed to concern context-based memory updating, indicated by a P3b-like component or microstate for which underlying sources were localized in the right middle temporal gyrus, anterior cingulate and right parahippocampal areas. Given that the 3 expertise groups were carefully matched for demographic factors, these results provide evidence of the progressive impact of training on brain and behavior. PMID:29163017

Electrical Neuroimaging of Music Processing Reveals Mid-Latency Changes with Level of Musical Expertise.

PubMed

James, Clara E; Oechslin, Mathias S; Michel, Christoph M; De Pretto, Michael

2017-01-01

This original research focused on the effect of musical training intensity on cerebral and behavioral processing of complex music using high-density event-related potential (ERP) approaches. Recently we have been able to show progressive changes with training in gray and white matter, and higher order brain functioning using (f)MRI [(functional) Magnetic Resonance Imaging], as well as changes in musical and general cognitive functioning. The current study investigated the same population of non-musicians, amateur pianists and expert pianists using spatio-temporal ERP analysis, by means of microstate analysis, and ERP source imaging. The stimuli consisted of complex musical compositions containing three levels of transgression of musical syntax at closure that participants appraised. ERP waveforms, microstates and underlying brain sources revealed gradual differences according to musical expertise in a 300-500 ms window after the onset of the terminal chords of the pieces. Within this time-window, processing seemed to concern context-based memory updating, indicated by a P3b-like component or microstate for which underlying sources were localized in the right middle temporal gyrus, anterior cingulate and right parahippocampal areas. Given that the 3 expertise groups were carefully matched for demographic factors, these results provide evidence of the progressive impact of training on brain and behavior.

Fractal Dimension of EEG Activity Senses Neuronal Impairment in Acute Stroke

PubMed Central

Zappasodi, Filippo; Olejarczyk, Elzbieta; Marzetti, Laura; Assenza, Giovanni; Pizzella, Vittorio; Tecchio, Franca

2014-01-01

The brain is a self-organizing system which displays self-similarities at different spatial and temporal scales. Thus, the complexity of its dynamics, associated to efficient processing and functional advantages, is expected to be captured by a measure of its scale-free (fractal) properties. Under the hypothesis that the fractal dimension (FD) of the electroencephalographic signal (EEG) is optimally sensitive to the neuronal dysfunction secondary to a brain lesion, we tested the FD’s ability in assessing two key processes in acute stroke: the clinical impairment and the recovery prognosis. Resting EEG was collected in 36 patients 4–10 days after a unilateral ischemic stroke in the middle cerebral artery territory and 19 healthy controls. National Health Institute Stroke Scale (NIHss) was collected at T0 and 6 months later. Highuchi FD, its inter-hemispheric asymmetry (FDasy) and spectral band powers were calculated for EEG signals. FD was smaller in patients than in controls (1.447±0.092 vs 1.525±0.105) and its reduction was paired to a worse acute clinical status. FD decrease was associated to alpha increase and beta decrease of oscillatory activity power. Larger FDasy in acute phase was paired to a worse clinical recovery at six months. FD in our patients captured the loss of complexity reflecting the global system dysfunction resulting from the structural damage. This decrease seems to reveal the intimate nature of structure-function unity, where the regional neural multi-scale self-similar activity is impaired by the anatomical lesion. This picture is coherent with neuronal activity complexity decrease paired to a reduced repertoire of functional abilities. FDasy result highlights the functional relevance of the balance between homologous brain structures’ activities in stroke recovery. PMID:24967904

Fractal dimension of EEG activity senses neuronal impairment in acute stroke.

PubMed

Zappasodi, Filippo; Olejarczyk, Elzbieta; Marzetti, Laura; Assenza, Giovanni; Pizzella, Vittorio; Tecchio, Franca

2014-01-01

The brain is a self-organizing system which displays self-similarities at different spatial and temporal scales. Thus, the complexity of its dynamics, associated to efficient processing and functional advantages, is expected to be captured by a measure of its scale-free (fractal) properties. Under the hypothesis that the fractal dimension (FD) of the electroencephalographic signal (EEG) is optimally sensitive to the neuronal dysfunction secondary to a brain lesion, we tested the FD's ability in assessing two key processes in acute stroke: the clinical impairment and the recovery prognosis. Resting EEG was collected in 36 patients 4-10 days after a unilateral ischemic stroke in the middle cerebral artery territory and 19 healthy controls. National Health Institute Stroke Scale (NIHss) was collected at T0 and 6 months later. Highuchi FD, its inter-hemispheric asymmetry (FDasy) and spectral band powers were calculated for EEG signals. FD was smaller in patients than in controls (1.447±0.092 vs 1.525±0.105) and its reduction was paired to a worse acute clinical status. FD decrease was associated to alpha increase and beta decrease of oscillatory activity power. Larger FDasy in acute phase was paired to a worse clinical recovery at six months. FD in our patients captured the loss of complexity reflecting the global system dysfunction resulting from the structural damage. This decrease seems to reveal the intimate nature of structure-function unity, where the regional neural multi-scale self-similar activity is impaired by the anatomical lesion. This picture is coherent with neuronal activity complexity decrease paired to a reduced repertoire of functional abilities. FDasy result highlights the functional relevance of the balance between homologous brain structures' activities in stroke recovery.

Neurogenetics of developmental dyslexia: from genes to behavior through brain neuroimaging and cognitive and sensorial mechanisms

PubMed Central

Mascheretti, S; De Luca, A; Trezzi, V; Peruzzo, D; Nordio, A; Marino, C; Arrigoni, F

2017-01-01

Developmental dyslexia (DD) is a complex neurodevelopmental deficit characterized by impaired reading acquisition, in spite of adequate neurological and sensorial conditions, educational opportunities and normal intelligence. Despite the successful characterization of DD-susceptibility genes, we are far from understanding the molecular etiological pathways underlying the development of reading (dis)ability. By focusing mainly on clinical phenotypes, the molecular genetics approach has yielded mixed results. More optimally reduced measures of functioning, that is, intermediate phenotypes (IPs), represent a target for researching disease-associated genetic variants and for elucidating the underlying mechanisms. Imaging data provide a viable IP for complex neurobehavioral disorders and have been extensively used to investigate both morphological, structural and functional brain abnormalities in DD. Performing joint genetic and neuroimaging studies in humans is an emerging strategy to link DD-candidate genes to the brain structure and function. A limited number of studies has already pursued the imaging–genetics integration in DD. However, the results are still not sufficient to unravel the complexity of the reading circuit due to heterogeneous study design and data processing. Here, we propose an interdisciplinary, multilevel, imaging–genetic approach to disentangle the pathways from genes to behavior. As the presence of putative functional genetic variants has been provided and as genetic associations with specific cognitive/sensorial mechanisms have been reported, new hypothesis-driven imaging–genetic studies must gain momentum. This approach would lead to the optimization of diagnostic criteria and to the early identification of ‘biologically at-risk’ children, supporting the definition of adequate and well-timed prevention strategies and the implementation of novel, specific remediation approach. PMID:28045463

Brain MRI Tumor Detection using Active Contour Model and Local Image Fitting Energy

NASA Astrophysics Data System (ADS)

Nabizadeh, Nooshin; John, Nigel

2014-03-01

Automatic abnormality detection in Magnetic Resonance Imaging (MRI) is an important issue in many diagnostic and therapeutic applications. Here an automatic brain tumor detection method is introduced that uses T1-weighted images and K. Zhang et. al.'s active contour model driven by local image fitting (LIF) energy. Local image fitting energy obtains the local image information, which enables the algorithm to segment images with intensity inhomogeneities. Advantage of this method is that the LIF energy functional has less computational complexity than the local binary fitting (LBF) energy functional; moreover, it maintains the sub-pixel accuracy and boundary regularization properties. In Zhang's algorithm, a new level set method based on Gaussian filtering is used to implement the variational formulation, which is not only vigorous to prevent the energy functional from being trapped into local minimum, but also effective in keeping the level set function regular. Experiments show that the proposed method achieves high accuracy brain tumor segmentation results.

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.

Scopolamine effects on functional brain connectivity: a pharmacological model of Alzheimer's disease.

PubMed

Bajo, R; Pusil, S; López, M E; Canuet, L; Pereda, E; Osipova, D; Maestú, F; Pekkonen, E

2015-07-01

Scopolamine administration may be considered as a psychopharmacological model of Alzheimer's disease (AD). Here, we studied a group of healthy elderly under scopolamine to test whether it elicits similar changes in brain connectivity as those observed in AD, thereby verifying a possible model of AD impairment. We did it by testing healthy elderly subjects in two experimental conditions: glycopyrrolate (placebo) and scopolamine administration. We then analyzed magnetoencephalographic (MEG) data corresponding to both conditions in resting-state with eyes closed. This analysis was performed in source space by combining a nonlinear frequency band-specific measure of functional connectivity (phase locking value, PLV) with network analysis methods. Under scopolamine, functional connectivity between several brain areas was significantly reduced as compared to placebo, in most frequency bands analyzed. Besides, regarding the two complex network indices studied (clustering and shortest path length), clustering significantly decreased in the alpha band while shortest path length significantly increased also in alpha band both after scopolamine administration. Overall our findings indicate that both PLV and graph analysis are suitable tools to measure brain connectivity changes induced by scopolamine, which causes alterations in brain connectivity apparently similar to those reported in AD.

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

Weak Higher-Order Interactions in Macroscopic Functional Networks of the Resting Brain.

PubMed

Huang, Xuhui; Xu, Kaibin; Chu, Congying; Jiang, Tianzi; Yu, Shan

2017-10-25

Interactions among different brain regions are usually examined through functional connectivity (FC) analysis, which is exclusively based on measuring pairwise correlations in activities. However, interactions beyond the pairwise level, that is, higher-order interactions (HOIs), are vital in understanding the behavior of many complex systems. So far, whether HOIs exist among brain regions and how they can affect the brain's activities remains largely elusive. To address these issues, here, we analyzed blood oxygenation level-dependent (BOLD) signals recorded from six typical macroscopic functional networks of the brain in 100 human subjects (46 males and 54 females) during the resting state. Through examining the binarized BOLD signals, we found that HOIs within and across individual networks were both very weak regardless of the network size, topology, degree of spatial proximity, spatial scales, and whether the global signal was regressed. To investigate the potential mechanisms underlying the weak HOIs, we analyzed the dynamics of a network model and also found that HOIs were generally weak within a wide range of key parameters provided that the overall dynamic feature of the model was similar to the empirical data and it was operating close to a linear fluctuation regime. Our results suggest that weak HOI may be a general property of brain's macroscopic functional networks, which implies the dominance of pairwise interactions in shaping brain activities at such a scale and warrants the validity of widely used pairwise-based FC approaches. SIGNIFICANCE STATEMENT To explain how activities of different brain areas are coordinated through interactions is essential to revealing the mechanisms underlying various brain functions. Traditionally, such an interaction structure is commonly studied using pairwise-based functional network analyses. It is unclear whether the interactions beyond the pairwise level (higher-order interactions or HOIs) play any role in this process. Here, we show that HOIs are generally weak in macroscopic brain networks. We also suggest a possible dynamical mechanism that may underlie this phenomenon. These results provide plausible explanation for the effectiveness of widely used pairwise-based approaches in analyzing brain networks. More importantly, it reveals a previously unknown, simple organization of the brain's macroscopic functional systems. Copyright © 2017 the authors 0270-6474/17/3710481-17$15.00/0.

A critical view of the quest for brain structural markers of Albert Einstein's special talents (a pot of gold under the rainbow).

PubMed

Colombo, Jorge A

2018-06-01

Assertions regarding attempts to link glial and macrostructural brain events with cognitive performance regarding Albert Einstein, are critically reviewed. One basic problem arises from attempting to draw causal relationships regarding complex, delicately interactive functional processes involving finely tuned molecular and connectivity phenomena expressed in cognitive performance, based on highly variable brain structural events of a single, aged, formalin fixed brain. Data weaknesses and logical flaws are considered. In other instances, similar neuroanatomical observations received different interpretations and conclusions, as those drawn, e.g., from schizophrenic brains. Observations on white matter events also raise methodological queries. Additionally, neurocognitive considerations on other intellectual aptitudes of A. Einstein were simply ignored.

