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Non-monotonic accumulation of spike time variance during membrane potential oscillations

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Abstract

A spike-phase neural code has been proposed as a mechanism to encode stimuli based on the precise timing of spikes relative to the phase of membrane potential oscillations. This form of coding has been reported in both in vivo and in vitro experiments across several regions of the brain, yet there are concerns that such precise timing may be compromised by an effect referred to as variance accumulation, wherein spike timing variance increases over the phase of an oscillation. Here, we provide a straightforward explanation of this effect based on the theoretical spike time variance. The proposed theory is consistent with recordings of mitral neurons. It shows that spike time variance can increase in a nonlinear fashion with spike number, in a way that is dependent upon the frequency and amplitude of the oscillation. Further, non-monotonic accumulation of variance can arise from different combinations of oscillation parameters. Nonlinear accumulation sometimes leads to lower variance than that of a mean rate-matched homogeneous Poisson process, particularly for spikes that occur in later phases of oscillation. However, such an advantage is limited to a narrow range of oscillation amplitudes and frequencies. These results suggest fundamental constraints on spike-phase coding, and reveal how certain spikes in a sequence may exhibit increased firing time precision relative to their neighbors.

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References

  • Brody CD, Hopfield J (2003) Simple networks for spike-timing-based computation, with application to olfactory processing. Neuron 37(5):843–852

    Article  CAS  Google Scholar 

  • Buzsaki G, Draguhn A (2004) Neuronal oscillations in cortical networks. Science 304(5679):1926–1929

    Article  CAS  Google Scholar 

  • Buzsaki G, Wang XJ (2012) Mechanisms of gamma oscillations. Annu Rev Neurosci 35:203–225

    Article  CAS  Google Scholar 

  • Cang J, Isaacson JS (2003) In vivo whole-cell recording of odor-evoked synaptic transmission in the rat olfactory bulb. J Neurosci 23(10):4108–4116

    Article  CAS  Google Scholar 

  • Cohen J, Cohen P, West SG, Aiken LS (2013) Applied multiple regression/correlation analysis for the behavioral sciences. Routledge, Abingdon

    Book  Google Scholar 

  • Cury KM, Uchida N (2010) Robust odor coding via inhalation-coupled transient activity in the mammalian olfactory bulb. Neuron 68(3):570–585

    Article  CAS  Google Scholar 

  • Dumont G, Northoff G, Longtin A (2016) A stochastic model of input effectiveness during irregular gamma rhythms. J Comput Neurosci 40(1):85–101

    Article  Google Scholar 

  • Engel AK, Fries P, Singer W (2001) Dynamic predictions: oscillations and synchrony in top-down processing. Nat Rev Neurosci 2(10):704

    Article  CAS  Google Scholar 

  • Friedrich RW, Stopfer M (2001) Recent dynamics in olfactory population coding. Curr Opin Neurobiol 11(4):468–474

    Article  CAS  Google Scholar 

  • Fries P, Nikoli D, Singer W (2007) The gamma cycle. Trends Neurosci 30(7):309–316

    Article  CAS  Google Scholar 

  • Hafting T, Fyhn M, Bonnevie T, Moser MB, Moser EI (2008) Hippocampus-independent phase precession in entorhinal grid cells. Nature 453(7199):1248

    Article  CAS  Google Scholar 

  • Harris KD (2005) Neural signatures of cell assembly organization. Nat Rev Neurosci 6(5):399

    Article  CAS  Google Scholar 

  • Harris KD, Henze DA, Hirase H, Leinekugel X (2002) Spike train dynamics predicts theta-related phase precession in hippocampal pyramidal cells. Nature 417(6890):738

    Article  CAS  Google Scholar 

  • Jensen O, Colgin LL (2007) Cross-frequency coupling between neuronal oscillations. Trends Cogn Sci 11(7):267–269

    Article  Google Scholar 

  • Kayser C, Montemurro MA, Logothetis NK, Panzeri S (2009) Spike-phase coding boosts and stabilizes information carried by spatial and temporal spike patterns. Neuron 61(4):597–608

    Article  CAS  Google Scholar 

  • Latham PE, Lengyel M (2008) Phase coding: spikes get a boost from local fields. Curr Biol 18(8):R349–R351

    Article  CAS  Google Scholar 

  • Laurent G (2002) Olfactory network dynamics and the coding of multidimensional signals. Nat Rev Neurosci 3(11):884

