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. 2012	Bakker, R., Wachtler, T. and Diesmann, M.	CoCoMac 2.0 and the future of tract-tracing databases	Front Neuroinform. (2012) 6: 30. doi:10.3389/fninf.2012.00030	fulltext
Brüderle et al. 2011	Brüderle, 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 systems	Biological Cybernetics (2011) 104(4-5): 263-296 doi:10.1007/s00422-011-0435-9	abstract, fulltext
Deger et al. 2012	Deger, M., Helias, M., Rotter, S. and Diesmann, M.	Spike-Timing Dependence of Structural Plasticity Explains Cooperative Synapse Formation in the Neocortex	PLoS Comput Biol (2012) 8(9): e1002689 doi:10.1371/journal.pcbi.1002689
Denker et al. 2011c	Denker, M., Roux, S., Lindén, H., Diesmann, M., Riehle, A. and Grün, S.	The local field potential reflects surplus spike synchrony	Cerebral Cortex (2011) 21:2681-2695 doi:10.1093/cercor/bhr040	abstract, fulltext
Gerstein et al. 2012	Gerstein, G.L., Williams, E.R., Diesmann, M., Grün, S. and Trengove, C.	Detecting synfire chains in parallel spike data	Journal of Neuroscience Methods (2012) 206(1): 54-64 doi:10.1016/j.jneumeth.2012.02.003	fulltext
Grytskyy et al. 2013	Grytskyy, D., Tetzlaff, T., Diesmann, M., and Helias, M.	A unified view on weakly correlated recurrent networks	Front Comput Neurosci. (2013) 7:131 doi:10.3389/fncom.2013.00131	fulltext
Grytskyy et al. 2013b	Grytskyy, D., Tetzlaff, T., Diesmann, M. and Helias, M.	A unified view on weakly correlated recurrent networks	Frontiers in computational neuroscience (2013) 7(131): 1-19 doi:10.3389/fncom.2013.00131	fulltext
Helias et al. 2011	Helias, M., Deger, M., Rotter, S. and Diesmann, M.	Finite post synaptic potentials cause a fast neuronal response	Front. Neurosci. (2011) 5:19 doi:10.3389/fnins.2011.00019	abstract, fulltext
Helias et al. 2012	Helias, 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 neuroscience	Front. Neuroinform. (2012) 6:26 doi:10.3389/fninf.2012.00026	fulltext
Helias et al. 2013	Helias, 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	fulltext
Helias et al. 2014	Helias, M., Tetzlaff, T. and Diesmann, M.	The Correlation Structure of Local Neuronal Networks Intrinsically Results from Recurrent Dynamics	PLoS Computational Biology (2014) 10(1): e1003428 doi:10.1371/journal.pcbi.1003428	fulltext
Kriener et al. 2014b	Helias, 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 regime	Frontiers in computational neuroscience (2014) 7: 1 doi:10.3389/fncom.2013.00187	fulltext
Kunkel et al. 2011	Kunkel, S., Diesmann, M. and Morrison, A.	Limits to the Development of Feed-Forward Structures in Large Recurrent Neuronal Networks	Front. Comput. Neurosci. (2011) 4:160 doi:10.3389/fncom.2010.00160	abstract, fulltext
Kunkel et al. 2011b	Kunkel, S., Potjans, T.C., Eppler, J.M., Plesser, H.E., Morrison, A. and Diesmann, M.	Meeting the memory challenges of brain-scale network simulation	Front. Neuroinform. (2011) 5:35 doi:10.3389/fninf.2011.00035	abstract
Kunkel et al. 2014	Kunkel, 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 computers	Front. Neuroinform. (2014) 8:78 doi:10.3389/fninf.2014.00078	abstract, fulltext
Lindén et al. 2011	Lindén, H., Tetzlaff, T., Potjans, T.C., Pettersen, K.H., Grün, S., Diesmann, M. and Einevoll, G.T.	Modeling the spatial reach of the LFP	Neuron (2011) 72(5): 859-872 doi:10.1016/j.neuron.2011.11.006	fulltext
Pfeil et al. 2012b	Pfeil, 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 hardware	Front. Neurosci. (2012) 6:90 doi:10.3389/fnins.2012.00090	abstract, fulltext
Potjans and Diesmann 2012	Potjans, T. and Diesmann, M.	The Cell-Type Specific Cortical Microcircuit: Relating Structure and Activity in a Full-Scale Spiking Network Model	First published online: December 2, 2012. Cereb. Cortex (2014) 24 (3): 785-806 doi:10.1093/cercor/bhs358	abstract, fulltext
Potjans et al. 2011b	Potjans, W., Diesmann, M. and Morrison, A.	An Imperfect Dopaminergic Error Signal Can Drive Temporal-Difference Learning	PLoS Comput Biol. (2011) 7(5): e1001133 doi:10.1371/journal.pcbi.1001133	abstract, fulltext
