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Cortical feedback alters visual response properties of dLGN relay cells (Martínez-Cañada et al 2018)
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Model Information
Model File
Citations
Accession:
239878
Network model that includes biophysically detailed, single-compartment and multicompartment neuron models of relay-cells and interneurons in the dLGN and a population of orientation-selective layer 6 simple cells, consisting of pyramidal cells (PY). We have considered two different arrangements of synaptic feedback from the ON and OFF zones in the visual cortex to the dLGN: phase-reversed (‘push-pull’) and phase-matched (‘push-push’), as well as different spatial extents of the corticothalamic projection pattern. This project is the result of a research work and its associated publication is: (Martínez-Cañada et al 2018). Installation instructions as well as the latest version can be found in the Github repository: https://github.com/CINPLA/biophysical_thalamocortical_system
Reference:
1 .
Martínez-Cañada P, Mobarhan MH, Halnes G, Fyhn M, Morillas C, Pelayo F, Einevoll GT (2018) Biophysical network modeling of the dLGN circuit: Effects of cortical feedback on spatial response properties of relay cells.
PLoS Comput Biol
14
:e1005930
[
PubMed
]
Model Information
(Click on a link to find other models with that property)
Model Type:
Realistic Network;
Brain Region(s)/Organism:
Thalamus;
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment:
LFPy;
NEURON;
NEST;
Python;
Model Concept(s):
Vision;
Implementer(s):
Martínez-Cañada, Pablo [pablomc at ugr.es];
Download the displayed file
/
Biophysical_thalamocortical_system
cortex_neurons
.README.swp
README
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Cortical feedback alters visual response properties of dLGN relay cells (Martínez-Cañada et al 2018)
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load_file("nrngui.hoc") load_file("rundemo.hoc")
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