As goes the omnipresence of smartphones and wearable bio-behavioral technologies, such as activity tracking wrist bands, so goes the integration of these technologies into the lives of individuals with central nervous system (CNS) disorders and into the arena of clinical brain and behavior research [1,2,3,4,5]. Digital phenotyping is one result of the interaction between pervasive personal technology, patients and neurobehavioral researchers and drug developers. Defined as the momentary, ecological quantification of behavior, as measured using sensors embedded in personal technologies [6] and coupled with digitized symptom rating scales and behavioral tasks, digital phenotyping is about unobtrusively capturing the patterns by which individuals interact with their devices and the environment.

Advertisers and others already know that “Where you go is who you are.” [7]. It is valuable insight and it is largely dependent on one of many possible smartphone and wearable device data streams (geolocation). The picture gets significantly richer by integrating other data types and related metadata [8,9,10]. Talk, text, and email communication and social media app usage reveal social behavioral patterns and linguistic capacity, sleep and wake cycle data can be derived from around-the-clock phone interaction patterns, like dips and spikes in screen touches or acceleration (movement), and typing speed data may be a clinically-meaningful surrogate of psychomotor function. These findings suggest that digital phenotyping is a vivid, scalable rainbow with a pot of human behavioral gold at the end.

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