Visual illusions in neural networks: Line neutralization, tilt after effect, and angle expansion

Abstract

Certain visual illusions occur in neural networks that are capable of storing partially contrasted enhanced spatial patterns in short term memory (STM), and whose feature detectors are interconnected by nontrivial generalization gradients. These include neutralization, or adaptation, of nearly vertical or horizontal lines, tilt after-effect of successively viewed lines, and perceived angle expansion. Neutralization can be achieved by networks whose vertical and horizontal representations have higher saturation levels, broader tuning curves, or stronger input pathways. Tilt after-effect and angle expansion can be achieved by shunting lateral inhibition that causes an outward peak shift in the orientationally-coded STM pattern. The amount of outward peak shift is also dependent on the size of the potassium equilibrium point. Differences between the directions of tilt aftereffect (successive contrast) and angle expansion (simultaneous contrast) are ascribed to a normalization of total activity in the STM buffer whereby present stimuli and representations in STM of past stimuli interact to form a consistent action-oriented consensus.