Speech Mismatch Negativity (MMN) in Schizophrenia with Auditory Verbal Hallucinations
Bibliographic record
Abstract
Auditory verbal hallucinations (AVH) are experienced by many individuals with schizophrenia (SZ), a neurodevelopmental disease that encumbers the quality of life and psychosocial outcome of those afflicted by it. While many hypotheses attempt to better define the etiology of AVHs in SZ, their neural profile and its moderation by current neuroleptics remains limited. The Mismatch Negativity (MMN) is an event related potential (ERP) measured from electroencephalographic (EEG) activity during the presentation of a deviance detection auditory paradigm. The neural regions and activity underlying the generation of the MMN include the primary auditory cortex and the prefrontal cortex which are regions also found to be activated during the experience of AVHs. Decreased MMN amplitudes have been robustly noted in SZ patients during the presentation of MMN tasks using auditory tones. However, the MMN generation to speech stimuli has not been extensively examined in SZ nor in relation to AVHs. The primary objective of this study was to examine the MMN to five speech-based deviants in SZ patients and healthy controls. Second, we assessed MMN features with AVH characteristics in 19 SZ patients and 21 HC. While AVH features did not correlate with measures of MMN, we found decreased MMN amplitudes to speech-based frequency and vowel change deviants in SZ patients compared to HC potentially reflecting deficiencies in basic speech processing mechanisms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 | 0.002 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".