Neuronal Stochastic Variability Influences On Spiking Dynamics And Network Activity PDF Download
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Author | : Mark D. McDonnell |
Publisher | : Frontiers Media SA |
Total Pages | : 158 |
Release | : 2016-07-18 |
Genre | : Neurosciences. Biological psychiatry. Neuropsychiatry |
ISBN | : 2889198847 |
Download Neuronal Stochastic Variability: Influences on Spiking Dynamics and Network Activity Book in PDF, ePub and Kindle
Stochastic fluctuations are intrinsic to and unavoidable at every stage of neural dynamics. For example, ion channels undergo random conformational changes, neurotransmitter release at synapses is discrete and probabilistic, and neural networks are embedded in spontaneous background activity. The mathematical and computational tool sets contributing to our understanding of stochastic neural dynamics have expanded rapidly in recent years. New theories have emerged detailing the dynamics and computational power of the balanced state in recurrent networks. At the cellular level, novel stochastic extensions to the classical Hodgkin-Huxley model have enlarged our understanding of neuronal dynamics and action potential initiation. Analytical methods have been developed that allow for the calculation of the firing statistics of simplified phenomenological integrate-and-fire models, taking into account adaptation currents or temporal correlations of the noise. This Research Topic is focused on identified physiological/internal noise sources and mechanisms. By "internal", we mean variability that is generated by intrinsic biophysical processes. This includes noise at a range of scales, from ion channels to synapses to neurons to networks. The contributions in this Research Topic introduce innovative mathematical analysis and/or computational methods that relate to empirical measures of neural activity and illuminate the functional role of intrinsic noise in the brain.
Author | : |
Publisher | : |
Total Pages | : 0 |
Release | : 2016 |
Genre | : |
ISBN | : |
Download Neuronal Stochastic Variability: Influences on Spiking Dynamics and Network Activity Book in PDF, ePub and Kindle
Stochastic fluctuations are intrinsic to and unavoidable at every stage of neural dynamics. For example, ion channels undergo random conformational changes, neurotransmitter release at synapses is discrete and probabilistic, and neural networks are embedded in spontaneous background activity. The mathematical and computational tool sets contributing to our understanding of stochastic neural dynamics have expanded rapidly in recent years. New theories have emerged detailing the dynamics and computational power of the balanced state in recurrent networks. At the cellular level, novel stochastic extensions to the classical Hodgkin-Huxley model have enlarged our understanding of neuronal dynamics and action potential initiation. Analytical methods have been developed that allow for the calculation of the firing statistics of simplified phenomenological integrate-and-fire models, taking into account adaptation currents or temporal correlations of the noise. This Research Topic is focused on identified physiological/internal noise sources and mechanisms. By "internal", we mean variability that is generated by intrinsic biophysical processes. This includes noise at a range of scales, from ion channels to synapses to neurons to networks. The contributions in this Research Topic introduce innovative mathematical analysis and/or computational methods that relate to empirical measures of neural activity and illuminate the functional role of intrinsic noise in the brain.
Author | : Wulfram Gerstner |
Publisher | : Cambridge University Press |
Total Pages | : 591 |
Release | : 2014-07-24 |
Genre | : Computers |
ISBN | : 1107060834 |
Download Neuronal Dynamics Book in PDF, ePub and Kindle
This solid introduction uses the principles of physics and the tools of mathematics to approach fundamental questions of neuroscience.
Author | : Emili Balaguer-Ballester |
Publisher | : Frontiers Media SA |
Total Pages | : 152 |
Release | : 2018-03-19 |
Genre | : |
ISBN | : 2889454371 |
Download Metastable Dynamics of Neural Ensembles Book in PDF, ePub and Kindle
A classical view of neural computation is that it can be characterized in terms of convergence to attractor states or sequential transitions among states in a noisy background. After over three decades, is this still a valid model of how brain dynamics implements cognition? This book provides a comprehensive collection of recent theoretical and experimental contributions addressing the question of stable versus transient neural population dynamics from complementary angles. These studies showcase recent efforts for designing a framework that encompasses the multiple facets of metastability in neural responses, one of the most exciting topics currently in systems and computational neuroscience.
Author | : Tatjana Tchumatchenko |
Publisher | : Frontiers E-books |
Total Pages | : 237 |
Release | : 2014-12-03 |
Genre | : Brain function |
ISBN | : 2889193578 |
Download Correlated neuronal activity and its relationship to coding, dynamics and network architecture Book in PDF, ePub and Kindle
Correlated activity in populations of neurons has been observed in many brain regions and plays a central role in cortical coding, attention, and network dynamics. Accurately quantifying neuronal correlations presents several difficulties. For example, despite recent advances in multicellular recording techniques, the number of neurons from which spiking activity can be simultaneously recorded remains orders magnitude smaller than the size of local networks. In addition, there is a lack of consensus on the distribution of pairwise spike cross correlations obtained in extracellular multi-unit recordings. These challenges highlight the need for theoretical and computational approaches to understand how correlations emerge and to decipher their functional role in the brain.
