锥体神经元柱能否充当注意力头？一篇关于 Transformer 注意力头生物学构造的假说分析
Pyramidal Columns Acting as Attention Heads
AI 导读
这篇 arXiv 论文提出假说：后颞叶语言区（PTLRs）中一组恰当组织的锥体神经元柱，可能构成注意力头的神经形态机械实现之生物学构造。作者将 Transformer attention head 描述为通过输出-输入与输出-权重互连连接的简单神经网络系统，并考察了锥体柱内外的信号传递与调制机制如何对应支持这一构造。
正文 · 原文
Abstract:Can the functional architecture of a Transformer attention head be given a biological construction? More specifically, could a suitable group of pyramidal columns in posterior temporal language regions (PTLRs) constitute the biological construction of a neuromorphic mechanical realization of an attention head, under a mathematical instantiation that need not coincide with its standard Transformer instantiation? This paper investigates this hypothesis by examining possible correspondences between the functional organization of attention heads and neurophysiological mechanisms operating within and across pyramidal columns involved in human language processing. Our analysis builds on a mechanical-structural description of Transformer attention heads as systems of simple neural networks linked through output-input and output-weight interconnections. We examine the functional organization of an attention head and the input-dependent transformations it produces, and ask how the corresponding processing relations could be constructed in biological neural tissue. We then identify candidate neural mechanisms of signal transmission and modulation within and across pyramidal columns that may jointly support such a construction. On this basis, we propose that a suitably organized group of pyramidal columns in PTLRs could constitute a biological construction of a neuromorphic mechanical realization of an attention head. Whether the required functional organization actually exists in PTLRs remains an open empirical question. The hypothesis does not require the biological system to reproduce the standard mathematical instantiation of Transformer attention: the same functional architecture may be mechanically realized and mathematically instantiated in a different way, consistent with its biological construction.
| Comments: | v1: main text (20 pp., 7 figs.) and supplementary materials (12 figures) |
| Subjects: | Neurons and Cognition (q-bio.NC); Artificial Intelligence (cs.AI); Neural and Evolutionary Computing (cs.NE) |
| Cite as: | arXiv:2611.16057 [q-bio.NC] |
| (or arXiv:2611.16057v1 [q-bio.NC] for this version) | |
| https://doi.org/10.48550/arXiv.2611.16057 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Marco Giunti [view email]
[v1]
Wed, 11 Nov 2026 22:13:12 UTC (1,695 KB)
来源：arXiv cs.AI · arxiv.org