Babaev Olga, Cruces-Solis Hugo, Arban Roberto
Central Nervous System Diseases Research, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riß, Germany.
Central Nervous System Diseases Research, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riß, Germany.
Neuropharmacology. 2022 Jun 15;211:109056. doi: 10.1016/j.neuropharm.2022.109056. Epub 2022 Apr 6.
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.
开发针对精神分裂症和重度抑郁症患者所经历的动机缺陷的新疗法，需要在临床前模型中可靠评估与努力相关行为的程序。基于触摸屏的高通量测试与人类患者的计算机化评估相似，为建立具有高度转化效度的任务提供了一个平台。人们已经做出了相当大的努力来验证触摸屏版本的任务，这些任务测量动物为了获得奖励愿意投入的努力程度，比如渐进比率任务。虽然动机研究主要集中在报告断点的变化，但触摸屏评估允许收集多种测量数据，特别是如果有额外的任务适用于触摸屏环境的话。将这些测量数据分类到不同的行为子领域对于评估临床前模型是必要的。在这里，我们应用数据驱动的分类技术，从在渐进比率任务和我们在触摸屏箱中建立并验证的一个新的与努力相关的选择任务中获得的数据集中识别行为簇。此外，我们测量多巴胺水平的药理学操纵对描述与努力相关活动、非特异性活动、运动和与努力相关选择的各个行为子领域的影响，多巴胺是奖励和努力相关加工的关键调节因子。我们的方法扩展了基于触摸屏的动机症状临床前模型评估，识别了评估奖励驱动努力程度时最相关的行为测量指标，并有助于理解多巴胺在介导与努力相关动机的不同方面所起的作用。
