How structure determines correlations in neuronal networks V Pernice, B Staude, S Cardanobile, S Rotter PLoS computational biology 7 (5), e1002059, 2011 | 337 | 2011 |
The role of inhibition in generating and controlling Parkinson’s disease oscillations in the basal ganglia A Kumar, S Cardanobile, S Rotter, A Aertsen Frontiers in Systems Neuroscience 5, 2011 | 156 | 2011 |
Recurrent interactions in spiking networks with arbitrary topology V Pernice, B Staude, S Cardanobile, S Rotter Physical Review E—Statistical, Nonlinear, and Soft Matter Physics 85 (3 …, 2012 | 82 | 2012 |
Parabolic systems with coupled boundary conditions S Cardanobile, D Mugnolo Journal of Differential Equations 247 (4), 1229-1248, 2009 | 40* | 2009 |
Nonequilibrium dynamics of stochastic point processes with refractoriness M Deger, M Helias, S Cardanobile, FM Atay, S Rotter Physical Review E—Statistical, Nonlinear, and Soft Matter Physics 82 (2 …, 2010 | 37* | 2010 |
The relevance of network micro-structure for neural dynamics V Pernice, M Deger, S Cardanobile, S Rotter Frontiers in computational neuroscience 7, 72, 2013 | 35 | 2013 |
Analysis of a FitzHugh–Nagumo–Rall model of a neuronal network S Cardanobile, D Mugnolo Mathematical methods in the applied sciences 30 (18), 2281-2308, 2007 | 33 | 2007 |
Multiplicatively interacting point processes and applications to neural modeling S Cardanobile, S Rotter Journal of computational neuroscience 28 (2), 267-284, 2010 | 30 | 2010 |
Well-posedness and symmetries of strongly coupled network equations S Cardanobile, D Mugnolo, R Nittka Journal of Physics A: Mathematical and Theoretical 41 (5), 055102, 2008 | 25 | 2008 |
Mean-field analysis of orientation selectivity in inhibition-dominated networks of spiking neurons S Sadeh, S Cardanobile, S Rotter SpringerPlus 3, 1-35, 2014 | 16 | 2014 |
Simulation methods for generating reduced order models of MEMS sensors with geometric nonlinear drive motion M Putnik, S Cardanobile, M Sniegucki, S Kehrberg, M Kuehnel, ... 2018 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL …, 2018 | 14 | 2018 |
Incorporating geometrical nonlinearities in reduced order models for MEMS gyroscopes M Putnik, M Sniegucki, S Cardanobile, S Kehrberg, M Kuehnel, C Nagel, ... 2017 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL …, 2017 | 12 | 2017 |
Emergent properties of interacting populations of spiking neurons S Cardanobile, S Rotter Frontiers in computational neuroscience 5, 59, 2011 | 12 | 2011 |
Simulation and modelling of the drive mode nonlinearity in MEMS-gyroscopes M Putnik, S Cardanobile, C Nagel, P Degenfeld-Schonburg, J Mehner Procedia engineering 168, 950-953, 2016 | 11 | 2016 |
Predicting the resonance frequencies in geometric nonlinear actuated MEMS M Putnik, M Sniegucki, S Cardanobile, M Kühnel, S Kehrberg, JE Mehner Journal of Microelectromechanical Systems 27 (6), 954-962, 2018 | 10 | 2018 |
Stiffening of higher modes in doubly-clamped beam resonators depending on ground state amplitude M Putnik, S Cardanobile, C Höppner, J Mehner 2016 17th International Conference on Thermal, Mechanical and Multi-Physics …, 2016 | 8 | 2016 |
Inferring general relations between network characteristics from specific network ensembles S Cardanobile, V Pernice, M Deger, S Rotter PLoS One 7 (6), e37911, 2012 | 8 | 2012 |
Diffusion systems and heat equations on networks S Cardanobile arXiv preprint arXiv:0807.2362, 2008 | 8 | 2008 |
The L2-strong maximum principle on arbitrary countable networks S Cardanobile Linear algebra and its applications 435 (6), 1315-1325, 2011 | 5 | 2011 |
Toward a gauge theory for evolution equations on vector-valued spaces S Cardanobile, D Mugnolo Journal of mathematical physics 50 (10), 2009 | 5 | 2009 |