Guo Lei, Wang Zhixian, Song Yihua, Liu Huan
Tianjin Key Laboratory of Bioelectromagnetic Technology and Intelligent Health, School of Health Sciences and Biomedical Engineering, Hebei University of Technology, Tianjin 300131, China.
State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300131, China.
Biomimetics (Basel). 2025 Mar 6;10(3):162. doi: 10.3390/biomimetics10030162.
Specific neural coding (SNC) forms the basis of information processing in bio-brain, which generates distinct patterns of neural coding in response to corresponding exterior forms of stimulus. The performance of SNC is extremely dependent on brain-inspired models. However, the bio-rationality of a brain-inspired model remains inadequate. The purpose of this paper is to investigate a more bio-rational brain-inspired model and the SNC of this brain-inspired model. In this study, we construct a complex spiking neural network (CSNN) in which its topology has the small-word property and the scale-free property. Then, we investigated the SNC of CSNN under various strengths of various stimuli and discussed its mechanism. Our results indicate that (1) CSNN has similar neural time coding under same kind of stimulus; (2) CSNN has significant SNC based on time coding under various exterior stimuli; (3) our discussion implies that the inherent factor of SNC is synaptic plasticity.
特异性神经编码（SNC）构成了生物大脑中信息处理的基础，它会根据相应的外部刺激形式产生不同的神经编码模式。SNC的性能极度依赖于受大脑启发的模型。然而，受大脑启发的模型的生物合理性仍然不足。本文的目的是研究一种更具生物合理性的受大脑启发的模型以及该受大脑启发的模型的SNC。在本研究中，我们构建了一个复杂脉冲神经网络（CSNN），其拓扑结构具有小世界特性和无标度特性。然后，我们研究了CSNN在各种强度的各种刺激下的SNC，并讨论了其机制。我们的结果表明：（1）CSNN在同种刺激下具有相似的神经时间编码；（2）CSNN在各种外部刺激下基于时间编码具有显著的SNC；（3）我们的讨论表明SNC的内在因素是突触可塑性。
