Modeling in the Neurosciences

Regular price €291.40
Quantity:
In stock with our UK publisher. 14-28 days
Delivery/Collection within 10-20 working days
14 days return policy Shipping & Delivery
advanced neural systems modeling
AMPA Receptor
Axial Current
Backpropagating Action Potentials
Bifurcation Points
biophysical modeling
branch
Cable Equation
CaMKII Activation
Category=PSAN
cellular neurophysiology
computational neuroscience
dendritic
Dendritic Growth Model
Dendritic Segment
Dendritic Spines
Dendritic Tree
Electrotonic Length
eq_bestseller
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_science
Equivalent Cable
Equivalent Cylinder
Extracellular Potential
Green's Function
Green’s Function
Intracellular Potential
long-term
mathematical neuroscience methods
membrane
Membrane Potential
neuronal circuit analysis
NMDA Receptor Channel
Persistent Sodium
potential
potentiation
Pyramidal Neurons
spike
Spike Train
spine
Synaptic Conductance
Synaptic Inputs
synaptic plasticity
Tail Current
train
Transmembrane Current
tree

Product details

  • ISBN 9780415328685
  • Weight: 1440g
  • Dimensions: 178 x 254mm
  • Publication Date: 29 Mar 2005
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
Secure checkout Fast Shipping Easy returns

Computational 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 suffer from oversimplification in the former case and excessive discretization in the second. This book introduces an integrative approach to modeling neurons and neuronal circuits that retains the integrity of the biological units at all hierarchical levels.

With contributions from more than 40 renowned experts, Modeling in the Neurosciences, Second Edition is essential for those interested in constructing more structured and integrative models with greater biological insight. Focusing on new mathematical and computer models, techniques, and methods, this book represents a cohesive and comprehensive treatment of various aspects of the neurosciences from the molecular to the network level. Many state-of-the-art examples illustrate how mathematical and computer modeling can contribute to the understanding of mechanisms and systems in the neurosciences. Each chapter also includes suggestions of possible refinements for future modeling in this rapidly changing and expanding field.

This book will benefit and inspire the advanced modeler, and will give the beginner sufficient confidence to model a wide selection of neuronal systems at the molecular, cellular, and network levels.

G. N. Reeke, R. R. Poznanski, K. A. Lindsay, J. R. Rosenberg, O. Sporns