Mobile Footprinting: Linking Individual Distinctiveness in Mobility Patterns to Mood, Sleep, and Brain Functional Connectivity
Cedric Huchuan XiaiD, Ian BarnettiD, Tinashe M. TaperaiD, Azeez AdebimpeiD, Justin Taylor BakeriD, Danielle S. BassettiD, Melissa A. BrotmaniD, Monica E. CalkinsiD, Zaixu CuiiD, Ellen LeibenluftiD, Sophia LinguitiiD, David M. Lydon‐StaleyiD, Melissa L. MartiniD, Tyler M. MooreiD, Kristin A. MurthaiD, Kayla Piiwaa, Adam Robert PinesiD, David R. RoalfiD, Sage Rush‐Goebel, Daniel H. WolfiD, Lyle UngariD, Theodore Daniel SatterthwaiteiD
Abstract
Mapping individual differences in behavior is fundamental to personalized neuroscience. Here, we establish that statistical patterns of smartphone-based mobility features represent unique "footprints" that allow individual identification. Critically, mobility footprints exhibit varying levels of person-specific distinctiveness and are associated with individual differences in affective instability, circadian irregularity, and brain functional connectivity. Together, this work suggests that real-world mobility patterns may provide an individual-specific signature linking brain, behavior, and mood.
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