Skip to main content
Log in

Possible Stochastic Mechanism for Improving the Selectivity of Olfactory Projection Neurons

  • Published:
Neurophysiology Aims and scope

A possible mechanism that provides increased selectivity of olfactory bulb projection neurons, as compared to that of the primary olfactory receptor neurons, has been proposed. The mechanism operates at low concentrations of the odor molecules, when the lateral inhibition mechanism becomes inefficient. The mechanism proposed is based on a threshold-type reaction to the stimuli received by a projection neuron from a few receptor neurons, the stochastic nature of these stimuli, and the existence of electrical leakage in the projection neurons. The mechanism operates at the level of the single individual projection neuron and does not require the involvement of other bulbar neurons.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. K. J. Ressler, S. L. Sullivan, and L. B. Buck, “Information coding in the olfactory system: evidence for a stereotyped and highly organized epitope map in the olfactory bulb,” Cell, 79, 1245–1255 (1994).

    Article  CAS  PubMed  Google Scholar 

  2. V. W. Drongelen, “Unitary recordings of near threshold responses of receptor cells in the olfactory mucosa of the frog,” J. Physiol., 277, No. 1, 423–435 (1978).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. V. W. Drongelen, A. Holley, and K. B. Døving, “Convergence in the olfactory system: Quantitative aspects of odour sensitivity,” J. Theor. Biol., 71, No. 1, 39–48 (1978).

    Article  PubMed  Google Scholar 

  4. P. Duchamp-Viret, A. Duchamp, and M. Vigoroux, “Amplifying role of convergence in olfactory system. A comparative study of receptor cell and second-order neuron sensitivities,” J. Neurophysiol., 61, No. 5, 1085–1094 (1989).

    Article  CAS  PubMed  Google Scholar 

  5. A. Duchamp, “Electrophysiological responses of olfactory bulb neurons to odour stimuli in the frog. A comparison with receptor cells,” Chem. Senses,7, No. 2, 191–210 (1982).

    Article  CAS  Google Scholar 

  6. S. Kikuta, M. L. Fletcher, R. Homma et al., “Odorant response properties of individual neurons in an olfactory glomerular module,” Neuron, 77, No. 6, 1122–1135 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. A. P. Davison, J. Feng, and D. Brown, “Dendrodendritic inhibition and simulated odor responses in a detailed olfactory bulb network model,” J. Neurophysiol., 90, No. 3, 1921–1935 (2003).

    Article  CAS  PubMed  Google Scholar 

  8. T. A. Cleland and C. Linster, “Computation in the olfactory system,” Chem. Senses, 30, No. 9, 801–813 (2005).

    Article  PubMed  Google Scholar 

  9. R. Granit and J. C. Eccles, “Aspects of excitation and inhibition in the retina,” Proc. Roy. Soc. Lond. Ser. B Biol. Sci.,140, No. 899, 191–199 (1952).

    Article  CAS  Google Scholar 

  10. H. B. Barlow, “Summation and inhibition in the frog’s retina,” J. Physiol.,119, No. 1, 69–88 (1953).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. H. K. Hartline, H. G. Wagner, and F. Ratliff, “Inhibition in the eye of Limulus,” J. Gen. Physiol., 39, No. 5, 651–673 (1956).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. M. Yokoi, K. Mori, and S. Nakanishi, “Refinement of odor molecule tuning by dendrodendritic synaptic inhibition in the olfactory bulb,” Proc. Natl. Acad. Sci. USA,92, No. 8, 3371–3375 (1995).

    Article  CAS  PubMed  Google Scholar 

  13. N. N. Urban and B. Sakmann, “Reciprocal intra glomerular excitation and intra- and interglomerular lateral inhibition between mouse olfactory bulb mitral cells,” J. Physiol., 542, No. 2, 355–367 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. A. L. Fantana, E. R. Soucy, and M. Meister, “Rat olfactory bulb mitral cells receive sparse glomerular inputs,” Neuron,59, No. 5, 802–814 (2008).

    Article  CAS  PubMed  Google Scholar 

  15. M. T. Valley and S. Firestein, “A lateral look at olfactory bulb lateral inhibition,” Neuron,59, No. 5, 682–684 (2008).

    Article  CAS  PubMed  Google Scholar 

  16. P. Duchamp-Viret, A. Duchamp, and G. Sicard, “Olfac tory discrimination over a wide concentration range. Compa rison of receptor cell and bulb neuron abilities,” Brain Res., 517, Nos. 1–2, 256-262 (1990).

    Article  CAS  PubMed  Google Scholar 

  17. A. K. Vidybida, “Selectivity of chemoreceptor neuron,” BioSystems,58, 125–132 (2000).

    Article  CAS  PubMed  Google Scholar 

  18. A. K. Vidybida, A. S. Usenko, and J. P. Rospars, “Selectivity improvement in a model of olfactory receptor neuron with adsorption-desorption noise,” J. Biol. Syst., 16, No. 4, 531–545 (2008).

