Temporal information of subsecond sensory stimuli in primary visual cortex is encoded via high dimensional population vectors

Abstract

Whether in music, language, baking, or memory, our experience of the world is fundamentally linked to time. However, it is unclear how temporal information is encoded, particularly in the range of milliseconds to seconds. Temporal processing at this scale is critical to prediction and survival, such as in a prey anticipating not only where a charging predator will go but alsowhenthe predator will arrive at that location. Several models of timing have been proposed that suggest that either time is encoded intrinsically in the dynamics of a network or that time is encoded by mechanisms that are explicitly dedicated to temporal processing. To determine how temporal information is encoded, we recorded neural activity in primary visual cortex (V1) as mice (male and female) performed a goal directed sensory discrimination task, in which patterns of subsecond stimuli differed only in their temporal profiles. We found that temporal information was encoded in the changing population vector of the network and that the space between these vectors was maximized in learned sessions. Our results suggest that temporal information in the subsecond range is encoded intrinsically and does not rely upon specialized timing mechanisms.SIGNIFICANCE STATEMENTOur experience of the world is fundamentally linked to time, but it is unclear how temporal information is encoded, particularly in the range of milliseconds to seconds. Using a sensory discrimination task in which patterns of subsecond stimuli differed in their temporal profiles, we found that primary visual cortex encodes temporal information via the changing population vector of the network. As temporal processing via population encoding has been shown to rely on inhibitory activity in computational models, our results may provide insight into temporal processing deficits in disorders such as autism spectrum disorder in which there is inhibitory-excitatory imbalance. Furthermore, our results may underlie processing of higher-order sensory stimuli, such as language, that are characterized by complex temporal sequences.