EMG-projected MEG high-resolution source imaging of human motor execution: Brain-muscle coupling above movement frequencies.

corticokinematic coupling corticomuscular coupling electromyography magnetoencephalography primary motor theta band

Journal

Imaging neuroscience (Cambridge, Mass.)
ISSN: 2837-6056
Titre abrégé: Imaging Neurosci (Camb)
Pays: United States
ID NLM: 9918663686606676

Informations de publication

Date de publication:
01 Jan 2024
Historique:
received: 23 06 2023
revised: 29 11 2023
accepted: 30 11 2023
medline: 18 9 2024
pubmed: 18 9 2024
entrez: 18 9 2024
Statut: epublish

Résumé

Magnetoencephalography (MEG) is a non-invasive functional imaging technique for pre-surgical mapping. However, movement-related MEG functional mapping of primary motor cortex (M1) has been challenging in presurgical patients with brain lesions and sensorimotor dysfunction due to the large numbers of trials needed to obtain adequate signal to noise. Moreover, it is not fully understood how effective the brain communication is with the muscles at frequencies above the movement frequency and its harmonics. We developed a novel Electromyography (EMG)-projected MEG source imaging technique for localizing early-stage (-100 to 0 ms) M1 activity during ~l min recordings of left and right self-paced finger movements (~1 Hz). High-resolution MEG source images were obtained by projecting M1 activity towards the skin EMG signal without trial averaging. We studied delta (1-4 Hz), theta (4-7 Hz), alpha (8-12 Hz), beta (15-30 Hz), gamma (30-90 Hz), and upper-gamma (60-90 Hz) bands in 13 healthy participants (26 datasets) and three presurgical patients with sensorimotor dysfunction. In healthy participants, EMG-projected MEG accurately localized M1 with high accuracy in delta (100.0%), theta (100.0%), and beta (76.9%) bands, but not alpha (34.6%) or gamma/upper-gamma (0.0%) bands. Except for delta, all other frequency bands were above the movement frequency and its harmonics. In three presurgical patients, M1 activity in the affected hemisphere was also accurately localized, despite highly irregular EMG movement patterns in one patient. Altogether, our EMG-projected MEG imaging approach is highly accurate and feasible for M1 mapping in presurgical patients. The results also provide insight into movement-related brain-muscle coupling above the movement frequency and its harmonics.

Identifiants

pubmed: 39290632
doi: 10.1162/imag_a_00056
pii: imag_a_00056
pmc: PMC11403128
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1-20

Informations de copyright

© 2023 Massachusetts Institute of Technology. Published under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.

Déclaration de conflit d'intérêts

All authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Ming-Xiong Huang (MX)

Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, United States.
Department of Radiology, University of California, San Diego, CA, United States.
Department of Electrical and Computer Engineering, University of California, San Diego, CA, United States.

Deborah L Harrington (DL)

Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, United States.
Department of Radiology, University of California, San Diego, CA, United States.

Annemarie Angeles-Quinto (A)

Department of Radiology, University of California, San Diego, CA, United States.

Zhengwei Ji (Z)

Department of Radiology, University of California, San Diego, CA, United States.

Ashley Robb-Swan (A)

Department of Radiology, University of California, San Diego, CA, United States.

Charles W Huang (CW)

Department of Bioengineering, Stanford University, Stanford, CA, United States.

Qian Shen (Q)

Department of Radiology, University of California, San Diego, CA, United States.

Hayden Hansen (H)

Department of Radiology, University of California, San Diego, CA, United States.

Jared Baumgartner (J)

Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, United States.

Jaqueline Hernandez-Lucas (J)

Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, United States.

Sharon Nichols (S)

Department of Neurosciences, University of California, San Diego, CA, United States.

Joanna Jacobus (J)

Department of Psychiatry, University of California, San Diego, CA, United States.

Tao Song (T)

Department of Radiology, University of California, San Diego, CA, United States.

Imanuel Lerman (I)

Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, United States.

Maksim Bazhenov (M)

Department of Medicine, University of California, San Diego, CA, United States.

Giri P Krishnan (GP)

Department of Medicine, University of California, San Diego, CA, United States.

Dewleen G Baker (DG)

Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, United States.
Department of Psychiatry, University of California, San Diego, CA, United States.
VA Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, United States.

Ramesh Rao (R)

Department of Electrical and Computer Engineering, University of California, San Diego, CA, United States.

Roland R Lee (RR)

Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, United States.
Department of Radiology, University of California, San Diego, CA, United States.

Classifications MeSH