发表机构
McGovern Institute for Brain Research, Massachusetts Institute of Technology; The NSF AI Institute for Artificial Intelligence and Fundamental Interactions (IAIFI)（麻省理工学院麦戈文脑研究所; 美国国家科学基金会人工智能基础相互作用研究所）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究提出冰神经元作为零增益界面模型，揭示生物神经元中几何、动力学与场相互塑造，场闭合增强远端持久性，区别于纯结构形态。
AI 中文摘要
树突轮廓是廉价的。池塘冰神经元、扩散限制聚集、最小化布线的树状结构以及生物神经元可以共享一个分支统计量，因为它们共享一种生长不稳定性，而非因为它们在功能上相似。我们将这一观察作为建模约束。冰神经元仅在结构上类似于生物神经元。生物神经元携带内部状态和它帮助生成的场，使几何、动力学和场相互共同塑造。在我们的构建中，冰神经元是界面系统的零增益极限，其中FitzHugh-Nagumo状态存在于移动前沿，并写回驱动它的场，具有无量纲增益$\gamma$。在$\gamma=0$时，形态和内部动力学解耦为Mullins-Sekerka生长带和阻尼振荡器。有限的$\gamma$使谱变形，改变选定的不稳定性，并在孤立的Hopf阈值以下打开振荡区域。在$\gamma=0$下生长然后冻结的树突上，场闭合增加远端持久性而不改变几何；其一阶效应在相同生长规则的重复实现中保持为正，并局限于少量非电缆场捷径。非线性动力学在线性不稳定性之外保持有限：在阈值以下，闭合几乎等同于传输；在尖峰幅度时，它是再生电缆事件的修正。因此，树突树本质上不是结构上的附属物。仅形状是没有内部状态或源项的形态。这就是冰神经元的树突轮廓。兴奋性增加了一个主动电缆。场闭合是生物物理混合体，其中神经元帮助编写作用于其自身的场，塑造其动力学，并在生长期间塑造其结构。这就是生物神经元。
英文摘要
Dendritic silhouettes are cheap. Pond ice neurons, diffusion-limited aggregates, wiring-minimizing arbors, and biological neurons can share a branching statistic because they share a growth instability, not because they are functionally similar. We take that observation as a modeling constraint. The ice neuron only structurally resembles a biological neuron. A biological neuron carries an internal state and a field that it helps generate, letting geometry, dynamics, and field co-sculpt one another. In our construction, the ice neuron is the zero-gain limit of an interfacial system in which a FitzHugh--Nagumo state lives on the moving front and writes back into the field that drives it, with dimensionless gain $γ$. At $γ=0$, morphology and internal dynamics decouple into a Mullins--Sekerka growth band and a damped oscillator. Finite $γ$ deforms the spectrum, shifts the selected instability, and opens an oscillatory region below the isolated Hopf threshold. On a dendrite grown at $γ=0$ and then frozen, field closure increases distal persistence without changing the geometry; its first-order effect remains positive across repeated realizations of the same growth rule and localizes to a small set of non-cable field shortcuts. Nonlinear dynamics remain finite beyond the linear instability: below threshold, closure is almost the transmission; at spike amplitude, it is a correction to a regenerative cable event. A dendritic tree therefore is not intrinsically a structural spandrel. Shape alone is morphology without an internal state or a source term. That is the dendritic silhouette of the ice neuron. Excitability adds an active cable. Field closure is the biophysical mélange in which the neuron helps write the field that acts back on it, sculpting its dynamics and, during growth, its structure. That is a biological neuron.