Schultze-Kraft et al. 2013	Schultze-Kraft, M., Diesmann, M., Grün, S. and Helias, M.	Noise Suppression and Surplus Synchrony by Coincidence Detection	PLoS Comput Biol. (2013) 9(4):e1002904 doi:10.1371/journal.pcbi.1002904
Tetzlaff et al. 2012	Tetzlaff, T., Helias, M., Einevoll, G. T. and Diesmann, M.	Decorrelation of Neural-Network Activity by Inhibitory Feedback	PLoS Comput Biol (2012) 8(8): e1002596 doi:10.1371/journal.pcbi.1002596	fulltext
van Albada et al. 2015	van Albada, S.J., Helias, M. and Diesmann, M.	Scalability of Asynchronous Networks Is Limited by One-to-One Mapping between Effective Connectivity and Correlations	PLoS Comput Biol (2015) 11(9): e1004490 doi:10.1371/journal.pcbi.1004490
Wagatsuma et al. 2011	Wagatsuma, N., Potjans, T.C., Diesmann, M. and Fukai, T.	Layer-dependent attentional processing by top-down signals in a visual cortical microcircuit model	Front. Comput. Neurosci. (2011) 5:31 doi:10.3389/fncom.2011.00031	abstract, fulltext

Book chapter

Lansner and Diesmann 2012	Lansner, A. and Diesmann, M.	Virtues, Pitfalls, and Methodology of Neuronal Network Modeling and Simulations on Supercomputers	Computational 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. 2014	van 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 2014	Bakker, 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 a	Diesmann, M.	Active decorrelation in local cortical networks	Biology and Physics of Information Processing ; Nordita, Stockholm ; Sweden ; 04/16/2012 - 05/11/2012
Diesmann 2012b	Diesmann, M.	Brain-scale neuronal network simulations on K	4th Biosupercomputing Symposium ; Tokyo ; Japan ; 12/03/2012 - 12/05/2012
Diesmann 2012c	Diesmann, M.	Decorrelation of neural-network activity by inhibitory feedback	Variance & Invariants in Brain and Behavior ; TECHNION, Haifa ; Israel ; 05/21/2012 - 05/23/2012
Diesmann2013	Diesmann, 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
Diesmann2013b	Diesmann, M.	Future plans on meso/macro measures from cellular resolution	Modeling and Analysis of LFP, Ski, Norway, 01/08/2013 - 01/09/2013
Diesmann2013c	Diesmann, M.	Integrating brain structure and dynamics with spiking neuronal network models	Workshop on Brain Inspired Computing, Cetraro, Italy, 7/08/2013 - 07/11/2013
Diesmann2013d	Diesmann, 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
Diesmann2013e	Diesmann, 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
Diesmann2013f	Diesmann, M.	Theorie und Simulation grosser neuronaler Netzwerke	Brain Week, Bern, Switzerland, 03/11/2013 - 3/17/2013
Diesmann2013g	Diesmann, M.	Use cases for interactive supercomputing in computational neuroscience	HBP workshop Interactive Supercomputing, Frankfurt, Germany, 09/30/2013 - 10/01/2013
Diesmann2014	Diesmann, M.	The K computer as an instrument to study brain-scale neuronal networks at microscopic resolution	Fujitsu HPC Forum, Tokyo, Japan, 08/26/2014 - 08/26/2014
Diesmann2014b	Diesmann, M.	HBP - HUMAN BRAIN PROJECT - SP4: Mathematical and Theoretical Foundations of Brain Research and SP6: Brain Simulation Platform	HBP - Human Brain Project - SP4, The Hague, Netherlands
Diesmann2014c	Diesmann, M.	My brain is finite	The European Institute for Theoretical Neuroscience (EITN) inauguration, Paris, Frankreich
Diesmann2014d	Diesmann, M.	Towards brain-scale spiking network models	Maastricht, Netherlands,
Diesmann2014e	Diesmann, M.	Cortical multi-area multi-layer network models: data integration and simulation technology	Seattle, USA (2014)
Diesmann2014f	Diesmann, M.	Simulation of brain-scale neuronal networks at cellular and synaptic resolution	4th HPC-Status Conference of the Gauss-Allianz, Aachen, Germany, 12/04/2014 - 12/05/2014
Diesmann2014g	Diesmann, M.	A full-scale spiking model of the local cortical network	Alghero, Sardinia, Italy, 05/14/2014 - 05/16/2014
