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Erik De Schutter
Person information
- affiliation: Okinawa Institute of Science / Technology Graduate University, Okinawa, Japan
- affiliation (former): University of Antwerp, Belgium
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2020 – today
- 2023
- [j70]Erik De Schutter
:
Efficient simulation of neural development using shared memory parallelization. Frontiers Neuroinformatics 17 (2023) - [j69]Mizuki Kato
Models of Purkinje cell dendritic tree selection during early cerebellar development. PLoS Comput. Biol. 19(7) (2023) - 2022
- [j68]Weiliang Chen, Tristan Carel, Omar Awile, Nicola Cantarutti, Giacomo Castiglioni, Alessandro Cattabiani, Baudouin Del Marmol, Iain Hepburn
STEPS 4.0: Fast and memory-efficient molecular simulations of neurons at the nanoscale. Frontiers Neuroinformatics 16 (2022) - [j67]Sergio Oscar Verduzco-Flores
A differential Hebbian framework for biologically-plausible motor control. Neural Networks 150: 237-258 (2022) - 2021
- [j66]Giorgio A. Ascoli
Farewell, Neuroinformatics! Neuroinformatics 19(4): 551-552 (2021) - [c2]Audrey Denizot
Stochastic Spatially-Extended Simulations Predict the Effect of ER Distribution on Astrocytic Microdomain Ca2+ Activity. NANOCOM 2021: 20:1-20:5 - 2020
- [j65]Ines Wichert, Sanghun Jee, Erik De Schutter
Pycabnn: Efficient and Extensible Software to Construct an Anatomical Basis for a Physiologically Realistic Neural Network Model. Frontiers Neuroinformatics 14: 31 (2020) - [c1]Dongqi Han, Erik De Schutter, Sungho Hong:
Lamina-specific neuronal properties promote robust, stable signal propagation in feedforward networks. NeurIPS 2020 - [i3]Dongqi Han, Erik De Schutter, Sungho Hong:
Lamina-specific neuronal properties promote robust, stable signal propagation in feedforward networks. CoRR abs/2010.12127 (2020)
2010 – 2019
- 2019
- [j64]Sergio Oscar Verduzco-Flores
Draculab: A Python Simulator for Firing Rate Neural Networks With Delayed Adaptive Connections. Frontiers Neuroinformatics 13: 18 (2019) - [j63]Erik De Schutter
Fallacies of Mice Experiments. Neuroinformatics 17(2): 181-183 (2019) - [j62]Shyam Kumar Sudhakar
Correction: Spatiotemporal network coding of physiological mossy fiber inputs by the cerebellar granular layer. PLoS Comput. Biol. 15(10) (2019) - 2018
- [j61]Erik De Schutter
Deep Learning and Computational Neuroscience. Neuroinformatics 16(1): 1-2 (2018) - 2017
- [j60]Weiliang Chen
Parallel STEPS: Large Scale Stochastic Spatial Reaction-Diffusion Simulation with High Performance Computers. Frontiers Neuroinformatics 11: 13 (2017) - [j59]Weiliang Chen
Time to Bring Single Neuron Modeling into 3D. Neuroinformatics 15(1): 1-3 (2017) - [j58]Shyam Kumar Sudhakar
Spatiotemporal network coding of physiological mossy fiber inputs by the cerebellar granular layer. PLoS Comput. Biol. 13(9) (2017) - 2016
- [j57]Erik De Schutter
Neuroinformatics for Degenerate Brains. Neuroinformatics 14(1): 1-3 (2016) - [i2]Weiliang Chen, Erik De Schutter:
Parallel STEPS: Large Scale Stochastic Spatial Reaction-Diffusion Simulation with High Performance Computers. CoRR abs/1610.02258 (2016) - 2015
- [j56]Erik De Schutter
The Missing Piece of the Puzzle: Neuroinformatics at the Bench. Neuroinformatics 13(2): 131-132 (2015) - [j55]João Couto
On the Firing Rate Dependency of the Phase Response Curve of Rat Purkinje Neurons In Vitro. PLoS Comput. Biol. 11(3) (2015) - [j54]Shyam Kumar Sudhakar
Cerebellar Nuclear Neurons Use Time and Rate Coding to Transmit Purkinje Neuron Pauses. PLoS Comput. Biol. 11(12) (2015) - [i1]Iain Hepburn, Weiliang Chen, Erik De Schutter:
Accurate Reaction-Diffusion Operator Splitting on Tetrahedral Meshes for Parallel Stochastic Molecular Simulations. CoRR abs/1512.03126 (2015) - 2014
- [j53]Weiliang Chen
Python-based geometry preparation and simulation visualization toolkits for STEPS. Frontiers Neuroinformatics 8: 37 (2014) - [j52]Cory M. Simon
