DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: High-Performance Computing in Neuroscience for Data-Driven Discovery, Integration, and Dissemination

Abstract

© 2016 Opportunities offered by new neuro-technologies are threatened by lack of coherent plans to analyze, manage, and understand the data. High-performance computing will allow exploratory analysis of massive datasets stored in standardized formats, hosted in open repositories, and integrated with simulations.

Authors:
 [1];  [2];  [3];  [4];  [5];  [6];  [7];  [8];  [9];  [10];  [7];  [11];  [12];  [13]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Biolgoical Systems and Engineering Division; Univ. of California, San Francisco, CA (United States). Kavli Inst. for Fundamental Neuroscience; Univ. of California, Berkeley, CA (United States). Helen Wills Neuroscience Inst.
  2. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Center for Computing Research
  3. The Kavli Foundation, Oxnard, CA (United States)
  4. Google Research, Mountain View, CA (United States)
  5. Julich Research Centre (Germany). Inst. of Neuroscience and Medicine (INM-6) and INst. for Advanced Simulation (IAS-6)
  6. Julich Research Centre (Germany). Inst. of Neuroscience and Medicine (INM-6) and INst. for Advanced Simulation (IAS-6); RWTH Aachen Univ. (Germany). Dept. of Psychiatry and Dept. of Physics
  7. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division
  8. Univ. of California, San Francisco, CA (United States). Kavli Inst. for Fundamental Neuroscience, Howard Hughes Medical Inst. and Dept. of Physiology
  9. Argonne National Lab. (ANL), Argonne, IL (United States). Nanoscience Division; Univ. of Chicago, IL (United States). Dept. of Neurobiology
  10. Allen Inst. for Brain Science, Seattle, WA (United States)
  11. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  12. Univ. of California, Berkeley, CA (United States). Redwood Center for Theoretical Neuroscience
  13. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). NERSC
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1332918
Alternate Identifier(s):
OSTI ID: 1461976
Report Number(s):
SAND2016-11039J
Journal ID: ISSN 0896-6273; PII: S0896627316307851; TRN: US1700177
Grant/Contract Number:  
AC04-94AL85000; AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
Neuron
Additional Journal Information:
Journal Volume: 92; Journal Issue: 3; Journal ID: ISSN 0896-6273
Publisher:
Cell Press - Elsevier
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Bouchard, Kristofer E., Aimone, James B., Chun, Miyoung, Dean, Thomas, Denker, Michael, Diesmann, Markus, Donofrio, David D., Frank, Loren M., Kasthuri, Narayanan, Koch, Chirstof, Ruebel, Oliver, Simon, Horst D., Sommer, Friedrich T., and ., Prabhat. High-Performance Computing in Neuroscience for Data-Driven Discovery, Integration, and Dissemination. United States: N. p., 2016. Web. doi:10.1016/j.neuron.2016.10.035.
Bouchard, Kristofer E., Aimone, James B., Chun, Miyoung, Dean, Thomas, Denker, Michael, Diesmann, Markus, Donofrio, David D., Frank, Loren M., Kasthuri, Narayanan, Koch, Chirstof, Ruebel, Oliver, Simon, Horst D., Sommer, Friedrich T., & ., Prabhat. High-Performance Computing in Neuroscience for Data-Driven Discovery, Integration, and Dissemination. United States. https://doi.org/10.1016/j.neuron.2016.10.035
Bouchard, Kristofer E., Aimone, James B., Chun, Miyoung, Dean, Thomas, Denker, Michael, Diesmann, Markus, Donofrio, David D., Frank, Loren M., Kasthuri, Narayanan, Koch, Chirstof, Ruebel, Oliver, Simon, Horst D., Sommer, Friedrich T., and ., Prabhat. Wed . "High-Performance Computing in Neuroscience for Data-Driven Discovery, Integration, and Dissemination". United States. https://doi.org/10.1016/j.neuron.2016.10.035. https://www.osti.gov/servlets/purl/1332918.
@article{osti_1332918,
title = {High-Performance Computing in Neuroscience for Data-Driven Discovery, Integration, and Dissemination},
author = {Bouchard, Kristofer E. and Aimone, James B. and Chun, Miyoung and Dean, Thomas and Denker, Michael and Diesmann, Markus and Donofrio, David D. and Frank, Loren M. and Kasthuri, Narayanan and Koch, Chirstof and Ruebel, Oliver and Simon, Horst D. and Sommer, Friedrich T. and ., Prabhat},
abstractNote = {© 2016 Opportunities offered by new neuro-technologies are threatened by lack of coherent plans to analyze, manage, and understand the data. High-performance computing will allow exploratory analysis of massive datasets stored in standardized formats, hosted in open repositories, and integrated with simulations.},
doi = {10.1016/j.neuron.2016.10.035},
journal = {Neuron},
number = 3,
volume = 92,
place = {United States},
year = {Wed Nov 02 00:00:00 EDT 2016},
month = {Wed Nov 02 00:00:00 EDT 2016}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Citation Metrics:
Cited by: 21 works
Citation information provided by
Web of Science

