President Obama launched the BRAIN Initiative (Brain Research Through Advancing Innovative Neurotechnologies) in 2013, a scientific grand challenge aimed at accelerating the development and application of new technologies and tools to understand the structure and function of the brain.
The goal of the BRAIN Initiative is to gain insight into the structure and function of the brain, as well as to better understand interactions within the nervous system that play a role in health and the onset and progression of disease.
This large-scale initiative requires collaboration between governmental agencies, including the National Institutes of Health, the FDA, the National Science Foundation, Intelligence Advanced Research Projects Activity (IARPA), and the Defense Advanced Research Projects Agency (DARPA), as well as those in academic research settings and industry.1,2
“A new, deeper understanding of the brain will change everything: how we conceive of ourselves as human beings, how we educate our children, how we think about personal responsibility and the law, and how we understand human decision-making in economic and political systems,” said William Newsome, PhD, a professor of neurobiology at Stanford University School of Medicine in California.
Specifically, the BRAIN Initiative aims to identify and provide experimental access to different brain cell types, in order to help:
- Determine brain cells’ roles in health and disease
- Generate circuit diagrams that vary in resolution from synapses to the whole brain
- Produce a dynamic overview of brain function by developing and applying improved methods for large-scale monitoring of neural activity
- Link brain activity to behavior with precise interventional tools that change neural circuit dynamics
The goal is also to develop innovative technologies to understand the human brain and treat its disorders, identify the brain’s role in health and disease, and discover how dynamic patterns of neural activity are transformed into cognition, emotion, perception.1
Assembling a complete list of nerve cells in the brain is imperative to better understanding their function.
“We need to know the ‘parts list’ (how many different kinds of neurons are present), the circuits (how the neurons are wired up into individual but interacting circuits), and the signals (or information) that flows within these circuits,” Newsome said.
The next step will then be to determine the activity that flows within specific circuits and how they function in generating cognition and behavior. After that researchers can develop theories about how neural circuits actually process information and how that information is related to cognition and behavior, he explained.
Collaboration, New Tools, and Data Sharing
Beyond the immense challenge of identifying and understanding the role and function of nerve cells in the brain, researchers working under the BRAIN Initiative are facing a more spacial problem.
The new technologies being used are generating an enormous, almost incomprehensible amount of data that needs to not only be stored but to be made accessible and shareable.
The former requires not only an enormous database but also a change of heart within the research community. The call to adopt a more open-access environment can be heard loud and clear from researchers involved in the initiative.
Collaboration across specialties, institutions, and other research initiatives, like the Human Connectome Project, is key to an outcome that will serve individuals both inside and outside of the scientific community.
Data collection and sharing are just the first steps. To discover the fundamental rules by which the brain operates, researchers need to interpret and analyze these massive and complex data sets to find interesting patterns, derive deep underlying principles, and then design thoughtful, targeted experiments to test them rigorously.5,6
Jeremy Freeman, PhD, of Howard Hughes Medical Institute in Chevy Chase, Maryland, and colleagues have evaluated a new approach to analyze large-scale neural data using cluster computing.
Referred to as the Thunder system, Freeman and his team have managed to build out the analysis tool on a pre-existing, open-access platform called Spark that’s widely used across the research community.
“We built Thunder on top of Spark, because it has a number of unique features, making it ideally suited to scientific applications like ours. Thunder has grown rapidly since the paper was published, including several contributions from the community, and we are excited to see where it goes,” Freeman said.
“The BRAIN Initiative will fuel an ongoing revolution in neuroscience techniques that are allowing researchers to gain unprecedented insights into the circuits of the brain, how those circuits process information about the external world and about the internal states of our bodies, and how this information processing is related to perception, learning, memory, emotion, thinking, and movement,” Newsome said.
This knowledge will provide new insights into the causes of and treatments for psychiatric and neurological disease, and will lay the foundation for a neurotechnology industry that will be born after the fundamental research is performed.
Beth Gilbert is a freelance health and science writer. She has an undergraduate degree in chemical engineering from Lehigh University and a Master’s in biomedical engineering from Columbia University.
This article was medically reviewed by Pat F. Bass III, MD, MS, MPH.
- NIH Brain 2025 – A Scientific Vision. Brain Research through Advancing Innovative Technologies (BRAIN) Working Group. Available at: http://www.braininitiative.nih.gov/2025/BRAIN2025.pdf. NIH Brain Initiative. Brain Research through Advancing Innovative Neurotechnologies. Available at: http://acd.od.nih.gov/ACD-BRAIN-working-group-Report.pdf.
- The Kavli Foundation. The Brain Initiative: Surviving the Data Deluge. Available at: http://www.kavlifoundation.org/science-spotlights/brain-initiative-surviving-data-deluge#.VGZv4_nF-0s. Choudhury S, Fishman JR, et al. Big data, open science and the brain: lessons learns from genomics. Frontiers in Human Neuroscience. 2014; 8 (239): 1-10.
- Freeman J, Vladimirov N, et al. Mapping Brain Activity at Scale with Cluster Computing. Nature Methods. 2014; 11 (9): 941-957.
- Howard Hughes Medical Institute. New Tools to Help Neuroscientists Analyze Big Data. Available at: http://www.hhmi.org/news/new-tools-help-neuroscientists-analyze-big-data.
- Cunningham JP, Yu BM. Dimensionality reduction for large-scale neural recordings. Nature Neuroscience. 2014: 17(11): 1500 -1509.
- Science Daily. Neuroscience and Big Data: How to Find Simplicity in the Brain. Available at: http://www.sciencedaily.com/releases/2014/08/140824152349.htm.
All electronic documents accessed Nov. 30, 2014.