In 2013, then-President Obama launched the brain initiative, which allocated funding to map every neuron in the brain. Understanding how the brain works can revolutionize the lives of many Americans, solving the complex problems of Alzheimer’s and Parkinson’s disease, depression, and traumatic brain injury (1). However, mapping the brain alone does not reveal how it functions. Different parts of the brain appear similar but function differently, and each person has unique brain anatomy (2).
Neuroscientists have historically worked alone on individual projects, but as technology and data advance, they have to team up to achieve meaningful results. The need for data analysis has allocated neuroscience graduate students to solving complex computer science problems. This presents two significant problems. First, the number of years to achieve a neuroscience Ph.D. is increasing. Second, each graduate student solves the problems presented to them in isolation, which fails to create continuity either after they leave or between research teams. The result is a vast amount of available data failing to achieve its potential. Enter “stabilizing” disruptor Dimitri Yatsenko, CEO of DataJoint, who explains to Karla Jo Helms, host of the Disruption Interruption podcast, that to be used effectively for the greater good, the vast data recorded about the brain has to be analyzed with continuity between universities, laboratories, and research teams.
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Dimitri Yatsenko’s background in computer science gave him a unique perspective when his fascination with the human brain led him to neuroscience. He saw independent labs repeatedly reinventing ways of doing data analysis, weighing grad students down with data analysis that had little to do with their passions, and falling short of their collaborative potential. Dimitri said to himself, THAT’S IT — I’M DONE WITH THE STATUS QUO and began to develop a computational framework to create continuity across projects, teams, and applications. He made it cloud compatible, containerized, and web-accessible so it can be quickly deployed for multi-lab collaborations, and DataJoint was born.
Dimitri explains:
We have more data gathered about the brain and its circuits than at any other time in history. We need to combine molecular, genetic, and electrophysiology data, which is beyond the scope of any single neuroscientist. Understanding the brain requires a systematic approach to data and modeling.
Progress is limited by the tsunami of data and the systems required to model and analyze it. Up to half of the time spent on any neuroscience project is software engineering and systems engineering.
Neuroscientists are fundamentally curious about how the brain, its circuits, our interaction with the environment, and our genetic programming work to produce intelligence. However, the next level of understanding relates to how molecules, genes, and stimuli interact to shape circuits and how circuit systems produce adaptive behavior.
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The brain is complex but has patterns to it. You can make the same circuits of the neocortex (the outer portion of the mammalian brain) solve very different problems. The more we understand the principles of how this works, the more effectively we can apply machine learning to understand how circuits and populations of neurons work together in the living brain.
What neuroscience teams want to achieve logically and computationally requires infrastructure, communication, and organization across departments. They haven’t had the tools to support this requirement, and it’s adding to the overhead costs of research.
Commercial companies can help execute things more effectively and provide computation as a service rather than having each lab reproduce the same computation with graduate students.
DataJoint provides a systematic framework to work with data and computation and bridge communication gaps in one unified framework.
Disruption Interruption is the podcast where you’ll hear from today’s biggest Industry Disruptors. Learn what motivated them to bring about change and how they overcome opposition to adoption.
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[To share your insights with us, please write to sghosh@martechseries.com]
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