2021-12-10 : CONECT seminar - "Sequence anticipation and STDP emerge from a voltage-based predictive learning rule" (Matteo Saponati)

A seminar by Matteo Saponati at the Institute of Neurosciences Timone in Marseille.

2021-12-10 1211:00

During a seminar at the Institute of Neurosciences Timone in Marseille, Matteo Saponati, will present his recent work showing that “Sequence anticipation and STDP emerge from a voltage-based predictive learning rule”:

Intelligent behavior depends on the brain’s ability to anticipate future events. However, the learning rules that enable neurons to predict and fire ahead of sensory inputs remain largely unknown. We propose a plasticity rule based on predictive processing, where the neuron learns a low-rank model of the synaptic input dynamics in its membrane potential. Neurons thereby amplify those synapses that maximally predict other synaptic inputs based on their temporal relations, which provide a solution to an optimization problem that can be implemented at the single-neuron level using only local information. Consequently, neurons learn sequences over long timescales and shift their spikes towards the first inputs in a sequence. We show that this mechanism can explain the development of anticipatory motion signaling and recall in the visual system. Furthermore, we demonstrate that the learning rule gives rise to several experimentally observed STDP (spike-timing-dependent plasticity) mechanisms. These findings suggest prediction as a guiding principle to orchestrate learning and synaptic plasticity in single neurons. https://www.biorxiv.org/content/10.1101/2021.10.31.466667v1

Antoine Grimaldi
Antoine Grimaldi
Phd candidate in Computational Neuroscience

During my PhD, I am focusing on pUltra-fast vision using Spiking Neural Networks.

Laurent U Perrinet
Laurent U Perrinet
Researcher in Computational Neuroscience

My research interests include Machine Learning and computational neuroscience applied to Vision.