A Meta-Analysis of Functional Neuroimaging Studies of Ketamine Administration in Healthy Volunteers
Bibliographic record
Abstract
Ketamine administration leads to a psychotomimetic state when taken in large bolus doses, making it a valid model of psychosis. Therefore, understanding ketamine's effects on brain functioning is particularly relevant. This meta-analysis focused on neuroimaging studies that examined ketamine-induced brain activation at rest and during a task. Included are 10 resting-state studies and 23 task-based studies, 9 of which were measuring executive functions. Using a stringent statistical threshold (TFCE <0.05), the results showed increased activity at rest in the dorsal anterior cingulate cortex (ACC), and increased activation of the right Heschl's gyrus during executive tasks, following ketamine administration. Uncorrected results showed increased activation at rest in the right (anterior) insula and the right-fusiform gyrus, as well as increased activation during executive tasks in the rostral ACC. Rest-state studies highlighted alterations in core hubs of the salience network, while task-based studies suggested an impact on task-irrelevant brain regions. Increased activation in the rostral ACC may indicate a failure to deactivate the default mode network during executive tasks following ketamine administration. The results are coherent with alterations found in schizophrenia, which confer external validity to the ketamine model of psychosis. Studies investigating the neural mechanisms of ketamine's antidepressant action are warranted.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.014 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".