Impaired coherence for semantic but not episodic autobiographical memory in semantic variant primary progressive aphasia
Bibliographic record
Abstract
Language deficits, including word-finding difficulties and impaired single-word comprehension, have been found in patients with semantic variant primary progressive aphasia (svPPA). These deficits characterize the linguistic abilities of patients with svPPA on a micro-linguistic level (word and sentence level). On a macro-linguistic level (discourse level), svPPA patients’ discourse has been described as “empty”. Few studies have considered the contribution of a linguistic impairment to the difficulty of producing autobiographical narratives. In the present study, we assessed svPPA patients’ discourse coherence during autobiographical narratives in order to characterize the nature of their speech on a macro-linguistic level and to investigate the relationship between discourse production and memory in a naturalistic context. We collected samples of discourse in which svPPA patients and healthy controls (matched in age, education, sex and handedness) reported autobiographical events. Their narratives were assessed with a rating scale to evaluate global coherence of discourse. The protocols were also analysed using the Autobiographical Interview method (Levine, Svoboda, Hay, Winocur, & Moscovitch, 2002) and categorized as episodic (information about events at a specific time and place), semantic (general knowledge), or supplementary details (metacognitive statements, repeated information, editorializing). Where possible, patients were assessed longitudinally at three time points over two years. Patients with svPPA produced a reduced number of episodic details, while the number of semantic details produced was comparable to controls. However, the episodic information produced by patients was coherent with the topic of discourse, while semantic information was not. These results suggest that svPPA patients produce semantic information comparable to controls in quantity but not quality, whereas the opposite is the case for episodic information.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".