Concept

Non-spiking neuron

Publications associées (179)

À propos
Confidentialité
Mentions légales

Graph Chatbot

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Connectez-vous pour utiliser Chat avec Graph Search

Non-spiking neuron

Graph Chatbot

Chattez avec Graph Search

Simple Neuron Models and Adaptation

The quantitative single-neuron modeling competition

Identifying, tabulating, and analyzing contacts between branched neuron morphologies

Extracting non-linear integrate-and-fire models from experimental data using dynamic I – V curves

A supervised learning approach based on STDP and polychronization in spiking neuron networks

Structure and dynamics of the neocortical microcircuit connectivity

Automatic Methods for Motor Intention Recognition from Spike Rates

Optimality Model of Unsupervised Spike-Timing Dependent Plasticity: Synaptic Memory and Weight Distribution

Spiking Neuron Networks A survey

A supervised learning approach based on STDP and polychronization in spiking neuron networks

Extracting non-linear integrate-and-fire models from experimental data using dynamic I – V curves

Identifying, tabulating, and analyzing contacts between branched neuron morphologies

Spiking Neuron Networks A survey

Simple Neuron Models and Adaptation

The quantitative single-neuron modeling competition

Structure and dynamics of the neocortical microcircuit connectivity

A supervised learning approach based on STDP and polychronization in spiking neuron networks

Automatic Methods for Motor Intention Recognition from Spike Rates

A supervised learning approach based on STDP and polychronization in spiking neuron networks

Optimality Model of Unsupervised Spike-Timing Dependent Plasticity: Synaptic Memory and Weight Distribution