M31. An Investigation of Feedback-Guided Decision-Making in Schizophrenia
Notice bibliographique
Résumé
Background: Evidence from probabilistic reinforcement learning tasks have revealed impaired reward-driven learning in schizophrenia. This has been examined exclusively in the context of binary probabilistic choice paradigms. In real-world decision-making, however, individuals must also make choices when there are more than 2 competing options that vary in the frequency and magnitude of potential rewards and losses. To advance our understanding of decision-making in schizophrenia, it is important to examine how patients manage choices in the face of concurrent rewards and losses—especially when the immediately rewarding choice is not necessarily the advantageous option in the long run. Thus, the current study examined Win-Stay/Lose-Shift (WSLS) behavior on the Iowa Gambling Task (IGT) in order to examine the influence of immediate rewards and losses in guiding real-world decision-making in schizophrenia. Methods: Fifty-one patients with schizophrenia and 39 healthy controls completed the IGT, as well as a series of cognitive and clinical measures. We assessed WSLS by quantifying trial-by-trial choice behavior following wins and losses. Total Win-Stay refers to the proportion of times the same deck was chosen immediately after a reward, whereas Total Lose-Shift is the proportion of choice-shifts after receiving a loss. Additionally, Advantageous Win-Stay and Lose-Shift variables were calculated in order to index optimal decision-making on the IGT. Results: Group comparisons revealed that patients demonstrated significantly lower Total Win-Stay rates (t = −3.3, P = .001), but higher Total Lose-Shift rates (t = 2.3, P = .026) compared to controls. This same effect was also seen for Advantageous WSLS rates. Further, patients made more disadvantageous choices, shifted their choices more often, and performed significantly worse on the task overall compared to controls. However, groups did not differ in total number of rewards or losses received. After partialling out the effects of working memory, correlational analyses revealed that for patients, depression and apathy severity were significantly related to lower Total Win-Stay rates, and higher levels of choice-shifting overall. Further, overall performance on the IGT was correlated with WSLS rates for both groups. Conclusion: The results of this study suggest that patients with schizophrenia experience impaired reward-driven decision-making in the context of multiple choices with concurrent gains and losses. This appears to be driven by a reduced propensity for Win-Stay behavior, accompanied by excessive Lose-Shift behavior. With the importance of reward processing and decision-making in generating goal-directed behavior, these findings suggest a potential mechanism contributing to the motivation deficits seen in schizophrenia.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».