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Malte Schilling and Holk Cruse Avoid the hard problem: employment of mental simulation for prediction is already a crucial step article Barron and Klein emphasize the significance of a simulation-based account of planning ahead in cognition, tied to central circuits of the human and insect brain. They suggest that some invertebrates also possess the ability to plan ahead using internal body simulations. The authors connect this concept to consciousness, but without evidence that such abilities necessarily result in subjective experience. Instead of delving into subjective experience, the article proposes separating consciousness into access consciousness and reflexive consciousness, a view aligning with Barron and Klein’s. Modeling tests on simpler systems reveal that once a functional model of the body and environment is included, such systems can exhibit aspects of access consciousness. However, such modifications haven’t been observed in real-life insects. – AI-generated abstract.

Avoid the hard problem: employment of mental simulation for prediction is already a crucial step

Malte Schilling and Holk Cruse

Proceedings of the National Academy of Sciences, vol. 113, no. 27, 2016

Abstract

Barron and Klein emphasize the significance of a simulation-based account of planning ahead in cognition, tied to central circuits of the human and insect brain. They suggest that some invertebrates also possess the ability to plan ahead using internal body simulations. The authors connect this concept to consciousness, but without evidence that such abilities necessarily result in subjective experience. Instead of delving into subjective experience, the article proposes separating consciousness into access consciousness and reflexive consciousness, a view aligning with Barron and Klein’s. Modeling tests on simpler systems reveal that once a functional model of the body and environment is included, such systems can exhibit aspects of access consciousness. However, such modifications haven’t been observed in real-life insects. – AI-generated abstract.

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