Diesmann2014h	Diesmann, M.	A full-scale spiking model of the local cortical network	Maastricht, The Netherlands
Diesmann2014i	Diesmann, M.	Simulation of brain-scale neuronal networks at cellular and synaptic resolution	NeuroVisionen 10, Juelich, Germany, 09/26/2014
Diesmann2014j	Diesmann, M.	Spiking network simulation code for the peta scale	BrainScaleS, Heidelberg, Germany,
Grytskyy et al. 2012	Grytskyy, D., Tetzlaff, T., Diesmann, M. and Helias, M.	Unifying propagators and covariances of network models by Ornstein-Uhlenbeck process	12th 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. 2012b	Grytskyy, D., Tetzlaff, T., Diesmann, M. and Helias, M.	Unification of covariances in different neuron network models through the mapping onto Ornstein-Uhlenbeck process	Applied Mathematics, Control and Informatics, Belgorod, Russia, 10/03/2012 - 10/05/2012
Grytskyyet al 2013c	Grytskyy, 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. 2014a	Helias, M., Kunkel, S., Morrison, A. and Diesmann, M.	NEST, simulation technology for brain-scale networks at cellular and synaptic resolution	SOS18 Conference on distributed supercomputing, St. Moritz, Switzerland, 03/17/2014 - 03/20/2014
Kunkel et al. 2014c	Kunkel, S., Helias, M., Diesmann, M. and Morrison, A.	Specifying supercomputers for brain-scale neuronal network simulations	HPC for Life Science, Brussels, Belgium, 05/26/2014 - 05/27/2014
Kunkel et al. 2014d	Kunkel, S., Helias, M., Diesmann, M. and Morrison, A.	Supercomputer simulations of spiking neuronal networks	Progress on Brain-Like Computing, Stockholm, Sweden, 02/05/2014 - 02/06/2014
Kunkelet al 2013	Kunkel, 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. 2013	Nowke, 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 Data	BioVis Symposium at the IEEE BioVis 2013, 13-18 Oct. 2013, Atlanta, Georgia, USA
Potjans Tet al 2013	Potjans, 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. 2013c	Schmidt, 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. 2014	Schmidt, M., Schücker, J., van Albada, S., Bakker, R., Helias, M. and Diesmann, M.	Multi-area network model of visual cortex	4th BrainScaleS plenary meeting, Manchester, Grossbritannien, 19 - 21 March 2014
Tetzlaffet al 2013	Tetzlaff, 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. 2014c	van Albada, S., Helias, M. and Diesmann, M.	One-to-one relationship between effective connectivity and correlations in asynchronous networks	Bernstein Conference, Göttingen, Germany, 09/03/2014 - 09/05/2014
van Albada et al. 2014d	van 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. 2014b	Bakker, 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 2012	Bakker, 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 2013	Bakker, 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. 2014	Bos, 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 computing	HBP Workshop on Stochastic Neural Computation, Paris, France, 11/27/2014 - 11/28/2014
Dahmen et al. 2013	Dahmen, 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 approach	Bernstein Conference, 25-27 September 2013, Tübingen, Germany
Dahmen et al. 2014	Dahmen, 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 V1	SFN Neuroscience 2014, Washington, D.C., United States of America, 11/15/2014 - 11/19/2014
Denker et al. 2011a	Denker, M., Davison, A., Grün, S. and Diesmann, M.	How collaborative projects that involve complicated electrophysiological data sets profit from workflow design	Poster at the 4th INCF Congress of Neuroinformatics, Boston, USA doi:10.3389/conf.fninf.2011.08.00080	fulltext
Denker et al. 2011b	Denker, M., Davison, A., Grün, S. and Diesmann, M.	Towards guiding principles in workflow design to facilitate collaborative projects involving massively parallel electrophysiological data	BMC Neuroscience 2011, 12(Suppl 1):P131 doi:10.1186/1471-2202-12-S1-P131	fulltext
