Download or read book Inhibition Stabilized Network Model in the Primary Visual Cortex written by Jun Zhao and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Both studies led to network solutions in the ISN regime, suggesting that ISN mechanisms might play an important role in the neural circuitry in the primary visual cortex.
Download or read book Inhibitory Synaptic Plasticity written by Melanie A. Woodin and published by Springer Science & Business Media. This book was released on 2010-11-02 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume will explore the most recent findings on cellular mechanisms of inhibitory plasticity and its functional role in shaping neuronal circuits, their rewiring in response to experience, drug addiction and in neuropathology. Inhibitory Synaptic Plasticity will be of particular interest to neuroscientists and neurophysiologists.
Download or read book Development of an Integrated Model of Primary Visual Cortex written by Benjamin Selby and published by . This book was released on 2016 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt: Network-level models of visual processing have potentially important insights for applications such as computer vision and robotics. Primary visual cortex is a key stage of visual processing with involvement in many circuits proposed for these applications including motion tracking, object recognition, and control of eye movements. However, no model of V1 to date has captured the complete set of observed behaviour in a large-scale model. Linear kernel methods with threshold and divisive non-linearities can reproduce classical receptive field behaviour, but not the full range of non-classical behaviours. The stabilized supralinear network (SSN) provides a simple scheme of lateral interactions that produce a wealth of observed V1 behaviour not previously captured with linear kernel methods. However, the SSN is restricted in stimulus selectivity and is not pixel-computable, limiting its utility for real-world applications. Integrating a linear kernel model with the SSN resulted in a model that is pixel-computable and produces a wide range of classical and non-classical behaviour. With further development this network model will be usable in visual processing circuits. The SSN was also expanded to use binocular stimuli. Using an optimization procedure, SSN parameters were found that produce interocular transfer of suppression in excitatory units, but not inhibitory ones. The lack of interocular transfer in inhibitory units may indicate that an alternate inhibition-stabilization scheme is more biophysically realistic. Mammalian visual perception is enabled not only by neural processing but also by precise eye movements, which allow for efficient scanning of the environment. This thesis describes the requirements for a robot that can orient cameras with the same dynamics as macaque monkey eyes as well as a camera system that reproduces macaque visual acuity.
Download or read book A Network Model of the Primary Visual Cortex written by Alan B. Saul and published by . This book was released on 1981 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Inhibitory Mechanisms in the Primary Visual Cortex written by Gary Allan Walker and published by . This book was released on 1998 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Mathematical Foundations of Neuroscience written by G. Bard Ermentrout and published by Springer Science & Business Media. This book was released on 2010-07-01 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book applies methods from nonlinear dynamics to problems in neuroscience. It uses modern mathematical approaches to understand patterns of neuronal activity seen in experiments and models of neuronal behavior. The intended audience is researchers interested in applying mathematics to important problems in neuroscience, and neuroscientists who would like to understand how to create models, as well as the mathematical and computational methods for analyzing them. The authors take a very broad approach and use many different methods to solve and understand complex models of neurons and circuits. They explain and combine numerical, analytical, dynamical systems and perturbation methods to produce a modern approach to the types of model equations that arise in neuroscience. There are extensive chapters on the role of noise, multiple time scales and spatial interactions in generating complex activity patterns found in experiments. The early chapters require little more than basic calculus and some elementary differential equations and can form the core of a computational neuroscience course. Later chapters can be used as a basis for a graduate class and as a source for current research in mathematical neuroscience. The book contains a large number of illustrations, chapter summaries and hundreds of exercises which are motivated by issues that arise in biology, and involve both computation and analysis. Bard Ermentrout is Professor of Computational Biology and Professor of Mathematics at the University of Pittsburgh. David Terman is Professor of Mathematics at the Ohio State University.
