Publications of Diesmann, M

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140 publication entries, 81 of them (printed in bold in the list) acknowledge the project support.
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Paper (reviewed)

Bakker et al. 2012Bakker, R., Wachtler, T. and Diesmann, M.CoCoMac 2.0 and the future of tract-tracing databasesFront Neuroinform. (2012) 6: 30.
doi:10.3389/fninf.2012.00030
fulltext
Brüderle et al. 2011Brüderle, D., Petrovici, M. A., Vogginger, B., Ehrlich, M., Pfeil, T., Millner, S., Grübl, A., Wendt, K., Müller, E., Schwartz, M.-O., de Oliveira, D. H., Jeltsch, S., Fieres, J., Schilling, M., Müller, P., Breitwieser, O., Petkov, V., Muller, L., Davison, A. P., Krishnamurthy, P., Kremkow, J., Lundqvist, M., Muller, E., Partzsch, J., Scholze, S., Zühl, L., Mayr, C., Destexhe, A., Diesmann, M., Potjans, T. C., Lansner, A., Schüffny, R., Schemmel, J. and Meier, K. A comprehensive workflow for general-purpose neural modeling with highly configurable neuromorphic hardware systemsBiological Cybernetics (2011) 104(4-5): 263-296
doi:10.1007/s00422-011-0435-9
abstract, fulltext
Deger et al. 2012Deger, M., Helias, M., Rotter, S. and Diesmann, M. Spike-Timing Dependence of Structural Plasticity Explains Cooperative Synapse Formation in the NeocortexPLoS Comput Biol (2012) 8(9): e1002689
doi:10.1371/journal.pcbi.1002689
Denker et al. 2011cDenker, M., Roux, S., Lindén, H., Diesmann, M., Riehle, A. and Grün, S.The local field potential reflects surplus spike synchronyCerebral Cortex (2011) 21:2681-2695
doi:10.1093/cercor/bhr040
abstract, fulltext
Gerstein et al. 2012Gerstein, G.L., Williams, E.R., Diesmann, M., Grün, S. and Trengove, C.Detecting synfire chains in parallel spike dataJournal of Neuroscience Methods (2012) 206(1): 54-64
doi:10.1016/j.jneumeth.2012.02.003
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Grytskyy et al. 2013Grytskyy, D., Tetzlaff, T., Diesmann, M., and Helias, M.A unified view on weakly correlated recurrent networksFront Comput Neurosci. (2013) 7:131
doi:10.3389/fncom.2013.00131
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Grytskyy et al. 2013bGrytskyy, D., Tetzlaff, T., Diesmann, M. and Helias, M.A unified view on weakly correlated recurrent networksFrontiers in computational neuroscience (2013) 7(131): 1-19
doi:10.3389/fncom.2013.00131
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Helias et al. 2011Helias, M., Deger, M., Rotter, S. and Diesmann, M.Finite post synaptic potentials cause a fast neuronal responseFront. Neurosci. (2011) 5:19
doi:10.3389/fnins.2011.00019
abstract, fulltext
Helias et al. 2012Helias, M., Kunkel, S., Masumoto, G., Igarashi, J., Eppler, J. M., Ishii, S., Fukai, T., Morrison, A. and Diesmann, M. Supercomputers ready for use as discovery machines for neuroscienceFront. Neuroinform. (2012) 6:26
doi:10.3389/fninf.2012.00026
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Helias et al. 2013Helias, M., Tetzlaff, T., and Diesmann, M.Echoes in correlated neural systems New J. Phys. (2013) 15: 023002
doi:10.1088/1367-2630/15/2/023002
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Helias et al. 2014Helias, M., Tetzlaff, T. and Diesmann, M. The Correlation Structure of Local Neuronal Networks Intrinsically Results from Recurrent DynamicsPLoS Computational Biology (2014) 10(1): e1003428
doi:10.1371/journal.pcbi.1003428
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Kriener et al. 2014bHelias, M., Rotter, S., Diesmann, M. and Einevoll, G. T. How pattern formation in ring networks of excitatory and inhibitory spiking neurons depends on the input current regimeFrontiers in computational neuroscience (2014) 7: 1
doi:10.3389/fncom.2013.00187
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Kunkel et al. 2011Kunkel, S., Diesmann, M. and Morrison, A.Limits to the Development of Feed-Forward Structures in Large Recurrent Neuronal NetworksFront. Comput. Neurosci. (2011) 4:160
doi:10.3389/fncom.2010.00160
abstract, fulltext
Kunkel et al. 2011bKunkel, S., Potjans, T.C., Eppler, J.M., Plesser, H.E., Morrison, A. and Diesmann, M.Meeting the memory challenges of brain-scale network simulationFront. Neuroinform. (2011) 5:35
doi:10.3389/fninf.2011.00035
abstract
Kunkel et al. 2014Kunkel, S., Schmidt, M., Eppler, J.M., Plesser, H.E., Masumoto, G., Igarashi, J., Ishii, S., Fukai, T., Morrison, A., Diesmann, M. and Helias, M. Spiking network simulation code for petascale computersFront. Neuroinform. (2014) 8:78
doi:10.3389/fninf.2014.00078
abstract, fulltext
Lindén et al. 2011Lindén, H., Tetzlaff, T., Potjans, T.C., Pettersen, K.H., Grün, S., Diesmann, M. and Einevoll, G.T.Modeling the spatial reach of the LFPNeuron (2011) 72(5): 859-872
doi:10.1016/j.neuron.2011.11.006
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Pfeil et al. 2012bPfeil, T., Potjans, T. C., Schrader, S., Potjans, W., Schemmel, J., Diesmann, M. and Meier, K. Is a 4-bit synaptic weight resolution enough? - constraints on enabling spike-timing dependent plasticity in neuromorphic hardwareFront. Neurosci. (2012) 6:90
doi:10.3389/fnins.2012.00090
abstract, fulltext
Potjans and Diesmann 2012Potjans, T. and Diesmann, M.The Cell-Type Specific Cortical Microcircuit: Relating Structure and Activity in a Full-Scale Spiking Network ModelFirst published online: December 2, 2012. Cereb. Cortex (2014) 24 (3): 785-806
doi:10.1093/cercor/bhs358
abstract, fulltext
Potjans et al. 2011bPotjans, W., Diesmann, M. and Morrison, A.An Imperfect Dopaminergic Error Signal Can Drive Temporal-Difference LearningPLoS Comput Biol. (2011) 7(5): e1001133
doi:10.1371/journal.pcbi.1001133
abstract, fulltext
Schultze-Kraft et al. 2013Schultze-Kraft, M., Diesmann, M., Grün, S. and Helias, M.Noise Suppression and Surplus Synchrony by Coincidence DetectionPLoS Comput Biol. (2013) 9(4):e1002904
doi:10.1371/journal.pcbi.1002904
Tetzlaff et al. 2012Tetzlaff, T., Helias, M., Einevoll, G. T. and Diesmann, M. Decorrelation of Neural-Network Activity by Inhibitory FeedbackPLoS Comput Biol (2012) 8(8): e1002596
doi:10.1371/journal.pcbi.1002596
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van Albada et al. 2015van Albada, S.J., Helias, M. and Diesmann, M.Scalability of Asynchronous Networks Is Limited by One-to-One Mapping between Effective Connectivity and CorrelationsPLoS Comput Biol (2015) 11(9): e1004490
doi:10.1371/journal.pcbi.1004490
Wagatsuma et al. 2011Wagatsuma, N., Potjans, T.C., Diesmann, M. and Fukai, T.Layer-dependent attentional processing by top-down signals in a visual cortical microcircuit modelFront. Comput. Neurosci. (2011) 5:31
doi:10.3389/fncom.2011.00031
abstract, fulltext