Denker et al. 2014a	Zehl, L., Kilavik, B., Diesmann, M., Brochier, T., Riehle, A. and Grün, S.	Characterizing spatially organized LFP beta oscillations in the macaque motor cortex	AREADNE 2014, Santorini, Greece, 06/25/2014 - 06/29/2014
Denkeret al 2013	Denker, 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. 2011	Eppler, J.M., Kunkel, S., Plesser, H.E., Gewaltig, M.-O., Morrison, A. and Diesmann, M.	NEST: An efficient simulator for spiking neural network models	Poster at the Ninth Göttingen Meeting of the German Neuroscience Society 2011: T27-9B	abstract
Eppler et al. 2011b	Eppler, 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 NEST	Poster at the 4th INCF Congress of Neuroinformatics, Boston, USA doi:10.3389/conf.fninf.2011.08.00085	abstract
Eppler et al. 2012	Eppler, J. M., Djurfeldt, M., Muller, E., Diesmann, M. and Davison, A.	Combining simulator independent network descriptions with run-time interoperability based on PyNN and MUSIC	In Conference Abstract: 5th INCF Congress of Neuroinformatics, Front. Neuroinform. (2012)
EpplerM et al 2013	Eppler, 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. 2012	Eppler, 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. 2012c	Grytskyy, 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. 2012d	Grytskyy, D., Helias, M., Tetzlaff, T., Diesmann, M.	Ornstein-Uhlenbeck-process joins and extends different theories of correlations	Bernstein Conference 2012, Munich, Germany; Front Comp Neurosci 6 (2012) doi:10.3389/conf.fncom.2012.55.00101	abstract
Grytskyy et al. 2012e	Grytskyy, 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. 2014b	Grytskyy, D., Diesmann, M. and Helias, M.	Activity propagation in plastic feed-forward networks of nonlinear neurons	Machine Learning Summer School 2014, MLSS, Reykjavik, Iceland, 04/24/2014 - 05/04/2014
Grytskyyet al 2013b	Grytskyy, 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 2013d	Grytskyy, 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. 2014	Grytskyy, D. ; Diesmann, M. ; Helias, M.	Activity propagation in plastic feed-forward networks of nonlinear neurons	Bernstein Conference 2014, BCCN 2014, Goettingen, Germany, 09/03/2014 - 09/05/2014
Hageet al 2013	Hagen, 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. 2015	Hagen, 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 networks	11th Göttingen Meeting of the German Neuroscience Society, Göttingen, Germany, 03/18/2015 - 03/21/2015
Helias et al. 2011b	Helias, M., Tetzlaff, T. and Diesmann, M.	Towards a unified theory of correlations in recurrent neural networks	BMC Neuroscience 2011, 12(Suppl 1):P73 doi:10.1186/1471-2202-12-S1-P73	fulltext
Helias et al. 2011c	Helias, M., Grytskyy, D., Tetzlaff, T. and Diesmann, M.	Model-invariant features of correlations in recurrent networks	Front. 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. 2012a	Helias, 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 supercomputers	INCF Meeting, 10-12 Sept 2012, Munich, Germany
Heliaset al 2013	Helias, 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 2013b	Helias, 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 2013	Jordan, 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 2013b	Jordan, 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 2015	Jordan, 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 study	11th Göttingen Meeting of the German Neuroscience Society, Göttingen, Germany, 03/18/2015 - 03/21/2015
Jordanet al. 2014b	Jordan, 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 Systems	OCCAM 2014, Osnabrueck, Germany, 05/07/2014 - 05/09/2014
Krieneret al 2013	Kriener, 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 2013b	Kunkel, 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. 2011b	Lindén, 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 2012	Maksimov, 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 2013	Maximov, 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. 2011	Morrison, 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 processing	Poster at the Ninth Göttingen Meeting of the German Neuroscience Society 2011: T27-11B	abstract
