Desensitization Due to Overstimulation: A Second-Order Adaptive Network Model

Alex Korthouwer; David Noordberg; Jan Treur

doi:10.1007/978-3-030-77964-1_19

Desensitization Due to Overstimulation: A Second-Order Adaptive Network Model

Alex Korthouwer, David Noordberg, Jan Treur^*

^*Corresponding author for this work

Computer Science

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

176 Downloads (Pure)

Abstract

In this paper, a second-order adaptive network model is presented for the effects of supernormal stimuli. The model describes via the underlying mechanisms in the brain how responses on stimuli occur in absence of a supernormal stimulus. Moreover, it describes how these normal responses are lost after a supernormal stimulus occurs and due to that adaptive desensitization takes place. By simulated example scenarios, it was evaluated that the model describes the expected dynamics. By stationary point analysis correctness of the implemented model with respect to its design was verified.

Original language	English
Title of host publication	Computational Science – ICCS 2021
Subtitle of host publication	21st International Conference, Krakow, Poland, June 16–18, 2021, Proceedings, Part II
Editors	Maciej Paszynski, Dieter Kranzlmüller, Valeria V. Krzhizhanovskaya, Jack J. Dongarra, Peter M.A. Sloot
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	238-249
Number of pages	12
Volume	2
ISBN (Electronic)	9783030779641
ISBN (Print)	9783030779634
DOIs	https://doi.org/10.1007/978-3-030-77964-1_19
Publication status	Published - 2021
Event	21st International Conference on Computational Science, ICCS 2021 - Virtual, Online Duration: 16 Jun 2021 → 18 Jun 2021

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12743 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	21st International Conference on Computational Science, ICCS 2021
City	Virtual, Online
Period	16/06/21 → 18/06/21

Bibliographical note

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.

Keywords

Adaptive network model
Desensitization
Overstimulation

Access to Document

10.1007/978-3-030-77964-1_19

Korthouwer2021_Chapter_DesensitizationDueToOverstimulationFinal published version, 1.55 MBLicence: Article 25fa Dutch Copyright Act

https://www.researchgate.net/publication/350158983

Persistent URL (handle)

Persistent link

Cite this

Korthouwer, A., Noordberg, D., & Treur, J. (2021). Desensitization Due to Overstimulation: A Second-Order Adaptive Network Model. In M. Paszynski, D. Kranzlmüller, V. V. Krzhizhanovskaya, J. J. Dongarra, & P. M. A. Sloot (Eds.), Computational Science – ICCS 2021: 21st International Conference, Krakow, Poland, June 16–18, 2021, Proceedings, Part II (Vol. 2, pp. 238-249). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12743 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-77964-1_19

Korthouwer, Alex ; Noordberg, David ; Treur, Jan. / Desensitization Due to Overstimulation : A Second-Order Adaptive Network Model. Computational Science – ICCS 2021: 21st International Conference, Krakow, Poland, June 16–18, 2021, Proceedings, Part II. editor / Maciej Paszynski ; Dieter Kranzlmüller ; Valeria V. Krzhizhanovskaya ; Jack J. Dongarra ; Peter M.A. Sloot. Vol. 2 Springer Science and Business Media Deutschland GmbH, 2021. pp. 238-249 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{b8cba7240d724e2eb61b5b37e1662a6c,

title = "Desensitization Due to Overstimulation: A Second-Order Adaptive Network Model",

abstract = "In this paper, a second-order adaptive network model is presented for the effects of supernormal stimuli. The model describes via the underlying mechanisms in the brain how responses on stimuli occur in absence of a supernormal stimulus. Moreover, it describes how these normal responses are lost after a supernormal stimulus occurs and due to that adaptive desensitization takes place. By simulated example scenarios, it was evaluated that the model describes the expected dynamics. By stationary point analysis correctness of the implemented model with respect to its design was verified.",

keywords = "Adaptive network model, Desensitization, Overstimulation",

author = "Alex Korthouwer and David Noordberg and Jan Treur",

note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.; 21st International Conference on Computational Science, ICCS 2021 ; Conference date: 16-06-2021 Through 18-06-2021",

