1. Neuroscience
Download icon

Revealing the distribution of transmembrane currents along the dendritic tree of a neuron from extracellular recordings

  1. Dorottya Cserpán
  2. Domokos Meszéna
  3. Lucia Wittner
  4. Kinga Tóth
  5. István Ulbert
  6. Zoltán Somogyvári
  7. Daniel K Wojcik  Is a corresponding author
  1. Hungarian Academy of Sciences, Hungary
  2. Nencki Institute of Experimental Biology, Poland
Tools and Resources
  • Cited 3
  • Views 1,759
  • Annotations
Cite this article as: eLife 2017;6:e29384 doi: 10.7554/eLife.29384

Abstract

Revealing the current source distribution along the neuronal membrane is a key step on the way to understanding neural computations, however, the experimental and theoretical tools to achieve sufficient spatiotemporal resolution for the estimation remain to be established. Here we address this problem using extracellularly recorded potentials with arbitrarily distributed electrodes for a neuron of known morphology. We use simulations of models with varying complexity to validate the proposed method and to give recommendations for experimental applications. The method is applied to in vitro data from rat hippocampus.

Article and author information

Author details

  1. Dorottya Cserpán

    Wigner Research Centre for Physics, Hungarian Academy of Sciences, Budapest, Hungary
    Competing interests
    The authors declare that no competing interests exist.
  2. Domokos Meszéna

    Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Hungarian Academy of Sciences, Budapest, Hungary
    Competing interests
    The authors declare that no competing interests exist.
  3. Lucia Wittner

    Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Hungarian Academy of Sciences, Budapest, Hungary
    Competing interests
    The authors declare that no competing interests exist.
  4. Kinga Tóth

    Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Hungarian Academy of Sciences, Budapest, Hungary
    Competing interests
    The authors declare that no competing interests exist.
  5. István Ulbert

    Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Hungarian Academy of Sciences, Budapest, Hungary
    Competing interests
    The authors declare that no competing interests exist.
  6. Zoltán Somogyvári

    Wigner Research Centre for Physics, Hungarian Academy of Sciences, Budapest, Hungary
    Competing interests
    The authors declare that no competing interests exist.
  7. Daniel K Wojcik

    Department of Neurophysiology, Nencki Institute of Experimental Biology, Warsaw, Poland
    For correspondence
    d.wojcik@nencki.gov.pl
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0812-9872

Funding

Ministerstwo Nauki i Szkolnictwa Wyższego (Grant 2729/7.PR/2013/2)

  • Daniel K Wojcik

Nemzeti Kutatási, Fejlesztesi és Innovacios Hivatal (Grant K 113147)

  • Zoltán Somogyvári

Nemzeti Agykutatasi Program (Grant KTIA NAP 13-1-2013-0001)

  • István Ulbert

Nemzeti Kutatasi, Fejilesztesi es Innovacios Hivatal (Grant NN 118902)

  • Zoltán Somogyvári

Nemzeti Agykutatasi Program (Grant KTIA-13-NAP-A-IV/1 2 3 4 6)

  • István Ulbert

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Animal experimentation: The in vitro experiment was performed according to the EC Council Directive of November 24, 1986 (86/89/EEC) and all procedures were reviewed and approved by the local ethical committee and the Hungarian Central Government Office (license number: PEI/001/695-9/2015).

Reviewing Editor

  1. Frances K Skinner, Krembil Research Institute, University Health Network, Canada

Publication history

  1. Received: June 7, 2017
  2. Accepted: November 16, 2017
  3. Accepted Manuscript published: November 17, 2017 (version 1)
  4. Version of Record published: December 5, 2017 (version 2)
  5. Version of Record updated: December 5, 2017 (version 3)
  6. Version of Record updated: February 20, 2018 (version 4)

Copyright

© 2017, Cserpán et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 1,759
    Page views
  • 339
    Downloads
  • 3
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Download citations (links to download the citations from this article in formats compatible with various reference manager tools)

Open citations (links to open the citations from this article in various online reference manager services)

Further reading

    1. Neuroscience
    Nathan P Achilly et al.
    Short Report

    Rett syndrome is a devastating childhood neurological disorder caused by mutations in MECP2. Of the many symptoms, motor deterioration is a significant problem for patients. In mice, deleting Mecp2 from the cortex or basal ganglia causes motor dysfunction, hypoactivity, and tremor, which are abnormalities observed in patients. Little is known about the function of Mecp2 in the cerebellum, a brain region critical for motor function. Here we show that deleting Mecp2 from the cerebellum, but not from its neuronal subtypes, causes a delay in motor learning that is overcome by additional training. We observed irregular firing rates of Purkinje cells and altered heterochromatin architecture within the cerebellum of knockout mice. These findings demonstrate that the motor deficits present in Rett syndrome arise, in part, from cerebellar dysfunction. For Rett syndrome and other neurodevelopmental disorders, our results highlight the importance of understanding which brain regions contribute to disease phenotypes.

    1. Neuroscience
    Willem AM Wybo et al.
    Tools and Resources

    Dendrites shape information flow in neurons. Yet, there is little consensus on the level of spatial complexity at which they operate. Through carefully chosen parameter fits, solvable in the least-squares sense, we obtain accurate reduced compartmental models at any level of complexity. We show that (back-propagating) action potentials, Ca2+ spikes, and N-methyl-D-aspartate spikes can all be reproduced with few compartments. We also investigate whether afferent spatial connectivity motifs admit simplification by ablating targeted branches and grouping affected synapses onto the next proximal dendrite. We find that voltage in the remaining branches is reproduced if temporal conductance fluctuations stay below a limit that depends on the average difference in input resistance between the ablated branches and the next proximal dendrite. Furthermore, our methodology fits reduced models directly from experimental data, without requiring morphological reconstructions. We provide software that automatizes the simplification, eliminating a common hurdle toward including dendritic computations in network models.