Networks of spiking neurons: a review of tools and strategies (Brette et al. 2007)
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Updated
Feb 25, 2022 - C++
Networks of spiking neurons: a review of tools and strategies (Brette et al. 2007)
Perfect Integrate and fire with noisy adaptation or fractional noise (Richard et al 2018)
E-I balance modulates formation and dynamics of neuronal assemblies (Sadeh and Clopath, 2021)
Diffusive homeostasis in a spiking network model (Sweeney et al. 2015)
Excitatory and inhibitory population activity (Bittner et al 2017) (Litwin-Kumar & Doiron 2017)
Sequence learning via biophysically realistic learning rules (Cone and Shouval 2021)
A full-scale cortical microcircuit spiking network model (Shimoura et al 2018)
A spiking NN for amplification of feature-selectivity with specific connectivity (Sadeh et al 2015)
Code to calc. spike-trig. ave (STA) conduct. from Vm (Pospischil et al. 2007, Rudolph et al. 2007)
Optimal Localist and Distributed Coding Through STDP (Masquelier & Kheradpisheh 2018)
Short Term Depression, Presynaptic Inhib., Neuron Diversity Roles in Antennal Lobe (Wei & Lo 2020)
V1 and AL spiking neural network for visual contrast response in mouse (Meijer et al. 2020)
Generalized Carnevale-Hines algorithm (van Elburg and van Ooyen 2009)
Minimal model of interictal and ictal discharges “Epileptor-2” (Chizhov et al 2018)
Leaky Integrate and Fire Neuron Model of Context Integration (Calvin, Redish 2021)
I&F recurrent networks with current- or conductance-based synapses (Cavallari et al. 2014)
Models for cortical UP-DOWN states in a bistable inhibitory-stabilized network (Jercog et al 2017)
Double boundary value problem (A. Bose and J.E. Rubin, 2015)
Oscillations, phase-of-firing coding and STDP: an efficient learning scheme (Masquelier et al. 2009)
A spiking neural network model of model-free reinforcement learning (Nakano et al 2015)
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