揭开人脑视觉信息处理的神秘面纱
Unveiling the mystery of visual information processing in human brain
摘要：
人们普遍认为，人类视觉是一个极其强大的信息处理系统，它促进了我们与周围世界的互动。然而，尽管广泛和广泛的研究努力，其中包括许多探索领域，在人类大脑中的视觉信息处理的基本原理和操作原则仍然未知。我们仍然无法弄清楚从眼睛到大脑皮层的路径上，视网膜感知到的感觉输入在哪里以及如何转换成有意义的物体表征，这可以被大脑有意识地操纵。在研究了大量有关大脑信息处理各个方面的文献后，我惊讶地发现，那些受人尊敬的学术讨论对基本的主题问题完全漠不关心：“什么是信息？或者“什么是视觉信息？“尤其是。在过去，人们认为任何科学研究方法都必须首先确定其基本出发点。为什么在大脑信息处理研究中它被忽视了仍然是一个谜。在本文中，我试图为这种奇怪的情况找到一种补救办法。我提出了一个不寻常的定义的“信息”，它可以从Kolmogorov的复杂性理论和Chaitin的概念的计算机信息。接受这一新定义将不可避免地导致对传统教条的修正，这些教条塑造了大脑信息处理研究的艺术状态。我希望这一修订将更好地服务于人类视觉信息处理建模的挑战性目标。
英文摘要：
It is generally accepted that human vision is an extremely powerful information processing system that facilitates our interaction with the surrounding world. However, despite extended and extensive research efforts, which encompass many exploration fields, the underlying fundamentals and operational principles of visual information processing in human brain remain unknown. We still are unable to figure out where and how along the path from eyes to the cortex the sensory input perceived by the retina is converted into a meaningful object representation, which can be consciously manipulated by the brain. Studying the vast literature considering the various aspects of brain information processing, I was surprised to learn that the respected scholarly discussion is totally indifferent to the basic keynote question: "What is information?" in general or "What is visual information?" in particular. In the old days, it was assumed that any scientific research approach has first to define its basic departure points. Why was it overlooked in brain information processing research remains a conundrum. In this paper, I am trying to find a remedy for this bizarre situation. I propose an uncommon definition of "information", which can be derived from Kolmogorov's Complexity Theory and Chaitin's notion of Algorithmic Information. Embracing this new definition leads to an inevitable revision of traditional dogmas that shape the state of the art of brain information processing research. I hope this revision would better serve the challenging goal of human visual information processing modeling.
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。
