SadehEtAl2017-InhibitionStabilizedNetworks

Sadeh et al. 2017 - Inhibition Stabilized Networks

Continuous build using OMV

Models of Inhibition Stabilized Networks in mammalian neocortex. Theoretical, firing-rate and spiking models of cortical networks with increasing realism, to explore how networks respond to perturbation of neural activity. From:

Sadeh S, Silver RA, Mrsic-Flogel TD, Muir DR Assessing the Role of Inhibition in Stabilizing Neocortical Networks Requires Large-Scale Perturbation of the Inhibitory Population.. J Neurosci. 2017, 37(49):12050-12067.

Linear Threshold Models

Firing rate models for the network in MATLAB can be found here.

SpikingSimulationModels

Spiking network models can be found here.

DOI

Reusing this model

The code in this repository is provided under the terms of the software license included with it. If you use this model in your research, we respectfully ask you to cite the references outlined in the CITATION file.

Being converted to PyNN/NeuroML2

This model was originally developed in: NEST

The code for this model is hosted on GitHub: https://github.com/OpenSourceBrain/SadehEtAl2017-InhibitionStabilizedNetworks.git