Synchrony-driven Assemblies Reliably Represent Complex Stimuli in Ferret Auditory Cortex

Abstract

Neuronal assemblies defined by coordination at high temporal resolution are thought to act as functional modules for information processing throughout the brain. Here, we develop a new method for identifying these assemblies from analytical tests of pairwise synchrony, benefiting from three rigorous criteria for assembly detection and sensitivity to rare but significant coordinated firing patterns. Following validation through simulations and in vivo recordings, we perform synchrony-based analysis on datasets from both primary (A1) and non-primary (PEG) ferret auditory cortex during passive listening to complex natural sounds. We show that synchrony-driven assemblies (SDAs) in both areas exhibit regular temporal dynamics, including the production of stereotypical spike sequences. In-keeping with their enhanced inter-neuronal reliability, SDAs are observed to outperform random assemblies in two versions of rate-based decoding. We extend these results to temporal decoding, and consistently observe optimal integration windows of 10-20ms. Thus, we suggest that SDAs are sufficient for the accurate representation of diverse sets of complex auditory stimuli, and that this increase in information depends entirely on coordination at very fine temporal scales.