Prior Haloperidol, but not Olanzapine, Exposure Augments the Pursuit of Reward Cues: Implications for Substance Abuse in Schizophrenia
Bibliographic record
Abstract
Drug abuse and addiction are excessively common in schizophrenia. Chronic antipsychotic treatment might contribute to this comorbidity by inducing supersensitivity within the brain's dopamine system. Dopamine supersensitivity can enhance the incentive motivational properties of reward cues, and reward cues contribute to the maintenance and severity of drug addiction. We have shown previously that rats withdrawn from continuous haloperidol (HAL) treatment (via subcutaneous minipump) develop dopamine supersensitivity and pursue reward cues more vigorously than HAL-naive rats following an amphetamine (AMPH) challenge. Atypical antipsychotic drugs are thought to be less likely than typicals to produce dopamine supersensitivity. Thus, we compared the effects of HAL and the atypical antipsychotic olanzapine (OLZ) on the pursuit of reward cues. Rats were trained to associate a light-tone cue with water then treated with HAL or OLZ. Following antipsychotic withdrawal, we assessed AMPH-induced enhancement of lever pressing for the cue. Withdrawal from HAL, but not from OLZ, enhanced this effect. HAL, but not OLZ, also enhanced AMPH-induced psychomotor activation and c-fos mRNA expression in the caudate-putamen. Thus, prior HAL, but not OLZ, enhanced conditioned reward following an AMPH challenge, and this was potentially linked to enhanced behavioral sensitivity to AMPH and AMPH-induced engagement of the caudate-putamen. These findings suggest that HAL, but not an atypical like OLZ, modifies reward circuitry in ways that increase responsiveness to reward cues. Because enhanced responsiveness to reward cues can promote drug-seeking behavior, it should be investigated whether atypical antipsychotics might be a preferential option in schizophrenic patients at risk for drug abuse or addiction.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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".