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人类与啮齿动物神经元在持续活动表现上的比较:一项具有生物学合理性的计算研究

Comparison Between Human and Rodent Neurons for Persistent Activity Performance: A Biologically Plausible Computational Investigation.

作者信息

Zhang Qian, Zeng Yi, Zhang Tielin, Yang Taoyi

机构信息

Institute of Automation, Chinese Academy of Sciences (CAS), Beijing, China.

University of Chinese Academy of Sciences, Beijing, China.

出版信息

Front Syst Neurosci. 2021 Sep 9;15:628839. doi: 10.3389/fnsys.2021.628839. eCollection 2021.

Abstract

Elucidating the multi-scale detailed differences between the human brain and other brains will help shed light on what makes us unique as a species. Computational models help link biochemical and anatomical properties to cognitive functions and predict key properties of the cortex. Here, we present a detailed human neocortex network, with all human neuron parameters derived from the newest Allen Brain human brain cell database. Compared with that of rodents, the human neural network maintains more complete and accurate information under the same graphic input. Unique membrane properties in human neocortical neurons enhance the human brain's capacity for signal processing.

摘要

阐明人类大脑与其他大脑之间多尺度的详细差异,将有助于揭示使我们成为独特物种的因素。计算模型有助于将生化和解剖学特性与认知功能联系起来,并预测皮层的关键特性。在此,我们展示了一个详细的人类新皮层网络,其所有人类神经元参数均来自最新的艾伦脑库人类脑细胞数据库。与啮齿动物相比,人类神经网络在相同图形输入下能保持更完整、准确的信息。人类新皮层神经元独特的膜特性增强了人类大脑的信号处理能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e31/8459009/c83cb36f6a39/fnsys-15-628839-g001.jpg

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