Motor synergy patterns are recognized as physiological markers of motor cortical damage, providing insights into how motor cortex coordinates spinal motor modules to generate movements. However, how these patterns adapt to tasks of varying complexity following post-stroke cortical damage is not yet fully understood. We aimed to understand how motor synergy patterns are distorted across tasks of increasing complexity after stroke induced cortical damage, also to provide a reference for task selection when using muscle synergy patterns as biomarkers for stroke evaluation or intervention. This was a pilot, cross sectional study. We investigated muscle synergies during five tasks with varying complexity in 20 healthy individuals (13 females and 7 males, aged 64.33 ± 6.94 years) and in 12 participants with chronic stroke (4 females and 8 males, aged 64.4 ± 6.54 years). Surface electromyographic activities were recorded from 16 upper limb muscles (8 muscles per limb: upper/lower trapezius, anterior/posterior deltoid, triceps brachii lateral head, biceps brachii short head, flexor digitorum superficialis, and extensor digitorum communis). Non-negative matrix factorization was performed to extract the muscle synergies. We categorized the stroke-induced synergy plasticity based on healthy synergy centroids, compared the synergy plasticity between affected and unaffected limbs, and investigated the correlation between synergy plasticity and patient’s motor function, In healthy individuals, the number of muscle synergies exhibited a U-shaped pattern as task complexity increased, whereas in stroke patients, both the affected and unaffected limbs showed a decreasing trend in muscle synergy number with increasing task complexity. Besides, the unaffected arm exhibited significantly more preservation synergies (synergies resembling healthy patterns) than the affected arm in moderate (Placing 30 cm: Z(11) = -2.144, corrected p = 0.031, Rosenthal’s r = -0.646) and high complexity tasks (Z(11) = -2.558, corrected p = 0.028, Rosenthal’s r = -0.771), and fewer mutation synergies (synergies deviating from healthy patterns) with marginal significance (Placing 30 cm: Z(11) = -1.992, corrected p = 0.058, Rosenthal’s r = -0.600; Drinking: Z(11) = -2.070, corrected p = 0.058, Rosenthal’s r = -0.624). Notably, this asymmetry in preservation synergies was significantly correlated with patients’ motor function (Fugl-Meyer Assessment-Upper Limb: R = -0.711, permutation p = 0.010; Modified Ashworth Scale for elbow flexion: R = 0.603, permutation p = 0.044). This study is among the first to investigate how task complexity influences muscle synergy plasticity and its asymmetry in participants with chronic stroke. Patients demonstrate spatial asymmetry in muscle synergies between the unaffected and affected sides. This asymmetry is magnified by task complexity and shows a strong correlation with motor performance. Therefore, we recommend that when using muscle synergy patterns as biomarkers for stroke assessment, the influence of task complexity should be explicitly considered, as it plays a critical role in shaping these patterns.
Wang et al. (Mon,) studied this question.