Dissociating speech perception and comprehension at reduced levels of awareness
Bibliographic record
Abstract
We used functional MRI and the anesthetic agent propofol to assess the relationship among neural responses to speech, successful comprehension, and conscious awareness. Volunteers were scanned while listening to sentences containing ambiguous words, matched sentences without ambiguous words, and signal-correlated noise (SCN). During three scanning sessions, participants were nonsedated (awake), lightly sedated (a slowed response to conversation), and deeply sedated (no conversational response, rousable by loud command). Bilateral temporal-lobe responses for sentences compared with signal-correlated noise were observed at all three levels of sedation, although prefrontal and premotor responses to speech were absent at the deepest level of sedation. Additional inferior frontal and posterior temporal responses to ambiguous sentences provide a neural correlate of semantic processes critical for comprehending sentences containing ambiguous words. However, this additional response was absent during light sedation, suggesting a marked impairment of sentence comprehension. A significant decline in postscan recognition memory for sentences also suggests that sedation impaired encoding of sentences into memory, with left inferior frontal and temporal lobe responses during light sedation predicting subsequent recognition memory. These findings suggest a graded degradation of cognitive function in response to sedation such that "higher-level" semantic and mnemonic processes can be impaired at relatively low levels of sedation, whereas perceptual processing of speech remains resilient even during deep sedation. These results have important implications for understanding the relationship between speech comprehension and awareness in the healthy brain in patients receiving sedation and in patients with disorders of consciousness.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".