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

Autor:	Pascucci D; Brain Mind Institute, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.; Perceptual Networks Group, University of Fribourg, Fribourg, Switzerland., Rubega M; Department of Neurosciences, University of Padova, Padova, Italy., Rué-Queralt J; Perceptual Networks Group, University of Fribourg, Fribourg, Switzerland.; Connectomics Lab, Department of Radiology, University Hospital of Lausanne and University of Lausanne (CHUV-SUNIL), Lausanne, Switzerland., Tourbier S; Connectomics Lab, Department of Radiology, University Hospital of Lausanne and University of Lausanne (CHUV-SUNIL), Lausanne, Switzerland., Hagmann P; Connectomics Lab, Department of Radiology, University Hospital of Lausanne and University of Lausanne (CHUV-SUNIL), Lausanne, Switzerland., Plomp G; Perceptual Networks Group, University of Fribourg, Fribourg, Switzerland.
Jazyk:	angličtina
Zdroj:	Network neuroscience (Cambridge, Mass.) [Netw Neurosci] 2022 Jun 01; Vol. 6 (2), pp. 401-419. Date of Electronic Publication: 2022 Jun 01 (Print Publication: 2022).
DOI:	10.1162/netn_a_00218
Abstrakt:	The 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. (© 2021 Massachusetts Institute of Technology.)
Databáze:	MEDLINE
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