Higher-order adaptive dynamical system modeling of the role of epigenetics in substance use disorder

Dominik Schlöder; Sophie C.F. Hendrikse; Jan Treur

doi:10.1007/978-3-031-76516-2_35

Higher-order adaptive dynamical system modeling of the role of epigenetics in substance use disorder

Dominik Schlöder, Sophie C.F. Hendrikse, Jan Treur^*

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

Abstract

In this paper, we present a higher-order adaptive self-modelling network model developed to explain the role of epigenetics in the development and progression of Substance Use Disorder (SUD), particularly concerning cocaine addiction. The model includes multiple adaptive levels to simulate the complex dynamics of addiction progression, where pathways of higher orders of adaptivity adjust and regulate the characteristics of those in lower orders. This higher-order adaptive dynamical system is constructed following the self-modeling network model principle and is based on relevant neurobiological processes, including the role of the transcription factor CREB on the prodynorphin gene that is vital in modulating the epigenetic changes induced by cocaine abuse, which contribute to the persistent, long-term effects on the brain and behavior of an individual.

Original language	English
Title of host publication	Biologically inspired cognitive architectures 2024
Subtitle of host publication	Proceedings of the 15th annual meeting of the BICA society
Editors	Alexei V. Samsonovich, Tingting Liu
Publisher	Springer Cham
Pages	358-368
Number of pages	11
ISBN (Electronic)	9783031765162
ISBN (Print)	9783031765186, 9783031765155
DOIs	https://doi.org/10.1007/978-3-031-76516-2_35
Publication status	Published - 10 Dec 2024
Externally published	Yes
Event	15th annual international conference on brain-inspired cognitive architectures for artificial intelligence - Seattle, United States Duration: 13 Aug 2024 → 16 Aug 2024 Conference number: 15

Publication series

Name	Studies in computational intelligence
Publisher	Springer
Volume	477
ISSN (Print)	1860-949X
ISSN (Electronic)	1860-9503

Conference

Conference	15th annual international conference on brain-inspired cognitive architectures for artificial intelligence
Abbreviated title	BICA*AI 2024
Country/Territory	United States
City	Seattle
Period	13/08/24 → 16/08/24

Keywords

CREB
Dynorphin
Epigenetics
Network-Oriented Modeling
Prodynorphin
Substance Use Disorder

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-031-76516-2_35

Cite this

Schlöder, D., Hendrikse, S. C. F., & Treur, J. (2024). Higher-order adaptive dynamical system modeling of the role of epigenetics in substance use disorder. In A. V. Samsonovich, & T. Liu (Eds.), Biologically inspired cognitive architectures 2024: Proceedings of the 15th annual meeting of the BICA society (pp. 358-368). (Studies in computational intelligence; Vol. 477). Springer Cham. https://doi.org/10.1007/978-3-031-76516-2_35

Schlöder, Dominik ; Hendrikse, Sophie C.F. ; Treur, Jan. / Higher-order adaptive dynamical system modeling of the role of epigenetics in substance use disorder. Biologically inspired cognitive architectures 2024: Proceedings of the 15th annual meeting of the BICA society. editor / Alexei V. Samsonovich ; Tingting Liu. Springer Cham, 2024. pp. 358-368 (Studies in computational intelligence).

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title = "Higher-order adaptive dynamical system modeling of the role of epigenetics in substance use disorder",

abstract = "In this paper, we present a higher-order adaptive self-modelling network model developed to explain the role of epigenetics in the development and progression of Substance Use Disorder (SUD), particularly concerning cocaine addiction. The model includes multiple adaptive levels to simulate the complex dynamics of addiction progression, where pathways of higher orders of adaptivity adjust and regulate the characteristics of those in lower orders. This higher-order adaptive dynamical system is constructed following the self-modeling network model principle and is based on relevant neurobiological processes, including the role of the transcription factor CREB on the prodynorphin gene that is vital in modulating the epigenetic changes induced by cocaine abuse, which contribute to the persistent, long-term effects on the brain and behavior of an individual.",

keywords = "CREB, Dynorphin, Epigenetics, Network-Oriented Modeling, Prodynorphin, Substance Use Disorder",

author = "Dominik Schl{\"o}der and Hendrikse, \{Sophie C.F.\} and Jan Treur",

year = "2024",

month = dec,

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doi = "10.1007/978-3-031-76516-2\_35",

language = "English",

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series = "Studies in computational intelligence",

