Volker Steuber
Volker Steuber
Professor of Computational Neuroscience, University of Hertfordshire
Verified email at - Homepage
Cited by
Cited by
Synaptic depression enables neuronal gain control
JS Rothman, L Cathala, V Steuber, RA Silver
Nature 457 (7232), 1015-1018, 2009
neuroConstruct: a tool for modeling networks of neurons in 3D space
P Gleeson, V Steuber, RA Silver
Neuron 54 (2), 219-235, 2007
Cerebellar LTD and pattern recognition by Purkinje cells
V Steuber, W Mittmann, FE Hoebeek, RA Silver, CI De Zeeuw, M Häusser, ...
Neuron 54 (1), 121-136, 2007
Structural features of a close homologue of L1 (CHL1) in the mouse: a new member of the L1 family of neural recognition molecules
J Holm, R Hillenbrand, V Steuber, U Bartsch, M Moos, H Lübbert, ...
European Journal of Neuroscience 8 (8), 1613-1629, 1996
Cerebellar output controls generalized spike‐and‐wave discharge occurrence
L Kros, OHJ Eelkman Rooda, JK Spanke, P Alva, MN van Dongen, ...
Annals of neurology 77 (6), 1027-1049, 2015
Patterns and pauses in Purkinje cell simple spike trains: experiments, modeling and theory
E De Schutter, V Steuber
Neuroscience 162 (3), 816-826, 2009
Determinants of synaptic integration and heterogeneity in rebound firing explored with data-driven models of deep cerebellar nucleus cells
V Steuber, NW Schultheiss, RA Silver, E De Schutter, D Jaeger
Journal of computational neuroscience 30, 633-658, 2011
Distinctive role of KV1. 1 subunit in the biology and functions of low threshold K+ channels with implications for neurological disease
SV Ovsepian, M LeBerre, V Steuber, VB O'Leary, C Leibold, JO Dolly
Pharmacology & therapeutics 159, 93-101, 2016
A biophysical model of synaptic delay learning and temporal pattern recognition in a cerebellar Purkinje cell
V Steuber, D Willshaw
Journal of computational neuroscience 17, 149-164, 2004
Modeling the generation of output by the cerebellar nuclei
V Steuber, D Jaeger
Neural Networks 47, 112-119, 2013
STD-dependent and independent encoding of input irregularity as spike rate in a computational model of a cerebellar nucleus neuron
J Luthman, FE Hoebeek, R Maex, N Davey, R Adams, CI De Zeeuw, ...
The Cerebellum 10, 667-682, 2011
The Open Source Brain Initiative: enabling collaborative modelling in computational neuroscience
P Gleeson, E Piasini, S Crook, R Cannon, V Steuber, D Jaeger, S Solinas, ...
BMC neuroscience 13, 1-2, 2012
Passive models of neurons in the deep cerebellar nuclei: the effect of reconstruction errors
V Steuber, E De Schutter, D Jaeger
Neurocomputing 58, 563-568, 2004
A defined heteromeric KV1 channel stabilizes the intrinsic pacemaking and regulates the output of deep cerebellar nuclear neurons to thalamic targets
SV Ovsepian, V Steuber, M Le Berre, L O’Hara, VB O’Leary, JO Dolly
The Journal of physiology 591 (7), 1771-1791, 2013
Adaptive leaky integrator models of cerebellar Purkinje cells can learn the clustering of temporal patterns
V Steuber, DJ Willshaw
Neurocomputing 26, 271-276, 1999
The role of parvalbumin-positive interneurons in auditory steady-state response deficits in schizophrenia
C Metzner, B Zurowski, V Steuber
Scientific reports 9 (1), 18525, 2019
Creating, documenting and sharing network models
SM Crook, JA Bednar, S Berger, R Cannon, AP Davison, M Djurfeldt, ...
Network: Computation in Neural Systems 23 (4), 131-149, 2012
Long-term depression and recognition of parallel fibre patterns in a multi-compartmental model of a cerebellar Purkinje cell
V Steuber, E De Schutter
Neurocomputing 38, 383-388, 2001
25th annual computational neuroscience meeting: CNS-2016
TO Sharpee, A Destexhe, M Kawato, V Sekulić, FK Skinner, DK Wójcik, ...
BMC neuroscience 17, 1-112, 2016
Dendritic morphology predicts pattern recognition performance in multi-compartmental model neurons with and without active conductances
G De Sousa, R Maex, R Adams, N Davey, V Steuber
Journal of computational neuroscience 38, 221-234, 2015
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