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Updated: Jan 10, 2026

Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks

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Brain Entropy: Linking Brain Structure to Task Activation.

Donghui Song^1,2

¹State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing,100091, China.

Biorxiv : the Preprint Server for Biology

|November 24, 2025

Summary

This summary is machine-generated.

Brain entropy (BEN) quantifies brain activity dynamics. This study shows BEN uniquely predicts task activation, independent of brain structure (gray matter volume), highlighting its role as a functional bridge.

Keywords:

Brain entropy Gray matter volume MRI Task activation brain structure and function

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Area of Science:

Neuroscience
Brain Imaging
Computational Neuroscience

Background:

Understanding brain function emergence from structure is a key neuroscience goal.
Brain entropy (BEN) quantifies brain activity dynamics using fMRI.
Prior studies link BEN to brain morphology and task activation, but the structure-function pathway needs clarification.

Purpose of the Study:

To investigate if controlling for gray matter volume (GMV) affects the relationship between BEN and task activation.
To determine if BEN captures unique variance in task activation beyond GMV.

Main Methods:

Replicated prior findings on BEN and GMV relationships with age, sex, and spatial correlations.
Examined correlations between GMV and task activation.
Assessed the BEN-task activation correlation after controlling for GMV across social cognition, reward, and emotion tasks.

Main Results:

Prior findings regarding BEN, GMV, age, sex, and their correlations were successfully replicated.
The relationship between BEN and task activation remained significant after controlling for GMV.
BEN explains unique variance in task activation not accounted for by GMV.

Conclusions:

Brain entropy (BEN) serves as a functional bridge, linking brain structure (GMV) to task activation.
BEN provides insights into brain function beyond structural information alone.
Future research should explore predictive modeling to quantify BEN's added value.