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editor = "Samsonovich, \{Alexei V.\} and Tingting Liu",

booktitle = "Biologically inspired cognitive architectures 2024",

note = "15th annual international conference on brain-inspired cognitive architectures for artificial intelligence, BICA*AI 2024 ; Conference date: 13-08-2024 Through 16-08-2024",

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Schlöder, D, Hendrikse, SCF & Treur, J 2024, Higher-order adaptive dynamical system modeling of the role of epigenetics in substance use disorder. in AV Samsonovich & T Liu (eds), Biologically inspired cognitive architectures 2024: Proceedings of the 15th annual meeting of the BICA society. Studies in computational intelligence, vol. 477, Springer Cham, pp. 358-368, 15th annual international conference on brain-inspired cognitive architectures for artificial intelligence, Seattle, Washington, United States, 13/08/24. https://doi.org/10.1007/978-3-031-76516-2_35

Higher-order adaptive dynamical system modeling of the role of epigenetics in substance use disorder. / Schlöder, Dominik; Hendrikse, Sophie C.F.; Treur, Jan.
Biologically inspired cognitive architectures 2024: Proceedings of the 15th annual meeting of the BICA society. ed. / Alexei V. Samsonovich; Tingting Liu. Springer Cham, 2024. p. 358-368 (Studies in computational intelligence; Vol. 477).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

TY - GEN

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AU - Schlöder, Dominik

AU - Hendrikse, Sophie C.F.

AU - Treur, Jan

N1 - Conference code: 15

PY - 2024/12/10

Y1 - 2024/12/10

N2 - In this paper, we present a higher-order adaptive self-modelling network model developed to explain the role of epigenetics in the development and progression of Substance Use Disorder (SUD), particularly concerning cocaine addiction. The model includes multiple adaptive levels to simulate the complex dynamics of addiction progression, where pathways of higher orders of adaptivity adjust and regulate the characteristics of those in lower orders. This higher-order adaptive dynamical system is constructed following the self-modeling network model principle and is based on relevant neurobiological processes, including the role of the transcription factor CREB on the prodynorphin gene that is vital in modulating the epigenetic changes induced by cocaine abuse, which contribute to the persistent, long-term effects on the brain and behavior of an individual.

AB - In this paper, we present a higher-order adaptive self-modelling network model developed to explain the role of epigenetics in the development and progression of Substance Use Disorder (SUD), particularly concerning cocaine addiction. The model includes multiple adaptive levels to simulate the complex dynamics of addiction progression, where pathways of higher orders of adaptivity adjust and regulate the characteristics of those in lower orders. This higher-order adaptive dynamical system is constructed following the self-modeling network model principle and is based on relevant neurobiological processes, including the role of the transcription factor CREB on the prodynorphin gene that is vital in modulating the epigenetic changes induced by cocaine abuse, which contribute to the persistent, long-term effects on the brain and behavior of an individual.

KW - CREB

KW - Dynorphin

KW - Epigenetics

KW - Network-Oriented Modeling

KW - Prodynorphin

KW - Substance Use Disorder

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DO - 10.1007/978-3-031-76516-2_35

M3 - Conference contribution

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SN - 9783031765155

T3 - Studies in computational intelligence

SP - 358

EP - 368

BT - Biologically inspired cognitive architectures 2024

A2 - Samsonovich, Alexei V.

A2 - Liu, Tingting

PB - Springer Cham

T2 - 15th annual international conference on brain-inspired cognitive architectures for artificial intelligence

Y2 - 13 August 2024 through 16 August 2024

ER -

Schlöder D, Hendrikse SCF, Treur J. Higher-order adaptive dynamical system modeling of the role of epigenetics in substance use disorder. In Samsonovich AV, Liu T, editors, Biologically inspired cognitive architectures 2024: Proceedings of the 15th annual meeting of the BICA society. Springer Cham. 2024. p. 358-368. (Studies in computational intelligence). doi: 10.1007/978-3-031-76516-2_35

Higher-order adaptive dynamical system modeling of the role of epigenetics in substance use disorder

Abstract

Publication series

Conference

Keywords

UN SDGs

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