Mammalian brains respond to new concepts via a type of neural coding termed “concept coding.” During concept coding, the dentate gyrus (DG) plays a vital role in pattern separation and pattern integration of concepts because it is a brain region with substantial neurogenesis in adult mammals. Although concept coding properties of the brain have been extensively studied by experimental work, modeling of the process to guide both further experimental studies and applications such as natural language processing is scarce. To model brain-like concept coding, we built a spiking neural network inspired by adulthood neurogenesis in the DG. Our model suggests that neurogenesis may facilitate integration of closely related concepts and separation of less relevant concepts. Such pattern agrees with the previous experimental observations in classification tasks and place cells in the hippocampus. Therefore, our simulation provides insight for future experimental studies on the neural coding difference between perception and cognition. By presenting 14 contexts each containing 4 concepts to the network, we found that neural responses of the DG changed dynamically as the context repetition time increased and were eventually consistent with the category organization of humans. Thus, our work provides a new framework of word representation for the construction of brain-like knowledge map.

中文翻译：

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齿状回的成年神经发生的类脑概念编码模型。

哺乳动物的大脑通过一种称为“概念编码”的神经编码对新概念做出反应。在概念编码期间，齿状回（DG）在概念的模式分离和模式整合中起着至关重要的作用，因为它是成年哺乳动物中具有大量神经发生的大脑区域。尽管已经通过实验工作对大脑的概念编码特性进行了广泛研究，但仍然缺乏对过程进行建模以指导进一步的实验研究和应用（例如自然语言处理）的知识。为了模拟类似大脑的概念编码，我们建立了一个受DG中成年神经发生启发的尖峰神经网络。我们的模型表明，神经发生可能促进紧密相关概念的整合和较不相关概念的分离。这种模式与先前在分类任务中的实验观察结果一致，并将细胞放置在海马体中。因此，我们的仿真为感知和认知之间的神经编码差异的未来实验研究提供了见识。通过将14个上下文（每个包含4个概念）呈现给网络，我们发现DG的神经反应随着上下文重复时间的增加而动态变化，并且最终与人类的类别组织保持一致。因此，我们的工作为构建类似大脑的知识图谱提供了新的单词表示框架。通过将14个上下文（每个包含4个概念）呈现给网络，我们发现DG的神经反应随着上下文重复时间的增加而动态变化，并且最终与人类的类别组织保持一致。因此，我们的工作为构建类似大脑的知识图谱提供了新的单词表示框架。通过将14个上下文（每个包含4个概念）呈现给网络，我们发现DG的神经反应随着上下文重复时间的增加而动态变化，并且最终与人类的类别组织保持一致。因此，我们的工作为构建类似大脑的知识图谱提供了新的单词表示框架。