Book chapter

Lansner and Diesmann 2012Lansner, A. and Diesmann, M. Virtues, Pitfalls, and Methodology of Neuronal Network Modeling and Simulations on SupercomputersComputational Systems Neurobiology, Editors N. Le Novère, ISBN: 978-94-007-3857-7 (Print) 978-94-007-3858-4 (Online) (2012): 283-315 abstract
van Albada et al. 2014van Albada, S., Helias, M. and Diesmann, M. Integrating brain structure and dynamics on supercomputers"Springer Cham Heidelberg New York Dordrecht London
ISBN: 978-3-319-12083-6 (print), 978-3-319-12084-3 (electronic)

Lecture Notes in Computer Science 8603, 22-32 (2014) [10.1007/978-3-319-12084-3_3] "

doi:10.1007/978-3-319-12084-3_3
fulltext

Conference contribution: talk

Bakker and Diesmann 2014Bakker, R., Thomas, W. and Diesmann, M. Do gold standards remain gold standards when compiling a large number of published tract-tracing studies into a connectivity database?Neuroinformatics 2014, Leiden, Netherlands, 25 Aug - 27 Aug, 2014., INCF2014, Leiden, Netherlands, 08/25/2014 - 08/27/2014
doi:10.3389/conf.fninf.2014.18.00072
fulltext
Diesmann 2012 aDiesmann, M. Active decorrelation in local cortical networksBiology and Physics of Information Processing ; Nordita, Stockholm ; Sweden ; 04/16/2012 - 05/11/2012
Diesmann 2012bDiesmann, M. Brain-scale neuronal network simulations on K4th Biosupercomputing Symposium ; Tokyo ; Japan ; 12/03/2012 - 12/05/2012
Diesmann 2012cDiesmann, M. Decorrelation of neural-network activity by inhibitory feedbackVariance & Invariants in Brain and Behavior ; TECHNION, Haifa ; Israel ; 05/21/2012 - 05/23/2012
Diesmann2013Diesmann, M.From local to brain-scale models at cellular and synaptic resolution
CENEM San Pedro Workshop, San Pedro de Atacama, Chile, 10/23/2013 - 10/25/2013
Diesmann2013bDiesmann, M.Future plans on meso/macro measures from cellular resolution
Modeling and Analysis of LFP, Ski, Norway, 01/08/2013 - 01/09/2013
Diesmann2013cDiesmann, M.
Integrating brain structure and dynamics with spiking neuronal network models
Workshop on Brain Inspired Computing, Cetraro, Italy, 7/08/2013 - 07/11/2013
Diesmann2013dDiesmann, M.Relating structure and activity in a full-scale local cortical network model
Computational and Systems Neuroscience (Cosyne) 2013, Snowbird, USA, 03/04/2013 - 03/05/2013
Diesmann2013eDiesmann, M.Some further insights on the correlation structure of cortex and supercomputers as instruments of neuroscience
Brain Week, Bern, Switzerland, 03/11/2013 - 03/17/2013
Diesmann2013fDiesmann, M.Theorie und Simulation grosser neuronaler Netzwerke
Brain Week, Bern, Switzerland, 03/11/2013 - 3/17/2013
Diesmann2013gDiesmann, M.Use cases for interactive supercomputing in computational neuroscience
HBP workshop Interactive Supercomputing, Frankfurt, Germany, 09/30/2013 - 10/01/2013
Diesmann2014Diesmann, M.The K computer as an instrument to study brain-scale neuronal networks at microscopic resolutionFujitsu HPC Forum, Tokyo, Japan, 08/26/2014 - 08/26/2014
Diesmann2014bDiesmann, M.HBP - HUMAN BRAIN PROJECT - SP4: Mathematical and Theoretical Foundations of Brain Research and SP6: Brain Simulation PlatformHBP - Human Brain Project - SP4, The Hague, Netherlands
Diesmann2014cDiesmann, M.My brain is finiteThe European Institute for Theoretical Neuroscience (EITN) inauguration, Paris, Frankreich
Diesmann2014dDiesmann, M.Towards brain-scale spiking network modelsMaastricht, Netherlands,
Diesmann2014eDiesmann, M.Cortical multi-area multi-layer network models: data integration and simulation technologySeattle, USA (2014)
Diesmann2014fDiesmann, M.Simulation of brain-scale neuronal networks at cellular and synaptic resolution4th HPC-Status Conference of the Gauss-Allianz, Aachen, Germany, 12/04/2014 - 12/05/2014
Diesmann2014gDiesmann, M.A full-scale spiking model of the local cortical networkAlghero, Sardinia, Italy, 05/14/2014 - 05/16/2014
