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  • 标题:Brain activity forecasts video engagement in an internet attention market
  • 本地全文:下载
  • 作者:Lester C. Tong ; M. Yavuz Acikalin ; Alexander Genevsky
  • 期刊名称:Proceedings of the National Academy of Sciences
  • 印刷版ISSN:0027-8424
  • 电子版ISSN:1091-6490
  • 出版年度:2020
  • 卷号:117
  • 期号:12
  • 页码:6936-6941
  • DOI:10.1073/pnas.1905178117
  • 出版社:The National Academy of Sciences of the United States of America
  • 摘要:The growth of the internet has spawned new “attention markets,” in which people devote increasing amounts of time to consuming online content, but the neurobehavioral mechanisms that drive engagement in these markets have yet to be elucidated. We used functional MRI (FMRI) to examine whether individuals’ neural responses to videos could predict their choices to start and stop watching videos as well as whether group brain activity could forecast aggregate video view frequency and duration out of sample on the internet (i.e., on youtube.com ). Brain activity during video onset predicted individual choice in several regions (i.e., increased activity in the nucleus accumbens [NAcc] and medial prefrontal cortex [MPFC] as well as decreased activity in the anterior insula [AIns]). Group activity during video onset in only a subset of these regions, however, forecasted both aggregate view frequency and duration (i.e., increased NAcc and decreased AIns)—and did so above and beyond conventional measures. These findings extend neuroforecasting theory and tools by revealing that activity in brain regions implicated in anticipatory affect at the onset of video viewing (but not initial choice) can forecast time allocation out of sample in an internet attention market..
  • 关键词:forecasting ; video ; accumbens ; insula ; FMRI
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