The neural code of thoughts and feelings. Comment on "Topodynamics of metastable brains" by Arturo Tozzi et al.

NASA Astrophysics Data System (ADS)

Jaušovec, Norbert

2017-07-01

Recently the number of theories trying to explain the brain - cognition - behavior relation has been increased. Promoted on the one hand by the development of sophisticated brain imaging techniques, such as functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI), and on the other, by complex computational models based on chaos and graph theory. But has this really advanced our understanding of the brain-behavior relation beyond Descartes's dualistic mind body division? One could critically argue that replacing the pineal body with extracellular electric fields represented in the electroencephalogram (EEG) as rapid transitional processes (RTS), combined with algebraic topology and dubbed brain topodynamics [1] is just putting lipstick on an outmoded evergreen.

Genetic strategies to investigate neuronal circuit properties using stem cell-derived neurons

PubMed Central

Garcia, Isabella; Kim, Cynthia; Arenkiel, Benjamin R.

2012-01-01

The mammalian brain is anatomically and functionally complex, and prone to diverse forms of injury and neuropathology. Scientists have long strived to develop cell replacement therapies to repair damaged and diseased nervous tissue. However, this goal has remained unrealized for various reasons, including nascent knowledge of neuronal development, the inability to track and manipulate transplanted cells within complex neuronal networks, and host graft rejection. Recent advances in embryonic stem cell (ESC) and induced pluripotent stem cell (iPSC) technology, alongside novel genetic strategies to mark and manipulate stem cell-derived neurons, now provide unprecedented opportunities to investigate complex neuronal circuits in both healthy and diseased brains. Here, we review current technologies aimed at generating and manipulating neurons derived from ESCs and iPSCs toward investigation and manipulation of complex neuronal circuits, ultimately leading to the design and development of novel cell-based therapeutic approaches. PMID:23264761

Longitudinal sleep EEG trajectories indicate complex patterns of adolescent brain maturation.

PubMed

Feinberg, Irwin; Campbell, Ian G

2013-02-15

New longitudinal sleep data spanning ages 6-10 yr are presented and combined with previous data to analyze maturational trajectories of delta and theta EEG across ages 6-18 yr in non-rapid eye movement (NREM) and rapid eye movement (REM) sleep. NREM delta power (DP) increased from age 6 to age 8 yr and then declined. Its highest rate of decline occurred between ages 12 and 16.5 yr. We attribute the delta EEG trajectories to changes in synaptic density. Whatever their neuronal underpinnings, these age curves can guide research into the molecular-genetic mechanisms that underlie adolescent brain development. The DP trajectories in NREM and REM sleep differed strikingly. DP in REM did not initially increase but declined steadily from age 6 to age 16 yr. We hypothesize that the DP decline in REM reflects maturation of the same brain arousal systems that eliminate delta waves in waking EEG. Whereas the DP age curves differed in NREM and REM sleep, theta age curves were similar in both, roughly paralleling the age trajectory of REM DP. The different maturational curves for NREM delta and theta indicate that they serve different brain functions despite having similar within-sleep dynamics and responses to sleep loss. Period-amplitude analysis of NREM and REM delta waveforms revealed that the age trends in DP were driven more by changes in wave amplitude rather than incidence. These data further document the powerful and complex link between sleep and brain maturation. Understanding this relationship would shed light on both brain development and the function of sleep.

Developmental imaging genetics: linking dopamine function to adolescent behavior.

PubMed

Padmanabhan, Aarthi; Luna, Beatriz

2014-08-01

Adolescence is a period of development characterized by numerous neurobiological changes that significantly influence behavior and brain function. Adolescence is of particular interest due to the alarming statistics indicating that mortality rates increase two to three-fold during this time compared to childhood, due largely to a peak in risk-taking behaviors resulting from increased impulsivity and sensation seeking. Furthermore, there exists large unexplained variability in these behaviors that are in part mediated by biological factors. Recent advances in molecular genetics and functional neuroimaging have provided a unique and exciting opportunity to non-invasively study the influence of genetic factors on brain function in humans. While genes do not code for specific behaviors, they do determine the structure and function of proteins that are essential to the neuronal processes that underlie behavior. Therefore, studying the interaction of genotype with measures of brain function over development could shed light on critical time points when biologically mediated individual differences in complex behaviors emerge. Here we review animal and human literature examining the neurobiological basis of adolescent development related to dopamine neurotransmission. Dopamine is of critical importance because of (1) its role in cognitive and affective behaviors, (2) its role in the pathogenesis of major psychopathology, and (3) the protracted development of dopamine signaling pathways over adolescence. We will then focus on current research examining the role of dopamine-related genes on brain function. We propose the use of imaging genetics to examine the influence of genetically mediated dopamine variability on brain function during adolescence, keeping in mind the limitations of this approach. Copyright © 2014 Elsevier Inc. All rights reserved.

What kind of noise is brain noise: anomalous scaling behavior of the resting brain activity fluctuations

PubMed Central

Fraiman, Daniel; Chialvo, Dante R.

2012-01-01

The study of spontaneous fluctuations of brain activity, often referred as brain noise, is getting increasing attention in functional magnetic resonance imaging (fMRI) studies. Despite important efforts, much of the statistical properties of such fluctuations remain largely unknown. This work scrutinizes these fluctuations looking at specific statistical properties which are relevant to clarify its dynamical origins. Here, three statistical features which clearly differentiate brain data from naive expectations for random processes are uncovered: First, the variance of the fMRI mean signal as a function of the number of averaged voxels remains constant across a wide range of observed clusters sizes. Second, the anomalous behavior of the variance is originated by bursts of synchronized activity across regions, regardless of their widely different sizes. Finally, the correlation length (i.e., the length at which the correlation strength between two regions vanishes) as well as mutual information diverges with the cluster's size considered, such that arbitrarily large clusters exhibit the same collective dynamics than smaller ones. These three properties are known to be exclusive of complex systems exhibiting critical dynamics, where the spatio-temporal dynamics show these peculiar type of fluctuations. Thus, these findings are fully consistent with previous reports of brain critical dynamics, and are relevant for the interpretation of the role of fluctuations and variability in brain function in health and disease. PMID:22934058

Simulated driving and brain imaging: combining behavior, brain activity, and virtual reality.

PubMed

Carvalho, Kara N; Pearlson, Godfrey D; Astur, Robert S; Calhoun, Vince D

2006-01-01

Virtual reality in the form of simulated driving is a useful tool for studying the brain. Various clinical questions can be addressed, including both the role of alcohol as a modulator of brain function and regional brain activation related to elements of driving. We reviewed a study of the neural correlates of alcohol intoxication through the use of a simulated-driving paradigm and wished to demonstrate the utility of recording continuous-driving behavior through a new study using a programmable driving simulator developed at our center. Functional magnetic resonance imaging data was collected from subjects while operating a driving simulator. Independent component analysis (ICA) was used to analyze the data. Specific brain regions modulated by alcohol, and relationships between behavior, brain function, and alcohol blood levels were examined with aggregate behavioral measures. Fifteen driving epochs taken from two subjects while also recording continuously recorded driving variables were analyzed with ICA. Preliminary findings reveal that four independent components correlate with various aspects of behavior. An increase in braking while driving was found to increase activation in motor areas, while cerebellar areas showed signal increases during steering maintenance, yet signal decreases during steering changes. Additional components and significant findings are further outlined. In summary, continuous behavioral variables conjoined with ICA may offer new insight into the neural correlates of complex human behavior.

Embodying Markov blankets. Comment on "Answering Schrödinger's question: A free-energy formulation" by Maxwell James Désormeau Ramstead et al.

NASA Astrophysics Data System (ADS)

Pezzulo, Giovanni; Levin, Michael

2018-03-01

The free-energy principle (FEP) has been initially proposed as a theory of brain structure and function [1], but its scope is rapidly extending to explain biological phenomena at multiple levels of complexity, from simple life forms and their morphology [2] to complex societal and cultural dynamics [3].

Anti-Inflammatory Effects of Omega-3 Fatty Acids in the Brain: Physiological Mechanisms and Relevance to Pharmacology.

PubMed

Layé, Sophie; Nadjar, Agnès; Joffre, Corinne; Bazinet, Richard P

2018-01-01

Classically, polyunsaturated fatty acids (PUFA) were largely thought to be relatively inert structural components of brain, largely important for the formation of cellular membranes. Over the past 10 years, a host of bioactive lipid mediators that are enzymatically derived from arachidonic acid, the main n-6 PUFA, and docosahexaenoic acid, the main n-3 PUFA in the brain, known to regulate peripheral immune function, have been detected in the brain and shown to regulate microglia activation. Recent advances have focused on how PUFA regulate the molecular signaling of microglia, especially in the context of neuroinflammation and behavior. Several active drugs regulate brain lipid signaling and provide proof of concept for targeting the brain. Because brain lipid metabolism relies on a complex integration of diet, peripheral metabolism, including the liver and blood, which supply the brain with PUFAs that can be altered by genetics, sex, and aging, there are many pathways that can be disrupted, leading to altered brain lipid homeostasis. Brain lipid signaling pathways are altered in neurologic disorders and may be viable targets for the development of novel therapeutics. In this study, we discuss in particular how n-3 PUFAs and their metabolites regulate microglia phenotype and function to exert their anti-inflammatory and proresolving activities in the brain. Copyright © 2017 by The American Society for Pharmacology and Experimental Therapeutics.

Age-and Brain Region-Specific Differences in Mitochondrial ...

EPA Pesticide Factsheets

Mitochondria are central regulators of energy homeostasis and play a pivotal role in mechanisms of cellular senescence. The objective of the present study was to evaluate mitochondrial bio­-energetic parameters in five brain regions [brainstem (BS), frontal cortex (FC), cerebellum (CER), striatum (STR), hippocampus (HIP)] of four diverse age groups [1 Month (young), 4 Month (adult), 12 Month (middle-aged), 24 Month (old age)] to understand age-related differences in selected brain regions and their contribution to age-related chemical sensitivity. Mitochondrial bioenergetics parameters and enzyme activity were measured under identical conditions across multiple age groups and brain regions in Brown Norway rats (n = 5). The results indicate age- and brain region-specific patterns in mitochondrial functional endpoints. For example, an age-specific decline in ATP synthesis (State 111 respiration) was observed in BS and HIP. Similarly, the maximal respiratory capacities (State V1 and V2) showed age-specific declines in all brain regions examined (young > adult > middle-aged > old age). Amongst all regions, HIP had the greatest change in mitochondrial bioenergetics, showing declines in the 4, 12 and 24 Month age groups. Activities of mitochondrial pyruvate dehydrogenase complex (PDHC) and electron transport chain (ETC) complexes I, II, and IV enzymes were also age- and brain-region specific. In general changes associated with age were more pronounced, with

Forging our understanding of lncRNAs in the brain.

PubMed

Andersen, Rebecca E; Lim, Daniel A

2018-01-01

During both development and adulthood, the human brain expresses many thousands of long noncoding RNAs (lncRNAs), and aberrant lncRNA expression has been associated with a wide range of neurological diseases. Although the biological significance of most lncRNAs remains to be discovered, it is now clear that certain lncRNAs carry out important functions in neurodevelopment, neural cell function, and perhaps even diseases of the human brain. Given the relatively inclusive definition of lncRNAs-transcripts longer than 200 nucleotides with essentially no protein coding potential-this class of noncoding transcript is both large and very diverse. Furthermore, emerging data indicate that lncRNA genes can act via multiple, non-mutually exclusive molecular mechanisms, and specific functions are difficult to predict from lncRNA expression or sequence alone. Thus, the different experimental approaches used to explore the role of a lncRNA might each shed light upon distinct facets of its overall molecular mechanism, and combining multiple approaches may be necessary to fully illuminate the function of any particular lncRNA. To understand how lncRNAs affect brain development and neurological disease, in vivo studies of lncRNA function are required. Thus, in this review, we focus our discussion upon a small set of neural lncRNAs that have been experimentally manipulated in mice. Together, these examples illustrate how studies of individual lncRNAs using multiple experimental approaches can help reveal the richness and complexity of lncRNA function in both neurodevelopment and diseases of the brain.

