BRAIN Integrated Resource for Human Anatomy and Intracranial Neurophysiology

项目总结/文摘

PROJECT SUMMARY/ABSTRACT Intracranial recordings in patients undergoing neurosurgical interventions provide a unique opportunity to directly access, study, and learn about both normal human brain function and neuropsychiatric disease. Because of their value, the NIH has made significant investments in this line of research through the BRAIN Initiative and has likewise required public archiving of data through the Data Archive for the BRAIN Initiative (DABI). With the accumulation of data from over 500 subjects, DABI presents a unique opportunity to conduct large scale studies using data from multiple sites and investigations. Moreover, with the inclusion of both neurophysiological and imaging data (including anatomic and connectivity-based imaging), DABI has the potential to address important questions about functional-anatomic relationships in human neurophysiology and sources of variability across age, disease, and anatomy. There is a strong emerging yet underexplored literature that neural oscillation patterns relate to brain morphometry, yet the tools to explore this with greater spatial precision and spectral sensitivity are currently unavailable. While the multimodal nature of DABI data has the potential to significantly impact such questions, the data is not currently in a form that makes it easily accessible or analyzable. The BRAIN integrated Resource for human Anatomy and Intracranial Neurophysiology, B(RAIN)2, has an overall aim of creating a spatially integrated and standardized dataset that will enable such large scale studies. In Aim 1, we will (1) identify and curate data for inclusion in B(RAIN)2 based on required data elements (as well as solicit additional archiving from BRAIN funded investigators), (2) perform standardized neurophysiological signal processing and anatomic localization, (3) perform standard anatomic image processing, based on the Human Connectome Project framework and established quality control measures, and (4) transform all data into a standard space for large scale analyses. To ensure high impact and continued growth of B(RAIN)2, in Aim 2, we will share, document, and define pipelines for continued data integration, including webinars and training modules and providing support to potential users. Finally, in Aim 3, we will conduct a demonstration project to highlight the power of B(RAIN)2, investigating the relationships between motor cortical beta power and peak frequency as a function of cortical thickness, connectivity, and disease. The proposed work will enable investigators to harness the power of intracranial physiology and neuroimaging collected across BRAIN-funded sites to increase the power and impact of these valuable and relatively rare signals. Future investigators will use the B(RAIN)2 standardized metrics across anatomy and physiology in both native and standard space to perform novel analyses and gain unique insights into anatomic contributions to variability in human neural oscillator signals.