Antipsychotic Medications: Linking Receptor Antagonism to Neuropsychological Functioning in First Episode Psychosis
Bibliographic record
Abstract
Antipsychotic medications can contribute to neurocognitive and motor impairments, but specific links to individualized pharmacological treatment regimens are unclear. In 68 participants with stabilized first-episode psychosis (FEP), we investigated the links between neuropsychological functions and an established anticholinergic potency index and a new D(2) antagonist potency index developed in our lab. Each participant's psychiatric medication regimen was converted into estimated receptor antagonist loads based upon specific medication dosage(s) and reported in vitro brain muscarinic cholinergic and D(2) receptor antagonism. In addition to the global neuropsychological impairments of FEP participants, the findings supported the hypothesized links between receptor antagonist loads and specific deficits. Higher anticholinergic load was associated with poorer delayed verbal memory but was not related to motor functioning. In contrast, higher D(2) load was associated with poorer motor functioning but not verbal memory. These selective antagonist load associations explained 19% of the variance in motor functioning and 17% of the variance in delayed verbal memory. Evidently, some of the neuropsychological impairments found in persons with FEP are selectively related to the specific pharmacodynamics and the dosing of their medication regimens. Moreover, these effects can be readily estimated from practical and inexpensive indices.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".