Decoding the Brain’s Surface to Track Deeper Activity

Simple item page
dc.contributor.authorTenzer, Mark L.en
dc.contributor.authorLisinsk, Jonathan M.en
dc.contributor.authorLaConte, Stephen M.en
dc.date.accessioned2023-04-18T17:54:52Zen
dc.date.available2023-04-18T17:54:52Zen
dc.date.issued2022-03-17en
dc.description.abstractNeural activity can be readily and non-invasively recorded from the scalp using electromagnetic and optical signals, but unfortunately all scalp-based techniques have depth-dependent sensitivities. We hypothesize, though, that the cortex’s connectivity with the rest of the brain could serve to construct proxy signals of deeper brain activity. For example, functional magnetic resonance imaging (fMRI)-derived models that link surface connectivity to deeper regions could subsequently extend the depth capabilities of other modalities. Thus, as a first step toward this goal, this study examines whether or not surface-limited support vector regression of resting-state fMRI can indeed track deeper regions and distributed networks in independent data. Our results demonstrate that depth-limited fMRI signals can in fact be calibrated to report ongoing activity of deeper brain structures. Although much future work remains to be done, the present study suggests that scalp recordings have the potential to ultimately overcome their intrinsic physical limitations by utilizing the multivariate information exchanged between the surface and the rest of the brain.en
dc.description.versionPublished versionen
dc.format.extent13 pgen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationTenzer ML, Lisinski JM and LaConte SM (2022) Decoding the Brain’s Surface to Track Deeper Activity. Front. Neuroimaging 1:815778. doi: 10.3389/fnimg.2022.815778en
dc.identifier.doihttps://doi.org/10.3389/fnimg.2022.815778en
dc.identifier.urihttp://hdl.handle.net/10919/114551en
dc.identifier.volume1en
dc.language.isoenen
dc.publisherFrontiers Mediaen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectsupport vector machineen
dc.subjectresting state connectivityen
dc.subjectfunctional magnetic resonance imaging, multimodalen
dc.subjectcerebral cortexen
dc.titleDecoding the Brain’s Surface to Track Deeper Activityen
dc.title.serialFrontiers in Neuroimagingen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
fnimg-01-815778.pdf
Size:
5.68 MB
Format:
Adobe Portable Document Format
Description:
Download

Collections

Open Access Subvention Fund Articles
Scholarly Works, Biomedical Engineering and Mechanics
Scholarly Works, Fralin Biomedical Research Institute at VTC