Brain Aperiodic Dynamics
10.16476/j.pibb.2024.0254
- VernacularTitle:大脑非周期动力学
- Author:
Zhi-Cai HU
1
;
Zhen ZHANG
1
;
Jiang WANG
1
;
Gui-Ping LI
2
;
Shan LIU
1
;
Hai-Tao YU
1
Author Information
1. School of Electrical and Information Engineering, Tianjin University, Tianjin300072, China
2. The First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin300193, China
- Publication Type:Journal Article
- Keywords:
aperiodic brain activity;
neural dynamics;
aperiodic exponent;
biomarker
- From:
Progress in Biochemistry and Biophysics
2025;52(1):99-118
- CountryChina
- Language:Chinese
-
Abstract:
Brain’s neural activities encompass both periodic rhythmic oscillations and aperiodic neural fluctuations. Rhythmic oscillations manifest as spectral peaks of neural signals, directly reflecting the synchronized activities of neural populations and closely tied to cognitive and behavioral states. In contrast, aperiodic fluctuations exhibit a power-law decaying spectral trend, revealing the multiscale dynamics of brain neural activity. In recent years, researchers have made notable progress in studying brain aperiodic dynamics. These studies demonstrate that aperiodic activity holds significant physiological relevance, correlating with various physiological states such as external stimuli, drug induction, sleep states, and aging. Aperiodic activity serves as a reflection of the brain’s sensory capacity, consciousness level, and cognitive ability. In clinical research, the aperiodic exponent has emerged as a significant potential biomarker, capable of reflecting the progression and trends of brain diseases while being intricately intertwined with the excitation-inhibition balance of neural system. The physiological mechanisms underlying aperiodic dynamics span multiple neural scales, with activities at the levels of individual neurons, neuronal ensembles, and neural networks collectively influencing the frequency, oscillatory patterns, and spatiotemporal characteristics of aperiodic signals. Aperiodic dynamics currently boasts broad application prospects. It not only provides a novel perspective for investigating brain neural dynamics but also holds immense potential as a neural marker in neuromodulation or brain-computer interface technologies. This paper summarizes methods for extracting characteristic parameters of aperiodic activity, analyzes its physiological relevance and potential as a biomarker in brain diseases, summarizes its physiological mechanisms, and based on these findings, elaborates on the research prospects of aperiodic dynamics.
