Free-Energy Model of Emotion Potential: Modeling Arousal Potential as Information Content Induced by Complexity and Novelty

Appropriate levels of arousal potential induce hedonic responses (i.e., emotional valence). However, the relationship between arousal potential and its factors (e.g., novelty, complexity, and uncertainty) have not been formalized. This paper proposes a mathematical model that explains emotional arou...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autor principal:	Hideyoshi Yanagisawa
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	emotion free energy bayes gaussian generative models arousal uncertainty Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
Acceso en línea:	https://doaj.org/article/df3685c462974facb748710d2b83590b
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:df3685c462974facb748710d2b83590b
record_format	dspace
spelling	oai:doaj.org-article:df3685c462974facb748710d2b83590b2021-11-19T13:00:35ZFree-Energy Model of Emotion Potential: Modeling Arousal Potential as Information Content Induced by Complexity and Novelty1662-518810.3389/fncom.2021.698252https://doaj.org/article/df3685c462974facb748710d2b83590b2021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fncom.2021.698252/fullhttps://doaj.org/toc/1662-5188Appropriate levels of arousal potential induce hedonic responses (i.e., emotional valence). However, the relationship between arousal potential and its factors (e.g., novelty, complexity, and uncertainty) have not been formalized. This paper proposes a mathematical model that explains emotional arousal using minimized free energy to represent information content processed in the brain after sensory stimuli are perceived and recognized (i.e., sensory surprisal). This work mathematically demonstrates that sensory surprisal represents the summation of information from novelty and uncertainty, and that the uncertainty converges to perceived complexity with sufficient sampling from a stimulus source. Novelty, uncertainty, and complexity all act as collative properties that form arousal potential. Analysis using a Gaussian generative model shows that the free energy is formed as a quadratic function of prediction errors based on the difference between prior expectation and peak of likelihood. The model predicts two interaction effects on free energy: that between prediction error and prior uncertainty (i.e., prior variance) and that between prediction error and sensory variance. A discussion on the potential of free energy as a mathematical principle is presented to explain emotion initiators. The model provides a general mathematical framework for understanding and predicting the emotions caused by novelty, uncertainty, and complexity. The mathematical model of arousal can help predict acceptable novelty and complexity based on a target population under different uncertainty levels mitigated by prior knowledge and experience.Hideyoshi YanagisawaFrontiers Media S.A.articleemotionfree energybayesgaussian generative modelsarousaluncertaintyNeurosciences. Biological psychiatry. NeuropsychiatryRC321-571ENFrontiers in Computational Neuroscience, Vol 15 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	emotion free energy bayes gaussian generative models arousal uncertainty Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
spellingShingle	emotion free energy bayes gaussian generative models arousal uncertainty Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571 Hideyoshi Yanagisawa Free-Energy Model of Emotion Potential: Modeling Arousal Potential as Information Content Induced by Complexity and Novelty
description	Appropriate levels of arousal potential induce hedonic responses (i.e., emotional valence). However, the relationship between arousal potential and its factors (e.g., novelty, complexity, and uncertainty) have not been formalized. This paper proposes a mathematical model that explains emotional arousal using minimized free energy to represent information content processed in the brain after sensory stimuli are perceived and recognized (i.e., sensory surprisal). This work mathematically demonstrates that sensory surprisal represents the summation of information from novelty and uncertainty, and that the uncertainty converges to perceived complexity with sufficient sampling from a stimulus source. Novelty, uncertainty, and complexity all act as collative properties that form arousal potential. Analysis using a Gaussian generative model shows that the free energy is formed as a quadratic function of prediction errors based on the difference between prior expectation and peak of likelihood. The model predicts two interaction effects on free energy: that between prediction error and prior uncertainty (i.e., prior variance) and that between prediction error and sensory variance. A discussion on the potential of free energy as a mathematical principle is presented to explain emotion initiators. The model provides a general mathematical framework for understanding and predicting the emotions caused by novelty, uncertainty, and complexity. The mathematical model of arousal can help predict acceptable novelty and complexity based on a target population under different uncertainty levels mitigated by prior knowledge and experience.
format	article
author	Hideyoshi Yanagisawa
author_facet	Hideyoshi Yanagisawa
author_sort	Hideyoshi Yanagisawa
title	Free-Energy Model of Emotion Potential: Modeling Arousal Potential as Information Content Induced by Complexity and Novelty
title_short	Free-Energy Model of Emotion Potential: Modeling Arousal Potential as Information Content Induced by Complexity and Novelty
title_full	Free-Energy Model of Emotion Potential: Modeling Arousal Potential as Information Content Induced by Complexity and Novelty
title_fullStr	Free-Energy Model of Emotion Potential: Modeling Arousal Potential as Information Content Induced by Complexity and Novelty
title_full_unstemmed	Free-Energy Model of Emotion Potential: Modeling Arousal Potential as Information Content Induced by Complexity and Novelty
title_sort	free-energy model of emotion potential: modeling arousal potential as information content induced by complexity and novelty
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/df3685c462974facb748710d2b83590b
work_keys_str_mv	AT hideyoshiyanagisawa freeenergymodelofemotionpotentialmodelingarousalpotentialasinformationcontentinducedbycomplexityandnovelty
_version_	1718420101808521216

Free-Energy Model of Emotion Potential: Modeling Arousal Potential as Information Content Induced by Complexity and Novelty

Ejemplares similares