| Reconstruction and simulation of neocortical microcircuitry H Markram, E Muller, S Ramaswamy, MW Reimann, M Abdellah, ... Cell 163 (2), 456-492, 2015 | 1296 | 2015 |
| Models of neocortical layer 5b pyramidal cells capturing a wide range of dendritic and perisomatic active properties E Hay, S Hill, F Schürmann, H Markram, I Segev PLoS computational biology 7 (7), e1002107, 2011 | 314 | 2011 |
| A novel multiple objective optimization framework for constraining conductance-based neuron models by experimental data S Druckmann, Y Banitt, AA Gidon, F Schürmann, H Markram, I Segev Frontiers in neuroscience 1, 56, 2007 | 289 | 2007 |
| Caries detection with near-infrared transillumination using deep learning F Casalegno, T Newton, R Daher, M Abdelaziz, A Lodi-Rizzini, ... Journal of dental research 98 (11), 1227-1233, 2019 | 175 | 2019 |
| Statistical connectivity provides a sufficient foundation for specific functional connectivity in neocortical neural microcircuits SL Hill, Y Wang, I Riachi, F Schürmann, H Markram Proceedings of the National Academy of Sciences 109 (42), E2885-E2894, 2012 | 173 | 2012 |
| The quantitative single-neuron modeling competition R Jolivet, F Schürmann, TK Berger, R Naud, W Gerstner, A Roth Biological cybernetics 99, 417-426, 2008 | 151 | 2008 |
| The scientific case for brain simulations GT Einevoll, A Destexhe, M Diesmann, S Grün, V Jirsa, M de Kamps, ... Neuron 102 (4), 735-744, 2019 | 147 | 2019 |
| The neocortical microcircuit collaboration portal: a resource for rat somatosensory cortex S Ramaswamy, JD Courcol, M Abdellah, SR Adaszewski, N Antille, ... Frontiers in neural circuits 9, 44, 2015 | 142 | 2015 |
| BluePyOpt: leveraging open source software and cloud infrastructure to optimise model parameters in neuroscience W Van Geit, M Gevaert, G Chindemi, C Rössert, JD Courcol, EB Muller, ... Frontiers in neuroinformatics 10, 17, 2016 | 135 | 2016 |
| Fully implicit parallel simulation of single neurons ML Hines, H Markram, F Schürmann Journal of computational neuroscience 25, 439-448, 2008 | 87 | 2008 |
| The physiological variability of channel density in hippocampal CA1 pyramidal cells and interneurons explored using a unified data-driven modeling workflow R Migliore, CA Lupascu, LL Bologna, A Romani, JD Courcol, S Antonel, ... PLoS computational biology 14 (9), e1006423, 2018 | 81 | 2018 |
| A hierarchical structure of cortical interneuron electrical diversity revealed by automated statistical analysis S Druckmann, S Hill, F Schürmann, H Markram, I Segev Cerebral Cortex 23 (12), 2994-3006, 2013 | 75 | 2013 |
| Edge of chaos computation in mixed-mode vlsi-a hard liquid F Schürmann, K Meier, J Schemmel Advances in neural information processing systems 17, 2004 | 73 | 2004 |
| Channelpedia: an integrative and interactive database for ion channels R Ranjan, G Khazen, L Gambazzi, S Ramaswamy, SL Hill, F Schürmann, ... Frontiers in neuroinformatics 5, 36, 2011 | 65 | 2011 |
| Channelpedia: an integrative and interactive database for ion channels R Ranjan, G Khazen, L Gambazzi, S Ramaswamy, SL Hill, F Schürmann, ... Frontiers in neuroinformatics 5, 36, 2011 | 65 | 2011 |
| CoreNEURON: an optimized compute engine for the NEURON simulator P Kumbhar, M Hines, J Fouriaux, A Ovcharenko, J King, F Delalondre, ... Frontiers in neuroinformatics 13, 63, 2019 | 61 | 2019 |
| CoreNEURON: an optimized compute engine for the NEURON simulator P Kumbhar, M Hines, J Fouriaux, A Ovcharenko, J King, F Delalondre, ... Frontiers in neuroinformatics 13, 63, 2019 | 61 | 2019 |
| Effective stimuli for constructing reliable neuron models S Druckmann, TK Berger, F Schürmann, S Hill, H Markram, I Segev PLoS computational biology 7 (8), e1002133, 2011 | 59 | 2011 |
| Evaluating automated parameter constraining procedures of neuron models by experimental and surrogate data S Druckmann, TK Berger, S Hill, F Schürmann, H Markram, I Segev Biological cybernetics 99, 371-379, 2008 | 59 | 2008 |
| A mixed-mode analog neural network using current-steering synapses J Schemmel, S Hohmann, K Meier, F Schürmann Analog Integrated Circuits and Signal Processing 38, 233-244, 2004 | 58 | 2004 |
