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103. Amsalem, O., Van Geit, W., Muller, E., Markram, H., and Segev, I. (2016). From Neuron Biophysics to Orientation Selectivity in Electrically Coupled Networks of Neocortical L2/3 Large Basket Cells. Cereb. Cortex 26, 3655–3668.
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100. Halnes, G., Mäki-Marttunen, T., Keller, D., Pettersen, K.H., Andreassen, O.A., and Einevoll, G.T. (2016). Effect of Ionic Diffusion on Extracellular Potentials in Neural Tissue. PLoS Comput. Biol. 12, e1005193.
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98. Kanari, L., Dlotko, P., Scolamiero, M., Levi, R., Shillcock, J., Hess, K., and Markram, H. (2016). Quantifying topological invariants of neuronal morphologies. arXiv.

97. Knoll A., Gewaltig M-O., Neurorobotics: A strategic pillar of the Human Brain Project (2016). Chapter in Supplement to Science. Robotics in Brain- inspired intelligent robotics: The intersection of robotics and neuroscience.
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96. Kumbhar, P., Hines, M., Ovcharenko, A., Mallon, D.A., King, J., Sainz, F., Schürmann, F., and Delalondre, F. (2016). Leveraging a Cluster-Booster Architecture for Brain-Scale Simulations. In High Performance Computing, J.M. Kunkel, P. Balaji, and J. Dongarra, eds. (Springer International Publishing), pp. 363–380.
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94. Lytton, W.W., Seidenstein, A.H., Dura-Bernal, S., McDougal, R.A., Schürmann, F., and Hines, M.L. (2016). Simulation Neurotechnologies for Advancing Brain Research: Parallelizing Large Networks in NEURON. Neural Comput 28, 2063–2090.
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93. Magalhães, B.R.C., Tauheed, F., Heinis, T., Ailamaki, A., and Schürmann, F. (2016). An Efficient Parallel Load-Balancing Framework for Orthogonal Decomposition of Geometrical Data. In: Kunkel J., Balaji P., Dongarra J. (eds) High Performance Computing. Lecture Notes in Computer Science,. In High Performance Computing, J.M. Kunkel, P. Balaji, and J. Dongarra, eds. (Springer International Publishing), pp. 81–97.
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91. Shillcock, J.C., Hawrylycz, M., Hill, S., and Peng, H. (2016). Reconstructing the brain: from image stacks to neuron synthesis. Brain Inform 3, 205–209.
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90. Van Geit, W., Gevaert, M., Chindemi, G., Rössert, C., Courcol, J.-D., Muller, E.B., Schürmann, F., Segev, I., and Markram, H. (2016). BluePyOpt: Leveraging Open Source Software and Cloud Infrastructure to Optimise Model Parameters in Neuroscience. Front Neuroinform 10.
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89. Vanherpe, L., Kanari, L., Atenekeng, G., Palacios, J., and Shillcock, J. (2016). Framework for efficient synthesis of spatially embedded morphologies. Phys Rev E 94, 023315.
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88. Vanherpe, L., Kanari, L., Atenekeng, G., Palacios, J., and Shillcock, J. (2016). In situ synthesis and simulation of polydisperse amphiphilic membranes. International Journal of Advances in Engineering Sciences and Applied Mathematics 8, 126–133.
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87. Wang, Q., Abdul, S., Almeida, L., Ananiadou, S., Balderas-Martínez, Y.I., Batista-Navarro, R., Campos, D., Chilton, L., Chou, H.-J., Contreras, G., Cooper, L., Dai, H.-J., Ferrell, B., Fluck, J., Gama-Castro, S., George, N., Gkoutos, G., Irin, A.K., Jensen, L.J., Jimenez, S., Jue, T.R., Keseler, I., Madan, S., Matos, S., McQuilton, P., Milacic, M., Mort, M., Natarajan, J., Pafilis, E., Pereira, E., Rao, S., Rinaldi, F., Rothfels, K., Salgado, D., Silva, R.M., Singh, O., Stefancsik, R., Su, C.-H., Subramani, S., Tadepally, H.D., Tsaprouni, L., Vasilevsky, N., Wang, X., Chatr-Aryamontri, A., Laulederkind, S.J.F., Matis-Mitchell, S., McEntyre, J., Orchard, S., Pundir, S., Rodriguez-Esteban, R., Van Auken, K., Lu, Z., Schaeffer, M., Wu, C.H., Hirschman, L., Arighi, C.N. (2016). Overview of the interactive task in BioCreative V. Database: The Journal of Biological Databases and Curation (Oxford), Volume 2016, 1 January 2016, DOI:  10.1093/database/baw119.

