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Neural Masses And Fields Modelling The Dynamics Of Brain Activity


Neural Masses And Fields Modelling The Dynamics Of Brain Activity
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Neural Masses And Fields Modelling The Dynamics Of Brain Activity


Neural Masses And Fields Modelling The Dynamics Of Brain Activity
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Author : Karl Friston
language : en
Publisher: Frontiers Media SA
Release Date : 2015-05-25

Neural Masses And Fields Modelling The Dynamics Of Brain Activity written by Karl Friston and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-25 with Differential equations categories.


Biophysical modelling of brain activity has a long and illustrious history and has recently profited from technological advances that furnish neuroimaging data at an unprecedented spatiotemporal resolution. Neuronal modelling is a very active area of research, with applications ranging from the characterization of neurobiological and cognitive processes, to constructing artificial brains in silico and building brain-machine interface and neuroprosthetic devices. Biophysical modelling has always benefited from interdisciplinary interactions between different and seemingly distant fields; ranging from mathematics and engineering to linguistics and psychology. This Research Topic aims to promote such interactions by promoting papers that contribute to a deeper understanding of neural activity as measured by fMRI or electrophysiology. In general, mean field models of neural activity can be divided into two classes: neural mass and neural field models. The main difference between these classes is that field models prescribe how a quantity characterizing neural activity (such as average depolarization of a neural population) evolves over both space and time as opposed to mass models, which characterize activity over time only; by assuming that all neurons in a population are located at (approximately) the same point. This Research Topic focuses on both classes of models and considers several aspects and their relative merits that: span from synapses to the whole brain; comparisons of their predictions with EEG and MEG spectra of spontaneous brain activity; evoked responses, seizures, and fitting data - to infer brain states and map physiological parameters.



Neural Fields


Neural Fields
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Author : Stephen Coombes
language : en
Publisher: Springer
Release Date : 2014-06-17

Neural Fields written by Stephen Coombes and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-17 with Mathematics categories.


Neural field theory has a long-standing tradition in the mathematical and computational neurosciences. Beginning almost 50 years ago with seminal work by Griffiths and culminating in the 1970ties with the models of Wilson and Cowan, Nunez and Amari, this important research area experienced a renaissance during the 1990ties by the groups of Ermentrout, Robinson, Bressloff, Wright and Haken. Since then, much progress has been made in both, the development of mathematical and numerical techniques and in physiological refinement und understanding. In contrast to large-scale neural network models described by huge connectivity matrices that are computationally expensive in numerical simulations, neural field models described by connectivity kernels allow for analytical treatment by means of methods from functional analysis. Thus, a number of rigorous results on the existence of bump and wave solutions or on inverse kernel construction problems are nowadays available. Moreover, neural fields provide an important interface for the coupling of neural activity to experimentally observable data, such as the electroencephalogram (EEG) or functional magnetic resonance imaging (fMRI). And finally, neural fields over rather abstract feature spaces, also called dynamic fields, found successful applications in the cognitive sciences and in robotics. Up to now, research results in neural field theory have been disseminated across a number of distinct journals from mathematics, computational neuroscience, biophysics, cognitive science and others. There is no comprehensive collection of results or reviews available yet. With our proposed book Neural Field Theory, we aim at filling this gap in the market. We received consent from some of the leading scientists in the field, who are willing to write contributions for the book, among them are two of the founding-fathers of neural field theory: Shun-ichi Amari and Jack Cowan.



Nonlinear Dynamics In Computational Neuroscience


Nonlinear Dynamics In Computational Neuroscience
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Author : Fernando Corinto
language : en
Publisher: Springer
Release Date : 2018-06-19

Nonlinear Dynamics In Computational Neuroscience written by Fernando Corinto and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-19 with Technology & Engineering categories.


This book provides an essential overview of computational neuroscience. It addresses a broad range of aspects, from physiology to nonlinear dynamical approaches to understanding neural computation, and from the simulation of brain circuits to the development of engineering devices and platforms for neuromorphic computation. Written by leading experts in such diverse fields as neuroscience, physics, psychology, neural engineering, cognitive science and applied mathematics, the book reflects the remarkable advances that have been made in the field of computational neuroscience, an emerging discipline devoted to the study of brain functions in terms of the information-processing properties of the structures forming the nervous system. The contents build on the workshop “Nonlinear Dynamics in Computational Neuroscience: from Physics and Biology to ICT,” which was held in Torino, Italy in September 2015.



Computational Systems Neurobiology


Computational Systems Neurobiology
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Author : N. Le Novère
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-07-20

Computational Systems Neurobiology written by N. Le Novère and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-07-20 with Medical categories.


Computational neurosciences and systems biology are among the main domains of life science research where mathematical modeling made a difference. This book introduces the many different types of computational studies one can develop to study neuronal systems. It is aimed at undergraduate students starting their research in computational neurobiology or more senior researchers who would like, or need, to move towards computational approaches. Based on their specific project, the readers would then move to one of the more specialized excellent textbooks available in the field. The first part of the book deals with molecular systems biology. Functional genomics is introduced through examples of transcriptomics and proteomics studies of neurobiological interest. Quantitative modelling of biochemical systems is presented in homogeneous compartments and using spatial descriptions. A second part deals with the various approaches to model single neuron physiology, and naturally moves to neuronal networks. A division is focused on the development of neurons and neuronal systems and the book closes on a series of methodological chapters. From the molecules to the organ, thinking at the level of systems is transforming biology and its impact on society. This book will help the reader to hop on the train directly in the tank engine.



Insights In Computational Neuroscience


Insights In Computational Neuroscience
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Author : Si Wu
language : en
Publisher: Frontiers Media SA
Release Date : 2023-04-11

Insights In Computational Neuroscience written by Si Wu and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-11 with Science categories.




