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Browsing by Author "Silver, R.A."
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Cerebellar LTD and pattern recognition by Purkinje cells
Steuber, Volker; Mittmann, W.; Hoebeek, F.E.; Silver, R.A.; De Zeeuw, C.I.; Hausser, M.; De Schutter, E. (2007) -
Computational Intelligence in Electrophysiology: Trends and Open Problems
Gunay, C.; Smolinski, T.G.; Lytton, W.W.; Morse, T.M.; Gleeson, P.; Crook, S.; Steuber, Volker; Silver, R.A.; Voicu, H.; Andrews, P.; Bokil, H.; Maniar, H.; Loader, C.; Mehta, S.; Kleinfeld, D.; Thomson, D.; Mitra, P.P.; Aaron, G.; Fellous, J-M. (Springer Nature, 2008)This chapter constitutes mini-proceedings of the Workshop on Physiology Databases and Analysis Software that was a part of the Annual Computational Neuroscience Meeting CNS*2007 that took place in July 2007 in Toronto, ... -
Determinants of synaptic integration and heterogeneity in rebound firing explored with data-driven models of deep cerebellar nucleus cells
Steuber, Volker; Schultheiss, N.W.; Silver, R.A.; De Schutter, E.; Jaeger, D. (2011)Significant inroads have been made to understand cerebellar cortical processing but neural coding at the output stage of the cerebellum in the deep cerebellar nuclei (DCN) remains poorly understood. The DCN are unlikely ... -
neuroConstruct: a tool for modeling networks of neurons in 3D space
Gleeson, P.; Steuber, Volker; Silver, R.A. (2007) -
Synaptic depression enables neuronal gain control
Rothman, J.S.; Cathala, L.; Steuber, Volker; Silver, R.A. (2009)To act as computational devices, neurons must perform mathematical operations as they transform synaptic and modulatory input into output firing rate. Experiments and theory indicate that neuronal firing typically represents ... -
Using neuroConstruct to develop and modify biologically detailed 3D neuronal network models in health and disease
Gleeson, P.; Steuber, Volker; Silver, R.A. (Academic Press, 2008)In this chapter, we describe neuroConstruct, a new software tool for developing, modifying and analyzing neural network models with biologically realistic properties in 3D space (Gleeson et al, 2007). Network models are ...