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.
Thursday, April 02, 2020
Brain regions that predict money choices also predict allocation of time to watching videos
People currently spend over 1 billion hours every day in attention markets watching video content, and the world’s second-most popular search engine is the video site youtube.com. Combining neuroimaging with a behavioral task, Tong et al. extend the neuroeconomic toolkit to find that brain activity in regions previously shown to predict allocation of money also predicted choices to allocate time to watching videos in the youtube.com attention market. They also find that sampled activity in a subset of these brain regions implicates anticipatory affect at video onset generalizes to forecast the frequency of choices to allocate time as well as the duration of time allocated to videos. Their abstract: