Search results: Found 7

Listing 1 - 7 of 7
Sort by
Wiring Principles of Cerebral Cortex

Authors: ---
Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889196920 Year: Pages: 171 DOI: 10.3389/978-2-88919-692-0 Language: English
Publisher: Frontiers Media SA
Subject: Science (General) --- Neurology
Added to DOAB on : 2016-08-16 10:34:25
License:

Loading...
Export citation

Choose an application

Abstract

Cerebral cortex is probably the most complex biological network. Here many millions of individual neurons, the functional units of cortex, are interconnected through a massive yet highly organized pattern of axonal and dendritic wiring. This wiring enables both near and distant cells to coordinate their responses and generate a rich variety of cognitions and behaviours. When the wiring is damaged through disease or trauma it may reorganize but this may lead to characteristic pathological behaviours. While there have been significant advances in mapping cortical connectivity, the organizing principles and function of this connectivity are not well understood. On the one hand, there appears to be general design constraints governing cortical wiring, as first recognised by Rámon y Cajal's in his laws of conduction, material, and volume conservation. Yet on the other hand, particular patterns of cortical wiring exist to serve specific functions. There is a wide gap in understanding how the response and connectivity properties of a single neuron contribute to emergent network functions such as in detecting perceptually relevant features. Unravelling this intimate causal relationship represents one of the major challenges in neuroscience. This Research Topic will examine progress in understanding cortical wiring principles. This Research Topic aims to draw together recent advances in methods and understanding as well as recent challenges to existing ideas about how cerebral cortex is wired. This is particularly timely because new automated techniques may soon yield huge datasets in need of explanation. Recent studies have, for instance, empirically evaluated Rámon y Cajal's conservation laws for cerebral cortex, while others have shown some unexpected connectivity features that may refine the traditional view of how corticocortical connections are organised with regard to functional representations of auditory, somatosensory and visual cortices. Understanding these data will help improve the fidelity of neural models of cerebral cortical function and take into account the diversity of connections at both micro- and mesoscopic scales not seen at such a depth before.

Mapping Psychopathology with fMRI and Effective Connectivity Analysis

Authors: --- ---
Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889452071 Year: Pages: 140 DOI: 10.3389/978-2-88945-207-1 Language: English
Publisher: Frontiers Media SA
Subject: Neurology --- Science (General)
Added to DOAB on : 2017-10-13 14:57:01
License:

Loading...
Export citation

Choose an application

Abstract

There is a growing appreciation that many psychiatric (and neurological) conditions can be understood as functional disconnection syndromes – as reflected in aberrant functional integration and synaptic connectivity. This Research Topic considers recent advances in understanding psychopathology in terms of aberrant effective connectivity – as measured noninvasively using functional magnetic resonance imaging (fMRI).Recently, there has been increasing interest in inferring directed connectivity (effective connectivity) from fMRI data. Effective connectivity refers to the influence that one neural system exerts over another and quantifies the directed coupling among brain regions – and how they change with pathophysiology. Compared to functional connectivity, effective connectivity allows one to understand how brain regions interact with each other in terms of context sensitive changes and directed coupling – and therefore may provide mechanistic insights into the neural basis of psychopathology.Established models of effective connectivity include psychophysiological interaction (PPI), structural equation modeling (SEM) and dynamic causal modelling (DCM). DCM is unique because it explicitly models the interaction among brain regions in terms of latent neuronal activity. Moreover, recent advances in DCM such as stochastic and spectral DCM, make it possible to characterize the interaction between different brain regions both at rest and during a cognitive task.

Information-based methods for neuroimaging: analyzing structure, function and dynamics

Authors: --- ---
Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889195022 Year: Pages: 191 DOI: 10.3389/978-2-88919-502-2 Language: English
Publisher: Frontiers Media SA
Subject: Neurology --- Science (General)
Added to DOAB on : 2015-12-03 13:02:24
License:

Loading...
Export citation

Choose an application

Abstract

The aim of this Research Topic is to discuss the state of the art on the use of Information-based methods in the analysis of neuroimaging data. Information-based methods, typically built as extensions of the Shannon Entropy, are at the basis of model-free approaches which, being based on probability distributions rather than on specific expectations, can account for all possible non-linearities present in the data in a model-independent fashion.Mutual Information-like methods can also be applied on interacting dynamical variables described by time-series, thus addressing the uncertainty reduction (or information) in one variable by conditioning on another set of variables.In the last years, different Information-based methods have been shown to be flexible and powerful tools to analyze neuroimaging data, with a wide range of different methodologies, including formulations-based on bivariate vs multivariate representations, frequency vs time domains, etc. Apart from methodological issues, the information bit as a common unit represents a convenient way to open the road for comparison and integration between different measurements of neuroimaging data in three complementary contexts: Structural Connectivity, Dynamical (Functional and Effective) Connectivity, and Modelling of brain activity. Applications are ubiquitous, starting from resting state in healthy subjects to modulations of consciousness and other aspects of pathophysiology.Mutual Information-based methods have provided new insights about common-principles in brain organization, showing the existence of an active default network when the brain is at rest. It is not clear, however, how this default network is generated, the different modules are intra-interacting, or disappearing in the presence of stimulation. Some of these open-questions at the functional level might find their mechanisms on their structural correlates. A key question is the link between structure and function and the use of structural priors for the understanding of the functional connectivity measures. As effective connectivity is concerned, recently a common framework has been proposed for Transfer Entropy and Granger Causality, a well-established methodology originally based on autoregressive models. This framework can open the way to new theories and applications.This Research Topic brings together contributions from researchers from different backgrounds which are either developing new approaches, or applying existing methodologies to new data, and we hope it will set the basis for discussing the development and validation of new Information-based methodologies for the understanding of brain structure, function, and dynamics.

