Spatial and Temporal Organization of Composite Receptive Fields in the Songbird Auditory Forebrain

The mechanisms underlying how single auditory neurons and neuron populations encode natural and acoustically complex vocal signals, such as human speech or bird songs, are not well understood. Classical models focus on individual neurons, whose spike rates vary systematically as a function of change in a small number of simple acoustic dimensions. However, neurons in the caudal medial nidopallium (NCM), an auditory forebrain region in songbirds that is analogous to the secondary auditory cortex in mammals, have composite receptive fields (CRFs) that comprise multiple acoustic features tied to both increases and decreases in firing rates. Here, we investigated the anatomical organization and temporal activation patterns of auditory CRFs in European starlings exposed to natural vocal communication signals (songs). We recorded extracellular electrophysiological responses to various bird songs at auditory NCM sites, including both single and multiple neurons, and we then applied a quadratic model to extract large sets of CRF features that were tied to excitatory and suppressive responses at each measurement site. We found that the superset of CRF features yielded spatially and temporally distributed, generalizable representations of a conspecific song. Individual sites responded to acoustically diverse features, as there was no discernable organization of features across anatomically ordered sites. The CRF features at each site yielded broad, temporally distributed responses that spanned the entire duration of many starling songs, which can last for 50 s or more. Based on these results, we estimated that a nearly complete representation of any conspecific song, regardless of length, can be obtained by evaluating populations as small as 100 neurons. We conclude that natural acoustic communication signals drive a distributed yet highly redundant representation across the songbird auditory forebrain, in which adjacent neurons contribute to the encoding of multiple diverse and time-varying spectro-temporal features.