Brain criticality through nonadditive entropic analysis of electroencephalograms

TL;DR

This study uses nonadditive entropy analysis of EEG data to reveal critical brain behavior and higher complexity in ADHD children, suggesting potential biomarkers for psychiatric diagnosis.

Contribution

It demonstrates that nonadditive entropic analysis can identify criticality and increased complexity in ADHD brain activity through EEG data.

Findings

$q$ varies monotonically with $eta$ indicating critical brain behavior

ADHD subjects exhibit higher brain complexity than typical subjects

Potential biomarkers for psychiatric diagnosis identified through entropic analysis

Abstract

On the grounds of nonadditive entropies -- appropriate for complex systems -- we investigate the electroencephalogram amplitudes of typical and ADHD children. The corresponding probability distributions are $q$-Gaussians, i.e., $\rho(x) \propto e_q^{-\beta x^2} \equiv [1+(q-1) \beta x^2]^{1/(1-q)}$, where $(q,\beta)$ are, respectively, the entropic index characterizing complexity and the inverse width. We show that $q$ tends to monotonically vary with $\beta$ for both typical and ADHD subjects, thus revealing critical behavior of the brain. Moreover, we verify that ADHD subjects have a higher complexity than the typical ones. Consistently, biomarkers for objective phychyatric diagnosis could emerge along this path. We show that $q$ tends to monotonically vary with $\beta$ for both typical and ADHD subjects, thus revealing critical behavior of the brain. Moreover, we verify that ADHD subjects have a higher complexity than the typical ones. Consistently, biomarkers for objective phychyatric diagnosis could emerge along this path.