高效神经生物学编码的时间平滑约束意味着时间特化
Temporal smoothness constraints on efficient neurobiological codes imply temporal specialization
神经子系统常在各自典型的时间尺度上变化，这种时间尺度差异是否与编码分工有关尚不清楚。作者提出一个高效编码模型，把系统变化快于自身典型时间尺度视为有能量代价，并精确求解最优分工。结果显示慢子系统应表征更慢变的时间特征，且最优编码的子系统表征彼此正交的时间特征，对应 Sturm-Liouville 问题的本征函数。该文为预印本，已被 NeurIPS 2026 接收。
arXiv:2610.36272v1 Announce Type: new Abstract: Neurobiological circuits may be energy efficient in part because there is a division of labor: different subsystems compute or represent different things. In light of this, it is interesting that a major difference between subsystems is the time scale on which they typically vary. Here, we argue that temporal smoothness constraints---the idea that it may be energetically costly for systems to vary much more quickly than their typical time scale---imply a certain division of labor with respect to temporal stimulus features. In particular, slow subsystems ought to represent slowly varying stimulus features, and fast subsystems ought to represent quickly varying features. We formulate a novel efficient coding model that we use to investigate this claim, and exactly solve for the optimal division of labor. In addition to finding that slower subsystems ought to represent more slowly varying temporal features, we find surprising structure of mathematical interest: optimal codes have subsystems which represent orthogonal temporal features, and which correspond to the eigenfunctions of a Sturm-Liouville problem.
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来源：arXiv q-bio.NC 预印本 · arxiv.org