How a Crowdsourcing Challenge Turbocharged Brain Research During Lockdown

Thanks to big data and machine learning, large-scale collaborations for mapping the brain have already been made possible through data-sharing, such as the Human Brain Project or the BRAIN Initiative. However, applying these collaborative ideas to clinical datasets has been difficult, in part due to the complexity and messiness of the data, as well as privacy concerns. The NeurekaTM challenge is much smaller in scale, but it embodies the same principles. The project employed an open database of electroencephalogram (EEG) brain recordings from people with epilepsy, curated by Dr. Joseph Picone and colleagues at the Temple University Hospital (TUH), and challenged a global community of neurotech enthusiasts—while away from their labs and staying at home—to deploy machine learning and other AI tools to better decipher those neural data and predict seizures before they occur.