Reinforcement learning modeling reveals a reward-history-dependent strategy underlying reversal learning in squirrel monkeys.
Reinforcement learning modeling reveals a reward-history-dependent strategy underlying reversal learning in squirrel monkeys.
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DOI：
10.1037/bne0000492
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发表时间：
2022-03
影响因子：
1.9
通讯作者：
Bradberry CW
中科院分区：
文献类型：
--
作者：
Bari BA;Moerke MJ;Jedema HP;Effinger DP;Cohen JY;Bradberry CW
对精神疾病的洞察和治疗方法的发展依赖于研究多个物种中相似认知结构的行为任务。逆向学习任务是一种流行的范式，它探索灵活的行为，其畸变被认为是在许多疾病状态中很重要的。尽管广泛使用，但仍需要一种高通量的灵长类动物模型，可以弥合啮齿动物和人类之间的遗传，解剖和行为差距。在这里，我们训练松鼠猴，一个有前途的临床前模型，在图像引导的确定性逆转学习任务。我们发现，松鼠猴表现出其他物种的两个关键行为特征：在许多试验中整合奖励历史和特定于侧面的偏见。我们采用了一种强化学习模型，并证明它可以模拟松鼠猴子的行为，捕捉与训练相关的轨迹，并提供对动物所采用策略的洞察。这些结果验证了松鼠猴作为研究行为灵活性的模型。
Insight into psychiatric disease and development of therapeutics relies on behavioral tasks that study similar cognitive constructs in multiple species. The reversal learning task is one popular paradigm that probes flexible behavior, aberrations of which are thought to be important in a number of disease states. Despite widespread use, there is a need for a high-throughput primate model that can bridge the genetic, anatomic, and behavioral gap between rodents and humans. Here, we trained squirrel monkeys, a promising preclinical model, on an image-guided deterministic reversal learning task. We found that squirrel monkeys exhibited two key hallmarks of behavior found in other species: integration of reward history over many trials and a side-specific bias. We adapted a reinforcement learning model and demonstrated that it could simulate squirrel monkey-like behavior, capture training-related trajectories, and provide insight into the strategies animals employed. These results validate squirrel monkeys as a model in which to study behavioral flexibility.
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影响因子：
64.8
作者：
Daw, Nathaniel D.;O'Doherty, John P.;Dayan, Peter;Seymour, Ben;Dolan, Raymond J.
通讯作者：
Dolan, Raymond J.
影响因子：
4.3
作者：
Ebitz, R. Becket;Sleezer, Brianna J.;Hayden, Benjamin Y.
通讯作者：
Hayden, Benjamin Y.
影响因子：
16.2
作者：
Bari, Bilal A.;Grossman, Cooper D.;Cohen, Jeremiah Y.
通讯作者：
Cohen, Jeremiah Y.
DOI：
10.5334/cpsy.71
发表时间：
2021-01-01
期刊：
Computational psychiatry (Cambridge, Mass.)
影响因子：
--
作者：
Gershman, Samuel J;Lai, Lucy
通讯作者：
Lai, Lucy
影响因子：
3
作者：
Ballard, Ian C.;McClure, Samuel M.
通讯作者：
McClure, Samuel M.