Towards a theory of mind.
Summary: The language of nonlinear dynamical systems and ergodic theory is used to present a theoretical framework for the study of mind. The basic space \(X\) consists of the collection of all brain images (clusters of activated neurons) that are relevant to consciousness. The dynamics of the brain is modelled by means of a discrete time transformation \(T\) which takes a cluster of activated brain cells into another cluster of activated brain cells. The space \(X\) is partitioned into subcollections of brain images, namely those generated by the five senses and by other processes that produce brain images relevant to consciousness. It is argued that \(T\) is a Markov transformation with respect to this partition of \(X\). This leads to the existence of an object \(\mu\), referred to as an SRB measure which possesses properties that make it a candidate for mind: \(\mu\) is `aware' of the brain images in its support; \(\mu\) is time-invariant and acts as an attractor into which all orbits of (conscious) brain images settle. Furthermore, the dynamical systems model for mind allows the estimation of brain information rates and provides a framework in which a number of mind related issues can be discussed.
scientific article; zbMATH DE number 1529580