每条路径都算数，但有些更算数：秀丽隐杆线虫大脑的最大加视角
Every route counts, but some count more: a max-plus view of the C. elegans brain
常用连接组分析对所有路径求和，可能模糊掉维持内部状态的反馈回路。作者把神经信号视为路由而非扩散，用最大加代数建模秀丽隐杆线虫功能连接组，该连接组由电、突触、单胺、神经肽和激素层随时间变化组合而成，并在这一框架下分析五个网络。结果显示每个网络都收敛到少数主导反馈环路，既对应已知回路，也提示新的候选回路；作者据此提出脑状态可能位于格而非欧氏空间。该文为预印本，尚未经同行评审。
arXiv:2610.37587v1 Announce Type: cross Abstract: Brains do not simply add up every signal they receive: they select which routes dominate. Yet connectomes are usually analyzed with tools that sum over all paths and place neural states in Euclidean spaces, blurring the feedback circuits that may sustain internal states. Here we treat neural signaling as routing instead of diffusion and describe it with max-plus algebra, in which signals accumulate along a path and the strongest route prevails. We propose a model in which the functional connectome of Caenorhabditis elegans emerges from the time-varying combination of electrical, synaptic, monoaminergic, neuropeptidergic and hormonal layers, and analyze five networks within this framework. Each collapses onto a handful of dominant feedback loops, which recover well-characterized circuits and point to new candidates for experimental study. Unlike linear spectra, these structures keep the biological meaning of the data, and their order-based description suggests that brain states live in lattices rather than Euclidean spaces.
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来源：arXiv · Neural and Evolutionary Computing · arxiv.org