Representation of Auditory Task Components and of Their Relationships in Primate Auditory Cortex

Abstract

The current study aimed to resolve some of the inconsistencies in the literature on which mental processes affect auditory cortical activity. To this end, we studied auditory cortical firing in four monkeys with different experience while they were involved in six conditions with different arrangements of the task components sound, motor action, and water reward. Firing rates changed most strongly when a sound-only condition was compared to a condition in which sound was paired with water. Additional smaller changes occurred in more complex conditions in which the monkeys received water for motor actions before or after sounds. Our findings suggest that auditory cortex is most strongly modulated by the subjects' level of arousal, thus by a psychological concept related to motor activity triggered by reinforcers and to readiness for operant behavior. Our findings also suggest that auditory cortex is involved in associative and emotional functions, but not in agency and cognitive effort.

Dissociation of task engagement and arousal effects in auditory cortex and midbrain

“…In the current study, we were able to use pupil size to explain changes in neural activity across both passive and active conditions. Changes in neural activity explained by pupil size are likely to overlap with some of the differences previously reported between task conditions, which may engage different levels of arousal (e.g., (Carcea et al, 2017;Knyazeva et al, 2020; Rodgers and DeWeese, 2014)). At the same time, pupil size is unlikely to explain changes in neural activity specific to a task.…”

“…Several previous studies have shown that transitioning from passive listening to active behavior leads to sizable changes in neural activity in A1 (Fritz et al, 2003;Niwa et al, 2012;Otazu et al, 2009) and IC (Ryan and Miller, 1977;Slee and David, 2015). The specific changes depend on properties of the task stimuli (Fritz et al, 2003;Jaramillo and Zador, 2011;Lee and Middlebrooks, 2011) and on structural elements of the task, such as reward contingencies (David et al, 2012), task difficulty (Atiani et al, 2009), the degree of engagement (Carcea et al, 2017;Knyazeva et al, 2020), and the focus of selective attention (Hocherman et al, 1976;Lakatos et al, 2013;Schwartz and David, 2018). In the current study, we were able to use pupil size to explain changes in neural activity across both passive and active conditions.…”

“…We observed this same pattern of suppression at the target frequency during behavior in the current dataset, even after accounting for pupil size ( Figure 6-figure supplement 1). Task engagement effects could also depend on the difficulty or other structural elements of the task (Carcea et al, 2017;Knyazeva et al, 2020). We considered whether state-dependent effects varied with task difficulty but found no differences between pure tone, high SNR tone-in-noise (easy), and low SNR tone-in-noise (hard) conditions ( Figure 6-figure supplement 2).…”

“…The substantial variability of effects across studies suggests that task engagement activates a constellation of non-auditory signals that comprise a complex internal state. Task-related changes in the activity of auditory neurons have been attributed to temporal expectation (Jaramillo and Zador, 2011), reward associations (Beaton and Miller, 1975;David et al, 2012), self-generated sound (Eliades and Wang, 2008), and non-sound related variables, such as motor planning Huang et al, 2019), motor activity (Schneider et al, 2014;Zhou et al, 2014), degree of engagement (Carcea et al, 2017;Knyazeva et al, 2020), and behavioral choice (Tsunada et al, 2015). Even in the absence of explicit behavior, fluctuations in neural activity are observed throughout the forebrain, including primary sensory regions (Ringach, 2009;Stringer et al, 2019).…”

Correlates of auditory decision making in prefrontal, auditory, and basal lateral amygdala cortical areas

“…Taken together it suggests that the strength and timing of the information transfer between AC and dlPFC can be flexibly allocated and is dependent on task demands. Lastly, comparison of the active and passive conditions highlights the sustained nonsensory motor/reward related activity in "primary" sensory cortex (AC) (Knyazeva, Selezneva et al 2020).…”