Meta-Learning through Hebbian Plasticity in Random Networks: https://arxiv.org/abs/2007.02686

Code to accompany our paper "The combination of Hebbian and predictive plasticity learns invariant object representations in deep sensory networks"

Code for paper NeurIPS AMHN 2023

Computational Neuroscience projects.

Code for Computational Neuroscience course 2020/2021 @ UniPi

Differentiable Plasticity: A Meta-Learning Framework for Evolving Universal Learning Rules : This work synthesizes concepts from: Hebbian neuroscience (activity-dependent synaptic modification) Meta-learning (learning to learn) Differentiable programming (end-to-end gradient flow) Neuroplasticity (adaptive weight modification)

Towards a biologically plausible model of LGN-V1 pathways (Lian et al 2019)