Ashwood Zoe C, Roy Nicholas A, Stone Iris R, Urai Anne E, Churchland Anne K, Pouget Alexandre, Pillow Jonathan W
Deptartment of Computer Science, Princeton University, Princeton, NJ, USA.
Princeton Neuroscience Institute, Princeton, NJ, USA.
Nat Neurosci. 2022 Feb;25(2):201-212. doi: 10.1038/s41593-021-01007-z. Epub 2022 Feb 7.
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.
传统的感知决策模型假定,受试者采用单一、一致的策略来做出决策,或者决策策略会随着时间缓慢演变。在此,我们展示的新分析表明,这种普遍观点是错误的。我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。这些策略以隐藏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,并且在一个实验环节中常常会多次切换。所识别出的决策策略在小鼠之间高度一致,包括一个单一的“专注”状态,在此状态下决策严重依赖感觉刺激,以及几个偏差状态,在这些状态下错误频繁发生。这些结果为在啮齿动物行为实验中经常观察到的“失误”提供了一个有力的替代性解释,并表明标准的绩效衡量指标掩盖了跨试验中策略的重大变化。