Active Filtering: A Predictive Function of Recurrent Circuits of Sensory Cortex

Abstract

Our brains encode many features of the sensory world into memories: We can sing along with songs we have heard before, interpret spoken and written language composed of words we have learned, and recognize faces and objects. Where are these memories stored? Each area of cerebral cortex has a huge number of local recurrent excitatory–excitatory synapses, as many as 500 million per cubic millimeter. Here I outline evidence for the theory that cortical recurrent connectivity in sensory cortex is a substrate for sensory memories. Evidence suggests that the local recurrent network encodes the structure of natural sensory input and that it does so via active filtering, transforming network inputs to boost or select those associated with natural sensation. Active filtering is a form of predictive processing—in which the cortical recurrent network selectively amplifies some input patterns and attenuates others—and a form of memory.