Differential representation of auditory categories between cell classes in primate auditory cortex

Abstract

Key points• The role that pyramidal neurons and interneurons have in auditory behaviour and cognition remains unknown.• In this study, we tested the hypothesis that pyramidal cells and interneurons in the auditory cortex play a differential role in auditory categorization.• Putative interneurons in the auditory cortex were more selective for auditory categories than putative pyramidal neurons.• The greater category selectivity in putative interneurons may be a characteristic of auditory categorization in the microcircuit of the auditory cortex.Abstract A comprehensive understanding of the neural mechanisms of cognitive function requires an understanding of how neural representations are transformed across different scales of neural organization: from within local microcircuits to across different brain areas. However, the neural transformations within the local microcircuits are poorly understood. Particularly, the role that two main cell classes of neurons in cortical microcircuits (i.e. pyramidal neurons and interneurons) have in auditory behaviour and cognition remains unknown. In this study, we tested the hypothesis that pyramidal cells and interneurons in the auditory cortex play a differential role in auditory categorization. To test this hypothesis, we recorded single-unit activity from the auditory cortex of rhesus monkeys while they categorized speech sounds. Based on the spike-waveform shape, a neuron was classified as either a narrow-spiking putative interneuron or a broad-spiking putative pyramidal neuron. We found that putative interneurons and pyramidal neurons in the auditory cortex differentially coded category information: interneurons were more selective for auditory categories than pyramidal neurons. These differences between cell classes may be an essential property of the neural computations underlying auditory categorization within the microcircuitry of the auditory cortex.

Detection of Tones and Their Modification by Noise in Nonhuman Primates

“…While many studies have looked at the behavioral and neurophysiological responses to simple and complex stimuli presented in isolation (Populin 2006;O'Connor et al 2011;Populin and Rajala 2010;Fishman and Steinschneider 2011;Tsunada et al 2011Tsunada et al , 2012, there have been very few studies of nonhuman primate hearing in noisy backgrounds. This study describes modification of behavioral responses by noise, as a prelude to our studies of the neurophysiological bases of hearing in natural environments.…”

Physiology, Psychoacoustics and Cognition in Normal and Impaired Hearing

“…While monkeys categorized speech sounds, we tested whether neural activity was modulated by monkeys' categorical judgements. We found that AL neurons were not modulated by the monkeys' reports (Tsunada et al 2011(Tsunada et al , 2012. In a separate line of studies, we asked monkeys to listen to a sequence of tone bursts and report whether the sequence had a "low" or "high" pitch.…”

Natural variability in species-specific vocalizations constrains behavior and neural activity

“…We recorded from well-isolated neurons in the anterolateral belt (AL) region of the auditory cortex of monkeys H and B. AL is part of the ventral auditory stream, which is thought to mediate auditory perception, and is known to be modulated strongly by vocalizations (Bizley and Cohen, 2013; Kusmierek et al, 2012; Rauschecker, 2012; Rauschecker and Tian, 2000; Rauschecker and Scott, 2009; Romanski and Averbeck, 2009; Russ et al, 2008b; Tsunada et al, 2011, 2012). Under isofluorane anesthesia and using aseptic surgical techniques, each monkey was implanted with a head-positioning post and a recording chamber.…”

“…Neurons were not selected based on their (a) sensitivity to particular coos or grunts nor (b) frequency tuning or other response properties. This strategy was justified because AL neurons respond broadly to different types of auditory stimuli (Kusmierek et al, 2012; Rauschecker and Tian, 2000; Russ et al, 2008b; Tsunada et al, 2011, 2012). …”

“…Extracellular neural signals were sampled at 24 kHz, amplified, and filtered (0.6–6.0 kHz) with a multi-channel recording system (Tucker–Davis Technologies). Spiking activity from individual neurons was extracted offline and sorted with a spike-sorting algorithm (WaveClus) (Quiroga et al, 2004; Tsunada et al, 2011, 2012) that ran on the Matlab (The Mathworks Inc.) programming platform.…”