As the pandemic spread across the US, neuroscience labs shuttered their doors, leaving behind half-finished experiments, aging lab animals, and precious brain specimens that—if unprocessed—could mean losing months of hard work. Like many other fields, the pandemic has brought hands-on, “wet lab” brain research to a screeching halt. Solving the brain’s mysteries will just have to wait.
Or will it?
In mid-March, a trifecta of academic, non-profit, and commercial neurotech companies united to launch a neuroscientific challenge that embodied a more collaborative future for solving the brain, while physically apart and working from home. (Full disclosure: I was fortunate to be involved in the very initial organization of the project.) The challenge embraced a one-two formula for accelerating scientific progress, most recently encapsulated by research into Covid-19. One, large open databases enabling AI-based tools for analysis; and two, global interest and unity.
These sentiments aren’t exactly new to neuroscience. 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.
In just six weeks, the challenge received over a dozen submissions from Australia, Belgium, China, Israel, India, Russia, and other countries, with several innovative solutions to capture seizure warnings using the brain’s electrical signals alone.
“These challenges can only be successful when there’re sufficient data resources to support the development of the technology and a common scoring methodology that allows direct comparison of results,” said Dr. Picone.
To Yannick Roy, co-founder and Executive Director of NeuroTechX, a non-profit organization that supports education and development of a global community of neurotechnology professionals and enthusiasts, the challenge highlights the promise of AI in deciphering neural signals—as long as the dataset is widely available.
“Large clinical datasets will be key to unlocking AI in the coming years in fields like epilepsy. Dr. Picone has helped greatly, not just in terms of the dataset but also the tools, documentation, and support to understand and use the data,” said Roy, who led the organization of the challenge.
The results aren’t just a scientific community’s self-pat on the back. Results from the challenge, when further explored, could potentially revolutionize epilepsy monitoring for patients at home. This is particularly critical as patients with chronic disorders are hesitant to visit the clinic in fear of Covid-19.
“Telehealth is especially important today when we’re staying home to help flatten the Covid curve,” said Ray Iskander, CEO of Novela Neurotech, which helped conceptualize and sponsor the challenge. “But more importantly, the Neureka competition shows us what can be done with an open dataset, even during lockdown, to move neuroscience research forward. Our goal is to support similar data-driven approaches to personalize neurological solutions in telehealth.”