Sensitivity to perturbations in vivo implies high noise and suggests rate coding in cortex

Michael London, Arnd Roth, Lisa Beeren, Michael Häusser, Peter E. Latham

Research output: Contribution to journalArticlepeer-review

309 Scopus citations

Abstract

It is well known that neural activity exhibits variability, in the sense that identical sensory stimuli produce different responses, but it has been difficult to determine what this variability means. Is it noise, or does it carry important informationabout, for example, the internal state of the organism? Here we address this issue from the bottom up, by asking whether small perturbations to activity in cortical networks are amplified. Based on in vivo whole-cell patch-clamp recordings in rat barrel cortex, we find that a perturbation consisting of a single extra spike in one neuron produces approximately 28 additional spikes in its postsynaptic targets. We also show, using simultaneous intra-and extracellular recordings, that a single spike in a neuron produces a detectable increase in firing rate in the local network. Theoretical analysis indicates that this amplification leads to intrinsic, stimulus-independent variations in membrane potential of the order of 2.2-4.5 mVvariations that are pure noise, and so carry no information at all. Therefore, for the brain to perform reliable computations, it must either use a rate code, or generate very large, fast depolarizing events, such as those proposed by the theory of synfire chains. However, in our in vivo recordings, we found that such events were very rare. Our findings are thus consistent with the idea that cortex is likely to use primarily a rate code.

Original languageEnglish
Pages (from-to)123-127
Number of pages5
JournalNature
Volume466
Issue number7302
DOIs
StatePublished - 1 Jul 2010
Externally publishedYes

Bibliographical note

Funding Information:
Acknowledgements We thank P. Dayan for discussions, I. van Welie and P. Dayan for comments on the manuscript, and H. Cuntz for comments on the spike detection algorithm. P.E.L. was supported by the Gatsby Charitable Foundation and US National Institute of Mental Health grant R01 MH62447. M.L., A.R., L.B. and M.H. were supported by the Wellcome Trust, the Gatsby Charitable Foundation, the Engineering and Physical Sciences Research Council and the Medical Research Council.

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