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

  • Robert Egger
  • Vincent J. Dercksen
  • Christiaan P. J. de Kock
  • Marcel Oberlaender
Chapter
Part of the Springer Series in Computational Neuroscience book series (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.

Keywords

Passive Touch Ventral Posterior Medial Whisker Movement Underlie Network Structure Synaptic Innervation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

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.

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Robert Egger
    • 1
    • 2
  • Vincent J. Dercksen
    • 3
  • Christiaan P. J. de Kock
    • 4
  • Marcel Oberlaender
    • 1
    • 5
    • 6
  1. 1.Computational Neuroanatomy Group, Max Planck Institute for Biological CyberneticsTuebingenGermany
  2. 2.Graduate School of Neural Information ProcessingUniversity of TuebingenTuebingenGermany
  3. 3.Department of Visualization and Data AnalysisZuse Institute BerlinBerlinGermany
  4. 4.Center for Neurogenomics and Cognitive ResearchNeuroscience Campus Amsterdam, VU University AmsterdamAmsterdamThe Netherlands
  5. 5.Bernstein Center for Computational NeuroscienceTuebingenGermany
  6. 6.Digital Neuroanatomy, Max Planck Florida Institute for NeuroscienceJupiterUSA

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