神经计算运行于循环校准下的耗散结构：一个关于睡眠的系统视角
Neural Computation Runs on Dissipative Structures Under Cyclic Calibration: A Systems Perspective on Sleep
一篇 arXiv 预印本提出，睡眠是神经计算在热力学约束下所需的系统性重校准阶段。清醒时神经活动持续消耗并破坏其赖以产生的低熵结构，导致增益、阈值和整合时间等信号参数漂移、计算精度下降；睡眠通过重校准功能—结构耦合来对抗熵漂移，从而维持跨活动周期的计算准确性。该视角将睡眠需求重新解释为神经计算在热力学约束下的涌现属性，并提出可检验的实证预测，尚未完成同行评审。
arXiv:2610.21486v1 Announce Type: new Abstract: Biological function operates far from thermodynamic equilibrium, sustained by metastable structures that continuously cycle through synthesis, function execution, and degradation--consuming energy and exporting entropy in the process. Neural computation exemplifies this dissipative organization, relying on low-entropy structures engaged in dynamic processes that define key information transfer and processing parameters such as gain, threshold, and integration time. This perspective proposes that sleep serves as a systemic recalibration phase required to reset crucial signaling parameters that drift during dissipative processing. During wakefulness, neural activity progressively consumes and disrupts the organization of the very substrate from which it emerges, leading to parameter drift and reduced computational precision. Sleep maintains computational accuracy across activity cycles by recalibrating function-structure coupling--that is, by counterbalancing entropic drift. Rather than explaining the experimentally observed sleep need through homeostatic regulation of unknown physiological variables, this perspective reframes it as an emergent property of neural computation under thermodynamic constraints.
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来源：arXiv q-bio.NC 预印本 · arxiv.org