Using fMRI to localize target regions for implanted brain-computer interfaces in locked-in syndrome.
Brain-computer interface
Electrocorticography
Implant
Locked-in syndrome
fMRI
Journal
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
ISSN: 1872-8952
Titre abrégé: Clin Neurophysiol
Pays: Netherlands
ID NLM: 100883319
Informations de publication
Date de publication:
Nov 2023
Nov 2023
Historique:
received:
10
02
2023
revised:
29
06
2023
accepted:
09
08
2023
pubmed:
2
9
2023
medline:
2
9
2023
entrez:
1
9
2023
Statut:
ppublish
Résumé
Electrocorticography (ECoG)-based brain-computer interface (BCI) systems have the potential to improve quality of life of people with locked-in syndrome (LIS) by restoring their ability to communicate independently. Before implantation of such a system, it is important to localize ECoG electrode target regions. Here, we assessed the predictive value of functional magnetic resonance imaging (fMRI) for the localization of suitable target regions on the sensorimotor cortex for ECoG-based BCI in people with locked-in syndrome. Three people with locked-in syndrome were implanted with a chronic, fully implantable ECoG-BCI system. We compared pre-surgical fMRI activity with post-implantation ECoG activity from areas known to be active and inactive during attempted hand movement (sensorimotor hand region and dorsolateral prefrontal cortex, respectively). Results showed a spatial match between fMRI activity and changes in ECoG low and high frequency band power (10 - 30 and 65 - 95 Hz, respectively) during attempted movement. Also, we found that fMRI can be used to select a sub-set of electrodes that show strong task-related signal changes that are therefore likely to generate adequate BCI control. Our findings indicate that fMRI is a useful non-invasive tool for the pre-surgical workup of BCI implant candidates. If these results are confirmed in more BCI studies, fMRI might be used for more efficient surgical BCI procedures with focused cortical coverage and lower participant burden.
Identifiants
pubmed: 37657190
pii: S1388-2457(23)00700-9
doi: 10.1016/j.clinph.2023.08.003
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1-15Informations de copyright
Copyright © 2023 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Interest NFR is co-founder and director at Braincarta, which specializes in off-the-shelf fMRI software for clinical assessment of brain anatomy and functioning. Braincarta software was not used for the analyses described in this manuscript. The authors report no other competing interests.