Different aspects of hand grip performance associated with structural connectivity of distinct sensorimotor networks in chronic stroke

Author:

Schranz Christian1,Srivastava Shraddha1,Seamon Bryant A.23ORCID,Marebwa Barbara4,Bonilha Leonardo5,Ramakrishnan Viswanathan6,Wilmskoetter Janina7,Neptune Richard R.8,Kautz Steve A.123,Seo Na Jin139ORCID

Affiliation:

1. Department of Health Sciences and Research Medical University of South Carolina Charleston South Carolina USA

2. Division of Physical Therapy, Department of Rehabilitation Sciences Medical University of South Carolina Charleston South Carolina USA

3. Ralph H. Johnson VA Health Care System Charleston South Carolina USA

4. Department of Neurology Medical University of South Carolina Charleston South Carolina USA

5. Department of Neurology Emory University Atlanta Georgia USA

6. Department of Public Health Sciences Medical University of South Carolina Charleston South Carolina USA

7. Division of Speech‐Language Pathology, Department of Rehabilitation Sciences Medical University of South Carolina Charleston South Carolina USA

8. Walker Department of Mechanical Engineering The University of Texas at Austin Austin Texas USA

9. Division of Occupational Therapy, Department of Rehabilitation Sciences Medical University of South Carolina Charleston South Carolina USA

Abstract

AbstractKnowledge regarding the neural origins of distinct upper extremity impairments may guide the choice of interventions to target neural structures responsible for specific impairments. This cross‐sectional pilot study investigated whether different brain networks explain distinct aspects of hand grip performance in stroke survivors. In 22 chronic stroke survivors, hand grip performance was characterized as grip strength, reaction, relaxation times, and control of grip force magnitude and direction. In addition, their brain structural connectomes were constructed from diffusion tensor MRI. Prominent networks were identified based on a two‐step factor analysis using the number of streamlines among brain regions relevant to sensorimotor function. We used regression models to estimate the predictive value of sensorimotor network connectivity for hand grip performance measures while controlling for stroke lesion volumes. Each hand grip performance measure correlated with the connectivity of distinct brain sensorimotor networks. These results suggest that different brain networks may be responsible for different aspects of hand grip performance, which leads to varying clinical presentations of upper extremity impairment following stroke. Understanding the brain network correlates for different hand grip performances may facilitate the development of personalized rehabilitation interventions to directly target the responsible brain network for specific impairments in individual patients, thus improving outcomes.

Funder

National Center for Medical Rehabilitation Research

National Institute of General Medical Sciences

Publisher

Wiley

Subject

Physiology (medical),Physiology

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