Schwartz, Z. P. | bioRxiv Science

bioRxiv2019

Pupil-associated states modulate excitability but not stimulus selectivity in primary auditory cortex

Recent research in mice indicates that luminance-independent fluctuations in pupil size predict variability in spontaneous and evoked activity of single neurons in auditory and visual cortex. These findings suggest that pupil is an indicator of large-scale changes in arousal state that affect sensory processing. However, it is not known whether pupil-related state also influences the selectivity of auditory neurons. We recorded pupil size and single-unit spiking activity in the primary auditory cortex (A1) of non-anesthetized male and female ferrets during presentation of natural vocalizations and tone stimuli that allow measurement of frequency and level tuning. Neurons showed a systematic increase in both spontaneous and sound-evoked activity when pupil was large, as well as desynchronization and a decrease in trial-to-trial variability. Relationships between pupil size and firing rate were non-monotonic in some cells. In most neurons, several measurements of tuning, including acoustic threshold, spectral bandwidth, and best frequency, remained stable across large changes in pupil size. Across the population, however, there was a small but significant decrease in acoustic threshold when pupil was dilated. In some recordings, we observed rapid, saccade-like eye movements during sustained pupil constriction, which may indicate sleep. Including the presence of this state as a separate variable in a regression model of neural variability accounted for some, but not all, of the variability and non-monotonicity associated with changes in pupil size.\n\nNew & NoteworthyCortical neurons vary in their response to repeated stimuli, and some portion of the variability is due to fluctuations in network state. By simultaneously recording pupil and single-neuron activity in auditory cortex of ferrets, we provide new evidence that network state affects the excitability of auditory neurons, but not sensory selectivity. In addition, we report the occurrence of possible sleep states, adding to evidence that pupil provides an index of both sleep and physiological arousal.

neuroscience↗

bioRxiv2019

Spectral tuning of adaptation supports coding of sensory context in auditory cortex

Perception of vocalizations and other behaviorally relevant sounds requires integrating acoustic information over hundreds of milliseconds, but the latency of sound-evoked activity in auditory cortex typically has much shorter latency. It has been observed that the acoustic context, i.e., sound history, can modulate sound evoked activity. Contextual effects are attributed to modulatory phenomena, such as stimulus-specific adaption and contrast gain control. However, an encoding model that links context to natural sound processing has yet to be established. We tested whether a model in which spectrally tuned inputs undergo adaptation mimicking short-term synaptic plasticity can account for contextual effects during natural sound processing. Single-unit activity was recorded from primary auditory cortex of awake ferrets during presentation of noise with natural temporal dynamics and fully natural sounds. Encoding properties were characterized by a standard linear-nonlinear spectro-temporal receptive field model (LN STRF) and STRF variants that incorporated STP-like adaptation. In two models, STP was applied either globally across all spectral channels or locally to subsets of channels. For most neurons, STRFs incorporating locally tuned STP predicted neural activity as well or better than the LN and global STP STRF. The strength of nonlinear adaptation varied across neurons. Within neurons, adaptation was generally stronger for activation with excitatory than inhibitory gain. Neurons showing improved STP model performance also tended to undergo stimulus-specific adaptation, suggesting a common mechanism for these phenomena. When STP STRFs were compared between passive and active behavior conditions, response gain often changed, but average STP parameters were stable. Thus, spectrally and temporally heterogeneous adaptation, subserved by a mechanism with STP-like dynamics, may support representation of the diverse spectro-temporal patterns that comprise natural sounds. Author summarySuccessfully discriminating between behaviorally relevant sounds such as vocalizations and environmental noise requires processing how acoustic information changes over many tens to hundreds of milliseconds. The sound-evoked activity measured for most auditory cortical neurons is relatively short (< 50 ms), so it is not clear how the auditory cortex encodes sound information over longer periods. In this study, we propose that nonlinear adaptation, mimicking the effects of short-term synaptic plasticity (STP), enables auditory neurons to encode longer and more complex spectro-temporal patterns. A model in which sound history is stored in the latent state of plastic synapses is able to describe responses of single cortical neurons to natural sounds better than a standard encoding model that does not include nonlinear adaptation. Moreover, STP-like adaptation can account for contextual effects on sound evoked activity that cannot be accounted for by standard encoding models.

neuroscience↗