Abstract
The brains of higher organisms are composed of anatomically and functionally distinct regions performing specialised tasks; but regions do not operate in isolation. Orchestration of complex behaviours requires communication between brain regions, but how neural activity dynamics are organised to facilitate reliable transmission is not well understood. We studied this process directly by generating neural activity that propagates between brain regions and drives behaviour, allowing us to assess how populations of neurons in sensory cortex cooperate to transmit information. We achieved this by imaging two hierarchically organised and densely interconnected regions, the primary and secondary somatosensory cortex (S1 and S2) in mice while performing two-photon photostimulation of S1 neurons and assigning behavioural salience to the photostimulation. We found that the probability of perception is determined not only by the strength of the photostimulation signal, but also by the variability of S1 neural activity. Therefore, maximising the signal-to-noise ratio of the stimulus representation in cortex relative to the noise or variability in cortex is critical to facilitate activity propagation and perception. Further, we show that propagated, behaviourally salient activity elicits balanced, persistent, and generalised activation of the downstream region. Hence, our work adds to existing understanding of cortical function by identifying how population activity is formatted to ensure robust transmission of information, allowing specialised brain regions to communicate and coordinate behaviour.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
- Added additional data and analysis using pupil monitoring of behavioural state, showing that population variance is not obviously related to arousal state and that arousal state does not majorly impact behavioural performance on this task (EDF 14). - Added additional analyses that extend our observation of stronger recurrency prior to miss trials from S1 to S2, hinting at a meso-scale change in dynamics (EDF 11). - Added additional analyses with novel measurements of recurrency strength directly estimated from the responses to photostimulation, solidifying our earlier recurrency results (Fig. 5). - Added additional analyses showing that the hit/miss difference in pre-trial activity is not evident in low-dimensional projections of the correlation structure (Fig. 5), directly testing alternative hypotheses regarding how the network state could modulate perception. - Added additional analyses regarding the influence of response time on the dynamics of neural decoding accuracy, in particular to elaborate the comparison between hit trials and reward only trials (EDF 6). - Added additional analyses regarding decoding vectors, specifically considering larger time windows for analysis and quantifying the dynamic change of similarity between different decoding vectors. - Added detailed interpretation of our findings in the Discussion, specifically expanding on the relation to existing theoretical work regarding interareal feedback, the role of inhibition, other metrics of neural variability, and causality of our experiments. - Added additional citations and Discussion. - Streamlined the narrative
