Cognitive modes underlying attentional control deficits in schizophrenia: A functional magnetic resonance imaging (fMRI) study
Bibliographic record
Abstract
The current functional magnetic resonance imaging (fMRI) study examined the anatomical and functional patterns associated with attentional control deficits in schizophrenia. Participants completed a trivalent task switching paradigm in which they alternatively completed three tasks (i.e., identify colour, parity, or letter case), while viewing stimuli with one (univalent), two (bivalent), or three (trivalent) dimension(s). This required participants to counteract their attentional capture by biasing their attention away from up to two task-irrelevant dimensions. Three cognitive modes emerged via constrained principal component analysis (CPCA): (1) Multiple Demand (MD), (2) Language (LAN), and (3) Default Mode B (DM-B). Relative to neurotypical participants, patients with schizophrenia showed impaired task performance, muted but sustained activation of the MD mode, hypoactivation of the LAN mode, and hyperdeactivation of the DM-B mode. Moreover, the muted and sustained activation of the MD mode was associated with higher scores on hallucinations and delusions, while the hypoactivation of the LAN mode and the hyperdeactivation of the DM-B mode were associated with higher scores on poverty of speech and flattened affect. Thus, attentional biasing impairments in schizophrenia may reflect reduced engagement of task-positive MD and LAN modes and excessive suppression of task-negative DM-B mode, with mode-specific associations to symptom severity.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".