Curcumin prevents mitochondrial dysfunction in the brain of the senescence-accelerated mouse-prone 8.

PubMed

Eckert, Gunter P; Schiborr, Christina; Hagl, Stephanie; Abdel-Kader, Reham; Müller, Walter E; Rimbach, Gerald; Frank, Jan

2013-04-01

The aging brain suffers mitochondrial dysfunction and a reduced availability of energy in the form of ATP, which in turn may cause or promote the decline in cognitive, sensory, and motor function observed with advancing age. There is a need for animal models that display some of the pathological features of human brain aging in order to study their prevention by e.g. dietary factors. We thus investigated the suitability of the fast-aging senescence-accelerated mouse-prone 8 (SAMP8) strain and its normally aging control senescence-accelerated mouse-resistant 1 (SAMR1) as a model for the age-dependent changes in mitochondrial function in the brain. To this end, 2-months old male SAMR1 (n=10) and SAMP8 mice (n=7) were fed a Western type diet (control groups) for 5months and one group of SAMP8 mice (n=6) was fed an identical diet fortified with 500mg curcumin per kg. Dissociated brain cells and brain tissue homogenates were analyzed for malondialdehyde, heme oxygenase-1 mRNA, mitochondrial membrane potential (MMP), ATP concentrations, protein levels of mitochondrial marker proteins for mitochondrial membranes (TIMM, TOMM), the mitochondrial permeability transition pore (ANT1, VDAC1, TSPO), respiration complexes, and fission and fusion (Fis, Opa1, Mfn1, Drp1). Dissociated brain cells isolated from SAMP8 mice showed significantly reduced MMP and ATP levels, probably due to significantly diminished complex V protein expression, and increased expression of TSPO. Fission and fusion marker proteins indicate enhanced mitochondrial fission in brains of SAMP8 mice. Treatment of SAMP8 mice with curcumin improved MMP and ATP and restored mitochondrial fusion, probably by up-regulating nuclear factor PGC1α protein expression. In conclusion, SAMP8 compared to SAMR1 mice are a suitable model to study age-dependent changes in mitochondrial function and curcumin emerges as a promising nutraceutical for the prevention of neurodegenerative diseases that are accompanied or caused by mitochondrial dysfunction. Copyright © 2013 Elsevier Ltd. All rights reserved.

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.

Narrative Skill in Children with Early Unilateral Brain Injury: A Possible Limit to Functional Plasticity

PubMed Central

Demir, Özlem Ece; Levine, Susan C.; Goldin-Meadow, Susan

2009-01-01

Children with pre- or perinatal brain injury (PL) exhibit marked plasticity for language learning. Previous work mostly focused on the emergence of earlier developing skills, such as vocabulary and syntax. Here we ask whether this plasticity for earlier developing aspects of language extends to more complex, later-developing language functions by examining the narrative production of children with PL. Using an elicitation technique that involves asking children to create stories de novo in response to a story stem, we collected narratives from 11 children with PL and 20 typically-developing (TD) children. Narratives were analyzed for length, diversity of the vocabulary used, use of complex syntax, complexity of the macro-level narrative structure and use of narrative evaluation. Children’s language performance on vocabulary and syntax tasks outside of the narrative context was also measured. Findings show that children with PL produced shorter stories, used less diverse vocabulary, produced structurally less complex stories at the macro-level, and made fewer inferences regarding the cognitive states of the story characters. These differences in the narrative task emerged even though children with PL did not differ from TD children on vocabulary and syntax tasks outside of the narrative context. Thus, findings suggest that there may be limitations to the plasticity for language functions displayed by children with PL, and that these limitations may be most apparent in complex, decontextualized language tasks such as narrative production. PMID:20590727

Neurophotonics: optical methods to study and control the brain

NASA Astrophysics Data System (ADS)

Doronina-Amitonova, L. V.; Fedotov, I. V.; Fedotov, A. B.; Anokhin, K. V.; Zheltikov, A. M.

2015-04-01

Methods of optical physics offer unique opportunities for the investigation of brain and higher nervous activity. The integration of cutting-edge laser technologies and advanced neurobiology opens a new cross-disciplinary area of natural sciences - neurophotonics - focusing on the development of a vast arsenal of tools for functional brain diagnostics, stimulation of individual neurons and neural networks, and the molecular engineering of brain cells aimed at the diagnosis and therapy of neurodegenerative and psychic diseases. Optical fibers help to confront the most challenging problems in brain research, including the analysis of molecular-cellular mechanisms of the formation of memory and behavior. New generation optical fibers provide new solutions for the development of fundamentally new, unique tools for neurophotonics and laser neuroengineering - fiber-optic neuroendoscopes and neurointerfaces. These instruments broaden research horizons when investigating the most complex brain functions, enabling a long-term multiplex detection of fluorescent protein markers, as well as photostimulation of neuronal activity in deep brain areas in living, freely moving animals with an unprecedented spatial resolution and minimal invasiveness. This emerging technology opens new horizons for understanding learning and long-term memory through experiments with living, freely moving mammals. Here, we present a brief review of this rapidly growing field of research.

Neural-endocrine-immune complex in the central modulation of tumorigenesis: facts, assumptions, and hypotheses.

PubMed

Mravec, Boris; Gidron, Yori; Kukanova, Barbara; Bizik, Jozef; Kiss, Alexander; Hulin, Ivan

2006-11-01

For the precise coordination of systemic functions, the nervous system uses a variety of peripherally and centrally localized receptors, which transmit information from internal and external environments to the central nervous system. Tight interconnections between the immune, nervous, and endocrine systems provide a base for monitoring and consequent modulation of immune system functions by the brain and vice versa. The immune system plays an important role in tumorigenesis. On the basis of rich interconnections between the immune, nervous and endocrine systems, the possibility that the brain may be informed about tumorigenesis is discussed in this review article. Moreover, the eventual modulation of tumorigenesis by central nervous system is also considered. Prospective consequences of the interactions between tumor and brain for diagnosis and therapy of cancer are emphasized.

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

Hand in glove: brain and skull in development and dysmorphogenesis

PubMed Central

Flaherty, Kevin

2013-01-01

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

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

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

Understanding the evolution of Mammalian brain structures; the need for a (new) cerebrotype approach.

PubMed

Willemet, Romain

2012-05-18

The mammalian brain varies in size by a factor of 100,000 and is composed of anatomically and functionally distinct structures. Theoretically, the manner in which brain composition can evolve is limited, ranging from highly modular ("mosaic evolution") to coordinated changes in brain structure size ("concerted evolution") or anything between these two extremes. There is a debate about the relative importance of these distinct evolutionary trends. It is shown here that the presence of taxa-specific allometric relationships between brain structures makes a taxa-specific approach obligatory. In some taxa, the evolution of the size of brain structures follows a unique, coordinated pattern, which, in addition to other characteristics at different anatomical levels, defines what has been called here a "taxon cerebrotype". In other taxa, no clear pattern is found, reflecting heterogeneity of the species' lifestyles. These results suggest that the evolution of brain size and composition depends on the complex interplay between selection pressures and constraints that have changed constantly during mammalian evolution. Therefore the variability in brain composition between species should not be considered as deviations from the normal, concerted mammalian trend, but in taxa and species-specific versions of the mammalian brain. Because it forms homogenous groups of species within this complex "space" of constraints and selection pressures, the cerebrotype approach developed here could constitute an adequate level of analysis for evo-devo studies, and by extension, for a wide range of disciplines related to brain evolution.

Understanding the Evolution of Mammalian Brain Structures; the Need for a (New) Cerebrotype Approach

PubMed Central

Willemet, Romain

2012-01-01

The mammalian brain varies in size by a factor of 100,000 and is composed of anatomically and functionally distinct structures. Theoretically, the manner in which brain composition can evolve is limited, ranging from highly modular (“mosaic evolution”) to coordinated changes in brain structure size (“concerted evolution”) or anything between these two extremes. There is a debate about the relative importance of these distinct evolutionary trends. It is shown here that the presence of taxa-specific allometric relationships between brain structures makes a taxa-specific approach obligatory. In some taxa, the evolution of the size of brain structures follows a unique, coordinated pattern, which, in addition to other characteristics at different anatomical levels, defines what has been called here a “taxon cerebrotype”. In other taxa, no clear pattern is found, reflecting heterogeneity of the species’ lifestyles. These results suggest that the evolution of brain size and composition depends on the complex interplay between selection pressures and constraints that have changed constantly during mammalian evolution. Therefore the variability in brain composition between species should not be considered as deviations from the normal, concerted mammalian trend, but in taxa and species-specific versions of the mammalian brain. Because it forms homogenous groups of species within this complex “space” of constraints and selection pressures, the cerebrotype approach developed here could constitute an adequate level of analysis for evo-devo studies, and by extension, for a wide range of disciplines related to brain evolution. PMID:24962772

Small molecule analysis and imaging of fatty acids in the zebra finch song system using time-of-flight-secondary ion mass spectrometry.

PubMed

Amaya, Kensey R; Sweedler, Jonathan V; Clayton, David F

2011-08-01

Fatty acids are central to brain metabolism and signaling, but their distributions within complex brain circuits have been difficult to study. Here we applied an emerging technique, time-of-flight secondary ion mass spectrometry (ToF-SIMS), to image specific fatty acids in a favorable model system for chemical analyses of brain circuits, the zebra finch (Taeniopygia guttata). The zebra finch, a songbird, produces complex learned vocalizations under the control of an interconnected set of discrete, dedicated brain nuclei 'song nuclei'. Using ToF-SIMS, the major song nuclei were visualized by virtue of differences in their content of essential and non-essential fatty acids. Essential fatty acids (arachidonic acid and docosahexaenoic acid) showed distinctive distributions across the song nuclei, and the 18-carbon fatty acids stearate and oleate discriminated the different core and shell subregions of the lateral magnocellular nucleus of the anterior nidopallium. Principal component analysis of the spectral data set provided further evidence of chemical distinctions between the song nuclei. By analyzing the robust nucleus of the arcopallium at three different ages during juvenile song learning, we obtain the first direct evidence of changes in lipid content that correlate with progression of song learning. The results demonstrate the value of ToF-SIMS to study lipids in a favorable model system for probing the function of lipids in brain organization, development and function. © 2011 The Authors. Journal of Neurochemistry © 2011 International Society for Neurochemistry.

The social brain hypothesis of schizophrenia.

PubMed

Burns, Jonathan

2006-06-01

The social brain hypothesis is a useful heuristic for understanding schizophrenia. It focuses attention on the core Bleulerian concept of autistic alienation and is consistent with well-replicated findings of social brain dysfunction in schizophrenia as well as contemporary theories of human cognitive and brain evolution. The contributions of Heidegger, Merleau-Ponty and Wittgenstein allow us to arrive at a new "philosophy of interpersonal relatedness", which better reflects the "embodied mind" and signifies the end of Cartesian dualistic thinking. In this paper I review the evolution, development and neurobiology of the social brain - the anatomical and functional substrate for adaptive social behaviour and cognition. Functional imaging identifies fronto-temporal and fronto-parietal cortical networks as comprising the social brain, while the discovery of "mirror neurons" provides an understanding of social cognition at a cellular level. Patients with schizophrenia display abnormalities in a wide range of social cognition tasks such as emotion recognition, theory of mind and affective responsiveness. Furthermore, recent research indicates that schizophrenia is a disorder of functional and structural connectivity of social brain networks. These findings lend support to the claim that schizophrenia represents a costly by-product of social brain evolution in Homo sapiens. Individuals with this disorder find themselves seriously disadvantaged in the social arena and vulnerable to the stresses of their complex social environments. This state of "disembodiment" and interpersonal alienation is the core phenomenon of schizophrenia and the root cause of intolerable suffering in the lives of those affected.

