Haloperidol, but Not Olanzapine, Impairs Cognitive Performance After Traumatic Brain Injury in Rats
Bibliographic record
Abstract
OBJECTIVE: Traumatic brain injury can cause a variety of impairments, including persistent alterations in personality, mood, and cognition. Antipsychotic agents are frequently used to treat pathologic behaviors in traumatic brain injury patients, but the influence of prolonged administration of such drugs on cognition after injury is unknown. The effects of two antipsychotic drugs on cognitive recovery after traumatic brain injury were assessed using the fluid percussion model in rats. DESIGN: The typical antipsychotic, haloperidol, and the third-generation antipsychotic, olanzapine, were administered via intraperitoneal injection beginning 24 hr after injury and continuing daily for the duration of the study. Morris water maze performance was assessed on days 11-15 postinjury. RESULTS: Haloperidol, an antagonist acting on D2-like dopamine receptors, exacerbated the cognitive deficits induced by injury, as injured rats treated with 0.30 mg/kg haloperidol performed worse in the Morris water maze than injured rats treated with vehicle. CONCLUSIONS: Our results demonstrate the importance of the D2 receptor in cognitive recovery after traumatic brain injury. Also, the data illustrate that some classes of antipsychotic drugs may influence cognitive recovery, and further research is needed to determine the optimal pharmacologic treatment of aggression, agitation, and other pathologic behaviors in patients with traumatic brain injury.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".