Research & Development World

  • R&D World Home
  • Topics
    • Aerospace
    • Automotive
    • Biotech
    • Careers
    • Chemistry
    • Environment
    • Energy
    • Life Science
    • Material Science
    • R&D Management
    • Physics
  • Technology
    • 3D Printing
    • A.I./Robotics
    • Software
    • Battery Technology
    • Controlled Environments
      • Cleanrooms
      • Graphene
      • Lasers
      • Regulations/Standards
      • Sensors
    • Imaging
    • Nanotechnology
    • Scientific Computing
      • Big Data
      • HPC/Supercomputing
      • Informatics
      • Security
    • Semiconductors
  • R&D Market Pulse
  • R&D 100
    • Call for Nominations: The 2025 R&D 100 Awards
    • R&D 100 Awards Event
    • R&D 100 Submissions
    • Winner Archive
    • Explore the 2024 R&D 100 award winners and finalists
  • Resources
    • Research Reports
    • Digital Issues
    • Educational Assets
    • R&D Index
    • Subscribe
    • Video
    • Webinars
  • Global Funding Forecast
  • Top Labs
  • Advertise
  • SUBSCRIBE

Digitizing Neurons: Project will convert 2-D Microscope Images into 3-D Models

By R&D Editors | May 14, 2015

BigNeuron, a new project led by the Allen Institute for Brain Science, aims to streamline scientist’s ability to create 3-D digital models of neurons. Courtesy of Allen Institute for Brain ScienceA new initiative designed to advance how scientists digitally reconstruct and analyze individual neurons in the human brain will receive support from the supercomputing resources at the Department of Energy’s Oak Ridge National Laboratory (ORNL). Led by the Allen Institute for Brain Science, the BigNeuron project aims to create a common platform for analyzing the three-dimensional structure of neurons.

Mapping the complex structures of individual neurons, which can contain thousands of branches, is a labor-intensive and time-consuming process when done by hand. BigNeuron’s goal is to streamline this process of neuronal reconstruction — converting two-dimensional microscope images of neurons into 3-D digital models.

“Neuronal reconstruction is a huge challenge for this field,” said ORNL’s Arvind Ramanathan. “Unless you understand how these different nerve endings are connected to each other, you’re not going to make any sense of how the brain is functioning.”  

Digital algorithms could help automate the process, but researchers worldwide use different approaches to collect images, manage data and create their models. The BigNeuron collaborators hope to standardize the process and identify which algorithms are best suited for different neuron types, which would accelerate scientists’ attempts to map every neuron in the brain. The human brain contains nearly 100 billion neurons.

ORNL’s Titan, the second most powerful supercomputer in the world, will allow scientists to gauge which algorithms are most effective at reconstruction and tune the codes to take advantage of high-performance computers. 

“By bench-testing, we’ll get an idea of which ones tend to perform better than others,” Ramanathan said. “If Titan were to help even one of these algorithms to run faster or better, then I think that would be a huge win.”

In a series of BigNeuron workshops, participants will contribute neuron reconstruction algorithms and datasets to a common software platform. ORNL will provide a supporting framework through its computing and data management resources, including the lab’s Health Data Sciences Institute, a multidisciplinary initiative designed to examine these kinds of complex, heterogeneous datasets.

“Neuroscience imaging represents a unique type of dataset that typically requires supercomputing,” Ramanathan said. “The computers will be used for what they do best, which is massive amounts of computation in a short amount of time. Plus, hosting these very large and complex datasets is at the heart of what we do every day.”

Ramanthan also hopes ORNL’s involvement in the initiative will further integrate the high-performance computing and brain science communities. Although supercomputing is used for image reconstruction in applications such as satellite imagery, neuroscience presents unique challenges.

“Brain science is very specialized; you can’t take an existing algorithm and make it to work with brain data,” he said. “We want to show that Titan can handle all these types of datasets.”

Scientists anticipate that mapping the neuronal connections in an entire brain could provide a wealth of insights in medicine, but Ramanathan notes that BigNeuron is only an initial step in that direction. The project aims to lay the groundwork to enable these future studies.

“The biological implications are huge,” said Ramanathan. “If it works on a healthy human brain, then you can do these analyses on a diseased human brain, on patients with Alzheimer’s or Parkinson’s for instance, to try to understand how the wiring is different. That could lead to many different avenues and hopefully drive the future of medicine.

“First we need to build the basics, the tools of trade. Because these systems are so complex and so important, the community is trying to do this as accurately and systematically as possible,” he said.

  • For more information about BigNeuron, visit https://alleninstitute.org/bigneuron/about/.

Related Articles Read More >

Microsoft’s 4D geometric codes slash quantum errors by 1,000x
Berkeley Lab’s Dell and NVIDIA-powered ‘Doudna’ supercomputer to enable real-time data access for 11,000 researchers
QED-C outlines road map for merging quantum and AI
Quantum computing hardware advance slashes superinductor capacitance >60%, cutting substrate loss
rd newsletter
EXPAND YOUR KNOWLEDGE AND STAY CONNECTED
Get the latest info on technologies, trends, and strategies in Research & Development.
RD 25 Power Index

R&D World Digital Issues

Fall 2024 issue

Browse the most current issue of R&D World and back issues in an easy to use high quality format. Clip, share and download with the leading R&D magazine today.

Research & Development World
  • Subscribe to R&D World Magazine
  • Enews Sign Up
  • Contact Us
  • About Us
  • Drug Discovery & Development
  • Pharmaceutical Processing
  • Global Funding Forecast

Copyright © 2025 WTWH Media LLC. All Rights Reserved. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of WTWH Media
Privacy Policy | Advertising | About Us

Search R&D World

  • R&D World Home
  • Topics
    • Aerospace
    • Automotive
    • Biotech
    • Careers
    • Chemistry
    • Environment
    • Energy
    • Life Science
    • Material Science
    • R&D Management
    • Physics
  • Technology
    • 3D Printing
    • A.I./Robotics
    • Software
    • Battery Technology
    • Controlled Environments
      • Cleanrooms
      • Graphene
      • Lasers
      • Regulations/Standards
      • Sensors
    • Imaging
    • Nanotechnology
    • Scientific Computing
      • Big Data
      • HPC/Supercomputing
      • Informatics
      • Security
    • Semiconductors
  • R&D Market Pulse
  • R&D 100
    • Call for Nominations: The 2025 R&D 100 Awards
    • R&D 100 Awards Event
    • R&D 100 Submissions
    • Winner Archive
    • Explore the 2024 R&D 100 award winners and finalists
  • Resources
    • Research Reports
    • Digital Issues
    • Educational Assets
    • R&D Index
    • Subscribe
    • Video
    • Webinars
  • Global Funding Forecast
  • Top Labs
  • Advertise
  • SUBSCRIBE