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Encoding a temporally structured stimulus with a temporally structured neural representation

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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Figure 1: The responses of projection neurons change with odor and inter-pulse intervals.
Figure 2: The responses of projection neurons to odors and the extent of interference between overlapping responses patterns vary greatly depending on the odor and the cell.
Figure 3: Over time, the responses of projection neurons varied more across odors and concentrations than across trials.
Figure 4: Cross-correlations indicate that the response of the projection-neuron ensemble evolves gradually over the duration of the response.
Figure 5: Visualization of the projection-neuron ensemble responses over time reveals invariant odor-specific trajectories, regardless of odor delivery pattern.
Figure 6: Ensemble responses are well classified, regardless of odor delivery pattern.
Figure 7: Correlation and classification analyses show that responses to single odor pulses are comparable to responses during odor pulse trains.
Figure 8: Kenyon cells fire sparsely throughout the odor responses.

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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.

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Correspondence to Mark Stopfer.

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Supplementary information

Supplementary Fig. 1

Slow temporal patterns of PN responses determine when PNs are co-active (PDF 937 kb)

Supplementary Fig. 2

Trajectories representing low odor concentration responses occupied the same manifolds as those of high concentrations (PDF 168 kb)

Supplementary Fig. 3

Templates taken from the beginning of a pulse response provide best classification success for all pulses regardless of pulse pattern (PDF 54 kb)

Supplementary Fig. 4

Classification success decreased with decreasing PN ensemble size (PDF 74 kb)

Supplementary Fig. 5

Establishing significance levels: Histogram of classification success when the template-based classification algorithm was applied to times prior to odor delivery (PDF 52 kb)

Supplementary Fig. 6

Monte-Carlo simulation shows low probability of re-sampled PNs in the pooled ensemble (PDF 57 kb)

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Brown, S., Joseph, J. & Stopfer, M. Encoding a temporally structured stimulus with a temporally structured neural representation. Nat Neurosci 8, 1568–1576 (2005). https://doi.org/10.1038/nn1559

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