Producing and Analyzing Macro-Connectomes: Current State and Challenges

Authors: --- ---
Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889199815 Year: Pages: 139 DOI: 10.3389/978-2-88919-981-5 Language: English
Publisher: Frontiers Media SA
Subject: Science (General) --- Neurology
Added to DOAB on : 2016-01-19 14:05:46
License:

Loading...
Export citation

Choose an application

Abstract

Construction of comprehensive and detailed brain regions neuroanatomical connections matrices (macro-connectomes) is necessary to understand how the nervous system is organized and to elucidate how its different parts interact. Macro-connectomes also are the structural foundation of any finer granularity approaches at the neuron classes and types (meso-connectomes) or individual neuron (micro-connectomes) levels. The advent of novel neuroanatomical methods, as well as combinations of classic techniques, form the basis of several large scale projects with the ultimate goal of producing publicly available connectomes at different levels. A parallel approach, that of systematic and comprehensive collation of connectivity data from the published literature and from publicly accessible neuroinformatics platforms, has produced macro-connectomes of different parts of the central nervous system (CNS) in several mammalian species. The emergence of these public platforms that allow for the manipulation of rich connectivity data sets and enable the construction of CNS macro-connectomes in different species may have significant and long lasting implications. Moreover, when these efforts are leveraged by novel statistical methods, they may influence our way of thinking about the brain. Hence, the present brain region-centric paradigm may be challenged by a network-centric one. Ultimately, these projects will provide the information and knowledge for understanding how different neuronal parts communicate and function, developing novel approaches to diseases and disorders, and facilitating translational efforts in neurosciences. With this Research Topic we bring together the current state of macro-connectome related projects including the large scale production of thousands of publicly available neuronatomical experiments, databases with tens of thousands of connectivity records collated from the published literature, and the newest methods for displaying and analyzing this information. This topic also includes a wide range of challenges and how they are addressed - from platforms designed to integrate connectivity data across different sources, species and CNS levels of organization, to languages specifically designed to use these data in models at different scales of resolution, to efforts of 3D reconstruction and data integration, and to approaches for extraction and representation of this knowledge. Finally, we address the present state of different efforts of meso-connectomes construction, and of computational modeling in the context of the

Neuropsychopharmacology of Psychosis: Relation of Brain Signals, Cognition and Chemistry

Authors: ---
Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889193356 Year: Pages: 276 DOI: 10.3389/978-2-88919-335-6 Language: English
Publisher: Frontiers Media SA
Subject: Psychiatry --- Medicine (General)
Added to DOAB on : 2016-03-10 08:14:32
License:

Loading...
Export citation

Choose an application

Abstract

Previous research over the past decades has identified diverse neurobiological underpinnings of psychosis. In particular, by combining a variety of different neuroimaging modalities, it has been shown that psychotic states and the actual transition phase from a clinical high-risk state to established psychosis is characterized by structural, functional and neurochemical changes across different brain regions.Further evidence revealed that maybe not only focal brain abnormalities are characteristic for psychosis but specifically also an abnormal functional integration among various brain areas. Some evidence also suggests that dysfunctional brain connectivity proceeds during the development of psychosis when subjects perform a cognitive task. Notably, altered brain connectivity during cognitive challenges was often found to be associated with psychopathological measures, suggesting a mechanistic relation between functional network integrity and the clinical expression of psychosis.Several works proposed that disordered brain connectivity in psychosis results from abnormal N-methyl- D -aspartate receptor (NMDAR)-dependent synaptic plasticity, which can be mediated by other neurotransmitter systems such as dopamine or serotonin. Specific chemically mediated changes in synaptic plasticity may contribute to abnormal functional integration among brain regions and in consequence to impaired learning performances and inferences. Model-based connectivity investigations on synaptic signalling demonstrated for example that manipulation of the NMDA or α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor system altered synaptic plasticity in healthy volunteers, which was predictive for subjects’ cognitive performance and psychopathology. In patients with psychosis, the activity in the prefrontal cortex during the processing of prediction errors, a specific form of learning, which is conveyed via synaptic connections, was linked with individuals’ formation of delusions. These results fit well with many works suggesting that psychotic symptoms or also drug-induced psychosis-like experiences can be explained by disturbances within a hierarchically organized neuronal network, leading to maladaptive integrations of new incoming evidence and thereby to false formations of prediction errors and false beliefs.In this research topic, we like to cover the most recent neurobiological correlates for early stage psychosis and in particular for the prediction of psychosis by using different neurophysiological measures (e.g. structural and functional MRI, EEG, DTI or PET). Studies exploring effective connectivity or complex brain networks such as small-world properties with techniques like dynamic causal modelling, structural equation modelling, or graph theory analysis are highly appreciated. Very welcome are studies proving a link between clinical features such as psychopathology and cognition, brain signals, and chemistry (also in regard of antipsychotic treatments or substance-induced psychotic states). Moreover, environmental factors that may influence psychosis onset or its’ developmental processes will be brought together with a diversity of different research modalities. We also collect critical reviews, mini-reviews or theoretical reflections from leading international researcher and clinicians in this field. The purpose of our research topic is intended to provide a state-of-the-art cognitive perspective to consider developing psychosis, which might shed more lights into the pathophysiological and neurobiological mechanisms of psychosis.