    Article  CAS  Google Scholar 

  • Laurent G, Davidowitz H (1994) Encoding of olfactory information with oscillating neural assemblies. Science 265(5180):1872–1875

    Article  CAS  Google Scholar 

  • Lisman J (2005) The theta/gamma discrete phase code occuring during the hippocampal phase precession may be a more general brain coding scheme. Hippocampus 15(7):913–922

    Article  Google Scholar 

  • Margrie TW, Schaefer AT (2003) Theta oscillation coupled spike latencies yield computational vigour in a mammalian sensory system. J Physiol 546(2):363–374

    Article  CAS  Google Scholar 

  • Masuda N, Doiron B (2007) Gamma oscillations of spiking neural populations enhance signal discrimination. PLoS Comput Biol 3(11):e236

    Article  Google Scholar 

  • Mehta M, Lee A, Wilson M (2002) Role of experience and oscillations in transforming a rate code into a temporal code. Nature 417(6890):741

    Article  CAS  Google Scholar 

  • Miura K, Mainen ZF, Uchida N (2012) Odor representations in olfactory cortex: distributed rate coding and decorrelated population activity. Neuron 74(6):1087–1098

    Article  CAS  Google Scholar 

  • Montemurro MA, Rasch MJ, Murayama Y, Logothetis NK, Panzeri S (2008) Phase-of-firing coding of natural visual stimuli in primary visual cortex. Curr Biol 18(5):375–380

    Article  CAS  Google Scholar 

  • O’Keefe J, Burgess N (2005) Dual phase and rate coding in hippocampal place cells: theoretical significance and relationship to entorhinal grid cells. Hippocampus 15(7):853–866

    Article  Google Scholar 

  • Panzeri S, Petersen RS, Schultz SR, Lebedev M, Diamond ME (2001) The role of spike timing in the coding of stimulus location in rat somatosensory cortex. Neuron 29(3):769–777

    Article  CAS  Google Scholar 

  • Ross S (2007) Introduction to probability models. Academic Press, Boston

    Google Scholar 

  • Schaefer AT, Angelo K, Spors H, Margrie TW (2006) Neuronal oscillations enhance stimulus discrimination by ensuring action potential precision. PLoS Biol 4(6):e163

    Article  Google Scholar 

  • Shusterman R, Smear MC, Koulakov AA, Rinberg D (2011) Precise olfactory responses tile the sniff cycle. Nat Neurosci 14(8):1039–1044

    Article  CAS  Google Scholar 

  • Singer W (1999) Neuronal synchrony: a versatile code for the definition of relations? Neuron 24(1):49–65

    Article  CAS  Google Scholar 

  • Thorpe S, Fize D, Marlot C (1996) Speed of processing in the human visual system. Nature 381:520

    Article  CAS  Google Scholar 

  • Tiesinga P, Fellous JM, Sejnowski TJ (2008) Regulation of spike timing in visual cortical circuits. Nat Rev Neurosci 9(2):97

    Article  CAS  Google Scholar 

  • Turesson HK, Logothetis NK, Hoffman KL (2012) Category-selective phase coding in the superior temporal sulcus. Proc Natl Acad Sci USA 109(47):19,438–19,443

    Article  CAS  Google Scholar 

  • Wang HP, Spencer D, Fellous JM, Sejnowski TJ (2010) Synchrony of thalamocortical inputs maximizes cortical reliability. Science 328(5974):106–109

    Article  CAS  Google Scholar 

  • Wang XJ (2010) Neurophysiological and computational principles of cortical rhythms in cognition. Physiol Rev 90(3):1195–1268

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by grants to J.P.T. from the Natural Sciences and Engineering Council of Canada (NSERC Grant No. 210977 and No. 210989), the Canadian Institutes of Health Research (CIHR Grant No. 6105509), and the University of Ottawa Brain and Mind Institute (uOBMI), as well as a graduate scholarship to E.S.K. from NSERC. AL also acknowledges support from NSERC. The authors are thankful to Alfonso Renart, Andreas Schaefer, and Maurice Chacron for useful discussions.

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Correspondence to Jean-Philippe Thivierge.

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Communicated by J. Leo van Hemmen.

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Kuebler, E.S., Calderini, M., Longtin, A. et al. Non-monotonic accumulation of spike time variance during membrane potential oscillations. Biol Cybern 112, 539–545 (2018). https://doi.org/10.1007/s00422-018-0782-x

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