认知悖论与大脑机制

E. Brändas
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摘要

哲学家和神经科学家普遍认为,大脑科学与心灵意识本质之间的主要障碍源于客观-主观二分法。此外,人们还通常从认识论价值和本体论存在属性的角度对自然科学进行分类。著名哲学家约翰-塞尔(John Searle)以不同的方式表述道:"自然界中没有图灵机!然而,伟大的物理学家约翰-阿奇博尔德-惠勒(John Archibald Wheeler)提出了著名的 "它来自比特"(it from bit)的论断,确实传授了一种与现实的真正本质略有不同的方法。为了调和这两种截然不同的描述,我们将根据自我参照原理,提出一幅不同的图景,并将其应用于脑-心问题。我们将展示这一原理是如何为日益复杂的物理系统之间的通信提供热量子比特语法,即 "比特自它"。总之,稳态情况会产生用于量化和存储信息的负熵口袋。通信协议包含了认知机制,显示出意想不到的等价关系,促使人们从根本上解释内克尔立方体、鲁宾花瓶和旋转舞者等一般光学幻觉。推导出的语法还体现了对最近观察到的十二角形大脑信号的有趣解构,该信号是由阿尼尔班-班迪奥帕德希(Anirban Bandyopadhyay)及其团队通过实验阐明的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cognitive paradoxes and brain mechanisms
It is generally agreed amongst philosophers and neuroscientists that the main obstacle between the science of the brain and the conscious nature of the mind is rooted in an objective-subjective dichotomy. It is further common to classify natural sciences in terms of their epistemological values and their ontological existential attributes. As a result, one concludes that a computer that is useful for studying nature, such as the conscious mind, is not itself part of nature, or as phrased differently by the noted philosopher, John Searle, ‘there are no Turing Machines in nature! However, the great physicist John Archibald Wheeler, by declaring the famous dictum, ‘it from bit’, did impart a somewhat different approach to the true nature of reality. To reconcile the two contrasting portraits, a different picture, based on the principle of self-reference, will be presented, and applied to the brain-mind problem. It is demonstrated how this principle imparts a thermo-qubit syntax, i.e., ‘bit from it’, for communication between increasingly more complex physical systems. Altogether, the steady state situation produces negentropic pockets for quantification and storage of information. The communication protocol entails cognition mechanisms that display unexpected equivalences that prompts fundamental interpretations of general optical illusions such as Necker’s cube, the Rubin vase, and the Spinning Dancer. The derived syntax also embodies an interesting deconstruction of the recently observed dodecanogram brain signal, experimentally elucidated by Anirban Bandyopadhyay and his team.
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