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Modeling study of gamma oscillations in the mammalian olfactory bulb
BMC Neuroscience volume 10, Article number: P264 (2009)
The dynamics of the mammalian olfactory bulb (OB) are characterized by local field potential oscillations that are either slow, in the theta range (2–10 Hz, tightly linked to the respiratory rhythm), or fast, in the beta (15–30 Hz) or gamma (40–90 Hz) range. Despite that these fast oscillations have been known for a long time and have been shown to be modulated by odorant features  and animal experience or state [2, 3], both their mechanisms and implication in coding are still not well understood. In this study, we focused on the underlying dynamics generating the gamma oscillations. These oscillations have been shown to be generated intrinsically to the OB in response to strong excitation of the olfactory sensory neurons . Moreover experimental  and modeling  studies have shown that they are generated by the interplay between excitatory mitral cells and inhibitory granule cells. However, existing models do not take into account the recently discovered columnar organization of the OB . In this study, we show how this organization may account for a local generation of gamma oscillations by the strongest activated glomeruli in a very specific frequency range and how this oscillation can then entrain mitral cells linked to less activated glomeruli.
Methods and results
A model of a single glomerular column including simple models of mitral and granule cells has been constructed (similar to ). Simulations of this model have been performed using the open source simulator BRIAN . This model can generate oscillations in a wide range of frequency (20–100 Hz) depending on its stimulation strength (excitation of mitral cells). However, the frequency of gamma oscillations recorded in vivo is restricted to a very narrow range: 60–70 Hz. We searched for which model aspects could constrain the oscillations in such a range. We took into account the strong intraglomerular mitral to mitral excitatory connections (see for example ) and show how for a wide range of input strengths, they can put the model in a high activation state leading to oscillations in the experimentally observed gamma range. Finally, we completed this model by adding other similar glomerular columns and tested how the strongest activated columns could entrain the other into the gamma oscillation.
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