Global brain initiatives generate tsunami of neuroscience data

November 22, 2016, Lawrence Berkeley National Laboratory
Rendering of a group connectome -- or comprehensive map of neural connections in the brain -- based on 20 subjects. Credit: Wikimedia Commons

Three years ago the White House launched the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative to accelerate the development and application of novel technologies that will give us a better understanding about how brains work.

Since then, dozens of technology firms, academic institutions, scientists and other have been developing new tools to give researchers unprecedented opportunities to explore how the brain processes, utilizes, stores and retrieves information. But without a coherent strategy to analyze, manage and understand the data generated by these new technologies, advancements in the field will be limited.

This is precisely why Lawrence Berkeley National Laboratory (Berkeley Lab) Computational Neuroscientist Kristofer Bouchard assembled an international team of interdisciplinary researchers—including mathematicians, computer scientists, physicists and experimental and computational neuroscientists—to develop a plan for managing, analyzing and sharing neuroscience data. Their recommendations were published in a recent issue of Neuron.

"The U.S. BRAIN Initiative is just one of many national and private neuroscience initiatives globally that are working toward accelerating our understanding of brains," says Bouchard. "Many of these efforts have given a lot of attention to the technological challenges of measuring and manipulating neural activity, while significantly less attention has been paid to the computing challenges associated with the vast amounts of data that these technologies are generating."

To maximize the return on investments in global neuroscience initiatives, Bouchard and his colleagues argue that the international neuroscience community should have an integrated strategy for data management and analysis. This coordination would facilitate the reproducibility of workflows, which then allows researchers to build on each other's work.

For a first step, the authors recommend that researchers from all facets of neuroscience agree on standard descriptions and file formats for products derived from and simulations. After that, the researchers should work with computer scientists to develop hardware and software ecosystems for archiving and sharing data.

The authors suggest an ecosystem similar to the one used by the physics community to share data collected by experiments like the Large Hadron Collider (LHC). In this case, each research group has their own local repository of physiological or simulation data that they've collected or generated. But eventually, all of this information should also be included in "meta-repositories" that are accessible to the greater neuroscience community. Files in the "meta-repositories" should be in a common format, and the repositories would ideally be hosted by an open-science supercomputing facility like the Department of Energy's (DOE's) National Energy Research Scientific Computing Center (NERSC), located at Berkeley Lab.

Because novel technologies are producing unprecedented amounts of data, Bouchard and his colleagues also propose that neuroscientists collaborate with mathematicians to develop new approaches for data analysis and modify existing analysis tools to run on supercomputers. To maximize these collaborations, the analysis tools should be open-source and should integrate with brain-scale simulations, they emphasize.

"These are the early days for neuroscience and big data, but we can see the challenges coming. This is not the first research community to face big data challenges; climate and high energy physics have been there and overcome many of the same issues," says Prabhat, who leads NERSC's Data & Analytics Services Group.

Berkeley Lab is well positioned to help neuroscientists address these challenges because of its long tradition of interdisciplinary science, Prabhat adds. DOE facilities like NERSC and the Energy Sciences Network (ESnet) have worked closely with Lab computer scientists to help a range of science communities—from astronomy to battery research—collaborate and manage and archive their data. Berkeley Lab mathematicians have also helped researchers in various scientific disciplines develop new tools and methods for analysis on supercomputers.

"Harnessing the power of HPC resources will require neuroscientists to work closely with computer scientists and will take time, so we recommend rapid and sustained investment in this endeavor now," says Bouchard. "The insights generated from this effort will have high-payoff outcomes. They will support neuroscience efforts to reveal both the universal design features of a species' brain and help us understand what makes each individual unique."

Explore further: Researchers have developed a computational framework for standardizing neuroscience data worldwide

Related Stories

Researchers have developed a computational framework for standardizing neuroscience data worldwide

December 19, 2014
Thanks to standardized image file formats—like JPEG, PNG or TIFF—which store information every time you take a digital photo, you can easily share selfies and other pictures with anybody connected to a computer, mobile ...

Researchers and supercomputers to help create a standard 3D neuron model

April 1, 2015
Before scientists can unlock the secrets of the human brain, they must fully understand neurons—the cells of our brain, spinal cord and overall nervous system. Thousands of detailed neuron images, from different organisms, ...

Neuroscientists call for deep collaboration to 'crack' the human brain

November 8, 2016
The time is ripe, the communication technology is available, for teams from different labs and different countries to join efforts and apply new forms of grassroots collaborative research in brain science. This is the right ...

Research institutions announce collaboration for sharing, standardizing neuroscience data

August 4, 2014
The Allen Institute for Brain Science, California Institute of Technology, New York University School of Medicine, the Howard Hughes Medical Institute (HHMI) and the University of California, Berkeley (UC Berkeley) are collaborating ...

Allen Brain Observatory launched

July 13, 2016
The Allen Institute for Brain Science today announced the release of the Allen Brain Observatory: a highly standardized survey of cellular-level activity in the mouse visual system. This dynamic tool empowers scientists to ...

Recommended for you

Broken shuttle may interfere with learning in major brain disorders

June 22, 2018
Unable to carry signals based on sights and sounds to the genes that record memories, a broken shuttle protein may hinder learning in patients with intellectual disability, schizophrenia, and autism.

Scientists discover fundamental rule of brain plasticity

June 21, 2018
Our brains are famously flexible, or "plastic," because neurons can do new things by forging new or stronger connections with other neurons. But if some connections strengthen, neuroscientists have reasoned, neurons must ...

Waking up is hard to do: Prefrontal cortex implicated in consciousness

June 21, 2018
Philosophers have pondered the nature of consciousness for thousands of years. In the 21st century, the debate over how the brain gives rise to our everyday experience continues to puzzle scientists. To help, researchers ...

Researchers find mechanism behind choosing alcohol over healthy rewards

June 21, 2018
A new study links molecular changes in the brain to behaviours that are central in addiction, such as choosing a drug over alternative rewards. The researchers have developed a method in which rats learn to get an alcohol ...

Scientists discover how brain signals travel to drive language performance

June 21, 2018
Effective verbal communication depends on one's ability to retrieve and select the appropriate words to convey an intended meaning. For many, this process is instinctive, but for someone who has suffered a stroke or another ...

Study on instinctive behaviour elucidates a synaptic mechanism for computing escape decisions

June 21, 2018
How does your brain decide what to do in a threatening situation? A new paper published in Nature describes a mechanism by which the brain classifies the level of a threat and decides when to escape.

1 comment

Adjust slider to filter visible comments by rank

Display comments: newest first

TogetherinParis
not rated yet Nov 22, 2016
Seems a stupid waste to me.

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.