86. H. Markram, E. Muller, S. Ramaswamy, Michael W. Reimann, M. Abdellah, Carlos A. Sanchez, A. Ailamaki, L. Alonso-Nanclares, N. Antille, S. Arsever, Guy Antoine A. Kahou, Thomas K. Berger, A. Bilgili, N. Buncic, A. Chalimourda, G. Chindemi, J.-D. Courcol, F. Delalondre, V. Delattre, S. Druckmann, R. Dumusc, J. Dynes, S. Eilemann, E. Gal, Michael E. Gevaert, J.-P. Ghobril, A. Gidon, Joe W. Graham, A. Gupta, V. Haenel, E. Hay, T. Heinis, Juan B. Hernando, M. Hines, L. Kanari, D. Keller, J. Kenyon, G. Khazen, Y. Kim, James G. King, Z. Kisvarday, P. Kumbhar, S. Lasserre, J.-V. Le Bé, Bruno R.C. Magalhães, A. Merchán-Pérez, J. Meystre, Benjamin R. Morrice, J. Muller, A. Muñoz-Céspedes, S. Muralidhar, K. Muthurasa, D. Nachbaur, Taylor H. Newton, M. Nolte, A. Ovcharenko, J. Palacios, L. Pastor, R. Perin, R. Ranjan, I. Riachi, J.-R. Rodríguez, Juan L. Riquelme, C. Rössert, K. Sfyrakis, Y. Shi, Julian C. Shillcock, G. Silberberg, R. Silva, F. Tauheed, M. Telefont, M. Toledo-Rodriguez, T. Tränkler, W. Van Geit, Jafet V. Díaz, R. Walker, Y. Wang, Stefano M. Zaninetta, J. DeFelipe, Sean L. Hill, I. Segev, and F. Schürmann, Reconstruction and Simulation of Neocortical Microcircuitry. Cell 163, 2015, 456-492.
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85. S. Ramaswamy, J.-D. Courcol, M. Abdellah, S.R. Adaszewski, N. Antille, S. Arsever, G. Atenekeng, A. Bilgili, Y. Brukau, A. Chalimourda, G. Chindemi, F. Delalondre, R. Dumusc, S. Eilemann, M.E. Gevaert, P. Gleeson, J.W. Graham, J.B. Hernando, L. Kanari, Y. Katkov, D. Keller, J.G. King, R. Ranjan, M.W. Reimann, C. Rössert, Y. Shi, J.C. Shillcock, M. Telefont, W. Van Geit, J. Villafranca Diaz, R. Walker, Y. Wang, S.M. Zaninetta, J. DeFelipe, S.L. Hill, J. Muller, I. Segev, F. Schürmann, E.B. Muller, and H. Markram, The neocortical microcircuit collaboration portal: a resource for rat somatosensory cortex. Front. Neural Circuits, 2015, 44.
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84. M. Reimann, E.Muller, S.Ramaswamy, H.Markram: An Algorithm to Predict the Connectome of Neural Microcircuits. 2015. Frontiers in Neural Circuits 9 2015, 28.
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83. A. Devresse, F. Delalondre, F. Schürmann, Blue Brain Project Fully Automated Workflows and Ecosystem to guarantee Scientific Result Reproducibility across Platforms, Software Environment and Systems. International Conference for High Performance Computing, Networking, Storage and Analysis 2015, Austin, Texas.
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82. T. Ewart, S. Yates, F. Cremonesi, P. Kumbhar, F. Schuermann, F. Delalondre, Performance Evaluation of the IBM POWER8 system to Support Computational Neuroscientific Application Using Morphologically Detailed Neurons. PMBS15 Workshop, Supercomputing 2015, Austin, Texas.
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81. M.Abdellah, A.Bilgilli, S.Eilemann, H.Markram, F.Schürmann : Physically-based in silico light sheet microscopy for visualizing fluorescent brain models. BMC Bioinformatics. 2015 Aug 13;16 Suppl 11:S8
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80. V.Delattre, D.Keller, M.Perich, H.Markram, E.B.Muller: Network-timing-dependent plasticity. Front Cell Neurosci. 2015 Ju 9;9:220.
