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Updated: Jun 7, 2025

Electroencephalography Network Indices as Biomarkers of Upper Limb Impairment in Chronic Stroke
Published on: July 14, 2023
Body ownership alterations in stroke emerge from reduced proprioceptive precision and damage to the frontoparietal
Giulio Mastria1, Tommaso Bertoni1, Henri Perrin1
1MySpace Lab, Department of Clinical Neurosciences, Lausanne University Hospital, University of Lausanne, 1011 Lausanne, Switzerland.
Background:
Stroke patients often experience alterations in their subjective feeling of ownership for the affected limb, which can hinder motor function and interfere with rehabilitation. In this study, we aimed at disentangling the complex relationship between sensory impairment, body ownership (BO), and motor control in stroke patients.
Methods:
We recruited 20 stroke patients with unilateral upper limb sensory deficits and 35 age-matched controls. Participants performed a virtual reality reaching task with a varying displacement between their real unseen hand and a visible virtual hand. We measured reaching errors and subjective ownership ratings as indicators of hand ownership. Reaching errors were modeled using a probabilistic causal inference model, in which ownership for the virtual hand is inferred from the level of congruency between visual and proprioceptive inputs and used to weigh the amount of visual adjustment to reaching movements.
Findings:
Stroke patients were more likely to experience ownership over an incongruent virtual hand and integrate it into their motor plans. The model explained this tendency in terms of a decreased capability of detecting visuo-proprioceptive incongruences, proportionally to the amount of proprioceptive deficit. Lesion analysis further revealed that BO alterations, not fully explained by the proprioceptive deficit, are linked to frontoparietal network damage, suggesting a disruption in higher-level multisensory integration functions.
Conclusions:
Collectively, our results show that BO alterations in stroke patients can be quantitatively predicted and explained in a computational framework as the result of sensory loss and higher-level multisensory integration deficits.
Funding:
Swiss National Science Foundation (163951).
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