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Individualized video recommendation modulates functional connectivity between large scale networks

With the emergence of AI‐powered recommender systems and their extensive use in the video streaming service, questions and concerns also arise. Why can recommended video content continuously capture users' attention? What is the impact of long‐term exposure to personalized video content on one&...

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Autores principales: Su, Conghui, Zhou, Hui, Wang, Chunjie, Geng, Fengji, Hu, Yuzheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8519862/
https://www.ncbi.nlm.nih.gov/pubmed/34363282
http://dx.doi.org/10.1002/hbm.25616
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author Su, Conghui
Zhou, Hui
Wang, Chunjie
Geng, Fengji
Hu, Yuzheng
author_facet Su, Conghui
Zhou, Hui
Wang, Chunjie
Geng, Fengji
Hu, Yuzheng
author_sort Su, Conghui
collection PubMed
description With the emergence of AI‐powered recommender systems and their extensive use in the video streaming service, questions and concerns also arise. Why can recommended video content continuously capture users' attention? What is the impact of long‐term exposure to personalized video content on one's behaviors and brain functions? To address these questions, we designed an fMRI experiment presenting participants with personally recommended videos and generally recommended ones. To examine how large‐scale networks were modulated by personalized video content, graph theory analysis was applied to investigate the interaction between seven networks, including the ventral and dorsal attention networks (VAN, DAN), frontal–parietal network (FPN), salience network (SN), and three subnetworks of default mode network (dorsal medial prefrontal (dMPFC), Core, and medial temporal lobe (MTL)). Our results showed that viewing nonpersonalized video content mainly enhanced the connectivity in the DAN‐FPN‐Core pathway, whereas viewing personalized ones increased not only the connectivity in this pathway but also the DAN‐VAN‐dMPFC pathway. In addition, both personalized and nonpersonalized short videos decreased the couplings between SN and VAN as well as between two DMN subsystems, Core and MTL. Collectively, these findings uncovered distinct patterns of network interactions in response to short videos and provided insights into potential neural mechanisms by which human behaviors are biased by personally recommended content.
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spelling pubmed-85198622021-10-22 Individualized video recommendation modulates functional connectivity between large scale networks Su, Conghui Zhou, Hui Wang, Chunjie Geng, Fengji Hu, Yuzheng Hum Brain Mapp Research Articles With the emergence of AI‐powered recommender systems and their extensive use in the video streaming service, questions and concerns also arise. Why can recommended video content continuously capture users' attention? What is the impact of long‐term exposure to personalized video content on one's behaviors and brain functions? To address these questions, we designed an fMRI experiment presenting participants with personally recommended videos and generally recommended ones. To examine how large‐scale networks were modulated by personalized video content, graph theory analysis was applied to investigate the interaction between seven networks, including the ventral and dorsal attention networks (VAN, DAN), frontal–parietal network (FPN), salience network (SN), and three subnetworks of default mode network (dorsal medial prefrontal (dMPFC), Core, and medial temporal lobe (MTL)). Our results showed that viewing nonpersonalized video content mainly enhanced the connectivity in the DAN‐FPN‐Core pathway, whereas viewing personalized ones increased not only the connectivity in this pathway but also the DAN‐VAN‐dMPFC pathway. In addition, both personalized and nonpersonalized short videos decreased the couplings between SN and VAN as well as between two DMN subsystems, Core and MTL. Collectively, these findings uncovered distinct patterns of network interactions in response to short videos and provided insights into potential neural mechanisms by which human behaviors are biased by personally recommended content. John Wiley & Sons, Inc. 2021-08-06 /pmc/articles/PMC8519862/ /pubmed/34363282 http://dx.doi.org/10.1002/hbm.25616 Text en © 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Research Articles
Su, Conghui
Zhou, Hui
Wang, Chunjie
Geng, Fengji
Hu, Yuzheng
Individualized video recommendation modulates functional connectivity between large scale networks
title Individualized video recommendation modulates functional connectivity between large scale networks
title_full Individualized video recommendation modulates functional connectivity between large scale networks
title_fullStr Individualized video recommendation modulates functional connectivity between large scale networks
title_full_unstemmed Individualized video recommendation modulates functional connectivity between large scale networks
title_short Individualized video recommendation modulates functional connectivity between large scale networks
title_sort individualized video recommendation modulates functional connectivity between large scale networks
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8519862/
https://www.ncbi.nlm.nih.gov/pubmed/34363282
http://dx.doi.org/10.1002/hbm.25616
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