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79. Anastassiou CA, Perin R, Buzsáki G, Markram H, Koch C. Cell type- and activity-dependent extracellular correlates of intracellular spiking. J Neurophysiol. 2015 Jul;114(1):608-23. doi: 10.1152/jn.00628.2014.
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78. S.Ramaswamy, H.Markram: Anatomy and Physiology of the thick-tufted layer 5 pyramidal neuron, Front Cell Neurosci. 2015; 9:233.
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77. D.Keller, N.Babai, O.Kochubey, Y.Han, H.Markram, F.Schürmann, R.Schneggenburger: An Exclusion Zone for Ca2+ Channels around Docked Vesicles Explains Release Control by Multiple Channels at a CNS Synapse, PLoS Comput Biol. 2015 May 7;11(5):e1004253.
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76. Costantini I, Ghobril JP, Di Giovanna AP, Allegra Mascaro AL, Silvestri L, Müllenbroich MC, Onofri L, Conti V, Vanzi F, Sacconi L, Guerrini R, Markram H, Iannello G, Pavone FS A versatile clearing agent for multi-modal brain imaging. Scientific Reports. 2015 May 7;5:9808.
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75. Frackowiak R, Markram H. The future of human cerebral cartography: a novel approach. Philos Trans R Soc Lond B Biol Sci. 2015 May 19;370(1668). pii: 20140171.
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74. Vannucci, L., Ambrosano, A., Cauli, N., Albanese, U., Falotico, E., Ulbrich, S., Pfotzer, L., Hinkel, G., Denninger, O., Peppicelli, D., Guyot, L., Von Arnim, A., Deser, S., Maier, P., Dillman, R., Klinker, G., Levi, P., Knoll, A., Gewaltig, M.-O., and Laschi, C. (2015). A visual tracking model implemented on the iCub robot as a use case for a novel neurorobotic toolkit integrating brain and physics simulation. In 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids), pp. 1179–1184.
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73. X.Vasques, R.Richardet, SL.Hill, D.Slater, J-C.Chappelier, E.Pralong. J.Bloh, B.Draganski, L.Cif: Automatic target validation based on neuroscientific literature mining for tractography, Front Neuroanat. 2015 May 27;9:66.
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72. R.Richardet, J-C.Chappelier, M.Telefont, S.Hill: Large-scale extraction of brain connectivity from the neuroscientific literature, Bioinformatics. 2015 May; 31(10):1640-1647.
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71. S. Ramaswamy and E. Muller, Cell-type specific modulation of neocortical UP and DOWN states. Frontiers in Cellular Neuroscience, 9:370, 2015.
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70. S. Ramaswamy, Exciting times for inhibition: GABAergic synaptic transmission in dentate gyrus interneuron networks. Frontiers in Neural Circuits, 9:13, 2015.
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69. E. Muller, J. A. Bednar Diesmann M., M.-O., Gewaltig, M. Hines , A.P. Davison,. Python in Neuroscience. Frontiers in Neuroinformatics, 2015, 9.
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68. Wybo, W.A.M., Boccalini, D., Torben-Nielsen, B., and Gewaltig, M.-O. (2015). A Sparse Reformulation of the Green’s Function Formalism Allows Efficient Simulations of Morphological Neuron Models. Neural Comput 27, 2587–2622.

