Category: Spiking
Related organisations
Organisation for neuroscientists interested in spiking neural networks.
Related software
A Python simulator for spiking neural networks.
Spike sorting.
Related videos
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Brain Inspired interviewInterview / 2024
Dan Goodman interview on Brain Inspired podcast -
Multimodal units fuse-then-accumulate evidence across channelsTalk / 2023
Talk on multimodal processing given at VVTNS 2023 seminar series -
Cosyne tutorial on spiking neural networks (2/2)Tutorial / 2022
Part 2 - (Machine) learning with SNNs -
Cosyne tutorial on spiking neural networks (1/2)Tutorial / 2022
Part 1 - "Classical" SNNs -
Understanding the role of neural heterogeneity in learningTalk / 2021
Talk on neural heterogeneity by Nicolas Perez. -
Neural heterogeneity promotes robust learningTalk / 2021
Talk on neural heterogeneity by Dan Goodman.
Related publications
2024
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Ghosh M, et al.
Spiking neural network models of sound localisation via a massively collaborative process.
Preprint -
Ghosh M, Béna G, Bormuth V, Goodman DFM (2024)
Nonlinear fusion is optimal for a wide class of multisensory tasks.
PLoS Computational Biology -
Habashy KG, Evans BD, Goodman DFM, Bowers JS
Adapting to time: why nature evolved a diverse set of neurons.
Preprint
2023
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Perez N (2023)
Robust and efficient training on deep spiking neural networks.
PhD thesis, Imperial College London
2022
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Goodman D, Fiers T, Gao R, Ghosh M, Perez N (2022)
Spiking Neural Network Models in Neuroscience - Cosyne Tutorial 2022.
Zenodo
2021
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Perez-Nieves N, Goodman DFM (2021)
Sparse spiking gradient descent.
Advances in Neural Information Processing Systems -
Perez-Nieves N, Leung VCH, Dragotti PL, Goodman DFM (2021)
Neural heterogeneity promotes robust learning.
Nature Communications -
Zenke F, et al. (2021)
Visualizing a joint future of neuroscience and neuromorphic engineering.
Neuron
2020
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Stimberg M, Goodman DFM, Nowotny T (2020)
Brian2GeNN: a system for accelerating a large variety of spiking neural networks with graphics hardware.
Scientific Reports -
Hathway P (2020)
Biologically-inspired machine learning approaches to large-scale neural data analysis.
PhD thesis, Imperial College London
2019
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Stimberg M, Goodman DFM, Brette R, De Pittà M (2019)
Modeling neuron-glia interactions with the Brian 2 simulator.
Springer -
Stimberg M, Brette R, Goodman DFM (2019)
Brian 2, an intuitive and efficient neural simulator.
eLife -
Perez-Nieves N, Leung VCH, Dragotti PL, Goodman DFM (2019)
Advantages of heterogeneity of parameters in spiking neural network training.
Cognitive Computational Neuroscience - + 1 conference paper
2018
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Blundell I, et al. (2018)
Code Generation in Computational Neuroscience: A Review of Tools and Techniques.
Frontiers in Neuroinformatics -
Goodman DFM, Winter IM, Léger AC, de Cheveigné A, Lorenzi C (2018)
Modelling firing regularity in the ventral cochlear nucleus: mechanisms, and effects of stimulus level and synaptopathy.
Hearing Research
2016
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Rossant C, et al. (2016)
Spike sorting for large, dense electrode arrays.
Nature Neuroscience
2014
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Stimberg M, Goodman DFM, Benichoux V, Brette R (2014)
Equation-oriented specification of neural models for simulations.
Frontiers in Neuroinformatics -
Kadir SN, Goodman DFM, Harris KD (2014)
High-dimensional cluster analysis with the masked EM algorithm.
Neural Computation
2013
2012
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Brette R, Goodman DFM (2012)
Simulating spiking neural networks on GPU.
Network: Computation in Neural Systems
2011
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Fontaine B, Goodman DFM, Benichoux V, Brette R (2011)
Brian Hears: online auditory processing using vectorisation over channels.
Frontiers in Neuroinformatics -
Rossant C, Goodman DFM, Fontaine B, Platkiewicz J, Magnusson AK, Brette R (2011)
Fitting neuron models to spike trains.
Frontiers in Neuroscience -
Kremer Y, Léger J-F, Goodman D, Brette R, Bourdieu L (2011)
Late emergence of the vibrissa direction selectivity map in the rat barrel cortex.
Journal of Neuroscience -
Brette R, Goodman DFM (2011)
Vectorised algorithms for spiking neural network simulation.
Neural Computation
2010
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Goodman DFM, Brette R (2010)
Learning to localise sounds with spiking neural networks.
Advances in Neural Information Processing Systems -
Rossant C, Goodman DFM, Platkiewicz J, Brette R (2010)
Automatic fitting of spiking neuron models to electrophysiological recordings.
Frontiers in Neuroinformatics -
Goodman DFM, Brette R (2010)
Spike-timing-based computation in sound localization.
PLoS Computational Biology
2009
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Brette R, Goodman D (2009)
Brian: a simple and flexible simulator for spiking neural networks.
The Neuromorphic Engineer