The role of inhibitory neurons in novelty sound detection in regular and random statistical contexts.

Abstract

Detecting statistical regularities in sound and responding to violations of these patterns, termed deviance detection, is a core function of the auditory system. In the human brain, studies have shown that deviance responses are enhanced in regular compared to random auditory contexts, but the underlying neuronal circuit mechanisms remain unclear. Here, we examined how inhibitory neurons contribute to context-dependent deviance responses in mouse auditory cortex (AC). Using two-photon calcium imaging in AC of awake head-fixed male and female mice, we recorded neuronal activity during presentation of spectro-temporally rich moving ripple sounds, with deviant ripples embedded in either regular or random ripple sequences. AC neurons exhibited stronger responses to deviant sounds in regular contexts compared to random ones. To identify circuit mechanisms, we selectively inactivated parvalbumin (PV), somatostatin (SST), or vasoactive intestinal polypeptide (VIP) inhibitory neurons during the deviant stimulus presentation. Inactivation of PV and SST neurons broadly increased deviance responses in both contexts. In contrast, VIP inactivation selectively reduced responses to deviant stimuli in the regular, but not random, context, decreasing the context-dependent deviance signal enhancement. At the population level, inactivating all three neuronal subtypes increased detectability of the deviant stimulus, but the effects were context-dependent only for VIP inactivation. These findings reveal a distinct role for VIP neurons in modulating deviance signals based on context regularity, identifying a specific inhibitory neuron type that is critical for context-sensitive auditory processing and predictive coding. SIGNIFICANCE STATEMENTUnderstanding how the brain detects and responds to predictable and unexpected sounds is critical for communication and navigation in complex acoustic environments. Although prior studies have shown that detection of novel sounds is enhanced by regularity in background sound patterns, the underlying circuit mechanisms have remained unknown. Here, we find that neurons in the auditory cortex exhibit stronger deviance responses when the deviant sounds are embedded in regular, predictable sound sequences as compared to random sound sequences. Importantly, we identify a distinct role for specific inhibitory neurons in modulating this context-dependent enhancement. These findings reveal a new insight into how cortical circuits implement predictive coding strategies to optimize sensory processing.