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Reverse Engineering the 3D Structure and Sensory-Evoked Signal Flow of Rat Vibrissal Cortex

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The Computing Dendrite

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

Abstract

Soma location, dendrite morphology, and synaptic innervation are key determinants of neuronal function. Unfortunately, conventional functional measurements of sensory-evoked activity in vivo yield limited structural information. In particular, when trying to infer mechanistic principles that underlie perception and behavior, interpretations from functional recordings of individual or small groups of neurons often remain ambiguous without detailed knowledge of the underlying network structures. Here we review a novel reverse engineering approach that allows investigating sensory-evoked signal flow through individual and ensembles of neurons within the context of their surrounding neural networks. To do so, spontaneous and sensory-evoked activity patterns are recorded from individual neurons in vivo. In addition, the complete 3D dendrite and axon projection patterns of such in vivo-characterized neurons are reconstructed and integrated into an anatomically realistic model of the rat vibrissal cortex. This model allows estimating the number and cell type-specific subcellular distribution of synapses on these neurons with 50 μm precision. As a result, each neuron can be described by a rich set of parameters that allows investigating structure–function relationships and simulation experiments at single-neuron and network levels.

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Acknowledgments

We thank Bert Sakmann for advice and initiation of the collaborative project; Randy Bruno for labeling thalamocortical axon morphologies; and Hanno-Sebastian Meyer for immunohistochemistry staining of neuron somata.

Author contributions: Conceived and designed the project: MO. Performed the experiments: CPJdK. Performed the simulations: RE. Analyzed the data: RE MO. Contributed network assembly and analysis tools: VJD. Wrote the paper: MO.

Funding: Funding was provided by the Bernstein Center for Computational Neuroscience, Tuebingen (funded by the German Federal Ministry of Education and Research (BMBF; FKZ: 01GQ1002)) (MO and RE); by the Max Planck Institute for Biological Cybernetics, Tuebingen (MO and RE); by the Max Planck Florida Institute for Neuroscience, Jupiter (MO); by the Werner Reichardt Center for Integrative Neuroscience, Tuebingen (MO); by the Studienstiftung des Deutschen Volkes (RE); by the Center for Neurogenomics and Cognitive Research—CNCR (CPJdK); by the Zuse Institute Berlin (VJD); and by the Max Planck Institute of Neurobiology, Martinsried (VJD). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Author information

Authors and Affiliations

  1. Computational Neuroanatomy Group, Max Planck Institute for Biological Cybernetics, Spemannstraße 38-44, Tuebingen, 72076, Germany

    Robert Egger & Marcel Oberlaender

  2. Graduate School of Neural Information Processing, University of Tuebingen, Tuebingen, Germany

    Robert Egger

  3. Department of Visualization and Data Analysis, Zuse Institute Berlin, Berlin, Germany

    Vincent J. Dercksen

  4. Center for Neurogenomics and Cognitive Research, Neuroscience Campus Amsterdam, VU University Amsterdam, Amsterdam, The Netherlands

    Christiaan P. J. de Kock

  5. Bernstein Center for Computational Neuroscience, Tuebingen, Germany

    Marcel Oberlaender

  6. Digital Neuroanatomy, Max Planck Florida Institute for Neuroscience, Jupiter, FL, USA

    Marcel Oberlaender

Authors
  1. Robert Egger
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  2. Vincent J. Dercksen
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  3. Christiaan P. J. de Kock
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  4. Marcel Oberlaender
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Corresponding author

Correspondence to Marcel Oberlaender .

Editor information

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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Egger, R., Dercksen, V.J., de Kock, C.P.J., Oberlaender, M. (2014). Reverse Engineering the 3D Structure and Sensory-Evoked Signal Flow of Rat Vibrissal Cortex. 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_8

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