Motor Learning in Parkinson’s Disease: Underlying Effective Connectivity and Influential Factors

Overview

Parkinson's disease (PD) is characterized by severe motor symptoms that can only be partially alleviated by medication. It was shown previously that rehabilitation is an important therapeutic supplement for micrographia in early disease. However, what is unknown is how motor learning impacts on the underlying neural networks in patients with different disease progression and how this interacts with dopaminergic medication. Furthermore, difficulties with upper limb motor control has a severe impact on the daily lives of PD patients since fine motor skills become increasingly important for the use of smartphones and tablets. Therefore, the current project will include a newly developed Swipe-Slide Pattern test, resembling the pattern codes used to unlock smartphones and tablets. This task will be used to determine learning-induced neuroplasticity of cortico-striatal effective connectivity across disease stages in PD. Using a combination of behavioral assessment and functional magnetic resonance imaging, the investigators aim to contribute to the understanding of upper limb motor learning in patients with PD for the development of individualized rehabilitation programs.

Full Title of Study: “Motor Learning in Parkinson’s Disease: Underlying Effective Connectivity and Influential Factors”

Study Type

  • Study Type: Interventional
  • Study Design
    • Allocation: Non-Randomized
    • Intervention Model: Single Group Assignment
    • Primary Purpose: Basic Science
    • Masking: None (Open Label)
  • Study Primary Completion Date: September 2022

Detailed Description

For this study, 25 healthy controls, 25 early patients and 25 mid-stage patients will be included. The sample size was predicted by a power-analysis based on our own pilot study and the study of Dan et al., using a β=0.20, α=0.05. Mean movement time after the first 18 blocks of the SSP-task were available for healthy controls and PD patients in the mid-stage and predicted for early-stage patients. To counter potential dropout from the studies or data loss, the recruitment numbers are at least 30% higher than the ones resulting from the power analysis. Patients will be tested during the OFF phase of the medication cycle, i.e. approximately 12 h after last medication intake. The distinction between early and mid-stage patients is based on a combined criterion of disease duration and upper limb items of the MDS-UPDRS-III (while OFF medication). Patients are considered as early when ≤ 2 years have passed since the first symptoms emerged (note this is not years since diagnosis) in combination with maximal score of 2 on each of the upper limb MDS-UPDRS-III items. Patients are considered as mid-stage when either one of these criteria is not fulfilled.

Participants will first undergo an inclusion session at home. During this session, they will undergo an extensive behavioral test battery, assessing cognitive and motor skills. Patients will start this session in the OFF phase of the medication phase and will therefore be asked to postpone their morning medication. First, motor skills will be assessed by means of the Movement Disorders Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) and Clinch token transfer test (C3T). Cognitive assessment includes the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA) and Trail Making Test (TMT). Additionally, tablet skills will be tested extensively using a newly developed test battery, including performance of tapping between two spots, swiping in a single direction and swiping in multiple directions in random order, in single and dual task conditions. Additionally, a mobile phone task will be performed in which participants have to type in a pre-defined phone number on a smartphone. This part of the assessment will take approximately 60 min. Afterwards patients will be able to take their regular medication and several questionnaires will be filled out. These include the New Freezing Of Gait Questionnaire (NFOG-Q), the non-gait freezing questionnaire, the Dexterity questionnaire (DextQ-24), the Mobile Device Proficiency Questionnaire (MDPQ-16), questions regarding smartphone and tablet use and remaining parts of the MDS-UPDRS. Furthermore, daily levodopa doses will be recorded. Healthy controls will undergo a similar protocol, though disease-specific assessments and questionnaires will not be performed (i.e. MDS-UPDRS, NFOG-Q, non-gait freezing questionnaire and medication intake).

Following inclusion, participants will be invited to the radiology dept. UZ Leuven. They will train the SSP-task on an MRI-compatible tablet, while their hemodynamic responses are measured using fMRI. Training will include two runs of 7 min 50 s. The SSP-task is based on the finger movements that have to be made to unlock smartphones or tablets or the trajectory that can be used to quickly form words using a keyboard on a smartphone. During this test, participants will have to make different pre-defined patterns. To reduce cognitive load, the pattern will be visible in one of the upper corners of the screen. During the task, participants will be able to see the lines they are drawing. Every pattern will begin in one of nine circles and will consist of equally long movements. Participants will be asked to move the hand without fully lifting the finger stylus from the screen to maintain the online trace. In addition, participants will be instructed to return to a fixed starting point when the pattern is complete. An MRI-compatible version of the touch-sensitive tablet will be used. Participants will see the trace of their pen on the tablet by means of a built-in mirror on top of the head coil. In addition to the task-based fMRI, a high-resolution T1-weighted anatomical scan and diffusion weighted imaging will be performed. Before and after the scan, participants will perform the mobile phone task, a single- and dual-task version of the SSP (to test automatization) and the tapping between two spots test outside the scanner. Additionally, participants will fill out the Hospital Anxiety and Depression Scale (HADS) and Pittsburgh Sleep Quality Index (PSQI).

