Human vision research aims at understanding the brain processes that enable us to see the world as a structured whole consisting of separate objects. To explain how humans organize a visual pattern, structural information theory starts from the idea that our visual system prefers the organization with the simplest descriptive code, that is, the code that captures a maximum of visual regularity. Empirically, structural information theory gained support from psychological data on a wide variety of perceptual phenomena, but theoretically, the computation of guaranteed simplest codes remained a troubling problem. Here, the graph-theoretical concept of “hyperstrings” is presented as a key to the solution of this problem. A hyperstring is a distributed data structure that allows a search for regularity in O(2N) strings as if only one string of length N were concerned. Thereby, hyperstrings enable transparallel processing, a previously uncharacterized form of processing that might also be a form of cognitive processing.
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机译：人类视觉研究旨在了解大脑过程，使我们能够将世界视为由独立对象组成的结构化整体。为了解释人类如何组织视觉模式，结构信息理论从这样的想法开始，即我们的视觉系统更喜欢具有最简单描述性代码的组织，即能捕获最大视觉规律性的代码。从经验上讲，结构信息理论获得了关于各种感知现象的心理数据的支持，但是从理论上讲，保证最简单代码的计算仍然是一个令人困扰的问题。在这里，提出了“超弦”的图论概念，作为解决此问题的关键。超字符串是一种分布式数据结构，它允许在O（2 N ）个字符串中搜索规则性，就好像只关心一个长度为N的字符串一样。从而，超弦使得能够进行并行处理，这是先前未表征的处理形式，也可能是认知处理的形式。
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