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Encoding a temporally structured stimulus with a temporally structured neural representation

Nature Neuroscience volume 8, pages 15681576 (2005) | Download Citation

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Abstract

Sensory neural systems use spatiotemporal coding mechanisms to represent stimuli. These time-varying response patterns sometimes outlast the stimulus. Can the temporal structure of a stimulus interfere with, or even disrupt, the spatiotemporal structure of the neural representation? We investigated this potential confound in the locust olfactory system. When odors were presented in trains of nearly overlapping pulses, responses of first-order interneurons (projection neurons) changed reliably, and often markedly, with pulse position as responses to one pulse interfered with subsequent responses. However, using the responses of an ensemble of projection neurons, we could accurately classify the odorants as well as characterize the temporal properties of the stimulus. Further, we found that second-order follower neurons showed firing patterns consistent with the information in the projection-neuron ensemble. Thus, ensemble-based spatiotemporal coding could disambiguate complex and potentially confounding temporally structured sensory stimuli and thereby provide an invariant response to a stimulus presented in various ways.

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Acknowledgements

We are grateful to members of the Stopfer lab for helpful discussions. This work was funded by an intramural grant from the National Institutes of Health, the National Institute of Child Health and Human Development.

Author information

Affiliations

  1. National Institute of Child Health and Human Development, US National Institutes of Health, Building 35, Room 3A-102, Bethesda, Maryland 20892, USA.

    • Stacey L Brown
    • , Joby Joseph
    •  & Mark Stopfer

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Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Mark Stopfer.

Supplementary information

PDF files

  1. 1.

    Supplementary Fig. 1

    Slow temporal patterns of PN responses determine when PNs are co-active

  2. 2.

    Supplementary Fig. 2

    Trajectories representing low odor concentration responses occupied the same manifolds as those of high concentrations

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    Supplementary Fig. 3

    Templates taken from the beginning of a pulse response provide best classification success for all pulses regardless of pulse pattern

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    Supplementary Fig. 4

    Classification success decreased with decreasing PN ensemble size

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    Supplementary Fig. 5

    Establishing significance levels: Histogram of classification success when the template-based classification algorithm was applied to times prior to odor delivery

  6. 6.

    Supplementary Fig. 6

    Monte-Carlo simulation shows low probability of re-sampled PNs in the pooled ensemble

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DOI

https://doi.org/10.1038/nn1559

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