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Structure supports function: Informing directed and dynamic functional connectivity with anatomical priors

Type of publication Peer-reviewed
Publikationsform Original article (peer-reviewed)
Author Pascucci David, Rubega Maria, Rué-Queralt Joan, Tourbier Sebastien, Hagmann Patric, Plomp Gijs,
Project Exploring brain communication pathways by combining diffusion based quantitative structural connectivity and EEG source imaging : application to physiological and epileptic networks
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Original article (peer-reviewed)

Journal Network Neuroscience
Page(s) 1 - 19
Title of proceedings Network Neuroscience
DOI 10.1162/netn_a_00218

Open Access

URL http://doi.org/10.1162/netn_a_00218
Type of Open Access Publisher (Gold Open Access)

Abstract

AbstractThe dynamic repertoire of functional brain networks is constrained by the underlying topology of structural connections. Despite this intrinsic relationship between structural connectivity (SC) and functional connectivity (FC), integrative and multimodal approaches to combine the two remain limited. Here, we propose a new adaptive filter for estimating dynamic and directed FC using structural connectivity information as priors. We tested the filter in rat epicranial recordings and human event-related EEG data, using SC priors from a meta-analysis of tracer studies and diffusion tensor imaging metrics, respectively. We show that, particularly under conditions of low signal-to-noise ratio, SC priors can help to refine estimates of directed FC, promoting sparse functional networks that combine information from structure and function. In addition, the proposed filter provides intrinsic protection against SC-related false negatives, as well as robustness against false positives, representing a valuable new tool for multimodal imaging in the context of dynamic and directed FC analysis.
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