Dose-response curve of associative plasticity in human motor cortex and interactions with motor practice
Bibliographic record
Abstract
Associative plasticity is hypothesized to be an important neurophysiological correlate of memory formation and learning with potentials for applications in neurorehabilitation and for the development of new electrophysiological measures to study disorders of cortical plasticity. We hypothesized that the magnitude of the paired associative stimulation (PAS)-induced long-term potentiation (LTP)-like effect depends on the number of pairs in the PAS protocol. We also hypothesized that homeostatic interaction of PAS with subsequent motor learning is related to the magnitude of the PAS-induced LTP-like effect. We studied 10 healthy subjects. In experiment 1a, subjects received 90 (PAS90), 180 (PAS180), or 270 (PAS270) pairs of stimuli, followed by a dynamic motor practice (DMP) 1 h after the end of the PAS protocols. In experiment 1b, the DMP preceded the PAS protocol. In experiment 2, the time course of PAS270 was studied. We found that PAS270 resulted in greater increase in motor evoked potential (MEP) amplitude compared with protocols with fewer pairs of stimuli. Moreover, the interaction between PAS protocols with motor learning differed depending on the number of stimulus pairs used to induce PAS. While DMP alone increased MEP amplitudes, DMP during the LTP-like effects induced by PAS270 led to a long-term depression (LTD)-like effect (homeostatic interaction). This homeostatic interaction did not occur after PAS90 and PAS180. In conclusion, we found a dose-dependent effect of the number of stimulus pairs used in the PAS protocol on cortical plasticity. Homeostatic interaction between PAS and DMP was observed only after PAS270.
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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 | 0.003 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".