The timing of action potentials relative to sensory stimuli can be precise down to milliseconds in the visual system1,2,3,4,5,6,7, even though the relevant timescales of natural vision are much slower. The existence of such precision contributes to a fundamental debate over the basis of the neural code and, specifically, what timescales are important for neural computation8,9,10. Using recordings in the lateral geniculate nucleus, here we demonstrate that the relevant timescale of neuronal spike trains depends on the frequency content of the visual stimulus, and that ‘relative’, not absolute, precision is maintained both during spatially uniform white-noise visual stimuli and naturalistic movies. Using information-theoretic techniques, we demonstrate a clear role of relative precision, and show that the experimentally observed temporal structure in the neuronal response is necessary to represent accurately the more slowly changing visual world. By establishing a functional role of precision, we link visual neuron function on slow timescales to temporal structure in the response at faster timescales, and uncover a straightforward purpose of fine-timescale features of neuronal spike trains.
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This work was supported by a Charles King Trust Postdoctoral Fellowship (Bank of America, Co-Trustee, Boston; D.A.B), by the NGIA (D.A.B., N.A.L., G.B.S.), by the NIH and by the SUNY Research Foundation (C.W., J.J., C.-I.Y., J.-M.A.). We thank M. Goldman, M. Meister, G. Desbordes and A. Boloori for comments on the manuscript, C. Kayser for providing the natural-scene movies, and P. Wolfe for discussions regarding sampling issues.
Reprints and permissions information is available at www.nature.com/reprints. The authors declare no competing financial interests.
This file contains Supplementary Methods and Discussion with Supplementary Figures. The Supplementary Methods describe the calculation of receptive fields and temporal scales. The Supplementary Figures and Discussion address the following: changes in temporal scale with stimulus class; temporal precision in phenomenological models; the relationship between jitter and frequency content and controlling for the effects of phase-locking. (PDF 1295 kb)
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Butts, D., Weng, C., Jin, J. et al. Temporal precision in the neural code and the timescales of natural vision. Nature 449, 92–95 (2007) doi:10.1038/nature06105
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