Subanesthetic Ketamine Disrupts Predictive Signaling in the Prefrontal Cortex
Bibliographic record
Abstract
Abstract Corollary discharge (CD) signals allow the brain to predict and suppress the sensory consequences of its own actions, providing stability to perception and thought. Disruption of these predictive mechanisms has long been hypothesized to contribute to the disorganization of experience in schizophrenia, yet direct circuit-level evidence has been lacking. Here, we show that ketamine, a dissociative N-methyl-D-aspartate receptor (NMDAR) antagonist, at subanesthetic doses, selectively disrupts CD signaling in the lateral prefrontal cortex (LPFC)—a region thought to be the seed of mental representations and one of the most affected areas in schizophrenia. We recorded activity from 1,342 neurons in LPFC areas 8a and 9/46 of macaques performing a visuospatial working-memory task in a virtual environment, before and after subanesthetic ketamine administration. Ketamine impaired performance and increased overall firing rates but markedly suppressed saccade-related responses carrying CD signals. This led to decreased discriminability of eye movement signals. This finding links two major ideas in neuroscience research: the role of disrupted glutamate signaling and the failure of the brain’s predictive models. It provides evidence for how these mechanisms may interact in the prefrontal cortex to disturb the sense of reality.
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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 | 0.000 |
| 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".