The cerebellum and embodied semantics: evidence from a case of genetic ataxia due to <i>STUB1</i> mutations
Bibliographic record
Abstract
Abundant research on lexicosemantic processing indicates that damage to movement-related regions (the motor and premotor cortices, Broca´s area and the basal ganglia1) distinctively impairs processing of action verbs, that is, verbs denoting bodily motion. Moreover, such deficits could be hereditary,2 suggesting an association with genetic factors. We, thus, hypothesised that genetically based deterioration of other motor regions could involve similar impairments. In particular, through a combination of structural and functional MRI (fMRI) with genetic and behavioural analysis, this case study indicates that distinctive action-verb deficits can also be linked to genetic mutations affecting the cerebellum, a key motor hub implicated in balance, posture and movement coordination. Accordingly, in line with the embodied cognition framework, our data illuminate a potential functional specialisation of the cerebellum within the lexicosemantic domain.To test our hypothesis, we profited from access to a unique case of genetic ataxia and assessed action-verb processing together with cerebellar atrophy and related functional connectivity. The patient is a 26-year-old, Spanish-speaking male, with 13 years of education and a normal score (26/30) on the Montreal Cognitive Assessment (MoCA). He was diagnosed with cerebellar ataxia plus myoclonus, and exome sequencing revealed novel compound heterozygous mutations in the STUB1 gene3 (see online supplementary appendix e-1). His condition is characterised by severe dysarthria, action and postural tremor in the upper limbs, abnormalities of manual and facial movements and progressive disturbances of balance and gait.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 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".