Computational Neurology And Psychiatry


Computational Neurology And Psychiatry
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Author : Péter Érdi
language : en
Publisher: Springer
Release Date : 2017-01-25

Computational Neurology And Psychiatry written by Péter Érdi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-25 with Technology & Engineering categories.


This book presents the latest research in computational methods for modeling and simulating brain disorders. In particular, it shows how mathematical models can be used to study the relationship between a given disorder and the specific brain structure associated with that disorder. It also describes the emerging field of computational psychiatry, including the study of pathological behavior due to impaired functional connectivity, pathophysiological activity, and/or aberrant decision-making. Further, it discusses the data analysis techniques that will be required to analyze the increasing amount of data being generated about the brain. Lastly, the book offers some tips on the application of computational models in the field of quantitative systems pharmacology. Mainly written for computational scientists eager to discover new application fields for their model, this book also benefits neurologists and psychiatrists wanting to learn about new methods.



Complex Physical Biophysical And Econophysical Systems Proceedings Of The 22nd Canberra International Physics Summer School


Complex Physical Biophysical And Econophysical Systems Proceedings Of The 22nd Canberra International Physics Summer School
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Author : Robert L Dewar
language : en
Publisher: World Scientific
Release Date : 2010-03-09

Complex Physical Biophysical And Econophysical Systems Proceedings Of The 22nd Canberra International Physics Summer School written by Robert L Dewar and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-03-09 with Science categories.


This book arose from a conference organized under the auspices of the Australian Research Council's Complex Open Systems Research Network (which has become the most prominent for complex systems in the world — just Google “complex systems network”), the ANU Centre for Complex Systems, and the Asia-Pacific Center for Theoretical Physics. The book is unique in the scope of its coverage of applications of complex systems science: Extraterrestrial — astrophysical, solar and space plasmas; Earth System — climate, ecosystems; Human systems — brain dynamics, social networks, financial statistics, advanced technologies.It also presents up-to-date discussions of new theoretical approaches, in particular those based on entropy and entropy production maximization, a field still under development but with much promise for providing a much-needed unifying principle for complex systems science.The authors are at the forefront of their fields, and organized their chapters to effectively bring out common features of complex systems. A comprehensive and common lexicon of keywords has been used to unify indexing, thus making the book an invaluable introduction to anyone seeking an overview of complex systems science.



Sleep And Anesthesia


Sleep And Anesthesia
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Author : Axel Hutt
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-07-12

Sleep And Anesthesia written by Axel Hutt and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-07-12 with Science categories.


Sleep and anesthesia resemble in many ways at a first glance. The most prominent common feature of course is the loss of consciousness, i.e. the loss of awareness of external stimuli. However a closer look at the loss of consciousness reveals already a difference between sleep and anesthesia: anesthesia is induced by an anesthetic drug whereas we may fall asleep without external cause. Other questions may arise about the difference of the two effects: do we dream during surgery under anesthesia, do we feel pain during sleep? Essentially, we may ask: what is common and what are the differences between sleep and anesthesia? To answer these questions, we may take a look at the neural origin of both effects and the involved physiological pathways. In which way do they resemble? Moreover, we ask what are the detailed features of normal sleep and general anesthesia as applied during surgery and which features exist in both phenomena? If yes in which way? To receive answers to these questions, it is necessary to consider several experimental techniques that reveal underlying neural mechanisms of sleep and anesthesia. Moreover, theoretical models of neural activity may model both phenomena and comes up with predictions or even theories on the underlying mechanisms. Such models may attack several different description levels, from the microscopic level of single neurons to the macroscopic level of neural populations. Such models may give deeper insight into the phenomena if their assumptions are based on experimental findings and their predictions can be compared to experimental results. This comparison step is essential for valuable theoretical models. The book is motivated by two successful workshops on anesthesia and sleep organized during the Computational Neuroscience Conferences in Toronto in 2007 and in Berlin 2009. It aims to cover all the previous aspects with a focus on the link to experimental findings. It elucidates important issues in theoretical models that at the same time reflect some current major research interests. Moreover it considers some diverse issues which are very important to get an overview of the fields. For instance, the book discusses not only neural activity in the brain but also the effects of general anesthesia on the cardio-vascular system and the spinal cord in the context of analgesia. In addition, it considers different experimental techniques on various spatial scales, such as fMRI and EEG-experiments on the macroscopic scale and single neuron and LFP-measurements on the microscopic scale. In total all book chapters reveal aspects of the neural correlates of sleep and anesthesia motivated by experimental data. This focus on the neural mechanism in the light of experimental data is the common feature of the topics and the chapters. In addition, the book aims to clarify the shared physiological mechanisms of both phenomena, but also reveal their physiological differences.



Advanced State Space Methods For Neural And Clinical Data


Advanced State Space Methods For Neural And Clinical Data
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Author : Zhe Chen
language : en
Publisher: Cambridge University Press
Release Date : 2015-10-15

Advanced State Space Methods For Neural And Clinical Data written by Zhe Chen and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-15 with Computers categories.


An authoritative and in-depth treatment of state space methods, with a range of applications in neural and clinical data.



Information Based Methods For Neuroimaging Analyzing Structure Function And Dynamics


Information Based Methods For Neuroimaging Analyzing Structure Function And Dynamics
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Author : Jesus M. Cortés
language : en
Publisher: Frontiers Media SA
Release Date : 2015-05-07

Information Based Methods For Neuroimaging Analyzing Structure Function And Dynamics written by Jesus M. Cortés and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-07 with Neurosciences. Biological psychiatry. Neuropsychiatry categories.


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.