Diverse cortical codes for scene segmentation in primate auditory cortex

Abstract

The temporal coherence of amplitude fluctuations is a critical cue for segmentation of complex auditory scenes. The auditory system must accurately demarcate the onsets and offsets of acoustic signals. We explored how and how well the timing of onsets and offsets of gated tones are encoded by auditory cortical neurons in awake rhesus macaques. Temporal features of this representation were isolated by presenting otherwise identical pure tones of differing durations. Cortical response patterns were diverse, including selective encoding of onset and offset transients, tonic firing, and sustained suppression. Spike train classification methods revealed that many neurons robustly encoded tone duration despite substantial diversity in the encoding process. Excellent discrimination performance was achieved by neurons whose responses were primarily phasic at tone offset and by those that responded robustly while the tone persisted. Although diverse cortical response patterns converged on effective duration discrimination, this diversity significantly constrained the utility of decoding models referenced to a spiking pattern averaged across all responses or averaged within the same response category. Using maximum likelihood-based decoding models, we demonstrated that the spike train recorded in a single trial could support direct estimation of stimulus onset and offset. Comparisons between different decoding models established the substantial contribution of bursts of activity at sound onset and offset to demarcating the temporal boundaries of gated tones. Our results indicate that relatively few neurons suffice to provide temporally precise estimates of such auditory "edges," particularly for models that assume and exploit the heterogeneity of neural responses in awake cortex.

A Hierarchy of Time Scales for Discriminating and Classifying the Temporal Shape of Sound in Three Auditory Cortical Fields

“…Prior studies indicate that the synchronized response duration or sound encoding time increases with increasing sound burst duration in A1 (Malone et al, 2015) and non-primary cortex (Lee et al, 2016) providing a potential neural code for temporal shape in the sound envelope. The "encoding time" corresponds to the time window over which a neuron conveys information about an ongoing sound and it can be quantified as a spike-timing variance (Theunissen and Miller, 1995;Chen et al, 2012) or alternatively as the duration of the response measured in the period histogram; that is, the histogram that is synchronized to the sound (Malone et al, 2015). Here we use the latter approach to examine how spiking patterns change throughout the duration of a sound burst by plotting the population response histogram and examine whether similar principles hold for non-primary cortices (see Materials and Methods; Fig.…”

“…2). A similar approach has been used previously to quantify temporal response patterns in inferior colliculus (Zheng and Escabí, 2008) and cortex (Malone et al, 2007(Malone et al, , 2015. The period histogram is constructed by aligning the spike-time histogram relative to the sound onset.…”

“…Because in this study, sounds were delivered at a repetition rate of 2 Hz all period histograms lasted 500 ms. This repetition frequency was chosen because it yields highly reliable trial-by-trial responses in the three cortices examined here (Lee et al, 2016) and in A1 of awake monkeys (Malone et al, 2015). Population period histograms were computed by summing responses across all cycles for all neurons for a given cortical field, binned in 2 ms windows ( Fig.…”

Parallel streams define the temporal dynamics of speech processing across human auditory cortex

“…Our work uncovered two major response types in Zone 1 and Zone 2 with "transient" and "sustained" responsivity to sentences. Such "phasic" and "tonic" response types have been observed in single unit electrophysiological recordings throughout the auditory system, including the temporal lobe auditory cortex (Eggermont, 2001;Malone et al, 2015;Romanski et al, 1999), auditory brain stem (Atencio et al, 2012;Zheng and Escab, 2008), and even prefrontal cortex, where they may be involved in decision making and object identification within the "ventral stream" (Bizley and Cohen, 2013;Romanski and Goldman-Rakic, 2002;Romanski et al, 1999;Tsunada et al, 2016). Previous studies, however, have not clearly documented the spatial segregation of these response types in auditory cortex.…”

Revealing the functions of supra-temporal and insular auditory responsive areas in humans

“…The auditory cortex encodes various temporal information (Brasselet et al, 2012;Fishman and Steinschneider, 2009;Ince et al, 2013;Malone et al, 2010,). This capability may benefit from the separated neuron populations which selectively respond to different temporal features (Malone et al, 2015;Hamilton et al, 2018). One of the lesion studies suggested that InsP may involve in auditory temporal processing (Bamiou et al, 2006).…”