Parvalbumin neurons enhance temporal coding and reduce cortical noise in complex auditory scenes

Cortical representations supporting many cognitive abilities emerge from underlying circuits comprised of several different cell types. However, cell type-specific contributions to rate and timing-based cortical coding are not well-understood. Here, we investigated the role of parvalbumin neurons in cortical complex scene analysis. Many complex scenes contain sensory stimuli which are highly dynamic in time and compete with stimuli at other spatial locations. Parvalbumin neurons play a fundamental role in balancing excitation and inhibition in cortex and sculpting cortical temporal dynamics; yet their specific role in encoding complex scenes via timing-based coding, and the robustness of temporal representations to spatial competition, has not been investigated. Here, we address these questions in auditory cortex of mice using a cocktail party-like paradigm, integrating electrophysiology, optogenetic manipulations, and a family of spike-distance metrics, to dissect parvalbumin neurons' contributions towards rate and timing-based coding. We find that suppressing parvalbumin neurons degrades cortical discrimination of dynamic sounds in a cocktail party-like setting via changes in rapid temporal modulations in rate and spike timing, and over a wide range of time-scales. Our findings suggest that parvalbumin neurons play a critical role in enhancing cortical temporal coding and reducing cortical noise, thereby improving representations of dynamic stimuli in complex scenes. Analysis of mouse auditory cortex activity in a complex auditory scene suggests that parvalbumin neurons improve the brain's ability to analyze complex scenes by enhancing the timing of cortical responses, while also reducing cortical noise

Automated summary

By studying the auditory cortex of mice, it is found that parvalbumin neurons play a critical role in encoding complex scenes through timing-based coding, improving the cortex's ability to process dynamic stimuli and reducing cortical noise, thereby enhancing the representation of dynamic stimuli in complex scenes.