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The 'ecological' probability density function for linear optic flow: implications for neurophysiology
Authors:Ivins J  Porrill J  Frisby J  Orban G
Institution:Department of Computer Science, Curtin University of Technology, Perth, Western Australia. ivinsj@cs.curtin.edu.au
Abstract:A theoretical analysis of the recovery of shape from optic flow highlights the importance of the deformation components; however, pure deforming stimuli elicit few responses from flow-sensitive neurons in the medial superior temporal (MST) area of the cerebral cortex. This finding has prompted the conclusion that MST cells are not involved in shape recovery. However, this conclusion may be unjustified in view of the emerging consensus that MST cells perform nonlinear pattern matching, rather than linear projection as implicitly assumed in many neurophysiological studies. Artificial neural models suggest that the input probability density function (PDF) is crucial in determining the distribution of responses shown by pattern-matching cells. This paper therefore describes a Monte-Carlo study of the joint PDF for linear optic-flow components produced by ego-motion in a simulated planar environment. The recent search for deformation-selective cells in MST is then used to illustrate the importance of the input PDF in determining cell characteristics. The results are consistent with the finding that MST cells exhibit a continuum of responses to translation, rotation, and divergence. In addition, there are negative correlations between the deformation and conformal components of optic flow. Consequently, if cells responsible for shape analysis are present in the MST area, they should respond best to combinations of deformation with other first-order flow components, rather than to the pure stimuli used in previous neurophysiological studies.
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