Refining the study of decision-making in animals: differential effects of d-amphetamine and haloperidol in a novel touchscreen-automated Rearing-Effort Discounting (RED) task and the Fixed-Ratio Effort Discounting (FRED) task

Lopez-Cruz, Laura; Phillips, Benjamin U; Hailwood, Jon M; Saksida, Lisa M; Heath, Christopher and Bussey, Timothy J (2023). Refining the study of decision-making in animals: differential effects of d-amphetamine and haloperidol in a novel touchscreen-automated Rearing-Effort Discounting (RED) task and the Fixed-Ratio Effort Discounting (FRED) task. Neuropsychopharmacology [Early Access].

DOI: https://doi.org/10.1038/s41386-023-01707-z

Abstract

Effort-based decision-making is impaired in multiple psychopathologies leading to significant impacts on the daily life of patients. Preclinical studies of this important transdiagnostic symptom in rodents are hampered, however, by limitations present in currently available decision-making tests, including the presence of delayed reinforcement and off-target cognitive demands. Such possible confounding factors can complicate the interpretation of results in terms of decision-making per se. In this study we addressed this problem using a novel touchscreen Rearing-Effort Discounting (RED) task in which mice choose between two single-touch responses: rearing up to touch an increasingly higher positioned stimulus to obtain a High Reward (HR) or touching a lower stimulus to obtain a Low Reward (LR). To explore the putative advantages of this new approach, RED was compared with a touchscreen version of the well-studied Fixed Ratio-based Effort Discounting (FRED) task, in which multiple touches are required to obtain an HR, and a single response is required to obtain an LR. Results from dopaminergic (haloperidol and d-amphetamine), behavioral (changes in the order of effort demand; fixed-ratio schedule in FRED or response height in RED), and dietary manipulations (reward devaluation by pre-feeding) were consistent with the presence of variables that may complicate interpretation of conventional decision-making tasks, and demonstrate how RED appears to minimize such variables.

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