4.4 Article

Functional Connectivity in Dorsolateral Frontal Cortex: Intracranial Electroencephalogram Study

Journal

BRAIN CONNECTIVITY
Volume 11, Issue 10, Pages 850-864

Publisher

MARY ANN LIEBERT, INC
DOI: 10.1089/brain.2020.0816

Keywords

eloquent cortex; epilepsy; motor system; networks; sample entropy

Categories

Funding

  1. Wilder Family Endowments to the University of Florida

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The study investigates the relationship between brain dynamics and brain networks, revealing a rostrocaudal topography in the EEG presentation over the lateral frontal lobe, consistent with the structural and functional parcellation of the human frontal lobe.
Motivation: Mechanisms underlying the variation in the appearance of electroencephalogram (EEG) over human head are not well characterized. We hypothesized that spatial variation of the EEG, being ultimately linked to variations in cortical neurobiology, was dependent on cortical connectivity patterns. Specifically, we explored the relationship of resting-state functional connectivity derived from intracranial EEG (iEEG) data in seven (N=7) human epilepsy patients with the intrinsic dynamic variability of the local iEEG. We asked whether primary and association brain areas over the lateral frontal lobe-due to their sharply different connectivity patterns-were thus dissociable in EEG space. Methods: Functional connectivity between pairs of subdural grid electrodes was averaged to yield an electrode connectivity (EC) whose time-average yielded mean electrode connectivity (mEC), compared with that electrode's time-averaged sample entropy (SE; mean electrode sample entropy, mESE). Results: We found that mEC and mESE were generally in inverse proportion to each other. Extreme values of mEC and mESE occurred over the Rolandic region and were part of a more general rostrocaudal gradient observed in all patients, with larger (smaller) values of mEC (mESE) occurring anteriorly. Conclusions: Brain networks influence brain dynamics. Over the lateral frontal lobe, mEC and mESE demonstrate a rostrocaudal topography, consistent with current notions regarding the structural and functional parcellation of the human frontal lobe. Our findings distinguish the frontal association cortex from primary sensorimotor cortex, effectively diagnosing Rolandic iEEG independent of the classical mu rhythm associated with the latter brain region.

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