Diesmann2014hDiesmann, M.A full-scale spiking model of the local cortical networkMaastricht, The Netherlands
Diesmann2014iDiesmann, M.Simulation of brain-scale neuronal networks at cellular and synaptic resolutionNeuroVisionen 10, Juelich, Germany, 09/26/2014
Diesmann2014jDiesmann, M.Spiking network simulation code for the peta scaleBrainScaleS, Heidelberg, Germany,
Grytskyy et al. 2012Grytskyy, D., Tetzlaff, T., Diesmann, M. and Helias, M. Unifying propagators and covariances of network models by Ornstein-Uhlenbeck process12th Granada* Seminar - Physics, Computation and the Mind - Advances and Challenges at Interfaces ; La Herradura ; Spain ; 09/17/2012 - 09/21/2012 abstract
Grytskyy et al. 2012bGrytskyy, D., Tetzlaff, T., Diesmann, M. and Helias, M.Unification of covariances in different neuron network models through the mapping onto Ornstein-Uhlenbeck processApplied Mathematics, Control and Informatics, Belgorod, Russia, 10/03/2012 - 10/05/2012
Grytskyyet al 2013cGrytskyy, D. ; Tetzlaff, T. ; Diesmann, M. ; Helias, M. Covariances in neural networks in linear approximation
Donders Discussion 2013, Nijmegen, Netherlands, 10/31/2013 - 11/01/2013
Helias et al. 2014aHelias, M., Kunkel, S., Morrison, A. and Diesmann, M. NEST, simulation technology for brain-scale networks at cellular and synaptic resolutionSOS18 Conference on distributed supercomputing, St. Moritz, Switzerland, 03/17/2014 - 03/20/2014
Kunkel et al. 2014cKunkel, S., Helias, M., Diesmann, M. and Morrison, A. Specifying supercomputers for brain-scale neuronal network simulationsHPC for Life Science, Brussels, Belgium, 05/26/2014 - 05/27/2014
Kunkel et al. 2014dKunkel, S., Helias, M., Diesmann, M. and Morrison, A. Supercomputer simulations of spiking neuronal networksProgress on Brain-Like Computing, Stockholm, Sweden, 02/05/2014 - 02/06/2014
Kunkelet al 2013Kunkel, S. ; Diesmann, M.Simulation technology at cellular and synaptic resolution for the largest computers
EU - US workshop on Cortical Processors, Heidelberg, Germany, 10/14/2013 - 10/15/2013
Nowke et al. 2013Nowke, C., Schmidt, M., van Albada, S. J., Eppler, J. M., Bakker, R., Diesmann, M., Hentschel, B. and Kuhlen, T. VisNEST - Interactive Analysis of Neural Activity DataBioVis Symposium at the IEEE BioVis 2013, 13-18 Oct. 2013, Atlanta, Georgia, USA
Potjans Tet al 2013Potjans, T. C. ; Diesmann, M.
A minimal cell-type specific model of the cortical microcircuit

Dynamics of Neuronal Systems, Freiburg, Germany, 03/18/2013 - 03/20/2013
Schmidt et al. 2013cSchmidt, M. ; van Albada, S. ; Bakker, R. ; Diesmann, M.
A spiking multi-area network model of macaque visual cortex
Osaka, Japan, 07/02/2014 - 07/02/2014
Schmidt et al. 2014Schmidt, M., Schücker, J., van Albada, S., Bakker, R., Helias, M. and Diesmann, M. Multi-area network model of visual cortex4th BrainScaleS plenary meeting, Manchester, Grossbritannien, 19 - 21 March 2014
Tetzlaffet al 2013Tetzlaff, T. ; Helias, M. ; Jordan, J. ; Petrovici, M. ; Breitwieser, O. ; Diesmann, M.
Decorrelation of neural-network activity by inhibitory feedback: Mechanism and applications
22nd Annual Computational Neuroscience Meeting (CNS*2013), workshop on "Functional role of correlations: theory and experiment", CNS13, Paris, France, 07/13/2013 - 07/18/2013
van Albada et al. 2014cvan Albada, S., Helias, M. and Diesmann, M.One-to-one relationship between effective connectivity and correlations in asynchronous networksBernstein Conference, Göttingen, Germany, 09/03/2014 - 09/05/2014
van Albada et al. 2014dvan Albada, S., Schmidt, M. and Diesmann, M. NEST for large-scale simulations of physiology-based spiking networks"Bernstein Network - Simulation Lab Neuroscience" HPC Workshop, Jülich, Germany, 06/04/2014 - 06/05/2014

