Bono J, Clopath C. (2017). Modeling somatic and dendritic spike mediated plasticity at the single neuron and network level. Nature communications. 8 [PubMed]

• Modeling dendritic spikes and plasticity (Bono and Clopath 2017) [Model]

Brette R. (2012). Computing with neural synchrony. PLoS computational biology. 8 [PubMed]

• Computing with neural synchrony (Brette 2012) [Model]

Brette R, Goodman DF. (2011). Vectorized algorithms for spiking neural network simulation. Neural computation. 23 [PubMed]

• Vectorized algorithms for spiking neural network simulation (Brette and Goodman 2011) [Model]

Cohen MX. (2014). Fluctuations in oscillation frequency control spike timing and coordinate neural networks. The Journal of neuroscience : the official journal of the Society for Neuroscience. 34 [PubMed]

• Input strength and time-varying oscillation peak frequency (Cohen MX 2014) [Model]

Costa RP, Froemke RC, Sjöström PJ, van Rossum MC. (2015). Unified pre- and postsynaptic long-term plasticity enables reliable and flexible learning. eLife. 4 [PubMed]

• Memory savings through unified pre- and postsynaptic STDP (Costa et al 2015) [Model]

Evans BD, Jarvis S, Schultz SR, Nikolic K. (2016). PyRhO: A Multiscale Optogenetics Simulation Platform. Frontiers in neuroinformatics. 10 [PubMed]

• PyRhO: A multiscale optogenetics simulation platform (Evans et al 2016) [Model]

Gewaltig MO, Cannon R. (2014). Current practice in software development for computational neuroscience and how to improve it. PLoS computational biology. 10 [PubMed]

Gilson M, Masquelier T, Hugues E. (2011). STDP allows fast rate-modulated coding with Poisson-like spike trains. PLoS computational biology. 7 [PubMed]

• STDP allows fast rate-modulated coding with Poisson-like spike trains (Gilson et al. 2011) [Model]

Gleeson P et al. (2010). NeuroML: a language for describing data driven models of neurons and networks with a high degree of biological detail. PLoS computational biology. 6 [PubMed]

Goodman DFM, Brette R. (2013). Brian simulator Scholarpedia. 8(1)

Khalil R, Moftah MZ, Moustafa AA. (2017). The effects of dynamical synapses on firing rate activity: a spiking neural network model. The European journal of neuroscience. 46 [PubMed]

Kim CM, Nykamp DQ. (2017). The influence of depolarization block on seizure-like activity in networks of excitatory and inhibitory neurons. Journal of computational neuroscience. 43 [PubMed]

• Modeling epileptic seizure induced by depolarization block (Kim & Dykamp 2017) [Model]

Kim J, Leahy W, Shlizerman E. (2019). Neural Interactome: Interactive Simulation of a Neuronal System. Frontiers in computational neuroscience. 13 [PubMed]

• Neural Interactome: interactive simulation of a neuronal system (Kim et al 2019) [Model]

Li G, Henriquez CS, Fröhlich F. (2017). Unified Thalamic Model Generates Multiple Distinct Oscillations with State-dependent Entrainment by Stimulation PLOS Computational Biology. 13(10)

• A unified thalamic model of multiple distinct oscillations (Li, Henriquez and Fröhlich 2017) [Model]

Masquelier T, Deco G. (2013). Network bursting dynamics in excitatory cortical neuron cultures results from the combination of different adaptive mechanisms. PloS one. 8 [PubMed]

• Network bursts in cultured NN result from different adaptive mechanisms (Masquelier & Deco 2013) [Model]

Masquelier T, Hugues E, Deco G, Thorpe SJ. (2009). Oscillations, phase-of-firing coding, and spike timing-dependent plasticity: an efficient learning scheme. The Journal of neuroscience : the official journal of the Society for Neuroscience. 29 [PubMed]

• Oscillations, phase-of-firing coding and STDP: an efficient learning scheme (Masquelier et al. 2009) [Model]

McDougal RA, Bulanova AS, Lytton WW. (2016). Reproducibility in Computational Neuroscience Models and Simulations. IEEE transactions on bio-medical engineering. 63 [PubMed]

