解放军医学院学报2025，Vol.46Issue(1)：8-15,8.DOI:10.12435/j.issn.2095-5227.2024.111
感觉编码时空活动模式的类脑表达与计算——算法篇
Brain-inspired representation and computation for similarity structure from spatiotemporal patterns in sensory coding:Algorithms
摘要
Abstract
Based on a deep understanding of the visual encoding neurophysiological mechanisms between the retina,lateral geniculate body,and visual cortex of the brain,we have constructed a novel neural network-based brain-inspired intelligent unit architecture,laying a solid foundation for the implementation of large-scale integrated neural network-based brain-inspired models.This information theory foundation for our understanding of the expression and computation of brain sensory encoding is formed by the architecture of brain-inspired intelligent units.This article delves into the training methods,strategies,and specific algorithm examples of brain-inspired models,and proposes a comprehensive strategy that combines the redundancy reduction principle of sensory data flow expression and computation,self-organizing feature mapping,and recurrent oscillation synchronization mechanism,aiming to improve the biological rationality and interpretability of brain-inspired models,as well as efficiently and quickly mimic complex brain functions.关键词
冗余减少/压缩编码/稀疏编码/自组织映射/脑连接图/脑科学/类脑表达Key words
redundancy reduction/compression coding/sparse coding/self-organization mapping/brain connectivity map/brain science/brain-inspired representation分类
基础医学引用本文复制引用
王卫东..感觉编码时空活动模式的类脑表达与计算——算法篇[J].解放军医学院学报,2025,46(1):8-15,8.基金项目
新一代人工智能国家科技重大专项(2020AAA0105801) （2020AAA0105801）
