Simulation Environment: NEURON (web link to model)

  1. A gap junction network of Amacrine Cells controls Nitric Oxide release (Jacoby et al 2018)
  2. A model for how correlation depends on the neuronal excitability type (Hong et al. 2012)
  3. A two-stage model of dendritic integration in CA1 pyramidal neurons (Katz et al. 2009)
  4. Active dendritic integration in robust and precise grid cell firing (Schmidt-Hieber et al 2017)
  5. Apical Length Governs Computational Diversity of Layer 5 Pyramidal Neurons (Galloni et al 2020)
  6. Axonal Projection and Interneuron Types (Helmstaedter et al. 2008)
  7. BDNF morphological contributions to AP enhancement (Galati et al. 2016)
  8. Behavioral time scale synaptic plasticity underlies CA1 place fields (Bittner et al. 2017)
  9. Beta-cell hubs maintain Ca2+ oscillations in human and mouse islet simulations (Lei et al 2018)
  10. Biophysical basis of Subthalamic LFPs Recorded from DBS electrodes (Maling et al 2018)
  11. BK Channels Promote Bursting in Pituitary Cells (Tabak et al 2011)
  12. CA1 pyramidal neuron synaptic integration (Jarsky et al. 2005)
  13. CA1 Pyramidal Neuron: Synaptic Scaling (London, Segev 2001)
  14. Cellular classes revealed by heartbeat-related modulation of extracellular APs (Mosher et al 2020)
  15. Collection of simulated data from a thalamocortical network model (Glabska, Chintaluri, Wojcik 2017)
  16. Combining modeling, deep learning for MEA neuron localization, classification (Buccino et al 2018)
  17. Composite spiking network/neural field model of Parkinsons (Kerr et al 2013)
  18. Comprehensive models of human cortical pyramidal neurons (Eyal et al 2018)
  19. Contribution of the axon initial segment to APs recorded extracellularly (Telenczuk et al 2018)
  20. Current Dipole in Laminar Neocortex (Lee et al. 2013)
  21. Dendrites enable a robust mechanism for neuronal stimulus selectivity (Caze et al 2017)
  22. Dendritic spikes enhance stimulus selectivity in cortical neurons in vivo (Smith et al 2013)
  23. Dichotomy of action-potential backpropagation in CA1 pyramidal neuron dendrites (Golding et al 2001)
  24. Dipolar extracellular potentials generated by axonal projections (McColgan et al 2017)
  25. Disrupted information processing in Fmr1-KO mouse layer 4 barrel cortex (Domanski et al 2019)
  26. Dynamical assessment of ion channels during in vivo-like states (Guet-McCreight & Skinner 2020)
  27. Dynamics of sleep oscillations coupled to brain temperature on multiple scales (Csernai et al 2019)
  28. Electrical compartmentalization in neurons (Wybo et al 2019)
  29. Fully-Asynchronous Cache-Efficient Simulation of Detailed Neural Networks (Magalhaes et al 2019)
  30. Global and multiplexed dendritic computations under in vivo-like conditions (Ujfalussy et al 2018)
  31. High entrainment constrains synaptic depression in a globular bushy cell (Rudnicki & Hemmert 2017)
  32. High-Res. Recordings Using a Real-Time Computational Model of the Electrode (Brette et al. 2008)
  33. Hippocampal CA1 NN with spontaneous theta, gamma: full scale & network clamp (Bezaire et al 2016)
  34. Ion channel modeling with whole cell and a genetic algorithm (Gurkiewicz and Korngreen 2007)
  35. Layer V pyramidal cell model with reduced morphology (Mäki-Marttunen et al 2018)
  36. LFP signature of monosynaptic thalamocortical connection (Hagen et al 2017)
  37. Mature and young adult-born dentate granule cell models (T2N interface) (Beining et al. 2017)
  38. Modeling conductivity profiles in the deep neocortical pyramidal neuron (Wang K et al. 2013)
  39. Modelling large scale electrodiffusion near morphologically detailed neurons (Solbra et al 2018)
  40. Neural recruitment during synchronous multichannel microstimulation (Hokanson et al 2018)
  41. NeuroManager: a workflow analysis based simulation management engine (Stockton & Santamaria 2015)
  42. Opposing roles for Na+/Ca2+ exchange and Ca2+-activated K+ currents during STDP (O`Halloran 2020)
  43. Principles of Computational Modelling in Neuroscience (Book) (Sterratt et al. 2011)
  44. PyPNS: Multiscale Simulation of a Peripheral Nerve in Python (Lubba et al 2018)
  45. PyRhO: A multiscale optogenetics simulation platform (Evans et al 2016)
  46. Self-organized olfactory pattern recognition (Kaplan & Lansner 2014)
  47. Sloppy morphological tuning in identified neurons of the crustacean STG (Otopalik et al 2017)
  48. Software for teaching neurophysiology of neuronal circuits (Grisham et al. 2008)
  49. Software for teaching the Hodgkin-Huxley model (Hernandez & Zurek 2013) (SENB written in NEURON hoc)
  50. Spatial summation of excitatory and inhibitory inputs in pyramidal neurons (Hao et al. 2010)
  51. Stimulated and physiologically induced APs: frequency and fiber diameter (Sadashivaiah et al 2018)
  52. Systematic integration of data into multi-scale models of mouse primary V1 (Billeh et al 2020)
  53. The basis of sharp spike onset in standard biophysical models (Telenczuk et al 2017)
  54. The microcircuits of striatum in silico (Hjorth et al 2020)
  55. The neocortical microcircuit collaboration portal (Markram et al. 2015)
  56. Visual physiology of the layer 4 cortical circuit in silico (Arkhipov et al 2018)
  57. Voltage attenuation in CA1 pyramidal neuron dendrites (Golding et al 2005)
http://www.neuron.yale.edu

NEURON is a simulation environment for developing and exercising models of neurons and networks of neurons. It is particularly well-suited to problems where cable properties of cells play an important role, possibly including extracellular potential close to the membrane), and where cell membrane properties are complex, involving many ion-specific channels, ion accumulation, and second messengers. It evolved from a long collaboration between Michael Hines and John W. Moore at the Department of Neurobiology, Duke University. Their express goal was to create a tool designed specifically for solving the equations that describe nerve cells.
Top authors for NEURON (web link to model):
Top concepts studied with NEURON (web link to model):
Top neurons studied with NEURON (web link to model):
Top currents studied with NEURON (web link to model):
Top references cited by these models:
This website requires cookies and limited processing of your personal data in order to function. By continuing to browse or otherwise use this site, you are agreeing to this use. See our Privacy policy and how to cite and terms of use.