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Synapses with short-term plasticity are optimal estimators of presynaptic membrane potentials

Nature Neuroscience volume 13, pages 1271–1275 (2010)Cite this article

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Abstract

The trajectory of the somatic membrane potential of a cortical neuron exactly reflects the computations performed on its afferent inputs. However, the spikes of such a neuron are a very low-dimensional and discrete projection of this continually evolving signal. We explored the possibility that the neuron′s efferent synapses perform the critical computational step of estimating the membrane potential trajectory from the spikes. We found that short-term changes in synaptic efficacy can be interpreted as implementing an optimal estimator of this trajectory. Short-term depression arose when presynaptic spiking was sufficiently intense as to reduce the uncertainty associated with the estimate; short-term facilitation reflected structural features of the statistics of the presynaptic neuron such as up and down states. Our analysis provides a unifying account of a powerful, but puzzling, form of plasticity.

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Figure 1: Estimating the presynaptic membrane potential from spiking information.
Figure 2: Estimating the presynaptic membrane potential when the resting membrane potential randomly switches between two different values.
Figure 3: The optimal estimator reproduces experimentally observed patterns of synaptic depression and facilitation.
Figure 4: Estimation performance of the presynaptic membrane potential.

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Acknowledgements

We thank M. Häusser and R. Brown for useful references and L. Abbott, Sz. Káli and members of the Budapest Computational Neuroscience Forum for valuable discussions. This work was supported by the Wellcome Trust (J.-P.P., M.L. and P.D.) and the Gatsby Charitable Foundation (P.D.).

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Authors and Affiliations

  1. Department of Engineering, Computational and Biological Learning Lab, University of Cambridge, Cambridge, UK

    Jean-Pascal Pfister & Máté Lengyel

  2. Gatsby Computational Neuroscience Unit, University College London, London, UK

    Peter Dayan

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  1. Jean-Pascal Pfister
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  2. Peter Dayan
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  3. Máté Lengyel
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Contributions

J.-P.P. and M.L. developed the mathematical framework. J.-P.P. performed the numerical simulations. All of the authors wrote the manuscript.

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Correspondence to Jean-Pascal Pfister.

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Pfister, JP., Dayan, P. & Lengyel, M. Synapses with short-term plasticity are optimal estimators of presynaptic membrane potentials. Nat Neurosci 13, 1271–1275 (2010). https://doi.org/10.1038/nn.2640

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