The social brain hypothesis of schizophrenia

PubMed Central

BURNS, JONATHAN

2006-01-01

The social brain hypothesis is a useful heuristic for understanding schizophrenia. It focuses attention on the core Bleulerian concept of autistic alienation and is consistent with well-replicated findings of social brain dysfunction in schizophrenia as well as contemporary theories of human cognitive and brain evolution. The contributions of Heidegger, Merleau-Ponty and Wittgenstein allow us to arrive at a new "philosophy of interpersonal relatedness", which better reflects the "embodied mind" and signifies the end of Cartesian dualistic thinking. In this paper I review the evolution, development and neurobiology of the social brain - the anatomical and functional substrate for adaptive social behaviour and cognition. Functional imaging identifies fronto-temporal and fronto-parietal cortical networks as comprising the social brain, while the discovery of "mirror neurons" provides an understanding of social cognition at a cellular level. Patients with schizophrenia display abnormalities in a wide range of social cognition tasks such as emotion recognition, theory of mind and affective responsiveness. Furthermore, recent research indicates that schizophrenia is a disorder of functional and structural connectivity of social brain networks. These findings lend support to the claim that schizophrenia represents a costly by-product of social brain evolution in Homo sapiens. Individuals with this disorder find themselves seriously disadvantaged in the social arena and vulnerable to the stresses of their complex social environments. This state of "disembodiment" and interpersonal alienation is the core phenomenon of schizophrenia and the root cause of intolerable suffering in the lives of those affected. PMID:16946939

Brain-Computer Interfaces in Medicine

PubMed Central

Shih, Jerry J.; Krusienski, Dean J.; Wolpaw, Jonathan R.

2012-01-01

Brain-computer interfaces (BCIs) acquire brain signals, analyze them, and translate them into commands that are relayed to output devices that carry out desired actions. BCIs do not use normal neuromuscular output pathways. The main goal of BCI is to replace or restore useful function to people disabled by neuromuscular disorders such as amyotrophic lateral sclerosis, cerebral palsy, stroke, or spinal cord injury. From initial demonstrations of electroencephalography-based spelling and single-neuron-based device control, researchers have gone on to use electroencephalographic, intracortical, electrocorticographic, and other brain signals for increasingly complex control of cursors, robotic arms, prostheses, wheelchairs, and other devices. Brain-computer interfaces may also prove useful for rehabilitation after stroke and for other disorders. In the future, they might augment the performance of surgeons or other medical professionals. Brain-computer interface technology is the focus of a rapidly growing research and development enterprise that is greatly exciting scientists, engineers, clinicians, and the public in general. Its future achievements will depend on advances in 3 crucial areas. Brain-computer interfaces need signal-acquisition hardware that is convenient, portable, safe, and able to function in all environments. Brain-computer interface systems need to be validated in long-term studies of real-world use by people with severe disabilities, and effective and viable models for their widespread dissemination must be implemented. Finally, the day-to-day and moment-to-moment reliability of BCI performance must be improved so that it approaches the reliability of natural muscle-based function. PMID:22325364

Functional Polarity of Microvascular Brain Endothelial Cells Supported by Neurovascular Unit Computational Model of Large Neutral Amino Acid Homeostasis

PubMed Central

Taslimifar, Mehdi; Buoso, Stefano; Verrey, Francois; Kurtcuoglu, Vartan

2018-01-01

The homeostatic regulation of large neutral amino acid (LNAA) concentration in the brain interstitial fluid (ISF) is essential for proper brain function. LNAA passage into the brain is primarily mediated by the complex and dynamic interactions between various solute carrier (SLC) transporters expressed in the neurovascular unit (NVU), among which SLC7A5/LAT1 is considered to be the major contributor in microvascular brain endothelial cells (MBEC). The LAT1-mediated trans-endothelial transport of LNAAs, however, could not be characterized precisely by available in vitro and in vivo standard methods so far. To circumvent these limitations, we have incorporated published in vivo data of rat brain into a robust computational model of NVU-LNAA homeostasis, allowing us to evaluate hypotheses concerning LAT1-mediated trans-endothelial transport of LNAAs across the blood brain barrier (BBB). We show that accounting for functional polarity of MBECs with either asymmetric LAT1 distribution between membranes and/or intrinsic LAT1 asymmetry with low intraendothelial binding affinity is required to reproduce the experimentally measured brain ISF response to intraperitoneal (IP) L-tyrosine and L-phenylalanine injection. On the basis of these findings, we have also investigated the effect of IP administrated L-tyrosine and L-phenylalanine on the dynamics of LNAAs in MBECs, astrocytes and neurons. Finally, the computational model was shown to explain the trans-stimulation of LNAA uptake across the BBB observed upon ISF perfusion with a competitive LAT1 inhibitor. PMID:29593549

The influence of sex chromosome aneuploidy on brain asymmetry.

PubMed

Rezaie, Roozbeh; Daly, Eileen M; Cutter, William J; Murphy, Declan G M; Robertson, Dene M W; DeLisi, Lynn E; Mackay, Clare E; Barrick, Thomas R; Crow, Timothy J; Roberts, Neil

2009-01-05

The cognitive deficits present in individuals with sex chromosome aneuploidies suggest that hemispheric differentiation of function is determined by an X-Y homologous gene [Crow (1993); Lancet 342:594-598]. In particular, females with Turner's syndrome (TS) who have only one X-chromosome exhibit deficits of spatial ability whereas males with Klinefelter's syndrome (KS) who possess a supernumerary X-chromosome are delayed in acquiring words. Since spatial and verbal abilities are generally associated with right and left hemispheric function, such deficits may relate to anomalies of cerebral asymmetry. We therefore applied a novel image analysis technique to investigate the relationship between sex chromosome dosage and structural brain asymmetry. Specifically, we tested Crow's prediction that the magnitude of the brain torque (i.e., a combination of rightward frontal and leftward occipital asymmetry) would, as a function of sex chromosome dosage, be respectively decreased in TS women and increased in KS men, relative to genotypically normal controls. We found that brain torque was not significantly different in TS women and KS men, in comparison to controls. However, TS women exhibited significantly increased leftward brain asymmetry, restricted to the posterior of the brain and focused on the superior temporal and parietal-occipital association cortex, while KS men showed a trend for decreased brain asymmetry throughout the frontal lobes. The findings suggest that the number of sex chromosomes influences the development of brain asymmetry not simply to modify the torque but in a complex pattern along the antero-posterior axis. 2008 Wiley-Liss, Inc.

What We Know About the Brain Structure-Function Relationship.

PubMed

Batista-García-Ramó, Karla; Fernández-Verdecia, Caridad Ivette

2018-04-18

How the human brain works is still a question, as is its implication with brain architecture: the non-trivial structure–function relationship. The main hypothesis is that the anatomic architecture conditions, but does not determine, the neural network dynamic. The functional connectivity cannot be explained only considering the anatomical substrate. This involves complex and controversial aspects of the neuroscience field and that the methods and methodologies to obtain structural and functional connectivity are not always rigorously applied. The goal of the present article is to discuss about the progress made to elucidate the structure–function relationship of the Central Nervous System, particularly at the brain level, based on results from human and animal studies. The current novel systems and neuroimaging techniques with high resolutive physio-structural capacity have brought about the development of an integral framework of different structural and morphometric tools such as image processing, computational modeling and graph theory. Different laboratories have contributed with in vivo, in vitro and computational/mathematical models to study the intrinsic neural activity patterns based on anatomical connections. We conclude that multi-modal techniques of neuroimaging are required such as an improvement on methodologies for obtaining structural and functional connectivity. Even though simulations of the intrinsic neural activity based on anatomical connectivity can reproduce much of the observed patterns of empirical functional connectivity, future models should be multifactorial to elucidate multi-scale relationships and to infer disorder mechanisms.

[The Biology of Learning].

PubMed

Campo-Cabal, Gerardo

2012-01-01

The effort to relate mental and biological functioning has fluctuated between two doctrines: 1) an attempt to explain mental functioning as a collective property of the brain and 2) as one relatied to other mental processes associated with specific regions of the brain. The article reviews the main theories developed over the last 200 years: phrenology, the psuedo study of the brain, mass action, cellular connectionism and distributed processing among others. In addition, approaches have emerged in recent years that allows for an understanding of the biological determinants and individual differences in complex mental processes through what is called cognitive neuroscience. Knowing the definition of neuroscience, the learning of memory, the ways in which learning occurs, the principles of the neural basis of memory and learning and its effects on brain function, among other things, allows us the basic understanding of the processes of memory and learning and is an important requirement to address the best manner to commit to the of training future specialists in Psychiatry. Copyright © 2012 Asociación Colombiana de Psiquiatría. Publicado por Elsevier España. All rights reserved.

Contributions of Philip Teitelbaum to affective neuroscience.

PubMed

Berridge, Kent C

2012-06-01

As part of a festschrift issue for Philip Teitelbaum, I offer here the thesis that Teitelbaum deserves to be viewed as an important forefather to the contemporary field of affective neuroscience (which studies motivation, emotion and affect in the brain). Teitelbaum's groundbreaking analyses of motivation deficits induced by lateral hypothalamic damage, of roles of food palatability in revealing residual function, and of recovery of 'lost' functions helped shape modern understanding of how motivation circuits operate within the brain. His redefinition of the minimum requirement for identifying motivation raised the conceptual bar for thinking about the topic among behavioral neuroscientists. His meticulous analyses of patterned stages induced by brain manipulations, life development and clinical disorders added new dimensions to our appreciation of how brain systems work. His steadfast highlighting of integrative functions and behavioral complexity helped provide a healthy functionalist counterbalance to reductionist trends in science of the late 20th century. In short, Philip Teitelbaum can be seen to have made remarkable contributions to several domains of psychology and neuroscience, including affective neuroscience. Copyright © 2011 Elsevier B.V. All rights reserved.

Contributions of Philip Teitelbaum to affective neuroscience

PubMed Central

Berridge, Kent C.

2011-01-01

As part of a festschrift issue for Philip Teitelbaum, I offer here the thesis that Teitelbaum deserves to be viewed as an important forefather to the contemporary field of affective neuroscience (which studies motivation, emotion and affect in the brain). Teitelbaum’s groundbreaking analyses of motivation deficits induced by lateral hypothalamic damage, of roles of food palatability in revealing residual function, and of recovery of ‘lost’ functions helped shape modern understanding of how motivation circuits operate within the brain. His redefinition of the minimum requirement for identifying motivation raised the conceptual bar for thinking about the topic among behavioral neuroscientists. His meticulous analyses of patterned stages induced by brain manipulations, life development and clinical disorders added new dimensions to our appreciation of how brain systems work. His steadfast highlighting of integrative functions and behavioral complexity helped provide a healthy functionalist counterbalance to reductionist trends in science of the late 20th century. In short, Philip Teitelbaum can be seen to have made remarkable contributions to several domains of psychology and neuroscience, including affective neuroscience. PMID:22051942

The Autism Brain Imaging Data Exchange: Towards Large-Scale Evaluation of the Intrinsic Brain Architecture in Autism

PubMed Central

Di Martino, Adriana; Yan, Chao-Gan; Li, Qingyang; Denio, Erin; Castellanos, Francisco X.; Alaerts, Kaat; Anderson, Jeffrey S.; Assaf, Michal; Bookheimer, Susan Y.; Dapretto, Mirella; Deen, Ben; Delmonte, Sonja; Dinstein, Ilan; Ertl-Wagner, Birgit; Fair, Damien A.; Gallagher, Louise; Kennedy, Daniel P.; Keown, Christopher L.; Keysers, Christian; Lainhart, Janet E.; Lord, Catherine; Luna, Beatriz; Menon, Vinod; Minshew, Nancy; Monk, Christopher S.; Mueller, Sophia; Müller, Ralph-Axel; Nebel, Mary Beth; Nigg, Joel T.; O’Hearn, Kirsten; Pelphrey, Kevin A.; Peltier, Scott J.; Rudie, Jeffrey D.; Sunaert, Stefan; Thioux, Marc; Tyszka, J. Michael; Uddin, Lucina Q.; Verhoeven, Judith S.; Wenderoth, Nicole; Wiggins, Jillian L.; Mostofsky, Stewart H.; Milham, Michael P.

