Laboratory of Systems Neuroscience, Tohoku University Graduate School of Life Sciences, Aoba, Sendai 980-8577, Japan.
Department of Orthoptics, Kawasaki University of Medical Welfare, Matsushima, Kurashiki, Okayama 701-0913, Japan.
J Neurosci. 2022 Aug 17;42(33):6380-6391. doi: 10.1523/JNEUROSCI.2286-21.2022. Epub 2022 Jul 8.
Category-based thinking is a fundamental form of logical thinking. Here, we aimed to investigate its neural process at the local circuit level in the prefrontal cortex (PFC). We recorded single-unit PFC activity while male monkeys () performed a task in which the category and rule were prerequisites of logical thinking and the outcome contingency was its consequence. Different groups of neurons coded a single type of information discretely or multiple types in a transitional form. Results of time-by-time analysis of neuronal activity suggest an information flow from category-coding and rule-coding neurons to transitional intermediate neurons, and then to contingency-coding neurons. Category-coding, rule-coding, and contingency-coding neurons showed stable coding of information, whereas intermediate neurons showed dynamic coding, as if it integrated category and rule to derive contingency. A similar process was confirmed by using a spiking neural network model that consisted of subnetworks coding category and rule on the input layer and those coding contingency on the output layer, with a subnetwork for integration in the intermediate layer. These results suggest that category-based logical thinking is realized in the PFC by separated neural populations organized for working in a feedforward manner. To elucidate the neural process for logical thinking, we combined an in-depth analysis of single-unit activity data with a biologically plausible computational model. Results of time-by-time analysis of prefrontal neuronal activity suggest an information flow from category-coding and rule-coding neurons to transitional intermediate neurons, and then to contingency-coding neurons. Category-coding, rule-coding, and contingency-coding neurons showed stable coding, whereas intermediate neurons showed dynamic coding, as if they integrated category and rule to derive contingency. A spiking neural network model reproduced similar temporal changes of information as the recorded neuronal data. Our results suggest that the prefrontal cortex (PFC) is critically involved in category-based thought process, and this process may be produced by separated neural populations organized for working in a feedforward manner.
基于类别（category-based）的思维是逻辑思维的一种基本形式。在这里，我们旨在研究前额叶皮层（PFC）局部回路水平上的这种神经过程。当雄性猴子（）执行一项任务时，我们记录了单个 PFC 神经元的活动，其中类别和规则是逻辑思维的前提，而结果的必然性是其结果。不同组的神经元以离散的方式或过渡形式编码一种类型的信息。神经元活动的逐时分析结果表明，信息流从类别编码和规则编码神经元流向过渡中间神经元，然后流向必然性编码神经元。类别编码、规则编码和必然性编码神经元对信息进行稳定编码，而中间神经元则进行动态编码，好像它整合了类别和规则来推导必然性。使用包含输入层编码类别和规则的子网以及输出层编码必然性的子网以及中间层用于集成的子网的尖峰神经网络模型证实了类似的过程。这些结果表明，基于类别（category-based）的逻辑思维是通过组织成前馈方式工作的分离的神经元群体在 PFC 中实现的。为了阐明逻辑思维的神经过程，我们将单个神经元活动数据的深入分析与具有生物学合理性的计算模型相结合。前额叶神经元活动的逐时分析结果表明，信息流从类别编码和规则编码神经元流向过渡中间神经元，然后流向必然性编码神经元。类别编码、规则编码和必然性编码神经元对信息进行稳定编码，而中间神经元则进行动态编码，好像它们整合了类别和规则来推导必然性。尖峰神经网络模型再现了与记录神经元数据相似的信息时间变化。我们的结果表明，前额叶皮层（PFC）在基于类别的思维过程中起着至关重要的作用，这个过程可能是由组织成前馈方式工作的分离的神经元群体产生的。
