Parallel network simulations with NEURON

The NEURON Simulation Environment

Hines, M. L., & Carnevale, N. T. (1997) · Neural Computation · doi:10.1162/neco.1997.9.6.1179 · Cited by 2,630

Multilevelk-way Partitioning Scheme for Irregular Graphs

Karypis, G., & Kumar, V. (1998) · Journal of Parallel and Distributed Computing · doi:10.1006/jpdc.1997.1404 · Cited by 1,693

Linda in context

Carriero, N. J., & Gelernter, D. H. (1989) · Communications of the ACM · doi:10.1145/63334.63337 · Cited by 1,405

The Blue Brain Project

Markram, H. (2006) · Nature reviews. Neuroscience · doi:10.1038/nrn1848 · Cited by 1,227

Role of an A-Type K+ Conductance in the Back-Propagation of Action Potentials in the Dendrites of Hippocampal Pyramidal Neurons

Migliore, M., Hoffman, D. A., Magee, J. C., & Johnston, D. (1999) · Journal of Computational Neuroscience · doi:10.1023/a:1008906225285 · Cited by 334

Role of mossy fiber sprouting and mossy cell loss in hyperexcitability: a network model of the dentate gyrus incorporating cell types and axonal topography

Santhakumar, V., Aradi, I., & Soltesz, I. (2005) · Journal of Neurophysiology · doi:10.1152/jn.00777.2004 · Cited by 262

Advancing the Boundaries of High-Connectivity Network Simulation with Distributed Computing

Morrison, A., Mehring, C., Geisel, T., Aertsen, A., & Diesmann, M. (2005) · Neural Computation · doi:10.1162/0899766054026648 · Cited by 201

Efficient Event-Driven Simulation of Large Networks of Spiking Neurons and Dynamical Synapses

Mattia, M., & Giudice, P. D. (2000) · Neural Computation · doi:10.1162/089976600300014953 · Cited by 164

Optimization of MPI collective communication on BlueGene/L systems

Almasi, G. S., Heidelberger, P., Archer, C. J., Martorell, X., Erway, C. C., Moreira, J. E., Steinmacher-Burow, B., & Zheng, Y. (2005) · International Conference on Supercomputing · doi:10.1145/1088149.1088183 · Cited by 160

SpikeNET: an event-driven simulation package for modelling large networks of spiking neurons

Delorme, A., & Thorpe, S. J. (2003) · Network Computation in Neural Systems · doi:10.1088/0954-898x/14/4/301 · Cited by 98

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

Simulation 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

NEURON and Python

Hines, M. L. (2009) · Frontiers in Neuroinformatics · doi:10.3389/neuro.11.001.2009 · Cited by 414

Neural 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

Interneuronal mechanisms of hippocampal theta oscillations in a full-scale model of the rodent CA1 circuit

Bezaire, M. J., Raikov, I., Burk, K., Vyas, D., & Soltesz, I. (2016) · eLife · doi:10.7554/elife.18566 · Cited by 198

neuroConstruct: A Tool for Modeling Networks of Neurons in 3D Space

Gleeson, P., Steuber, V., & Silver, R. A. (2007) · Neuron · doi:10.1016/j.neuron.2007.03.025 · Cited by 211

Advancing the Boundaries of High-Connectivity Network Simulation with Distributed Computing

Morrison, A., Mehring, C., Geisel, T., Aertsen, A., & Diesmann, M. (2005) · Neural Computation · doi:10.1162/0899766054026648 · Cited by 201

Structural neurobiology: missing link to a mechanistic understanding of neural computation

Denk, W. T., Briggman, K. L., & Helmstaedter, M. N. (2012) · Nature reviews. Neuroscience · doi:10.1038/nrn3169 · Cited by 194

NetPyNE, a tool for data-driven multiscale modeling of brain circuits

Dura-Bernal, S., Suter, B. A., Gleeson, P., Cantarelli, M., Quintana, A., Rodriguez, F., Kedziora, D. J., Chadderdon, G. L., Kerr, C. C., Neymotin, S. A., et al. (2019) · eLife · doi:10.7554/elife.44494 · Cited by 169

The Emergent neural modeling system

Aisa, B., Mingus, B., & O'Reilly, R. (2008) · Neural Networks · doi:10.1016/j.neunet.2008.06.016 · Cited by 152

Why Are Computational Neuroscience and Systems Biology So Separate?

Schutter, E. D. (2008) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000078 · Cited by 109

CoreNEURON : An Optimized Compute Engine for the NEURON Simulator

Kumbhar, P., Hines, M. L., FOURIAUX, J., Ovcharenko, A., King, J. G., Delalondre, F., & Schürmann, F. (2019) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2019.00063 · Cited by 98

Accurate and Fast Simulation of Channel Noise in Conductance-Based Model Neurons by Diffusion Approximation

Linaro, D., Storace, M., & Giugliano, M. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1001102 · Cited by 88

Arbor — A Morphologically-Detailed Neural Network Simulation Library for Contemporary High-Performance Computing Architectures

Akar, N. A., Cumming, B., Karakasis, V., Kusters, A., Klijn, W., Peyser, A., & Yates, S. (2019) · Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP) · doi:10.1109/empdp.2019.8671560 · Cited by 87

Efficient Parallel Simulation of Large-Scale Neuronal Networks on Clusters of Multiprocessor Computers

Pleßer, H. E., Eppler, J. M., Morrison, A., Diesmann, M., & Gewaltig, M.-O. (2007) · Lecture notes in computer science · doi:10.1007/978-3-540-74466-5_71 · Cited by 87

Fully implicit parallel simulation of single neurons

Hines, M. L., Markram, H., & Schürmann, F. (2008) · Journal of Computational Neuroscience · doi:10.1007/s10827-008-0087-5 · Cited by 79

Reproducibility in Computational Neuroscience Models and Simulations

McDougal, R. A., Bulanova, A., & Lytton, W. W. (2016) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2016.2539602 · Cited by 73

Neurofitter: A parameter tuning package for a wide range of electrophysiological neuron models

Geit, W. A. H. V. (2007) · Frontiers in Neuroinformatics · doi:10.3389/neuro.11.001.2007 · Cited by 70

Translating network models to parallel hardware in NEURON

Hines, M. L., & Carnevale, N. T. (2007) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2007.09.010 · Cited by 66

Realizing biological spiking network models in a configurable wafer-scale hardware system

Fieres, J., Schemmel, J., & Meier, K. (2008) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2008.4633916 · Cited by 66

NEURON Simulation Environment

Hines, M. L., & Carnevale, T. (2015) · Encyclopedia of Computational Neuroscience · doi:10.1007/978-1-4614-6675-8_795 · Cited by 66

Circuit reconstruction tools today

Smith, S. J. (2007) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2007.11.004 · Cited by 63

A General and Efficient Method for Incorporating Precise Spike Times in Globally Time-Driven Simulations

Hanuschkin, A., Kunkel, S., Helias, M., Morrison, A., & Diesmann, M. (2010) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2010.00113 · Cited by 61

Toward a full-scale computational model of the rat dentate gyrus

Schneider, C. J., Bezaire, M. J., & Soltész, I. (2012) · Frontiers in Neural Circuits · doi:10.3389/fncir.2012.00083 · Cited by 60

Responses of Retinal Ganglion Cells to Extracellular Electrical Stimulation, from Single Cell to Population: Model-Based Analysis

Tsai, D., Chen, S. C., Protti, D. A., Morley, J. W., Suaning, G. J., & Lovell, N. H. (2012) · PLoS ONE · doi:10.1371/journal.pone.0053357 · Cited by 56

BioNet: A Python interface to NEURON for modeling large-scale networks

Gratiy, S. L., Billeh, Y. N., Dai, K., Mitelut, C., Feng, D. H., Gouwens, N. W., Cain, N., Koch, C., Anastassiou, C. A., & Arkhipov, A. S. (2018) · PLoS ONE · doi:10.1371/journal.pone.0201630 · Cited by 53

HRLSim: A High Performance Spiking Neural Network Simulator for GPGPU Clusters

Minkovich, K., Thibeault, C. M., O'Brien, M. J., Nogin, A., Cho, Y., & Srinivasa, N. (2014) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2013.2276056 · Cited by 54

