Adaptive Networks at the Crossroad of Artificial Intelligence and Formal, Biological, Medical, and Social Sciences

Abstract

General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.

Modelling Metaplasticity and Memory Reconsolidation During an Eye-Movement Desensitization and Reprocessing Treatment

“…However, the focus on EMDR is new, and also addressing both plasticity and metaplasticity. By the new approach to adaptive networks by network reification and it dedicated generic software environment [41,42], in contrast to [14] it became possible to design the introduced adaptive network model at the modelling level without doing any programming. Moreover, in the same way this enabled to easily add (again without any programming) second-order adaptation to model metaplasticity that plays a crucial role in stress-related disorders, as shown by Garcia [17].…”

“…Y, representing causal impacts. The main elements of a temporal-causal network structure are the network structure characteristics for connectivity, aggregation and timing; see also [41,42].…”

“…Each network model is assigned a sequence of basic combination functions c j (..), j = 1, .., m. They are used for aggregation in the network. These basic combination functions are from an available library presented in [42].…”

“…The other planes depict the connectivity of the reification levels. The 3D representation shows how network reification is used in this model, representing the structure of a second-order adaptive network [41,42]. The first reification level of the adaptive network is used for adaptive links and modelled using Hebbian Learning [20] for the connections X !…”

“…In this study, a network-oriented modelling approach [41,42] is used to introduce a (second-order) adaptive temporal-causal network model in order to simulate EMDR treatment and its effects. The traumatic event, its resulting emotionality, stress regulation, the relevant plasticity and metaplasticity [1], and the effects of EMDR therapy, such as resource competition, are all covered by the introduced network model.…”