Muller L, Brette R, Gutkin B. (2011). Spike-timing dependent plasticity and feed-forward input oscillations produce precise and invariant spike phase-locking. Frontiers in computational neuroscience. 5 [PubMed]

• STDP and oscillations produce phase-locking (Muller et al. 2011) [Model]

Pastoll H, Solanka L, van Rossum MC, Nolan MF. (2013). Feedback inhibition enables theta-nested gamma oscillations and grid firing fields. Neuron. 77 [PubMed]

• An attractor network model of grid cells and theta-nested gamma oscillations (Pastoll et al 2013) [Model]

Platkiewicz J, Brette R. (2010). A threshold equation for action potential initiation. PLoS computational biology. 6 [PubMed]

• A threshold equation for action potential initiation (Platkiewicz & Brette 2010) [Model]

Platkiewicz J, Brette R. (2011). Impact of fast sodium channel inactivation on spike threshold dynamics and synaptic integration. PLoS computational biology. 7 [PubMed]

• Impact of fast Na channel inact. on AP threshold & synaptic integration (Platkiewicz & Brette 2011) [Model]

Richert M, Nageswaran JM, Dutt N, Krichmar JL. (2011). An efficient simulation environment for modeling large-scale cortical processing. Frontiers in neuroinformatics. 5 [PubMed]

• Efficient simulation environment for modeling large-scale cortical processing (Richert et al. 2011) [Model]

Richmond P, Buesing L, Giugliano M, Vasilaki E. (2011). Democratic population decisions result in robust policy-gradient learning: a parametric study with GPU simulations. PloS one. 6 [PubMed]

• Democratic population decisions result in robust policy-gradient learning (Richmond et al. 2011) [Model]

Sherfey JS et al. (2018). DynaSim: A MATLAB Toolbox for Neural Modeling and Simulation. Frontiers in neuroinformatics. 12 [PubMed]

• DynaSim: a MATLAB toolbox for neural modeling and simulation (Sherfey et al 2018) [Model]

Sweeney Y, Hellgren Kotaleski J, Hennig MH. (2015). A Diffusive Homeostatic Signal Maintains Neural Heterogeneity and Responsiveness in Cortical Networks. PLoS computational biology. 11 [PubMed]

• Diffusive homeostasis in a spiking network model (Sweeney et al. 2015) [Model]

Tan AY, Andoni S, Priebe NJ. (2013). A spontaneous state of weakly correlated synaptic excitation and inhibition in visual cortex. Neuroscience. 247 [PubMed]

• Spontaneous weakly correlated excitation and inhibition (Tan et al. 2013) [Model]

Taxidis J, Coombes S, Mason R, Owen MR. (2012). Modeling sharp wave-ripple complexes through a CA3-CA1 network model with chemical synapses. Hippocampus. 22 [PubMed]

• CRH modulates excitatory transmission and network physiology in hippocampus (Gunn et al. 2017) [Model]

Tikidji-Hamburyan RA, El-Ghazawi TA, Narayana V, Bozkus Z. (2017). Software for Brain Network Simulations: A Comparative Study Front. Neuroinform..

• Brain networks simulators - a comparative study (Tikidji-Hamburyan et al 2017) [Model]

Touboul J, Brette R. (2008). Dynamics and bifurcations of the adaptive exponential integrate-and-fire model. Biological cybernetics. 99 [PubMed]

• Brette-Gerstner model (Touboul and Brette 2008) [Model]

Ursino M, Ricci G, Magosso E. (2020). Transfer Entropy as a Measure of Brain Connectivity: A Critical Analysis With the Help of Neural Mass Models Frontiers in computational neuroscience. 14 [PubMed]

• A neural mass model for critical assessment of brain connectivity (Ursino et al 2020) [Model]

Yang GR, Murray JD, Wang XJ. (2016). A dendritic disinhibitory circuit mechanism for pathway-specific gating. Nature communications. 7 [PubMed]

• A dendritic disinhibitory circuit mechanism for pathway-specific gating (Yang et al. 2016) [Model]

de Wiljes OO, van Elburg RAJ, Keijzer FA. (2017). Modelling the effects of short and random proto-neural elongations. Journal of the Royal Society, Interface. 14 [PubMed]

• Modelling the effects of short and random proto-neural elongations (de Wiljes et al 2017) [Model]