Neuroplastic Effects of Dance Training in Parkinson’s Disease: Functional and Structural Modulation in Speech-Related Brain Regions
Bibliographic record
Abstract
Abstract Background Parkinson’s disease (PD) is a neurodegenerative disorder characterized by progressive motor and non-motor impairments, including speech deficits. Dance-based interventions have been proposed as a promising rehabilitative strategy for enhancing motor function, cognitive engagement, and neuroplasticity. However, the neural mechanisms underlying dance-induced neuroplasticity remain poorly understood. Objective This study aimed to investigate the effects of an 8-month dance training program on functional brain activity, cortical structure, and white matter integrity in people with PD (PwPD) using a multi-modal neuroimaging approach. Methods Ten individuals with PD participated in dance training and underwent functional MRI (fMRI) and cortical thickness analysis (T1-weighted MRI) at four time points, and 4 of them underwent diffusion-weighted imaging (DWI) at the last two time points. fMRI examined BOLD signal changes in the motor cortex (inferior frontal gyrus) and the supplementary motor area (SMA) during a dance-imagery task. Cortical thickness was measured in Broca’s area and the left supplementary frontal language (SFL) area. A reference group from the Michael J. Fox Foundation’s Parkinson’s Progression Markers Initiative (PPMI) dataset was selected for cortical thickness analysis. White matter integrity between Broca’s area and the SFL area was assessed using fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD). Additionally, fundamental frequency standard deviation (F0SD), a key indicator of speech prosody, was analyzed in three participants over a 5-year follow-up period to examine the functional relevance of neuroplastic changes. Results Reductions in BOLD signal were observed in the motor cortex (inferior frontal gyrus) between September and January ( p = 0.021), suggesting increased neural efficiency. In contrast, SMA exhibited a significant increase in BOLD signal activity between September and January ( p = 0.010), indicating enhanced motor-speech integration. No further notable changes in functional activity in both regions were detected between January and April. The dance group showed significant changes in cortical thickness in the left SFL area across time, with increases from September to December ( p = 0.049) followed by decreases from December to April ( p = 0.046). However, no changes were detected in Broca’s area for the dance or reference groups. Additionally, the reference group did not exhibit any significant changes in the left SFL area across the same time points. FA increased significantly between January and April ( p = 0.024), suggesting enhanced white matter organization in speech-motor pathways. AD showed a marginal increase during this period ( p = 0.056), while RD and MD remained stable. Critically, voice feature analysis revealed significant improvements in F0SD over the 5-year follow-up period ( p < 0.0001), demonstrating sustained functional benefits in speech prosody that were associated with the earlier neuroplastic adaptations. Conclusion Dance training was associated with significant functional and white matter neuroplastic changes in PD, particularly in motor-related functional activity and white matter connectivity between motor and language networks. The neuroplastic adaptations observed during the 8-month intervention period were associated with sustained improvements in speech prosody that persisted for years, providing compelling evidence for the clinical relevance of dance-induced brain changes. While dynamic cortical thickness changes were observed in the SFL area, the functional and structural connectivity adaptations appear to be the primary drivers of therapeutic benefit. These findings highlight dance as a promising, intervention for enhancing neural efficiency and motor-linguistic integration in PD, with demonstrated long-term functional benefits that warrant further investigation in larger, controlled studies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".