Publications

2019

E. De Schutter: Fallacies of Mice Experiments. Neuroinformatics 17: 181-183.
N. Vrieler, S. Loyola, Y. Yarden-Rabinowitz, J. Hoogendorp, N. Medvedev, T.M. Hoogland, C.I. De Zeeuw, E. De Schutter, Y. Yarom, M. Negrello, B. Torben-Nielsen, and M.Y. Uusisaari: Variability and directionality of inferior olive neuron dendrites revealed by detailed 3D characterization of an extensive morphological library. Brain Structure and Function: 224: 1677–1695.
S.O. Verduzco Flores and E. De Schutter: Draculab: A Python simulator for firing rate neural networks with delayed adaptive connections. Frontiers in Neuroinformatics 13:18. 

2018

C.G. Zamora Chimal and E. De Schutter: Ca2+ requirements for Long-Term Depression are frequency sensitive in Purkinje Cells. Frontiers in Molecular Neuroscience 11: 438. 
Y. Zang, S. Dieudonné and E. De Schutter: Voltage- and Branch-specific Climbing Fiber Responses in Purkinje Cells. Cell Reports 24: 1536–1549. 
J. Myung*, C. Schmal*, S. Hong*, Y. Tsukizawa, P. Rose, Y. Zhang, M. Holtzman, E. De Schutter, H. Herzel, G. Bordyugov and T. Takumi: The Choroid Plexus is an Important Circadian Clock Component. Nature Communications 9: 1062. 
A.R. Gallimore, T. Kim, K. Tanaka-Yamamoto and E. De Schutter: Switching on depression and potentiation in the cerebellum. Cell Reports 22: 722-733. 
E. De Schutter: Deep learning and computational neuroscience. Neuroinformatics 16: 1-2.
S. Nanda, H. Chen, R. Das, S. Bhattacharjee, H. Cuntz, B. Torben-Nielsen, H. Peng, D. Cox, E. De Schutter, and G. Ascoli: Design and implementation of multi-signal and time-varying neural reconstructions. Scientific Data​ 5:170207.

2017

J. Myung and S.D. Pauls: Encoding seasonal information in a two-oscillator model of the multi-oscillator circadian clock. European Journal of Neuroscience​ 48: 2718-2727 (2018).
S.K. Sudhakar*, S. Hong*, I. Raikov, R. Publio, C. Lang, T. Close, D. Guo, M. Negrello and E. De Schutter: Spatiotemporal network coding of physiological mossy fiber inputs by the cerebellar granular layer. PLoS Computational Biology 13: e1005754. 
C. Schmal, J. Myung, H. Herzel and G. Bordyugov: Using Moran’s I to analyze spatio-temporal pattern formation in neural imaging data. Bioinformatics 33:3072-3079.
W. Chen and E. De Schutter: Parallel STEPS: Large Scale Stochastic Spatial Reaction-Diffusion Simulation with High Performance Computers. Frontiers in Neuroinformatics 11: 13.  
I. Hepburn, A. Jain, H. Gangal, Y. Yamamoto, K. Tanaka-Yamamoto and E. De Schutter: A model of induction of cerebellar Long-Term Depression including RKIP inactivation of Raf and MEK. Frontiers in Molecular Neuroscience 10: 19. 
W. Chen and E. De Schutter: Time to bring single neuron modeling into 3D. Neuroinformatics 15: 1-3.

2016

I. Hepburn, W. Chen and E. De Schutter: Accurate reaction-diffusion operator splitting on tetrahedral meshes for parallel stochastic molecular simulations. Journal of Chemical Physics 145: 054118. 
A.R. Gallimore and R.J. Strassman: A model for the application of target-controlled intravenous infusion for a prolonged immersive DMT psychedelic experience. Frontiers in Pharmacology 7: 211.
S. Hong, M. Negrello, M. Junker, A. Smilgin, P. Thier and E. De Schutter: Multiplexed coding by cerebellar Purkinje neurons. eLife 5: e13810.
M. Negrello and E. De Schutter: Models of the Cortico-cerebellar System. Neuroscience in the 21st Century, D.W. Pfaff and N.D. Volkow, editors, 24 p.
A.R. Gallimore, A.R. Aricescu, M. Yuzaki, R. Calinescu: A computational model for the AMPA receptor phosphorylation master switch regulating cerebellar long-term depression. PLoS Computational Biology 12: e1004664.
E. De Schutter: Neuroinformatics for degenerate brains. Neuroinformatics 14: 1-3.
 

