Response outcome gates the effect of spontaneous cortical state fluctuations on perceptual decisions

Abstract

Sensory responses of cortical neurons are more discriminable when evoked on a baseline of desynchronized spontaneous activity, but cortical desynchronization has not generally been associated with more accurate perceptual decisions. Here we show that mice perform more accurate auditory judgements when activity in the auditory cortex is elevated and desynchronized before stimulus onset, but only if the previous trial was an error, and that this relationship is occluded if previous outcome is ignored. We confirmed that the outcome-dependent effect of brain state on performance is neither due to idiosyncratic associations between the slow components of either signal, nor to the existence of specific cortical states evident only after errors. Instead, errors appear to gate the effect of cortical state fluctuations on discrimination accuracy. Neither facial movements nor pupil size during the baseline were associated with accuracy, but they were predictive of measures of responsivity, such as the probability of not responding to the stimulus or of responding prematurely. These results suggest that the functional role of cortical state on behavior is dynamic and constantly regulated by performance monitoring systems.

Perception and propagation of activity through the cortical hierarchy is determined by neural variability

“…We do not have the experimental capacity to disentangle all potential paths driving S2 activity. These include, but are not limited to: direct, monosynaptic transmission from S1 to S2 38,41,98 , indirect paths via other brain regions 99 , brain state changes due to reward consumption 83 , or reafference from the whiskers 100 or muscles 95,96 . Thus, while we can make statements about a causal relation, we cannot make any claim about the specific paths or their relative contributions.…”

“…Other metrics of pre-stimulus neural variability, such as single-cell temporal variance 13,82 , synchrony 16,83 and neural oscillation power 19,84,85 have all previously been linked to task performance. Although differences in recording techniques preclude direct comparisons, in particular, lower variance of single-cell membrane potentials were also found to enhance stimulus detection performance 82,86 , possibly providing a link between single-cell and population variability.…”

Facial expressions in mice reveal latent cognitive variables and their neural correlates

“…A key step in this direction has been to link facial expressions to controllable and quantifiable variables. Recent examples of this are facial expressions being linked to auditory-evoked responses ( 13 , 14 ) and to arousal state ( 16 , 21 ). Clayton et al 2024 ( 14 ), in particular, showed that facial movement is not only more sensitive to the intensity of auditory stimuli, but also that it reports the spectral and temporal structure of sound.…”

Propagation of activity through the cortical hierarchy and perception are determined by neural variability

“…Other metrics of pre-stimulus neural variability, such as single-cell temporal variance 10 , synchrony 54 and neural oscillation power 15,55 , have all previously been linked to task performance. Although differences and the number of cells targeted by photostimulation defines the probability of a hit trial.…”

“…These include, but are not limited to, direct, monosynaptic transmission from S1 to S2 (ref. 31), indirect paths via other brain regions 60 , brain state changes due to reward consumption 54 , reafference from the whiskers 61 or movement 1 . Thus, although we can make statements about a causal relation, we cannot make any claim about the specific paths or their relative contributions.…”