year = "2021",

doi = "10.1007/978-3-030-77964-1_19",

language = "English",

isbn = "9783030779634",

volume = "2",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "238--249",

editor = "Maciej Paszynski and Dieter Kranzlm{\"u}ller and Krzhizhanovskaya, {Valeria V.} and Dongarra, {Jack J.} and Sloot, {Peter M.A.}",

booktitle = "Computational Science – ICCS 2021",

address = "Germany",

}

Korthouwer, A, Noordberg, D & Treur, J 2021, Desensitization Due to Overstimulation: A Second-Order Adaptive Network Model. in M Paszynski, D Kranzlmüller, VV Krzhizhanovskaya, JJ Dongarra & PMA Sloot (eds), Computational Science – ICCS 2021: 21st International Conference, Krakow, Poland, June 16–18, 2021, Proceedings, Part II. vol. 2, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12743 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 238-249, 21st International Conference on Computational Science, ICCS 2021, Virtual, Online, 16/06/21. https://doi.org/10.1007/978-3-030-77964-1_19

Desensitization Due to Overstimulation: A Second-Order Adaptive Network Model. / Korthouwer, Alex; Noordberg, David; Treur, Jan.
Computational Science – ICCS 2021: 21st International Conference, Krakow, Poland, June 16–18, 2021, Proceedings, Part II. ed. / Maciej Paszynski; Dieter Kranzlmüller; Valeria V. Krzhizhanovskaya; Jack J. Dongarra; Peter M.A. Sloot. Vol. 2 Springer Science and Business Media Deutschland GmbH, 2021. p. 238-249 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12743 LNCS).

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

TY - GEN

T1 - Desensitization Due to Overstimulation

T2 - 21st International Conference on Computational Science, ICCS 2021

AU - Korthouwer, Alex

AU - Noordberg, David

AU - Treur, Jan

PY - 2021

Y1 - 2021

N2 - In this paper, a second-order adaptive network model is presented for the effects of supernormal stimuli. The model describes via the underlying mechanisms in the brain how responses on stimuli occur in absence of a supernormal stimulus. Moreover, it describes how these normal responses are lost after a supernormal stimulus occurs and due to that adaptive desensitization takes place. By simulated example scenarios, it was evaluated that the model describes the expected dynamics. By stationary point analysis correctness of the implemented model with respect to its design was verified.

AB - In this paper, a second-order adaptive network model is presented for the effects of supernormal stimuli. The model describes via the underlying mechanisms in the brain how responses on stimuli occur in absence of a supernormal stimulus. Moreover, it describes how these normal responses are lost after a supernormal stimulus occurs and due to that adaptive desensitization takes place. By simulated example scenarios, it was evaluated that the model describes the expected dynamics. By stationary point analysis correctness of the implemented model with respect to its design was verified.

KW - Adaptive network model

KW - Desensitization

KW - Overstimulation

UR - http://www.scopus.com/inward/record.url?scp=85111383000&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85111383000&partnerID=8YFLogxK

UR - https://m.youtube.com/watch?v=uuqW61xQwU4

U2 - 10.1007/978-3-030-77964-1_19

DO - 10.1007/978-3-030-77964-1_19

M3 - Conference contribution

AN - SCOPUS:85111383000

SN - 9783030779634

VL - 2

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 238

EP - 249

BT - Computational Science – ICCS 2021

A2 - Paszynski, Maciej

A2 - Kranzlmüller, Dieter

A2 - Krzhizhanovskaya, Valeria V.

A2 - Dongarra, Jack J.

A2 - Sloot, Peter M.A.

PB - Springer Science and Business Media Deutschland GmbH

Y2 - 16 June 2021 through 18 June 2021

ER -

Korthouwer A, Noordberg D, Treur J. Desensitization Due to Overstimulation: A Second-Order Adaptive Network Model. In Paszynski M, Kranzlmüller D, Krzhizhanovskaya VV, Dongarra JJ, Sloot PMA, editors, Computational Science – ICCS 2021: 21st International Conference, Krakow, Poland, June 16–18, 2021, Proceedings, Part II. Vol. 2. Springer Science and Business Media Deutschland GmbH. 2021. p. 238-249. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). Epub 2021 Jun 9. doi: 10.1007/978-3-030-77964-1_19

Desensitization Due to Overstimulation: A Second-Order Adaptive Network Model

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

Persistent URL (handle)

Other files and links

Fingerprint

Cite this