集成信息论中的非唯一性问题。

IF 3.1 Q1 PSYCHOLOGY, BIOLOGICAL Neuroscience of Consciousness Pub Date : 2023-01-01 DOI:10.1093/nc/niad014
Jake R Hanson, Sara I Walker
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引用次数: 0

摘要

集成信息理论(IIT) 3.0是当代神经科学中关于意识的主要理论之一。该理论的核心依赖于意识的标量数学度量的计算,Φ,其灵感来自该理论的现象学公理。在这里,我们表明,尽管它的广泛应用,Φ并不是一个定义良好的数学概念,因为它指定的值是非唯一的。为了证明这一点,我们引入了一种算法,该算法严格按照理论的数学定义计算给定系统的所有可能的Φ值。我们表明,到目前为止,所有公布的Φ值都是从众多同样有效的选项中任意选择的。至关重要的是,[公式:见文]和[公式:见文]经常同时被预测,使得对这些系统的任何解释都是有意识的或无意识的,在当前的IIT公式中是不可确定的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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On the non-uniqueness problem in integrated information theory.

Integrated Information Theory (IIT) 3.0 is among the leading theories of consciousness in contemporary neuroscience. The core of the theory relies on the calculation of a scalar mathematical measure of consciousness, Φ, which is inspired by the phenomenological axioms of the theory. Here, we show that despite its widespread application, Φ is not a well-defined mathematical concept in the sense that the value it specifies is non-unique. To demonstrate this, we introduce an algorithm that calculates all possible Φ values for a given system in strict accordance with the mathematical definition from the theory. We show that, to date, all published Φ values under consideration are selected arbitrarily from a multitude of equally valid alternatives. Crucially, both [Formula: see text] and [Formula: see text] are often predicted simultaneously, rendering any interpretation of these systems as conscious or not, non-decidable in the current formulation of IIT.

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来源期刊
Neuroscience of Consciousness
Neuroscience of Consciousness Psychology-Clinical Psychology
CiteScore
6.90
自引率
2.40%
发文量
16
审稿时长
19 weeks
期刊最新文献
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