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Individualized video recommendation modulates functional connectivity between large scale networks.

Conghui Su1, Hui Zhou1, Chunjie Wang2

  • 1Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou, China.

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|August 7, 2021
PubMed
Summary
This summary is machine-generated.

Personalized videos enhance brain network connectivity, particularly involving the dorsal attention network (DAN) and ventral attention network (VAN). This reveals neural mechanisms behind how recommended content influences user behavior.

Keywords:
graph theorynetwork interactionpersonalized short videosrecommender system

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Media Studies

Background:

  • AI-powered recommender systems are prevalent in video streaming.
  • Concerns exist regarding the impact of personalized content on user attention and behavior.

Purpose of the Study:

  • To investigate the neural mechanisms underlying user engagement with personalized video content.
  • To examine the effects of personalized vs. non-personalized videos on large-scale brain network interactions.

Main Methods:

  • fMRI experiment with participants viewing personalized and generally recommended videos.
  • Graph theory analysis to assess interactions among seven brain networks (VAN, DAN, FPN, SN, dMPFC, Core, MTL).

Main Results:

  • Non-personalized videos strengthened the DAN-FPN-Core pathway connectivity.
  • Personalized videos enhanced the DAN-FPN-Core and DAN-VAN-dMPFC pathways.
  • Both video types reduced connectivity between the SN-VAN and Core-MTL (DMN subsystems).

Conclusions:

  • Distinct brain network interaction patterns emerge in response to personalized and non-personalized short videos.
  • Findings offer insights into the neural basis of behavior modification by recommender systems.