How Big Data and High-Performance Computing Drive Brain Science

Chen, S., He, Z., Han, X., He, X., Li, R., Zhu, H., Zhao, D., Dai, C., Zhang, Y., Lu, Z., et al. (2019) · Genomics Proteomics & Bioinformatics · doi:10.1016/j.gpb.2019.09.003 · Cited by 57

A novel CPU/GPU simulation environment for large-scale biologically realistic neural modeling

Hoang, R. V., Tanna, D., Bray, L. C. J., Dascalu, S. M., & Harris, F. C. (2013) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2013.00019 · Cited by 53

Software for Brain Network Simulations: A Comparative Study

Tikidji-Hamburyan, R. A., Narayana, V. K., Bozkuş, Z., & El-Ghazawi, T. A. (2017) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2017.00046 · Cited by 60

Modernizing the NEURON Simulator for Sustainability, Portability, and Performance

Awile, O., Kumbhar, P., Cornu, N., Durá-Bernal, S., King, J. G., Lupton, O., Magkanaris, I., McDougal, R. A., Newton, A. J. H., Pereira, F., et al. (2022) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2022.884046 · Cited by 53

An Ultrascalable Solution to Large-scale Neural Tissue Simulation

Kozloski, J., & Wagner, J. (2011) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2011.00015 · Cited by 50

A MODEL OF GRID CELLS INVOLVING EXTRA HIPPOCAMPAL PATH INTEGRATION, AND THE HIPPOCAMPAL LOOP

Gaussier, P., Banquet, J. P., Sargolini, F., GIOVANNANGELI, C., Save, É., & Poucet, B. (2007) · Journal of Integrative Neuroscience · doi:10.1142/s021963520700160x · Cited by 54

A GENERALIZED LEAKY INTEGRATE-AND-FIRE NEURON MODEL WITH FAST IMPLEMENTATION METHOD

Wang, Z., Guo, L., & Adjouadi, M. (2014) · International Journal of Neural Systems · doi:10.1142/s0129065714400048 · Cited by 47

Neuron splitting in compute-bound parallel network simulations enables runtime scaling with twice as many processors

Hines, M. L., Eichner, H., & Schürmann, F. (2008) · Journal of Computational Neuroscience · doi:10.1007/s10827-007-0073-3 · Cited by 47

Meeting the Memory Challenges of Brain-Scale Network Simulation

Kunkel, S., Potjans, T. C., Eppler, J. M., Pleßer, H. E., Morrison, A., & Diesmann, M. (2012) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2011.00035 · Cited by 50

Experimentally guided modelling of dendritic excitability in rat neocortical pyramidal neurones

Keren, N., Bar‐Yehuda, D., & Korngreen, A. (2009) · The Journal of Physiology · doi:10.1113/jphysiol.2008.167130 · Cited by 48

Propagation of Seizure-like Activity in a Model of Neocortex

van Drongelen, W., Lee, H. C., Stevens, R. L., & Hereld, M. (2007) · Journal of Clinical Neurophysiology · doi:10.1097/wnp.0b013e318039b4de · Cited by 43

Simulation Neurotechnologies for Advancing Brain Research: Parallelizing Large Networks in NEURON

Lytton, W. W., Seidenstein, A. H., Durá-Bernal, S., McDougal, R. A., Schürmann, F., & Hines, M. L. (2016) · Neural Computation · doi:10.1162/neco_a_00876 · Cited by 43

Code Generation in Computational Neuroscience: A Review of Tools and Techniques

Blundell, I., Brette, R., Cleland, T. A., Close, T., Coca, D., Davison, A. P., Diaz-Pier, S., Musoles, C. F., Gleeson, P., Goodman, D. F. M., et al. (2018) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2018.00068 · Cited by 43

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

Comparison of neuronal spike exchange methods on a Blue Gene/P supercomputer

Hines, M. L. (2011) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2011.00049 · Cited by 42

Variability in State-Dependent Plasticity of Intrinsic Properties during Cell-Autonomous Self-Regulation of Calcium Homeostasis in Hippocampal Model Neurons

Srikanth, S., & Narayanan, R. (2015) · eNeuro · doi:10.1523/eneuro.0053-15.2015 · Cited by 41

Concurrent heterogeneous neural model simulation on real-time neuromimetic hardware

Rast, A. D., Galluppi, F., Davies, S., Plana, L. A., Patterson, C., Sharp, T., Lester, D., & Furber, S. B. (2011) · Neural Networks · doi:10.1016/j.neunet.2011.06.014 · Cited by 39

A GPU-based computational framework that bridges neuron simulation and artificial intelligence

Zhang, Y., He, G., Ма, Л., Liu, X., Hjorth, J. J. J., Kozlov, A., He, Y., Zhang, S., Kotaleski, J. H., Tian, Y., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-41553-7 · Cited by 40

Evolutionary algorithm optimization of biological learning parameters in a biomimetic neuroprosthesis

Durá-Bernal, S., Neymotin, S. A., Kerr, C. C., Sivagnanam, S., Majumdar, A., Francis, J. T., & Lytton, W. W. (2017) · IBM Journal of Research and Development · doi:10.1147/jrd.2017.2656758 · Cited by 42

Early experiences in developing and managing the neuroscience gateway

Sivagnanam, S., Majumdar, A., Yoshimoto, K. K., Astakhov, V., Bandrowski, A. E., Martone, M. E., & Carnevale, N. T. (2014) · Concurrency and Computation Practice and Experience · doi:10.1002/cpe.3283 · Cited by 39

Limits to the development of feed-forward structures in large recurrent neuronal networks

Kunkel, S. (2010) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2010.00160 · Cited by 39

NEURON Simulation Environment

Hines, M. L., Carnevale, T., & McDougal, R. A. (2022) · Encyclopedia of Computational Neuroscience · doi:10.1007/978-1-0716-1006-0_795 · Cited by 37

A Million-Plus Neuron Model of the Hippocampal Dentate Gyrus: Critical Role for Topography in Determining Spatiotemporal Network Dynamics

Hendrickson, P. J., Yu, G. J., Song, D. B., & Berger, T. W. (2015) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2015.2445771 · Cited by 36

A Process for Digitizing and Simulating Biologically Realistic Oligocellular Networks Demonstrated for the Neuro-Glio-Vascular Ensemble

Coggan, J. S., Calì, C., Keller, D. X., Agus, M., Boges, D. J., Abdellah, M., Kare, K., Lehväslaiho, H., Eilemann, S., Jolivet, R., et al. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00664 · Cited by 36

Tonic-Clonic Transitions in Computer Simulation

Lytton, W. W., & Omurtag, A. (2007) · Journal of Clinical Neurophysiology · doi:10.1097/wnp.0b013e3180336fc0 · Cited by 36

Scalable event-driven native parallel processing

Rast, A. D., Jin, X., Galluppi, F., Plana, L. A., Patterson, C., & Furber, S. B. (2010) · ACM International Conference on Computing Frontiers (CF) · doi:10.1145/1787275.1787279 · Cited by 36

T2N as a new tool for robust electrophysiological modeling demonstrated for mature and adult-born dentate granule cells

Beining, M., Mongiat, L. A., Schwarzacher, S. W., Cuntz, H., & Jedlička, P. (2017) · eLife · doi:10.7554/elife.26517 · Cited by 36

Neuron simulation environment

Carnevale, T. (2007) · Scholarpedia · doi:10.4249/scholarpedia.1378 · Cited by 34

Just-in-Time Connectivity for Large Spiking Networks

Lytton, W. W., Omurtag, A., Neymotin, S. A., & Hines, M. L. (2008) · Neural Computation · doi:10.1162/neco.2008.10-07-622 · Cited by 34

A forecast-based STDP rule suitable for neuromorphic implementation

Davies, S., Galluppi, F., Rast, A. D., & Furber, S. B. (2012) · Neural Networks · doi:10.1016/j.neunet.2012.02.018 · Cited by 31

Constructing Neuronal Network Models in Massively Parallel Environments

Ippen, T., Eppler, J. M., Pleßer, H. E., & Diesmann, M. (2017) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2017.00030 · Cited by 31

A Component-Based Extension Framework for Large-Scale Parallel Simulations in NEURON

King, J. G. (2009) · Frontiers in Neuroinformatics · doi:10.3389/neuro.11.010.2009 · Cited by 30

Optimization of applications with non-blocking neighborhood collectives via multisends on the Blue Gene/P supercomputer

