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Computing Temporal Sequence with Dendrites

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Book cover The Computing Dendrite

Part of the book series: Springer Series in Computational Neuroscience ((NEUROSCI,volume 11))

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Abstract

This chapter describes recent experimental results showing that dendrites of cortical pyramidal neurons can compute the temporal sequence of synaptic input. Electrophysiological recordings combined with two-photon glutamate uncaging, calcium imaging, and compartmental modeling have shown that single cortical dendrites have a gradient of nonlinear synaptic integration, which relies on dendritic impedance gradients and nonlinear synaptic NMDA receptor activation. This gradient confers high sensitivity to the temporal input sequence, allowing single dendrites and individual neurons to implement a fundamental cortical computation.

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Authors and Affiliations

  1. MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge Biomedical Campus, Cambridge, CB2 0QH, UK

    Tiago Branco

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  1. Tiago Branco
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Correspondence to Tiago Branco .

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Editors and Affiliations

  1. Institute of Clinical Neuroanatomy, Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society & Goethe-University, Frankfurt, Germany

    Hermann Cuntz

  2. Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Berlin, Germany

    Michiel W.H. Remme

  3. Department of Neurobiology, Hebrew University of Jerusalem, Jerusalem, Israel

    Benjamin Torben-Nielsen

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Branco, T. (2014). Computing Temporal Sequence with Dendrites. In: Cuntz, H., Remme, M., Torben-Nielsen, B. (eds) The Computing Dendrite. Springer Series in Computational Neuroscience, vol 11. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8094-5_15

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