小柯机器人

小鼠在知觉决策过程中交替使用离散策略
2022-02-10 21:27

美国普林斯顿大学神经科学研究所Jonathan W. Pillow和Zoe C. Ashwood研究团队合作提出了小鼠在感知决策过程中交替使用离散策略。这一研究成果于2022年2月7日发表在国际顶尖学术期刊《自然—神经科学》上。

他们提出了新的分析,表明之前经典模型的普遍观点是不正确的。他们分析了来自小鼠和人类决策实验的数据,发现选择行为依赖于多种交错策略之间的相互作用。这些策略以隐马尔可夫模型中的状态为特征,在切换之前会持续数十到数百次试验,并且通常在一个会话中切换多次。确定的决策策略在小鼠之间高度一致,包括一个单一的“参与”状态,其中决策严重依赖于感觉刺激,以及几个经常发生错误的有偏见的状态。

这些结果为啮齿动物行为实验中经常观察到的“失误”提供了强有力的替代解释,并表明标准的绩效衡量标准掩盖了试验中战略重大变化的存在。

据悉,感知决策的经典模型假设受试者使用单一、一致的策略来形成决策,或者决策策略随着时间的推移缓慢演变。

附:英文原文

Title: Mice alternate between discrete strategies during perceptual decision-making

Author: Ashwood, Zoe C., Roy, Nicholas A., Stone, Iris R., Urai, Anne E., Churchland, Anne K., Pouget, Alexandre, Pillow, Jonathan W.

Issue&Volume: 2022-02-07

Abstract: Classical models of perceptual decision-making assume that subjects use a single, consistent strategy to form decisions, or that decision-making strategies evolve slowly over time. Here we present new analyses suggesting that this common view is incorrect. We analyzed data from mouse and human decision-making experiments and found that choice behavior relies on an interplay among multiple interleaved strategies. These strategies, characterized by states in a hidden Markov model, persist for tens to hundreds of trials before switching, and often switch multiple times within a session. The identified decision-making strategies were highly consistent across mice and comprised a single ‘engaged’ state, in which decisions relied heavily on the sensory stimulus, and several biased states in which errors frequently occurred. These results provide a powerful alternate explanation for ‘lapses’ often observed in rodent behavioral experiments, and suggest that standard measures of performance mask the presence of major changes in strategy across trials. 

DOI: 10.1038/s41593-021-01007-z

Source: https://www.nature.com/articles/s41593-021-01007-z

Nature Neuroscience:《自然—神经科学》,创刊于1998年。隶属于施普林格·自然出版集团,最新IF:28.771
官方网址:https://www.nature.com/neuro/
投稿链接:https://mts-nn.nature.com/cgi-bin/main.plex


本期文章:《自然—神经科学》:Online/在线发表

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