title: Model cortical association fields account for the time course and dependence on target complexity of human contour perception.
abstract: Can lateral connectivity in the primary visual cortex account for the time dependence and intrinsic task difficulty of human contour detection? To answer this question, we created a synthetic image set that prevents sole reliance on either low-level visual features or high-level context for the detection of target objects. Rendered images consist of smoothly varying, globally aligned contour fragments (amoebas) distributed among groups of randomly rotated fragments (clutter). The time course and accuracy of amoeba detection by humans was measured using a two-alternative forced choice protocol with self-reported confidence and variable image presentation time (20-200 ms), followed by an image mask optimized so as to interrupt visual processing. Measured psychometric functions were well fit by sigmoidal functions with exponential time constants of 30-91 ms, depending on amoeba complexity. Key aspects of the psychophysical experiments were accounted for by a computational network model, in which simulated responses across retinotopic arrays of orientation-selective elements were modulated by cortical association fields, represented as multiplicative kernels computed from the differences in pairwise edge statistics between target and distractor images. Comparing the experimental and the computational results suggests that each iteration of the lateral interactions takes at least [Formula: see text] ms of cortical processing time. Our results provide evidence that cortical association fields between orientation selective elements in early visual areas can account for important temporal and task-dependent aspects of the psychometric curves characterizing human contour perception, with the remaining discrepancies postulated to arise from the influence of higher cortical areas.
authors: Center for Nonlinear Studies and T-5, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America. vgintautas@chatham.edu
authors: Vadas
authors: V
authors: Gintautas
authors: Michael I
authors: MI
authors: Ham
authors: Benjamin
authors: B
authors: Kunsberg
authors: Shawn
authors: S
authors: Barr
authors: Steven P
authors: SP
authors: Brumby
authors: Craig
authors: C
authors: Rasmussen
authors: John S
authors: JS
authors: George
authors: Ilya
authors: I
authors: Nemenman
authors: Luís M A
authors: LM
authors: Bettencourt
authors: Garrett T
authors: GT
authors: Kenyon
authors: Garret T
authors: GT
authors: Kenyon
mesh_terms: D019295:Computational Biology; D005556:Form Perception / Q000502:physiology*; D006801:Humans; D008959:Models, Neurological; D010775:Photic Stimulation; D011601:Psychophysics; D011930:Reaction Time; D013997:Time Factors; D014793:Visual Cortex / Q000502:physiology*