Development of spiking grid cells and place cells in the entorhinal-hippocampal system to represent positions in large spaces
Model Type: Realistic Network; Neuron or other electrically excitable cell; Synapse; Connectionist Network
Cell Type(s): Hippocampus CA1 pyramidal GLU cell; Hippocampus CA3 pyramidal GLU cell; Entorhinal cortex stellate cell
Currents: I Cl, leak
Receptors: GabaA; AMPA; NMDA; Glutamate; Gaba
Transmitters: Gaba; Glutamate; Ions
Model Concept(s): Action Potential Initiation; Pattern Recognition; Activity Patterns; Ion Channel Kinetics; Oscillations; Detailed Neuronal Models; Synaptic Plasticity; Long-term Synaptic Plasticity; Synaptic Integration; Learning; Unsupervised Learning; Place cell/field; Connectivity matrix; Development; Brain Rhythms; Grid cell
Simulation Environment: MATLAB
Implementer(s): Pilly, Praveen [praveen.pilly at gmail.com]
References:
Pilly PK, Grossberg S. (2013). Spiking neurons in a hierarchical self-organizing map model can learn to develop spatial and temporal properties of entorhinal grid cells and hippocampal place cells PloS one. 8 [PubMed]