The Company Prosodic Deficits Keep Following Right Hemisphere Stroke: A Systematic Review
Bibliographic record
Abstract
OBJECTIVES: The aim of this systematic review was to identify the presence and nature of relationships between specific forms of aprosodia (i.e., expressive and receptive emotional and linguistic prosodic deficits) and other cognitive-communication deficits and disorders in individuals with right hemisphere damage (RHD) due to stroke. METHODS: One hundred and ninety articles from 1970 to February 2020 investigating receptive and expressive prosody in patients with relatively focal right hemisphere brain damage were identified via database searches. RESULTS: Fourteen articles were identified that met inclusion criteria, passed quality reviews, and included sufficient information about prosody and potential co-occurring deficits. Twelve articles investigated receptive emotional aprosodia, and two articles investigated receptive linguistic aprosodia. Across the included studies, receptive emotional prosody was not systematically associated with hemispatial neglect, but did co-occur with deficits in emotional facial recognition, interpersonal interactions, or emotional semantics. Receptive linguistic processing was reported to co-occur with amusia and hemispatial neglect. No studies were found that investigated the co-occurrence of expressive emotional or linguistic prosodic deficits with other cognitive-communication impairments. CONCLUSIONS: This systematic review revealed significant gaps in the research literature regarding the co-occurrence of common right hemisphere disorders with prosodic deficits. More rigorous empirical inquiry is required to identify specific patient profiles based on clusters of deficits associated with right hemisphere stroke. Future research may determine whether the co-occurrences identified are due to shared cognitive-linguistic processes, and may inform the development of evidence-based assessment and treatment recommendations for individuals with cognitive-communication deficits subsequent to RHD.
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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 | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".