Related Experiment Video
Updated: Aug 22, 2026

Electroencephalography Network Indices as Biomarkers of Upper Limb Impairment in Chronic Stroke
Published on: July 14, 2023
EEG Connectomics in Rotator Cuff Injury: Central Network Reorganization During Three-Plane Antagonistic Shoulder
None:
We characterised central nervous system reorganisation in rotator cuff injury (RCI) during three-plane antagonistic shoulder tasks using electroencephalography (EEG) connectomics, and tested whether graph metrics discriminate RCI from healthy controls (HC). We enrolled 51 RCI patients and 50 HCs performing three-plane tasks. EEG (64 channels) was preprocessed and source-localised; source-space connectivity was computed in five bands (θ, α, β, low-γ, high-γ) using the weighted phase-lag index (WPLI). Whole-brain graph metrics (global efficiency (GE), characteristic path length (CPL), clustering coefficient (CC), modularity (Mod) and small-worldness (SW)) were derived, and network-based statistics (NBS) identified differential subnetworks from which mean subnetwork strength (WPLINBS) and related measures were extracted. Per action-band, single-feature linear support vector machines (SVMs) were evaluated with nested cross-validation for RCI-HC classification. Group differences were frequency-specific: β (13-30 Hz) and low-γ (30-50 Hz) showed RCI "over-integration/under-segregation" (higher GE and CC), whereas CPL, Mod and SW were higher in HC; θ/α effects were weak, whereas high-γ effects were less robust and less consistent across shoulder tasks than the β and low-γ effects. NBS detected significant components only in β/low-γ, characterised by stronger coupling between occipital visual cortex and frontoparietal/cerebellar regions; within these components, WPLINBS, nodal strength and local efficiency were higher in RCI. CPL, GE or WPLINBS in β/low-γ provided robust classification (ACC≈0.86; AUC≈0.90). Overall, RCI is associated with β/low-γ-centred network reorganisation and enhanced occipito-parietal-frontal coupling, suggesting greater engagement of visual-related visuomotor networks during shoulder task execution. These EEG graph metrics may serve as candidate CNS biomarkers and potential targets for personalised rehabilitation.
More Related Videos
04:43Investigating the Effect of Different Types of Exercise on Upper Limb Functional Recovery in Patients with Right Hemisphere Damage Based on fNIRS
Published on: February 9, 2024
07:22Arthroscopic Management of Massive Irreparable Rotator Cuff Tears: Whole Rotator Cable Reconstruction Using Proximal Biceps Tendon Autograft
Published on: June 6, 2025