Models that contain the Model Concept : Methods

(Research on numerical, mathematical, or computational neuroscience algorithms.)
Re-display model names with descriptions
    Models
1. 3D-printer visualization of NEURON models (McDougal and Shepherd, 2015)
2. A comparative computer simulation of dendritic morphology (Donohue and Ascoli 2008)
3. A CORF computational model of a simple cell that relies on LGN input (Azzopardi & Petkov 2012)
4. A detailed data-driven network model of prefrontal cortex (Hass et al 2016)
5. A fast model of voltage-dependent NMDA Receptors (Moradi et al. 2013)
6. A finite volume method for stochastic integrate-and-fire models (Marpeau et al. 2009)
7. A generic MAPK cascade model for random parameter sampling analysis (Mai and Liu 2013)
8. A set of reduced models of layer 5 pyramidal neurons (Bahl et al. 2012)
9. A simplified cerebellar Purkinje neuron (the PPR model) (Brown et al. 2011)
10. Accurate and fast simulation of channel noise in conductance-based model neurons (Linaro et al 2011)
11. Activity constraints on stable neuronal or network parameters (Olypher and Calabrese 2007)
12. Allosteric gating of K channels (Horrigan et al 1999)
13. Analyzing neural time series data theory and practice (Cohen 2014)
14. AP shape and parameter constraints in optimization of compartment models (Weaver and Wearne 2006)
15. Boolean network-based analysis of the apoptosis network (Mai and Liu 2009)
16. Cell splitting in neural networks extends strong scaling (Hines et al. 2008)
17. Channel parameter estimation from current clamp and neuronal properties (Toth, Crunelli 2001)
18. Code to calc. spike-trig. ave (STA) conduct. from Vm (Pospischil et al. 2007, Rudolph et al. 2007)
19. Collection of simulated data from a thalamocortical network model (Glabska, Chintaluri, Wojcik 2017)
20. Comparison of full and reduced globus pallidus models (Hendrickson 2010)
21. Composite spiking network/neural field model of Parkinsons (Kerr et al 2013)
22. Connection-set Algebra (CSA) for the representation of connectivity in NN models (Djurfeldt 2012)
23. Constructed Tessellated Neuronal Geometries (CTNG) (McDougal et al. 2013)
24. Data-driven, HH-type model of the lateral pyloric (LP) cell in the STG (Nowotny et al. 2008)
25. Detailed analysis of trajectories in the Morris water maze (Gehring et al. 2015)
26. Dipole Localization Kit (Mechler & Victor, 2012)
27. Discrete event simulation in the NEURON environment (Hines and Carnevale 2004)
28. Distinct current modules shape cellular dynamics in model neurons (Alturki et al 2016)
29. Distributed computing tool for NEURON, NEURONPM (screensaver) (Calin-Jageman and Katz 2006)
30. Efficient estimation of detailed single-neuron models (Huys et al. 2006)
31. Efficient simulation environment for modeling large-scale cortical processing (Richert et al. 2011)
32. Electrodiffusive astrocytic and extracellular ion concentration dynamics model (Halnes et al. 2013)
33. Evaluation of stochastic diff. eq. approximation of ion channel gating models (Bruce 2009)
34. Fast population coding (Huys et al. 2007)
35. Fully Implicit Parallel Simulation of Single Neurons (Hines et al. 2008)
36. Generic Bi-directional Real-time Neural Interface (Zrenner et al. 2010)
37. Globus pallidus multi-compartmental model neuron with realistic morphology (Gunay et al. 2008)
38. High-Res. Recordings Using a Real-Time Computational Model of the Electrode (Brette et al. 2008)
39. Hippocampal CA1 NN with spontaneous theta, gamma: full scale & network clamp (Bezaire et al 2016)
40. Impact of dendritic size and topology on pyramidal cell burst firing (van Elburg and van Ooyen 2010)
41. Impedance spectrum in cortical tissue: implications for LFP signal propagation (Miceli et al. 2017)
42. Implementation issues in approximate methods for stochastic Hodgkin-Huxley models (Bruce 2007)
43. Increased computational accuracy in multi-compartmental cable models (Lindsay et al. 2005)
44. Inferring connection proximity in electrically coupled networks (Cali et al. 2007)
45. Ion channel modeling with whole cell and a genetic algorithm (Gurkiewicz and Korngreen 2007)
46. KInNeSS : a modular framework for computational neuroscience (Versace et al. 2008)
47. Local variable time step method (Lytton, Hines 2005)
