Brain connectivity alterations after additional sensorimotor or motor therapy for the upper limb in the early-phase post stroke: a randomized controlled trial

Neurorehabil Neural Repair

Bonkhoff

Saenen

et al. 2023

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Background. Altered dynamic functional connectivity has been associated with motor impairments in the acute phase post-stroke. Its association with somatosensory impairments in the early sub-acute phase remains unexplored. Objective. To investigate altered dynamic functional connectivity associated with somatosensory impairments in the early sub-acute phase post-stroke. Methods. We collected resting state magnetic resonance imaging and clinical somatosensory function of the upper limb of 20 subacute stroke patients and 16 healthy controls (HC). A sliding-window approach was used to identify 3 connectivity states based on the estimated dynamic functional connectivity of sensorimotor related networks. Network components were subdivided into 3 domains: cortical and subcortical sensorimotor, as well as cognitive control network. Between-group differences were investigated using independent t-tests and Mann–Whitney- U tests. Analyzes were performed with correction for age, head motion and time post-stroke and corrected for multiple comparisons. Results. Stroke patients spent significantly less time in a weakly connected network state (state 3; dwell time: pstate3 = 0.003, meanstroke = 53.02, SDstroke = 53.13; meanHC = 118.92, SDHC = 72.84), and stayed shorter but more time intervals in a highly connected intra-domain network state (state 1; fraction time: pstate 1 < 0.001, meanstroke = 0.46, SDstroke = 0.26; meanHC = 0.26, SDHC = 0.21) compared to HC. After 8 weeks of therapy, improvements in wrist proprioception were moderately associated with decreases in dwell and fraction times toward a more normalized pattern. Conclusion. Changes in temporal properties of large-scale network interactions are present in the early rehabilitation phase post-stroke and could indicate enhanced neural plasticity. These findings could augment the understanding of cerebral reorganization after loss of neural tissue specialized in somatosensory functions.

Section: Methodsmentioning

confidence: 90%

Altered Dynamic Resting State Functional Connectivity Associated With Somatosensory Impairments in the Upper Limb in the Early Sub-Acute Phase Post-Stroke

Neurorehabil Neural Repair

Bonkhoff

Saenen

et al. 2023

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“…Participants. In this study we included two cohorts of stroke patients previously assessed elsewhere 65,66 . The first cohort consisted of 25 patients who developed upper limb sensorimotor impairments after stroke, and they were recruited from the University Hospital Leuven and the University Hospital St-Luc Brussels.…”

Section: Methodsmentioning

confidence: 99%

Multimodal and multidomain lesion network mapping enhances prediction of sensorimotor behavior in stroke patients

Jiménez-Marín

Gooijers

et al. 2022

Sci Rep

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Beyond the characteristics of a brain lesion, such as its etiology, size or location, lesion network mapping (LNM) has shown that similar symptoms after a lesion reflects similar dis-connectivity patterns, thereby linking symptoms to brain networks. Here, we extend LNM by using a multimodal strategy, combining functional and structural networks from 1000 healthy participants in the Human Connectome Project. We apply multimodal LNM to a cohort of 54 stroke patients with the aim of predicting sensorimotor behavior, as assessed through a combination of motor and sensory tests. Results are two-fold. First, multimodal LNM reveals that the functional modality contributes more than the structural one in the prediction of sensorimotor behavior. Second, when looking at each modality individually, the performance of the structural networks strongly depended on whether sensorimotor performance was corrected for lesion size, thereby eliminating the effect that larger lesions generally produce more severe sensorimotor impairment. In contrast, functional networks provided similar performance regardless of whether or not the effect of lesion size was removed. Overall, these results support the extension of LNM to its multimodal form, highlighting the synergistic and additive nature of different types of network modalities, and their corresponding influence on behavioral performance after brain injury.

“…In this study we included two cohorts of stroke patients previously assessed elsewhere 47, 48 . The first cohort consisted of 25 patients who developed upper limb sensorimotor impairments after stroke, and they were recruited from the University Hospital Leuven and the University Hospital St-Luc Brussels.…”

Section: Methodsmentioning

confidence: 99%

Multimodal lesion network mapping to predict sensorimotor behavior in stroke patients

Jiménez-Marín

Gooijers

et al. 2021

Preprint

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Lesion network mapping (LNM) has proved to be a successful technique to map symptoms to brain networks after acquired brain injury. Beyond the characteristics of a lesion, such as its etiology, size or location, LNM has shown that common symptoms in patients after injury may reflect the effects of their lesions on the same circuits, thereby linking symptoms to specific brain networks. Here, we extend LNM to its multimodal form, using a combination of functional and structural connectivity maps drawn from data from 1000 healthy participants in the Human Connectome Project. We applied the multimodal LNM to a cohort of 54 stroke patients with the aim of predicting sensorimotor behavior, as assessed through a combination of motor and sensory tests. Test scores were predicted using a Canonical Correlation Analysis with multimodal brain maps as independent variables, and cross-validation strategies were employed to overcome overfitting. The results obtained led us to draw three conclusions. First, the multimodal analysis reveals how functional connectivity maps contribute more than structural connectivity maps in the optimal prediction of sensorimotor behavior. Second, the maximal association solution between the behavioral outcome and multimodal lesion connectivity maps suggests an equal contribution of sensory and motor coefficients, in contrast to the unimodal analyses where the sensory contribution dominates in both structural and functional maps. Finally, when looking at each modality individually, the performance of the structural connectivity maps strongly depends on whether sensorimotor performance was corrected for lesion size, thereby eliminating the effect of larger lesions that produce more severe sensorimotor dysfunction. By contrast, the maps of functional connectivity performed similarly irrespective of any correction for lesion size. Overall, these results support the extension of LNM to its multimodal form, highlighting the synergistic and additive nature of different types of imaging modalities, and the influence of their corresponding brain networks on behavioral performance after acquired brain injury.