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展开的论点:为什么 IIT 和其他因果结构理论不能解释意识。

The unfolding argument: Why IIT and other causal structure theories cannot explain consciousness.

机构信息

Laboratory of Psychophysics, Brain Mind Institute, EPFL, Switzerland.

INSERM, Cognitive Neuroimaging Unit, NeuroSpin Center, Gif sur Yvette 91191, France; Commissariat à l'Energie Atomique, Direction des Sciences du Vivant, I2BM, NeuroSpin Center, Gif sur Yvette 91191, France; Department of Psychology, Crean College of Health and Behavioral Sciences, Chapman University, Orange, CA, USA; Institute for Interdisciplinary Brain and Behavioral Sciences, Chapman University, Irvine, CA, USA.

出版信息

Conscious Cogn. 2019 Jul;72:49-59. doi: 10.1016/j.concog.2019.04.002. Epub 2019 May 9.

Abstract

How can we explain consciousness? This question has become a vibrant topic of neuroscience research in recent decades. A large body of empirical results has been accumulated, and many theories have been proposed. Certain theories suggest that consciousness should be explained in terms of brain functions, such as accessing information in a global workspace, applying higher order to lower order representations, or predictive coding. These functions could be realized by a variety of patterns of brain connectivity. Other theories, such as Information Integration Theory (IIT) and Recurrent Processing Theory (RPT), identify causal structure with consciousness. For example, according to these theories, feedforward systems are never conscious, and feedback systems always are. Here, using theorems from the theory of computation, we show that causal structure theories are either false or outside the realm of science.

摘要

我们如何解释意识?这个问题在最近几十年已经成为神经科学研究的一个热门话题。大量的实证结果已经积累起来,许多理论也已经提出。某些理论认为,意识应该用大脑功能来解释,例如在全局工作空间中访问信息、将高级别表示应用于低级别表示,或者预测编码。这些功能可以通过多种模式的大脑连接来实现。其他理论,如信息整合理论(IIT)和循环处理理论(RPT),将因果结构与意识联系起来。例如,根据这些理论,前馈系统永远没有意识,而反馈系统总是有意识的。在这里,我们使用计算理论中的定理表明,因果结构理论要么是错误的,要么超出了科学的范围。

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