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

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

Author information

1
Laboratory of Psychophysics, Brain Mind Institute, EPFL, Switzerland. Electronic address: adrien.doerig@gmail.com.
2
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.
3
Laboratory for Topology and Neuroscience, Brain Mind Institute, EPFL, Switzerland.
4
Laboratory of Psychophysics, Brain Mind Institute, EPFL, Switzerland.

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.

KEYWORDS:

Causal structure; Consciousness; IIT; Neural networks; RPT; Theories

PMID:
31078047
DOI:
10.1016/j.concog.2019.04.002
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