Kumar, S., Heidelberger, P., Chen, D., & Hines, M. L. (2010) · IEEE International Parallel and Distributed Processing Symposium (IPDPS) · doi:10.1109/ipdps.2010.5470407 · Cited by 29

Computational modeling of epilepsy

Bezaire, M. J., & Soltész, I. (2011) · Epilepsia · doi:10.1111/j.1528-1167.2011.03225.x · Cited by 27

Toward Brain-Inspired Learning With the Neuromorphic Snake-Like Robot and the Neurorobotic Platform

Chen, G., Bing, Z., Röhrbein, F., Conradt, J., Huang, K., Cheng, L., Jiang, Z., & Knoll, A. (2017) · IEEE Transactions on Cognitive and Developmental Systems · doi:10.1109/tcds.2017.2712712 · Cited by 26

Simplicity and Efficiency of Integrate-and-Fire Neuron Models

Pleßer, H. E., & Diesmann, M. (2008) · Neural Computation · doi:10.1162/neco.2008.03-08-731 · Cited by 24

Jaxley: differentiable simulation enables large-scale training of detailed biophysical models of neural dynamics

Deistler, M., Kadhim, K. L., Pals, M., Beck, J., Huang, Z., Gloeckler, M., Lappalainen, J. K., Schröder, C., Berens, P., Gonçalves, P. J., et al. (2025) · Nature Methods · doi:10.1038/s41592-025-02895-w · Cited by 38

Linking Macroscopic with Microscopic Neuroanatomy Using Synthetic Neuronal Populations

Schneider, C. J., Cuntz, H., & Soltész, I. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003921 · Cited by 26

Large-scale biophysically detailed model of somatosensory thalamocortical circuits in NetPyNE

Borges, F. S., Moreira, J. V. S., Takarabe, L. M., Lytton, W. W., & Durá-Bernal, S. (2022) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2022.884245 · Cited by 23

Degeneracy in the emergence of spike-triggered average of hippocampal pyramidal neurons

Jain, A., & Narayanan, R. (2020) · Scientific Reports · doi:10.1038/s41598-019-57243-8 · Cited by 23

Neurite, a Finite Difference Large Scale Parallel Program for the Simulation of Electrical Signal Propagation in Neurites under Mechanical Loading

García-Grajales, J. A., Rucabado, G., García-Dopico, A., Peña, J.-M., & Jérusalem, A. (2015) · PLoS ONE · doi:10.1371/journal.pone.0116532 · Cited by 21

PAX: A mixed hardware/software simulation platform for spiking neural networks

Renaud, S., Tomas, J., Lewis, N., Bornat, Y., Daouzli, A., Rudolph, M., Alain Destexhe, A., & Saïghi, S. (2010) · Neural Networks · doi:10.1016/j.neunet.2010.02.006 · Cited by 21

PyRates—A Python framework for rate-based neural simulations

Gast, R., Rose, D., Salomon, C. J., Möller, H. E., Weiskopf, N., & Knösche, T. R. (2019) · PLoS ONE · doi:10.1371/journal.pone.0225900 · Cited by 21

Neural Simulations on Multi-Core Architectures

Eichner, H. (2009) · Frontiers in Neuroinformatics · doi:10.3389/neuro.11.021.2009 · Cited by 20

Efficient phase coding in hippocampal place cells

Seenivasan, P., & Narayanan, R. (2020) · Physical Review Research · doi:10.1103/physrevresearch.2.033393 · Cited by 22

Whole Brain Emulation

Sandberg, A., Bostrom, N., & Martin, J. (2008) · Cited by 20

Computational models of dentate gyrus with epilepsy-induced morphological alterations in granule cells

Tejada, J., & Roque, A. C. (2014) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2014.02.007 · Cited by 19

Accelerating compartmental modeling on a graphical processing unit

Ben‐Shalom, R., Liberman, G., & Korngreen, A. (2013) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2013.00004 · Cited by 19

NEURON Simulation Environment

Hines, M. L., Carnevale, T., & McDougal, R. A. (2019) · Encyclopedia of Computational Neuroscience · doi:10.1007/978-1-4614-7320-6_795-2 · Cited by 19

