Ting, C-M;
Skipper, JI;
Noman, F;
Small, SL;
Ombao, H;
(2021)
Separating Stimulus-Induced and Background Components of Dynamic Functional Connectivity in Naturalistic fMRI.
IEEE Transactions on Medical Imaging
10.1109/TMI.2021.3139428.
(In press).
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Abstract
We consider the challenges in extracting stimulus-related neural dynamics from other intrinsic processes and noise in naturalistic functional magnetic resonance imaging (fMRI). Most studies rely on inter-subject correlations (ISC) of low-level regional activity and neglect varying responses in individuals. We propose a novel, data-driven approach based on low-rank plus sparse (L+S) decomposition to isolate stimulus-driven dynamic changes in brain functional connectivity (FC) from the background noise, by exploiting shared network structure among subjects receiving the same naturalistic stimuli. The time-resolved multi-subject FC matrices are modeled as a sum of a low-rank component of correlated FC patterns across subjects, and a sparse component of subject-specific, idiosyncratic background activities. To recover the shared low-rank subspace, we introduce a fused version of principal component pursuit (PCP) by adding a fusion-type penalty on the differences between the columns of the low-rank matrix. The method improves the detection of stimulus-induced group-level homogeneity in the FC profile while capturing inter-subject variability. We develop an efficient algorithm via a linearized alternating direction method of multipliers to solve the fused-PCP. Simulations show accurate recovery by the fused-PCP even when a large fraction of FC edges are severely corrupted. When applied to natural fMRI data, our method reveals FC changes that were time-locked to auditory processing during movie watching, with dynamic engagement of sensorimotor systems for speech-in-noise. It also provides a better mapping to auditory content in the movie than ISC.
| Type: | Article |
|---|---|
| Title: | Separating Stimulus-Induced and Background Components of Dynamic Functional Connectivity in Naturalistic fMRI |
| Location: | United States |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/TMI.2021.3139428 |
| Publisher version: | https://doi.org/10.1109/TMI.2021.3139428 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Low-rank plus sparse decomposition, dynamic functional connectivity, inter-subject correlation, fMRI |
| UCL classification: | UCL 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 > Div of Psychology and Lang Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Experimental Psychology |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10141806 |
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