A spatial model of the intermediate superior colliculus. It reproduces the collicular saccade-generating output profile from NMDA receptor-driven burst neurons, shaped by integrative inhibitory feedback from spreading buildup neuron activity. The model is consistent with the view that collicular activity directly shapes the temporal profile of saccadic eye movements. We use the Adaptive exponential integrate and fire neuron model, augmented with an NMDA-like membrane potential-dependent receptor. In addition, we use a synthetic spike integrator model as a stand-in for a spike-integrator circuit in the reticular formation. NOTE: We use a couple of custom neuron models, so the supplied model file includes an entire version of NEST. I also include a patch that applies to a clean version of the simulator (see the doc/README).
Model Type: Realistic Network; Connectionist Network
Region(s) or Organism(s): Superior colliculus
Cell Type(s): Abstract integrate-and-fire adaptive exponential (AdEx) neuron
Receptors: NMDA
Model Concept(s): Activity Patterns; Bursting; Spatio-temporal Activity Patterns; Action Selection/Decision Making
Simulation Environment: NEST; Python
References:
Morén J, Shibata T, Doya K. (2013). The mechanism of saccade motor pattern generation investigated by a large-scale spiking neuron model of the superior colliculus. PloS one. 8 [PubMed]