Interactions between inhibitory interneurons and excitatory associational circuitry in determining Spatio-Temporal dynamics of hippocampal dentate granule cells: A Large-Scale computational study

Hendrickson, P. J., Yu, G. J., Song, D., & Berger, T. W. (2015) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2015.00155 · Cited by 18

Recent Advances and New Frontiers in Spiking Neural Networks

Zhang, D., Zhang, T., Jia, S., Wang, Q., & Xu, B. (2022) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2022/790 · Cited by 25

Virtues, Pitfalls, and Methodology of Neuronal Network Modeling and Simulations on Supercomputers

Lansner, A., & Diesmann, M. (2012) · Springer eBooks · doi:10.1007/978-94-007-3858-4_10 · Cited by 19

NEST by Example: An Introduction to the Neural Simulation Tool NEST

Gewaltig, M.-O., Morrison, A., & Pleßer, H. E. (2012) · Springer eBooks · doi:10.1007/978-94-007-3858-4_18 · Cited by 18

Parallel architecture and optimization for discrete-event simulation of spike neural networks

Tang, Y., Zhang, B., Wu, J., Hu, T., Zhou, J., & Liu, F. (2012) · Science China Technological Sciences · doi:10.1007/s11431-012-5084-2 · Cited by 17

Rebasing I/O for Scientific Computing: Leveraging Storage Class Memory in an IBM BlueGene/Q Supercomputer

Schürmann, F., Delalondre, F., Kumbhar, P., Biddiscombe, J., Gila, M., Tacchella, D., Curioni, A., Metzler, B., Morjan, P., Fenkes, J., et al. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-07518-1_21 · Cited by 16

The NEST Dry-Run Mode: Efficient Dynamic Analysis of Neuronal Network Simulation Code

Kunkel, S., & Schenck, W. (2017) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2017.00040 · Cited by 16

Silicon-Based Dynamic Synapse With Depressing Response

Dowrick, T., Hall, S., & Mcdaid, L. J. (2012) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2012.2211035 · Cited by 16

NeMo

Plagge, M., Carothers, C. D., Gonsiorowski, E. J., & McGlohon, N. (2018) · ACM Transactions on Modeling and Computer Simulation · doi:10.1145/3186317 · Cited by 16

A Federated Design for a Neurobiological Simulation Engine: The CBI Federated Software Architecture

Cornelis, H., Coop, A. D., & Bower, J. M. (2012) · PLoS ONE · doi:10.1371/journal.pone.0028956 · Cited by 15

Decision making under uncertainty in a spiking neural network model of the basal ganglia

Héricé, C., Khalil, R., Moftah, M. Z., Boraud, T., Guthrie, M., & Garenne, A. (2016) · Journal of Integrative Neuroscience · doi:10.1142/s021963521650028x · Cited by 14

Math Model of Neuron and Nervous System Research Based on AI Constructor Creating Virtual Neural Circuits

Galiautdinov, R., & Mkrttchian, V. S. (2019) · Advances in computational intelligence and robotics book series · doi:10.4018/978-1-7998-1581-5.ch015 · Cited by 14

Brain-like optoelectronic artificial synapses with ultralow energy consumption based on MXene floating-gates for emotion recognition

Cao, Y., Zhao, C., Zhao, T., Sun, Y., Liu, Z., Li, X., Yin, L., Gu, J., Ren, H., Geng, X., et al. (2023) · Journal of Materials Chemistry C · doi:10.1039/d2tc04745d · Cited by 14

A Modular Workflow for Performance Benchmarking of Neuronal Network Simulations

Albers, J., Pronold, J., Kurth, A. C., Vennemo, S. B., Mood, K. H., Patronis, A., Terhorst, D., Jordan, J., Kunkel, S., Tetzlaff, T., et al. (2022) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2022.837549 · Cited by 14

Simulations of cortical networks using spatially extended conductance‐based neuronal models

Haufler, D., Ito, S., Koch, C., & Arkhipov, A. S. (2022) · The Journal of Physiology · doi:10.1113/jp284030 · Cited by 13

Integrating Brain Structure and Dynamics on Supercomputers

van Albada, S. J., Kunkel, S., Morrison, A., & Diesmann, M. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-12084-3_3 · Cited by 13

The virtual slice setup

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