The role of dendritic spine morphology in the compartmentalization and delivery of surface receptors. J. Comput. Neurosci. 36(3): 483-497 (2014) - [j51]Erik De Schutter
The Dangers of Plug-and-Play Simulation Using Shared Models. Neuroinformatics 12(2): 227-228 (2014) - 2013
- [j50]Iain Hepburn
Efficient calculation of the quasi-static electrical potential on a tetrahedral mesh and its implementation in STEPS. Frontiers Comput. Neurosci. 7: 129 (2013) - [j49]Erik De Schutter
Collaborative Modeling in Neuroscience: Time to Go Open Model? Neuroinformatics 11(2): 135-136 (2013) - [j48]Erik De Schutter
The importance of stochastic signaling processes in the induction of long-term synaptic plasticity. Neural Networks 47: 3-10 (2013) - 2012
- [j47]Iain Hepburn
STEPS: efficient simulation of stochastic reaction-diffusion models in realistic morphologies. BMC Syst. Biol. 6: 36 (2012) - [j46]Ivan Raikov, Erik De Schutter
The Promise and Shortcomings of XML as an Interchange Format for Computational Models of Biology. Neuroinformatics 10(1): 1-3 (2012) - [j45]Erik De Schutter
Ten Years of Neuroinformatics. Neuroinformatics 10(4): 329-330 (2012) - [j44]Yihwa Kim, Robert Sinclair
Geometric Theory Predicts Bifurcations in Minimal Wiring Cost Trees in Biology Are Flat. PLoS Comput. Biol. 8(4) (2012) - [j43]Ivan Raikov, Erik De Schutter
The Layer-Oriented Approach to Declarative Languages for Biological Modeling. PLoS Comput. Biol. 8(5) (2012) - 2011
- [j42]Volker Steuber
Determinants of synaptic integration and heterogeneity in rebound firing explored with data-driven models of deep cerebellar nucleus cells. J. Comput. Neurosci. 30(3): 633-658 (2011) - [j41]David N. Kennedy, Giorgio A. Ascoli, Erik De Schutter
Next Steps in Data Publishing. Neuroinformatics 9(4): 317-320 (2011) - 2010
- [j40]Erik De Schutter
Data Publishing and Scientific Journals: The Future of the Scientific Paper in a World of Shared Data. Neuroinformatics 8(3): 151-153 (2010)
2000 – 2009
- 2009
- [j39]Stefan Wils, Erik De Schutter:
STEPS: modeling and simulating complex reaction-diffusion systems with Python. Frontiers Neuroinformatics 3: 15 (2009) - [j38]Erik De Schutter
The International Neuroinformatics Coordinating Facility: Evaluating the First Years. Neuroinformatics 7(3): 161-163 (2009) - [j37]Erik De Schutter, Giorgio A. Ascoli, David N. Kennedy:
Review of Papers Describing Neuroinformatics Software. Neuroinformatics 7(4): 211-212 (2009) - 2008
- [j36]Werner Van Geit, Erik De Schutter
Automated neuron model optimization techniques: a review. Biol. Cybern. 99(4-5): 241-251 (2008) - [j35]Pablo Achard, Erik De Schutter
Calcium, synaptic plasticity and intrinsic homeostasis in Purkinje neuron models. Frontiers Comput. Neurosci. 2: 8 (2008) - [j34]Erik De Schutter:
Reviewing Multi-Disciplinary Papers: a Challenge in Neuroscience? Neuroinformatics 6(4): 253-255 (2008) - [j33]Erik De Schutter
Why Are Computational Neuroscience and Systems Biology So Separate? PLoS Comput. Biol. 4(5) (2008) - 2007
- [j32]Werner Van Geit
Neurofitter: a parameter tuning package for a wide range of electrophysiological neuron models. Frontiers Neuroinformatics 1: 1 (2007) - [j31]Hugo Cornelis, Erik De Schutter:
Neurospaces: Towards automated model partitioning for parallel computers. Neurocomputing 70(10-12): 2117-2121 (2007) - [j30]Erik De Schutter
A second look back. Neuroinformatics 5(1): 1-2 (2007) - [j29]Robert C. Cannon, Marc-Oliver Gewaltig, Padraig Gleeson
Interoperability of Neuroscience Modeling Software: Current Status and Future Directions. Neuroinformatics 5(2): 127-138 (2007) - [j28]Erik De Schutter
Neuroscience Leading the Way: Reviews Cascade by the INCF. Neuroinformatics 5(4): 205-206 (2007) - 2006
- [j27]Erik De Schutter
On the future of the human brain project. Neuroinformatics 4(2): 129-130 (2006) - [j26]Pablo Achard, Erik De Schutter
Complex Parameter Landscape for a Complex Neuron Model. PLoS Comput. Biol. 2(7) (2006) - [j25]Ulrich G. Hofmann
A Novel High Channel-Count System for Acute Multisite Neuronal Recordings. IEEE Trans. Biomed. Eng. 53(8): 1672-1677 (2006) - 2005