2015

S.K. Sudhakar, B. Torben-Nielsen, E. De Schutter: Cerebellar nuclear neurons use time and rate coding to transmit Purkinje neuron pauses. PLoS Computational Biology 11: e1004641. 
S. Huang, S. Hong and E. De Schutter: Non-linear leak currents affect mammalian neuron physiology. Frontiers in Cellular Neuroscience 9:432. 
C. Yalgin, S. Ebrahimi,  C. Delandre, L. Foong Yoong, S. Akimoto, H. Tran, R. Amikura, R. Spokony, B. Torben-Nielsen, K.P. White & A.W. Moore: Centrosomin represses dendrite branching by orienting microtubule nucleation. Nature Neuroscience 18: 1437-1446.
W. Wybo, D. Boccalini, B. Torben-Nielsen and M-O. Gewaltig: A sparse reformulation of the Green's function formalism allows efficient simulations of morphological neuron models. Neural Computation 27: 2587-2622.
J. Myung, S. Hong, D. DeWoskin, E De Schutter, D.B. Forger and T. Takumi: GABA-mediated repulsive coupling between circadian clock neurons in the SCN encodes seasonal time. Proceedings of the National Academy of Sciences USA 112: E3920-3929.
A.R. Gallimore: Restructuring consciousness – the psychedelic state in light of integrated information theory. Frontiers in Human Neuroscience 9:346.
E. De Schutter: The Missing Piece of the Puzzle: Neuroinformatics at the Bench. Neuroinformatics 13: 131-132.
P. Warnaar, J. Couto, M. Negrello, M. Junker, A. Smilgin, A. Ignashchenkova, M. Giugliano, P. Thier and E. De Schutter: Duration of Purkinje cell complex spikes increases with their firing frequency. Frontiers in Cellular Neuroscience 9: 122.
J. Couto, D. Linaro, E. De Schutter and M. Giugliano: On the firing rate dependency of the phase response curve of rat Purkinje neurons in vitro. PLoS Computational Biology 11: e1004112. 
 

2014

M. Negrello: Valentino Braitenberg: From neuroanatomy to behavior and back. Biological Cybernetics 108: 527-539.
B. Torben-Nielsen and  E. De Schutter: Context-aware modeling of neuronal morphologies. Frontiers in Neuroanatomy 8: 92.  
J. Laudanski*, B. Torben-Nielsen*, I. Segev, S. Shamma: Spatially distributed dendritic resonance selectively filters synaptic input. PLoS Computational Biology 10: e1003775.
H. Anwar, C. Roome, H. Nedelescu, W. Chen, B. Kuhn and E. De Schutter: Dendritic diameters affect the spatial variability of intracellular calcium dynamics in computer models. Frontiers in Cellular Neuroscience 8: 168. 
B. Torben-Nielsen: An efficient and extendable Python library to analyze neuronal morphologies. Neuroinformatics 12:619-622. 
W. Chen and E. De Schutter: Python-based geometry preparation and simulation visualization toolkits for STEPS. Frontiers in Neuroinformatics 8: 37.  
E. De Schutter: The dangers of plug-and-play simulation using shared models. Neuroinformatics 12: 227-228.
 

2013

K. Veys, D. J. Snyders and E. De Schutter: Kv3.3b expression defines the shape of the complex spike in the Purkinje cell. Frontiers in Cellular Neuroscience 7: 205.
C. Simon, W. Chen, I. Hepburn and E. De Schutter: The role of dendritic spine morphology in the compartmentalization and delivery of surface receptors. Journal of Computational Neuroscience 36: 483-497.
I. Hepburn, R. Cannon and E. De Schutter: Efficient calculation of the quasi-static electrical potential on a tetrahedral mesh and its implementation in STEPS. Frontiers in Computational Neuroscience 7: 129. 
H. Anwar*,  I. Hepburn*, H. Nedelescu, W. Chen and E. De Schutter: Stochastic calcium mechanisms cause dendritic calcium spike variability. Journal of Neuroscience 33: 15848-15867. 
S. Ratté, S. Hong, E. De Schutter and S.A. Prescott: Impact of neuronal properties on network coding: Roles of spike initiation dynamics and robust synchrony transfer. Neuron 78: 758-772.
S. Huang and M.Y. Uusisaari: Physiological temperature during brain slicing enhances the quality of acute slice preparations. Frontiers in Cellular Neuroscience 7: 48.
E. De Schutter: Collaborative modeling in neuroscience: time to go open model? Neuroinformatics 11: 135-136.
E. De Schutter: The importance of stochastic signaling processes in the induction of long-term synaptic plasticity. Neural Networks 47: 3-10.
M.R. Diaz, A. Wadleigh, S. Kumar, E. De Schutter and C.F. Valenzuela: Na+/K+-ATPase inhibition partially mimics the ethanol-induced increase of the Golgi cell-dependent component of the tonic GABAergic current in rat cerebellar granule cells. PLoS One 8:e55673.