67. Tiesinga, P., Bakker, R., Hill, S., and Bjaalie, J.G. (2015). Feeding the human brain model. Curr. Opin. Neurobiol. 32, 107–114.
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66. Jolivet, R., Coggan, J.S., Allaman, I., and Magistretti, P.J. (2015). Multi-timescale modeling of activity-dependent metabolic coupling in the neuron-glia-vasculature ensemble. PLoS Comput. Biol. 11, e1004036.
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65. E.Hay and I.Segev: Dendritic Excitability and Gain Control in Recurrent Cortical Microcircuits. Cerebral Cortex, 2014 Sep 9.
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64. F.Schürmann, F.Delalondre, P.S.Kumbhar, J.Biddiscombe, M.Gila, D.Tacchella, A.Curioni, B.Metzler, P.Morjan, J.Fenkes, M.M.Franceschini, R.S.Germain, L.Schneidenbach, T.J.C.Ward, B.G.Fitch: Rebasing I/O for Scientific Computing: Leveraging Storage Class Memory in an IBM BlueGene/Q Supercomputer. In J.M. Kunkel, T. Ludwig, and H.W. Meuer (Eds.): ISC 2014, LNCS 8488, pp. 331–347. Springer International Publishing Switzerland (2014).
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63. T.Ewart, F.Delalondre, F.Schürmann: Cyme: A Library Maximizing SIMD Computation on User-Defined Containers. In J.M. Kunkel, T. Ludwig, and H.W. Meuer (Eds.): ISC 2014, LNCS 8488, pp. 440–449. Springer International Publishing Switzerland (2014).
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62. S.Muralidhar, Y.Wang, H.Markram: Synaptic and cellular organization of layer 1 of the developing rat somatosensory cortex. Front Neuroanat. 2014 Jan 16;7:52.
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61. F.Tauheed, T.Heinis, F.Schürmann, H.Markram, A.Ailamaki : OCTOPUS: Efficient Query Execution on Dynamic Mesh Datasets, In Proceedings of the 30th IEEE International Conference on Data Engineering. Chicago, USA, March 2014.
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59. J.DeFelipe, E.Garrido, H.Markram: The death of Cajal and the end of scientific romanticism and individualism. Trends Neurosci. 37(10):525-7 (2014).
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58. Adaszewski, S. (2014). Mynodbcsv: lightweight zero-config database solution for handling very large C SV files. PLoS ONE 9, e103319.
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57. Babai, N., Kochubey, O., Keller, D., and Schneggenburger, R. (2014). An alien divalent ion reveals a major role for Ca2+ buffering in controlling slow transmitter release. J. Neurosci. 34, 12622–12635.
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56. Kriener, B., Enger, H., Tetzlaff, T., Plesser, H.E., Gewaltig, M.-O., and Einevoll, G.T. (2014). Dynamics of self-sustained asynchronous-irregular activity in random networks of spiking neurons with strong synapses. Front Comput Neurosci 8, 136.
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55. Toledo-Rodriguez, M., and Markram, H. (2014). New Edition: Single-cell RT-PCR, a technique to decipher the electrical, anatomical, and genetic determinants of neuronal diversity. In: Martina M., Taverna S. (eds)Patch-Clamp Methods and Protocols. Methods in Molecular Biology (Methods and Protocols). In Methods in Molecular Biology, pp. 143–158. [For accessible earlier version see Toledo-Rodriquez et al 2007.]
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54. M.W. Reimann, C.A.Anastassiou, R.Perin, S.L.Hill, H. Markram, C. Koch: A biophysically detailed model of neocortical local field potentials predicts the critical role of active membrane currents. Neuron, 79(2), 375-390, 2013.
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53. E. Hay, F. Schürmann, H. Markram, I. Segev: Preserving axosomatic spiking features despite diverse dendritic morphology. J Neurophysiol, 109(12), 2972-2981, 2013.
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52. J.B. Hernando, J. Biddiscombe, B. Bohara, S. Eilemann, F. Schürmann: Practical parallel rendering of detailed neuron simulations, EGPGV 2013.
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51. R.Perin, M.Telefont, H.Markram: Computing the size and number of neuronal clusters in local circuits, Front Neuroanat. 2013;7:1. Epub 2013 Feb 19.
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50. A.Loebel, JV.LeBe, MJ.Richardson, H.Markram, A.Herz: Matched pre- and post-synaptic changes underlie synaptic plasticity over long time scales. 2013. J Neurosci. 33(15):6257-66.

