Experience reorganizes content-specific memory traces in macaques.

Rare and novel conditions can present unique challenges for researchers, clinicians, and patients due to their low prevalence, phenotypic heterogeneity, and lack of natural history data. For rare and novel conditions, there is limited understanding of factors that trigger or modify symptom and disease progression. There is a need for patients to be better equipped with tools to follow their symptoms, along with insights about what improves and worsens their symptoms; for clinicians to be equipped with more accurate knowledge to help guide their patients; and for patient communities to better understand natural histories of their disease to guide research and clinical activities. Personal digital health technologies (P-DHTs []) such as smartphone apps and wearable devices harness the potential for real-world, high-resolution, and longitudinal health monitoring at the individual context []. Consumer-grade wearable and smart devices are capable of tracking semicontinuous biometric measures (eg, heart rate, heart rate variability, body temperature, blood pressure, oxygen saturation, and respiratory function), behavior (eg, activity, relative location, and sleep duration and quality), and social activity (eg, social media and phone use) []. Smartphone active data can capture high-frequency, in-the-moment subjective assessments of symptom experiences, and the individual-level context of a unique patient’s environment. Smartphone passive information, such as phone calls, text, and app usage, daily activities, and movement data, could reflect proxies of an individual’s daily habits, levels of fatigue, and cognitive disturbance in addition to facets of disease burden and quality of life []. Collectively, P-DHTs could detect objective measures of key symptoms that are unique and common across different rare or complex diseases. This rich information can be returned to the user in near real time, and if returned in the correct way, could empower patients to glean new insights into their condition and its modifiers—a “compass” view. The challenge in the collection of such multimodal objective and subjective information is how to effectively return this back to the user, or draw associations that are insightful []. Several consumer brand wearable devices enable users to follow specific measures of health via an associated app []. However, there is a lack of user-driven personalization and limited options to combine information from multiple P-DHTs among existing apps, limiting a true multimodal approach to better understanding health. Furthermore, existing apps are largely proprietary-based, come with a paywall, hide algorithms behind provided data and insights, and are not open source. These realities hinder progress to modify and tailor to the individual or population and limit the patient community's ability to benefit from collective insights []. An additional challenge is to inspire a user to engage with the app in the long term, so that health-related insights can be made. Most consumer apps target the achievement of fitness goals that are not appropriate for those with chronic illnesses [-]. Further, existing health-related apps show strikingly poor engagement [-]. Evidence suggests that this low engagement is in part the result of a lack of personalization and, in turn, low perceived value of the tool [].