Biophysics of Computation

📘 Book Details

• Author: Christof Koch

• Publisher: Oxford University Press

• Language: English

• Edition: Illustrated

• ISBN: 9780195181999

• Pages: 586

• Cover: Paperback

• Release Date: 01-10-2004

• Dimensions: 9.2 x 6.1 x 1.3 inches

📝 About The Book

"Biophysics of Computation: Information Processing in Single Neurons" by Christof Koch challenges traditional approaches to neural network research by highlighting the complex, dynamic nature of synapses, dendrites, and voltage-dependent ionic currents. Often, neural network models simplify neurons into linear threshold units, but this book uses detailed experimental and theoretical findings from cellular biophysics to demonstrate the diverse computational functions available to single neurons.

In this groundbreaking work, Koch explains how individual nerve cells can perform complex tasks such as multiplying, integrating, or delaying synaptic inputs, and how information is encoded in mechanisms like membrane voltage, intracellular calcium concentrations, or the timing of individual spikes. The book integrates theory with experimental data to offer a deep exploration of cellular biophysics and its connection to computation.

Key Topics Covered:

• Cellular Biophysics: The use of cellular biophysics in understanding computational functions of neurons.

• Synaptic Dynamics: Detailed analysis of chemical and electrical synapses and their computational aspects.

• Hodgkin-Huxley Model: In-depth discussion of the action potential generation and propagation.

• Neuronal Code: Exploration of how information is encoded and processed in individual neurons.

• Synaptic Plasticity: Models for short- and long-term changes in synaptic strength and their role in learning.

• Nonlinear Interactions: Understanding complex interactions between synaptic inputs in dendritic trees.

• Neuronal Firing: Stochastic models of neuronal firing and their impact on computation.

This book is an invaluable resource for students and professionals interested in cellular biophysics, computational neuroscience, and neural networks. It is particularly suited for advanced undergraduate and graduate courses and will appeal to anyone in neuroscience, electrical and computer engineering, and physics.