Brain Connectivity in Autism

Authors: --- --- --- --- et al.
Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889192823 Year: Pages: 264 DOI: 10.3389/978-2-88919-282-3 Language: English
Publisher: Frontiers Media SA
Subject: Science (General) --- Neurology
Added to DOAB on : 2015-12-10 11:59:06
License:

Loading...
Export citation

Choose an application

Abstract

The brain's ability to process information crucially relies on connectivity. Understanding how the brain processes complex information and how such abilities are disrupted in individuals with neuropsychological disorders will require an improved understanding of brain connectivity. Autism is an intriguingly complex neurodevelopmental disorder with multidimensional symptoms and cognitive characteristics. A biological origin for autism spectrum disorders (ASD) had been proposed even in the earliest published accounts (Kanner, 1943; Asperger, 1944). Despite decades of research, a focal neurobiological marker for autism has been elusive. Nevertheless, disruptions in interregional and functional and anatomical connectivity have been a hallmark of neural functioning in ASD. Theoretical accounts of connectivity perceive ASD as a cognitive and neurobiological disorder associated with altered functioning of integrative circuitry. Neuroimaging studies have reported disruptions in functional connectivity (synchronization of activated brain areas) during cognitive tasks and during task-free resting states. While these insights are valuable, they do not address the time-lagged causality and directionality of such correlations. Despite the general promise of the connectivity account of ASD, inconsistencies and methodological differences among studies call for more thorough investigations. A comprehensive neurological account of ASD should incorporate functional, effective, and anatomical connectivity measures and test the diagnostic utility of such measures. In addition, questions pertaining to how cognitive and behavioral intervention can target connection abnormalities in ASD should be addressed. This research topic of the Frontiers in Human Neuroscience addresses “Brain Connectivity in Autism” primarily from cognitive neuroscience and neuroimaging perspectives.

Proceedings of the International School on Magnetic Resonance and Brain Function - XII Workshop

Authors: ---
Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889455546 Year: Pages: 150 DOI: 10.3389/978-2-88945-554-6 Language: English
Publisher: Frontiers Media SA
Subject: Science (General) --- Neurology --- Physics (General)
Added to DOAB on : 2019-01-23 14:53:42
License:

Loading...
Export citation

Choose an application

Abstract

In the last thirty years, Magnetic Resonance has generated a wide revolution in biomedical research and in medical imaging in general. More recently, the "in vivo" studies of the human brain were extended by new original ways to the dynamic study of function and metabolism of the human brain. The enormous interest in expanding the investigation of the brain is emphasizing the search for new NMR methods capable of extracting information of so-far obscure aspects of the brain function. In fact, many quantitative approaches have been proposed in order to complement the information obtained by functional MRI, and several multimodal and multiparametric approaches have been developed to exploit the information, either functional or structural, made available by the flexible contrast generation typical of MRI, and to combine it with complementary information. The XII workshop of the International School on Magnetic Resonanceand Brain Function, held in Erice between 17 April and 6 May, 2016, was specially devoted to novel approaches aimed at better structural characterization of brain diseases, and at investigating frontiers MRI approaches to better understand the brain function. The papers included in this eBook offer a broad overview of the subjects covered during the Workshop, including applications of multiparametric MRI to neurological diseases, multimodal combination of MRI with electrophysiology, advanced methods for the investigation of brain networks and of brain physiology, and perspectives towards brain state reading.

Listing 1 - 7 of 7
Sort by
Narrow your search

Publisher

Frontiers Media SA (7)


License

CC by (7)


Language

english (7)


Year
From To Submit

2018 (1)

2017 (1)

2016 (1)

2015 (3)

2014 (1)