Michelle Rudolph
Affiliations: | UNIC, CNRS, Gif-sur-Yvette, Île-de-France, France |
Area:
cortexGoogle:
"Michelle Rudolph"Mean distance: 14.2 (cluster 17) | S | N | B | C | P |
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Publications
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Renaud S, Tomas J, Lewis N, et al. (2010) PAX: A mixed hardware/software simulation platform for spiking neural networks. Neural Networks : the Official Journal of the International Neural Network Society. 23: 905-16 |
Cagnan H, Meijer HG, van Gils SA, et al. (2009) Frequency-selectivity of a thalamocortical relay neuron during Parkinson's disease and deep brain stimulation: a computational study. The European Journal of Neuroscience. 30: 1306-17 |
Daouzli A, Saïghi S, Rudolph M, et al. (2009) Convergence in an adaptive neural network: The influence of noise inputs correlation Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5517: 140-148 |
Brette R, Rudolph M, Carnevale T, et al. (2007) Simulation of networks of spiking neurons: a review of tools and strategies. Journal of Computational Neuroscience. 23: 349-98 |
Rudolph M, Pospischil M, Timofeev I, et al. (2007) Inhibition determines membrane potential dynamics and controls action potential generation in awake and sleeping cat cortex. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 27: 5280-90 |
Destexhe A, Hughes SW, Rudolph M, et al. (2007) Are corticothalamic 'up' states fragments of wakefulness? Trends in Neurosciences. 30: 334-42 |
Pospischil M, Piwkowska Z, Rudolph M, et al. (2007) Calculating event-triggered average synaptic conductances from the membrane potential. Journal of Neurophysiology. 97: 2544-52 |
Rudolph M, Destexhe A. (2007) How much can we trust neural simulation strategies? Neurocomputing. 70: 1966-1969 |
Pospischil M, Piwkowska Z, Rudolph M, et al. (2007) Inhibitory conductance dynamics in cortical neurons during activated states Neurocomputing. 70: 1602-1604 |
Brette R, Piwkowska Z, Rudolph M, et al. (2007) A non-parametric electrode model for intracellular recording Neurocomputing. 70: 1597-1601 |