Nowke et al. 2012b	Nowke, C., Hentschel, B., Kuhlen, T., Eppler, J.M., van Albada, S., Bakker, R., Diesmann, M., Schmidt, M.	VisNEST - Interactive analysis of neural activity data	IEEE VisWeek 2012	abstract
Nowke et al. 2013b	Nowke, C., Schmidt, M., van Albada, S., Eppler, J., Bakker, R., Diesmann, M., Hentschel, B. and Kuhlen, T.	Interactive visualization of brain-scale spiking activity	Annual CNS Meeting 2013, BMC Neuroscience 2013, 14(Suppl 1):P110
Nowkeet al 2013	Nowke, 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 2014	Pfeil, T., Jordan, J., Tetzlaff, T., Grübl, A., Schemmel, J., Diesmann, M. and Meier, K.	Decorrelation of neural-network activity on heterogeneous neuromorphic hardware	10th Bernstein Conference 2014, Goettingen, Goettingen, Germany, 09/02/2014 - 09/05/2014 doi:10.12751/nncn.bc2014.0221	abstract
Potjans and Diesmann 2011b	Potjans, 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. 2011	Potjans, T.C., Kunkel, S., Morrison, A., Plesser, H.E. and Diesmann, M.	Beyond local cortical network modeling: linking microscopic and macroscopic connectivity in brainscale simulations	Poster at the Ninth Göttingen Meeting of the German Neuroscience Society 2011: T26-6A	abstract
Schmidt et al. 2013	Schmidt, M., van Albada, S., Bakker, R. and Diesmann, M.	Toward a spiking multi-area network model of macaque visual cortex	Proceedings of the 10th Meeting of the German Neuroscience Society, Neuroforum 2013 : T24-10D (2013)
Schmidt et al. 2013b	Schmidt, M., van Albada, S., Bakker, R. and Diesmann, M.	Integrating multi-scale data for a network model of macaque visual cortex	Annual CNS Meeting 2013, BMC Neuroscience 2013, 14(Suppl 1):P111 (2013)
Schmidt et al. 2014c	Schmidt, M., van Albada, S., Bakker, R. and Diesmann, M.	A spiking multi-area network model of macaque visual cortex	Annual meeting of the SfN, SfN2014, Washington, DC, USA, 11/15/2014 - 11/19/2014
Schmidt et al. 2014d	Schmidt, M., van Albada, S., Bakker, R. and Diesmann, M.	Connectomics of a multi-area network model of macaque visual cortex	Micro-, meso- and macro-connectomics of the brain, Paris, Frankreich, 05/05/2014 - 05/05/2014
Schmidtet al 2013b	Schmidt, 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. 2014a	Schücker, J., Diesmann, M. and Helias, M.	The transfer function of the LIF model: from white to filtered noise	Computation Neuroscience Conference 2014, CNS14, Quebec, Canada, 07/23/2014 - 07/31/2014
Schultze-Kraft et al. 2011	Schultze-Kraft, M., Diesmann, M., Grün, S. and Helias, M.	Correlation transmission of spiking neurons is boosted by synchronous input	BMC Neuroscience 2011, 12(Suppl 1):P144 doi:10.1186/1471-2202-12-S1-P144	fulltext
Stavrinou et al. 2015	Stavrinou, 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 networks	Neuro Informatics 2014, Leiden, Netherlands, 08/25/2014 - 08/27/2014
Tetzlaff et al. 2014	Tetzlaff, 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 architectures	10th Bernstein Conference 2014, Goettingen, Goettingen, Germany, 09/02/2014 - 09/05/2014 doi:10.12751/nncn.bc2014.0133	abstract
Tetzlaff et al. 2014b	Tetzlaff, 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 V1	NeuroVisionen 10 meeting, Jülich, Germany, 09/26/2014 - 09/26/2014
Tetzlaff et al. 2015	Tetzlaff, 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 networks	2nd International Symposium of the Clinical Research Group 219, Cologne, Germany, 02/26/2015 - 02/28/2015
van Albada et al. 2013	van Albada, S.J., Schrader, S., Helias, M. and Diesmann, M.	Influence of different types of downscaling on a cortical microcircuit model	BMC Neuroscience 2013, 14(Suppl 1):P112 doi:10.1186/1471-2202-14-S1-P112	abstract
van Albada et al. 2014k	van Albada, S, Helias, M. and Diesmann, M.	One-to-one relationship between effective connectivity and correlations in asynchronous networks	Bernstein Conference, Göttingen, Germany, 09/03/2014 - 09/05/2014
