Literature DB >> 35420350

Associations between resting-state functional connectivity changes and prolonged benefits of writing training in Parkinson's disease.

Joni De Vleeschhauwer1, Evelien Nackaerts2, Nicholas D'Cruz2, Britt Vandendoorent2, Letizia Micca2, Wim Vandenberghe3,4, Alice Nieuwboer2.   

Abstract

BACKGROUND: Our earlier work showed that automaticity and retention of writing skills improved with intensive writing training in Parkinson's disease (PD). However, whether this training changed the resting-state networks in the brain and how these changes underlie retention of motor learning is currently unknown.
OBJECTIVE: To examine changes in resting-state functional connectivity (rs-FC) and their relation to behavioral changes immediately after writing training and at 6 week follow-up.
METHODS: Twenty-five PD patients underwent resting-state fMRI (ON medication) before and after 6 weeks writing training. Motor learning was evaluated with a dual task paradigm pre- and post-training and at follow-up. Next, pre-post within-network changes in rs-FC were identified by an independent component analysis. Significant clusters were used as seeds in ROI-to-ROI analyses and rs-FC changes were correlated with changes in behavioral performance over time.
RESULTS: Similar to our larger cohort findings, writing accuracy in single and dual task conditions improved post-training and this was maintained at follow-up. Connectivity within the dorsal attentional network (DAN) increased pre-post training, particularly with the right superior and middle temporal gyrus (rS/MTG). This cluster also proved more strongly connected to parietal and frontal areas and to cerebellar regions. Behavioral improvements from pre- to post-training and follow-up correlated with increased rs-FC between rS/MTG and the cerebellum.
CONCLUSIONS: Training-driven improvements in dual task writing led to functional reorganization within the DAN and increased connectivity with cerebellar areas. These changes were associated with the retention of writing gains and could signify task-specific neural changes or an inability to segregate neural networks.
© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany.

Entities:  

Keywords:  Handwriting; Micrographia; Motor learning; Parkinson’s disease; Resting-state fMRI

Mesh:

Year:  2022        PMID: 35420350     DOI: 10.1007/s00415-022-11098-8

Source DB:  PubMed          Journal:  J Neurol        ISSN: 0340-5354            Impact factor:   6.682


  57 in total

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