49. H.Markram: Seven challenges for Neuroscience. 2013. Functional Neurology. 28(3):145-51.
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48. ER.Kandel, H.Markram, PM.Matthews, R.Yuste, C.Koch: Neuroscience thinks big (and collaboratively). 2013. Nat Rev Neurosci. 14(9):659-64.
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47. J.DeFelipe et al. [42 authors]: New insights into the classification and nomenclature of cortical GABAergic interneurons. 2013. Nat Rev Neurosci. 14(3):202-16.
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46. Wybo, W.A.M., Stiefel, K.M., and Torben-Nielsen, B. (2013). The Green’s function formalism as a bridge between single- and multi-compartmental modeling. Biol Cybern 107, 685–694.
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45. S.Druckmann, S.Hill, F.Schürmann, H.Markram, I.Segev : A Hierarchical Structure of Cortical Interneuron Electrical Diversity Revealed by Automated Statistical Analysis, Cerebral Cortex, (2012), doi: 10.1093/cercor/bhs290.
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44. Markram, H., Gerstner, W., and Sjöström, P.J. (2012). Editorial Article: Spike-timing-dependent plasticity: a comprehensive overview. Front Synaptic Neurosci 4, 2.
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43. Tauheed, F., Biveinis, L., Heinis, T., Schurmann, F., Markram, H., and Ailamaki, A. (2012a). Accelerating Range Queries for Brain Simulations. In Proceedings of the 2012 IEEE 28th International Conference on Data Engineering, (Washington, DC, USA: IEEE Computer Society), pp. 941–952.
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42. Hernando, J., Schürmann, F., and Pastor, L. (2012). Towards real-time visualization of detailed neural tissue models: View frustum culling for parallel rendering. In IEEE Symposium on Biological Data Visualization (BioVis), (IEEE), pp. 25–32.
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41. S.L.Hill, Y.Wang, I.Riachi, F.Schürmann, H.Markram: Statistical connectivity provides a sufficient foundation for specific functional connectivity in neocortical neural microcircuits, PNAS, Published online before print September 18, 2012.
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40. A.Gidon and I.Segev: Principles governing the operation of synaptic inhibition in dendrites, Neuron, 2012 Jul 26;75(2):330-41.
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39. F.Tauheed, T.Heinis, F.Schürmann, H.Markram, A.Ailamaki: SCOUT: Prefetching of Latent Structure Following Queries, VLDB 2012.
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38. G.Khazen, S.L.Hill, F.Schürmann , and H.Markram: Combinatorial Expression Rules of Ion Channel Genes in Juvenile Rat (Rattus norvegicus) Neocortical Neurons, PLoS One, 7(4): e34786.
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37. S.Eilemann, A.Bilgili, M.Abdellah, J.Hernando, M.Makhinya, R.Pajarola, and F.Schürmann: Parallel Rendering on Hybrid Multi-GPU Clusters, EGPGV 2012.
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36. S.Lasserre, J.Hernando, S.Hill, F.Schürmann, P. de Miguel Anasagasti, G.Abou Jaoudé, H.Markram : A Neuron Mesh Representation for Visualization of Electrophysiological Simulations, IEEE Transactions on Visualization and Computer Graphics, 18 (2): p. 214-217.
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35. S.Ramaswamy, S.L.Hill, J.G.King, F.Schürmann, Y.Wang, and H.Markram: Intrinsic Morphological Diversity of Thick-tufted Layer 5 Pyramidal Neurons Ensures Robust and Invariant Properties of in silico Synaptic Connections. J Physiol. 2012 Feb 15;590(Pt 4):737-52. Epub 2011 Nov 14.
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34. R.Ranjan, G.Khazen, L.Gambazzi, S.Ramaswamy, S.L.Hill, F.Schürmann, and H.Markram: Channelpedia: an integrative and interactive database for ion channels, Front. Neuroinform 2011. 5:36.
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33. M.Hines, S.Kumar, and F.Schürmann: Comparison of neuronal spike exchange methods on a Blue Gene/P supercomputer. Front. Comput. Neurosci 2011. 5:49.
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32. E.Hay, S.L.Hill, F.Schürmann, H.Markram, and I.Segev: Models of Neocortical Layer 5b Pyramidal Cells Capturing a Wide Range of Dendritic and Perisomatic Active Properties. PLoS Computational Biology 2011, 7(7): e1002107.
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31. S.Druckmann, T.K.Berger, F.Schürmann, S.L.Hill, H.Markram, and I.Segev: Effective stimuli for constructing reliable neuron models, Plos Computational Biology, 2011, 7(8): e1002133.
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30. R.Perin, T.K.Berger, and H.Markram: A synaptic organizing principle for cortical neuronal groups, PNAS, 2011, 108 (12).

