Optimal processing and sensorimotor coupling

Abstract

The cerebral cortex is a remarkably homogeneous structure suggesting a rather generic computational machinery. Indeed, under a variety of conditions, functions attributed to specialized areas can be supported by other regions. However, a host of studies have laid out an ever more detailed map of functional cortical areas. This leaves us with the puzzle of whether different cortical areas are intrinsically specialized, or whether they differ mostly by their position in the processing hierarchy and their inputs but apply the same computational principles. Here we show that the computational principle of optimal stability of sensory representations combined with local memory gives rise to a hierarchy of processing stages resembling the ventral visual pathway when it is exposed to continuous natural stimuli. Early processing stages show receptive fields similar to those observed in the primary visual cortex. Subsequent stages are selective for increasingly complex configurations of local features, as observed in higher visual areas. The last stage of the model displays place fields as observed in entorhinal cortex and hippocampus. Building on these results we derive the principle of optimal stability as the first order approximation of optimal predictability. We demonstrate that considering the action repertoire of an agent leads to a general framework for sensorimotor coupling.

About Peter König

His main scientific goal is the neurophysiological basis of cognitive funktions. He uses experimental and theoretical approaches to study sensory processing and sensory motor integration in the mammalian cortex under natural conditions. Emphasos is placed on the role of top-down signals, their relation to the fast dynamics, learning and plasticity in the neuronal network. Insights obtained from this work are transferred to real-world applications.

Peter König, Institute of Cognitive Science, Universität Osnabrück, Germany.