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How Can I Analyze Large-Scale Intrinsic Functional Networks with iEEG? - Chapter 33
Book chapter   Open access

How Can I Analyze Large-Scale Intrinsic Functional Networks with iEEG? - Chapter 33

Aaron Kucyi and Sepideh Sadaghiani
01 Jan 2023
DOI: https://doi.org/10.1007/978-3-031-20910-9_33
url
https://psyarxiv.com/tmvwf/View
SubmittedCC BY V4.0,  Open

Abstract

An intrinsic functional brain network is a set of discrete, spatial elements that exhibit statistically dependent activity (“functional connectivity”) with each other in a largely state-invariant manner (e.g. across wakeful rest, task performance, and sleep). Large-scale intrinsic networks—involving coupling between distant brain regions—were initially discovered with human functional neuroimaging (fMRI) based on hemodynamic signals. Though fMRI studies suggest critical relevance of these networks to brain function, findings remain challenging to interpret given the low temporal resolution and indirect nature of fMRI. Human iEEG is poised as a unique method that can deliver fundamental insights into the neurophysiological connectivity processes in intrinsic networks. In this chapter, we review iEEG analysis methods that have been used to identify electrophysiological networks closely resembling those found using classical fMRI functional connectivity. We focus on amplitude and phase coupling within multiple frequency bands as measures of iEEG intrinsic connectivity. We review evidence that iEEG connectivity shows state-invariant patterns of inter-regional coupling across multiple contexts. Moreover, we review applications of intrinsic iEEG connectivity patterns in predicting the roles of discrete neuronal populations in cognitive function. Finally, we explore how iEEG sheds light on the cognitive relevance of temporal dynamics within and between intrinsic networks.

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