29. S.Romand, Y.Wang, M.Toledo-Rodriguez, and H.Markram: Morphological development of thick-tufted layer v pyramidal cells in the rat somatosensory cortex, Front Neuroanat. 2011 5:5.
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28. CA.Anastassiou, R.Perin, H.Markram, and C.Koch: Ephaptic coupling of cortical neurons, Nat Neurosci. 2011 Feb;14(2):217-23.
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27. H. Markram, W. Gerstner, PJ. Sjöström: A history of spike-timing-dependent plasticity. Front Synaptic Neurosci. 2011;3:4. Epub 2011 Aug 29.
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26. H. Markram, R. Perin: Innate neural assemblies for lego memory. Front Neural Circuits. 2011;5:6. Epub 2011 May 16.
DOI: 10.3389/fncir.2011.00006

25. TK.Berger, G.Silberberg, R.Perin, and H.Markram: Brief bursts self-inhibit and correlate the pyramidal network, PLoS Biol. 2010 Sep 7;8(9).
DOI: 10.1371/journal.pbio.1000473

24. L.Bar-Ilan, A.Gidon, and I.Segev: Inter-regional synaptic competition in neurons with multiple STDP-inducing signals, J Neurophysiol (December 1, 2010).
DOI: 10.1152/jn.00612.2010.

23. A.Loebel, G.Silberberg, D.Helbig, H.Markram, M.Tsodyks, MJ.Richardson: Multiquantal release underlies the distribution of synaptic efficacies in the neocortex, Front Comput Neurosci. 2009; 3:27.
DOI: 10.3389/neuro.10.027.2009

22. TK.Berger, R.Perin, G.Silberberg, and H.Markram: Frequency-dependent disynaptic inhibition in the pyramidal network: a ubiquitous pathway in the developing rat neocortex, J Physiol. 2009 Nov 15;587(Pt 22):5411-25.
DOI: 10.1113/jphysiol.2009.176552

21. J.G.King, M.Hines, S.Hill, P.H.Goodman, H.Markram, F.Schürmann: A component-based extension framework for large-scale parallel simulations in NEURON , Front Neuroinformatics, 3:10.
DOI: 10.3389/neuro.11.010.2009

20. Anwar H., Riachi I., Schürmann F., Markram H. (2009). “An approach to capturing neuron morphological diversity,” in Computational Neuroscience: Realistic Modeling for Experimentalistsed. De Schutter E., editor. (Cambridge: The MIT Press) 211–232.
ISBN 978-0-262-01327

19. J.Kozloski, K.Sfyrakis, S.Hill, F.Schürmann, C.Peck, H.Markram: Identifying, tabulating, and analyzing contacts between branched neuron morphologies, IBM Journal of Research and Development, Vol 52, Number 1/2, 2008.

18. M.Hines, H.Eichner, F.Schürmann: Neuron splitting in compute-bound parallel network simulations enables runtime scaling with twice as many processors, J. Comput. Neurosci., 25(1):203-10, 2008.
DOI: 10.1007/s10827-007-0073-3

17. M.Hines, H.Markram, F.Schürmann: Fully Implicit Parallel Simulation of Single Neurons, J. Comput. Neurosci., 25(3):439-48, 2008.
DOI: 10.1007/s10827-008-0087-5

16. S.Druckmann, T.Berger, S.Hill, F.Schürmann, H.Markram, I.Segev: Evaluating automated parameter constraining procedures of neuron models by experimental and surrogate data, Biol Cybern, 99(4-5):371-9, 2008.
DOI: 10.1007/s00422-008-0269-2

15. C.Calì, TK.Berger, M.Pignatelli, A.Carleton, H.Markram, M.Giugliano: Inferring connection proximity in networks of electrically coupled cells by subthreshold frequency response analysis, J Comput Neurosci. 2008 Jun;24(3):330-45. Epub 2007 Nov 28.
DOI: 10.1007/s10827-007-0058-2

