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

("Python is a dynamic object-oriented programming language that can be used for many kinds of software development. It offers strong support for integration with other languages and tools, comes with extensive standard libraries, and can be learned in a few days. Many Python programmers report substantial productivity gains and feel the language encourages the development of higher quality, more maintainable code....")
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    Models
1.  A dendritic disinhibitory circuit mechanism for pathway-specific gating (Yang et al. 2016)
2.  A model for how correlation depends on the neuronal excitability type (Hong et al. 2012)
3.  A spiking NN for amplification of feature-selectivity with specific connectivity (Sadeh et al 2015)
4.  A threshold equation for action potential initiation (Platkiewicz & Brette 2010)
5.  Adaptive exponential integrate-and-fire model (Brette & Gerstner 2005)
6.  Alleviating catastrophic forgetting: context gating and synaptic stabilization (Masse et al 2018)
7.  Beta-cell hubs maintain Ca2+ oscillations in human and mouse islet simulations (Lei et al 2018)
8.  BK Channels Promote Bursting in Pituitary Cells (Tabak et al 2011)
9.  Brainstem circuits controlling locomotor frequency and gait (Ausborn et al 2019)
10.  Cochlea: inner ear models in Python (Zilany et al 2009, 2014; Holmberg M 2007)
11.  Cognitive and motor cortico-basal ganglia interactions during decision making (Guthrie et al 2013)
12.  Collection of simulated data from a thalamocortical network model (Glabska, Chintaluri, Wojcik 2017)
13.  Combining modeling, deep learning for MEA neuron localization, classification (Buccino et al 2018)
14.  Comprehensive models of human cortical pyramidal neurons (Eyal et al 2018)
15.  Contribution of the axon initial segment to APs recorded extracellularly (Telenczuk et al 2018)
16.  Cortical model with reinforcement learning drives realistic virtual arm (Dura-Bernal et al 2015)
17.  Current Dipole in Laminar Neocortex (Lee et al. 2013)
18.  Dendrites enable a robust mechanism for neuronal stimulus selectivity (Caze et al 2017)
19.  Different roles for inhibition in the rhythm-generating respiratory network (Harris et al 2017)
20.  Differential interactions between Notch and ID factors control neurogenesis (Boareto et al 2017)
21.  Dipolar extracellular potentials generated by axonal projections (McColgan et al 2017)
22.  Effects of Guanfacine and Phenylephrine on a model of working memory (Duggins et al 2017)
23.  Electrical compartmentalization in neurons (Wybo et al 2019)
24.  Fast global oscillations in networks of I&F neurons with low firing rates (Brunel and Hakim 1999)
25.  Global and multiplexed dendritic computations under in vivo-like conditions (Ujfalussy et al 2018)
26.  Heterosynaptic Spike-Timing-Dependent Plasticity (Hiratani & Fukai 2017)
27.  High entrainment constrains synaptic depression in a globular bushy cell (Rudnicki & Hemmert 2017)
28.  High-Res. Recordings Using a Real-Time Computational Model of the Electrode (Brette et al. 2008)
29.  Homeostatic mechanisms may shape oscillatory modulations (Peterson & Voytek 2020)
30.  Impact of fast Na channel inact. on AP threshold & synaptic integration (Platkiewicz & Brette 2011)
31.  Late emergence of the whisker direction selectivity map in rat barrel cortex (Kremer et al. 2011)
32.  ModFossa: a library for modeling ion channels using Python (Ferneyhough et al 2016)
33.  Multiple dynamical modes of thalamic relay neurons (Wang XJ 1994)
34.  Multiscale modeling of epileptic seizures (Naze et al. 2015)
35.  Noise promotes independent control of gamma oscillations and grid firing (Solanka et al 2015)
36.  Phase locking in leaky integrate-and-fire model (Brette 2004)
37.  PyPNS: Multiscale Simulation of a Peripheral Nerve in Python (Lubba et al 2018)
38.  PyRhO: A multiscale optogenetics simulation platform (Evans et al 2016)
39.  Reliability of spike timing is a general property of spiking model neurons (Brette & Guigon 2003)
40.  Reproducibility and comparability of models for astrocyte Ca2+ excitability (Manninen et al 2017)
41.  ROOTS: An Algorithm to Generate Biologically Realistic Cortical Axons (Bingham et al 2020)
42.  Sensitivity of noisy neurons to coincident inputs (Rossant et al. 2011)
43.  Sloppy morphological tuning in identified neurons of the crustacean STG (Otopalik et al 2017)
44.  Software (called Optimizer) for fitting neuronal models (Friedrich et al. 2014)
45.  Speed/accuracy trade-off between the habitual and the goal-directed processes (Kermati et al. 2011)
46.  Stable propagation of synchronous spiking in cortical neural networks (Diesmann et al 1999)
47.  The basis of sharp spike onset in standard biophysical models (Telenczuk et al 2017)
48.  Theory of arachnid prey localization (Sturzl et al. 2000)
49.  Theory of sequence memory in neocortex (Hawkins & Ahmad 2016)
50.  Time-warp-invariant neuronal processing (Gutig & Sompolinsky 2009)
51.  Two forms of synaptic depression by neuromodulation of presynaptic Ca2+ channels (Burke et al 2018)
52.  Vectorized algorithms for spiking neural network simulation (Brette and Goodman 2011)

Re-display model names with descriptions