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Rehabilitation Dataset Directory: Dataset Profile
Dataset: Investigating the Neurobiologic Basis for Loss of Cortical Laterality in Chronic Stroke Patients, Charleston, South Carolina, 2014-2016 ()
Basic Information | |
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Dataset Full Name | Investigating the Neurobiologic Basis for Loss of Cortical Laterality in Chronic Stroke Patients, Charleston, South Carolina, 2014-2016 |
Dataset Acronym | |
Summary | The primary goal of this project was to determine the neurobiologic basis for elevated activity in the contralesional primary motor cortex (PMC). In healthy individuals, unimanual movement (with either the left or right hand) is associated with activity in a network of predominantly contralateral brain regions, including the primary motor cortex. This laterality is often compromised following a middle cerebral artery (MCA) stroke. Neuroimaging studies of these patients have shown that unimanual movements with the effected hand are associated with elevated blood oxygen level dependent (BOLD) signal in both the lesioned and the nonlesioned primary motor cortices. Elevated activity in the contralesional PMC is well-established in chronic stroke patients and is associated with poor motor rehabilitation outcomes. Yet the neurobiologic basis for this aberrant neural activity is equivocal. One factor that may contribute to elevated activity in the contralesional PMC is increased cortical excitatory tone within the contralesional hemisphere. Another factor that may contribute to elevated activity in the contralesional PMC is a loss of transcallosal inhibition between the hemispheres. These two explanations were tested through a cross-sectional investigation of neural function in left MCA stroke patients with mild-moderate right upper extremity impairment and controls matched for age and cardiovascular risk factors. To assess the clinical relevance of these factors on motor dysfunction, the researchers performed a detailed kinematic assessment of movement efficiency, smoothness and compensation. |
Key Terms | Stroke, Motor dysfunction, Functional MRI, Anatomical Imaging, Magnetic resonance (MR) spectroscopy, Interleaved transcranial magnetic stimulation (TMS)/MRI, Single hemisphere paired-pulse TMS, Bi-hemispheric paired-pulse TMS |
Study Design | Cross-Sectional |
Data Type(s) |
Clinical Survey |
Sponsoring Agency/Entity | Medical University of South Carolina |
Health Conditions/Disability Measures |
Health Condition(s) | Stroke (left middle cerebral artery ischemic stroke), Depression, Anxiety disorders |
Disability Measures | Mental health disability measures: Quick Inventory of Depressive Symptomatology-Self-Report (QIDS-SR 16), Patient Health Questionnaire (PHQ-9), Beck Depression Inventory, State Anxiety Inventory, Trait Anxiety Inventory), Rasch-modified Fugl-Meyer upper extremity score Grip strength, Grasp, Fugl-Meyer Assessment of Motor Recovery after Stroke, Wolf Motor Function Test, Step length, Walking speed, Stroke Impact Scale (SIS), Action Research Arm Test |
Measures/Outcomes of Interest |
Topics | Middle cerebral artery (MCA) stroke, Neural activity, Neuroimaging, Brain stimulation, 3D optical imaging, Kinematics analyses (movement efficiency, movement smoothness, and motor compensation) |
Sample |
Sample Population | Control group and stroke patients: Adults aged 21-80 with at least two cardiovascular risk factors (smoking, high blood pressure, high cholesterol, diabetes, overweight, age (over 55 for men, over 65 for women), family history of stroke). Stroke patients: left middle cerebral artery ischemic stroke with at least 6 month chronicity, right upper extremity weakness with a Rasch-modified Fugl-Meyer upper extremity score of 20 to 50, ability to voluntarily flex the affected elbow and shoulder from 10-75% of the normal range, and ability to make a fist and relax the affected hand. |
Sample Size/Notes | n=37 (20 Stroke patients, 17 Control group) |
Unit of Observation | Individual/Patient |
Continent(s) | North America |
Countries | United States |
Geographic Coverage | All subjects were recruited from the larger Charleston, South Carolina community |
Geographic Specificity | NA |
Data Collection |
Data Collection Mode | Clinical, Survey, Experimental |
Years Collected | 2014-16 |
Data Collection Frequency | Data collected over 2 visits: Visit 1: Screening Visit 2: Stimulation/Scanning/Written Assessments For details see methodology |
Strengths and Limitations |
Strengths | Wide variety of measures taken and available for both stroke and control participants in study. |
Limitations | Data Details |
Primary Website | |
Data Access |
https://www.icpsr.umich.edu/web/ADDEP/studies/37313/datadocumentation |
Data Access Requirements | Restricted-Use: Researchers must agree to the terms and conditions of a Restricted Data Use Agreement in accordance with ICPSR servicing policies. |
Summary Tables/Reports | Variable level frequencies: https://www.icpsr.umich.edu/web/ADDEP/studies/37313/variables |
Data Components |
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Similar/Related Dataset(s) | Stroke focused studies: |
Selected Papers |
Other Papers | |
Technical | Data and Documentation: https://www.icpsr.umich.edu/web/ADDEP/studies/37313/datadocumentation |
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The Rehabilitation Research Cross-dataset Variable Catalog has been developed through the Center for Large Data Research & Data Sharing in Rehabilitation (CLDR). The Center for Large Data Research and Data Sharing in Rehabilitation involves a consortium of investigators from the University of Texas Medical Branch, Cornell University's Yang Tan Institute (YTI), and the University of Michigan. The CLDR is funded by NIH - National Institute of Child Health and Human Development, through the National Center for Medical Rehabilitation Research, the National Institute for Neurological Disorders and Stroke, and the National Institute of Biomedical Imaging and Bioengineering. (P2CHD065702).
Other CLDR supported resources and collaborative opportunities:
- Archive of Data on Disability to Enable Policy and research (ADDEP)
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Acknowledgements: This tool was developed through the efforts of William Erickson and Arun Karpur, and web designers Jason Criss and Jeff Trondsen at Cornell University. Many thanks to graduate students Kyoung Jo Oh and Yeong Joon Yoon who developed much of the content used in this tool.
For questions or comments please contact disabilitystatistics@cornell.edu