SA109. Examining Reward Responsiveness and Expectancy Across a Dimension of Motivation Deficits in Schizophrenia
Bibliographic record
Abstract
Background: Anhedonia has long been associated with schizophrenia (SZ); however, the true nature of this deficit remains elusive. Given the role of hedonic capacity within the larger motivational framework, we sought to examine reward responsiveness (RR) and reward expectancy (RE) across a spectrum of motivation deficits in SZ (Study 1). Further, we sought to better understand the relationship between hedonic capacity and specific facets of the motivational system (Study 2). Methods: In study 1, RR and RE were assessed using the self-report Temporal Experience of Pleasure Scale (TEPS) in a sample of 72 SZ patients and 74 healthy controls. In study 2, 99 healthy undergraduate students completed the TEPS as well as objective measures of RR, RE, reward valuation, effort valuation, and goal-directed decision-making using the International Affective Picture System (IAPS), Cued Reinforcement Reaction Time (CRRT) task, Kirby Delay Discounting (DD) task, Virtual Reality Progressive Ratio (ViPR) task, and the Multitasking in the City Test (MCT), respectively. Further, the Schizotypal Personality Questionnaire (SPQ) was administered to characterize subclinical schizotypal traits. In both studies, the Apathy Evaluation Scale (AES) was used to characterize participants into low, moderate, and high amotivation groups. Results: In both studies, a multivariate analysis of variance revealed a main effect of amotivation such that participants with high levels of amotivation reported significantly lower levels of RR and RE compared to those at low and moderate levels (Study 1: F(4, 280) = 2.962, P = .02, η2 = .041; Study 2: F(4, 170) = 4.453, P = .002, η2 = .095). In Study 1, an interaction effect revealed that patients with moderate levels of amotivation endorsed significantly higher levels of RE compared to healthy controls at the same level, and to patients at both low and high levels of amotivation (F(2) = 2.674, P = .007). In Study 2, correlational analyses revealed that both RR (r = .32, P = .002) and RE (r = .38, P < .001) were correlated with IAPS pleasantness ratings. Further, RE was correlated with IAPS arousal ratings on the IAPS (r = .33, P = .001) and the ViPR task (r = −.25, P = .032). RE (r = −.37, P < .001) and IAPS pleasantness (r = −.31, P = .003) and arousal (r = −.34, P = .001) ratings were also correlated with the negative subscale of the SPQ. Conclusion: Overall, the results of both studies suggest that impairments in RR and RE emerge exclusively in individuals with high levels of motivation deficits, regardless of diagnosis. Further, Study 1 illustrates the complex relationship between self-reported RE, amotivation, and diagnosis. Correlational analyses in Study 2 suggest that emotional arousal and cost–benefit analyses are related to the evaluation of prospective rewards on the TEPS. Going forward, utilizing both subjective and objective measures of hedonic capacity may serve to further our understanding of the nuances of motivation and reward system impairments in SZ.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".