Dual Counterstream Architecture May Support Separation Between Vision and Predictions

According to a predictive coding framework, visual processing involves the computation of prediction errors between sensory data and a generative model that is supplied via feedback projections. This implies that vision is cognitively penetrable by all sorts of top-down influences. In this paper, we review anatomical and functional data which suggest that feedforward and feedback projections are organized into two parallel processing streams: the supragranular and the infragranular counterstreams. The supragranular counterstream computes surface and motion representation in depth. It represents the best interpretation of what is given in the input image based on physical regularities that are built into this network. By contrast, the infragranular counterstream integrates vision with cognition, because it represents what is likely to be found in the environment based on the predictions derived from learned statistical regularities. The two counterstreams work in parallel, but independently of each other. They compete for dominance, and only one is allowed to deliver its output to higher-order areas at any instance of time. Such an arrangement allows the supragranular counterstream to remain cognitively impenetrable to top-down influences.