Save / Share:

Works referenced in this record:

The quiet revolution of numerical weather prediction
journal, September 2015

  • Bauer, Peter; Thorpe, Alan; Brunet, Gilbert
  • Nature, Vol. 525, Issue 7567
  • DOI: 10.1038/nature14956

Beta oscillations in a large-scale sensorimotor cortical network: Directional influences revealed by Granger causality
journal, June 2004

  • Brovelli, A.; Ding, M.; Ledberg, A.
  • Proceedings of the National Academy of Sciences, Vol. 101, Issue 26
  • DOI: 10.1073/pnas.0308538101

Dimensionality reduction for large-scale neural recordings
journal, August 2014

  • Cunningham, John P.; Yu, Byron M.
  • Nature Neuroscience, Vol. 17, Issue 11
  • DOI: 10.1038/nn.3776

On simplicity and complexity in the brave new world of large-scale neuroscience
journal, June 2015


Neo: an object model for handling electrophysiology data in multiple formats
journal, January 2014

  • Garcia, Samuel; Guarino, Domenico; Jaillet, Florent
  • Frontiers in Neuroinformatics, Vol. 8
  • DOI: 10.3389/fninf.2014.00010

Worldwide initiatives to advance brain research
journal, August 2016

  • Grillner, Sten; Ip, Nancy; Koch, Christof
  • Nature Neuroscience, Vol. 19, Issue 9
  • DOI: 10.1038/nn.4371

Inferring cortical function in the mouse visual system through large-scale systems neuroscience
journal, July 2016

  • Hawrylycz, Michael; Anastassiou, Costas; Arkhipov, Anton
  • Proceedings of the National Academy of Sciences, Vol. 113, Issue 27
  • DOI: 10.1073/pnas.1512901113

Spiking network simulation code for petascale computers
journal, October 2014

  • Kunkel, Susanne; Schmidt, Maximilian; Eppler, Jochen M.
  • Frontiers in Neuroinformatics, Vol. 8
  • DOI: 10.3389/fninf.2014.00078

The big data challenges of connectomics
journal, October 2014

  • Lichtman, Jeff W.; Pfister, Hanspeter; Shavit, Nir
  • Nature Neuroscience, Vol. 17, Issue 11
  • DOI: 10.1038/nn.3837

Reconstruction and Simulation of Neocortical Microcircuitry
journal, October 2015


Network Motifs: Simple Building Blocks of Complex Networks
journal, October 2002


Works referencing / citing this record:

The SONATA Data Format for Efficient Description of Large-Scale Network Models
posted_content, September 2019


NeuroChaT: A toolbox to analyse the dynamics of neuronal encoding in freely-behaving rodents in vivo
journal, January 2019


NeuroSuites-BNs: An open web framework for massive Bayesian networks focused on neuroscience
posted_content, July 2020


BayeSuites: An open web framework for massive Bayesian networks focused on neuroscience
journal, March 2021


The SONATA data format for efficient description of large-scale network models
journal, February 2020


The SONATA Data Format for Efficient Description of Large-Scale Network Models
posted_content, September 2019


NeuroChaT: A toolbox to analyse the dynamics of neuronal encoding in freely-behaving rodents in vivo
journal, January 2019


Reproducibility and Comparability of Computational Models for Astrocyte Calcium Excitability
journal, February 2017

  • Manninen, Tiina; Havela, Riikka; Linne, Marja-Leena
  • Frontiers in Neuroinformatics, Vol. 11
  • DOI: 10.3389/fninf.2017.00011

Arkheia: Data Management and Communication for Open Computational Neuroscience
journal, March 2018