FV 24 Connectome-based lesion symptom mapping: Disconnection patterns underlying specific aspects of motor impairment after stroke. (May 2022)

• Record Type: Journal Article
• Authors: Esser, F.; Raizor, E.; Binder, E.; Hensel, L.; Rehme, A.K.; Ringmaier, C.; Schönberger, A.; Tscherpel, C.; Grefkes, C.; Fink, G.R.; Grafton, S.T.; Volz, L.J.
• Is Part Of: Clinical neurophysiology. Volume 137(2022)
• Page Start: e13
• Page End: e14
• Publication Date: 2022-05
• Subjects: Neurophysiology -- Periodicals; Electroencephalography -- Periodicals; Electromyography -- Periodicals; Neurology -- Periodicals; 612.8
• DOI: 10.1016/j.clinph.2022.01.030
• Languages: English
• ISSNs: 1388-2457

Abstract

Abstract : Introduction: An accurate prediction of motor impairment from lesion information after stroke remains challenging, highlighting the complexity of structure-function relationships. While corticospinal tract (CST) integrity has been shown to correlate with motor impairment after stroke1, far less is known about the functional relevance of cortico-cortical connections for distinct aspects of motor function. Therefore, we investigated whether it is possible to infer distinct aspects of individual motor impairment and identify crucial task-specific connections using connection-based lesion-symptom mapping (CLSM) in acute stroke patients. Methods: Individual disconnectomes were estimated for 114 ischemic stroke patients using lesion masks designed based on routine MRI data and a normative structural connectome 2 . Relative grip strength and four subtests of the Action Research Arm Test 3 were performed to assess movements with varying demands of multi-joint movements, strength and fine-grained control. Nested and cross-validated support vector regressions (SVR) estimated impairment across motor tasks based on CLSM data and CST damage. Results: For each motor task, CLSM-SVR significantly predicted individual motor impairment (p<0.05 permutation testing) with higher or similar accuracy compared to CST-SVR. CLSM and CST-integrity represented largely independent aspects of variance in motor impairment. Permutation testing identified disconnection patterns underlying SVR predictions (Fig. 1). Discussion: Disconnections between ipsilesional subcortical motor areas and bihemispheric cortical motor areas were indicative of impairment across all motor tasks. Movements relying on fine-grained motor control were impacted by ipsilesional motor-temporal, and -prefrontal disconnections. Multi-joint movements involving proximal musculature relied on diverse interhemispheric (pre-)motor-prefrontal and -temporal connections, which may reflect several compensatory ways of motor execution. In summary, lesion-induced cortico-cortical disconnections were associated with distinct aspects of individual motor impairment, highlighting the potential of CLSM to further our understanding of crucial white matter structures in the human motor network. References 1. Koch et al., 2016. Structural connectivity analyses in motor recovery research after stroke. Annals of clinical and translational neurology, 3(3), 233-244. 2. Greene et al., 2019. Finding maximally disconnected subnetworks with shortest path tractography. NeuroImage: Clinical, 23, 101903. 3. Lyle, 1981. A performance test for assessment of upper limb function in physical rehabilitation treatment and research. International journal of rehabilitation research, 4(4), 483-492. Legend