Structured sparse multiset canonical correlation analysis of simultaneous fNIRS and EEG provides new insights into the human action‑observation network

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dc.contributor.authorDashtestani, Hadis
dc.contributor.authorMiguel, Helga O.
dc.contributor.authorCondy, Emma E.
dc.contributor.authorZeytinoglu, Selin
dc.contributor.authorMillerhagen, John B.
dc.contributor.authorDebnath, Ranjan
dc.contributor.authorSmith, Elizabeth
dc.contributor.authorAdali, Tulay
dc.contributor.authorFox, Nathan A.
dc.contributor.authorGandjbakhche, Amir H.
dc.date.accessioned2022-06-21T21:34:38Z
dc.date.available2022-06-21T21:34:38Z
dc.date.issued2022-04-27
dc.description.abstractThe action observation network (AON) is a network of brain regions involved in the execution and observation of a given action. The AON has been investigated in humans using mostly electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI), but shared neural correlates of action observation and action execution are still unclear due to lack of ecologically valid neuroimaging measures. In this study, we used concurrent EEG and functional Near Infrared Spectroscopy (fNIRS) to examine the AON during a live-action observation and execution paradigm. We developed structured sparse multiset canonical correlation analysis (ssmCCA) to perform EEG-fNIRS data fusion. MCCA is a generalization of CCA to more than two sets of variables and is commonly used in medical multimodal data fusion. However, mCCA suffers from multi-collinearity, high dimensionality, unimodal feature selection, and loss of spatial information in interpreting the results. A limited number of participants (small sample size) is another problem in mCCA, which leads to overfitted models. Here, we adopted graph-guided (structured) fused least absolute shrinkage and selection operator (LASSO) penalty to mCCA to conduct feature selection, incorporating structural information amongst the variables (i.e., brain regions). Benefitting from concurrent recordings of brain hemodynamic and electrophysiological responses, the proposed ssmCCA finds linear transforms of each modality such that the correlation between their projections is maximized. Our analysis of 21 right-handed participants indicated that the left inferior parietal region was active during both action execution and action observation. Our findings provide new insights into the neural correlates of AON which are more fine-tuned than the results from each individual EEG or fNIRS analysis and validate the use of ssmCCA to fuse EEG and fNIRS datasets.en_US
dc.description.sponsorshipThe present study was supported by the Intramural Research Program (IRP) of the National Institute of Child Health and Human Development (Project Number: 1ZIAHD008882-10) and the National Institute of Health’s Bench-to-Bedside Program. Open Access funding provided by the National Institutes of Health (NIH).en_US
dc.description.urihttps://www.nature.com/articles/s41598-022-10942-1en_US
dc.format.extent13 pagesen_US
dc.genrejournal articlesen_US
dc.identifierdoi:10.13016/m2o8m9-u0zw
dc.identifier.citationDashtestani, H., Miguel, H.O., Condy, E.E. et al. Structured sparse multiset canonical correlation analysis of simultaneous fNIRS and EEG provides new insights into the human action-observation network. Sci Rep 12, 6878 (2022). https://doi.org/10.1038/s41598-022-10942-1en_US
dc.identifier.urihttps://doi.org/10.1038/s41598-022-10942-1
dc.identifier.urihttp://hdl.handle.net/11603/25012
dc.language.isoen_USen_US
dc.publisherNatureen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.rightsThis work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.en_US
dc.rightsPublic Domain Mark 1.0*
dc.rights.urihttp://creativecommons.org/publicdomain/mark/1.0/*
dc.titleStructured sparse multiset canonical correlation analysis of simultaneous fNIRS and EEG provides new insights into the human action‑observation networken_US
dc.typeTexten_US
dcterms.creatorhttps://orcid.org/0000-0003-0594-2796en_US

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