    Article  CAS  Google Scholar 

  19. A. K. Vidybida, “Adsorption–desorption noise can be used for improving selectivity,” Sensors Actuators A:Physical., 107, No. 3, 233–237 (2003).

    Article  CAS  Google Scholar 

  20. V. S. Korolyuk, P. G. Kostyuk, B. Ya. Pjatigorskii, and E. P. Tkachenko, “Mathematical model of spontaneous activity of some neurons in the CNS,” Biofizika,12, No. 5, 895–899 (1967).

    Google Scholar 

  21. L. F. Abbott, “Lapique’s introduction of the integrateand- fire model neuron (1907),” Brain Res. Bull., 50, Nos. 5/6, 303–304 (1999).

    Article  CAS  PubMed  Google Scholar 

  22. L. B. Buck, “The molecular architecture of odor and pheromone sensing in mammals,” Cell,100, No. 6, 611–618 (2000).

    Article  CAS  PubMed  Google Scholar 

  23. A. K. Vidybida, Stochastic Models, NAS of Ukraine, BITP, Kyiv (2006).

    Google Scholar 

  24. J. N. Bourne and N. E. Schoppa, “Three-dimensional synaptic analyses of mitral cell and external tufted cell dendrites in rat olfactory bulb glomeruli,” J. Comp. Neurol., 525, No. 3, 592–609 (2017).

    Article  CAS  PubMed  Google Scholar 

  25. S. D. Burton and N. N. Urban, “Greater excitability and firing irregularity of tufted cells underlies distinct afferent-evoked activity of olfactory bulb mitral and tufted cells,” J. Physiol., 592, No. 10, 2097–2118 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. J. Tan, A. Savigner, M. Ma, and M. Luo, “Odor information processing by the olfactory bulb analyzed in gene-targeted mice,” Neuron,65, No. 6, 912–926 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. K. Mori, M. C. Nowycky, and G. M. Shepherd, “Electrophysiological analysis of mitral cells in the isolated turtle olfactory bulb,” J. Physiol., 314, No. 1, 281–294 (1981).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. R. J. Sayer, M. J. Friedlander, and S. J. Redman, “The time course and amplitude of EPSPs evoked at synapses between pairs of CA3/CA1 neurons in the hippocampal slice,” J. Neurosci., 10, No. 3, 826–836 (1990).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. A. Duchamp and G. Sicard, “Influence of stimulus intensity on odour discrimination by olfactory bulb neurons as compared with receptor cells,” Chem. Senses,8, No. 4, 355–366 (1984).

    Article  Google Scholar 

  30. P. Duchamp-Viret, and A. Duchamp, “Odor processing in the frog olfactory system,” Prog. Neurobiol., 53, No. 5, 561–602 (1997).

    Article  CAS  PubMed  Google Scholar 

  31. G. Lowe and G. H. Gold, “Olfactory transduction is intrinsically noisy,” Proc. Natl. Acad. Sci. USA, 92, No. 17, 7864–7868 (1995).

    Article  CAS  PubMed  Google Scholar 

  32. J. P. Rospars, P. Lánský, J. Vaillant, et al., “Spontaneous activity of first- and second-order neurons in the frog olfactory system,” Brain Res.,662, Nos. 1–2, 31–44 (1994).

    Article  PubMed  Google Scholar 

  33. V. Bhandawat, G. Maimon, M. H. Dickinson, and R. J. Wilson, “Olfactory modulation of flight in Drosophila is sensitive, selective and rapid,” J. Exp. Biol., 213, No. 21, 3625 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. M. Häusser, N. Spruston, and G. J. Stuart, “Diversity and dynamics of dendritic signaling,” Science,290, No. 5492, 739–744 (2000).

    Article  PubMed  Google Scholar 

  35. M. London and M. Häusser, “Dendritic computation,” Ann. Rev. Neurosci., 28, No. 1, 503–532 (2005).

    Article  CAS  PubMed  Google Scholar 

  36. J. P. Rospars, A. Grémiaux, D. Jarriault, et al., “Heterogeneity and convergence of olfactory first-order neurons account for the high speed and sensitivity of secondorder neurons,” PLOS Comput. Biol., 10, No. 12 (2014): e1003975.

    Article  PubMed  PubMed Central  Google Scholar 

  37. J. P. McGann. Presynaptic inhibition of olfactory sensory neurons: New mechanisms and potential functions,” Chem. Senses,38, No. 6, 459–474 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. P. M. Lledo, G. Gheusi, and J. D. Vincent, “Information processing in the mammalian olfactory system,” Physiol. Rev., 85, No. 1, 281–317 (2005).

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to A. K. Vidybida.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Vidybida, A.K. Possible Stochastic Mechanism for Improving the Selectivity of Olfactory Projection Neurons. Neurophysiology 51, 152–159 (2019). https://doi.org/10.1007/s11062-019-09808-6

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11062-019-09808-6

Keywords

Navigation