On the Topological Representation of Signals in Self-Organizing Nerve Fields
The brain can self-organize its structure based on environmental information. More specifically, when a set of signals is applied repeatedly to a nerve system, for each signal in the set, the system forms by self-organization sets of representative cells that are excited in response to particular signals but are not excited by any other signals. Such a representation may be regarded as a model of the outer world formed in the nervous system. This is one simple aspect of self-organization taking place in the brain. Physiologists have so far found hypercolumnar and microcolumnar structures in the primary visual cortex in which orientation-detecting cells, i.e., cells representative of lines of various orientations, are formed and fixed by self-organization. Moreover, hypercolumns are arranged retinotopically, and orientation-detecting cells are arranged in each hypercolumn in the order of preferable orientations. Physiologists have also found in various parts of the cerebrum cells which are responsive to specific shapes of objects, specific types of motions, and, in particular, faces of men or monkeys.
KeywordsRetina Convolution Sine Cose
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- Kohohen, T. : Self-Organization and Associative Memory, SpringerGoogle Scholar