48. Mapping function onto neuronal morphology (Stiefel and Sejnowski 2007)
49. Markov Chain-based Stochastic Shielding Hodgkin Huxley Model (Schmandt, Galan 2012)
50. Mean Field Equations for Two-Dimensional Integrate and Fire Models (Nicola and Campbell, 2013)
51. Measuring neuronal identification quality in ensemble recordings (isoitools) (Neymotin et al. 2011)
52. Method for counting motor units in mice (Major et al 2007)
53. Method for deriving general HH neuron model`s spiking input-output relation (Soudry & Meir 2014)
54. Method of probabilistic principle surfaces (PPS) (Chang and Ghosh 2001)
55. Modeling single neuron LFPs and extracellular potentials with LFPsim (Parasuram et al. 2016)
56. ModelView: online structural analysis of computational models (McDougal et al. 2015)
57. ModFossa: a library for modeling ion channels using Python (Ferneyhough et al 2016)
58. Moose/PyMOOSE: interoperable scripting in Python for MOOSE (Ray and Bhalla 2008)
59. Motion Clouds: Synthesis of random textures for motion perception (Leon et al. 2012)
60. Motoneuron simulations for counting motor units (Major and Jones 2005)
61. NETMORPH: creates NNs with realistic neuron morphologies (Koene et al. 2009, van Ooyen et al. 2014)
62. Networks of spiking neurons: a review of tools and strategies (Brette et al. 2007)
63. Neural mass model based on single cell dynamics to model pathophysiology (Zandt et al 2014)
64. Neural Query System NQS Data-Mining From Within the NEURON Simulator (Lytton 2006)
65. NEUROFIT: fitting HH models to voltage clamp data (Willms 2002)
66. NEURON + Python (Hines et al. 2009)
67. NEURON interfaces to MySQL and the SPUD feature extraction algorithm (Neymotin et al. 2007)
68. Neuron-based control mechanisms for a robotic arm and hand (Singh et al 2017)
69. Neuronvisio: a gui with 3D capabilities for NEURON (Mattioni et al. 2012)
70. Norns - Neural Network Studio (Visser & Van Gils 2014)
71. Numerical Integration of Izhikevich and HH model neurons (Stewart and Bair 2009)
72. On stochastic diff. eq. models for ion channel noise in Hodgkin-Huxley neurons (Goldwyn et al. 2010)
73. Oversampling method to extract excitatory and inhibitory conductances (Bedard et al. 2012)
74. Parallel network simulations with NEURON (Migliore et al 2006)
75. Parallel STEPS: Large scale stochastic spatial reaction-diffusion simulat. (Chen & De Schutter 2017)
76. Parallelizing large networks in NEURON (Lytton et al. 2016)
77. Phase-locking analysis with transcranial magneto-acoustical stimulation (Yuan et al 2017)
78. Properties of aconitine-induced block of KDR current in NG108-15 neurons (Lin et al. 2008)
79. Python demo of the VmT method to extract conductances from single Vm traces (Pospischil et al. 2009)
80. Quantitative assessment of computational models for retinotopic map formation (Hjorth et al. 2015)
81. Recording from rod bipolar axon terminals in situ (Oltedal et al 2007)
82. Reduction of nonlinear ODE systems possessing multiple scales (Clewley et al. 2005)
83. Response properties of neocort. neurons to temporally modulated noisy inputs (Koendgen et al. 2008)
84. Reverse-time correlation analysis for idealized orientation tuning dynamics (Kovacic et al. 2008)
85. Simulating ion channel noise in an auditory brainstem neuron model (Schmerl & McDonnell 2013)
86. Sloppy morphological tuning in identified neurons of the crustacean STG (Otopalik et al 2017)
87. Software (called Optimizer) for fitting neuronal models (Friedrich et al. 2014)
88. Spatial gridding and temporal accuracy in NEURON (Hines and Carnevale 2001)
89. Spectral method and high-order finite differences for nonlinear cable (Omurtag and Lytton 2010)
90. Spike exchange methods for a Blue Gene/P supercomputer (Hines et al., 2011)
91. Structure-dynamics relationships in bursting neuronal networks revealed (Mäki-Marttunen et al. 2013)
92. Theta phase precession in a model CA3 place cell (Baker and Olds 2007)
93. Translating network models to parallel hardware in NEURON (Hines and Carnevale 2008)
94. Vectorized algorithms for spiking neural network simulation (Brette and Goodman 2011)
95. Voltage and light-sensitive Channelrhodopsin-2 model (ChR2) (Williams et al. 2013)

Re-display model names with descriptions