Cerebellar Lesions Impair Reflexive but not Voluntary Covert Attention: Preliminary Findings
Bibliographic record
Abstract
Recent research has revealed that the cerebellum is involved in much more than just motor output. Interestingly, functional neuroimaging studies and human lesion studies have discovered that the cerebellum has been reported to be involved in various cognitive roles such as language, emotion, and attention. Specifically, our lab is interested in aspects of attention such as reflexive and voluntary covert attention. Previously, a neuroimaging study from our lab showed increased activity in the left cerebellum for covert reflexive attention compared to covert voluntary attention. However, this idea has not been directly tested behaviorally in patients with cerebellar lesions. Therefore, the current study examined how 10 patients with cerebellar lesions performed on reflexive and voluntary covert attention tasks. The results indicated that the cerebellar patients have a slowed onset of inhibition of return compared healthy-age matched controls (n=10). In addition, deficits in reflexive covert attention appeared to be linked with damage to the lateral cerebellum. In contrast, there were no differences between the patients and controls in the voluntary attention task. The current study provides converging evidence that the cerebellum may be more involved for reflexive covert attention compared to voluntary covert attention. Discipline: Psychology Honours Faculty Mentor: Dr. Christopher Striemer
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".