Adaptive Network Modeling for Criterial Causation

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

Propagation of activation of neurons depends on settings of a number of intrinsic char-acteristics of the network of neurons, such as synaptic connection strengths and excita-bility thresholds for neurons. These settings serve as criteria on the incoming signals for a neuron to get activated. As part of the plasticity of the neural processing these network characteristics also change over time. Such changes can be slow compared to propagation of activation, like in learning from a number of experiences, but they can also be fast, like in memory formation. From the informational perspective on the criteria, this can be considered a form of information formation, and the firing of neurons as driven by this information. This is called criterial causation. In this paper, an adaptive network model is presented modeling such criterial causation. Moreover, it is shown how criterial causation in the brain relates to the more general temporal factorisation principle for the world’s dynamics.
Original languageEnglish
Title of host publicationComplex Networks and Their Applications VIII
Subtitle of host publicationProceedings of the Eighth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2019
EditorsHocine Cherifi, Sabrina Gaito, José Fernendo Mendes, Esteban Moro, Luis Mateus Rocha
PublisherSpringer
Pages827-841
Number of pages15
Volume2
ISBN (Electronic)9783030366834
ISBN (Print)9783030366827
DOIs
Publication statusPublished - 10 Dec 2019

Publication series

NameStudies in Computational Intelligence
PublisherSpringer
Volume882

Fingerprint

Neurons
Chemical activation
Factorization
Plasticity
Brain
Data storage equipment
Processing

Cite this

Treur, J. (2019). Adaptive Network Modeling for Criterial Causation. In H. Cherifi, S. Gaito, J. F. Mendes, E. Moro, & L. M. Rocha (Eds.), Complex Networks and Their Applications VIII: Proceedings of the Eighth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2019 (Vol. 2, pp. 827-841). (Studies in Computational Intelligence ; Vol. 882). Springer. https://doi.org/10.1007%2F978-3-030-36683-4_66
Treur, Jan. / Adaptive Network Modeling for Criterial Causation. Complex Networks and Their Applications VIII: Proceedings of the Eighth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2019. editor / Hocine Cherifi ; Sabrina Gaito ; José Fernendo Mendes ; Esteban Moro ; Luis Mateus Rocha. Vol. 2 Springer, 2019. pp. 827-841 (Studies in Computational Intelligence ).
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Treur, J 2019, Adaptive Network Modeling for Criterial Causation. in H Cherifi, S Gaito, JF Mendes, E Moro & LM Rocha (eds), Complex Networks and Their Applications VIII: Proceedings of the Eighth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2019. vol. 2, Studies in Computational Intelligence , vol. 882, Springer, pp. 827-841. https://doi.org/10.1007%2F978-3-030-36683-4_66

Adaptive Network Modeling for Criterial Causation. / Treur, Jan.

Complex Networks and Their Applications VIII: Proceedings of the Eighth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2019. ed. / Hocine Cherifi; Sabrina Gaito; José Fernendo Mendes; Esteban Moro; Luis Mateus Rocha. Vol. 2 Springer, 2019. p. 827-841 (Studies in Computational Intelligence ; Vol. 882).

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

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Treur J. Adaptive Network Modeling for Criterial Causation. In Cherifi H, Gaito S, Mendes JF, Moro E, Rocha LM, editors, Complex Networks and Their Applications VIII: Proceedings of the Eighth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2019. Vol. 2. Springer. 2019. p. 827-841. (Studies in Computational Intelligence ). https://doi.org/10.1007%2F978-3-030-36683-4_66