CRCNS US-Israel Data Sharing Proposal: EEG-DaSh electroencephalography data and tool sharing resource

The EEG-DaSh project aims to enable Artificial Intelligence (AI)-driven breakthroughs in the realms of electroencephalography (EEG) and magnetoencephalography (MEG) by providing the necessary data and associated tools to process them. EEG and MEG are widely used methods for recording brain activity, which can be harnessed through AI to gain deeper insights into brain function and neurological disorders. EEG-DaSh addresses the current lack of large-scale, standardized datasets by providing annotated data from over 25 partner labs and reformatting data from existing archives. The project also focuses on educating scientists on utilizing AI in EEG and MEG research and offers free and open high-performance computing resources to support such efforts. The EEG-DaSh Gateway Project has three main objectives: First, create a comprehensive data-sharing platform for neuroelectromagnetic data featuring a user-friendly web interface for easy data management. This platform adopts a new data format optimized for machine learning and deep learning applications and uses the Hierarchical Event Descriptor (HED) system for standardized data annotation. Second, the project develops advanced automated processing pipelines, accessible through high-performance computing resources, to facilitate machine learning, deep learning, and EEG model fitting. These features include cutting-edge techniques for feature extraction, measures of critical brain dynamics, measures of connectivity between regions of interest, and customized neural fields and neural mass models for data augmentation. Deep learning example scripts that are compatible with EEG-DaSh will also be provided. Third, the project organizes workshops and provides in-person support to promote data sharing, train researchers, and foster collaboration in neuroscience. These efforts enhance the understanding of brain function and accelerate the development of AI applications in neurotechnology. A companion project is being funded by the US-Israel Binational Science Foundation (BSF). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.