An Adaptive Cognitive Temporal-Causal Model for Extreme Emotion Extinction Using Psilocybin

Seyed Sahand Mohammadi Ziabari; Jan Treur

doi:10.1007/978-3-030-31362-3_18

An Adaptive Cognitive Temporal-Causal Model for Extreme Emotion Extinction Using Psilocybin

Seyed Sahand Mohammadi Ziabari^*, Jan Treur

^*Corresponding author for this work

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

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Abstract

In this paper, an adaptive cognitive temporal-causal model using psilocybin for a reduction in extreme emotion is presented. Extreme emotion has an effect on some brain components such as visual cortex, auditory cortex, gustatory cortex, and somatosensory cortex as well as motor cortex such as primary motor cortex, and premotor cortex. Neuroscientific literature reviews show that using psilocybin has a significant effect mostly on two brain components, cerebral cortex, and thalamus. Network-oriented modeling via temporal-causal network-oriented modeling is presented to show the influences of using psilocybin on the cognitive part of the body, same as the brain components. Hebbian learning used to show the adaptivity and learning section of the presented model.

Original language	English
Title of host publication	Computational Statistics and Mathematical Modeling Methods in Intelligent Systems
Subtitle of host publication	Proceedings of 3rd Computational Methods in Systems and Software 2019
Editors	Radek Silhavy, Petr Silhavy, Zdenka Prokopova
Publisher	Springer
Pages	176-186
Number of pages	11
Volume	2
ISBN (Electronic)	9783030313623
ISBN (Print)	9783030313616
DOIs	https://doi.org/10.1007/978-3-030-31362-3_18
Publication status	Published - 2019
Event	3rd Computational Methods in Systems and Software, CoMeSySo 2019 - Zlin, Czech Republic Duration: 10 Sept 2019 → 12 Sept 2019

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	1047
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	3rd Computational Methods in Systems and Software, CoMeSySo 2019
Country/Territory	Czech Republic
City	Zlin
Period	10/09/19 → 12/09/19

Keywords

Extreme emotion
Network-oriented modeling
Psilocybin
Temporal-causal network

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10.1007/978-3-030-31362-3_18

MohammadiZiabari-Treur2019_Chapter_AnAdaptiveCognitiveTemporalCausalModelFinal published version, 599 KBLicence: Article 25fa Dutch Copyright Act

https://www.researchgate.net/publication/333610177

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Mohammadi Ziabari, S. S., & Treur, J. (2019). An Adaptive Cognitive Temporal-Causal Model for Extreme Emotion Extinction Using Psilocybin. In R. Silhavy, P. Silhavy, & Z. Prokopova (Eds.), Computational Statistics and Mathematical Modeling Methods in Intelligent Systems: Proceedings of 3rd Computational Methods in Systems and Software 2019 (Vol. 2, pp. 176-186). (Advances in Intelligent Systems and Computing; Vol. 1047). Springer. https://doi.org/10.1007/978-3-030-31362-3_18

Mohammadi Ziabari, Seyed Sahand ; Treur, Jan. / An Adaptive Cognitive Temporal-Causal Model for Extreme Emotion Extinction Using Psilocybin. Computational Statistics and Mathematical Modeling Methods in Intelligent Systems: Proceedings of 3rd Computational Methods in Systems and Software 2019. editor / Radek Silhavy ; Petr Silhavy ; Zdenka Prokopova. Vol. 2 Springer, 2019. pp. 176-186 (Advances in Intelligent Systems and Computing).

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title = "An Adaptive Cognitive Temporal-Causal Model for Extreme Emotion Extinction Using Psilocybin",

abstract = "In this paper, an adaptive cognitive temporal-causal model using psilocybin for a reduction in extreme emotion is presented. Extreme emotion has an effect on some brain components such as visual cortex, auditory cortex, gustatory cortex, and somatosensory cortex as well as motor cortex such as primary motor cortex, and premotor cortex. Neuroscientific literature reviews show that using psilocybin has a significant effect mostly on two brain components, cerebral cortex, and thalamus. Network-oriented modeling via temporal-causal network-oriented modeling is presented to show the influences of using psilocybin on the cognitive part of the body, same as the brain components. Hebbian learning used to show the adaptivity and learning section of the presented model.",

keywords = "Extreme emotion, Network-oriented modeling, Psilocybin, Temporal-causal network",

author = "{Mohammadi Ziabari}, {Seyed Sahand} and Jan Treur",

year = "2019",

doi = "10.1007/978-3-030-31362-3_18",

language = "English",

isbn = "9783030313616",

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series = "Advances in Intelligent Systems and Computing",

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pages = "176--186",

editor = "Radek Silhavy and Petr Silhavy and Zdenka Prokopova",

booktitle = "Computational Statistics and Mathematical Modeling Methods in Intelligent Systems",

note = "3rd Computational Methods in Systems and Software, CoMeSySo 2019 ; Conference date: 10-09-2019 Through 12-09-2019",

}

Mohammadi Ziabari, SS & Treur, J 2019, An Adaptive Cognitive Temporal-Causal Model for Extreme Emotion Extinction Using Psilocybin. in R Silhavy, P Silhavy & Z Prokopova (eds), Computational Statistics and Mathematical Modeling Methods in Intelligent Systems: Proceedings of 3rd Computational Methods in Systems and Software 2019. vol. 2, Advances in Intelligent Systems and Computing, vol. 1047, Springer, pp. 176-186, 3rd Computational Methods in Systems and Software, CoMeSySo 2019, Zlin, Czech Republic, 10/09/19. https://doi.org/10.1007/978-3-030-31362-3_18

An Adaptive Cognitive Temporal-Causal Model for Extreme Emotion Extinction Using Psilocybin. / Mohammadi Ziabari, Seyed Sahand; Treur, Jan.

Computational Statistics and Mathematical Modeling Methods in Intelligent Systems: Proceedings of 3rd Computational Methods in Systems and Software 2019. ed. / Radek Silhavy; Petr Silhavy; Zdenka Prokopova. Vol. 2 Springer, 2019. p. 176-186 (Advances in Intelligent Systems and Computing; Vol. 1047).

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

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AB - In this paper, an adaptive cognitive temporal-causal model using psilocybin for a reduction in extreme emotion is presented. Extreme emotion has an effect on some brain components such as visual cortex, auditory cortex, gustatory cortex, and somatosensory cortex as well as motor cortex such as primary motor cortex, and premotor cortex. Neuroscientific literature reviews show that using psilocybin has a significant effect mostly on two brain components, cerebral cortex, and thalamus. Network-oriented modeling via temporal-causal network-oriented modeling is presented to show the influences of using psilocybin on the cognitive part of the body, same as the brain components. Hebbian learning used to show the adaptivity and learning section of the presented model.

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Mohammadi Ziabari SS, Treur J. An Adaptive Cognitive Temporal-Causal Model for Extreme Emotion Extinction Using Psilocybin. In Silhavy R, Silhavy P, Prokopova Z, editors, Computational Statistics and Mathematical Modeling Methods in Intelligent Systems: Proceedings of 3rd Computational Methods in Systems and Software 2019. Vol. 2. Springer. 2019. p. 176-186. (Advances in Intelligent Systems and Computing). Epub 2019 Sept 20. doi: 10.1007/978-3-030-31362-3_18

An Adaptive Cognitive Temporal-Causal Model for Extreme Emotion Extinction Using Psilocybin

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