Information Integration from Distributed Threshold-Based Interactions
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 intelligenc...
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| Format: | Article |
| Language: | English |
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Wiley
2017-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2017/7046359 |
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| _version_ | 1850110071583801344 |
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| author | Valmir C. Barbosa |
| author_facet | Valmir C. Barbosa |
| author_sort | Valmir C. Barbosa |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-47f34a0b7f4a43ea88bff120cd4b72a3 |
| institution | OA Journals |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-47f34a0b7f4a43ea88bff120cd4b72a32025-08-20T02:37:55ZengWileyComplexity1076-27871099-05262017-01-01201710.1155/2017/70463597046359Information Integration from Distributed Threshold-Based InteractionsValmir C. Barbosa0Programa de Engenharia de Sistemas e Computação, COPPE, Universidade Federal do Rio de Janeiro, Caixa Postal 68511, 21941-972 Rio de Janeiro, RJ, BrazilWe 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.http://dx.doi.org/10.1155/2017/7046359 |
| spellingShingle | Valmir C. Barbosa Information Integration from Distributed Threshold-Based Interactions Complexity |
| title | Information Integration from Distributed Threshold-Based Interactions |
| title_full | Information Integration from Distributed Threshold-Based Interactions |
| title_fullStr | Information Integration from Distributed Threshold-Based Interactions |
| title_full_unstemmed | Information Integration from Distributed Threshold-Based Interactions |
| title_short | Information Integration from Distributed Threshold-Based Interactions |
| title_sort | information integration from distributed threshold based interactions |
| url | http://dx.doi.org/10.1155/2017/7046359 |
| work_keys_str_mv | AT valmircbarbosa informationintegrationfromdistributedthresholdbasedinteractions |