Computational model of dot-pattern selective cells.
A computational model of a dot-pattern selective neuron is proposed. This type of neuron is found in the inferotemporal cortex of monkeys. It responds strongly to groups of dots and spots of light intensity variation but very weakly or not at all to single dots and spots that are not part of a pattern. This non-linear behaviour is quite different from the spatial frequency filtering behaviour exhibited by other neurons that react to spot-shaped stimuli, such as neurons with centre-surround receptive field profiles found in the lateral geniculate nuclei and layer 4Cbeta of V1. It is implemented in the proposed computational model by using an AND-type non-linearity to combine the responses of centre-surround cells. The proposed model is capable of explaining the results of neurophysiological experiments as well as certain psychophysical observations.
Kruizinga
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P
lnstitute of Mathematics and Computing Science. University of Groningen, The Netherlands.
Petkov
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N
D000818:Animals; D003491:Cybernetics; D005829:Geniculate Bodies / Q000166:cytology / Q000502:physiology; D000882:Haplorhini; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology*; D017711:Nonlinear Dynamics; D016011:Normal Distribution; D009903:Optical Illusions / Q000502:physiology; D010364:Pattern Recognition, Visual / Q000502:physiology; D011601:Psychophysics; D013702:Temporal Lobe / Q000166:cytology* / Q000502:physiology; D014793:Visual Cortex / Q000166:cytology* / Q000502:physiology; D014794:Visual Fields / Q000502:physiology