Conference contribution: poster

Bakker et al. 2014bBakker, R., Thomas, W. and Diesmann, M. Do gold standards remain gold standards when compiling a large number of published tract-tracing studies into a connectivity database?Neuroinformatics 2014, Leiden, Netherlands, 25 Aug - 27 Aug, 2014., INCF2014, Leiden, Netherlands, 08/25/2014 - 08/27/2014
doi:10.3389/conf.fninf.2014.18.00072
fulltext
Bakkeret al 2012Bakker, R. ; Denker, M. ; Diesmann, M. ; Eppler, J. M. ; Grün, S. ; Grytskyy, D. ; Helias, M. ; Ito, J. ; Maximov, A. ; Schmidt, M. ; Tetzlaff, T. ; Torre, E. ; van Albada, S. ; Wiebelt, B. ; Zehl, L.
Planned activities in Jülich
BrainScales Conference, Jülich, Germany, 03/19/2012
Bakkeret al 2013Bakker, R. ; Paul H. E. , T. ; Diesmann, M. ; Thomas, W.
Setting up a web-based neuroscience database has never been easier: The CoCoMac engine goes open source
Neuroinformatics 2013, INCF2013, Stockholm, Sweden, 08/27/2013 - 08/29/2013
Bos et al. 2014Bos, H., Schmidt, M., Jordan, J., Schücker, J., van Albada, S., Bakker, R., Diesmann, M., Helias, M. and Tetzlaff, T.Cortical multi-layered, multi-area networks as a substrate for stochastic computingHBP Workshop on Stochastic Neural Computation, Paris, France, 11/27/2014 - 11/28/2014
Dahmen et al. 2013Dahmen, D., Hagen, E., Stavrinou, M. L., Linden, H., Tetzlaff, T., van Albada, S., Diesmann, M., Grün, S. and Einevoll, G. T. From spiking point-neuron networks to LFPs: a hybrid approachBernstein Conference, 25-27 September 2013, Tübingen, Germany
Dahmen et al. 2014Dahmen, D., Hagen, E., Stavrinou, M.L., Lindén, H., Tetzlaff, T., van Albada, S., Diesmann, M., Grün, S. and Einevoll, G.T. Computing local-field potentials based on a point-neuron network model of cat V1SFN Neuroscience 2014, Washington, D.C., United States of America, 11/15/2014 - 11/19/2014
Denker et al. 2011aDenker, M., Davison, A., Grün, S. and Diesmann, M. How collaborative projects that involve complicated electrophysiological data sets profit from workflow designPoster at the 4th INCF Congress of Neuroinformatics, Boston, USA
doi:10.3389/conf.fninf.2011.08.00080
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Denker et al. 2011bDenker, M., Davison, A., Grün, S. and Diesmann, M. Towards guiding principles in workflow design to facilitate collaborative projects involving massively parallel electrophysiological dataBMC Neuroscience 2011, 12(Suppl 1):P131
doi:10.1186/1471-2202-12-S1-P131
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Denker et al. 2014aZehl, L., Kilavik, B., Diesmann, M., Brochier, T., Riehle, A. and Grün, S. Characterizing spatially organized LFP beta oscillations in the macaque motor cortexAREADNE 2014, Santorini, Greece, 06/25/2014 - 06/29/2014
Denkeret al 2013Denker, M. ; Riehle, A. ; Diesmann, M. ; Grün, S.Relating excess spike synchrony to LFP-locked firing rate modulations.
Annual CNS Meeting 2013, Paris, France, 07/13/2013 - 07/18/2013
Eppler et al. 2011Eppler, J.M., Kunkel, S., Plesser, H.E., Gewaltig, M.-O., Morrison, A. and Diesmann, M.NEST: An efficient simulator for spiking neural network modelsPoster at the Ninth Göttingen Meeting of the German Neuroscience Society 2011: T27-9B abstract
Eppler et al. 2011bEppler, J.M., Enger, H., Heiberg, T., Kriener, B., Plesser, H.E., Diesmann, M. and Djurfeldt, M.Evaluating the Connection-Set Algebra for the neural simulator NESTPoster at the 4th INCF Congress of Neuroinformatics, Boston, USA
doi:10.3389/conf.fninf.2011.08.00085
abstract
Eppler et al. 2012Eppler, J. M., Djurfeldt, M., Muller, E., Diesmann, M. and Davison, A.Combining simulator independent network descriptions with run-time interoperability based on PyNN and MUSICIn Conference Abstract: 5th INCF Congress of Neuroinformatics, Front. Neuroinform. (2012)
EpplerM et al 2013Eppler, J. M. ; Kunkel, S. ; Helias, M. ; Zaytsev, Y. ; Plesser, H. E. ; Gewaltig, M.-O. ; Morrison, A. ; Diesmann, M.
20 years of NEST: a mature brain simulator
INM Retreat 2013, Jülich, Germany, 07/02/2013 - 07/03/2013
EpplerM et al. 2012Eppler, J. M. ; Wiebelt, B. ; Zaytsev, Y. ; Diesmann, M.
The NEST software development infrastructure
INM Retreat 2012, Jülich, Germany, 07/03/2012 - 07/04/2012
Grytskyy et al. 2012cGrytskyy, D., Helias, M., Tetzlaff, T., Diesmann, M.
Taming the model zoo: a unified view on correlations in recurrent networks
Twenty First Annual Computational Neuroscience Meeting, Decatur, GA, USA; BMC Neuroscience 2012, 13(Suppl 1):P147.
doi:10.1186/1471-2202-13-S1-P147
abstract
Grytskyy et al. 2012dGrytskyy, D., Helias, M., Tetzlaff, T., Diesmann, M.Ornstein-Uhlenbeck-process joins and extends different theories of correlationsBernstein Conference 2012, Munich, Germany; Front Comp Neurosci 6 (2012)

