Digital phenotyping of migraine aura

Migraine aura is a transient, focal neurological phenomenon, characterized by evolving visual, somatosensory, language, and, to a lesser extent, motor disturbances, among other symptoms that reflect dynamic alterations in brain function, involving not only cortical, but also subcortical structures. Despite advances in understanding its neurobiology, including the role of cortical spreading depolarization, migraine aura remains incompletely characterized. This is most likely because of its unpredictable onset, brief duration, individual and symptom variability, and reliance on retrospective clinical assessment. Consequently, its temporal evolution and biological heterogeneity remain to be fully elucidated. Digital phenotyping has emerged as a framework for characterizing health and disease through continuous real-world data collected using personal digital technologies. Here we examine the rationale for considering the potential application of digital phenotyping to migraine aura. We argue that aura's unique biological and temporal characteristics can make it a suitable choice for continuous multidimensional assessment. Integrating patient-reported symptoms with physiological, behavioral, and environmental data may improve phenotypic resolution. Consequently, it may help advance mechanistic understanding and capture within-person variability. Therefore, we present a conceptual framework alongside the methodological and translational challenges of digital phenotyping, including implementation-related challenges. Rather than replacing established clinical and neurobiological approaches, digital phenotyping is presented as a complementary framework that, if rigorously validated, could potentially advance our understanding of aura and migraine aura research, support the institution and consolidation of precision headache medicine, and facilitate patient care.