2014-01-01

Autism spectrum disorders (ASD) represent a formidable challenge for psychiatry and neuroscience because of their high prevalence, life-long nature, complexity and substantial heterogeneity. Facing these obstacles requires large-scale multidisciplinary efforts. While the field of genetics has pioneered data sharing for these reasons, neuroimaging had not kept pace. In response, we introduce the Autism Brain Imaging Data Exchange (ABIDE) – a grassroots consortium aggregating and openly sharing 1112 existing resting-state functional magnetic resonance imaging (R-fMRI) datasets with corresponding structural MRI and phenotypic information from 539 individuals with ASD and 573 age-matched typical controls (TC; 7–64 years) (http://fcon_1000.projects.nitrc.org/indi/abide/). Here, we present this resource and demonstrate its suitability for advancing knowledge of ASD neurobiology based on analyses of 360 males with ASD and 403 male age-matched TC. We focused on whole-brain intrinsic functional connectivity and also survey a range of voxel-wise measures of intrinsic functional brain architecture. Whole-brain analyses reconciled seemingly disparate themes of both hypo and hyperconnectivity in the ASD literature; both were detected, though hypoconnectivity dominated, particularly for cortico-cortical and interhemispheric functional connectivity. Exploratory analyses using an array of regional metrics of intrinsic brain function converged on common loci of dysfunction in ASD (mid and posterior insula, posterior cingulate cortex), and highlighted less commonly explored regions such as thalamus. The survey of the ABIDE R-fMRI datasets provides unprecedented demonstrations of both replication and novel discovery. By pooling multiple international datasets, ABIDE is expected to accelerate the pace of discovery setting the stage for the next generation of ASD studies. PMID:23774715

The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism.

PubMed

Di Martino, A; Yan, C-G; Li, Q; Denio, E; Castellanos, F X; Alaerts, K; Anderson, J S; Assaf, M; Bookheimer, S Y; Dapretto, M; Deen, B; Delmonte, S; Dinstein, I; Ertl-Wagner, B; Fair, D A; Gallagher, L; Kennedy, D P; Keown, C L; Keysers, C; Lainhart, J E; Lord, C; Luna, B; Menon, V; Minshew, N J; Monk, C S; Mueller, S; Müller, R-A; Nebel, M B; Nigg, J T; O'Hearn, K; Pelphrey, K A; Peltier, S J; Rudie, J D; Sunaert, S; Thioux, M; Tyszka, J M; Uddin, L Q; Verhoeven, J S; Wenderoth, N; Wiggins, J L; Mostofsky, S H; Milham, M P

2014-06-01

Autism spectrum disorders (ASDs) represent a formidable challenge for psychiatry and neuroscience because of their high prevalence, lifelong nature, complexity and substantial heterogeneity. Facing these obstacles requires large-scale multidisciplinary efforts. Although the field of genetics has pioneered data sharing for these reasons, neuroimaging had not kept pace. In response, we introduce the Autism Brain Imaging Data Exchange (ABIDE)-a grassroots consortium aggregating and openly sharing 1112 existing resting-state functional magnetic resonance imaging (R-fMRI) data sets with corresponding structural MRI and phenotypic information from 539 individuals with ASDs and 573 age-matched typical controls (TCs; 7-64 years) (http://fcon_1000.projects.nitrc.org/indi/abide/). Here, we present this resource and demonstrate its suitability for advancing knowledge of ASD neurobiology based on analyses of 360 male subjects with ASDs and 403 male age-matched TCs. We focused on whole-brain intrinsic functional connectivity and also survey a range of voxel-wise measures of intrinsic functional brain architecture. Whole-brain analyses reconciled seemingly disparate themes of both hypo- and hyperconnectivity in the ASD literature; both were detected, although hypoconnectivity dominated, particularly for corticocortical and interhemispheric functional connectivity. Exploratory analyses using an array of regional metrics of intrinsic brain function converged on common loci of dysfunction in ASDs (mid- and posterior insula and posterior cingulate cortex), and highlighted less commonly explored regions such as the thalamus. The survey of the ABIDE R-fMRI data sets provides unprecedented demonstrations of both replication and novel discovery. By pooling multiple international data sets, ABIDE is expected to accelerate the pace of discovery setting the stage for the next generation of ASD studies.

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.

Electrophysiological Measures of Resting State Functional Connectivity and Their Relationship with Working Memory Capacity in Childhood

ERIC Educational Resources Information Center

Barnes, Jessica J.; Woolrich, Mark W.; Baker, Kate; Colclough, Giles L.; Astle, Duncan E.

2016-01-01

Functional connectivity is the statistical association of neuronal activity time courses across distinct brain regions, supporting specific cognitive processes. This coordination of activity is likely to be highly important for complex aspects of cognition, such as the communication of fluctuating task goals from higher-order control regions to…

Shedding Light on Words and Sentences: Near-Infrared Spectroscopy in Language Research

ERIC Educational Resources Information Center

Rossi, Sonja; Telkemeyer, Silke; Wartenburger, Isabell; Obrig, Hellmuth

2012-01-01

Investigating the neuronal network underlying language processing may contribute to a better understanding of how the brain masters this complex cognitive function with surprising ease and how language is acquired at a fast pace in infancy. Modern neuroimaging methods permit to visualize the evolvement and the function of the language network. The…

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.

A Novel c-Jun N-terminal Kinase (JNK) Signaling Complex Involved in Neuronal Migration during Brain Development.

PubMed

Zhang, Feng; Yu, Jingwen; Yang, Tao; Xu, Dan; Chi, Zhixia; Xia, Yanheng; Xu, Zhiheng

2016-05-27

Disturbance of neuronal migration may cause various neurological disorders. Both the transforming growth factor-β (TGF-β) signaling and microcephaly-associated protein WDR62 are important for neuronal migration during brain development; however, the underlying molecular mechanisms involved remain unclear. We show here that knock-out or knockdown of Tak1 (TGFβ-activated kinase 1) and Jnk2 (c-Jun N-terminal kinase 2) perturbs neuronal migration during cortical development and that the migration defects incurred by knock-out and/or knockdown of Tβr2 (type II TGF-β receptor) or Tak1 can be partially rescued by expression of TAK1 and JNK2, respectively. Furthermore, TAK1 forms a protein complex with RAC1 and two scaffold proteins of the JNK pathway, the microcephaly-associated protein WDR62 and the RAC1-interacting protein POSH (plenty of Src homology). Components of the complex coordinate with each other in the regulation of TAK1 as well as JNK activities. We suggest that unique JNK protein complexes are involved in the diversified biological and pathological functions during brain development and pathogenesis of diseases. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Common brain regions underlying different arithmetic operations as revealed by conjunct fMRI-BOLD activation.

PubMed

Fehr, Thorsten; Code, Chris; Herrmann, Manfred

2007-10-03

The issue of how and where arithmetic operations are represented in the brain has been addressed in numerous studies. Lesion studies suggest that a network of different brain areas are involved in mental calculation. Neuroimaging studies have reported inferior parietal and lateral frontal activations during mental arithmetic using tasks of different complexities and using different operators (addition, subtraction, etc.). Indeed, it has been difficult to compare brain activation across studies because of the variety of different operators and different presentation modalities used. The present experiment examined fMRI-BOLD activity in participants during calculation tasks entailing different arithmetic operations -- addition, subtraction, multiplication and division -- of different complexities. Functional imaging data revealed a common activation pattern comprising right precuneus, left and right middle and superior frontal regions during all arithmetic operations. All other regional activations were operation specific and distributed in prominently frontal, parietal and central regions when contrasting complex and simple calculation tasks. The present results largely confirm former studies suggesting that activation patterns due to mental arithmetic appear to reflect a basic anatomical substrate of working memory, numerical knowledge and processing based on finger counting, and derived from a network originally related to finger movement. We emphasize that in mental arithmetic research different arithmetic operations should always be examined and discussed independently of each other in order to avoid invalid generalizations on arithmetics and involved brain areas.

Fitting Curves by Fractal Interpolation: AN Application to the Quantification of Cognitive Brain Processes

NASA Astrophysics Data System (ADS)

Navascues, M. A.; Sebastian, M. V.

Fractal interpolants of Barnsley are defined for any continuous function defined on a real compact interval. The uniform distance between the function and its approximant is bounded in terms of the vertical scale factors. As a general result, the density of the affine fractal interpolation functions of Barnsley in the space of continuous functions in a compact interval is proved. A method of data fitting by means of fractal interpolation functions is proposed. The procedure is applied to the quantification of cognitive brain processes. In particular, the increase in the complexity of the electroencephalographic signal produced by the execution of a test of visual attention is studied. The experiment was performed on two types of children: a healthy control group and a set of children diagnosed with an attention deficit disorder.

Functions and Mechanisms of Sleep

PubMed Central

Zielinski, Mark R.; McKenna, James T.; McCarley, Robert W.

2017-01-01

Sleep is a complex physiological process that is regulated globally, regionally, and locally by both cellular and molecular mechanisms. It occurs to some extent in all animals, although sleep expression in lower animals may be co-extensive with rest. Sleep regulation plays an intrinsic part in many behavioral and physiological functions. Currently, all researchers agree there is no single physiological role sleep serves. Nevertheless, it is quite evident that sleep is essential for many vital functions including development, energy conservation, brain waste clearance, modulation of immune responses, cognition, performance, vigilance, disease, and psychological state. This review details the physiological processes involved in sleep regulation and the possible functions that sleep may serve. This description of the brain circuitry, cell types, and molecules involved in sleep regulation is intended to further the reader’s understanding of the functions of sleep. PMID:28413828

Emotions and hemispheric specialization.

PubMed

Kyle, N L

1988-09-01

Studies of lateralization and specialization of brain function have increased our understanding of emotional processes in the brain. It has been said that the way in which we understand the emotional interrelatedness of brain layers and segments may have important effects on human society. Earlier studies of brain function, especially of limbic effects, suggested a dichotomous state of affairs between the phylogenetically older brain and the newer cortical areas--between affect and cognition. Such concepts are considered here in the light of specialization studies. From the beginning hemispheric laterality research has implicated emotionality and emotional pathology. It also appears that some limbic functions may be mediated in a lateralized fashion. Neuropsychologists have directed much work toward localization of function from its earliest stage; since the 1960s an emphasis has been on "mapping" of cortical functions in terms of psychopathologic disabilities. Various disability groups have been studied in this way, and it may be concluded that neuropsychologic measures are sensitive to changes in cerebral functioning and may have effective lateralizing and localizing ability under specified conditions. Studies of limbic effects in the brain emphasize their importance in emotional behavior but also their interrelatedness with other structures, for example, the frontal and temporal lobes, and particularly the right hemisphere. Studies of commissurotomy (split-brain) patients tend to bear out these relationships. In split-brain subjects the marked reduction in affective verbal and nonverbal behavior reflects the interruption of transcallosal impulses that normally permit emotional infusion of cortical structures to take place. These effects include verbal, visual, and auditory patterns that mediate the ability to decode complex nonverbal patterns and may result in a reduction of "inner speech," that is, symbollexia. They may further lead to a condition of "functional commissurotomy" in psychiatric patients with presumably intact brains. It would also appear that lateralization may be variable in terms of inhibitory and facilitative effects; emotional factors may play a part in this variability in some clinical cases in which functional or reactive features predominate, for example, in alexithymia. Ideas of hemispheric specialization have been extended to other areas of individual and social behavior. Creative ability has been understood by some authors to be a product of the relatively dynamic relationships existing between specialized areas of the brain.(ABSTRACT TRUNCATED AT 400 WORDS)

Functional brain segmentation using inter-subject correlation in fMRI.

