Uncovering Neural Dynamics in Mild Cognitive Impairment with Graph-based Synchrony and Permutation Entropy

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Sequeira, Melody N. and Campbell-Cousins, Avalon and Gonzalez-Montealegre, Rodrigo A. and González Hernández, Alfredis and Bonilla-Santos, Jasmin and Parra Rodriguez, Mario and Escudero, Javier (2026) Uncovering Neural Dynamics in Mild Cognitive Impairment with Graph-based Synchrony and Permutation Entropy. In: IEEE Engineering in Medicine and Biology Society, 2026-07-26 - 2026-07-30. (In Press)

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Abstract

Mild cognitive impairment (MCI) is an transitional state between healthy ageing and dementia. Electroencephalography (EEG) is a non-invasive and cost-effective tool that measures brain activity during cognitive processes. Here, we analyse EEG signals from individuals with MCI and healthy controls to detect subtle differences in neural dynamics using graph-based synchrony and permutation entropy (PEG). Source-reconstructed EEG from a binding task was used to build weighted phase lag index networks during task encoding and recall in the theta and alpha band. Individuals with MCI exhibited increased global and nodal synchrony during recall. Ordinal pattern distributions derived from PEG differed significantly across task phases, with MCI showing a higher prevalence of monotonic temporal patterns. Synchrony– PEG coupling was weaker and less phase dependent in MCI. The findings highlight the complementary value of graph-based EEG analyses to uncover neural signatures, supporting an accessible avenue for early identification of individuals at risk of dementia.

ORCID iDs

Sequeira, Melody N., Campbell-Cousins, Avalon, Gonzalez-Montealegre, Rodrigo A., González Hernández, Alfredis, Bonilla-Santos, Jasmin, Parra Rodriguez, Mario ORCID logoORCID: https://orcid.org/0000-0002-2412-648X and Escudero, Javier;
CORE (COnnecting REpositories)