The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
Parallel network simulations with NEURON
Open accessAbstract
The NEURON simulation environment has been extended to support parallel network simulations. Each processor integrates the equations for its subnet over an interval equal to the minimum (interprocessor) presynaptic spike generation to postsynaptic spike delivery connection delay. The performance of three published network models with very different spike patterns exhibits superlinear speedup on Beowulf clusters and demonstrates that spike communication overhead is often less than the benefit of an increased fraction of the entire problem fitting into high speed cache. On the EPFL IBM Blue Gene, almost linear speedup was obtained up to 100 processors. Increasing one model from 500 to 40,000 realistic cells exhibited almost linear speedup on 2,000 processors, with an integration time of 9.8 seconds and communication time of 1.3 seconds. The potential for speed-ups of several orders of magnitude makes practical the running of large network simulations that could otherwise not be explored.
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“Previously, we built a dentate gyrus model to study epileptic network dynamics (Santhakumar et al., 2005; Morgan and Soltesz, 2008) that was then used by several groups to study disparate topics including epilepsy, network mechanisms of inhibition and excitability, simulation optimization, and modeling software”
From Interneuronal mechanisms of hippocampal theta oscillations in a full-scale model of the rodent CA1 circuit (2016) · cites this paper as Migliore et al., 2006
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Cites
The NEURON Simulation Environment
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Advancing the Boundaries of High-Connectivity Network Simulation with Distributed Computing
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Dendrodendritic Inhibition and Simulated Odor Responses in a Detailed Olfactory Bulb Network Model
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SpikeNET: an event-driven simulation package for modelling large networks of spiking neurons
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Independent Variable Time-Step Integration of Individual Neurons for Network Simulations
Lytton, W. W., & Hines, M. L. (2005) · Neural Computation · doi:10.1162/0899766053429453 · Cited by 43
Self-citationDiscrete event simulation in the NEURON environment
Hines, M. L., & Carnevale, N. T. (2004) · Neurocomputing · doi:10.1016/j.neucom.2004.01.175 · Cited by 39
Self-citationA large-scale model of the cerebellar cortex using PGENESIS
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Reconstruction and Simulation of Neocortical Microcircuitry
Markram, H., Muller, E., Ramaswamy, S., Reimann, M. W., Abdellah, M., Sanchez, C. A., Ailamaki, A., Alonso-Nanclares, L., Antille, N., Arsever, S., et al. (2015) · Cell · doi:10.1016/j.cell.2015.09.029 · Cited by 1,557
Self-citationSimulation of networks of spiking neurons: A review of tools and strategies
Brette, R., Rudolph, M., Carnevale, T., Hines, M. L., Beeman, D., Bower, J. M., Diesmann, M., Morrison, A., Goodman, P. H., Harris, F. C., et al. (2007) · Journal of Computational Neuroscience · doi:10.1007/s10827-007-0038-6 · Cited by 853
Self-citationHines, M. L. (2009) · Frontiers in Neuroinformatics · doi:10.3389/neuro.11.001.2009 · Cited by 414
Self-citationNeural networks: An overview of early research, current frameworks and new challenges
Prieto, A., Prieto, B., Ortigosa, E. M., Ros, E., Pelayo, F. J., Ortega, J., & Rojas, I. (2016) · Neurocomputing · doi:10.1016/j.neucom.2016.06.014 · Cited by 411
Computer modelling of epilepsy
Lytton, W. W. (2008) · Nature reviews. Neuroscience · doi:10.1038/nrn2416 · Cited by 291
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Metadata
- Authors
- Migliore, M., Cannia, C., Lytton, W. W., Markram, H., & Hines, M. L.
- Affiliations
- National Research Council (IT)
- State University of New York (US)
- École Polytechnique Fédérale de Lausanne (CH)
- Yale University (US)
- Corresponding author
- Migliore, M.
- Venue
- Journal of Computational Neuroscience
- Published
- 2006-05-26
- Volume
- 21
- Issue
- 2
- Pages
- 119-129
- ISSN
- 0929-5313 (ISSN-L)
- 1573-6873
- PMC
- PMC2655137
- OpenAlex
- W2170402833
- Cited by
- 196
- References
- 20
- Citations by year
- 2026: 5 · 2025: 4 · 2024: 7 · 2023: 4 · 2022: 12 · 2021: 2 · 2020: 10 · 2019: 10 · 2018: 5 · 2017: 9 · 2016: 19 · 2015: 12 · 2014: 14 · 2013: 8 · 2012: 14
- FWCI
- 21.73
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Journal of Computational Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion, cc-by-nc-nd)
- Funders
- Yale University
- École Polytechnique Fédérale de Lausanne
- National Institutes of Health
- National Institute of Neurological Disorders and Stroke (NS11613, R01NS045612, NS045612, R01NS011613)
- Topics
- Physical Sciences › Computer Science › Hardware and Architecture › Parallel Computing and Optimization Techniques
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Physical Sciences › Computer Science › Computer Networks and Communications › Distributed and Parallel Computing Systems
- Keywords
- spiking neural networks, superlinear speedup, Beowulf cluster, network models, computational neuroscience
- MeSH terms
- Action Potentials, Algorithms, Animals, Cerebral Cortex, Humans, Nerve Net, Neural Pathways, Synaptic Transmission, Neurons, Software, Neural Networks, Computer
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