Mapping and decoding cortical engagement during motor imagery, mental arithmetic, and silent word generation using MEG

Vahab Youssofzadeh, Sujit Roy, Anirban Chowdhury, Aqil Izadysadr, Lauri Parkkonen, Manoj Raghavan, Girijesh Prasad

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)
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Accurate quantification of cortical engagement during mental imagery tasks remains a challenging brain-imaging problem with immediate relevance to developing brain–computer interfaces. We analyzed magnetoencephalography (MEG) data from 18 individuals completing cued motor imagery, mental arithmetic, and silent word generation tasks. Participants imagined movements of both hands (HANDS) and both feet (FEET), subtracted two numbers (SUB), and silently generated words (WORD). The task-related cortical engagement was inferred from beta band (17–25 Hz) power decrements estimated using a frequency-resolved beamforming method. In the hands and feet motor imagery tasks, beta power consistently decreased in premotor and motor areas. In the word and subtraction tasks, beta-power decrements showed engagements in language and arithmetic processing within the temporal, parietal, and inferior frontal regions. A support vector machine classification of beta power decrements yielded high accuracy rates of 74 and 68% for classifying motor-imagery (HANDS vs. FEET) and cognitive (WORD vs. SUB) tasks, respectively. From the motor-versus-nonmotor contrasts, excellent accuracy rates of 85 and 80% were observed for hands-versus-word and hands-versus-sub, respectively. A multivariate Gaussian-process classifier provided an accuracy rate of 60% for the four-way (HANDS-FEET-WORD-SUB) classification problem. Individual task performance was revealed by within-subject correlations of beta-decrements. Beta-power decrements are helpful metrics for mapping and decoding cortical engagement during mental processes in the absence of sensory stimuli or overt behavioral outputs. Markers derived based on beta decrements may be suitable for rehabilitation purposes, to characterize motor or cognitive impairments, or to treat patients recovering from a cerebral stroke.
Original languageEnglish
Pages (from-to)3324-3342
Number of pages20
JournalHuman Brain Mapping
Issue number8
Early online date29 Mar 2023
Publication statusPublished online - 29 Mar 2023

Bibliographical note

Funding Information:
This work is in part supported by the UKIERI Thematic Partnership project, “Advancing MEG‐based Brain‐computer Interface Supported Upper Limb Post‐Stroke Rehabilitation” (DST‐UKIERI‐2016‐17‐0128), and the Northern Ireland Functional Brain Mapping Facility project (1303/101154803), funded by InvestNI and Ulster University.

Publisher Copyright:
© 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.


  • Magnetoencephalography
  • Beta-decrements
  • Brain-computer interface
  • Task imagery
  • Classification
  • beta-decrements
  • brain–computer interface
  • classification
  • magnetoencephalography
  • task imagery


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