Computational Neuroscience: Theoretical Insights into Brain Function (eBook, PDF)

Redaktion: Cisek, Paul; Kalaska, John; Drew, Trevor

• Format: PDF

Produktbeschreibung

Computational neuroscience is a relatively new but rapidly expanding area of research which is becoming increasingly influential in shaping the way scientists think about the brain. Computational approaches have been applied at all levels of analysis, from detailed models of single-channel function, transmembrane currents, single-cell electrical activity, and neural signaling to broad theories of sensory perception, memory, and cognition. This book provides a snapshot of this exciting new field by bringing together chapters on a diversity of topics from some of its most important contributors. This includes chapters on neural coding in single cells, in small networks, and across the entire cerebral cortex, visual processing from the retina to object recognition, neural processing of auditory, vestibular, and electromagnetic stimuli, pattern generation, voluntary movement and posture, motor learning, decision-making and cognition, and algorithms for pattern recognition. Each chapter provides a bridge between a body of data on neural function and a mathematical approach used to interpret and explain that data. These contributions demonstrate how computational approaches have become an essential tool which is integral in many aspects of brain science, from the interpretation of data to the design of new experiments, and to the growth of our understanding of neural function.

. Includes contributions by some of the most influential people in the field of computational neuroscience
. Demonstrates how computational approaches are being used today to interpret experimental data
. Covers a wide range of topics from single neurons, to neural systems, to abstract models of learning

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Produktdetails

• Verlag: Elsevier Science & Techn.
• Seitenzahl: 570
• Erscheinungstermin: 14. November 2007
• Englisch
• ISBN-13: 9780080555027
• Artikelnr.: 52999148

Inhaltsangabe

The neuronal transfer function: contributions from voltage and time-dependent mechanisms E.P. Cook
A.C. Wilhelm
J.A. Guest
Y. Liang
N.Y. Masse and C.M. Colbert (Montreal QC
Canada and Houston
TX
USA). A simple growth model constructs critical avalanche networks L.F. Abbott and R. Rohrkemper (New York
NY
USA and Zurich
Switzerland). The dynamics of visual responses in the primary visual cortex R. Shapley
M. Hawken and D. Xing (New York
NY
USA). A quantitative theory of immediate visual recognition T. Serre
G. Kreiman
M. Kouh
C. Cadieu
U. Knoblich and T. Poggio (Boston
MA
USA). Attention in hierarchical models of object recognition D.B. Walther and C. Koch (Urbana
IL
and Pasadena
CA
USA). Towards a unified theory of neocortex: laminar cortical circuits for vision and cognition S. Grossberg (Boston
MA
USA). Real-time neural coding of memory J.Z. Tsien (Boston
MA
USA). Beyond timing in the auditory brainstem: intensity in the avian cochlear nucleus angularis K.M. MacLeod and C.E. Carr (College Park
MD
USA). Neural strategies for optimal processing of sensory signals L. Maler (Ottawa
ON
Canada). Coordinate transformations and sensory integration in the detection of spatial orientation and self-motion: from models to experiments A.M. Green and D.E. Angelaki (Montreal
QC
Canada and St. Louis
MO
USA). Sensorimotor optimization in higher dimensions . Tweed (Toronto
ON
USA). How tightly tuned are network parameters? Insight from computational and experimental studies in small rhythmic motor networks E. Marder
A.-E. Tobin and R. Grashow (Waltham
MA
USA). Spatial organization and state-dependent mechanisms for respiratory rhythm and pattern generation I.A. Rybak
A.P.L. Abdala
S.N. Markin
J.F.R. Paton and J.C. Smith (Philadelphia
PA and Bethesda
MD
USA and Bristol
UK). Modeling a vertebrate motor system - pattern generation
steering and control of body orientation S. Grillner
A. Kozlov
P. Dario
C. Stefanini
A. Menciassi
A. Lansner
J. Hellgren Kotaleski (Stockholm
Sweden and Pontedera
Italy). Modeling the mammalian locomotor CPG: insights from mistakes and perturbations D.A. McCrea and I.A. Rybak (Winnipeg
MB
Canada and Philadelphia
PA
USA). The neuromechanical tuning hypothesis A. Prochazka and S. Yakovenko (Edmonton
AB and Montreal
QC
Canada). Threshold position control and the principle of minimal interaction in motor actions A.G. Feldman
V. Goussev
A. Sangole and M.F. Levin (Montreal and Laval
QC
Canada). Modelling sensorimotor control of human upright stance T. Mergner (Freiburg
Germany). Dimensional reduction in sensorimotor systems: a framework for understanding muscle coordination of posture L.H. Ting (Atlanta
GA
USA). Primitives
premotor drives and pattern generation: a combined computational and neuroethological perspective S. Giszter
V. Patil and C. Hart (Philadelphia
PA
USA). A multi-level approach to understanding upper limb function I. Kurtzer and S.H. Scott (Kingston
ON
Canada). How is somatosensory information used to adapt to changes in the mechanical environment? T.E. Milner
M.R. Hinder and D.W. Franklin (Burnaby
BC
Queensland
Australia and Kyoto
Japan). Trial-by-trial motor adaptation: a window into elemental neural computation K.A. Thoroughman
M.S. Fine and J.A. Taylor (Saint Louis
MO
USA). Towards a computational neuropsychology of action J.W. Krakauer and R. Shadmehr (New York
NY and Baltimore
MD
USA). Motor control in a meta-network with attractor dynamics N.I. Krouvhev and J.F. Kalaska (Montreal
WC
Canada). Computing movement geometry - a step in sensory-motor transformations D. Zipser and E. Torres (Pasadena
CA
USA). Dynamics systems versus optimal control - a unifying view S. Schaal
P. Mohajerian and A. Ijspeert (Los Angeles
CA
USA
Kyoto
Japan and Lausanne
Switzerland). The place of 'codes' in nonlinear neurodynamics W.J. Freeman (Berkeley
CA
USA). From a representation of behaviour to the concept of cognitive syntax: a theoretical framework T. Gisiger and M. Kerszberg (Paris
France). A parallel framework for interactive behaviour P. Cisek (Montreal
QC
Canada). Statistical models for neural encoding
decoding
and optimal stimulus design L. Paninski
J. Pillow and J. Lewi (New York
NY
USA and London
UK). Probabilistic population codes and the exponential family of distributions J. Beck
W. Ma
P.E. Latham and A. Pouget (Rochester
NY
USA and London
UK). On the challenge of learning complex functions Y. Bengio (Montreal
QC
Canada). To recognize shapes
first learn to generate images G.E. Hinton (Toronto
Canada).