14. O.Melamed, O.Barak, G.Silberberg, H.Markram, M.Tsodyks: Slow oscillations in neural networks with facilitating synapses, J Comput Neurosci. 2008 Oct;25(2):308-16.
DOI: 10.1007/s10827-008-0080-z

13. GA.Ascoli, Alonso-Nanclares L, Anderson SA, Barrionuevo G, Benavides-Piccione R, Burkhalter A, Buzsáki G, Cauli B, Defelipe J, Fairén A, Feldmeyer D, Fishell G, Fregnac Y, Freund TF, Gardner D, Gardner EP, Goldberg JH, Helmstaedter M, Hestrin S, Karube F, Kisvárday ZF, Lambolez B, Lewis DA, Marin O, Markram H, Muñoz A, Packer A, Petersen CC, Rockland KS, Rossier J, Rudy B, Somogyi P, Staiger JF, Tamas G, Thomson AM, Toledo-Rodriguez M, Wang Y, West DC, Yuste R.: Petilla terminology: nomenclature of features of GABAergic interneurons of the cerebral cortex, Nat Rev Neurosci. 2008 Jul;9(7):557-68.
DOI: 10.1038/nrn2402

12. H.Markram: Fixing the location and dimensions of functional neocortical columns, HFSP J. 2008 Jun;2(3):132-5.
DOI: 10.2976/1.2919545

11. G.Silberberg and H.Markram: Disynaptic inhibition between neocortical pyramidal cells mediated by Martinotti cells, Neuron. 2007 Mar 1;53(5):735-46.
DOI: 10.1016/j.neuron.2007.02.012

10. H.Markram: Bioinformatics: industrializing neuroscience. Nature. 2007 Jan 11;445(7124):160-1.
DOI: 10.1038/445160a

9. A.Abid, A.Jan, L.Francioli, K.Sfyrakis, and F.Schürmann: Keyword Based Indexing and Searching over Storage Resource Broker. OTM Conferences, 2007, Proceedings, Part II. Lecture Notes in Computer Science 4804 Springer 2007, ISBN 978-3-540-76835-7, pp. 1233-43.
DOI: 10.1007/978-3-540-76843-2_6

8. S.Druckmann, Y.Banitt, A.Gidon, F.Schürmann, H.Markram, and I.Segev: A Novel Multiple Objective Optimization Framework for Constraining Conductance-Based Neuron Models by Experimental Data, Frontiers in Neuroscience, Vol. 1, Issue 1, 2007.
DOI: 10.3389/neuro.

7. M.Toledo-Rodriguez and H.Markram: Single-cell RT-PCR, a technique to decipher the electrical, anatomical, and genetic determinants of neuronal diversity, Methods Mol Biol. 2007;403:123-39.
DOI: 10.1007/978-1-59745-529-9_8

6. JV.Le Bé, G.Silberberg, Y.Wang, and H.Markram: Morphological, electrophysiological, and synaptic properties of corticocallosal pyramidal cells in the neonatal rat neocortex, Cereb Cortex. 2007 Sep;17(9):2204-13.
DOI: 10.1093/cercor/bhl127

5. M.Migliore, C.Cannia, W.W.Lytton, H.Markram, and M.L.Hines: Parallel network simulations with NEURON, J Comput Neurosci. 2006 Oct;21(2):119-29.
DOI: 10.1007/s10827-006-7949-5

4. H.Markram: The blue brain project. Nat Rev Neurosci. 7, 153-160, 2006.
DOI: 10.1038/nrn1848

3. Y.Wang, H.Markram, PH.Goodman, TK.Berger , J.Ma PS.Goldman-Rakic: Heterogeneity in the pyramidal network of the medial prefrontal cortex, Nat Neurosci. 2006 Apr;9(4):534-42.
DOI: 10.1038/nn1670

2. JV.Le Bé and H.Markram: Spontaneous and evoked synaptic rewiring in the neonatal neocortex, PNAS. 2006 Aug 29;103(35):13214-9.

1. A.J. Muhammad, H. Markram, NEOBASE: Databasing the Neocortical Microcircuit, Stud Health Technol Inform. 2005;112:167-77.