Author | : Krešimir Josic |
Publisher | : Springer Science & Business Media |
Total Pages | : 311 |
Release | : 2009-08-22 |
Genre | : Medical |
ISBN | : 1441903895 |
Download Coherent Behavior in Neuronal Networks Book in PDF, ePub and Kindle
Recent experimental research advances have led to increasingly detailed descriptions of how networks of interacting neurons process information. With these developments, it has become clear that dynamic network behaviors underlie information processing, and that the observed activity patterns cannot be fully explained by simple concepts such as synchrony and phase locking. These new insights raise significant challenges and offer exciting opportunities for experimental and theoretical neuroscientists. Coherent Behavior in Neuronal Networks features a review of recent research in this area from some of the world’s foremost experts on systems neuroscience. The book presents novel methodologies and interdisciplinary perspectives, and will serve as an invaluable resource to the research community. Highlights include the results of interdisciplinary collaborations and approaches as well as topics, such as the interplay of intrinsic and synaptic dynamics in producing coherent neuronal network activity and the roles of globally coherent rhythms and oscillations in the coordination of distributed processing, that are of significant research interest but have been underrepresented in the review literature. With its cutting-edge mathematical, statistical, and computational techniques, this volume will be of interest to all researchers and students in the field of systems neuroscience.
Author | : Wulfram Gerstner |
Publisher | : Cambridge University Press |
Total Pages | : 591 |
Release | : 2014-07-24 |
Genre | : Computers |
ISBN | : 113999316X |
Download Neuronal Dynamics Book in PDF, ePub and Kindle
What happens in our brain when we make a decision? What triggers a neuron to send out a signal? What is the neural code? This textbook for advanced undergraduate and beginning graduate students provides a thorough and up-to-date introduction to the fields of computational and theoretical neuroscience. It covers classical topics, including the Hodgkin–Huxley equations and Hopfield model, as well as modern developments in the field such as generalized linear models and decision theory. Concepts are introduced using clear step-by-step explanations suitable for readers with only a basic knowledge of differential equations and probabilities, and are richly illustrated by figures and worked-out examples. End-of-chapter summaries and classroom-tested exercises make the book ideal for courses or for self-study. The authors also give pointers to the literature and an extensive bibliography, which will prove invaluable to readers interested in further study.
Author | : Wulfram Gerstner |
Publisher | : Cambridge University Press |
Total Pages | : 498 |
Release | : 2002-08-15 |
Genre | : Computers |
ISBN | : 9780521890793 |
Download Spiking Neuron Models Book in PDF, ePub and Kindle
Neurons in the brain communicate by short electrical pulses, the so-called action potentials or spikes. How can we understand the process of spike generation? How can we understand information transmission by neurons? What happens if thousands of neurons are coupled together in a seemingly random network? How does the network connectivity determine the activity patterns? And, vice versa, how does the spike activity influence the connectivity pattern? These questions are addressed in this 2002 introduction to spiking neurons aimed at those taking courses in computational neuroscience, theoretical biology, biophysics, or neural networks. The approach will suit students of physics, mathematics, or computer science; it will also be useful for biologists who are interested in mathematical modelling. The text is enhanced by many worked examples and illustrations. There are no mathematical prerequisites beyond what the audience would meet as undergraduates: more advanced techniques are introduced in an elementary, concrete fashion when needed.
Author | : Michele Giugliano |
Publisher | : Springer Nature |
Total Pages | : 361 |
Release | : 2022-04-26 |
Genre | : Medical |
ISBN | : 3030894398 |
Download Computational Modelling of the Brain Book in PDF, ePub and Kindle
This volume offers an up-to-date overview of essential concepts and modern approaches to computational modelling, including the use of experimental techniques related to or directly inspired by them. The book introduces, at increasing levels of complexity and with the non-specialist in mind, state-of-the-art topics ranging from single-cell and molecular descriptions to circuits and networks. Four major themes are covered, including subcellular modelling of ion channels and signalling pathways at the molecular level, single-cell modelling at different levels of spatial complexity, network modelling from local microcircuits to large-scale simulations of entire brain areas and practical examples. Each chapter presents a systematic overview of a specific topic and provides the reader with the fundamental tools needed to understand the computational modelling of neural dynamics. This book is aimed at experimenters and graduate students with little or no prior knowledge of modelling who are interested in learning about computational models from the single molecule to the inter-areal communication of brain structures. The book will appeal to computational neuroscientists, engineers, physicists and mathematicians interested in contributing to the field of neuroscience. Chapters 6, 10 and 11 are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Author | : Edmund T. Rolls |
Publisher | : |
Total Pages | : 334 |
Release | : 2010-01-28 |
Genre | : Mathematics |
ISBN | : |
Download The Noisy Brain Book in PDF, ePub and Kindle
The activity of neurons in the brain is noisy in that the neuronal firing times are random for a given mean rate. The Noisy Brain shows that this is fundamental to understanding many aspects of brain function, including probabilistic decision-making, perception, memory recall, short-term memory, attention, and even creativity. There are many applications too of this understanding, to for example memory and attentional disorders, aging, schizophrenia, and obsessive-compulsive disorder.