Development of novel treatments for motivational deficits experienced by individuals with schizophrenia and major depressive disorder requires procedures that reliably assess effort-related behavior in pre-clinical models. High-throughput touchscreen-based testing, that parallels the computerized assessment of human patients, offers a platform for the establishment of tasks with high level of translational validity. Considerable efforts have been made to validate the touchscreen version of tasks that measure the degree of effort an animal is willing to invest for a reward, such as progressive ratio task. While motivational studies primarily focus on reporting alterations of a breakpoint, touchscreen assessment allows to collect multiple measures, especially if additional tasks would be adapted to the touchscreen environment. Classifying these measures to distinct behavioral subdomains is necessary for an evaluation of pre-clinical models. Here we apply data-driven classification techniques to identify behavioral clusters from dataset obtained in progressive ratio task and a novel effort-related choice task that we established and validated in the touchscreen boxes. Moreover, we measure the effect of pharmacological manipulations of the level of dopamine, a key regulator of reward- and effort-related processing, on individual behavioral subdomains that describe effort-related activity, non-specific activity, locomotion, and effort-related choice. Our approach expands the touchscreen-based assessment of pre-clinical models of motivational symptoms, identifies the most relevant behavioral measures in assessing the degree of reward-driven effort and contributes to the understanding of the role of dopamine in mediating distinct aspects of effort-related motivation.
Keywords: Dopamine; Effort-discounting task; Motivation; Negative symptoms; Progressive ratio; Touchscreen.
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