Visioning Workshop – Brain Meets mHealth
The mDOT Center is excited to announce the upcoming Brain Meets mHealth: Visioning Workshop on Optimizing Interventions Leveraging Brain, Behavior, and Physiology Interactions in the Natural Field Environment. This event will take place on Tuesday, October 15, 2024 in Salt Lake City, UT.
This workshop aims to bring together researchers from neuroscience, behavioral science and AI with mHealth experts from the mDOT Center to explore how recent advances in generative AI, foundation models, and digital twins can be used to develop a new unified framework to link brain, behavior, and physiology in people’s natural environment, to design and optimize the next generation of treatments and interventions.
Over the past fifteen years, mHealth has evolved from sensing and sense-making to triggering just-in-time interventions. AI-powered mHealth biomarkers derived from wearables are now being used by health researchers to discover and optimize the timing and content of behavioral interventions. Improving our understanding of the complex interactions between the brain, behavior, and physiology can help us maximize the efficacy and longevity of interventions targeted at behavior modifications.
Recent advances in mobile, wearable, and implantable sensing platforms (EEG/iEEG, fNIRS, IMU, ECG, PPG) make it possible to capture detailed information about the brain, behavior, and physiology in more naturalistic settings than traditional methods. Combining signals relating brain activity with continuous observation of physiology and behaviors via mHealth biomarkers captured by wearables in a new unified framework can enable the research community to link dynamic brain activity with observed changes in physiology and behaviors. In parallel, rapid progress in generative AI techniques and foundation models have, for the first time, made it possible to learn and exploit links between seemingly disparate data sources from multiple domains across different time scales and modalities. This, combined with digital twins, offers a potential to model brain, body, behavior interactions for data-informed decision-making under uncertainties inherent to the natural environment.
For more information please head to the mDOT Center website’s Workshop page:
https://mdotcenter.org/news-events/events/mhealth-meets-brain-workshop/
Workshop Objectives:
The workshop will explore new frontiers by integrating neuroscience, behavioral science, and AI to create a unified framework that bridges brain, behavior, and physiology in real-world settings. It will leverage advanced technologies like generative AI, foundation models, and digital twins to pioneer innovative, personalized, and adaptive interventions. Emphasizing real-world application, the workshop aims to ensure that research and interventions are grounded in natural field environments, leading to more scalable solutions. Collaborative innovation will be encouraged, fostering a multidisciplinary approach to solving complex problems at the intersection of these fields, ultimately pushing the boundaries of current mHealth research and application.
The workshop will focus on identifying both opportunities and challenges in advancing the integration of brain, behavior, and physiology within mHealth. It aims to map key opportunities by exploring how generative AI, foundation models, and digital twins can be used to create more precise interventions. The workshop will assess the potential for technological integration across neuroscience, behavioral science, and AI, while also evaluating the real-world implementation of these technologies, including the logistical, ethical, and technical challenges. Additionally, it will address the complexities of managing and interpreting data, identify gaps in current research and practice, and balance the pursuit of innovation with the feasibility of practical, scalable interventions.
The workshop will address the ethical and technical challenges of advancing brain, behavior, and physiology integration in mHealth by exploring the ethical implications of using generative AI, foundation models, and digital twins, with a focus on privacy, consent, and data security. It will emphasize responsible AI usage, ensuring transparency, fairness, and alignment with individuals’ best interests, while also tackling the technical challenges of data privacy, security, and the integration of complex systems into real-world environments. The workshop will address bias, promote equity, and focus on designing interventions that respect autonomy, enhance well-being, and are culturally sensitive, ensuring that innovation is both responsible and effective.
The workshop aims to foster an environment of cross-disciplinary learning and collaboration by encouraging active engagement through interactive sessions, such as breakout groups, demos, and brainstorming activities. Participants from neuroscience, behavioral science, AI, and mHealth will share knowledge and perspectives to deepen the collective understanding of brain, behavior, and physiology interactions. The workshop will also promote collaborative problem-solving, showcase real-world applications of advanced technologies, and provide networking opportunities to build lasting partnerships. Ultimately, the goal is to cultivate a shared vision for the future of integrated interventions, aligning efforts towards common goals.
A pivotal goal of the workshop is to develop a strategic roadmap. Through report-back sessions and working groups, attendees will summarize key findings, insights, and gaps identified during the workshop. These inputs will contribute to the development of a white paper outlining the research agenda for this emerging research area, guiding future studies and innovations in the field.
The closing session of the workshop will provide a platform for summarizing outcomes and contributions. Participants will share insights gained and discuss the next steps for the research community. The workshop aims to foster a sense of community, encouraging ongoing collaboration, knowledge exchange, and joint initiatives in the evolving landscape of generative mHealth interventions.