Abstract
In the previous works we analyzed and solved such problem of causal reflection of the outer world as a statistical ambiguity. We defined maximally specific causal relationships that have a property of an unambiguous inference: from consistent premises we infer consistent conclusions. We suppose that brain makes all possible inferences from causal relationships that produce a consistent model of the perceived world that shows up as consciousness. To discover maximally specific causal relationships by the brain, a formal model of neuron that is in line with Hebb rule was suggested. Causal relationships may create fixed points of cyclic inter-predictable attributes. We argue that, if we consider attributes of the outer world objects regardless of how we perceive them, a variety of fixed points of the objects’ attributes forms a “natural” classification of the outer world objects. And, if we consider fixed points of causal relationships between the stimuli of the objects we perceive, they form “natural” concepts described in cognitive sciences. And, if we consider the information processes of the brain when the system of causal relationships between object stimuli produces maximum integrated information, then this system may be considered as a fixed point which has a maximum consistency in the same sense as the entropic measure of integrated information. It was shown in other works that this model of consciousness explains purposeful behavior and perception.
The work is supported by the Russian Science Foundation grant № 17-11-01176.
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Vityaev, E. (2020). Consciousness as a Brain Complex Reflection of the Outer World Causal Relationships. In: Samsonovich, A. (eds) Biologically Inspired Cognitive Architectures 2019. BICA 2019. Advances in Intelligent Systems and Computing, vol 948. Springer, Cham. https://doi.org/10.1007/978-3-030-25719-4_72
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