# Relative timing and coupling of neural population bursts in large-scale recordings from multiple neuron populations

## TL;DR

This paper introduces a fast and accurate method to analyze the timing of neural bursts across brain regions in response to stimuli, revealing both consistent and individual-specific patterns in mice.

## Contribution

A novel analytical framework for estimating population burst timing and coupling that is faster and easier to apply than existing methods.

## Key findings

- The method accurately estimates burst timing and coupling across brain regions in simulated and real data.
- It revealed consistent and variable timing relationships across mice in visual cortical areas.
- The approach captures both shared and individual-specific patterns of population burst propagation.

## Abstract

The onset of a sensory stimulus elicits transient bursts of activity in neural populations, which are presumed to convey information about the stimulus to downstream populations. Although the timing at which these synchronized bursts reach their peak is highly variable across stimulus presentations, the relative timing of bursts across interconnected brain regions may be less variable, particularly for regions that are strongly functionally coupled.

We developed a simple analytical framework that provides accurate trial-by-trial estimates of population burst times and of the correlations in the timing of evoked population bursts across areas. The method was evaluated using simulated data and compared to a recently published alternative model. We then applied the approach to large-scale Neuropixels recordings from six cortical visual areas and one visual thalamic nucleus in thirteen mice presented with drifting grating stimuli.

Our method performed well on simulated data and was 85–90% faster than the alternative model while being substantially easier to apply. Applied to real data, the approach enabled identification of mouse-to-mouse variation in both peak times and region-to-region functional coupling for the first two population bursts following stimulus onset. The observed timing relationships were consistent with known anatomy and physiology.

Examining sequences of activity across areas revealed that some timing relationships were preserved across all mice, while others varied across individuals. These findings demonstrate that the general approach can produce sensitive, trial-resolved analyses of timing relationships across neural populations and can capture both shared and individual-specific patterns of population burst propagation.