Jargonaphasia as a disconnection syndrome: A study combining white matter electrical stimulation and disconnectome mapping
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Bibliographic record
Abstract
BACKGROUND: In jargonaphasia, speech is fluent but meaningless. While neuropsychological evaluation may distinguish a neologistic component characterised by non-word production and a semantic component where pronounced words are real but speech is senseless, how this relates to the underlying white matter anatomy is debated. OBJECTIVE: To identify white matter pathways causally involved in jargonaphasia. METHODS: We retrospectively screened the intraoperative brain mapping data of 571 awake oncological resections using direct cortico-subcortical electrostimulation. Jargonaphasia was induced in 17 patients (19 sites) during a naming task. Stimulation sites were normalized to the Montreal Neurological Institute template space and used to generate individual disconnectome maps. Non-parametric voxelwise one and two sample t-tests were performed to identify the underlying white matter anatomy. RESULTS: Jargonaphasia was induced only during stimulation of the left hemisphere. No cortical stimulation generated jargonaphasia. Subcortical sites causally associated with jargonaphasia clustered in 3 regions: in the temporal lobe (middle to inferior temporal gyri; n = 12), in the parietal lobe (supramarginal gyrus; n = 3) and in the temporal stem (n = 4). Disconnectome analysis indicated the inferior-fronto-occipital fasciculus (IFOF) was damaged in both neologistic and semantic jargonaphasia, while the involvement of the arcuate fasciculus was specific to neologistic jargonaphasia. CONCLUSION: For the first time, we show that jargonaphasia is induced by white matter stimulation, hinting at disconnection. As IFOF disconnection unites both variants, these may represent a continuum of disorders distinguished by semantic impairment. Conversely, damage to the arcuate fasciculus in addition to the IFOF is specific to neologistic jargonaphasia, thus suggesting a dual-disconnection syndrome.
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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 | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it