Immediate effects of risperidone on cortico–striato–thalamic loops and the hippocampus
Bibliographic record
Abstract
BACKGROUND: Functional imaging studies indicate that delusions and hallucinations in schizophrenia are associated with overactivity of the left hippocampus and ventral striatum. Hippocampal neuronal firing modulates feedback to cortex via cortico-striato-thalamic loops. AIMS: To test the hypothesis that recovery from psychosis is associated with decrease in activity in cortico-striato-thalamic circuits, and, furthermore, that reduction in hippocampal activity predicts the degree of alleviation of delusions and hallucinations. METHOD: Positron emission tomography (PET) was used to measure the effects of the atypical antipsychotic, risperidone, on glucose metabolism in eight first-episode schizophrenia patients. RESULTS: A single dose of risperidone produced decreases in metabolism in ventral striatum, thalamus and frontal cortex. The magnitude of decreases in left hippocampus predicted subsequent reduction in delusions and hallucinations. After six weeks' treatment with risperidone, the decreases in frontal metabolism were more extensive. CONCLUSIONS: The mechanism of antipsychotic action of risperidone entails reduction of hippocampal activity together with reduced feedback via cortico-striato-thalamic loops.
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 | 0.000 | 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".