Tim Vogels

Affiliations: 
University of Oxford, Oxford, United Kingdom 
Area:
Computational neuroscience
Website:
http://www.cncb.ox.ac.uk/team/group-leaders/vogels/
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"Tim Vogels"
Mean distance: 12.74 (cluster 6)
 
SNBCP
Cross-listing: Computational Biology Tree

Parents

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Larry F. Abbott grad student 2001-2007 Brandeis
Rafael Yuste post-doc 2007-2010 Columbia
Wulfram Gerstner post-doc 2010-2013 EPFL

Children

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Panagiotis Bozelos research assistant 2017- Oxford
Jake Patrick Stroud grad student Oxford
William F. Podlaski grad student 2014- Oxford
Yayoi Teramoto grad student 2015-
Homero Barrocas Soares Esmeraldo grad student 2017- Oxford
Richard Lonsdale post-doc
Chaitanya Chintaluri post-doc 2017- Oxford
Friedemann Zenke post-doc 2017-
Douglas Feitosa Tomé post-doc 2022- Institute of Science and Technology Austria
Rui Ponte Costa post-doc 2014-2017 Oxford
Everton J Agnes post-doc 2015-2020 Oxford

Collaborators

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Alexander Seeholzer collaborator 2014-2017
BETA: Related publications

Publications

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Agnes EJ, Vogels TP. (2024) Co-dependent excitatory and inhibitory plasticity accounts for quick, stable and long-lasting memories in biological networks. Nature Neuroscience
Chintaluri C, Vogels TP. (2023) Metabolically regulated spiking could serve neuronal energy homeostasis and protect from reactive oxygen species. Proceedings of the National Academy of Sciences of the United States of America. 120: e2306525120
Jia DW, Vogels TP, Costa RP. (2022) Developmental depression-to-facilitation shift controls excitation-inhibition balance. Communications Biology. 5: 873
Christodoulou G, Vogels TP, Agnes EJ. (2022) Regimes and mechanisms of transient amplification in abstract and biological neural networks. Plos Computational Biology. 18: e1010365
Zenke F, Vogels TP. (2021) The Remarkable Robustness of Surrogate Gradient Learning for Instilling Complex Function in Spiking Neural Networks. Neural Computation. 1-27
Agnes EJ, Luppi AI, Vogels TP. (2020) Complementary inhibitory weight profiles emerge from plasticity and allow flexible switching of receptive fields. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience
Gonçalves PJ, Lueckmann JM, Deistler M, et al. (2020) Training deep neural density estimators to identify mechanistic models of neural dynamics. Elife. 9
Stroud JP, Porter MA, Hennequin G, et al. (2018) Publisher Correction: Motor primitives in space and time via targeted gain modulation in cortical networks. Nature Neuroscience
Stroud JP, Porter MA, Hennequin G, et al. (2018) Motor primitives in space and time via targeted gain modulation in cortical networks. Nature Neuroscience. 21: 1774-1783
Stroud JP, Vogels TP. (2018) Cortical Signal Propagation: Balance, Amplify, Transmit. Neuron. 98: 8-9
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