Distinct Motor Cortex Interneuron Plasticity and Its Association with Prefrontal Brain Volume in Parkinson’s Disease
Bibliographic record
Abstract
Abstract Parkinson’s disease (PD) is characterized by motor and cognitive deficits, including abnormal primary motor cortex (M1) excitability and diminished sensorimotor neuroplasticity. While paired associative stimulation (PAS) can induce M1 plasticity, people with PD (PwPD) demonstrate variability that cannot be accounted for by disease progression or medication status. Distinct M1 interneuron populations and attention-related brain structures may influence the reduced PAS- induced neuroplasticity. We aimed to characterize M1 interneuron plasticity in PwPD using attention-modulated PAS and identify neurostructural correlates. PwPD underwent MRI, then a PAS protocol with task-relevant attention. Transcranial magnetic stimulation (TMS) assessments of corticospinal excitability using posterior-to-anterior (PA) and anterior-to-posterior (AP) current directions were employed before and three post-PAS time-points. PAS induced distinct time- dependent M1 interneuron excitability changes. PA TMS showed increased corticospinal excitability at all post-PAS time-points; AP TMS increased only at 30 minutes. Rostral middle frontal gyrus volume uniquely explained variance in PA-sensitive M1 interneuron plasticity. In contrast, AP-sensitive plasticity was associated with baseline AP TMS excitability and age. These findings highlight that M1 interneuron circuits show unique neuroplasticity patterns in PwPD and relate to prefrontal brain volume. Our results suggest a complex interplay between motor and cognition-related deficits as interrelated pathophysiological features in PD.
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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".