17 March 1994 Psychophysical evidence for both a "quasi-linear" and a "nonlinear" mechanism for the detection of motion
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Proceedings Volume 2054, Computational Vision Based on Neurobiology; (1994) https://doi.org/10.1117/12.171140
Event: Computational Vision Based on Neurobiology, 1993, Park Grove, CA, United States
Abstract
A random Gabor Kinematogram stimulus provides the opportunity to demonstrate Fourier and non-Fourier motion perception, and discontinuities of performance from one to the other, in a way that supports the existence of categorically distinct underlying mechanisms. Two-frame apparent motion was used with a stimulus comprised of micropatterns randomly distributed across the visual field. The micropatterns were Gabor functions that contain a narrow band of spatial frequencies and orientations while maintaining a local nature in space. Psychophysical techniques were used to assess the detection of motion of this stimulus; two underlying processes were identified and characterized. For short temporal intervals and spatially dense stimuli, the response of the visual system can be predicted from the direction information in the spatio-temporal Fourier power spectrum of the stimulus: a quasi-linear mechanism. For longer temporal intervals and spatially sparse stimuli, detection of motion is NOT predictable from the information in the spatio-temporal Fourier power spectrum. Performance is independent of the spatial frequency content and orientation of the micro-patterns, but is limited by the `density' of stimulus elements along the axis of motion: a nonlinear mechanism. It is proposed that the nonlinear mechanism is mediated by the parvocellular retina-cortical pathway, and the quasi-linear by the magnocellular pathway.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jane C. Boulton and Curtis L. Baker "Psychophysical evidence for both a "quasi-linear" and a "nonlinear" mechanism for the detection of motion", Proc. SPIE 2054, Computational Vision Based on Neurobiology, (17 March 1994); doi: 10.1117/12.171140; https://doi.org/10.1117/12.171140
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