- [j24]Erik De Schutter:
Computational Neuroscience: Trends in Research 2005. Neurocomputing 65-66: 1-3 (2005) - [j23]Michiel Berends, Reinoud Maex
The Effect of NMDA Receptors on Gain Modulation. Neural Comput. 17(12): 2531-2547 (2005) - [j22]Erik De Schutter:
Changes and opportunities. Neuroinformatics 3(2): 79-80 (2005) - 2004
- [j21]Volker Steuber
Passive models of neurons in the deep cerebellar nuclei: the effect of reconstruction errors. Neurocomputing 58-60: 563-568 (2004) - [j20]Michiel Berends, Reinoud Maex
A detailed three-dimensional model of the cerebellar granular layer. Neurocomputing 58-60: 587-592 (2004) - [j19]Hugo Cornelis, Erik De Schutter:
Neurospaces parameter handling. Neurocomputing 58-60: 1079-1084 (2004) - [j18]Erik De Schutter:
Computational Neuroscience: Trends in research 2004. Neurocomputing 58-60 (2004) - [j17]Erik De Schutter:
A look back. Neuroinformatics 2(1): 1-2 (2004) - 2003
- [j16]Sergio Solinas
Synchronization of Purkinje cell pairs along the parallel fiber axis: a model. Neurocomputing 52-54: 97-102 (2003) - [j15]Hugo Cornelis, Erik De Schutter:
NeuroSpaces: separating modeling and simulation. Neurocomputing 52-54: 227-231 (2003) - [j14]Dionyssios Theofilou, Volker Steuber
Novelty detection in a Kohonen-like network with a long-term depression learning rule. Neurocomputing 52-54: 411-417 (2003) - [j13]Kristl G. Claeys
Involvement of multiple functionally distinct cerebellar regions in visual discrimination: a human functional imaging study. NeuroImage 20(2): 840-854 (2003) - [j12]Giorgio A. Ascoli, Erik De Schutter
An information science infrastructure for neuroscience. Neuroinformatics 1(1): 1-2 (2003) - [j11]Peter Eckersley, Gary F. Egan, Erik De Schutter
Neuroscience data and tool sharing - A legal and policy framework for neuroinformatics. Neuroinformatics 1(2): 149-165 (2003) - 2002
- [j10]Volker Steuber
Rank order decoding of temporal parallel fibre input patterns in a complex Purkinje cell model. Neurocomputing 44-46: 183-188 (2002) - [j9]Nigel H. Goddard, David Beeman, Robert C. Cannon, Hugo Cornelis, Marc-Oliver Gewaltig, Greg Hood, Fredrick W. Howell, P. Rogister, Erik De Schutter, K. Shankar, Michael Hucka
NeuroML for plug and play neuronal modeling. Neurocomputing 44-46: 1077-1081 (2002) - [j8]Fidel Santamaría
Modulatory Effects of Parallel Fiber and Molecular Layer Interneuron Synaptic Activity on Purkinje Cell Responses to Ascending Segment Input: A Modeling Study. J. Comput. Neurosci. 13(3): 217-235 (2002) - 2001
- [j7]Volker Steuber
Long-term depression and recognition of parallel fibre patterns in a multi-compartmental model of a cerebellar Purkinje cell. Neurocomputing 38-40: 383-388 (2001) - [j6]Paul Franck, Reinoud Maex
Synchronization between patches of local excitation in a cerebellar granular layer model. Neurocomputing 38-40: 595-599 (2001) - [j5]Nigel H. Goddard, Greg Hood, Fredrick W. Howell, Michael L. Hines, Erik De Schutter:
NEOSIM: Portable large-scale plug and play modelling. Neurocomputing 38-40: 1657-1661 (2001) - 2000
- [j4]Fredrick W. Howell, Jonas Dyhrfjeld-Johnsen, Reinoud Maex
A large-scale model of the cerebellar cortex using PGENESIS. Neurocomputing 32-33: 1041-1046 (2000)
1990 – 1999
- 1995
- [j3]Farzan Nadim
Modeling the leech heartbeat elemental oscillator I. Interactions of intrinsic and synaptic currents. J. Comput. Neurosci. 2(3): 215-235 (1995) - 1994
- [j2]C. Staub, Erik De Schutter, Thomas Knöpfel
Voltage-imaging and simulation of effects of voltage- and agonist-activated conductances on soma-dendritic voltage coupling in cerebellar Purkinje cells. J. Comput. Neurosci. 1(4): 301-311 (1994) - 1993
- [j1]Erik De Schutter, James M. Bower:
Sensitivity of Synaptic Plasticity to the Ca2+ Permeability of NMDA Channels: A Model of Long-Term Potentiation in Hippocampal Neurons. Neural Comput. 5(5): 681-694 (1993)
Coauthor Index
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