Olfactory Computation in Insects

Chapter
Part of the Nonlinear Systems and Complexity book series (NSCH, volume 20)

Abstract

The olfactory system maps complex and high dimensional stimuli (odors) into unique and reproducible dynamic ensembles of neuronal activity. In the insect, olfactory receptor neurons (ORNs) synapse onto a smaller group of excitatory projection neurons (PNs) and inhibitory local neurons (LNs) in the antennal lobe (AL). The odor information is then transferred to the mushroom body (MB), a structure analogous to the olfactory cortex and where olfactory memories are formed. Inhibitory circuits of the AL and the MB shape the odor representation as it progresses through the olfactory system. The insect system is advantageous for studying and modeling olfactory coding because it is relatively simple and amenable to genetic manipulation.

Keywords

Synchronization Olfactory system Odor information 

Notes

Acknowledgements

The work is supported by NIH (R01 DC012943) to M. Bazhenov and M. Stopfer, and an intramural grant from NIH-NICHD to M. Stopfer.

References

  1. 1.
    MacLeod, K., Becker, A., Laurent, G.: Who reads temporal information contained across synchronized and oscillatory spike trains? Nature 395 (6703), 693–698 (1998)CrossRefGoogle Scholar
  2. 2.
    Stopfer, M., Bhagavan, S., Smith, B.H., Laurent, G.: Impaired odour discrimination on desynchronization of odour-encoding neural assemblies. Nature 390 (6655), 70–74 (1997)CrossRefGoogle Scholar
  3. 3.
    Borgers, C., Kopell, N.: Synchronization in networks of excitatory and inhibitory neurons with sparse, random connectivity. Neural Comput. 15, 509–538 (2003)CrossRefMATHGoogle Scholar
  4. 4.
    Linster, C., Cleland, T.: How spike synchronization among olfactory neurons can contribute to sensory discrimination. J. Comput. Neurosci. 10, 187–193 (2001)CrossRefGoogle Scholar
  5. 5.
    Stopfer, M., Laurent, G.: Short-term memory in olfactory network dynamics. Nature 402, 664–668 (1999)CrossRefGoogle Scholar
  6. 6.
    Bazhenov, M., Stopfer, M., Sejnowski, T.J., Laurent, G.: Fast odor learning improves reliability of odor responses in the locust antennal lobe. Neuron 46, 483–492 (2005)CrossRefGoogle Scholar
  7. 7.
    Bazhenov, M., Stopfer, M., Rabinovich, M., Huerta, R., Abarbanel, H.D.I., Sejnowski, T.J., Laurent, G.: Model of transient oscillatory synchronization in the locust antennal lobe. Neuron 30 (2), 553–567 (2001)CrossRefGoogle Scholar
  8. 8.
    Assisi, C., Stopfer, M., Bazhenov, M.: Using the structure of inhibitory networks to unravel mechanisms of spatiotemporal patterning. Neuron 69 (2), 373–86 (2011)CrossRefGoogle Scholar
  9. 9.
    Komarov, M.A., Osipov, G.V., Suykens, J.A.K.: Sequentially activated groups in neural networks. Europhys. Lett. 86 (6), 60006 (2009)CrossRefGoogle Scholar
  10. 10.
    Linster, C., Marsan, D., Masson, C., Kerszberg, M.: Odor processing in the bee: a preliminary study of the role of central input to the antennal lobe. Adv. Neural Inf. Proces. Syst. 6, 527–534–492 (1994)Google Scholar
  11. 11.
    Kerszberg, M., Masson, C.: Signal-induced selection among spontaneous oscillatory patterns in a model of honeybee olfactory glomeruli. Biol. Cybern. 72, 487–495 (1995)CrossRefGoogle Scholar
  12. 12.
    Linster, C., Masson, C.: A neural model of olfactory sensory memory in the honeybee’s antennal lobe. Neural Comput. 8, 94–114 (1996)CrossRefGoogle Scholar
  13. 13.
    Komarov, M., Bazhenov, M.: Linking dynamics of the inhibitory network to the input structure. J. Comput. Neurosci. 41, 367–391 (2016)MathSciNetCrossRefGoogle Scholar
  14. 14.
    Assisi, C., Bazhenov, M.: Synaptic inhibition controls transient oscillatory synchronization in a model of the insect olfactory system. Front. Neuroeng. 5, 7 (2012)CrossRefGoogle Scholar
  15. 15.
    Wojcik, J., Schwabedal, J., Clewley, R., Shilnikov, A.L.: Key Bifurcations of bursting polyrhythms in 3-cell central pattern generators. PLoS One 9 (4), e92918 (2014)CrossRefGoogle Scholar
  16. 16.
    Ito, I., Bazhenov, M., Ying Ong, R.C., Raman, B., Stopfer, M.: Frequency transitions in odor-evoked neural oscillations. Neuron 64 (5), 692–706 (2009)CrossRefGoogle Scholar
  17. 17.
    Raman, B., Joseph, J., Tang, J., Stopfer, M.: Temporally diverse firing patterns in olfactory receptor neurons underlie spatiotemporal neural codes for odors. J. Neurosci. 30, 1994–2006 (2010)CrossRefGoogle Scholar
  18. 18.
    Bazhenov, M., Stopfer, M., Rabinovich, M., Abarbanel, H.D.I., Sejnowski, T.J., Laurent, G.: Model of cellular and network mechanisms for odor-evoked temporal patterning in the locust antennal lobe. Neuron 30 (2), 569–581 (2001)CrossRefGoogle Scholar
  19. 19.
    Sivan, E., Kopell, N.: Oscillations and slow patterning in the antennal lobe. J. Comput. Neurosci. 20, 85–96 (2006)MathSciNetCrossRefMATHGoogle Scholar
  20. 20.
    Friedrich, R.W., Laurent, G.: Dynamics of olfactory bulb input and output activity during odor stimulation in zebrafish. J. Neurophys. 91 (6), 2658–2669 (2004)CrossRefGoogle Scholar
  21. 21.
    Assisi, C., Stopfer, M., Bazhenov, M.: Excitatory local interneurons enhance tuning of sensory information. PLoS Comput. Biol. 8, e1002563 (2012)CrossRefGoogle Scholar
  22. 22.
    Jortner, R.A., Farivar, S.S., Laurent, G.: A simple connectivity scheme for sparse coding in an olfactory system. J. Neurosci. 27, 1659–1669 (2007)CrossRefGoogle Scholar
  23. 23.
    Perez-Orive, J., Mazor, O., Turner, G.C., Cassenaer, S., Wilson, R.I., Laurent, G.: Oscillations and sparsening of odor representations in the mushroom body. Science 297, 359–365 (2002)CrossRefGoogle Scholar
  24. 24.
    Papadopoulou, M., Cassenaer, S., Nowotny, T., Laurent, G.: Normalization for sparse encoding of odors by a wide-field interneuron. Science 332, 721–725 (2011)CrossRefGoogle Scholar
  25. 25.
    Cassenaer, S., Laurent, G.: Hebbian STDP in mushroom bodies facilitates the synchronous flow of olfactory information in locusts. Nature 448, 709–713 (2007)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of MedicineUniversity of CaliforniaSan DiegoUSA
  2. 2.National Institutes of HealthNICHDBethesdaUSA

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