CTN: Kenneth Harris

Title: Multidimensional structure of activity in transcriptomically identified cortical cell types

Abstract: The cerebral cortex is comprised of hundreds of distinct cell types, connected into a network that underpins cognition.  To characterize the geometry of population activity in these cells, we recorded from thousands of neurons simultaneously in mouse visual cortex, and used post-hoc in situ transcriptomics to characterize their fine subtypes. We found that cortical population activity is organized around a single dimension shared between the subspace of spontaneous activity and responses to natural image stimuli, and that a neuron’s coupling with this dimension can be predicted from a its transcriptome.

Spontaneous population activity differed substantially with the animal’s behavioral state.  Population activity in alert states could be classified by two primary dimensions, the first distinguishing locomoting vs. stationary periods, and the second correlating with running speed; neurons correlated positively and negatively with both dimensions.  In non-alert states, spontaneous activity was organized around a single dominant dimension which spontaneously oscillated, and was close to orthogonal to the two running-related dimensions.  The coupling of neurons with this shared dimension was almost always non-negative.

Natural image stimuli drove population activity in a subspace that overlapped the subspace of spontaneous activity only in one dimension: the dimension that was active in spontaneous oscillations of non-alert states. Even though this dimension was spontaneously oscillatory only during non-alert states, sensory responses along this dimension were larger during running periods. This single shared dimension accounted for a larger fraction of total stimulus-related variance in inhibitory than excitatory neurons, and in superficial than deep excitatory populations.

The neurons to these three dimensions could be predicted from their transcriptomes.  This prediction was weaker amongst superficial excitatory neurons, whose strongest transcriptomic prediction was found for coupling to the oscillatory dimension.

We conclude that cortical activity is organized around a single dimension shared between spontaneous oscillations and natural image responses, and hypothesize that this dimension encodes the salience of sensory or non-sensory messages broadcast from visual cortex to other cortical regions.