2012

E. De Schutter, G.A. Ascoli and D.N. Kennedy: Ten years of Neuroinformatics. Neuroinformatics 10: 329-330.  
S. Hong, Q. Robberechts, E. De Schutter: Efficient estimation of phase response curves via compressive sensing. Journal of Neurophysiology 108: 2069-2081.
K. Veys, A. J. Labro, E. De Schutter* and D. J. Snyders*: Quantitative single-cell ion-channel gene expression profiling through an improved qRT-PCR technique combined with whole cell patch clamp. Journal of Neuroscience Methods 209: 227–234. 
M. Uzuntarla, M. Ozer and D. Q. Guo: Controlling the first-spike latency response of a single neuron via unreliable synaptic transmission. European Physical Journal B 85: 282-289.
G. Antunes and E. De Schutter: A stochastic signaling network mediates the probabilistic induction of cerebellar long-term depression.  Journal of Neuroscience 32: 9288 –9300.  
J. Myung, S. Hong, F. Hatanaka, Y. Nakajima, E. De Schutter and T. Takumi: Period coding of Bmal1 oscillators in the suprachiasmatic nucleus. Journal of Neuroscience 32: 8900-8918.
I. Raikov and E. De Schutter: The layer-oriented approach to biological modeling languages. PLoS Computational Biology 8: e1002521. 
Y. Kim*, R. Sinclair*, N. Chindapol, J. A. Kaandorp and E. De Schutter: The geometry of dendritic trees: minimal wiring cost bifurcations are flat. PLoS Computational Biology 8: e1002474.
I. Hepburn, S. Wils, W. Chen and E. De Schutter: STEPS: Efficient simulation of stochastic reaction-diffusion models in realistic morphologies. BMC Systems Biology 6: 36. 
P. Botta, F. M. Simões de Souza, T. Sangrey, E. De Schutter and F. Valenzuela: Excitation of rat cerebellar Golgi cells by ethanol: Further characterization of the mechanism. Alcoholism: Clinical and Experimental Research 36: 616-624. 
I. Raikov and E. De Schutter: The promise and shortcomings of XML as an interchange format for computational models of biology. Neuroinformatics 10: 1-3.
D. Guo, Q. Wang and M. Perc: Complex synchronous behavior in interneuronal networks with delayed inhibitory and fast electrical synapses. Physical Review E 85: 061905.
S. Hong, S. Ratté, S. Prescott* and E. De Schutter*: Single neuron firing properties impact correlation-based population coding. Journal of Neuroscience 32:1413–1428.
 

2011

F. Santamaria, S. Wils, E. De Schutter and G. J. Augustine: The diffusional properties of dendrites depend on the density of dendritic spines. European Journal of Neuroscience 34: 561-568. Featured article
Y. Le Franc, M. Giugliano, and E. De Schutter, E. The Belgian node: a  community platform toward the future. Acta Neurologica Belgica 11.
K. Tahon, M. Wijnants and E. De Schutter: The RAT-ROTADRUM: a reaction time task depending on a continuous stream of tactile sensory information to the rat. Journal of Neuroscience Methods 200: 153-163.
D.N. Kennedy, G.A. Ascoli, E. De Schutter: Next steps in data publishing. Neuroinformatics 9: 317-320.
K. Pfeiffer, M. Negrello and U. Homberg: Conditional Perception Under Stimulus Ambiguity: Polarization- and Azimuth-Sensitive Neurons in the Locust Brain Are Inhibited by Low Degrees of Polarization. Journal of Neurophysiology 105: 28-35.
W. Chen, R. Maex, R. Adams, V. Steuber, L. Calcraft and N. Davey: Clustering predicts memory performance in networks of spiking and non-spiking neurons. Frontiers in Computational Neuroscience 5, 14.
M. Uusisaari and E. De Schutter: The mysterious microcircuitry of the cerebellar nuclei. Journal of Physiology (London) 589: 3441-3457.
V. Steuber, N. Schultheiss, A. Silver, E. De Schutter and D. Jaeger: Determinants of synaptic integration and heterogeneity in rebound firing explored with date-driven models of deep cerebellar nuclei cells. Journal of Computational Neuroscience 30: 633-658.  
K. Tahon, M. Wijnants, E. De Schutter and R. Maex: Current source density correlates of cerebellar Golgi and Purkinje cell responses to tactile input. Journal of Neurophysiology 105: 1327-1341.
F. M. Simões de Souza and E. De Schutter: Robustness effect of gap junctions between Golgi cells on cerebellar cortex oscillations. Neural Systems & Circuits 1: 7.  
 