PubMed

Kauppi, Jukka-Pekka; Pajula, Juha; Niemi, Jari; Hari, Riitta; Tohka, Jussi

2017-05-01

The human brain continuously processes massive amounts of rich sensory information. To better understand such highly complex brain processes, modern neuroimaging studies are increasingly utilizing experimental setups that better mimic daily-life situations. A new exploratory data-analysis approach, functional segmentation inter-subject correlation analysis (FuSeISC), was proposed to facilitate the analysis of functional magnetic resonance (fMRI) data sets collected in these experiments. The method provides a new type of functional segmentation of brain areas, not only characterizing areas that display similar processing across subjects but also areas in which processing across subjects is highly variable. FuSeISC was tested using fMRI data sets collected during traditional block-design stimuli (37 subjects) as well as naturalistic auditory narratives (19 subjects). The method identified spatially local and/or bilaterally symmetric clusters in several cortical areas, many of which are known to be processing the types of stimuli used in the experiments. The method is not only useful for spatial exploration of large fMRI data sets obtained using naturalistic stimuli, but also has other potential applications, such as generation of a functional brain atlases including both lower- and higher-order processing areas. Finally, as a part of FuSeISC, a criterion-based sparsification of the shared nearest-neighbor graph was proposed for detecting clusters in noisy data. In the tests with synthetic data, this technique was superior to well-known clustering methods, such as Ward's method, affinity propagation, and K-means ++. Hum Brain Mapp 38:2643-2665, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Large-scale functional brain network changes in taxi drivers: evidence from resting-state fMRI.

PubMed

Wang, Lubin; Liu, Qiang; Shen, Hui; Li, Hong; Hu, Dewen

2015-03-01

Driving a car in the environment is a complex behavior that involves cognitive processing of visual information to generate the proper motor outputs and action controls. Previous neuroimaging studies have used virtual simulation to identify the brain areas that are associated with various driving-related tasks. Few studies, however, have focused on the specific patterns of functional organization in the driver's brain. The aim of this study was to assess differences in the resting-state networks (RSNs) of the brains of drivers and nondrivers. Forty healthy subjects (20 licensed taxi drivers, 20 nondrivers) underwent an 8-min resting-state functional MRI acquisition. Using independent component analysis, three sensory (primary and extrastriate visual, sensorimotor) RSNs and four cognitive (anterior and posterior default mode, left and right frontoparietal) RSNs were retrieved from the data. We then examined the group differences in the intrinsic brain activity of each RSN and in the functional network connectivity (FNC) between the RSNs. We found that the drivers had reduced intrinsic brain activity in the visual RSNs and reduced FNC between the sensory RSNs compared with the nondrivers. The major finding of this study, however, was that the FNC between the cognitive and sensory RSNs became more positively or less negatively correlated in the drivers relative to that in the nondrivers. Notably, the strength of the FNC between the left frontoparietal and primary visual RSNs was positively correlated with the number of taxi-driving years. Our findings may provide new insight into how the brain supports driving behavior. © 2014 Wiley Periodicals, Inc.

Network analysis of functional brain connectivity in borderline personality disorder using resting-state fMRI

PubMed Central

Xu, Tingting; Cullen, Kathryn R.; Mueller, Bryon; Schreiner, Mindy W.; Lim, Kelvin O.; Schulz, S. Charles; Parhi, Keshab K.

2016-01-01

Borderline personality disorder (BPD) is associated with symptoms such as affect dysregulation, impaired sense of self, and self-harm behaviors. Neuroimaging research on BPD has revealed structural and functional abnormalities in specific brain regions and connections. However, little is known about the topological organizations of brain networks in BPD. We collected resting-state functional magnetic resonance imaging (fMRI) data from 20 patients with BPD and 10 healthy controls, and constructed frequency-specific functional brain networks by correlating wavelet-filtered fMRI signals from 82 cortical and subcortical regions. We employed graph-theory based complex network analysis to investigate the topological properties of the brain networks, and employed network-based statistic to identify functional dysconnections in patients. In the 0.03–0.06 Hz frequency band, compared to controls, patients with BPD showed significantly larger measures of global network topology, including the size of largest connected graph component, clustering coefficient, small-worldness, and local efficiency, indicating increased local cliquishness of the functional brain network. Compared to controls, patients showed lower nodal centrality at several hub nodes but greater centrality at several non-hub nodes in the network. Furthermore, an interconnected subnetwork in 0.03–0.06 Hz frequency band was identified that showed significantly lower connectivity in patients. The links in the subnetwork were mainly long-distance connections between regions located at different lobes; and the mean connectivity of this subnetwork was negatively correlated with the increased global topology measures. Lastly, the key network measures showed high correlations with several clinical symptom scores, and classified BPD patients against healthy controls with high accuracy based on linear discriminant analysis. The abnormal topological properties and connectivity found in this study may add new knowledge to the current understanding of functional brain networks in BPD. However, due to limitation of small sample sizes, the results of the current study should be viewed as exploratory and need to be validated on large samples in future works. PMID:26977400

Network analysis of functional brain connectivity in borderline personality disorder using resting-state fMRI.

PubMed

Xu, Tingting; Cullen, Kathryn R; Mueller, Bryon; Schreiner, Mindy W; Lim, Kelvin O; Schulz, S Charles; Parhi, Keshab K

2016-01-01

Borderline personality disorder (BPD) is associated with symptoms such as affect dysregulation, impaired sense of self, and self-harm behaviors. Neuroimaging research on BPD has revealed structural and functional abnormalities in specific brain regions and connections. However, little is known about the topological organizations of brain networks in BPD. We collected resting-state functional magnetic resonance imaging (fMRI) data from 20 patients with BPD and 10 healthy controls, and constructed frequency-specific functional brain networks by correlating wavelet-filtered fMRI signals from 82 cortical and subcortical regions. We employed graph-theory based complex network analysis to investigate the topological properties of the brain networks, and employed network-based statistic to identify functional dysconnections in patients. In the 0.03-0.06 Hz frequency band, compared to controls, patients with BPD showed significantly larger measures of global network topology, including the size of largest connected graph component, clustering coefficient, small-worldness, and local efficiency, indicating increased local cliquishness of the functional brain network. Compared to controls, patients showed lower nodal centrality at several hub nodes but greater centrality at several non-hub nodes in the network. Furthermore, an interconnected subnetwork in 0.03-0.06 Hz frequency band was identified that showed significantly lower connectivity in patients. The links in the subnetwork were mainly long-distance connections between regions located at different lobes; and the mean connectivity of this subnetwork was negatively correlated with the increased global topology measures. Lastly, the key network measures showed high correlations with several clinical symptom scores, and classified BPD patients against healthy controls with high accuracy based on linear discriminant analysis. The abnormal topological properties and connectivity found in this study may add new knowledge to the current understanding of functional brain networks in BPD. However, due to limitation of small sample sizes, the results of the current study should be viewed as exploratory and need to be validated on large samples in future works.

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

PubMed Central

Tognoli, Emmanuelle; Kelso, J.A. Scott

2009-01-01

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

Précis of The brain and emotion.

PubMed

Rolls, E T

2000-04-01

The topics treated in The brain and emotion include the definition, nature, and functions of emotion (Ch. 3); the neural bases of emotion (Ch. 4); reward, punishment, and emotion in brain design (Ch. 10); a theory of consciousness and its application to understanding emotion and pleasure (Ch. 9); and neural networks and emotion-related learning (Appendix). The approach is that emotions can be considered as states elicited by reinforcers (rewards and punishers). This approach helps with understanding the functions of emotion, with classifying different emotions, and in understanding what information-processing systems in the brain are involved in emotion, and how they are involved. The hypothesis is developed that brains are designed around reward- and punishment-evaluation systems, because this is the way that genes can build a complex system that will produce appropriate but flexible behavior to increase fitness (Ch. 10). By specifying goals rather than particular behavioral patterns of responses, genes leave much more open the possible behavioral strategies that might be required to increase fitness. The importance of reward and punishment systems in brain design also provides a basis for understanding the brain mechanisms of motivation, as described in Chapters 2 for appetite and feeding, 5 for brain-stimulation reward, 6 for addiction, 7 for thirst, and 8 for sexual behavior.

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

PubMed

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

2018-06-11

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

Roles of mTOR Signaling in Brain Development.

PubMed

Lee, Da Yong

2015-09-01

mTOR is a serine/threonine kinase composed of multiple protein components. Intracellular signaling of mTOR complexes is involved in many of physiological functions including cell survival, proliferation and differentiation through the regulation of protein synthesis in multiple cell types. During brain development, mTOR-mediated signaling pathway plays a crucial role in the process of neuronal and glial differentiation and the maintenance of the stemness of neural stem cells. The abnormalities in the activity of mTOR and its downstream signaling molecules in neural stem cells result in severe defects of brain developmental processes causing a significant number of brain disorders, such as pediatric brain tumors, autism, seizure, learning disability and mental retardation. Understanding the implication of mTOR activity in neural stem cells would be able to provide an important clue in the development of future brain developmental disorder therapies.

Source-based neurofeedback methods using EEG recordings: training altered brain activity in a functional brain source derived from blind source separation

PubMed Central

White, David J.; Congedo, Marco; Ciorciari, Joseph

2014-01-01

A developing literature explores the use of neurofeedback in the treatment of a range of clinical conditions, particularly ADHD and epilepsy, whilst neurofeedback also provides an experimental tool for studying the functional significance of endogenous brain activity. A critical component of any neurofeedback method is the underlying physiological signal which forms the basis for the feedback. While the past decade has seen the emergence of fMRI-based protocols training spatially confined BOLD activity, traditional neurofeedback has utilized a small number of electrode sites on the scalp. As scalp EEG at a given electrode site reflects a linear mixture of activity from multiple brain sources and artifacts, efforts to successfully acquire some level of control over the signal may be confounded by these extraneous sources. Further, in the event of successful training, these traditional neurofeedback methods are likely influencing multiple brain regions and processes. The present work describes the use of source-based signal processing methods in EEG neurofeedback. The feasibility and potential utility of such methods were explored in an experiment training increased theta oscillatory activity in a source derived from Blind Source Separation (BSS) of EEG data obtained during completion of a complex cognitive task (spatial navigation). Learned increases in theta activity were observed in two of the four participants to complete 20 sessions of neurofeedback targeting this individually defined functional brain source. Source-based EEG neurofeedback methods using BSS may offer important advantages over traditional neurofeedback, by targeting the desired physiological signal in a more functionally and spatially specific manner. Having provided preliminary evidence of the feasibility of these methods, future work may study a range of clinically and experimentally relevant brain processes where individual brain sources may be targeted by source-based EEG neurofeedback. PMID:25374520

Glycolysis-mediated control of blood-brain barrier development and function.

PubMed

Salmina, Alla B; Kuvacheva, Natalia V; Morgun, Andrey V; Komleva, Yulia K; Pozhilenkova, Elena A; Lopatina, Olga L; Gorina, Yana V; Taranushenko, Tatyana E; Petrova, Lyudmila L

2015-07-01

The blood-brain barrier (BBB) consists of differentiated cells integrating in one ensemble to control transport processes between the central nervous system (CNS) and peripheral blood. Molecular organization of BBB affects the extracellular content and cell metabolism in the CNS. Developmental aspects of BBB attract much attention in recent years, and barriergenesis is currently recognized as a very important and complex mechanism of CNS development and maturation. Metabolic control of angiogenesis/barriergenesis may be provided by glucose utilization within the neurovascular unit (NVU). The role of glycolysis in the brain has been reconsidered recently, and it is recognized now not only as a process active in hypoxic conditions, but also as a mechanism affecting signal transduction, synaptic activity, and brain development. There is growing evidence that glycolysis-derived metabolites, particularly, lactate, affect barriergenesis and functioning of BBB. In the brain, lactate produced in astrocytes or endothelial cells can be transported to the extracellular space via monocarboxylate transporters (MCTs), and may act on the adjoining cells via specific lactate receptors. Astrocytes are one of the major sources of lactate production in the brain and significantly contribute to the regulation of BBB development and functioning. Active glycolysis in astrocytes is required for effective support of neuronal activity and angiogenesis, while endothelial cells regulate bioavailability of lactate for brain cells adjusting its bidirectional transport through the BBB. In this article, we review the current knowledge with regard to energy production in endothelial and astroglial cells within the NVU. In addition, we describe lactate-driven mechanisms and action of alternative products of glucose metabolism affecting BBB structural and functional integrity in developing and mature brain. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

PubMed

Tirapu-Ustarroz, J; Goni-Saez, F

2016-08-16

Consciousness is the result of a series of neurobiological processes in the brain and is, in turn, a feature of the level of its complexity. In fact, being conscious and being aware place us before what Chalmers called the 'soft problem' and the 'hard problem' of consciousness. The first refers to aspects such as wakefulness, attention or knowledge, while the second is concerned with such complex concepts as self-awareness, 'neural self' or social cognition. In this sense it can be said that the concept of consciousness as a unitary thing poses problems of approaching a highly complex reality. We outline the main models that have addressed the topic of consciousness from a neuroscientific perspective. On the one hand, there are the conscious experience models of Crick, Edelman and Tononi, and Llinas, and, on the other, the models and neuronal bases of self-consciousness by authors such as Damasio (core and extended consciousness), Tulving (autonoetic and noetic consciousness and chronesthesia), the problem of qualia (Dennett, Popper, Ramachandran) and the cognit model (Fuster). All the stimuli we receive from the outside world and from our own internal world are converted and processed by the brain so as to integrate them, and from there they become part of our identity. The perception of a dog and being able to recognise it as such or the understanding of our own consciousness are the result of the functioning of brain, neuronal and synaptic structures. The more complex processes of consciousness, such as self-awareness or empathy, are probably emergent brain processes.

