Hierarchical computation in the canonical auditory cortical circuit

Abstract

Sensory cortical anatomy has identified a canonical microcircuit underlying computations between and within layers. This feed-forward circuit processes information serially from granular to supragranular and to infragranular layers. How this substrate correlates with an auditory cortical processing hierarchy is unclear. We recorded simultaneously from all layers in cat primary auditory cortex (AI) and estimated spectrotemporal receptive fields (STRFs) and associated nonlinearities. Spike-triggered averaged STRFs revealed that temporal precision, spectrotemporal separability, and feature selectivity varied with layer according to a hierarchical processing model. STRFs from maximally informative dimension (MID) analysis confirmed hierarchical processing. Of two cooperative MIDs identified for each neuron, the first comprised the majority of stimulus information in granular layers. Second MID contributions and nonlinear cooperativity increased in supragranular and infragranular layers. The AI microcircuit provides a valid template for three independent hierarchical computation principles. Increases in processing complexity, STRF cooperativity, and nonlinearity correlate with the synaptic distance from granular layers.