Computational explorations in cognitive neuroscience - Randall C. O'Reilly

The goal of computational cognitive neuroscience is to understand how the
brain embodies the mind by using biologically based computational models comprising
networks of neuronlike units. This text, based on a course taught by Randall
O'Reilly and Yuko Munakata over the past several years, provides an in-depth
introduction to the main ideas in the field. The neural units in the simulations use
equations based directly on the ion channels that govern the behavior of real
neurons, and the neural networks incorporate anatomical and physiological properties
of the neocortex. Thus the text provides the student with knowledge of the basic
biology of the brain as well as the computational skills needed to simulate
large-scale cognitive phenomena.

The text consists of two parts.
The first part covers basic neural computation mechanisms: individual neurons,
neural networks, and learning mechanisms. The second part covers large-scale brain
area organization and cognitive phenomena: perception and attention, memory,
language, and higher-level cognition. The second part is relatively self-contained
and can be used separately for mechanistically oriented cognitive neuroscience
courses. Integrated throughout the text are more than forty different simulation
models, many of them full-scale research-grade models, with friendly interfaces and
accompanying exercises. The simulation software (PDP++, available for all major
platforms) and simulations can be downloaded free of charge from the Web. Exercise
solutions are available, and the text includes full information on the
software.