An attractor network model of grid cells and theta-nested gamma oscillations (Pastoll et al 2013)

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A two population spiking continuous attractor model of grid cells. This model combines the attractor dynamics with theta-nested gamma oscillatory activity. It reproduces the behavioural response of grid cells (grid fields) in medial entorhinal cortex, while at the same time allowing for nested gamma oscillations of post-synaptic currents.
1 . Pastoll H, Solanka L, van Rossum MC, Nolan MF (2013) Feedback inhibition enables theta-nested gamma oscillations and grid firing fields. Neuron 77:141-54 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Entorhinal cortex;
Cell Type(s): Entorhinal cortex stellate cell;
Gap Junctions:
Receptor(s): GabaA; NMDA; Glutamate;
Transmitter(s): Gaba; Glutamate;
Simulation Environment: Brian; Python;
Model Concept(s): Oscillations; Attractor Neural Network; Grid cell;
Implementer(s): Solanka, Lukas [l.solanka at];
Search NeuronDB for information about:  GabaA; NMDA; Glutamate; Gaba; Glutamate;
# Environment for Pastoll 2013 spiking continuous attractor network
# ModelDB accession 150031
# Example usage:
# docker build . -t pastoll2013
# docker run -it -v ${PWD}:/code -w /code/grid_cell_model pastoll2013 ./
FROM ubuntu:14.04

# Install python and system dependencies for numpy, scipy, and matplotlib
RUN apt-get update -y && \
    apt-get install -y python2.7 python-pip python-dev libblas3 libgfortran3 liblapack3 liblapack-dev libblas-dev gfortran libfreetype6-dev

# Finally install the python packages we need 
RUN pip install brian==1.4.0
RUN pip install numpy==1.6.2
RUN pip install scipy==0.11.0
RUN pip install matplotlib==1.1.1

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