TY - GEN
T1 - Adaptive Network Modeling for Criterial Causation
AU - Treur, Jan
PY - 2020
Y1 - 2020
N2 - Propagation of activation of neurons depends on settings of a number of intrinsic characteristics of the network of neurons, such as synaptic connection strengths and excitability 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.
AB - Propagation of activation of neurons depends on settings of a number of intrinsic characteristics of the network of neurons, such as synaptic connection strengths and excitability 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.
UR - http://www.scopus.com/inward/record.url?scp=85087855079&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85087855079&partnerID=8YFLogxK
UR - https://www.complexnetworks.org/
U2 - 10.1007/978-3-030-36683-4_66
DO - 10.1007/978-3-030-36683-4_66
M3 - Conference contribution
AN - SCOPUS:85087855079
SN - 9783030366827
VL - 2
T3 - Studies in Computational Intelligence
SP - 827
EP - 841
BT - Complex Networks and Their Applications VIII
A2 - Cherifi, Hocine
A2 - Gaito, Sabrina
A2 - Mendes, José Fernendo
A2 - Moro, Esteban
A2 - Rocha, Luis Mateus
PB - Springer
T2 - 8th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2019
Y2 - 10 December 2019 through 12 December 2019
ER -