Models that contain the Modeling Application : MATLAB (web link to model) (Home Page)

( MATLAB integrates mathematical computing, visualization, and a powerful language to provide a flexible environment for technical computing. The open architecture makes it easy to use MATLAB and its companion products to explore data, create algorithms, and create custom tools that provide early insights and competitive advantages.)
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1. A cardiac cell simulator (Puglisi and Bers 2001), applied to the QT interval (Busjahn et al 2004)
2. A comparison of mathematical models of mood in bipolar disorder (Cochran et al. 2017)
3. A CORF computational model of a simple cell that relies on LGN input (Azzopardi & Petkov 2012)
4. A detailed and fast model of extracellular recordings (Camunas-Mesa & Qurioga 2013)
5. A dynamic model of the canine ventricular myocyte (Hund, Rudy 2004)
6. A neural mass model of cross frequency coupling (Chehelcheraghi et al 2017)
7. A neurocomputational model of classical conditioning phenomena (Moustafa et al. 2009)
8. A reinforcement learning example (Sutton and Barto 1998)
9. A simple integrative electrophysiological model of bursting GnRH neurons (Csercsik et al. 2011)
10. Activity constraints on stable neuronal or network parameters (Olypher and Calabrese 2007)
11. Analyzing neural time series data theory and practice (Cohen 2014)
12. Auditory nerve spontaneous rate histograms (Jackson and Carney 2005)
13. Cat auditory nerve model (Zilany and Bruce 2006, 2007)
14. Cochlear implant models (Bruce et al. 1999a, b, c, 2000)
15. Continuous lateral oscillations as a mechanism for taxis in Drosophila larvae (Wystrach et al 2016)
16. Evaluation of stochastic diff. eq. approximation of ion channel gating models (Bruce 2009)
17. Fixed point attractor (Hasselmo et al 1995)
18. Gamma and theta rythms in biophysical models of hippocampus circuits (Kopell et al. 2011)
19. Generating coherent patterns of activity from chaotic neural networks (Sussillo and Abbott 2009)
20. High-Res. Recordings Using a Real-Time Computational Model of the Electrode (Brette et al. 2008)
21. Hippocampal context-dependent retrieval (Hasselmo and Eichenbaum 2005)
22. Hodgkin–Huxley model with fractional gating (Teka et al. 2016)
23. Human seizures couple across spatial scales through travelling wave dynamics (Martinet et al 2017)
24. Implementation issues in approximate methods for stochastic Hodgkin-Huxley models (Bruce 2007)
25. Inhibitory cells enable sparse coding in V1 model (King et al. 2013)
26. Integrate and fire model code for spike-based coincidence-detection (Heinz et al. 2001, others)
27. Long-term adaptation with power-law dynamics (Zilany et al. 2009)
28. Loss of phase-locking in non-weakly coupled inhib. networks of type-I neurons (Oh and Matveev 2009)
29. Mathematics for Neuroscientists (Gabbiani and Cox 2010)
30. MATLAB for brain and cognitive scientists (Cohen 2017)
31. Method for counting motor units in mice (Major et al 2007)
32. Method of probabilistic principle surfaces (PPS) (Chang and Ghosh 2001)
33. Microglial cytokine network (Anderson et al., 2015)
34. Model of neural responses to amplitude-modulated tones (Nelson and Carney 2004)
35. Modeling conductivity profiles in the deep neocortical pyramidal neuron (Wang K et al. 2013)
36. Models analysis for auditory-nerve synapse (Zhang and Carney 2005)
37. Models for diotic and dichotic detection (Davidson et al. 2009)
38. Multi-timescale adaptive threshold model (Kobayashi et al 2009)
39. Multistability of clustered states in a globally inhibitory network (Chandrasekaran et al. 2009)
40. Network topologies for producing limited sustained activation (Kaiser and Hilgetag 2010)
41. Neural mass model of spindle generation in the isolated thalamus (Schellenberger Costa et al. 2016)
42. Neural mass model of the neocortex under sleep regulation (Costa et al 2016)
43. Neural mass model of the sleeping thalamocortical system (Schellenberger Costa et al 2016)
44. Neural model of two-interval discrimination (Machens et al 2005)
45. NeuroManager: a workflow analysis based simulation management engine (Stockton & Santamaria 2015)
46. Nodose sensory neuron (Schild et al. 1994, Schild and Kunze 1997)
47. Nonlinear neuronal computation based on physiologically plausible inputs (McFarland et al. 2013)
48. Phase-locking analysis with transcranial magneto-acoustical stimulation (Yuan et al 2017)
49. Polychronization: Computation With Spikes (Izhikevich 2005)
50. Prefrontal cortical mechanisms for goal-directed behavior (Hasselmo 2005)
51. Prefrontal–striatal Parkinsons comp. model of multicue category learning (Moustafa and Gluck 2011)
52. Quantitative assessment of computational models for retinotopic map formation (Hjorth et al. 2015)
53. Reduction of nonlinear ODE systems possessing multiple scales (Clewley et al. 2005)
54. Response properties of an integrate and fire model (Zhang and Carney 2005)
55. Role of KCNQ1 and IKs in cardiac repolarization (Silva, Rudy 2005)
56. Squid axon (Hodgkin, Huxley 1952) (LabAXON)
57. Sympathetic neuron (Wheeler et al 2004)
58. The dynamics underlying pseudo-plateau bursting in a pituitary cell model (Teka et al. 2011)
59. Two-cell inhibitory network bursting dynamics captured in a one-dimensional map (Matveev et al 2007)
60. Voltage and light-sensitive Channelrhodopsin-2 model (ChR2) (Williams et al. 2013)

Re-display model names with descriptions