Theory of mind and the right cerebral hemisphere: Refining the scope of impairment
Bibliographic record
Abstract
The neuropsychological and functional characterisation of mental state attribution ("theory of mind" (ToM)) has been the focus of several recent studies. The literature contains opposing views on the functional specificity of ToM and on the neuroanatomical structures most relevant to ToM. Studies with brain-lesioned patients have consistently found ToM deficits associated with unilateral right hemisphere damage (RHD). Also, functional imaging performed with non-brain-injured adults implicates several specific neural regions, many of which are located in the right hemisphere. The present study examined the separation of ToM impairment from other deficits associated with brain injury. We tested 11 patients with unilateral right hemisphere damage (RHD) and 20 normal controls (NC) on a humour rating task, an emotion rating task, a graded (first-order, second-order) ToM task with non-mentalistic control questions, and two ancillary measures: (1) Trails A and B, in order to assess overall level of impairment and set-shifting abilities associated with executive function, and (2) a homograph reading task to assess central coherence skills. Our findings indicate that RHD can result in a functionally specific deficit in attributing intentional states, particularly those involving second-order attributions. Performance on ToM questions was not reliably related to measures of cognitive impairment; however, performance on non-ToM control questions was reliably predicted by Trails A and B. We also discuss individual RHD patients' performance with attention to lesion locus. Our findings suggest that damage to the areas noted as specialised in neuroimaging studies may not affect ToM performance, and underscore the necessity of combining lesion and imaging studies in determining functional-anatomical relations.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".