Advanced search
User account
Login
Register
Find models by
Model name
First author
Each author
Find models for
Brain region
Concept
Find models of
Realistic Microcircuits
Connectionist Networks
Vertical system (VS) fly cells with biophysics (Dan et al 2018)
Download zip file
Auto-launch
Help downloading and running models
Model Information
Model File
Versions
Accession:
231815
"The fly visual system offers a unique opportunity to explore computations performed by single neurons. Two previous studies characterized, in vivo, the receptive field (RF) of the vertical system (VS) cells of the blowfly (calliphora vicina), both intracellularly in the axon, and, independently using Ca2+ imaging, in hundreds of distal dendritic branchlets. We integrated this information into detailed passive cable and compartmental models of 3D reconstructed VS cells. Within a given VS cell type, the transfer resistance (TR) from different branchlets to the axon differs substantially, suggesting that they contribute unequally to the shaping of the axonal RF. ..."
Reference:
1 .
Dan O, Hopp E, Borst A, Segev I (2018) Non-uniform weighting of local motion inputs underlies dendritic computation in the fly visual system.
Sci Rep
8
:5787
[
PubMed
]
Citations
Citation Browser
Model Information
(Click on a link to find other models with that property)
Model Type:
Axon;
Brain Region(s)/Organism:
Cell Type(s):
Fly lobular plate vertical system cell;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment:
NEURON;
Model Concept(s):
Detailed Neuronal Models;
Implementer(s):
Dan, Ohad [Ohad.Dan at gmail.com];
Download the displayed file
/
vs_with_biophys
readme.html
init.hoc
mosinit.hoc
*
Other models using mosinit.hoc:
A network model of the vertebrate retina (Publio et al. 2009)
Availability of low-threshold Ca2+ current in retinal ganglion cells (Lee SC et al. 2003)
CA1 pyramidal neuron (Combe et al 2018)
CA1 pyramidal neurons: effect of external electric field from power lines (Cavarretta et al. 2014)
Changes of ionic concentrations during seizure transitions (Gentiletti et al. 2016)
Cortical network model of posttraumatic epileptogenesis (Bush et al 1999)
DBS of a multi-compartment model of subthalamic nucleus projection neurons (Miocinovic et al. 2006)
Effects of synaptic location and timing on synaptic integration (Rall 1964)
Extracellular fields for a three-dimensional network of cells using NEURON (Appukuttan et al 2017)
Feedforward heteroassociative network with HH dynamics (Lytton 1998)
Hippocampal basket cell gap junction network dynamics (Saraga et al. 2006)
Hodgkin-Huxley model of persistent activity in prefrontal cortex neurons (Winograd et al. 2008)
Model of repetitive firing in Grueneberg ganglion olfactory neurons (Liu et al., 2012)
NN activity impact on neocortical pyr. neurons integrative properties in vivo (Destexhe & Pare 1999)
Olfactory bulb mitral cell gap junction NN model: burst firing and synchrony (O`Connor et al. 2012)
Optimal balance predicts/explains amplitude and decay time of iPSGs (Kim & Fiorillo 2017)
Simulated light response in rod photoreceptors (Liu and Kourennyi 2004)
Space clamp problems in neurons with voltage-gated conductances (Bar-Yehuda and Korngreen 2008)
Spike propagation in dendrites with stochastic ion channels (Diba et al. 2006)
Striatal Output Neuron (Mahon, Deniau, Charpier, Delord 2000)
Sympathetic Preganglionic Neurone (Briant et al. 2014)
Synaptic integration by MEC neurons (Justus et al. 2017)
The cannula artifact (Chandler & Hodgkin 1965)
screenshot.png
shape_plt.ses
vs1_with_biophysics.hoc
vs2_with_biophysics.hoc
vs3_with_biophysics.hoc
vs4_with_biophysics.hoc
vs5_with_biophysics.hoc
vs9_with_biophysics.hoc
load_file("nrngui.hoc") load_file("init.hoc")