Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Olfactory pattern classification by discrete neuronal network states

Nature volume 465, pages 47–52 (2010)Cite this article

Subjects

Abstract

The categorial nature of sensory, cognitive and behavioural acts indicates that the brain classifies neuronal activity patterns into discrete representations. Pattern classification may be achieved by abrupt switching between discrete activity states of neuronal circuits, but few experimental studies have directly tested this. We gradually varied the concentration or molecular identity of odours and optically measured responses across output neurons of the olfactory bulb in zebrafish. Whereas population activity patterns were largely insensitive to changes in odour concentration, morphing of one odour into another resulted in abrupt transitions between odour representations. These transitions were mediated by coordinated response changes among small neuronal ensembles rather than by shifts in the global network state. The olfactory bulb therefore classifies odour-evoked input patterns into many discrete and defined output patterns, as proposed by attractor models. This computation is consistent with perceptual phenomena and may represent a general information processing strategy in the brain.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Get just this article for as long as you need it

$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Concentration dependence of mitral cell odour responses.
Figure 2: Morphing of similar odours.
Figure 3: Morphing of dissimilar odours.
Figure 4: Transitions between activity patterns are mediated by subsets of mitral cells.

References

  1. Wang, X. J. Decision making in recurrent neuronal circuits. Neuron 60, 215–234 (2008)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Machens, C. K., Romo, R. & Brody, C. D. Flexible control of mutual inhibition: a neural model of two-interval discrimination. Science 307, 1121–1124 (2005)

    Article  ADS  CAS  PubMed  Google Scholar 

  3. Leopold, D. A. & Logothetis, N. K. Multistable phenomena: changing views in perception. Trends Cogn. Sci. 3, 254–264 (1999)

    Article  CAS  PubMed  Google Scholar 

  4. Parker, A. J. & Krug, K. Neuronal mechanisms for the perception of ambiguous stimuli. Curr. Opin. Neurobiol. 13, 433–439 (2003)

    Article  CAS  PubMed  Google Scholar 

  5. Hopfield, J. J. Neural networks and physical systems with emergent collective computational abilities. Proc. Natl Acad. Sci. USA 79, 2554–2558 (1982)

    Article  ADS  MathSciNet  CAS  PubMed  PubMed Central  Google Scholar 

  6. Mozer, M. C. Attractor Networks. In Oxford Companion to Consciousness (eds Wilken, P. Bayne, T. & Cleeremans, A.) (Oxford Univ. Press, 2009)

    Google Scholar 

  7. Galan, R. F., Sachse, S., Galizia, C. G. & Herz, A. V. Odor-driven attractor dynamics in the antennal lobe allow for simple and rapid olfactory pattern classification. Neural Comput. 16, 999–1012 (2004)

    Article  Google Scholar 

  8. Wills, T. J., Lever, C., Cacucci, F., Burgess, N. & O’Keefe, J. Attractor dynamics in the hippocampal representation of the local environment. Science 308, 873–876 (2005)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  9. Freedman, D. J., Riesenhuber, M., Poggio, T. & Miller, E. K. Categorical representation of visual stimuli in the primate prefrontal cortex. Science 291, 312–316 (2001)

    Article  ADS  CAS  PubMed  Google Scholar 

  10. Khan, A. G., Thattai, M. & Bhalla, U. S. Odor representations in the rat olfactory bulb change smoothly with morphing stimuli. Neuron 57, 571–585 (2008)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Leutgeb, J. K. et al. Progressive transformation of hippocampal neuronal representations in “morphed” environments. Neuron 48, 345–358 (2005)

    Article  CAS  PubMed  Google Scholar 

  12. Friedrich, R. W. & Korsching, S. I. Combinatorial and chemotopic odorant coding in the zebrafish olfactory bulb visualized by optical imaging. Neuron 18, 737–752 (1997)

    Article  CAS  PubMed  Google Scholar 

  13. Johnson, B. A. & Leon, M. Modular representations of odorants in the glomerular layer of the rat olfactory bulb and the effects of stimulus concentration. J. Comp. Neurol. 422, 496–509 (2000)