Frequency-specific alterations in functional connectivity in treatment-resistant and -sensitive major depressive disorder.

PubMed

He, Zongling; Cui, Qian; Zheng, Junjie; Duan, Xujun; Pang, Yajing; Gao, Qing; Han, Shaoqiang; Long, Zhiliang; Wang, Yifeng; Li, Jiao; Wang, Xiao; Zhao, Jingping; Chen, Huafu

2016-11-01

Major depressive disorder (MDD) may involve alterations in brain functional connectivity in multiple neural circuits and present large-scale network dysfunction. Patients with treatment-resistant depression (TRD) and treatment-sensitive depression (TSD) show different responses to antidepressants and aberrant brain functions. This study aims to investigate functional connectivity patterns of TRD and TSD at the whole brain resting state. Seventeen patients with TRD, 17 patients with TSD, and 17 healthy controls matched with age, gender, and years of education were recruited in this study. The brain was divided using an automated anatomical labeling atlas into 90 regions of interest, which were used to construct the entire brain functional networks. An analysis method called network-based statistic was used to explore the dysconnected subnetworks of TRD and TSD at different frequency bands. At resting state, TSD and TRD present characteristic patterns of network dysfunction at special frequency bands. The dysconnected subnetwork of TSD mainly lies in the fronto-parietal top-down control network. Moreover, the abnormal neural circuits of TRD are extensive and complex. These circuits not only depend on the abnormal affective network but also involve other networks, including salience network, auditory network, visual network, and language processing cortex. Our findings reflect that the pathological mechanism of TSD may refer to impairment in cognitive control, whereas TRD mainly triggers the dysfunction of emotion processing and affective cognition. This study reveals that differences in brain functional connectivity at resting state reflect distinct pathophysiological mechanisms in TSD and TRD. These findings may be helpful in differentiating two types of MDD and predicting treatment responses. Copyright © 2016 Elsevier Ltd. All rights reserved.

Oxytocin: parallel processing in the social brain?

PubMed

Dölen, Gül

2015-06-01

Early studies attempting to disentangle the network complexity of the brain exploited the accessibility of sensory receptive fields to reveal circuits made up of synapses connected both in series and in parallel. More recently, extension of this organisational principle beyond the sensory systems has been made possible by the advent of modern molecular, viral and optogenetic approaches. Here, evidence supporting parallel processing of social behaviours mediated by oxytocin is reviewed. Understanding oxytocinergic signalling from this perspective has significant implications for the design of oxytocin-based therapeutic interventions aimed at disorders such as autism, where disrupted social function is a core clinical feature. Moreover, identification of opportunities for novel technology development will require a better appreciation of the complexity of the circuit-level organisation of the social brain. © 2015 The Authors. Journal of Neuroendocrinology published by John Wiley & Sons Ltd on behalf of British Society for Neuroendocrinology.

Neuroendocrine considerations in the treatment of men and women with epilepsy

PubMed Central

Harden, Cynthia L; Pennell, Page B

2016-01-01

Complex, multidirectional interactions between hormones, seizures, and the medications used to control them can present a challenge for clinicians treating patients with epilepsy. Many hormones act as neurosteroids, modulating brain excitability via direct binding sites. Thus, changes in endogenous or exogenous hormone levels can affect the occurrence of seizures directly as well as indirectly through pharmacokinetic effects that alter the concentrations of antiepileptic drugs. The underlying structural and physiological brain abnormalities of epilepsy and the metabolic activity of antiepileptic drugs can adversely affect hypothalamic and gonadal functioning. Knowledge of these complex interactions has increased and can now be incorporated in meaningful treatment approaches for men and women with epilepsy. PMID:23237902

Brain-wide Maps Reveal Stereotyped Cell-Type-Based Cortical Architecture and Subcortical Sexual Dimorphism.

PubMed

Kim, Yongsoo; Yang, Guangyu Robert; Pradhan, Kith; Venkataraju, Kannan Umadevi; Bota, Mihail; García Del Molino, Luis Carlos; Fitzgerald, Greg; Ram, Keerthi; He, Miao; Levine, Jesse Maurica; Mitra, Partha; Huang, Z Josh; Wang, Xiao-Jing; Osten, Pavel

2017-10-05

The stereotyped features of neuronal circuits are those most likely to explain the remarkable capacity of the brain to process information and govern behaviors, yet it has not been possible to comprehensively quantify neuronal distributions across animals or genders due to the size and complexity of the mammalian brain. Here we apply our quantitative brain-wide (qBrain) mapping platform to document the stereotyped distributions of mainly inhibitory cell types. We discover an unexpected cortical organizing principle: sensory-motor areas are dominated by output-modulating parvalbumin-positive interneurons, whereas association, including frontal, areas are dominated by input-modulating somatostatin-positive interneurons. Furthermore, we identify local cell type distributions with more cells in the female brain in 10 out of 11 sexually dimorphic subcortical areas, in contrast to the overall larger brains in males. The qBrain resource can be further mined to link stereotyped aspects of neuronal distributions to known and unknown functions of diverse brain regions. Copyright © 2017 Elsevier Inc. All rights reserved.

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/).

Computer modeling of Epilepsy

PubMed Central

Lytton, William W.

2009-01-01

Preface Epilepsy is a complex set of disorders that can involve many areas of cortex as well as underlying deep brain systems. The myriad manifestations of seizures, as varied as déjà vu and olfactory hallucination, can thereby give researchers insights into regional functions and relations. Epilepsy is also complex genetically and pathophysiologically, involving microscopic (ion channels, synaptic proteins), macroscopic (brain trauma and rewiring) and intermediate changes in a complex interplay of causality. It has long been recognized that computer modeling will be required to disentangle causality, to better understand seizure spread and to understand and eventually predict treatment efficacy. Over the past few years, substantial progress has been made modeling epilepsy at levels ranging from the molecular to the socioeconomic. We review these efforts and connect them to the medical goals of understanding and treating this disorder. PMID:18594562

A neurovascular perspective for long-term changes after brain trauma.

PubMed

Pop, V; Badaut, J

2011-12-01

Traumatic brain injury (TBI) affects all age groups in a population and is an injury generating scientific interest not only as an acute event, but also as a complex brain disease with several underlying neurobehavioral and neuropathological characteristics. We review early and long-term alterations after juvenile and adult TBI with a focus on changes in the neurovascular unit (NVU), including neuronal interactions with glia and blood vessels at the blood-brain barrier (BBB). Post-traumatic changes in cerebral blood-flow, BBB structures and function, as well as mechanistic pathways associated with brain aging and neurodegeneration are presented from clinical and experimental reports. Based on the literature, increased attention on BBB changes should be integrated in studies characterizing TBI outcome and may provide a meaningful therapeutic target to resolve detrimental post-traumatic dysfunction.

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.

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

Hemispheric asymmetry in new neurons in adulthood is associated with vocal learning and auditory memory.

PubMed

Tsoi, Shuk C; Aiya, Utsav V; Wasner, Kobi D; Phan, Mimi L; Pytte, Carolyn L; Vicario, David S

2014-01-01

Many brain regions exhibit lateral differences in structure and function, and also incorporate new neurons in adulthood, thought to function in learning and in the formation of new memories. However, the contribution of new neurons to hemispheric differences in processing is unknown. The present study combines cellular, behavioral, and physiological methods to address whether 1) new neuron incorporation differs between the brain hemispheres, and 2) the degree to which hemispheric lateralization of new neurons correlates with behavioral and physiological measures of learning and memory. The songbird provides a model system for assessing the contribution of new neurons to hemispheric specialization because songbird brain areas for vocal processing are functionally lateralized and receive a continuous influx of new neurons in adulthood. In adult male zebra finches, we quantified new neurons in the caudomedial nidopallium (NCM), a forebrain area involved in discrimination and memory for the complex vocalizations of individual conspecifics. We assessed song learning and recorded neural responses to song in NCM. We found significantly more new neurons labeled in left than in right NCM; moreover, the degree of asymmetry in new neuron numbers was correlated with the quality of song learning and strength of neuronal memory for recently heard songs. In birds with experimentally impaired song quality, the hemispheric difference in new neurons was diminished. These results suggest that new neurons may contribute to an allocation of function between the hemispheres that underlies the learning and processing of complex signals.

Hemispheric Asymmetry in New Neurons in Adulthood Is Associated with Vocal Learning and Auditory Memory

PubMed Central

Wasner, Kobi D.; Phan, Mimi L.; Pytte, Carolyn L.; Vicario, David S.

2014-01-01

Many brain regions exhibit lateral differences in structure and function, and also incorporate new neurons in adulthood, thought to function in learning and in the formation of new memories. However, the contribution of new neurons to hemispheric differences in processing is unknown. The present study combines cellular, behavioral, and physiological methods to address whether 1) new neuron incorporation differs between the brain hemispheres, and 2) the degree to which hemispheric lateralization of new neurons correlates with behavioral and physiological measures of learning and memory. The songbird provides a model system for assessing the contribution of new neurons to hemispheric specialization because songbird brain areas for vocal processing are functionally lateralized and receive a continuous influx of new neurons in adulthood. In adult male zebra finches, we quantified new neurons in the caudomedial nidopallium (NCM), a forebrain area involved in discrimination and memory for the complex vocalizations of individual conspecifics. We assessed song learning and recorded neural responses to song in NCM. We found significantly more new neurons labeled in left than in right NCM; moreover, the degree of asymmetry in new neuron numbers was correlated with the quality of song learning and strength of neuronal memory for recently heard songs. In birds with experimentally impaired song quality, the hemispheric difference in new neurons was diminished. These results suggest that new neurons may contribute to an allocation of function between the hemispheres that underlies the learning and processing of complex signals. PMID:25251077

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.

Mixed Effects Models for Resampled Network Statistics Improves Statistical Power to Find Differences in Multi-Subject Functional Connectivity

PubMed Central

Narayan, Manjari; Allen, Genevera I.

2016-01-01

Many complex brain disorders, such as autism spectrum disorders, exhibit a wide range of symptoms and disability. To understand how brain communication is impaired in such conditions, functional connectivity studies seek to understand individual differences in brain network structure in terms of covariates that measure symptom severity. In practice, however, functional connectivity is not observed but estimated from complex and noisy neural activity measurements. Imperfect subject network estimates can compromise subsequent efforts to detect covariate effects on network structure. We address this problem in the case of Gaussian graphical models of functional connectivity, by proposing novel two-level models that treat both subject level networks and population level covariate effects as unknown parameters. To account for imperfectly estimated subject level networks when fitting these models, we propose two related approaches—R2 based on resampling and random effects test statistics, and R3 that additionally employs random adaptive penalization. Simulation studies using realistic graph structures reveal that R2 and R3 have superior statistical power to detect covariate effects compared to existing approaches, particularly when the number of within subject observations is comparable to the size of subject networks. Using our novel models and methods to study parts of the ABIDE dataset, we find evidence of hypoconnectivity associated with symptom severity in autism spectrum disorders, in frontoparietal and limbic systems as well as in anterior and posterior cingulate cortices. PMID:27147940

MicroRNAs in neuronal function and dysfunction

PubMed Central

Im, Heh-In; Kenny, Paul J.

2012-01-01

MicroRNAs (miRNAs) are small noncoding RNA transcripts expressed throughout the brain that can regulate neuronal gene expression at the post-transcriptional level. Here, we provide an overview of the role for miRNAs in brain development and function, and review evidence suggesting that dysfunction in miRNA signaling contributes to neurodevelopment disorders such as Rett and fragile X syndromes, as well as complex behavioral disorders including schizophrenia, depression and drug addiction. A better understanding of how miRNAs influence the development of neuropsychiatric disorders may reveal fundamental insights into the causes of these devastating illnesses and offer novel targets for therapeutic development. PMID:22436491

Altered attentional control over the salience network in complex regional pain syndrome.

PubMed

Kim, Jungyoon; Kang, Ilhyang; Chung, Yong-An; Kim, Tae-Suk; Namgung, Eun; Lee, Suji; Oh, Jin Kyoung; Jeong, Hyeonseok S; Cho, Hanbyul; Kim, Myeong Ju; Kim, Tammy D; Choi, Soo Hyun; Lim, Soo Mee; Lyoo, In Kyoon; Yoon, Sujung

2018-05-10

The degree and salience of pain have been known to be constantly monitored and modulated by the brain. In the case of maladaptive neural responses as reported in centralized pain conditions such as complex regional pain syndrome (CRPS), the perception of pain is amplified and remains elevated even without sustained peripheral pain inputs. Given that the attentional state of the brain greatly influences the perception and interpretation of pain, we investigated the role of the attention network and its dynamic interactions with other pain-related networks of the brain in CRPS. We examined alterations in the intra- and inter-network functional connectivities in 21 individuals with CRPS and 49 controls. CRPS-related reduction in intra-network functional connectivity was found in the attention network. Individuals with CRPS had greater inter-network connectivities between the attention and salience networks as compared with healthy controls. Furthermore, individuals within the CRPS group with high levels of pain catastrophizing showed greater inter-network connectivities between the attention and salience networks. Taken together, the current findings suggest that these altered connectivities may be potentially associated with the maladaptive pain coping as found in CRPS patients.

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.

Individual Differences in Dynamic Functional Brain Connectivity across the Human Lifespan.

PubMed

Davison, Elizabeth N; Turner, Benjamin O; Schlesinger, Kimberly J; Miller, Michael B; Grafton, Scott T; Bassett, Danielle S; Carlson, Jean M

2016-11-01

Individual differences in brain functional networks may be related to complex personal identifiers, including health, age, and ability. Dynamic network theory has been used to identify properties of dynamic brain function from fMRI data, but the majority of analyses and findings remain at the level of the group. Here, we apply hypergraph analysis, a method from dynamic network theory, to quantify individual differences in brain functional dynamics. Using a summary metric derived from the hypergraph formalism-hypergraph cardinality-we investigate individual variations in two separate, complementary data sets. The first data set ("multi-task") consists of 77 individuals engaging in four consecutive cognitive tasks. We observe that hypergraph cardinality exhibits variation across individuals while remaining consistent within individuals between tasks; moreover, the analysis of one of the memory tasks revealed a marginally significant correspondence between hypergraph cardinality and age. This finding motivated a similar analysis of the second data set ("age-memory"), in which 95 individuals, aged 18-75, performed a memory task with a similar structure to the multi-task memory task. With the increased age range in the age-memory data set, the correlation between hypergraph cardinality and age correspondence becomes significant. We discuss these results in the context of the well-known finding linking age with network structure, and suggest that hypergraph analysis should serve as a useful tool in furthering our understanding of the dynamic network structure of the brain.

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

Structural and functional brain changes in early- and mid-stage primary open-angle glaucoma using voxel-based morphometry and functional magnetic resonance imaging.

PubMed

Jiang, Ming-Ming; Zhou, Qing; Liu, Xiao-Yong; Shi, Chang-Zheng; Chen, Jian; Huang, Xiang-He

2017-03-01

To investigate structural and functional brain changes in patients with primary open-angle glaucoma (POAG) by using voxel-based morphometry based on diffeomorphic anatomical registration through exponentiated Lie algebra (VBM-DARTEL) and blood oxygenation level dependent functional magnetic resonance imaging (BOLD-fMRI), respectively.Thirteen patients diagnosed with POAG and 13 age- and sex-matched healthy controls were enrolled in the study. For each participant, high-resolution structural brain imaging and blood flow imaging were acquired on a 3.0-Tesla magnetic resonance imaging (MRI) scanner. Structural and functional changes between the POAG and control groups were analyzed. An analysis was carried out to identify correlations between structural and functional changes acquired in the previous analysis and the retinal nerve fiber layer (RNFL).Patients in the POAG group showed a significant (P < 0.001) volume increase in the midbrain, left brainstem, frontal gyrus, cerebellar vermis, left inferior parietal lobule, caudate nucleus, thalamus, precuneus, and Brodmann areas 7, 18, and 46. Moreover, significant (P < 0.001) BOLD signal changes were observed in the right supramarginal gyrus, frontal gyrus, superior frontal gyrus, left inferior parietal lobule, left cuneus, and left midcingulate area; many of these regions had high correlations with the RNFL.Patients with POAG undergo widespread and complex changes in cortical brain structure and blood flow. (ClinicalTrials.gov number: NCT02570867).

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

PubMed

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

2014-04-01

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

Structural Connectivity Relates to Perinatal Factors and Functional Impairment at 7 Years in Children Born Very Preterm

PubMed Central

Thompson, Deanne K.; Chen, Jian; Beare, Richard; Adamson, Christopher L.; Ellis, Rachel; Ahmadzai, Zohra M.; Kelly, Claire E.; Lee, Katherine J.; Zalesky, Andrew; Yang, Joseph Y.M.; Hunt, Rodney W.; Cheong, Jeanie L.Y.; Inder, Terrie E.; Doyle, Lex W.; Seal, Marc L.; Anderson, Peter J.

2016-01-01

Objective To use structural connectivity to (1) compare brain networks between typically and atypically developing (very preterm) children, (2) explore associations between potential perinatal developmental disturbances and brain networks, and (3) describe associations between brain networks and functional impairments in very preterm children. Methods 26 full-term and 107 very preterm 7-year-old children (born <30 weeks’ gestational age and/or <1250 g) underwent T1- and diffusion-weighted imaging. Global white matter fiber networks were produced using 80 cortical and subcortical nodes, and edges created using constrained spherical deconvolution-based tractography. Global graph theory metrics were analysed, and regional networks were identified using network-based statistics. Cognitive and motor function were assessed at 7 years of age. Results Compared with full-term children, very preterm children had reduced density, lower global efficiency and higher local efficiency. Those with lower gestational age at birth, infection or higher neonatal brain abnormality score had reduced connectivity. Reduced connectivity within a widespread network was predictive of impaired IQ, while reduced connectivity within the right parietal and temporal lobes was associated with motor impairment in very preterm children. Conclusions This study utilized an innovative structural connectivity pipeline to reveal that children born very preterm have less connected and less complex brain networks compared with typically developing term-born children. Adverse perinatal factors led to disturbances in white matter connectivity, which in turn are associated with impaired functional outcomes, highlighting novel structure-function relationships. PMID:27046108

Docosahexaenoic acid augments hypothermic neuroprotection in a neonatal rat asphyxia model.

PubMed

Berman, Deborah R; Mozurkewich, Ellen; Liu, Yiqing; Shangguan, Yu; Barks, John D; Silverstein, Faye S

2013-01-01

In neonatal rats, early post-hypoxia-ischemia (HI) administration of the omega-3 fatty acid docosahexaenoic acid (DHA) improves sensorimotor function, but does not attenuate brain damage. To determine if DHA administration in addition to hypothermia, now standard care for neonatal asphyxial brain injury, attenuates post-HI damage and sensorimotor deficits. Seven-day-old (P7) rats underwent right carotid ligation followed by 90 min of 8% O2 exposure. Fifteen minutes later, pups received injections of DHA 2.5 mg/kg (complexed to 25% albumin) or equal volumes of albumin. After a 1-hour recovery, pups were cooled (3 h, 30°C). Sensorimotor and pathology outcomes were initially evaluated on P14. In subsequent experiments, sensorimotor function was evaluated on P14, P21, and P28; histopathology was assessed on P28. At P14, left forepaw function scores (normal: 20/20) were near normal in DHA + hypothermia-treated animals (mean ± SD 19.7 ± 0.7 DHA + hypothermia vs. 12.7 ± 3.5 albumin + hypothermia, p < 0.0001) and brain damage was reduced (mean ± SD right hemisphere damage 38 ± 17% with DHA + hypothermia vs. 56 ± 15% with albumin + hypothermia, p = 0.003). Substantial improvements on three sensorimotor function measures and reduced brain damage were evident up to P28. Unlike post-HI treatment with DHA alone, treatment with DHA + hypothermia produced both sustained functional improvement and reduced brain damage after neonatal HI. Copyright © 2013 S. Karger AG, Basel.

Connectomics and neuroticism: an altered functional network organization.

PubMed

Servaas, Michelle N; Geerligs, Linda; Renken, Remco J; Marsman, Jan-Bernard C; Ormel, Johan; Riese, Harriëtte; Aleman, André

2015-01-01

The personality trait neuroticism is a potent risk marker for psychopathology. Although the neurobiological basis remains unclear, studies have suggested that alterations in connectivity may underlie it. Therefore, the aim of the current study was to shed more light on the functional network organization in neuroticism. To this end, we applied graph theory on resting-state functional magnetic resonance imaging (fMRI) data in 120 women selected based on their neuroticism score. Binary and weighted brain-wide graphs were constructed to examine changes in the functional network structure and functional connectivity strength. Furthermore, graphs were partitioned into modules to specifically investigate connectivity within and between functional subnetworks related to emotion processing and cognitive control. Subsequently, complex network measures (ie, efficiency and modularity) were calculated on the brain-wide graphs and modules, and correlated with neuroticism scores. Compared with low neurotic individuals, high neurotic individuals exhibited a whole-brain network structure resembling more that of a random network and had overall weaker functional connections. Furthermore, in these high neurotic individuals, functional subnetworks could be delineated less clearly and the majority of these subnetworks showed lower efficiency, while the affective subnetwork showed higher efficiency. In addition, the cingulo-operculum subnetwork demonstrated more ties with other functional subnetworks in association with neuroticism. In conclusion, the 'neurotic brain' has a less than optimal functional network organization and shows signs of functional disconnectivity. Moreover, in high compared with low neurotic individuals, emotion and salience subnetworks have a more prominent role in the information exchange, while sensory(-motor) and cognitive control subnetworks have a less prominent role.

The effects of alcohol on the nonhuman primate brain: a network science approach to neuroimaging.

PubMed

Telesford, Qawi K; Laurienti, Paul J; Friedman, David P; Kraft, Robert A; Daunais, James B

2013-11-01

Animal studies have long been an important tool for basic research as they offer a degree of control often lacking in clinical studies. Of particular value is the use of nonhuman primates (NHPs) for neuroimaging studies. Currently, studies have been published using functional magnetic resonance imaging (fMRI) to understand the default-mode network in the NHP brain. Network science provides an alternative approach to neuroimaging allowing for evaluation of whole-brain connectivity. In this study, we used network science to build NHP brain networks from fMRI data to understand the basic functional organization of the NHP brain. We also explored how the brain network is affected following an acute ethanol (EtOH) pharmacological challenge. Baseline resting-state fMRI was acquired in an adult male rhesus macaque (n = 1) and a cohort of vervet monkeys (n = 10). A follow-up scan was conducted in the rhesus macaque to assess network variability and to assess the effects of an acute EtOH challenge on the brain network. The most connected regions in the resting-state networks were similar across species and matched regions identified as the default-mode network in previous NHP fMRI studies. Under an acute EtOH challenge, the functional organization of the brain was significantly impacted. Network science offers a great opportunity to understand the brain as a complex system and how pharmacological conditions can affect the system globally. These models are sensitive to changes in the brain and may prove to be a valuable tool in long-term studies on alcohol exposure. Copyright © 2013 by the Research Society on Alcoholism.