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Towards a Whole Brain Cellular Atlas

Bruce Fischl uses BU’s Shared Computing Cluster housed at the MGHPCC in research involving the development of techniques for the automatic construction and utilization of geometrically accurate and topologically correct models of the human cerebral cortex.

The brain is made up of numerous types of cells that are organized into different structures and regions.

Although several important steps have been made toward building models of the human brain, these advances have not produced the undistorted 3D images of cellular architecture needed to build accurate and detailed models.

In new research, led by Fischl, a team led by investigators at Massachusetts General Hospital (MGH), has overcome this challenge to offer scientists and clinicians a comprehensive cellular atlas of a part of the human brain known as Broca’s area, with detailed resolution to study brain function and health.

By combining different sophisticated imaging techniques—including magnetic resonance imaging, optical coherence tomography, and light-sheet fluorescence microscopy—the researchers were able to overcome the limitations associated with any single method to create a high-resolution cell census atlas of a specific region of the human cerebral cortex, or the outer layer of the brain’s surface.

For high-speed postprocessing, data saved on a local server were automatically uploaded to the Boston University Shared Computing Cluster (SCC), a high-performance computing resource located at the MGHPCC. Once data collection was complete, a parallelized postprocessing script was executed on SCC, which included distortion correction, volume stitching, and a variety of feature extraction algorithms.

Most recently, the project has extended into the human brainstem and is now also getting measures of axonal orientation that are helping the team compute connectivity in the brain.

Bruce Fischl, PhD
Director of the Computational Core at the Athinoula A. Martinos Center for Biomedical Imaging at MGH and a professor in Radiology at Harvard Medical School.

Research projects

A Future of Unmanned Aerial Vehicles
Yale Budget Lab
Volcanic Eruptions Impact on Stratospheric Chemistry & Ozone
Towards a Whole Brain Cellular Atlas
Tornado Path Detection
The Kempner Institute - Unlocking Intelligence
The Institute for Experiential AI
Taming the Energy Appetite of AI Models
Surface Behavior
Studying Highly Efficient Biological Solar Energy Systems
Software for Unreliable Quantum Computers
Simulating Large Biomolecular Assemblies
SEQer - Sequence Evaluation in Realtime
Revolutionizing Materials Design with Computational Modeling
Remote Sensing of Earth Systems
Quantum Computing in Renewable Energy Development
Pulling Back the Quantum Curtain on ‘Weyl Fermions’
New Insights on Binary Black Holes
NeuraChip
Network Attached FPGAs in the OCT
Monte Carlo eXtreme (MCX) - a Physically-Accurate Photon Simulator
Modeling Hydrogels and Elastomers
Modeling Breast Cancer Spread
Investigating Mantle Flow Through Analyses of Earthquake Wave Propagation
Impact of Marine Heatwaves on Coral Diversity
IceCube: Hunting Neutrinos
Genome Forecasting
Global Consequences of Warming-Induced Arctic River Changes
Exact Gravitational Lensing by Rotating Black Holes
Evolution of Viral Infectious Disease
Evaluating Health Benefits of Stricter US Air Quality Standards
Ephemeral Stream Water Contributions to US Drainage Networks
Energy Transport and Ultrafast Spectroscopy Lab
Electron Heating in Kinetic-Alfvén-Wave Turbulence
Discovering Evolution’s Master Switches
Dexterous Robotic Hands
Developing Advanced Materials for a Sustainable Energy Future
Detecting Protein Concentrations in Assays
Denser Environments Cultivate Larger Galaxies
Deciphering Alzheimer's Disease
Dancing Frog Genomes
Cyber-Physical Communication Network Security
Asteroid Data Mining
Analyzing the Gut Microbiome
Adaptive Deep Learning Systems Towards Edge Intelligence
Accelerating Rendering Power
ACAS X: A Family of Next-Generation Collision Avoidance Systems
Neurocognition at the Wu Tsai Institute, Yale
Computational Modeling of Biological Systems
Computational Molecular Ecology
Social Capital and Economic Mobility
Building for Floods
Better Pathogen Targeting
Tracking Environmental Health Risks
AI for Cancer Diagnosis
Microplastic-Free by Design
Supporting Data-intensive Social Science
Sailing the Symbiosis Seascape
Wrangle Range Modeling
Shining a Light on Dark Matter
Grid Responsive Data Centers
Multifunctional 3D-Printed Materials
AI Pareidolia
Computing Hidden Health Threats from Heat
Staving off the Banana Apocalypse
CRISPR Mice, Smarter Science
Naval and Ocean Renewable Energy Hydrodynamics
AI That Speaks Human About Health
A Safer Way to See Inside Cells
How Monkeys - and Machines - See in 3D
FlowER: AI for Predicting Chemical Reactions
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