From day 2 till 5, participants will continue practice of the SSP-task at home. For this, participants will be asked to perform the SSP-task on a tablet each morning, for patients this will be just before taking their regular medication. These training sessions will be limited to 10 minutes and contain the pattern that was learned on day 1, as well as two new patterns to allow variation. The patterns will be offered in a random order, as research has shown that random practice can improve retention and transfer in both healthy elderly adults and patients with PD. On day 5, the researcher will go to the participants' home and perform an immediate retention test, involving the single- and dual task version of the SSP-task. On days 6 and 7 participants will not practice to allow for a retention period. On day 8, all participants will have a (delayed) retention/transfer scan, consisting of two runs: (i) a run containing the learned pattern; and (ii) a run including a new pattern to assess transfer. Again, ST and DT performance on the SSP-task will be assessed outside the scanner, using a different pattern to avoid learning. Participants will also perform the mobile phone task and tapping between two spots test. To minimize head movements during the scan itself, a vacuum fixation pillow to accommodate these difficulties will be used.

Interventions

  • Behavioral: SSP training
    • Participants will practice the Swipe Slide Pattern (SSP) task. On day 1, participants perform two runs of the SSP-task (only one pattern), each lasting approx. 10 min, within an MR scanner. During each run, nine trials of 30s are performed, alternated with rest periods of 14s. In addition, instructions are provided before each trial (i.e. view of the pattern, 4s), as well as an answer option (i.e. participants have circle a random number from zero to nine, 6s). For the following four days (day 2-5), participants will continue practice of the SSP-task at home. During the at-home-sessions, participants will perform nine trials of 12 patterns each, alternated with rest periods of 14s. Instruction are also included. During at home practice, the same pattern as during scans is included, in combination with two new patterns.

Arms, Groups and Cohorts

  • Experimental: SSP training – early PD
    • Practice of the Swipe Slide Pattern task alone for a group of patients with early Parkinson’s disease (PD)
  • Experimental: SSP training – mid PD
    • Practice of the Swipe Slide Pattern task alone for a group of patients with mid-stage Parkinson’s disease (PD)
  • Experimental: SSP training – HC
    • Practice of the Swipe Slide Pattern task alone for a group of healthy age-matched controls (HC)

Clinical Trial Outcome Measures

Primary Measures

  • Change in movement time (s) of trained pattern
    • Time Frame: 7 days
    • 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 groups (early PD vs mid PD vs HC).
  • Change in dual task effect
    • Time Frame: 7 days
    • 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 groups (early PD vs mid PD vs HC) and time points
  • Change in brain activity during performance of trained pattern
    • Time Frame: 7 days
    • The BOLD activity pattern will be determined and compared between the 3 training phases (i.e. early learning, late learning and retention) and groups (early PD vs mid PD vs HC).
  • Change in brain connectivity during performance of trained pattern
    • Time Frame: 7 days
    • 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) and groups (early PD vs mid PD vs HC).
  • Diffusion weighted imaging as a predictor
    • Time Frame: 7 days
    • Anatomical connectivity at baseline will be calculated and investigated as a predictive factor for learning capacity.

Secondary Measures

  • Change in Euclidean distance of trained pattern
    • Time Frame: 7 days
    • 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 groups (early PD vs mid PD vs HC).
  • Change in movement time (s) of the untrained pattern
    • Time Frame: 7 days
    • 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 groups (early PD vs mid PD vs HC).
  • Change in Euclidean distance of the untrained pattern
    • Time Frame: 7 days
    • 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 groups (early PD vs mid PD vs HC).
  • Change in brain activity during performance of untrained pattern
    • Time Frame: 7 days
    • The BOLD activity pattern will be determined and compared between the training phases and groups (early PD vs mid PD vs HC).
  • Change in brain connectivity during performance of untrained pattern
    • Time Frame: 7 days
    • The BOLD activity pattern will be determined and connectivity measures will be extracted. Neural network changes will be compared between the training phases and groups (early PD vs mid PD vs HC).

Participating in This Clinical Trial

Inclusion Criteria

  • Diagnosis of Parkinson's disease based on the 'UK Brain Bank' criteria
  • Right handed
  • No dementia (Mini Mental State Examination > 24/30)
  • Early PD group: disease duration of ≤ 2 year since appearance of first symptoms in combination with a maximum score of 2 on each of the upper limb items of the MDS-UPDRS-III
  • Mid stage PD group: patients are considered as mid-stage in case one of the criteria for early PD is not fulfilled

Exclusion Criteria

  • Comorbidities of the upper limb that could interfere with the study and are not caused by Parkinson's disease (e.g. arthritis, fractures of the hand, etc.)
  • Other medical or psychiatric impairments that could interfere with the study protocol
  • Contra-indications for Magnetic Resonance Imaging
  • 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

Gender Eligibility: All

Minimum Age: 50 Years

Maximum Age: 80 Years

Are Healthy Volunteers Accepted: Accepts Healthy Volunteers

Investigator Details

  • Lead Sponsor
    • KU Leuven
  • Collaborator
    • Research Foundation Flanders
  • Provider of Information About this Clinical Study
    • Principal Investigator: Alice Nieuwboer, Full professor – KU Leuven
  • Overall Official(s)
    • Alice Nieuwboer, PhD, Principal Investigator, KU Leuven
  • Overall Contact(s)
    • Evelien Nackaerts, PhD, +3216329360, evelien.nackaerts@kuleuven.be

References

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.

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.

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. Epub 2016 Jun 24.

Dan X, King BR, Doyon J, Chan P. Motor Sequence Learning and Consolidation in Unilateral De Novo Patients with Parkinson's Disease. PLoS One. 2015 Jul 29;10(7):e0134291. doi: 10.1371/journal.pone.0134291. eCollection 2015.

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