doi:10.3389/conf.fncom.2012.55.00101
abstract
Grytskyy et al. 2012eGrytskyy, D., Tetzlaff, T., Diesmann, M. and Helias, M. Invariance of covariances arises out of noise AIP Conf. Proc. (2013) 1510: 258
doi:10.1063/1.4776531
abstract
Grytskyy et al. 2014bGrytskyy, D., Diesmann, M. and Helias, M. Activity propagation in plastic feed-forward networks of nonlinear neuronsMachine Learning Summer School 2014, MLSS, Reykjavik, Iceland, 04/24/2014 - 05/04/2014
Grytskyyet al 2013bGrytskyy, D. ; Diesmann, M. ; Helias, M.
Connectivity reconstruction from complete or partially known covariances in the asynchronous irregular regime
Bernstein Conference 2013, BCCN 2013, Tuebingen, Germany, 09/25/2013 - 09/27/2013
Grytskyyet al 2013dGrytskyy, D. ; Diesmann, M. ; Helias, M.
Reconstruction of network connectivity in the irregular firing regime
10th Goettingen Meeting of the German Neuroscience Society, NWG 2013, Goettingen, Germany, 03/13/2013 - 03/16/2013
Grytskyyet al. 2014Grytskyy, D. ; Diesmann, M. ; Helias, M. Activity propagation in plastic feed-forward networks of nonlinear neuronsBernstein Conference 2014, BCCN 2014, Goettingen, Germany, 09/03/2014 - 09/05/2014
Hageet al 2013Hagen, E. ; Stavrinou, M. ; Lindén, H. ; Dahmen, D. ; Tetzlaff, T. ; van Albada, S. ; Grün, S. ; Diesmann, M. ; Einevoll, G. T.
Hybrid scheme for modeling LFPs from spiking cortical network models
Proceedings of NeuroInformatics 2013
NeuroInformatics 2013, Stockholm, Sweden, 08/27/2013 - 08/29/2013
Hagen et al. 2015Hagen, E., Dahmen, D., Stavrinou, M.L., Linden, H., Tetzlaff, T., van Albada, S., Diesmann, M., Grün, S. and Einevoll, G.T. Hybrid scheme for modeling local field potentials from point-neuron networks11th Göttingen Meeting of the German Neuroscience Society, Göttingen, Germany, 03/18/2015 - 03/21/2015
Helias et al. 2011bHelias, M., Tetzlaff, T. and Diesmann, M.Towards a unified theory of correlations in recurrent neural networksBMC Neuroscience 2011, 12(Suppl 1):P73
doi:10.1186/1471-2202-12-S1-P73
fulltext
Helias et al. 2011cHelias, M., Grytskyy, D., Tetzlaff, T. and Diesmann, M.Model-invariant features of correlations in recurrent networksFront. Comput. Neurosci. (2011) Conference Abstract: BC11 : Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting 2011
doi:10.3389/conf.fncom.2011.53.00219
abstract
Helias et al. 2012aHelias, M., Kunkel, S., Eppler, J., Masumoto, G., Igarashi, J., Ishii, S., Fukai, T., Morrison, A. and Diesmann, M.Spiking neuronal network simulation technology for contemporary supercomputersINCF Meeting, 10-12 Sept 2012, Munich, Germany
Heliaset al 2013Helias, M. ; Tetzlaff, T. ; Diesmann, M.
Intrinsic and extrinsic sources of correlated activity in recurrent networks
10th Goettingen meeting of the German neuroscience Society, NWG 2013, Goettingen, Germany, 03/13/2013 - 03/16/2013
Heliaset al 2013bHelias, M. ; Tetzlaff, T. ; Diesmann, M.Recurrence and external sources differentially shape network correlations.
Computational Neuroscience Conference 2013, CNS*2013, Paris, France, 07/13/2013 - 07/18/2013
Jordanet al 2013Jordan, J. ; Tetzlaff, T. ; Breitwieser, O. ; Petrovici, M. ; Schemmel, J. ; Diesmann, M. ; Meier, K.
Generation of uncorrelated noise by recurrent neural networks
3rd BrainScaleS Plenary meeting, Marseille, France, 03/21/2013 - 03/22/2013
Jordanet al 2013bJordan, J. ; Tetzlaff, T. ; Breitwieser, O. ; Petrovici, M. ; Schemmel, J. ; Diesmann, M. ; Meier, K.
Generation of uncorrelated noise by recurrent neural networks
10th Goettingen Meeting of the German Neuroscience Society, Goettingen, Germany, 03/13/2013 - 03/16/2013
Jordanet al 2015Jordan, J. ; Pfeil, T. ; Tetzlaff, T. ; Grübl, A. ; Schemmel, J. ; Diesmann, M. ; Meier, K. The effect of heterogeneity on decorrelation mechanisms in spiking neural networks: a neuromorphic-hardware study11th Göttingen Meeting of the German Neuroscience Society, Göttingen, Germany, 03/18/2015 - 03/21/2015
Jordanet al. 2014bJordan, J., Petrovici, M., Pfeil, T., Breitwieser, O., Bytschok, I., Bill, J., Gruebl, A., Schemmel, J., Meier, K., Diesmann, M. and Tetzlaff, T. Neural Networks as Sources of uncorrelated Noise for functional neural SystemsOCCAM 2014, Osnabrueck, Germany, 05/07/2014 - 05/09/2014
Krieneret al 2013Kriener, B. ; Helias, M. ; Rotter, S. ; Diesmann, M. ; Einevoll, G. T.
How pattern formation in ring networks of excitatory and inhibitory spiking neurons depends on the input current regime
Computational Neuroscience Conference, CNS*2013, Paris, France, 07/13/2013 - 07/18/2013
Kunkelet al 2013bKunkel, S. ; Schmidt, M. ; Eppler, J. M. ; Igarashi, J. ; Masumoto, G. ; Fukai, T. ; Ishii, S. ; Plesser, H. E. ; Morrison, A. ; Diesmann, M. ; Helias, M.
Supercomputers ready for use as discovery machines for neuroscience
10th Meeting of the German Neuroscience Society, NWG 2013, Goettingen, Germany, 03/13/2013 - 03/18/2013
Lindén et al. 2011bLindén, H., Tetzlaff, T., Potjans, T.C., Pettersen, K.H., Grün, S., Diesmann, M. and Einevoll, G.T.How local is the local field potential?BMC Neuroscience 2011, 12(Suppl 1):O8
doi:10.1186/1471-2202-12-S1-O
fulltext
Maksimovet al 2012Maksimov, A. ; van Albada, S. J. ; Diesmann, M.
Understanding global whisker motion detection through large-scale simulation of the rodent whisker system
Okinawa Computational Neuroscience Course 2012
Okinawa, Japan, 2012-06-11"
Maximovet al 2013Maximov, A. ; van Albada, S. ; Diesmann, M.
Toward a biologically realistic spiking model of a rodent barrel column
Bernstein Conference 2013, Tuebingen, Germany, 09/25/2013 - 09/27/2013
Morrison et al. 2011Morrison, A., Denker, M., Wiebelt, B., Fliegner, D. and Diesmann, M.New possibilities for advanced analysis methods in neuroscience through modern approaches to trivial parallel data processingPoster at the Ninth Göttingen Meeting of the German Neuroscience Society 2011: T27-11B abstract
