三维空间认知：蜜蜂与蝙蝠
Three Dimensional Spatial Cognition: Bees and Bats
AI总结：
本研究构建了基于视觉/回声定位的3D空间最优贝叶斯模型，提出更适配动物大脑的跟踪近似模型，并论证波激发存储空间记忆的可行性与相关神经证据。
摘要：
本文描述了一个在马尔（Marr）1982年提出的第二层级上，通过视觉（针对蜜蜂）或回声定位（针对蝙蝠）计算最优3D空间贝叶斯模型的程序。该模型利用了强贝叶斯先验概率：当动物移动时，大多数其他物体不会移动。物体的3D位置通过连续的视觉观测或回声计算得出，即通过动物运动恢复结构（SFM）。该程序可下载运行。本文还计算了一种跟踪近似模型，相较于完整贝叶斯计算，它更适合动物大脑处理。仅当空间记忆存储误差较小时，跟踪模型的性能才接近完整贝叶斯模型。神经存储空间位置的误差水平过高，且速度过慢。另一种方案是，空间3D模型可以以波激发的形式存储，即真实空间的傅里叶变换形式。这种方式能提供高记忆容量与高精度，同时空间失真低、响应速度快、计算更简单。本文总结了相关论文的证据，表明波激发形式的空间记忆存在于哺乳动物丘脑以及昆虫大脑的中央体中。
英文摘要：
The paper describes a program which computes the best possible Bayesian model of 3D space from vision (in bees) or echo location (in bats), at Marrs [1982] Level 2. The model exploits the strong Bayesian prior probability that most other things do not move, as the animal moves. 3D locations of things are computed from successive sightings or echoes, computing structure from the animals motion (SFM). The program can be downloaded and run. It also computes a tracking approximate model, which is more tractable for animal brains than the full Bayesian computation. The tracking model is nearly as good as the full Bayesian model, but only if spatial memory storage errors are small. Neural storage of spatial positions gives too high error levels, and is too slow. Alternatively, a 3D model of space could be stored in a wave excitation, as a Fourier transform of real space. This could give high memory capacity and precision, with low spatial distortion, fast response, and simpler computation. Evidence is summarized from related papers that a wave excitation holds spatial memory in the mammalian thalamus, and in the central body of the insect brain.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
