I'm a theoretical neuroscientist interested in how neuronal networks process information and learn in different temporal and spatial scales.
Here you will find the code used in my latest papers:
-
https://github.com/ejagnes/codependent_plasticity for "Co-dependent excitatory and inhibitory plasticity accounts for quick, stable and long-lasting memories in biological networks" (2024) Everton J Agnes and Tim P Vogels, Nature Neuroscience 27:964-974; https://doi.org/10.1038/s41593-024-01597-4
-
https://github.com/ejagnes/transient_amplification_abst_bio for "Regimes and mechanisms of transient amplification in abstract and biological neural networks" (2022) Georgia Christodoulou, Tim P Vogels, and Everton J Agnes, PLoS Computational Biology 18:e1010365; https://doi.org/10.1371/journal.pcbi.101036
-
https://github.com/ejagnes/flexible_switch_2ISP for "Complementary inhibitory weight profiles emerge from plasticity and allow flexible switching of receptive fields" (2020) Everton J Agnes, Andrea I Luppi, and Tim P Vogels, Journal of Neuroscience 40:9634-9649; https://doi.org/10.1523/JNEUROSCI.0276-20.2020
-
From Basile Confavreux: https://github.com/basile6/MetaLearnBiologicallyPlausibleRules for "A meta-learning approach to (re)discover plasticity rules that carve a desired function into a neural network" (2020) Basile Confavreux, Friedemann Zenke, Everton J Agnes, Timothy Lillicrap, and Tim P Vogels, Advances in Neural Information Processing Systems 33:16398-16408; https://proceedings.neurips.cc/paper/2020/hash/bdbd5ebfde4934142c8a88e7a3796cd5-Abstract.html
For more info, please check out my Google Scholar profile (https://scholar.google.com/citations?user=-jI6Om0AAAAJ&hl=en) and my departmental website (https://www.biozentrum.unibas.ch/agnes).