Nowke et al. 2012bNowke, C., Hentschel, B., Kuhlen, T., Eppler, J.M., van Albada, S., Bakker, R., Diesmann, M., Schmidt, M.VisNEST - Interactive analysis of neural activity dataIEEE VisWeek 2012 abstract
Nowke et al. 2013bNowke, C., Schmidt, M., van Albada, S., Eppler, J., Bakker, R., Diesmann, M., Hentschel, B. and Kuhlen, T. Interactive visualization of brain-scale spiking activityAnnual CNS Meeting 2013, BMC Neuroscience 2013, 14(Suppl 1):P110
Nowkeet al 2013Nowke, C. ; Hentschel, B. ; Kuhlen, T. ; Schmidt, M. ; van Albada, S. ; Eppler, J. M. ; Bakker, R. ; Diesmann, M.
Interactive visualization of brain-scale spiking activity
Twenty Second Annual Computational Neuroscience Meeting, CNS 2013, Paris, France, 07/13/2013 - 07/18/2013
Pfeilet al 2014Pfeil, T., Jordan, J., Tetzlaff, T., Grübl, A., Schemmel, J., Diesmann, M. and Meier, K. Decorrelation of neural-network activity on heterogeneous neuromorphic hardware10th Bernstein Conference 2014, Goettingen, Goettingen, Germany, 09/02/2014 - 09/05/2014
doi:10.12751/nncn.bc2014.0221
abstract
Potjans and Diesmann 2011bPotjans, T.C. and Diesmann, M.Robustness vs. flexibility: how do external inputs shape the activity in a data-based layered cortical network model?BMC Neuroscience (2011) 12(Suppl 1):74
doi:10.1186/1471-2202-12-S1-P74
fulltext
Potjans et al. 2011Potjans, T.C., Kunkel, S., Morrison, A., Plesser, H.E. and Diesmann, M.Beyond local cortical network modeling: linking microscopic and macroscopic connectivity in brainscale simulationsPoster at the Ninth Göttingen Meeting of the German Neuroscience Society 2011: T26-6A abstract
Schmidt et al. 2013Schmidt, M., van Albada, S., Bakker, R. and Diesmann, M. Toward a spiking multi-area network model of macaque visual cortexProceedings of the 10th Meeting of the German Neuroscience Society, Neuroforum 2013 : T24-10D (2013)
Schmidt et al. 2013bSchmidt, M., van Albada, S., Bakker, R. and Diesmann, M. Integrating multi-scale data for a network model of macaque visual cortexAnnual CNS Meeting 2013, BMC Neuroscience 2013, 14(Suppl 1):P111 (2013)
Schmidt et al. 2014cSchmidt, M., van Albada, S., Bakker, R. and Diesmann, M. A spiking multi-area network model of macaque visual cortexAnnual meeting of the SfN, SfN2014, Washington, DC, USA, 11/15/2014 - 11/19/2014
Schmidt et al. 2014dSchmidt, M., van Albada, S., Bakker, R. and Diesmann, M. Connectomics of a multi-area network model of macaque visual cortexMicro-, meso- and macro-connectomics of the brain, Paris, Frankreich, 05/05/2014 - 05/05/2014
Schmidtet al 2013bSchmidt, M. ; van Albada, S. ; Bakker, R. ; Diesmann, M.
Toward a spiking Multi-area network model of macaque visual cortex
10th Meeting of the German Neuroscience Society, NWG 2013, Goettingen, Germany, 03/13/2013 - 03/16/2013
Schuecker et al. 2014aSchücker, J., Diesmann, M. and Helias, M. The transfer function of the LIF model: from white to filtered noiseComputation Neuroscience Conference 2014, CNS14, Quebec, Canada, 07/23/2014 - 07/31/2014
Schultze-Kraft et al. 2011Schultze-Kraft, M., Diesmann, M., Grün, S. and Helias, M.Correlation transmission of spiking neurons is boosted by synchronous inputBMC Neuroscience 2011, 12(Suppl 1):P144
doi:10.1186/1471-2202-12-S1-P144
fulltext
Stavrinou et al. 2015Stavrinou, M.L., Hagen, E., Dahmen, D., Linden, H., Tetzlaff, T., van Albada, S., Diesmann, M., Grün, S. and Einevoll, G.T. Computing local field potentials based on spiking cortical networksNeuro Informatics 2014, Leiden, Netherlands, 08/25/2014 - 08/27/2014
Tetzlaff et al. 2014Tetzlaff, T., Jordan, J., Petrovici, M., Breitwieser, O., Bytschok, I., Bill, J., Schemmel, J., Meier, K. and Diesmann, M. Neural networks as sources of uncorrelated noise for functional neural architectures10th Bernstein Conference 2014, Goettingen, Goettingen, Germany, 09/02/2014 - 09/05/2014
doi:10.12751/nncn.bc2014.0133
abstract
Tetzlaff et al. 2014bTetzlaff, T., Dahmen, D., Hagen, E., Stavrinou, M.L., Lindén, H., van Albada, S., Diesmann, M., Grün, S. and Einevoll, G.T. Computing local-field potentials based on a point-neuron network model of cat V1NeuroVisionen 10 meeting, Jülich, Germany, 09/26/2014 - 09/26/2014
Tetzlaff et al. 2015Tetzlaff, T., Hagen, E., Dahmen, D., Stavrinou, M.L., Linden, H., van Albada, S., Grün, S., Diesmann, M. and Einevoll, G.T.
Hybrid scheme for modeling local field potentials from point-neuron networks2nd International Symposium of the Clinical Research Group 219, Cologne, Germany, 02/26/2015 - 02/28/2015
van Albada et al. 2013van Albada, S.J., Schrader, S., Helias, M. and Diesmann, M.Influence of different types of downscaling on a cortical microcircuit modelBMC Neuroscience 2013, 14(Suppl 1):P112
doi:10.1186/1471-2202-14-S1-P112
abstract
van Albada et al. 2014kvan Albada, S, Helias, M. and Diesmann, M. One-to-one relationship between effective connectivity and correlations in asynchronous networksBernstein Conference, Göttingen, Germany, 09/03/2014 - 09/05/2014
Van Albadaet al 2013van Albada, S. ; Maximov, A. ; Schmidt, M. ; Bakker, R. ; Schrader, S. ; Lester, D. ; Diesmann, M.
Cortical multi-layer models for down-scaled implementation on neuromorphic hardware and full-scale implementation on supercomputers
3rd BrainScaleS plenary meeting, Marseille, France, 03/21/2013 - 03/22/2013
Wagatsuma et al. 2011bWagatsuma, N., Potjans, T.C., Diesmann, M. and Fukai, T.Layer dependent neural modulation of a realistic layered-microcircuit model in visual cortex based on bottom-up and top-down signalsBMC Neuroscience 2011, 12(Suppl 1):P114
doi:10.1186/1471-2202-12-S1-P114
fulltext