Van Albadaet al 2013	van 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. 2011b	Wagatsuma, 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 signals	BMC Neuroscience 2011, 12(Suppl 1):P114 doi:10.1186/1471-2202-12-S1-P114	fulltext

Web publication

Nowke et al. 2013c	Nowke, C., Schmidt, M., van Albada, S., Eppler, J., Bakker, R., Diesmann, M., Hentschel, B. and Kuhlen, T.	VisNEST - Interactive analysis of neural activity data	Video posted on vimeo: http://vimeo.com/82512745	fulltext
Potjans and Diesmann 2011	Potjans, T.C. and Diesmann, M.	The cell-type specific connectivity of the local cortical network explains prominent features of neuronal activity	arXiv:1106.5678v1 [q-bio.NC] 28 Jun 2011	abstract
Schuecker et al. 2014	Schuecker, J., Diesmann, M. and Helias, M.	Spectral properties of excitable systems subject to colored noise	arXiv:1411.0432	abstract, fulltext
van Albada et al. 2014b	Van 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 Gehirns	RWTH Themen (2014) 2: 52-57	fulltext
van Albada et al. 2014e	van Albada, S.J., Helias, M. and Diesmann, M.	Scalability of asynchronous networks is limited by one-to-one mapping between effective connectivity and correlations	arXiv:1411.4770	abstract, fulltext

Other

Chorley et al. 2014	Chorley, P., Diesmann, M., Helias, M. and Grün, S.	Correlated rate vector dynamics in motor cortex	INM Retreat, Jülich, Germany, 07/01/2014 - 07/02/2014
Dahmen et al. 2014b	Dahmen, 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 approach	BrainScaleS 4th plenary meeting, Manchester, United Kingdom, 03/19/2014 - 03/21/2014
Denker et al. 2014d	Denker, M., Zehl, L., Kilavik, B., Diesmann, M., Brochier, T., Riehle, A. and Grün, S.	Characterizing Spatially Organized LFP Beta Oscillations in Motor Cortex	INM Retreat 2014, Jülich, Germany, 07/01/2014 - 07/02/2014
Gruen and Diesmann 2012	Gruen, S. and Diesmann, M.	Hirnforschung braucht ein Netzwerk: Computational and Systems Neuroscience am Forschungszentrum Juelich	systembiologie.de (2012) 4: 36-39	fulltext
Jordan et al. 2014d	Jordan, 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 systems	4th BrainScaleS Plenary meeting, Manchester, England, 03/20/2014 - 03/21/2014
Jordan et al. 2014e	Jordan, 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 systems	4th BrainScaleS Plenary meeting, Manchester, England, 03/20/2014 - 03/21/2014
Jordanet al. 2014	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 Systems	INM Retreat 2014, Juelich, Germany, 07/01/2014 - 07/02/2014
Kunkel et al. 2012	Kunkel, 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 Scale	in 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. 2014b	Plesser, H.E., Helias, M., Diesmann, M. and Morrison, A.	The NEST 4g kernel: highly scalable simulation code from laptops to supercomputers	BrainScaleS CodeJam Workshop 6, Juelich, Germany, 01/27/2014 - 01/29/2014	BibTeX
Maximov et al. 2014	Maximov, 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. 2014	Schücker, J., Schmidt, M., van Albada, S., Diesmann, M. and Helias, M.	Stability analysis of a multi-area network model of macaque visual cortex	INM Retreat 2013, Juelich, Germany, 07/01/2014 - 07/02/2014
Schmidt et al. 2014b	Schmidt, M., Schücker, J., van Albada, S., Bakker, R., Helias, M. and Diesmann, M.	Multi-area network model of visual cortex	4th BrainScales plenary meeting, Manchester, Grossbritannien, 03/19/2014 - 03/21/2014
Tetzlaff et al. 2014c	Tetzlaff, 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 V1	INM retreat, Jülich, Germany, 07/01/2014 - 07/02/2014
van Albada and Diesmann 2014	van Albada, S. and Diesmann, M.	NEST HPC status - technology and theory	BrainScaleS Demo 1, 2 and 3 workshop, Gif-sur-Yvette, France, 11/25/2014 - 11/26/2014
van Albada et al. 2014l	van Albada, S., Schmidt, M., Bakker, R. and Diesmann, M.	Spiking multi-area model of macaque visual cortex	INM Retreat 2014, Jülich, Germany, 07/01/2014 - 07/02/2014