A model of rhythm production and rhythmic auditory stimulation in healthy and Parkinsonian basal ganglia
Bibliographic record
Abstract
Abstract In fMRI experiments, the basal ganglia is consistently activated by rhythmic action and sensorimotor synchronization to a metronome, and conditions like Parkinson’s Disease that affect basal ganglia and its dopaminergic modulation are experimentally seen to affect performance on both types of task. However, it is not clear what role this circuit or dopaminergic modulation play during rhythm production and synchronization tasks. Here, we propose that the basal ganglia may specify, maintain, and adapt the tempo with which rhythmic action (e.g. finger tapping or walking) is performed. We build a model based on previous “action selection” models of the cortico-basal-ganglia loop, altered such that cortico-basal-ganglia loops correspond not to distinct actions but to a continuum of possible action tempi. During rhythm production, an initial tempo is selected by cortical input, and rhythmic action can be automatized to continue in the absence of cortical input if tonic dopamine levels in striatum are sufficiently high. When striatal dopamine is reduced, our model reproduces two key features of dopamine deprivation in Parkinson’s disease: freezing of gait, and increased variation in produced intertap intervals during rhythmic tapping. By reanalyzing data from a recent experiment with Parkinsonian patients, we confirm the model’s prediction that increased interval variability should be largely attributable to increased tempo drift (rather than, e.g., increased timekeeper noise). This model of rhythm production is the first to invoke specific features of basal ganglia circuitry. It augments existing models of action selection in basal ganglia with the addition of continuous action parameters, and in doing so provides a starting point for further modeling of action timing and rhythm in the motor system. It offers a new model of the mechanism by which rhythmic auditory stimulation supports gait in Parkinson’s patients, and makes a new, testable prediction about sensorimotor synchronization under conditions of low tonic dopamine.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".