    Article  CAS  PubMed  Google Scholar 

  14. Meister, M. & Bonhoeffer, T. Tuning and topography in an odor map on the rat olfactory bulb. J. Neurosci. 21, 1351–1360 (2001)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Wachowiak, M. & Cohen, L. B. Representation of odorants by receptor neuron input to the mouse olfactory bulb. Neuron 32, 723–735 (2001)

    Article  CAS  PubMed  Google Scholar 

  16. Friedrich, R. W. & Laurent, G. Dynamic optimization of odor representations in the olfactory bulb by slow temporal patterning of mitral cell activity. Science 291, 889–894 (2001)

    Article  ADS  CAS  PubMed  Google Scholar 

  17. Friedrich, R. W. & Laurent, G. Dynamics of olfactory bulb input and output activity during odor stimulation in zebrafish. J. Neurophysiol. 91, 2658–2669 (2004)

    Article  PubMed  Google Scholar 

  18. Yaksi, E. & Friedrich, R. W. Reconstruction of firing rate changes across neuronal populations by temporally deconvolved Ca2+ imaging. Nature Methods 3, 377–383 (2006)

    Article  CAS  PubMed  Google Scholar 

  19. Yaksi, E., Judkewitz, B. & Friedrich, R. W. Topological reorganization of odor representations in the olfactory bulb. PLoS Biol. 5, e178 (2007)

    Article  PubMed  PubMed Central  Google Scholar 

  20. Stopfer, M., Jayaraman, V. & Laurent, G. Intensity versus identity coding in an olfactory system. Neuron 39, 991–1004 (2003)

    Article  CAS  PubMed  Google Scholar 

  21. Laurent, G. Olfactory network dynamics and the coding of multidimensional signals. Nature Rev. Neurosci. 3, 884–895 (2002)

    Article  CAS  Google Scholar 

  22. Cleland, T. A., Johnson, B. A., Leon, M. & Linster, C. Relational representation in the olfactory system. Proc. Natl Acad. Sci. USA 104, 1953–1958 (2007)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  23. Stewart, W. B., Kauer, J. S. & Shepherd, G. M. Functional organization of rat olfactory bulb analysed by the 2-deoxyglucose method. J. Comp. Neurol. 185, 715–734 (1979)

    Article  CAS  PubMed  Google Scholar 

  24. Krone, D., Mannel, M., Pauli, E. & Hummel, T. Qualitative and quantitative olfactometric evaluation of different concentrations of ethanol peppermint oil solutions. Phytother. Res. 15, 135–138 (2001)

    Article  CAS  PubMed  Google Scholar 

  25. Uchida, N. & Mainen, Z. F. Odor concentration invariance by chemical ratio coding. Front. Syst. Neurosci. 1, 3 (2007)

    PubMed  Google Scholar 

  26. Bathellier, B., Buhl, D. L., Accolla, R. & Carleton, A. Dynamic ensemble odor coding in the mammalian olfactory bulb: sensory information at different timescales. Neuron 57, 586–598 (2008)

    Article  CAS  PubMed  Google Scholar 

  27. Sachse, S. & Galizia, C. G. The coding of odour-intensity in the honeybee antennal lobe: local computation optimizes odour representation. Eur. J. Neurosci. 18, 2119–2132 (2003)

    Article  PubMed  Google Scholar 

  28. Abraham, N. M. et al. Maintaining accuracy at the expense of speed: stimulus similarity defines odor discrimination time in mice. Neuron 44, 865–876 (2004)

    CAS  PubMed  Google Scholar 

  29. Gross-Isseroff, R. & Lancet, D. Concentration-dependent changes of perceived odor quality. Chem. Senses 13, 191–204 (1988)

    Article  Google Scholar 

  30. Laing, D. G., Legha, P. K., Jinks, A. L. & Hutchinson, I. Relationship between molecular structure, concentration and odor qualities of oxygenated aliphatic molecules. Chem. Senses 28, 57–69 (2003)

