"Neural computations underlying cognitive functions require calibration of the strength of excitatory and inhibitory synaptic connections and are associated with modulation of gamma frequency oscillations in network activity. However, principles relating gamma oscillations, synaptic strength and circuit computations are unclear. We address this in attractor network models that account for grid firing and theta-nested gamma oscillations in the medial entorhinal cortex. ..."
Model Type: Realistic Network
Region(s) or Organism(s): Entorhinal cortex
Model Concept(s): Attractor Neural Network; Place cell/field; Brain Rhythms; Grid cell
Simulation Environment: Python (web link to model); NEST (web link to model)
Implementer(s): Solanka, Lukas [l.solanka at sms.ed.ac.uk]
References:
Solanka L, van Rossum MC, Nolan MF. (2015). Noise promotes independent control of gamma oscillations and grid firing within recurrent attractor networks. eLife. 4 [PubMed]