发表机构
Max Planck Institute of Animal Behavior; University of Konstanz（马克斯·普朗克动物行为研究所; 康斯坦茨大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究将光谱学原理应用于动物决策，提出谐波理论并发现线索几何通过对称性选择规则决定可观测谐波，实验验证了该理论在多种动物及果蝇神经罗盘中的有效性。
AI 中文摘要
光谱学通过向系统发送结构化探针并测量返回信号来读取结构。在此，我们将这一原理应用于动物决策。谐波理论将选择视为在朝向角度景观上的运动，其傅里叶分量构成动物的决策光谱。我们表明，线索的排列以结构因子的形式进入该景观，因此其分解类似于衍射振幅，并且对称性施加了选择规则：p重线索阵列消除所有不是p的倍数的谐波，而将两个线索分开扫过会在每个谐波中产生一个凹口。线索几何成为可调探针：实验者设定实验能看到的谐波。我们从果蝇、群游鱼类、斑马鱼幼体、小鼠和一种游泳藻类的公开记录中读取这些光谱，并从果蝇的神经罗盘中读取，其中对称场景抑制被禁止的谐波，而打破对称性则恢复它们。测量罗盘形状因子有利于理论的平滑凸起而非其方形凸起，并且提高线索对比度在每只果蝇中收窄该凸起。拟合一个谐波的宽度随后预测下一个。线索几何是决策的光谱仪，对称性决定其所能观察到的内容。
英文摘要
Spectroscopy reads structure by sending a structured probe into a system and measuring what comes back. Here we apply this principle to animal decision-making. Harmonic Theory casts choice as motion on an angular landscape over heading, whose Fourier components form an animal's decision spectrum. We show that the arrangement of cues enters that landscape as a structure factor, so it factors like a diffraction amplitude, and symmetry imposes selection rules: a p-fold cue array annihilates every harmonic that is not a multiple of p, and sweeping two cues apart draws a notch through each harmonic. Cue geometry becomes a tunable probe: the experimenter sets which harmonics an experiment can see. We read these spectra from public recordings of flies, schooling fish, larval zebrafish, mice and a swimming alga, and from the fly's neural compass, where symmetric scenes suppress the forbidden harmonics and breaking that symmetry restores them. Measuring the compass form factor favours the theory's smooth bump over its square one, and raising cue contrast narrows that bump in every fly. A width fitted to one harmonic then predicts the next. Cue geometry is a spectrometer for decisions, and symmetry sets what it can see.
Comments41 pages, 8 figures
