Sustainable Development, Dissemination, and Training for Scalable Software Tools for Optical Brain Mapping

/ABSTRACT We propose to broadly disseminate and extend intuitive, powerful cloud-based resources for optical brain mapping that facilitate efficient, accurate, and standardized processing that will harmonize the emerging set of optical measurement strategies within the growing ecosystem of network level analyses used throughout the greater brain mapping community. The neuroimaging community faces numerous challenges in data collection, preprocessing, estimation of brain connectivity, and analyses of relationships between brain connectivity and behavior. An ever-expanding community of researchers are employing optical methods based on functional near infrared spectroscopy (fNIRS) in order to infer pathophysiological states of the brain for detection/ characterization of disease or cerebral hemodynamics for understanding human brain health, development, and aging. Recent developments of high-density diffuse optical tomography (HD-DOT), a silent, flexible, and scalable technology have demonstrated dramatically improved anatomical specificity and image quality over traditional fNIRS. Further, recent developments in wearable HD-DOT, even using frequency domain and time resolved strategies, open the door to unconstrained mapping of naturalistic human brain function with superior image quality than previously possible. Given the growing worldwide adoption of fNIRS and HD-DOT methods and further developments of next-generation optical brain mapping methods via the BRAIN Initiative, there is an urgent and present need for standardized, accessible and flexible tools that directly support workflows from optical tissue parameter recovery to functional brain mapping to relating variance in brain function to behavior and outcome. Our team is funded by U24NS136402 to address these needs in the optical brain mapping community by developing and validating computational tools including NIRFASTer, NeuroDOT, and Network Level Analyses (NLA), for tissue parameter recovery, optical brain mapping, and model-based connectome-wide association studies of brain function and behavior, respectively. We address the unmet needs for data resources with: (1) greater dissemination and training for our tools with detailed documentation, training materials, and international workshops, (2) cloud deployment of our software to increase scale and accessibility, while easing the computational burden for the user, and (3) expanded utility of these sustainable, flexible tools to meet the evolving needs of users at the forefront of optical imaging technology development. This R50 will support a Research Software Engineer (RSE) to be an established senior RSE through gaining deeper experience expanding development, maintenance, and dissemination of the U24-supported tools while enhancing her skills and knowledge of best software engineering practices, FAIR standards, and optical neuroimaging methods, as well as common and emerging neuroimaging algorithms. This proposal directly supports execution of BRAIN Initiative goal 7 that seeks to integrate new technological and conceptual approaches to discover how dynamic patterns of neural activity are transformed into cognition, emotion, perception, and action in health and disease. Project Number: 1R50MH141892-01 | Fiscal Year: 2026 | NIH Institute/Center: National Institute of Mental Health (NIMH) | Principal Investigator: EMMA SPEH | Institution: WASHINGTON UNIVERSITY, SAINT LOUIS, MO | Award Amount: $140,109 | Activity Code: R50 | Study Section: Special Emphasis Panel[ZRG1 MCST-M (53)] View on NIH RePORTER: https://reporter.nih.gov/project-details/11240976