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Volume 2017, Article ID 7046359, 14 pages
Research Article

Information Integration from Distributed Threshold-Based Interactions

Programa de Engenharia de Sistemas e Computação, COPPE, Universidade Federal do Rio de Janeiro, Caixa Postal 68511, 21941-972 Rio de Janeiro, RJ, Brazil

Correspondence should be addressed to Valmir C. Barbosa; rb.jrfu.soc@rimlav

Received 7 July 2016; Accepted 28 September 2016; Published 11 January 2017

Academic Editor: Dimitri Volchenkov

Copyright © 2017 Valmir C. Barbosa. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


We consider distributed units that interact by message-passing. Each message carries a tag and causes the receiving unit to send out messages as a function of the tags it has received and a threshold. This simple model abstracts some of the essential characteristics of several artificial intelligence systems and of biological systems epitomized by the brain. We study the integration of information inside a temporal window as the dynamics unfolds. We quantify information integration by the total correlation, relative to the window’s duration, of a set of random variables valued as a function of message arrival. Total correlation refers to the rise of information gain above that which the units achieve individually, being therefore related to some models of consciousness. We report on extensive computational experiments exploring the interrelations of the model’s parameters (two probabilities and the threshold). We find that total correlation can occur at significant fractions of the maximum possible value and reinterpret the model’s parameters in terms of the current best estimates of some quantities pertaining to cortical structure and dynamics. We find the resulting possibilities to be well aligned with the time frames within which percepts are thought to be processed and eventually rendered conscious.