2010

H. Anwar, S. Hong, E. De Schutter: Controlling Ca2+-activated K+ channels with models of Ca2+ buffering in Purkinje cells. Cerebellum 11: 681-693 (2012).  
Q. Robberechts, M. Wijnants, M. Giugliano, and E. De Schutter: Long-term depression at parallel fiber to Golgi cell synapses. Journal of Neurophysiology104: 3413–3423. 
E. De Schutter: Data publishing and scientific journals: the future of the scientific paper in a world of shared data. Neuroinformatics 8: 151-153.
P. Botta, F. M. Simões de Souza, T. Sangrey, E. De Schutter and F. Valenzuela: Alcohol excites cerebellar Golgi cells by inhibiting the Na+/K+-ATPase. Neuropsychopharmacology 35: 1984-1996. 
 

2009

E. De Schutter (editor): Computational Modeling Methods for Neuroscientists. MIT Press, Cambridge, MA, USA, 432 pages.
E. De Schutter, G.A. Ascoli and D.N. Kennedy: Review of papers describing neuroinformatics software. Neuroinformatics 7: 211–212.
E. De Schutter and V. Steuber: Patterns and pauses in Purkinje cell simple spike trains: experiments, modeling and theory. Neuroscience 162: 816-826.
R. Publio, R. F. Oliveira and A.C. Roque: A Computational Study on the Role of Gap Junctions and Rod I-h Conductance in the Enhancement of the Dynamic Range of the Retina. PLoS One 4: e6970.
S. Wils and E. De Schutter: STEPS: Modeling and simulating complex reaction-diffusion systems with Python. Frontiers in Neuroinformatics 3: 15. 
F. Gheysen, W. Gevers, E. De Schutter, H. Van Waelvelde and W. Fias: Disentangling perceptual from motor implicit sequence learning with a serial color matching task. Experimental Brain Research 197:163–174.
E. De Schutter: The International Neuroinformatics Coordinating Facility: Evaluating the first years. Neuroinformatics 7: 161–163.
 

2008

S. Hong and E. De Schutter: Purkinje Neurons: What is the signal for complex spikes? Current Biology 18: R969-R971.
E. De Schutter: Reviewing multi-disciplinary papers: a challenge in neuroscience? Neuroinformatics 6: 253–255.
P. Achard and E. De Schutter: Calcium, synaptic plasticity and intrinsic homeostasis in Purkinje neuron models. Frontiers in Computational Neuroscience 2:8.
W. Van Geit, E. De Schutter and P. Achard: Automated neuron model optimization techniques: a review. Biological Cybernetics 99:241–251.
E. De Schutter: Why are Computational neuroscience and Systems biology so separate? PLoS Computational Biology 4: e1000078.
 

2007

E. De Schutter: Neuroscience leading the way: reviews cascade by the INCF. Neuroinformatics 5: 205-206.
V. Steuber, W. Mittmann, F.E. Hoebeek, R.A. Silver, C.I. De Zeeuw, M. Häusser and E. De Schutter: Cerebellar LTD and pattern recognition by Purkinje cells. Neuron 54: 121–136. 
S. Solinas, L. Forti, E. Cesana, J. Mapelli and E. De Schutter, E. D’Angelo: Fast-reset of pacemaking and theta-frequency resonance patterns in cerebellar Golgi cells: Simulations of their impact in vivo. Frontiers in Cellular Neuroscience 1:4. 
S. Solinas, L. Forti, E. Cesana, J. Mapelli and E. De Schutter, E. D’Angelo: Computational reconstruction of pacemaking and intrinsic electroresponsiveness in cerebellar Golgi cells. Frontiers in Cellular Neuroscience 1: 2.  
S.-L. Shin, F.E. Hoebeek, M. Schonewille, C.I. De Zeeuw, A. Aertsen and E. De Schutter: Regular temporal patterns in cerebellar Purkinje cell simple spike trains. PLoS One 2: e485.
W. Van Geit, P. Achard and E. De Schutter: Neurofitter: a parameter tuning package for a wide range of electrophysiological neuron models. Frontiers in Neuroinformatics 1: 1. 
 
 

Note: this page lists only the Unit's publications in international journals, conference proceedings and books. We do not list abstracts or PhD theses. A complete list of Erik De Schutter's publications can be found at the University of Antwerp (with reprints) and at ResearcherID.
* these authors contributed equally to this work