Abstract
Motor recovery is still limited for people with stroke especially those with greater functional impairments. In order to improve outcome, we need to understand more about the mechanisms underpinning recovery. Task-unbiased, blood-flow independent post-stroke neural activity can be acquired from resting brain electrophysiological recordings, and offers substantial promise to investigate physiological mechanisms, but behaviourally-relevant features of resting-state sensorimotor network dynamics have not yet been identified. Thirty-seven people with subcortical ischemic stroke and unilateral hand paresis of any degree were longitudinally evaluated at 3 weeks (early subacute) and 12 weeks (late subacute) after stroke. Resting-state magnetoencephalography and clinical scores of motor function were recorded and compared with matched controls. Magnetoencephalography data were decomposed using a data-driven Hidden Markov Model into 10 time-varying resting-state networks. People with stroke showed statistically significantly improved Action Research Arm Test and Fugl-Meyer upper extremity scores between 3 weeks and 12 weeks after stroke (both p < 0.001). Hidden Markov Model analysis revealed a primarily alpha-band ipsilesional resting-state sensorimotor network which had a significantly increased life-time (the average time elapsed between entering and exiting the network) and fractional occupancy (the occupied percentage among all networks) at 3 weeks after stroke when compared to controls. The life-time of the ipsilesional resting-state sensorimotor network positively correlated with concurrent motor scores in people with stroke who had not fully recovered. Specifically, this relationship was observed only in ipsilesional rather in contralesional sensorimotor network, default mode network or visual network. The ipsilesional sensorimotor network metrics were not significantly different from controls at 12 weeks after stroke. The increased recruitment of alpha-band ipsilesional resting-state sensorimotor network at subacute stroke served as functionally correlated biomarkers exclusively in people with stroke with not fully recovered hand paresis, plausibly reflecting functional motor recovery processes.
Original language | English |
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Article number | fcae011 |
Journal | Brain Communications |
Early online date | 23 Jan 2024 |
DOIs | |
Publication status | E-pub ahead of print - 23 Jan 2024 |
Bibliographical note
Funding:This work was supported by the Taiwan Ministry of Science and Technology (MOST, 106-2314-B-075-019-MY3, 107-2634-F-008-003, 108-2634-F-008-003, 109-2314-B-418-008), the Taipei Veterans General Hospital (V106C-023, V107C-064, V108C-052), the Far Eastern Memorial Hospital (FEMH-2014-C-018, FEMH-2015-C-025, FEMH-2021-003), the Taiwan Ministry of Education (Academic Strategic Alliance Project between Taiwan and Oxford University), and the National Yang Ming Chiao Tung University (Brain Research Center, from the Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Taiwan Ministry of Education). CJS holds a Senior Research Fellowship, funded by the Wellcome Trust (224430/Z/21/Z)
Keywords
- stroke
- motor recovery
- magnetoencephalography
- Hidden Markov Model