Download or read book The New Visual Neurosciences written by John S. Werner and published by MIT Press. This book was released on 2013-10-25 with total page 1693 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive review of contemporary research in the vision sciences, reflecting the rapid advances of recent years. Visual science is the model system for neuroscience, its findings relevant to all other areas. This essential reference to contemporary visual neuroscience covers the extraordinary range of the field today, from molecules and cell assemblies to systems and therapies. It provides a state-of-the art companion to the earlier book The Visual Neurosciences (MIT Press, 2003). This volume covers the dramatic advances made in the last decade, offering new topics, new authors, and new chapters. The New Visual Neurosciences assembles groundbreaking research, written by international authorities. Many of the 112 chapters treat seminal topics not included in the earlier book. These new topics include retinal feature detection; cortical connectomics; new approaches to mid-level vision and spatiotemporal perception; the latest understanding of how multimodal integration contributes to visual perception; new theoretical work on the role of neural oscillations in information processing; and new molecular and genetic techniques for understanding visual system development. An entirely new section covers invertebrate vision, reflecting the importance of this research in understanding fundamental principles of visual processing. Another new section treats translational visual neuroscience, covering recent progress in novel treatment modalities for optic nerve disorders, macular degeneration, and retinal cell replacement. The New Visual Neurosciences is an indispensable reference for students, teachers, researchers, clinicians, and anyone interested in contemporary neuroscience. Associate Editors Marie Burns, Joy Geng, Mark Goldman, James Handa, Andrew Ishida, George R. Mangun, Kimberley McAllister, Bruno Olshausen, Gregg Recanzone, Mandyam Srinivasan, W.Martin Usrey, Michael Webster, David Whitney Sections Retinal Mechanisms and Processes Organization of Visual Pathways Subcortical Processing Processing in Primary Visual Cortex Brightness and Color Pattern, Surface, and Shape Objects and Scenes Time, Motion, and Depth Eye Movements Cortical Mechanisms of Attention, Cognition, and Multimodal Integration Invertebrate Vision Theoretical Perspectives Molecular and Developmental Processes Translational Visual Neuroscience
Download or read book A self organizing neural network model of the primary visual cortex written by Joseph Sirosh and published by . This book was released on 1995 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The NEURON Book written by Nicholas T. Carnevale and published by Cambridge University Press. This book was released on 2006-01-12 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: The authoritative reference on NEURON, the simulation environment for modeling biological neurons and neural networks that enjoys wide use in the experimental and computational neuroscience communities. This book shows how to use NEURON to construct and apply empirically based models. Written primarily for neuroscience investigators, teachers, and students, it assumes no previous knowledge of computer programming or numerical methods. Readers with a background in the physical sciences or mathematics, who have some knowledge about brain cells and circuits and are interested in computational modeling, will also find it helpful. The NEURON Book covers material that ranges from the inner workings of this program, to practical considerations involved in specifying the anatomical and biophysical properties that are to be represented in models. It uses a problem-solving approach, with many working examples that readers can try for themselves.
Download or read book Principles of Computational Modelling in Neuroscience written by David Sterratt and published by Cambridge University Press. This book was released on 2023-10-05 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn to use computational modelling techniques to understand the nervous system at all levels, from ion channels to networks.
Download or read book Theory of Cortical Plasticity written by Leon N. Cooper and published by World Scientific. This book was released on 2004 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: This invaluable book presents a theory of cortical plasticity and shows how this theory leads to experiments that test both its assumptions and consequences. It elucidates, in a manner that is accessible to students as well as researchers, the role which the BCM theory has played in guiding research and suggesting experiments that have led to our present understanding of the mechanisms underlying cortical plasticity. Most of the connections between theory and experiment that are discussed require complex simulations. A unique feature of the book is the accompanying software package, Plasticity. This is provided complete with source code, and enables the reader to repeat any of the simulations quoted in the book as well as to vary either parameters or assumptions. Plasticity is thus a research and an educational tool. Readers can use it to obtain hands-on knowledge of the structure of BCM and various other learning algorithms. They can check and replicate our results as well as test algorithms andrefinements of their own.
Download or read book Development of the Visual System written by Retina Research Foundation (U.S.). Symposium and published by MIT Press. This book was released on 1991 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Development of the Visual System presents a selection of current studies that clearly illustrate principles of visual system development. These range from retinal development in fish and frogs to the effects of abnormal visual experience on the primary visual cortex of the cat. The book is unique in addressing four specific and fundamental aspects of development: cell lineage and cell fate, specificity and targeting of axons, specification of visual cortex, and correlates of the critical period. Encompassing technical advances in cellular and molecular biology and in video imaging and microscopy, contributions in each of these areas provide new information at the cellular and molecular levels to complement the now classic descriptions of visual development previously available at the level of neural systems.ContributorsKaren L. Allendoerfer, David M. Altshuler, Antonella Antonini, Seymour Benzer, Edward M. Callaway, Constance L. Cepko, Hollis T. Cline, Max S. Cynader, N. W. Daw, Scott E. Fraser, K. Fox, Eckhard Friauf, Anirvan Ghosh, R. W. Guillery, William A. Harris, Christine E. Holt, Lawrence C. Katz, Susan McConnell, Pamela A. Raymond, Thomas A. Reh, Carla J. Shatz, Michael P. Stryker, Claudia A. 0. Stuermer, Mriganka Sur, David L. Turner, T. N. Wiesel
Download or read book Neuronal Dynamics written by Wulfram Gerstner and published by Cambridge University Press. This book was released on 2014-07-24 with total page 591 pages. Available in PDF, EPUB and Kindle. Book excerpt: This solid introduction uses the principles of physics and the tools of mathematics to approach fundamental questions of neuroscience.
