Dynamics of Biologically Informed Neural Mass Models of the Brain
Author: Andreas Spiegler
Publisher:
Published: 2012
Total Pages:
ISBN-13:
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Neural Masses and Fields: Modelling the Dynamics of Brain Activity
Author: Karl Friston
Publisher: Frontiers Media SA
Published: 2015-05-25
Total Pages: 238
ISBN-13: 2889194272
DOWNLOAD EBOOKBiophysical 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.
Brain Dynamics
Author: Hermann Haken
Publisher: Springer Science & Business Media
Published: 2007-12-22
Total Pages: 331
ISBN-13: 3540752382
DOWNLOAD EBOOKThis is an excellent introduction for graduate students and nonspecialists to the field of mathematical and computational neurosciences. The book approaches the subject via pulsed-coupled neural networks, which have at their core the lighthouse and integrate-and-fire models. These allow for highly flexible modeling of realistic synaptic activity, synchronization and spatio-temporal pattern formation. The more advanced pulse-averaged equations are discussed.
Neural and Brain Modeling
Author: Ronald MacGregor
Publisher: Elsevier
Published: 2012-12-02
Total Pages: 656
ISBN-13: 0323143849
DOWNLOAD EBOOKNeural and Brain Modeling reviews models used to study neural interactions. The book also discusses 54 computer programs that simulate the dynamics of neurons and neuronal networks to illustrate between unit and systemic levels of nervous system functions. The models of neural and brain operations are composed of three sections: models of generic mechanisms; models of specific neuronal systems; and models of generic operations, networks, and systems. The text discusses the computational problems related to galvanizing a neuronal population though an activity in the multifiber input system. The investigator can use a computer technique to simulate multiple interacting neuronal populations. For example, he can investigate the case of a single local region that contains two populations of neurons: namely, a parent population of excitatory cells, and a second set of inhibitory neurons. Computer simulation models predict the various dynamic activity occurring in the complicated structure and physiology of neuronal systems. Computer models can be used in "top-down" brain/mind research where the systemic, global, and emergent properties of nervous systems are generated. The book is recommended for behavioral scientists, psychiatrists, psychologists, computer programmers, students, and professors in human behavior.
Rethinking Neural Networks
Author: Karl H. Pribram
Publisher: Psychology Press
Published: 2014-04-08
Total Pages: 566
ISBN-13: 1317780949
DOWNLOAD EBOOKThe result of the first Appalachian Conference on neurodynamics, this volume focuses on processing in biological neural networks. How do brain processes become organized during decision making? That is, what are the neural antecedents that determine which course of action is to be pursued? Half of the contributions deal with modelling synapto-dendritic and neural ultrastructural processes; the remainder, with laboratory research findings, often cast in terms of the models. The interchanges at the conference and the ensuing publication also provide a foundation for further meetings. These will address how processes in different brain systems, coactive with the neural residues of experience and with sensory input, determine decisions.
Integrative Neuroscience
Author: Evian Gordon
Publisher: CRC Press
Published: 2000-05-17
Total Pages: 282
ISBN-13: 9789058230546
DOWNLOAD EBOOKMost brain related activity has focussed on specialized interests within individual disciplines. Recent multidisciplinary activity has provided the impetus to break down these boundaries and encourage a freer exchange of information across disciplines. This text reflects these developments. It spans the landscape of brain science to provide core information from 12 disciplines (including evolution, philosophy, anatomy, chemistry, computer science, brain dynamics, psychology, neurology, psychiatry, psychotherapy and brain imaging). In outlining how and why it is now possible to realistically model aspects of the brain's dynamics from such a wide range of intellectual endeavors, this book will prove itself useful to undergraduates, postgraduates and all those seeking a contemporary perspective and evaluation of the current status and future directions in the brain sciences.
