Assessing spatiotemporal variability of brain spontaneous activity by multiscale entropy and functional connectivity

Mianxin Liu, Chenchen Song, Yuqi Liang, Thomas Knöpfel*, Changsong ZHOU

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

25 Citations (Scopus)


Brain signaling occurs across a wide range of spatial and temporal scales, and analysis of brain signal variability and synchrony has attracted recent attention as markers of intelligence, cognitive states, and brain disorders. However, current technologies to measure brain signals in humans have limited resolutions either in space or in time and cannot fully capture spatiotemporal variability, leaving it untested whether temporal variability and spatiotemporal synchrony are valid and reliable proxy of spatiotemporal variability in vivo. Here we used optical voltage imaging in mice under anesthesia and wakefulness to monitor cortical voltage activity at both high spatial and temporal resolutions to investigate functional connectivity (FC, a measure of spatiotemporal synchronization), Multi-Scale Entropy (MSE, a measure of temporal variability), and their relationships to Regional Entropy (RE, a measure of spatiotemporal variability). We observed that across cortical space, MSE pattern can largely explain RE pattern at small and large temporal scales with high positive and negative correlation respectively, while FC pattern strongly negatively associated with RE pattern. The time course of FC and small scale MSE tightly followed that of RE, while large scale MSE was more loosely coupled to RE. fMRI and EEG data simulated by reducing spatiotemporal resolution of the voltage imaging data or considering hemodynamics yielded MSE and FC measures that still contained information about RE based on the high resolution voltage imaging data. This suggested that MSE and FC could still be effective measures to capture spatiotemporal variability under limitation of imaging modalities applicable to human subjects. Our results support the notion that FC and MSE are effective biomarkers for brain states, and provide a promising viewpoint to unify these two principal domains in human brain data analysis.

Original languageEnglish
Pages (from-to)198-220
Number of pages23
Publication statusPublished - Sept 2019

Scopus Subject Areas

  • Neurology
  • Cognitive Neuroscience

User-Defined Keywords

  • Brain signal variability
  • Cortical circuit dynamics
  • Functional connectivity
  • Multiscale entropy
  • Optical voltage imaging


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