Predicting cognitive abilities across individuals using sparse EEG connectivity

Abstract

Human brains share a broadly similar functional organization with consequential individual variation. This duality in brain function has primarily been observed when using techniques that consider the spatial organization of the brain, such as MRI. Here, we ask whether these common and unique signals of cognition are also present in temporally sensitive, but spatially insensitive, neural signals. To address this question, we compiled EEG data from individuals performing multiple working memory tasks at two different data-collection sites (ns = 171 and 165). Results revealed that EEG connectivity patterns were stable within individuals and unique across individuals. Furthermore, models based on these connectivity patterns generalized across datasets to predict participants’ working memory capacity and general fluid intelligence. Thus, EEG connectivity provides a signature of working memory and fluid intelligence in humans and a new framework for characterizing individual differences in cognitive abilities.

Studying the connectome at a large scale

“…While CPM is most commonly applied to fMRI data, connectivity matrices from other modalities can be used, as demonstrated in recent studies using EEG (Hakim et al, 2020;Kabbara et al, 2022).…”