Uncovering the spatiotemporal structure of neural avalanches through optimal transport and dynamic time warping

Summary

Neural avalanches—bursts of coordinated brain activity—are typically studied using scale-free statistics, but their detailed spatiotemporal structure and recurrence have been difficult to analyze due to variability in duration and spatial extent. A new method using flexible alignment with unbalanced optimal transport and subsequence dynamic time warping allows comparison of events of different lengths and configurations. Applied to 64-channel EEG data from 63 participants in the PsiConnect psilocybin study, hierarchical clustering revealed 12 recurring propagation patterns. Under psilocybin, oscillating sequences—those with alternating polarity and spatial propagation—were reduced relative to stable sequences, shifting the balance toward stable patterns. This effect was confirmed by a permutation test and largely driven by one cluster, indicating specific neural dynamics temporally affected by psilocybin.

Study at a glance

Abstract

Neural avalanches - or threshold-defined bursts of coordinated activity - are traditionally characterised by scale-free statistics. However the study of their detailed spatiotemporal structure and their recurrence within spontaneous activity has been hindered by the variability of avalanches in duration and spatial extent. To tackle this challenge, we propose the use of flexible alignment: we employ a distance metric combining unbalanced optimal transport with subsequence dynamic time warping, enabling comparison across events of different lengths and spatial configurations. Applied to 64-channel EEG from 63 participants in the PsiConnect psilocybin study, hierarchical clustering revealed 12 recurring propagation patterns. These cluster templates were then traced in the original continuous recordings, identifying sequences where the same pattern recurred consecutively and immediately at least twice. Sequences with alternating polarity were classified as oscillating; those with consistent polarity as stable. Oscillating sequences predominantly corresponded to clusters exhibiting visually confirmed spatial propagation, while stable sequences corresponded to spatially fixed patterns. Under psilocybin, oscillating sequences were reduced relative to stable sequences, shifting the polarity balance toward stable; this overall shift was confirmed by a subject-level permutation test, while the apparent task- and training-specific effects did not survive it. This effect was also mostly driven by a specific cluster, suggesting that there is concrete neural dynamics that are temporally affected by the consumption of psilocybin. The developed methodology has been implemented in a publicly available stppy Python package.