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Research PaperResearchia:202603.24020

Brain Learning Principles Utilizing Non-Ideal Factors in Neural Circuits

Da-Zheng Feng

Abstract

The human brain achieves its remarkable computational prowess not despite its inherent non-ideal factors noise, heterogeneity, structural irregularities, decentralized plasticity, systematic errors, and chaotic dynamics but precisely because of them. This paper systematically demonstrates that these traits, long dismissed as imperfections in classical neuroscience and eliminated in digital engineering, are evolutionary design principles that endow the brain with robustness, adaptability, and cre...

Submitted: March 24, 2026Subjects: Neuroscience; Neuroscience

Description / Details

The human brain achieves its remarkable computational prowess not despite its inherent non-ideal factors noise, heterogeneity, structural irregularities, decentralized plasticity, systematic errors, and chaotic dynamics but precisely because of them. This paper systematically demonstrates that these traits, long dismissed as imperfections in classical neuroscience and eliminated in digital engineering, are evolutionary design principles that endow the brain with robustness, adaptability, and creativity.


Source: arXiv:2603.21542v1 - http://arxiv.org/abs/2603.21542v1 PDF: https://arxiv.org/pdf/2603.21542v1 Original Link: http://arxiv.org/abs/2603.21542v1

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Date:
Mar 24, 2026
Topic:
Neuroscience
Area:
Neuroscience
Comments:
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