The neural computation of the aperture problem: an iterative process

Abstract

The aperture problem is defined as one of integrating motion information from inside and outside of the aperture, and determination of the true direction of motion of a line. Much is known about it and many models have been proposed for its neural mechanisms. However, it is still a matter of debate whether the brain solves the problem by using only feed-forward neural connections, also known as the one-shot algorithm, or by using the iterative algorithm while utilizing feedback as well as horizontal neural connections. Here we show unequivocal evidence for the latter model. The model was tested using critically designed psychophysical experiments and the results were perfectly in line with the psychophysical performance of the observers.