The NEMAR gateway to neuroelectromagnetic (NEM) brain imaging data

COEX 

Although electroencephalography (EEG) was the first functional human brain monitoring modality (1926-), EEG data analysis long lagged in adapting new data analysis approaches – both in neurology, where visual pattern recognition applied to the raw scalp signal data is still the dominant approach, and in cognitive neuroscience where event-related potential (ERP) averages of individual scalp channel signals, collected from relatively small numbers of participants, long remained the predominant research measure. These methods, however, leave unrevealed much information about brain function contained in the data, and also cannot exploit consistencies in complex data that can only be identified in and extracted from large to very large data collections using new statistical and machine learning methods. Sharing neuroelectromagnetic (NEM) data is critical to leveraging public research investment and to supporting rigor and reproducibility in funded research. Several funding bodies require data sharing. Data sharing also allows researchers to use modern research tools to evaluate new data in a new way, by directly comparing it directly to ever accumulating stores of shared data collected in related or compatible paradigms.
Here we report initial results of building NEMAR (nemar.org), a large, publicly available human neuroelectromagnetic (NEM) data, tools, and compute resource tightly linked to a freely available high-performance computing resource, the Neuroscience Gateway (NSG). Our goal is to build a widely used and scientifically productive open resource for archiving, sharing, and further analysis and meta-analysis of NEM data.