Model Cortical Association Fields Account for the Time Course and Dependence on Target Complexity of Human Contour Perception
Vadas Gintautas, Michael I. Ham, Benjamin Kunsberg, Shawn Barr, Steven, P. Brumby, Craig Rasmussen, John S. George, Ilya Nemenman, Luis M. A., Bettencourt, Garrett T. Kenyon

TL;DR
This study demonstrates that cortical association fields in early visual cortex can explain the timing and difficulty of human contour perception, supported by psychophysical experiments and a computational model.
Contribution
The paper introduces a computational model linking cortical association fields to human contour detection timing and complexity dependence.
Findings
Psychometric functions fit by sigmoids with 30-91 ms time constants.
Model responses modulated by cortical association fields match human data.
Each lateral interaction iteration takes at least 37.5 ms.
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.…
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