Dynamical Systems in Neuroscience
Author: Eugene M. Izhikevich
Publisher: MIT Press
Published: 2007
Total Pages: 522
ISBN-13: 0262090430
DOWNLOAD EBOOKIn order to model neuronal behavior or to interpret the results of modeling studies, neuroscientists must call upon methods of nonlinear dynamics. This book offers an introduction to nonlinear dynamical systems theory for researchers and graduate students in neuroscience. It also provides an overview of neuroscience for mathematicians who want to learn the basic facts of electrophysiology. Dynamical Systems in Neuroscience presents a systematic study of the relationship of electrophysiology, nonlinear dynamics, and computational properties of neurons. It emphasizes that information processing in the brain depends not only on the electrophysiological properties of neurons but also on their dynamical properties. The book introduces dynamical systems, starting with one- and two-dimensional Hodgkin-Huxley-type models and continuing to a description of bursting systems. Each chapter proceeds from the simple to the complex, and provides sample problems at the end. The book explains all necessary mathematical concepts using geometrical intuition; it includes many figures and few equations, making it especially suitable for non-mathematicians. Each concept is presented in terms of both neuroscience and mathematics, providing a link between the two disciplines. Nonlinear dynamical systems theory is at the core of computational neuroscience research, but it is not a standard part of the graduate neuroscience curriculum—or taught by math or physics department in a way that is suitable for students of biology. This book offers neuroscience students and researchers a comprehensive account of concepts and methods increasingly used in computational neuroscience. An additional chapter on synchronization, with more advanced material, can be found at the author's website, www.izhikevich.com.
Modeling in the Neurosciences
Author: G. N. Reeke
Publisher: CRC Press
Published: 2005-03-29
Total Pages: 736
ISBN-13: 0203390970
DOWNLOAD EBOOKComputational models of neural networks have proven insufficient to accurately model brain function, mainly as a result of simplifications that ignore the physical reality of neuronal structure in favor of mathematically tractable algorithms and rules. Even the more biologically based "integrate and fire" and "compartmental" styles of modeling suff
Neurodynamics of Cognition and Consciousness
Author: Leonid I. Perlovsky
Publisher: Springer
Published: 2007-08-26
Total Pages: 369
ISBN-13: 3540732675
DOWNLOAD EBOOKExperimental evidence in humans and other mammalians indicates that complex neurodynamics is crucial for the emergence of higher-level intelligence. Dynamical neural systems with encoding in limit cycle and non-convergent attractors have gained increasing popularity in the past decade. The role of synchronization, desynchronization, and intermittent synchronization on cognition has been studied extensively by various authors, in particular by authors contributing to the present volume. This book addresses dynamical aspects of brain functions and cognition.
Observed Brain Dynamics
Author: Partha Mitra
Publisher: Oxford University Press
Published: 2007-12-07
Total Pages: 404
ISBN-13: 0199884366
DOWNLOAD EBOOKThe biomedical sciences have recently undergone revolutionary change, due to the ability to digitize and store large data sets. In neuroscience, the data sources include measurements of neural activity measured using electrode arrays, EEG and MEG, brain imaging data from PET, fMRI, and optical imaging methods. Analysis, visualization, and management of these time series data sets is a growing field of research that has become increasingly important both for experimentalists and theorists interested in brain function. Written by investigators who have played an important role in developing the subject and in its pedagogical exposition, the current volume addresses the need for a textbook in this interdisciplinary area. The book is written for a broad spectrum of readers ranging from physical scientists, mathematicians, and statisticians wishing to educate themselves about neuroscience, to biologists who would like to learn time series analysis methods in particular and refresh their mathematical and statistical knowledge in general, through self-pedagogy. It may also be used as a supplement for a quantitative course in neurobiology or as a textbook for instruction on neural signal processing. The first part of the book contains a set of essays meant to provide conceptual background which are not technical and shall be generally accessible. Salient features include the adoption of an active perspective of the nervous system, an emphasis on function, and a brief survey of different theoretical accounts in neuroscience. The second part is the longest in the book, and contains a refresher course in mathematics and statistics leading up to time series analysis techniques. The third part contains applications of data analysis techniques to the range of data sources indicated above (also available as part of the Chronux data analysis platform from http://chronux.org), and the fourth part contains special topics.
