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Mapping individual differences in behavior is fundamental to personalized neuroscience, but quantifying complex behavior in real world settings remains a challenge. While mobility patterns captured by smartphones have increasingly been linked to a range of psychiatric symptoms, existing research has not specifically examined whether individuals have person-specific mobility patterns. We collected over 3000 days of mobility data from a sample of 41 adolescents and young adults (age 17-30 years, 28 female) with affective instability. We extracted summary mobility metrics from GPS and accelerometer data and used their covariance structures to identify individuals and calculated the individual identification accuracy-i.e., their "footprint distinctiveness". We found that statistical patterns of smartphone-based mobility features represented unique "footprints" that allow individual identification (p &lt; 0.001). Critically, mobility footprints exhibited varying levels of person-specific distinctiveness (4-99%), which was associated with age and sex. Furthermore, reduced individual footprint distinctiveness was associated with instability in affect (p &lt; 0.05) and circadian patterns (p &lt; 0.05) as measured by environmental momentary assessment. Finally, brain functional connectivity, especially those in the somatomotor network, was linked to individual differences in mobility patterns (p &lt; 0.05). Together, these results suggest that real-world mobility patterns may provide individual-specific signatures relevant for studies of development, sleep, and psychopathology.

Mobile footprinting: linking individual distinctiveness in mobility patterns to mood, sleep, and brain functional connectivity