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Coding and processing of electrosensory information in gymnotiform fish
Author(s) -
Walter Heiligenberg
Publication year - 1989
Publication title -
journal of experimental biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.367
H-Index - 185
eISSN - 1477-9145
pISSN - 0022-0949
DOI - 10.1242/jeb.146.1.255
Subject(s) - stimulus (psychology) , neuroscience , biology , neural coding , communication , electric fish , stimulus modality , coding (social sciences) , efferent , psychology , sensory system , afferent , cognitive psychology , fish <actinopterygii> , mathematics , statistics , fishery
Studies of the electrosensory system of gymnotiform fish have revealed principles of neuronal coding and processing of information which also characterize more advanced systems, such as vision and audition in higher vertebrates. 1. Animals may have different classes of receptors adapted to code different variables within a given modality, and the separation of their central projections provides the basis for independent initial processing of these variables by higher-order neurones. 2. These separate pathways, however, eventually converge at the level of still higher-order neurones which are adapted to ‘recognize’ particular spatial and temporal constellations, or patterns, of the stimulus variables conveyed by these pathways. 3. As different stimulus patterns may control different forms of behavioural responses, corresponding neuronal structures can be identified which are adapted to recognize specific patterns. Neurones at an early level of pattern discrimination may still show very general response properties, whereas neurones closer to the ultimate control of a given behaviour show more specific response properties. These latter are less sensitive to stimulus features which are irrelevant to the control of the behaviour, and they code relevant features more purely and with higher acuity than do lower-level neurones. 4. The acuity of stimulus discrimination displayed by some high-order neurones may rival that observed at the behavioural level. This high sensitivity is achieved through pooling and integration of information supplied by large populations of less-sensitive receptors and lower-order neurones.

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