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Related Experiment Video

Updated: Jun 12, 2025

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

Published on: June 27, 2013

Normative Brain Entropy Across the Lifespan.

Gianpaolo Del Mauro¹, Xinglin Zeng¹, Ze Wang¹

¹Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland, United States.

Biorxiv : the Preprint Server for Biology

|June 4, 2025

Summary

This summary is machine-generated.

Brain entropy (BEN), a measure of neural complexity, increases nonlinearly across the human lifespan. This study reveals higher BEN in females compared to males, with consistent patterns observed across brain regions and networks.

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Area of Science:

Neuroscience
Cognitive Science
Biomedical Engineering

Background:

Brain entropy (BEN) reflects neural complexity and irregularity.
BEN shows potential as a marker for cognitive and clinical traits.
Normative lifespan trajectories of BEN are not well understood.

Purpose of the Study:

To investigate age-related changes in brain entropy across the human lifespan.
To model normative growth curves for brain entropy.
To examine sex differences in brain entropy trajectories.

Main Methods:

Utilized resting-state fMRI data from multiple Human Connectome Project cohorts (N = 2,415, ages 8-89).
Estimated brain entropy using Sample Entropy (SampEn).
Modeled normative growth curves with the GAMLSS framework.

Main Results:

Observed a nonlinear increase in average BEN from childhood to older adulthood.
Found significantly higher BEN in females compared to males.
Confirmed similar age-related patterns in regional and network-level analyses.

Conclusions:

Brain entropy exhibits a distinct nonlinear trajectory across the human lifespan.
Sex differences in brain entropy are evident, with females showing higher values.
These findings provide normative BEN trajectories and highlight sex-specific patterns in neural complexity.