Web publication

Nowke et al. 2013cNowke, C., Schmidt, M., van Albada, S., Eppler, J., Bakker, R., Diesmann, M., Hentschel, B. and Kuhlen, T. VisNEST - Interactive analysis of neural activity dataVideo posted on vimeo: http://vimeo.com/82512745 fulltext
Potjans and Diesmann 2011Potjans, T.C. and Diesmann, M.The cell-type specific connectivity of the local cortical network explains prominent features of neuronal activityarXiv:1106.5678v1 [q-bio.NC] 28 Jun 2011 abstract
Schuecker et al. 2014Schuecker, J., Diesmann, M. and Helias, M.Spectral properties of excitable systems subject to colored noisearXiv:1411.0432 abstract, fulltext
van Albada et al. 2014bVan Albada, S., Diesmann, M., Eppler, J.M., Hentschel, B., Kuhlen, T.. Nowke, C., Reske, M. and Schmidt, M.Modellierung und 3D-Visualisierung neuronaler Netzwerke in der Grössenordnung des GehirnsRWTH Themen (2014) 2: 52-57 fulltext
van Albada et al. 2014evan Albada, S.J., Helias, M. and Diesmann, M.Scalability of asynchronous networks is limited by one-to-one mapping between effective connectivity and correlationsarXiv:1411.4770 abstract, fulltext

