Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy.
Department of Neurobiology and Behavior, Center for Neural Circuit Dynamics and Institute for Advanced Computational Science, State University of New York at Stony Brook, Stony Brook, NY, USA.
Cell Rep. 2021 Apr 6;35(1):108934. doi: 10.1016/j.celrep.2021.108934.
Cortical activity related to erroneous behavior in discrimination or decision-making tasks is rarely analyzed, yet it can help clarify which computations are essential during a specific task. Here, we use a hidden Markov model (HMM) to perform a trial-by-trial analysis of the ensemble activity of dorsolateral prefrontal cortex (PFdl) neurons of rhesus monkeys performing a distance discrimination task. By segmenting the neural activity into sequences of metastable states, HMM allows us to uncover modulations of the neural dynamics related to internal computations. We find that metastable dynamics slow down during error trials, while state transitions at a pivotal point during the trial take longer in difficult correct trials. Both these phenomena occur during the decision interval, with errors occurring in both easy and difficult trials. Our results provide further support for the emerging role of metastable cortical dynamics in mediating complex cognitive functions and behavior.
在判别或决策任务中与错误行为相关的皮质活动很少被分析，但它可以帮助阐明在特定任务期间哪些计算是必不可少的。在这里，我们使用隐马尔可夫模型（HMM）对执行距离判别任务的猕猴背外侧前额叶皮层（PFdl）神经元的整体活动进行逐试分析。通过将神经活动分割成亚稳态序列，HMM 允许我们发现与内部计算相关的神经动力学的调制。我们发现，错误试验期间亚稳态动力学减慢，而在试验的关键时刻的状态转换在困难正确试验中花费更长时间。这两种现象都发生在决策间隔期间，在简单和困难的试验中都会出现错误。我们的结果为亚稳态皮质动力学在介导复杂认知功能和行为方面的新兴作用提供了进一步的支持。
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