Parkinson Disease Clinical Trial
Official title:
Triggering Motor Memory Consolidation in Parkinson's Disease: the Effects of Complex Practice on Brain Activity During Learning of Fine Motor Tasks
| Verified date | November 2023 |
| Source | KU Leuven |
| Contact | n/a |
| Is FDA regulated | No |
| Health authority | |
| Study type | Interventional |
Parkinson's disease (PD) is characterized by severe motor symptoms, including upper limb dysfunction, that is only partially alleviated by medication. PD is also a motor learning disease due to the degradation of the striatum, involved in the consolidation of motor memory. We showed earlier that motor practice improves writing deficits and that there is long term potential when it is applied in a focused manner. However, retention difficulties were also apparent. What is currently unclear, is which learning method leads to optimal retention in PD and how it is expressed in underlying neural network changes. In healthy controls, retention is improved by incorporating dual task (DT) conditions or by loading cognition during learning. Our own work showed that DT training also led to better retention than single task (ST) learning, at least in a subgroup of PD. Using a combination of behavioral assessment, functional magnetic resonance imaging and upper limb task training, this project aims to understand how to boost the robustness of practice in PD. Throughout, we will contrast ST with DT learning. As complex practice can now easily be delivered via novel technology, this study will set out future avenues for rehabilitation targeted at specific neural circuitry.
| Status | Active, not recruiting |
| Enrollment | 80 |
| Est. completion date | March 2024 |
| Est. primary completion date | May 16, 2023 |
| Accepts healthy volunteers | Accepts Healthy Volunteers |
| Gender | All |
| Age group | 50 Years to 80 Years |
| Eligibility | Inclusion Criteria: - Diagnosis of Parkinson's disease based on the 'UK Brain Bank' criteria - Hoehn and Yahr (H&Y) stage I-III - Without a history of intervening co-morbidities - Right handed - Participants in H&Y stage I should have the right side as the most affected side Exclusion Criteria: - Cognitive decline (Mini Mental State Examination < 24) - Visual impairments that impede the following of visual targets - Comorbidities of the upper limb that could interfere with the study and are not caused by Parkinson's disease - Contra-dinidcations for Magnetic Resonance Imaging (MRI) - Tremor of the head or right hand, as determined by the Movement Disorders Society Unified Parkinson's disease Rating scale part III - Color blindness as determined by the Ishihara test for color deficiency |
| Country | Name | City | State |
|---|---|---|---|
| Belgium | Department of Rehabilitation Sciences KU Leuven | Leuven |
| Lead Sponsor | Collaborator |
|---|---|
| KU Leuven |
Belgium,
Lin CH, Chiang MC, Wu AD, Iacoboni M, Udompholkul P, Yazdanshenas O, Knowlton BJ. Age related differences in the neural substrates of motor sequence learning after interleaved and repetitive practice. Neuroimage. 2012 Sep;62(3):2007-20. doi: 10.1016/j.neuroimage.2012.05.015. Epub 2012 May 11. — View Citation
Nackaerts E, Ginis P, Heremans E, Swinnen SP, Vandenberghe W, Nieuwboer A. Retention of touchscreen skills is compromised in Parkinson's disease. Behav Brain Res. 2020 Jan 27;378:112265. doi: 10.1016/j.bbr.2019.112265. Epub 2019 Sep 27. — View Citation
Sidaway B, Ala B, Baughman K, Glidden J, Cowie S, Peabody A, Roundy D, Spaulding J, Stephens R, Wright DL. Contextual Interference Can Facilitate Motor Learning in Older Adults and in Individuals With Parkinson's Disease. J Mot Behav. 2016 Nov-Dec;48(6):509-518. doi: 10.1080/00222895.2016.1152221. Epub 2016 Jun 24. — View Citation
| Type | Measure | Description | Time frame | Safety issue |
|---|---|---|---|---|
| Primary | Change in movement time (s) of trained pattern | Using the behavioral data gathered during task-based fMRI, the learning index and retention index, as described in Nackaerts et al. 2020, will be determined and compared between training types (ST vs DT) and groups (PD vs HC). | 7 days | |
| Primary | Change in dual task effect | Using the behavioral data gathered before and immediately after task-based fMRI, as well as at immediate and delayed retention, dual task interference will be calculated and compared between training types (ST vs DT), groups (PD vs HC) and time points. | 7 days | |
| Primary | Change in brain activity during performance of trained pattern | The BOLD activity pattern will be determined and compared between the 3 training phases (i.e. early learning, late learning and retention), between training types (ST vs DT) and groups (PD vs HC). | 7 days | |
| Primary | Change in brain connectivity during performance of trained pattern | The BOLD activity pattern will be determined and connectivity measures will be extracted. Neural network changes will be compared between the 3 training phases (i.e. early learning, late learning and retention), between training types (ST vs DT) and groups (PD vs HC). | 7 days | |
| Primary | Diffusion weighted imaging as a predictor | Anatomical connectivity at baseline will be calculated and investigated as a predictive factor for learning capacity. | 7 days | |
| Secondary | Change in Euclidean distance of trained pattern | Using the behavioral data gathered during task-based fMRI, the learning index and retention index, as described in Nackaerts et al. 2020, will be determined and compared between training types (ST vs DT) and groups (PD vs HC). | 7 days | |
| Secondary | Change in movement time (s) of the untrained pattern | Using the behavioral data gathered during task-based fMRI, the transfer index, as described in Nackaerts et al. 2020, will be determined and compared between training types (ST vs DT) and groups (PD vs HC). | 7 days | |
| Secondary | Change in Euclidean distance of the untrained pattern | Using the behavioral data gathered during task-based fMRI, the transfer index, as described in Nackaerts et al. 2020, will be determined and compared between training types (ST vs DT) and groups (PD vs HC). | 7 days | |
| Secondary | Change in brain activity during performance of untrained pattern | The BOLD activity pattern will be determined and compared between the training phases, training types (ST vs DT) and groups (PD vs HC). | 7 days | |
| Secondary | Change in brain connectivity during performance of untrained pattern | The BOLD activity pattern will be determined and connectivity measures will be extracted. Neural network changes will be compared between the training phases, between training types (ST vs DT) and groups (PD vs HC). | 7 days |
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