Spiking

  1. Learning to play with spikes: characterizing, predicting, and engineering unsupervised plasticity rules for spiking reservoir computing

    Kania, Confavreux, Vogels (2026). bioRxiv:2026.09.15.751573v1. DOI

  2. Proposal: Simulating Neuromorphic Toolbox nodes with snnlab

    No public source link available.

    Diegobro (2026). Proposal.

  3. Memory by a thousand rules: Automated discovery of multi-type plasticity rules reveals variety & degeneracy at the heart of learning

    Confavreux, Harrington, Kania, Ramesh, Krouglova, Bozelos, Macke, Saxe, Gonçalves, Vogels (2025). bioRxiv:2025.05.28.656584v2. DOI

  4. Bursting gamma oscillations in neural mass models

    Nandi, Valla, di Volo (2024). Frontiers in Computational Neuroscience. DOI

  5. Training Spiking Neural Networks Using Lessons From Deep Learning

    Eshraghian, Ward, Neftci, Wang, Lenz, Dwivedi, Bennamoun, Jeong, Lu (2023). arXiv:2109.12894v6.

  6. Neocortex saves energy by reducing coding precision during food scarcity

    Padamsey, Katsanevaki, Dupuy, Rochefort (2022). Neuron. DOI

  7. Integration, coincidence detection and resonance in networks of spiking neurons expressing Gamma oscillations and asynchronous states

    Susin, Destexhe (2021). PLOS Computational Biology. DOI

  8. A quantitative theory of gamma synchronization in macaque V1

    Lowet, Roberts, Peter, Gips, De Weerd (2017). eLife. DOI

  9. Phase Difference between Model Cortical Areas Determines Level of Information Transfer

    ter Wal, Tiesinga (2017). Frontiers in Computational Neuroscience. DOI

  10. Input-Dependent Frequency Modulation of Cortical Gamma Oscillations Shapes Spatial Synchronization and Enables Phase Coding

    Lowet, Roberts, Hadjipapas, Peter, van der Eerden, De Weerd (2015). PLOS Computational Biology. DOI

  11. The Asynchronous State in Cortical Circuits

    Renart, de la Rocha, Bartho, Hollender, Parga, Reyes, Harris (2010). Science. DOI

  12. The Asynchronous State in Cortical Circuits: Supporting Online Material

    Renart, de la Rocha, Bartho, Hollender, Parga, Reyes, Harris (2010). Science. DOI

  13. Bayesian inference with probabilistic population codes

    Ma, Beck, Latham, Pouget (2006). Nature Neuroscience. DOI

  14. Synchronization in Networks of Excitatory and Inhibitory Neurons with Sparse, Random Connectivity

    Börgers, Kopell (2003). Neural Computation. DOI

  15. Dynamics of Sparsely Connected Networks of Excitatory and Inhibitory Spiking Neurons

    Brunel (2000). Journal of Computational Neuroscience. DOI