Thinking without speaking: Neuropsychological testing with individuals who have communication impairments
Bibliographic record
Abstract
Cognitive ability may be masked by communication impairments. This study aimed to assess cognitive functioning using binary choice (i.e., yes/no) neuropsychological tests in patients with communication impairments. Four participants underwent neuropsychological testing. Two participants were in the minimally conscious state (MCS), one participant had locked-in syndrome and was an alternative communication user, and one participant was an augmentative communication user. There was better performance in all cognitive domains for the augmentative and alternative communication (AAC) users (who performed like the non-communication impaired normative data) compared to the MCS participants. However, using established yes/no communication methods, MCS participants performed above chance on a measure of memory and performance on measures of auditory comprehension was variable. Auditory comprehension appeared to be more influenced by working memory demands for the MCS participants than for the AAC users. For emotional functioning, the AAC users endorsed lower mood compared to the MCS participants. The results support the need to assess cognition, communication, as well as capacity in individuals with communication impairments with the consultation of a neuropsychologist and a speech-language pathologist.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".