A causal role for the cerebellum in semantic integration: a transcranial magnetic stimulation study
Bibliographic record
Abstract
Mounting evidence suggests that the cerebellum, a structure previously linked to motor function, is also involved in a wide range of non-motor processes. It has been proposed that the cerebellum performs the same computational processes in both motor and non-motor domains. Within motor functions, the cerebellum is involved in the integration of signals from multiple systems. Here we hypothesized that cerebellum may be involved in integration within semantic memory as well. Specifically, understanding a noun-adjective combination (e.g. red apple) requires combining the meaning of the adjective (red) with the meaning of the noun (apple). In two experiments, participants were asked to judge whether noun-adjective word-pairs were semantically related (e.g., red apple) or not (e.g., lucky milk) while online transcranial magnetic stimulation (TMS) was administered over the right cerebellum or over a control site (vertex in Experiment 1 and visual cortex in Experiment 2). Cerebellar TMS caused a decrease in participants' accuracy for related word-pairs while accuracy for unrelated stimuli was not affected. A third experiment using a control task where subjects compared pairs of random letters showed no effect of TMS. Taken together these results indicate that the right cerebellum is involved specifically in the processing of semantically related stimuli. These results are consistent with theories that proposed the existence of a unified cerebellar function within motor and non-motor domains, as well with recent perspectives about cerebellar involvement in semantic memory and predictive cognition.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".