Brain Learning Principles Utilizing Non-Ideal Factors in Neural Circuits
Fuente:
arXiv
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866911537557405696 |
|---|---|
| author | Feng, Da-Zheng Du, Hao-Xuan |
| author_facet | Feng, Da-Zheng Du, Hao-Xuan |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_21542 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Brain Learning Principles Utilizing Non-Ideal Factors in Neural Circuits Feng, Da-Zheng Du, Hao-Xuan Neurons and Cognition 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. |
| title | Brain Learning Principles Utilizing Non-Ideal Factors in Neural Circuits |
| topic | Neurons and Cognition |
| url | https://arxiv.org/abs/2603.21542 |