    Article  CAS  PubMed  Google Scholar 

  31. Valentincic, T., Kralj, J., Stenovec, M., Koce, A. & Caprio, J. The behavioral detection of binary mixtures of amino acids and their individual components by catfish. J. Exp. Biol. 203, 3307–3317 (2000)

    CAS  PubMed  Google Scholar 

  32. Laing, D. G. & Willcox, M. E. Perception of components in binary mixtures. Chem. Senses 7, 249–264 (1983)

    Article  CAS  Google Scholar 

  33. Laing, D. G., Panhuber, H., Willcox, M. E. & Pittman, E. A. Quality and intensity of binary odor mixtures. Physiol. Behav. 33, 309–319 (1984)

    Article  CAS  PubMed  Google Scholar 

  34. Wiltrout, C., Dogra, S. & Linster, C. Configurational and nonconfigurational interactions between odorants in binary mixtures. Behav. Neurosci. 117, 236–245 (2003)

    Article  CAS  PubMed  Google Scholar 

  35. Mazor, O. & Laurent, G. Transient dynamics versus fixed points in odor representations by locust antennal lobe projection neurons. Neuron 48, 661–673 (2005)

    Article  CAS  PubMed  Google Scholar 

  36. Freeman, W. J. Simulation of chaotic EEG patterns with a dynamic model of the olfactory system. Biol. Cybern. 56, 139–150 (1987)

    Article  CAS  PubMed  Google Scholar 

  37. Freeman, W. J. Spatial properties of an EEG event in the olfactory bulb and cortex. Electroencephalogr. Clin. Neurophysiol. 44, 586–605 (1978)

    Article  CAS  PubMed  Google Scholar 

  38. Wachowiak, M. & Shipley, M. T. Coding and synaptic processing of sensory information in the glomerular layer of the olfactory bulb. Semin. Cell Dev. Biol. 17, 411–423 (2006)

    Article  PubMed  Google Scholar 

  39. Urban, N. N. & Sakmann, B. Reciprocal intraglomerular excitation and intra- and interglomerular lateral inhibition between mouse olfactory bulb mitral cells. J. Physiol. 542, 355–367 (2002)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Schoppa, N. E. & Westbrook, G. L. Glomerulus-specific synchronization of mitral cells in the olfactory bulb. Neuron 31, 639–651 (2001)

    Article  CAS  PubMed  Google Scholar 

  41. Carlson, G. C., Shipley, M. T. & Keller, A. Long-lasting depolarizations in mitral cells of the rat olfactory bulb. J. Neurosci. 20, 2011–2021 (2000)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Yaksi, E., von Saint Paul, F., Niessing, J., Bundschuh, S. T. & Friedrich, R. W. Transformation of odor representations in target areas of the olfactory bulb. Nature Neurosci. 12, 474–482 (2009)

    Article  CAS  PubMed  Google Scholar 

  43. Hasselmo, M. E., Wilson, M. A., Anderson, B. P. & Bower, J. M. Associative memory function in piriform (olfactory) cortex: computational modeling and neuropharmacology. Cold Spring Harb. Symp. Quant. Biol. 55, 599–610 (1990)

    Article  CAS  PubMed  Google Scholar 

  44. Barnes, D. C., Hofacer, R. D., Zaman, A. R., Rennaker, R. L. & Wilson, D. A. Olfactory perceptual stability and discrimination. Nature Neurosci. 11, 1378–1380 (2008)

    Article  CAS  PubMed  Google Scholar 

  45. Li, J. et al. Early development of functional spatial maps in the zebrafish olfactory bulb. J. Neurosci. 25, 5784–5795 (2005)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Denk, W., Strickler, J. H. & Webb, W. W. Two-photon laser scanning fluorescence microscopy. Science 248, 73–76 (1990)

    Article  ADS  CAS  PubMed  Google Scholar 

  47. Murphy, G. J., Glickfeld, L. L., Balsen, Z. & Isaacson, J. S. Sensory neuron signaling to the brain: properties of transmitter release from olfactory nerve terminals. J. Neurosci. 24, 3023–3030 (2004)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Bozza, T., McGann, J. P., Mombaerts, P. & Wachowiak, M. In vivo imaging of neuronal activity by targeted expression of a genetically encoded probe in the mouse. Neuron 42, 9–21 (2004)

