Dynamical systems modeling of Continuous Flash Suppression

Abstract

Continuous Flash Suppression (CFS) is a technique in which a stationary image in one eye can be reliably suppressed by rapid presentation of different flashing images in the other. In this paper we address why flashing stimuli modulate the visibility of the stimuli. We determine, in particular, which type of neural network is sufficient for the modulation of the dominance duration, assuming that elemental units are endowed with reciprocal inhibition and adaptation. We show that the model introduced by Wilson (2007) reproduces flash suppression, which is considered to be involved in CFS, but does not reproduce CFS. We then extend the model by including a stimulus feature dimension. With this extension, we found that the model accounts for the modulation of visibility observed in CFS. In addition, this model captured some defining characteristics of CFS such as dependence on flash interval and the depth of suppression. Our findings suggest that a network with inhibition and adaptation including feature dimension provides a crucial mechanism for the modulation of the dominance duration in CFS.