Other

Chorley et al. 2014Chorley, P., Diesmann, M., Helias, M. and Grün, S. Correlated rate vector dynamics in motor cortexINM Retreat, Jülich, Germany, 07/01/2014 - 07/02/2014
Dahmen et al. 2014bDahmen, D., Hagen, E., Stavrinou, M.L., Lindén, H., Tetzlaff, T., van Albada, S., Diesmann, M., Grün, S., Einevoll, G.T.
From spiking point-neuron networks to LFPs: a hybrid approachBrainScaleS 4th plenary meeting, Manchester, United Kingdom, 03/19/2014 - 03/21/2014
Denker et al. 2014dDenker, M., Zehl, L., Kilavik, B., Diesmann, M., Brochier, T., Riehle, A. and Grün, S. Characterizing Spatially Organized LFP Beta Oscillations in Motor CortexINM Retreat 2014, Jülich, Germany, 07/01/2014 - 07/02/2014
Gruen and Diesmann 2012Gruen, S. and Diesmann, M.Hirnforschung braucht ein Netzwerk: Computational and Systems Neuroscience am Forschungszentrum Juelichsystembiologie.de (2012) 4: 36-39 fulltext
Jordan et al. 2014dJordan, J., Petrovici, M., Pfeil, T., Breitwieser, O., Bytschok, I., Bill, J., Gruebl, A., Schemmel, J., Meier, K., Diesmann, M. and Tetzlaff, T. Neural networks as sources of uncorrelated noise for functional neural systems4th BrainScaleS Plenary meeting, Manchester, England, 03/20/2014 - 03/21/2014
Jordan et al. 2014eJordan, J., Petrovici, M., Pfeil, T., Bytschok, I., Bill, J., Gruebel, A., Meier, K., Diesmann, M. and Tetzlaff, T. Neural networks as sources of uncorrelated noise for functional neural systems4th BrainScaleS Plenary meeting, Manchester, England, 03/20/2014 - 03/21/2014
Jordanet al. 2014Petrovici, M., Pfeil, T., Breitwieser, O., Bytschok, I., Bill, J., Gruebl, A., Schemmel, J., Meier, K., Diesmann, M. and Tetzlaff, T. Neural Networks as Sources of uncorrelated Noise for functional neural SystemsINM Retreat 2014, Juelich, Germany, 07/01/2014 - 07/02/2014
Kunkel et al. 2012Kunkel, S., Helias, M., Potjans, T. C., Eppler, J. M., Plesser, H.E., Diesmann, M. and Morrison, A.Memory Consumption of Neuronal Network Simulators at the Brain Scalein Binder K, Münster G, Kremer M (Eds) NIC Symposium 2012 Proceedings NIC Series Vol. 45, page 81, Jülich, Germany, ISBN 978-3-89336-758-0 fulltext
Kunkelet al. 2014bPlesser, H.E., Helias, M., Diesmann, M. and Morrison, A. The NEST 4g kernel: highly scalable simulation code from laptops to supercomputersBrainScaleS CodeJam Workshop 6, Juelich, Germany, 01/27/2014 - 01/29/2014 BibTeX
Maximov et al. 2014Maximov, A., van Albada, S. and Diesmann, M. Calibration of a simulated cortical microcircuit using slice data.INM Retreat 2014, Juelich, germany, 07/01/2014 - 07/02/2014
Schücker et al. 2014Schücker, J., Schmidt, M., van Albada, S., Diesmann, M. and Helias, M. Stability analysis of a multi-area network model of macaque visual cortexINM Retreat 2013, Juelich, Germany, 07/01/2014 - 07/02/2014
Schmidt et al. 2014bSchmidt, M., Schücker, J., van Albada, S., Bakker, R., Helias, M. and Diesmann, M. Multi-area network model of visual cortex4th BrainScales plenary meeting, Manchester, Grossbritannien, 03/19/2014 - 03/21/2014
Tetzlaff et al. 2014cTetzlaff, T., Dahmen, D., Hagen, E., Stavrinou, M. L., Lindén, H., van Albada, S., Diesmann, M., Grün, S. and Einevoll, G.T.M.Poster: Computing local-field potentials based on a point-neuron network model of cat V1INM retreat, Jülich, Germany, 07/01/2014 - 07/02/2014
van Albada and Diesmann 2014van Albada, S. and Diesmann, M. NEST HPC status - technology and theoryBrainScaleS Demo 1, 2 and 3 workshop, Gif-sur-Yvette, France, 11/25/2014 - 11/26/2014
van Albada et al. 2014lvan Albada, S., Schmidt, M., Bakker, R. and Diesmann, M. Spiking multi-area model of macaque visual cortexINM Retreat 2014, Jülich, Germany, 07/01/2014 - 07/02/2014


 
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26 August 2016