Classically, behavioural neuroscience theorizes about
experimental evidence in a qualitative way. However, more recently
there has been an increasing development of mathematical and
computational models of experimental results, and in general these
models are more clearly defined and more detailed than their
qualitative counter parts. These new computational models can be
set up so that they are consistent with both single neuron and
whole-system levels of operation, allowing physiological results to
be meshed with behavioural data thus closing the gap between
neurophysiology and human behaviour.
There is considerable diversity between models with respect to
the methodology of designing a model, the degree to which
neurophysiological processes are taken into account and the way
data (behavioural, electrophysiological, etc) constrains a model.
This book presents examples of this diversity and in doing so
represents the state-of-art in the field through a unique
collection of papers from the world's leading researchers in the
area of computational modelling in behavioural neuroscience.
Based on talks given at the third Behavioural Brain Sciences
Symposium, held at the Behavioural Brain Sciences Centre,
University of Birmingham, in May 2007, the book appeals to a broad
audience, from postgraduate students beginning to work in the field
to experienced experimenters interested in an overview.
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