Event Abstract

Building a 3D model of the mitral-granule cell network in the olfactory bulb

  • 1 Yale University, Neurobiology, United States
  • 2 National Research Council, Institute of Biophysics, Italy

We are interested in studying the basic mechanisms involved in odor recognition, a widely studied experimental model of sensory information processing. Recent findings have shown that odors may activate spatially distributed sites in the olfactory bulb with a sparse, columnar-like organization of mitral and granule cells. This organization challenges the classical center-surround organization, and there is thus a need to identify a new paradigm for signal discrimination that could have general implications as well for other brain regions. The possible underlying circuitry and the computational properties of the olfactory bulb have been widely investigated experimentally, especially in terms of odor selectivity and dynamics of cell responses. However, experiments are usually carried out in single cells or in small randomly selected sets of cells. This has prevented a clear understanding of the spatio-temporal organization of the mitral-granule cell network in representing an odor input, which requires simultaneous recording from a relevant subset of mitral and granule cells activated by an odor. The functional effects of a network-wide process such as lateral inhibition, in relation to the patterns of glomeruli activated by different odors, remain thus relatively unknown and difficult to explore experimentally.

The main challenge we are addressing here is the development of a 3D model of the mitral-granule cell network, allowing direct input of the experimental data for individual glomerular activation, in order to demonstrate and predict the learning mechanisms that will ultimately be responsible for the early processing stages of the sensory inputs. For this purpose, we implemented a 2mm^2 3D model of the olfactory bulb (about 1/20th of the entire system). Several 3D reconstructions of mitral cells with full dendritic trees (from Igarashi et al., 2012) were analyzed to extract morphological parameters to generate a population of some 700 synthetic mitral cells, 5 for each glomerulus. Approximately 20000 granule cells were then randomly inserted into the network and connected using a collision detection algorithm. The input activity elicited in 127 glomeruli in the dorsal olfactory bulb during presentation of 19 natural odorants (kindly provided by Alan Carleton, from Vincis et al., 2012) was then used to drive self-organization of the network under different conditions of odor input. This is the first 3D simulation of the olfactory bulb microcircuit using realistic cell properties and network connectivity. It provides a new framework for investigating the functions of a brain system.
The figure shows a rendering of the olfactory bulb 3D model. Green spheres: glomeruli; red spheres: activated glomeruli; white lines: mitral cell dendrites.

Figure 1


Igarashi, KM et al., (2012) Parallel mitral and tufted cell pathways route distinct odor information to different targets in the olfactory cortex, J. Neurosci. 32:7970 –7985.
Vincis R, Gschwend O, Bhaukaurally K, Beroud J, Carleton A (2011) Dense representation of natural odorants in the mouse olfactory bulb, Nat. Neurosci. 15:537-539.

Keywords: Olfactory Bulb, mitral-granule cell network, lateral inhibition, odor processing, natural odorants

Conference: Neuroinformatics 2013, Stockholm, Sweden, 27 Aug - 29 Aug, 2013.

Presentation Type: Oral presentation

Topic: Large scale modeling

Citation: Migliore M, Hines ML, Cavarretta F and Shepherd GM (2013). Building a 3D model of the mitral-granule cell network in the olfactory bulb. Front. Neuroinform. Conference Abstract: Neuroinformatics 2013. doi: 10.3389/conf.fninf.2013.09.00098

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Received: 26 Mar 2013; Published Online: 11 Jul 2013.

* Correspondence: Dr. Michele Migliore, Yale University, Neurobiology, New Haven, United States, michele.migliore@cnr.it