Download or read book Dynamic Clamp written by Alain Destexhe and published by Springer Science & Business Media. This book was released on 2009-03-11 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dynamic-clamp is a fascinating electrophysiology technique that consists of merging living neurons with computational models. The dynamic-clamp (also called “conductance injection”) allows experimentalists and theoreticians to challenge neurons (or any other type of cell) with complex conductance stimuli generated by a computer. The technique can be implemented from neural simulation environments and a variety of custom-made or commercial systems. The real-time interaction between the computer and cell also enables the design of recording paradigms with unprecedented accuracy via a computational model of the electrode. Dynamic-Clamp: From Principles to Applications contains contributions from leading researchers in the field, who investigate these paradigms at the cellular or network level, in vivo and in vitro, and in different brain regions and cardiac cells. Topics discussed include the addition of artificially-generated synaptic activity to neurons; adding, amplifying or neutralizing voltage-dependent conductances; creating hybrid networks with real and artificial cells; attaching simulated dendritic tree structures to the living cell; and connecting different neurons. This book will be of interest to experimental biophysicists, neurophysiologists, and cardiac physiologists, as well as theoreticians, engineers, and computational neuroscientists. Graduate and undergraduate students will also find up-to-date coverage of physiological problems and how they are investigated.
Download or read book Propagation of Orientation Selectivity in a Spiking Network Model of Layered Primary Visual Cortex written by Benjamin Merkt and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Neurons in different layers of sensory cortex generally have different functional properties. But what determines firing rates and tuning properties of neurons in different layers? Orientation selectivity in primary visual cortex (V1) is an interesting case to study these questions. Thalamic projections essentially determine the preferred orientation of neurons that receive direct input. But how is this tuning propagated though layers, and how can selective responses emerge in layers that do not have direct access to the thalamus? Here we combine numerical simulations with mathematical analyses to address this problem. We find that a large-scale network, which just accounts for experimentally measured layer and cell-type specific connection probabilities, yields firing rates and orientation selectivities matching electrophysiological recordings in rodent V1 surprisingly well. Further analysis, however, is complicated by the fact that neuronal responses emerge in a dynamic fashion and cannot be directly inferred from static neuroanatomy, as some connections tend to have unintuitive effects due to recurrent interactions and strong feedback loops. These emergent phenomena can be understood by linearizing and coarse-graining. In fact, we were able to derive a low-dimensional linear dynamical system effectively describing stimulus-driven activity layer by layer. This low-dimensional system explains layer-specific firing rates and orientation tuning by accounting for the different gain factors of the aggregate system. Our theory can also be used to design novel optogenetic stimulation experiments, thus facilitating further exploration of the interplay between connectivity and function
Download or read book Single Neuron Computation written by Thomas M. McKenna and published by Academic Press. This book was released on 2014-05-19 with total page 663 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains twenty-two original contributions that provide a comprehensive overview of computational approaches to understanding a single neuron structure. The focus on cellular-level processes is twofold. From a computational neuroscience perspective, a thorough understanding of the information processing performed by single neurons leads to an understanding of circuit- and systems-level activity. From the standpoint of artificial neural networks (ANNs), a single real neuron is as complex an operational unit as an entire ANN, and formalizing the complex computations performed by real neurons is essential to the design of enhanced processor elements for use in the next generation of ANNs.The book covers computation in dendrites and spines, computational aspects of ion channels, synapses, patterned discharge and multistate neurons, and stochastic models of neuron dynamics. It is the most up-to-date presentation of biophysical and computational methods.
Download or read book Methods and Models in Neurophysics written by Carson Chow and published by Elsevier. This book was released on 2005 with total page 876 pages. Available in PDF, EPUB and Kindle. Book excerpt: 1. E. Marder, Experimenting with theory -- 2. A. Borysuk and J. Rinzel, Understanding neuronal dynamics by geometrical dissection of minimal models -- 3. D. Terman, Geometry singular perturbation analysis of neuronal dynamics -- 4. G. Mato, Theory of neural synchrony -- 5. M. Shelley, Some useful numerical techniques for simulating integrate-and-fire networks -- 6. D. Golomb, Propagation of pulses in cortical networks: the single-spike approximation -- 7. M. Tsodyks, Activity-dependent transmission in neocortical synapses -- 8. H. Sompolinsky and J. White, Theory of large recurrent networks: from spikes to behavior -- 9. C. van Vreeswijk, Irregular activity in large networks of neurons -- 10. N. Brunel, Network models of memory -- 11. P. Bressloff, Pattern formation in visual cortex -- 12. F. Wolf, Symmetry breaking and pattern selection in visual cortical development -- 13. A. Treves and Y. Roudi, On the evolution of the brain -- 14. E. Brown, Theory of point processes for neural syst ...
