" ... We present a large-scale network model with single and multi-compartmental Hodgkin–Huxley type model neurons representing olfactory receptor neurons (ORNs) in the epithelium, periglomerular cells, mitral/tufted cells and granule cells in the olfactory bulb (OB), and three types of cortical cells in the piriform cortex (PC). Odor patterns are calculated based on affinities between ORNs and odor stimuli derived from physico-chemical descriptors of behaviorally relevant real-world odorants. ... The PC was implemented as a modular attractor network with a recurrent connectivity that was likewise organized through Hebbian–Bayesian learning. We demonstrate the functionality of the model in a one-sniff-learning and recognition task on a set of 50 odorants. Furthermore, we study its robustness against noise on the receptor level and its ability to perform concentration invariant odor recognition. Moreover, we investigate the pattern completion capabilities of the system and rivalry dynamics for odor mixtures."
Model Type: Realistic Network
Region(s) or Organism(s): Olfactory cortex; Olfactory bulb
Cell Type(s): Olfactory bulb main mitral GLU cell; Olfactory receptor GLU cell; Piriform cortex anterior pyramidal layer II GLU cell; Olfactory bulb main interneuron periglomerular GABA cell; Olfactory bulb main interneuron granule MC GABA cell; Olfactory bulb main interneuron granule TC GABA cell
Currents: I Na,t; I L high threshold; I T low threshold; I A; I K; I M; I K,Ca; I Calcium
Model Concept(s): Pattern Recognition; Activity Patterns; Attractor Neural Network; Olfaction
Simulation Environment: NEURON (web link to model)
References:
Kaplan BA, Lansner A. (2014). A spiking neural network model of self-organized pattern recognition in the early mammalian olfactory system. Frontiers in neural circuits. 8 [PubMed]