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Differential Inhibitory Responses to Temporal Features Enhance Cortical Coding of Dynamic Stimuli: A Network Model

Cortical circuits feature both excitatory and inhibitory cells that underlie the encoding of dynamic sensory stimuli, e.g., speech, music, odors, and natural scenes. While previous studies have shown that inhibition plays an important role in shaping the neural code, little is known about how excitatory and inhibitory cells coordinate to enhance encoding of temporally dynamic stimuli. Recent experimental recordings in mouse auditory cortex (ACx) have shown that optogenetic suppression of parvalbumin (PV) neurons results in a decrease of neural discriminability between dynamic stimuli with speech envelope modulations. Here, we present a multilayer model of a cortical circuit that mechanistically explains these results. The model incorporates characteristic short-term synaptic plasticity (STP) profiles of excitatory and PV cells. Crucially, the model performance is based on populations of PV cells that separately respond to stimulus onsets and offsets. We reveal that by tuning the relative strengths of inhibition from onset- and offset-responding PV cells, the cortical network model captures the broad range of neural discriminability profiles in cortical single-unit data, with varying contributions from rapid firing rate modulations and spike timing. The model also replicates and explains the experimentally observed reduction in neural discrimination performance during optogenetic suppression of PV neurons. These results suggest that distinct populations of PV neurons enhance cortical discriminability of dynamic stimuli by encoding distinct temporal features, enhancing temporal coding, and reducing cortical noise.