    Article  CAS  PubMed  Google Scholar 

  49. Higashijima, S., Masino, M. A., Mandel, G. & Fetcho, J. R. Imaging neuronal activity during zebrafish behavior with a genetically encoded calcium indicator. J. Neurophysiol. 90, 3986–3997 (2003)

    Article  PubMed  Google Scholar 

  50. Miyawaki, A. et al. Fluorescent indicators for Ca2+ based on green fluorescent proteins and calmodulin. Nature 388, 882–887 (1997)

    Article  ADS  CAS  PubMed  Google Scholar 

  51. Mathieson, W. B. & Maler, L. Morphological and electrophysiological properties of a novel in vitro preparation: the electrosensory lateral line lobe brain slice. J. Comp. Physiol. A 163, 489–506 (1988)

    Article  CAS  PubMed  Google Scholar 

  52. Carr, W. E. S. In Sensory Biology of Aquatic Animals (eds Atema, J., Fay, R. R., Popper, A. N. & Tavolga, W. N.) 3–27 (Springer, 1988)

    Book  Google Scholar 

  53. Michel, W. C. & Lubomudrov, L. M. Specificity and sensitivity of the olfactory organ of the zebrafish, Danio rerio. J. Comp. Physiol. A 177, 191–199 (1995)

    Article  CAS  PubMed  Google Scholar 

  54. Pologruto, T. A., Sabatini, B. L. & Svoboda, K. ScanImage: flexible software for operating laser scanning microscopes. Biomed. Eng. Online 2, 13 (2003)

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank A. Lüthi, T. Oertner, G. Jacobson and M. Wiechert for comments on the manuscript, and members of the Friedrich laboratory for discussions. This work was funded by the Novartis Research Foundation, the Max Planck Society, the Deutsche Forschungsgemeinschaft (FOR 643) and a fellowship from the Studienstiftung des deutschen Volkes (J.N.).

Author information

Authors and Affiliations

  1. Friedrich Miescher Institute for Biomedical Research, Maulbeerstr. 66, CH-4058 Basel, Switzerland,

    Jörn Niessing & Rainer W. Friedrich

Authors
  1. Jörn Niessing
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rainer W. Friedrich
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

J.N. performed all experiments and analysed the data. R.W.F. constructed equipment and participated in data analysis. R.W.F. and J.N. conceived the study and wrote the manuscript.

Corresponding author

Correspondence to Rainer W. Friedrich.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Information

This file contains Supplementary Figures 1-11 with legends and Supplementary References. (PDF 2339 kb)

Supplementary Movie 1

In this movie file we see that the trajectories, in 3D-principal component space, show the temporal evolution of odor response patterns evoked by different concentrations of Lys and the control odor Arg (10-5 M). Conventions are as in Figure 1e. (MOV 3747 kb)

Supplementary Movie 2

In this movie file we see that the trajectories, in 3D-principal component space, show the temporal evolution of odor response patterns evoked by different concentrations of Phe and the control odor Trp (10-5 M). Conventions are as in Supplementary Figure 2g. (MOV 6699 kb)

Supplementary Movie 3

In this movie file we see that the trajectories, in 3D-principal component space, show the temporal evolution of odor response patterns evoked by a morphing series from Phe to Trp, projected into the space defined by the first three principal components. Conventions are as in Figure 2d. (MOV 6263 kb)

Supplementary Movie 4

In this movie file we see that the trajectories, in 3D-principal component space, show the temporal evolution of odor response patterns evoked by a morphing series from Arg to His, projected into the space defined by the first three principal components. Conventions are as in Figure 3b. (MOV 3195 kb)

PowerPoint slides

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Niessing, J., Friedrich, R. Olfactory pattern classification by discrete neuronal network states. Nature 465, 47–52 (2010). https://doi.org/10.1038/nature08961

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nature08961

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing