Precise modeling of task-related sensorimotor activation based on simultaneous surface electromyography
6 affiliations
- 1Department of Neurology, Faculty of Medicine and Dentistry, Palacký University Olomouc, Olomouc, Czechia; Department of Biomedical Engineering, University Hospital Olomouc, Olomouc, Czechia
- 2Department of Neurology, Faculty of Medicine and Dentistry, Palacký University Olomouc, Olomouc, Czechia; Behavioural and Social Neuroscience, CEITEC – Central European Institute of Technology, Masaryk University, Brno, Czechia; Corresponding author at: Department of Neurology, Faculty of Medicine and Dentistry, Palacký University Olomouc, Zdravotníků 248/7, 779 00 Olomouc, Czechia.
- 3Multimodal and Functional Imaging Laboratory, CEITEC – Central European Institute of Technology, Masaryk University, Brno, Czechia
- 4Department of Rehabilitation, University Hospital Olomouc, Olomouc, Czechia
- 5Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia
- 6Department of Neurology, University Hospital Olomouc, Olomouc, Czechia
Abstract
The aim of this study was to evaluate the relationship between motor control of ankle movements and actual motor performance using simultaneous functional magnetic resonance imaging (fMRI) and surface electromyography (EMG) in healthy individuals. Twenty participants performed dorsi-/plantarflexion of the ankle (Ankle) and gait imagery in a block design during fMRI. First-level models consisting of task regressors included either orthogonalized accelerometry (Acc) from the foot, EMG from the tibialis anterior, EMG with Acc, EMG split across conditions, or none. Each model was additionally evaluated either by default with or without a temporal derivative (TD) of the ankle movement task regressor. Voxel-wise and post-hoc region-of-interest (ROI) analyses revealed that both Acc and EMG explained fMRI signal in the primary sensorimotor cortices, while EMG was additionally associated with activation in the cerebellar vermis and the secondary somatosensory cortex. The two latter findings were, however, neither reproduced when separating the signal fluctuations during rest and gait imagery nor reflected in pairwise comparisons. Leaving out the TD reduced each model’s performance by increasing unexplained variance, but resulted in more signal being explained by the EMG or Acc in the cerebellum, reflecting that it preferentially exhibited brief signal changes during transitions between conditions. Taken together, both EMG and Acc enabled capturing specific brain activity related to the movement variability; however, including the TD may significantly affect the ability to detect EMG- or Acc-related signal in regions with transient fMRI responses sensitive to changes in movement context, such as the cerebellum.
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BibTeX
@article{jasenska2026precise,
title = {{Precise modeling of task-related sensorimotor activation based on simultaneous surface electromyography}},
author = {Monika Jasenská and Pavel Hok and Martin Kojan and Ondřej Burkot and Barbora Kolářová and Aleš Holobar and Petr Hluštík},
journal = {NeuroImage},
year = {2026},
month = oct,
doi = {10.1016/j.neuroimage.2026.122300},
url = {https://doi.org/10.1016/j.neuroimage.2026.122300},
note = {CC BY},
}
RIS
TY - JOUR
TI - Precise modeling of task-related sensorimotor activation based on simultaneous surface electromyography
AU - Monika Jasenská
AU - Pavel Hok
AU - Martin Kojan
AU - Ondřej Burkot
AU - Barbora Kolářová
AU - Aleš Holobar
AU - Petr Hluštík
PY - 2026
DA - 2026/10/30
JO - NeuroImage
DO - 10.1016/j.neuroimage.2026.122300
UR - https://doi.org/10.1016/j.neuroimage.2026.122300
AB - The aim of this study was to evaluate the relationship between motor control of ankle movements and actual motor performance using simultaneous functional magnetic resonance imaging (fMRI) and surface electromyography (EMG) in healthy individuals. Twenty participants performed dorsi-/plantarflexion of the ankle (Ankle) and gait imagery in a block design during fMRI. First-level models consisting of task regressors included either orthogonalized accelerometry (Acc) from the foot, EMG from the tibialis anterior, EMG with Acc, EMG split across conditions, or none. Each model was additionally evaluated either by default with or without a temporal derivative (TD) of the ankle movement task regressor. Voxel-wise and post-hoc region-of-interest (ROI) analyses revealed that both Acc and EMG explained fMRI signal in the primary sensorimotor cortices, while EMG was additionally associated with activation in the cerebellar vermis and the secondary somatosensory cortex. The two latter findings were, however, neither reproduced when separating the signal fluctuations during rest and gait imagery nor reflected in pairwise comparisons. Leaving out the TD reduced each model’s performance by increasing unexplained variance, but resulted in more signal being explained by the EMG or Acc in the cerebellum, reflecting that it preferentially exhibited brief signal changes during transitions between conditions. Taken together, both EMG and Acc enabled capturing specific brain activity related to the movement variability; however, including the TD may significantly affect the ability to detect EMG- or Acc-related signal in regions with transient fMRI responses sensitive to changes in movement context, such as the cerebellum.
SN - 1095-9572
SN - 1053-8119
ER -