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Linking structural and effective brain connectivity: structurally informed Parametric Empirical Bayes (si-PEB)

Sokolov, AA; Zeidman, P; Erb, M; Ryvlin, P; Pavlova, MA; Friston, KJ; (2019) Linking structural and effective brain connectivity: structurally informed Parametric Empirical Bayes (si-PEB). Brain Structure and Function , 224 (1) pp. 205-217. 10.1007/s00429-018-1760-8. Green open access

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Abstract

Despite the potential for better understanding functional neuroanatomy, the complex relationship between neuroimaging measures of brain structure and function has confounded integrative, multimodal analyses of brain connectivity. This is particularly true for task-related effective connectivity, which describes the causal influences between neuronal populations. Here, we assess whether measures of structural connectivity may usefully inform estimates of effective connectivity in larger scale brain networks. To this end, we introduce an integrative approach, capitalising on two recent statistical advances: Parametric Empirical Bayes, which provides group-level estimates of effective connectivity, and Bayesian model reduction, which enables rapid comparison of competing models. Crucially, we show that structural priors derived from high angular resolution diffusion imaging on a dynamic causal model of a 12-region network—based on functional MRI data from the same subjects—substantially improve model evidence (posterior probability 1.00). This provides definitive evidence that structural and effective connectivity depend upon each other in mediating distributed, large-scale interactions in the brain. Furthermore, this work offers novel perspectives for understanding normal brain architecture and its disintegration in clinical conditions.

Type: Article
Title: Linking structural and effective brain connectivity: structurally informed Parametric Empirical Bayes (si-PEB)
Location: Germany
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/s00429-018-1760-8
Publisher version: https://doi.org/10.1007/s00429-018-1760-8
Language: English
Additional information: © The Author(s) 2018. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
Keywords: Effective connectivity, Dynamic causal modelling (DCM), Structural connectivity, Functional MRI
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience
URI: https://discovery.ucl.ac.uk/id/eprint/10060142
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