将弱集成信息理论分为启发和激励两种方法。

IF 3.1 Q1 PSYCHOLOGY, BIOLOGICAL Neuroscience of Consciousness Pub Date : 2023-05-17 eCollection Date: 2023-01-01 DOI:10.1093/nc/niad012
Angus Leung, Naotsugu Tsuchiya
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引用次数: 0

摘要

Mediano等人(弱综合信息论的强度)。趋势与认知科学2022;26:646-55.)将意识的综合信息理论(IIT)的强弱区分开来。他们将“强IIT”描述为试图推导出意识的通用公式,将“弱IIT”描述为寻找意识各方面的经验可测量的相关性。我们提出,他们对“弱IIT”的整体概念可能太弱了。相反,它应该被区分开来,以区分“抱负-IIT”,其目的是通过对其提出的措施进行权衡来对IIT进行实证测试,以及“IIT启发”方法,它采用IIT的高级思想,同时放弃其通过内省,第一原则方法达到的数学框架意识。
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Separating weak integrated information theory into inspired and aspirational approaches.

Mediano et al. (The strength of weak integrated information theory. Trends Cogn Sci 2022;26: 646-55.) separate out strong and weak flavours of the integrated information theory (IIT) of consciousness. They describe 'strong IIT' as attempting to derive a universal formula for consciousness and 'weak IIT' as searching for empirically measurable correlates of aspects of consciousness. We put forward that their overall notion of 'weak IIT' may be too weak. Rather, it should be separated out to distinguish 'aspirational-IIT', which aims to empirically test IIT by making trade-offs to its proposed measures, and 'IIT-inspired' approaches, which adopt high-level ideas of IIT while dropping the mathematical framework it reaches through its introspective, first-principles approach to consciousness.

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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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