Effects of Poisson noise in a IF model with STDP and spontaneous replay of periodic spatiotemporal patterns, in absence of cue stimulation

S Scarpetta, F Giacco, F Lombardi, A De Candia - Biosystems, 2013 - Elsevier
We consider a network of leaky integrate and fire neurons, whose learning mechanism is
based on the Spike-Timing-Dependent Plasticity. The spontaneous temporal dynamic of the …

A biological gradient descent for prediction through a combination of stdp and homeostatic plasticity

MN Galtier, G Wainrib - Neural computation, 2013 - direct.mit.edu
Identifying, formalizing, and combining biological mechanisms that implement known brain
functions, such as prediction, is a main aspect of research in theoretical neuroscience. In this …

Associative memory of phase-coded spatiotemporal patterns in leaky Integrate and Fire networks

S Scarpetta, F Giacco - Journal of Computational Neuroscience, 2013 - Springer
We study the collective dynamics of a Leaky Integrate and Fire network in which precise
relative phase relationship of spikes among neurons are stored, as attractors of the …

Storage of phase-coded patterns via STDP in fully-connected and sparse network: a study of the network capacity

S Scarpetta, A De Candia, F Giacco - Frontiers in synaptic …, 2010 - frontiersin.org
We study the storage and retrieval of phase-coded patterns as stable dynamical attractors in
recurrent neural networks, for both an analog and a integrate and fire spiking model. The …

Storage capacity of phase-coded patterns in sparse neural networks

S Scarpetta, F Giacco, A de Candia - Europhysics Letters, 2011 - iopscience.iop.org
We study the storage of multiple phase-coded patterns as stable dynamical attractors in
recurrent neural networks with sparse connectivity. To determine the synaptic strength of …

Capacity, fidelity, and noise tolerance of associative spatial-temporal memories based on memristive neuromorphic networks

D Gavrilov, D Strukov, KK Likharev - Frontiers in Neuroscience, 2018 - frontiersin.org
We have calculated key characteristics of associative (content-addressable) spatial-
temporal memories based on neuromorphic networks with restricted connectivity …

Spike-timing-dependent synaptic plasticity to learn spatiotemporal patterns in recurrent neural networks

M Yoshioka, S Scarpetta, M Marinaro - … 9-13, 2007, Proceedings, Part I 17, 2007 - Springer
Assuming asymmetric time window of the spike-timing-dependent synaptic plasticity (STDP),
we study spatiotemporal learning in recurrent neural networks. We first show numerical …

Learning of Spatiotemporal Patterns in Ising-Spin Neural Networks:<? format?> Analysis of Storage Capacity by Path Integral Methods

M Yoshioka - Physical review letters, 2009 - APS
We encode periodic spatiotemporal patterns in Ising-spin neural networks, using the simple
learning rule inspired by the spike-timing-dependent synaptic plasticity. It is then found that …

Encoding and replay of dynamic attractors with multiple frequencies: Analysis of a STDP based learning rule

S Scarpetta, M Yoshioka, M Marinaro - International School on Neural …, 2007 - Springer
In this paper we review a model of learning based on the Spike Timing Dependent Plasticity
(STDP), introduced in our previous works, and we extend the analysis to the case of multiple …

Critical behavior and memory function in a model of spiking neurons with a reservoir of spatio-temporal patterns

S Scarpetta - The Functional Role of Critical Dynamics in Neural …, 2019 - Springer
Two intriguing phenomena characterize cortical dynamics both in-vitro and in-vivo:(1) the
memory function, with the cue-induced and spontaneous reactivation of precise dynamical …