Pattern Dynamics and Stochasticity of the Brain Rhythms

Authors

Clarissa Hoffman
Jingheng Cheng
Daoyun Ji
Yuri Dabaghian

Language

English

Publication Date

4-4-2023

Journal

Proceedings of the National Academy of Sciences of the United States of America

DOI

10.1073/pnas.2218245120

PMID

36976768

PMCID

PMC10083604

PubMedCentral® Posted Date

3-28-2023

PubMedCentral® Full Text Version

Post-print

Abstract

Our current understanding of brain rhythms is based on quantifying their instantaneous or time-averaged characteristics. What remains unexplored is the actual structure of the waves—their shapes and patterns over finite timescales. Here, we study brain wave patterning in different physiological contexts using two independent approaches: The first is based on quantifying stochasticity relative to the underlying mean behavior, and the second assesses “orderliness” of the waves’ features. The corresponding measures capture the waves’ characteristics and abnormal behaviors, such as atypical periodicity or excessive clustering, and demonstrate coupling between the patterns’ dynamics and the animal’s location, speed, and acceleration. Specifically, we studied patterns of θ, γ, and ripple waves recorded in mice hippocampi and observed speed-modulated changes of the wave’s cadence, an antiphase relationship between orderliness and acceleration, as well as spatial selectiveness of patterns. Taken together, our results offer a complementary—mesoscale—perspective on brain wave structure, dynamics, and functionality.

Keywords

Animals, Mice, Hippocampus, Brain, Brain Waves, Periodicity, Theta Rhythm, patterning, waveforms, hippocampus, learning and memory

Published Open-Access

yes

Recommended Citation

Hoffman, Clarissa; Cheng, Jingheng; Ji, Daoyun; et al., "Pattern Dynamics and Stochasticity of the Brain Rhythms" (2023). Faculty and Staff Publications. 4920.
https://digitalcommons.library.tmc.edu/baylor_docs/4920