Circuits that contain the Model Concept : Methods

(Research on numerical, mathematical, or computational neuroscience algorithms.)
Re-display model names with descriptions
    Models
1. A detailed data-driven network model of prefrontal cortex (Hass et al 2016)
2. Activity constraints on stable neuronal or network parameters (Olypher and Calabrese 2007)
3. Cell splitting in neural networks extends strong scaling (Hines et al. 2008)
4. Collection of simulated data from a thalamocortical network model (Glabska, Chintaluri, Wojcik 2017)
5. Composite spiking network/neural field model of Parkinsons (Kerr et al 2013)
6. Connection-set Algebra (CSA) for the representation of connectivity in NN models (Djurfeldt 2012)
7. Efficient simulation environment for modeling large-scale cortical processing (Richert et al. 2011)
8. Fast population coding (Huys et al. 2007)
9. Hippocampal CA1 NN with spontaneous theta, gamma: full scale & network clamp (Bezaire et al 2016)
10. KInNeSS : a modular framework for computational neuroscience (Versace et al. 2008)
11. Mean Field Equations for Two-Dimensional Integrate and Fire Models (Nicola and Campbell, 2013)
12. Motion Clouds: Synthesis of random textures for motion perception (Leon et al. 2012)
13. NETMORPH: creates NNs with realistic neuron morphologies (Koene et al. 2009, van Ooyen et al. 2014)
14. Networks of spiking neurons: a review of tools and strategies (Brette et al. 2007)
15. Neural mass model based on single cell dynamics to model pathophysiology (Zandt et al 2014)
16. Neuron-based control mechanisms for a robotic arm and hand (Singh et al 2017)
17. Norns - Neural Network Studio (Visser & Van Gils 2014)
18. Numerical Integration of Izhikevich and HH model neurons (Stewart and Bair 2009)
19. Parallel network simulations with NEURON (Migliore et al 2006)
20. Parallelizing large networks in NEURON (Lytton et al. 2016)
21. Quantitative assessment of computational models for retinotopic map formation (Hjorth et al. 2015)
22. Response properties of neocort. neurons to temporally modulated noisy inputs (Koendgen et al. 2008)
23. Spike exchange methods for a Blue Gene/P supercomputer (Hines et al., 2011)
24. Structure-dynamics relationships in bursting neuronal networks revealed (Mäki-Marttunen et al. 2013)
25. Translating network models to parallel hardware in NEURON (Hines and Carnevale 2008)

Re-display model names with descriptions