Causal Event Networks: Cognition, Complexity and Physical Laws

2014/02/26 by Vahid Ramezani, Ramezani, Vahid R.
Computer Science · #Cognitive Computing and Networks #Cognitive Science and Mapping #FOS: Biological sciences #Neural Networks and Applications #Neurons and Cognition (q-bio.NC)

paper · pdf · doi:10.48550/arxiv.1402.7038

openalex publication_date 2014/02/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Information flow framed in a computational and complexity context is relevant to the understanding of cognitive processes and awareness. In this paper, we begin with analyzing an information theory framework developed in recent years under Information and Integration Theory (IIT) based on interactions among partitions of cognitive information sets. We discuss the scope and limitations of these ideas, introducing a related measure for partitioning information sets. We introduce a set of postulates describing cognition as a partially ordered set of events in space and time. We consider the relevant sequential and concurrent computational concepts in an idealized minimal cognitive device. The concept of fundamental cognitive chain formalizes temporal limits of cognition.

Citations

• The role of primary visual cortex (V1) in visual awareness

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