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


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.


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.



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.


  1. Alloway KD (2008) Information processing streams in rodent barrel cortex: the differential functions of barrel and septal circuits. Cereb Cortex 18(5):979–989PubMedCrossRefGoogle Scholar
  2. Ankerst M, Breunig M, Kriegel HP, Sander J (1999) OPTICS: ordering points to identify the clustering structure. In: Delis A, Faloutsous C, Ghandeharizadeh S (eds) ACM SIGMOD’99 International. Conference on Management of Data, Philadelphia, 1999. ACM Press New York, NY, pp 49–60Google Scholar
  3. Armstrong-James M, Fox K (1987) Spatiotemporal convergence and divergence in the rat S1 “barrel” cortex. J Comp Neurol 263(2):265–281PubMedCrossRefGoogle Scholar
  4. Aronoff R, Matyas F, Mateo C, Ciron C, Schneider B, Petersen CC (2010) Long-range connectivity of mouse primary somatosensory barrel cortex. Eu J Neurosci 31(12):2221–2233CrossRefGoogle Scholar
  5. Barth AL, Poulet JF (2012) Experimental evidence for sparse firing in the neocortex. Trends Neurosci 35(6):345–355PubMedCrossRefGoogle Scholar
  6. Binzegger T, Douglas RJ, Martin KA (2004) A quantitative map of the circuit of cat primary visual cortex. J Neurosci 24(39):8441–8453PubMedCrossRefGoogle Scholar
  7. Bock DD, Lee WC, Kerlin AM, Andermann ML, Hood G, Wetzel AW, Yurgenson S, Soucy ER, Kim HS, Reid RC (2011) Network anatomy and in vivo physiology of visual cortical neurons. Nature 471(7337):177–182PubMedCrossRefGoogle Scholar
  8. Brecht M, Sakmann B (2002) Whisker maps of neuronal subclasses of the rat ventral posterior medial thalamus, identified by whole-cell voltage recording and morphological reconstruction. J Physiol 538(Pt 2):495–515PubMedCrossRefGoogle Scholar
  9. Brecht M, Roth A, Sakmann B (2003) Dynamic receptive fields of reconstructed pyramidal cells in layers 3 and 2 of rat somatosensory barrel cortex. J Physiol 553(Pt 1):243–265PubMedCrossRefGoogle Scholar
  10. Briggman KL, Helmstaedter M, Denk W (2011) Wiring specificity in the direction-selectivity circuit of the retina. Nature 471(7337):183–188PubMedCrossRefGoogle Scholar
  11. Bruno RM, Sakmann B (2006) Cortex is driven by weak but synchronously active thalamocortical synapses. Science 312(5780):1622–1627PubMedCrossRefGoogle Scholar
  12. Celikel T, Sakmann B (2007) Sensory integration across space and in time for decision making in the somatosensory system of rodents. Proc Natl Acad Sci USA 104(4):1395–1400PubMedCrossRefGoogle Scholar
  13. de Kock CP, Sakmann B (2009) Spiking in primary somatosensory cortex during natural whisking in awake head-restrained rats is cell-type specific. Proc Natl Acad Sci USA 106(38):16446–16450PubMedCrossRefGoogle Scholar
  14. de Kock CP, Bruno RM, Spors H, Sakmann B (2007) Layer and cell type specific suprathreshold stimulus representation in primary somatosensory cortex. J Physiol 581(1):139–154PubMedCrossRefGoogle Scholar
  15. Denk W, Horstmann H (2004) Serial block-face scanning electron microscopy to reconstruct three-dimensional tissue nanostructure. PLoS Biol 2(11):e329PubMedCrossRefGoogle Scholar
  16. Dercksen VJ, Weber B, Guenther D, Oberlaender M, Prohaska S, Hege HC (2009) Automatic alignment of stacks of filament data. IEEE Int Symp on Biomedical Imaging: From Nano to Macro (ISBI) 971–974Google Scholar
  17. Dercksen VJ, Egger R, Hege HC, Oberlaender M (2012a) Synaptic connectivity in anatomically realistic neural networks: modeling and visual analysis. In: Eurographics workshop on visual computing for biology and medicineGoogle Scholar
  18. Dercksen VJ, Oberlaender M, Sakmann B, Hege HC (2012b) Interactive visualization: a key prerequisite for reconstruction of anatomically realistic neural networks. In: Proceedings of the 2009 workshop on visualization in medicine and life sciences (VMLS 09)Google Scholar
  19. Destexhe A, Mainen ZF, Sejnowski TJ (1994) Synthesis of models for excitable membranes, synaptic transmission and neuromodulation using a common kinetic formalism. J Comp Neurosci 1(3):195–230Google Scholar
  20. Egger R, Narayanan RT, Helmstaedter M, de Kock CP, Oberlaender M (2012) 3D reconstruction and standardization of the rat vibrissal cortex for precise registration of single neuron moprhology. PLoS Comput Biol 8(12):1–18CrossRefGoogle Scholar
  21. Feldmeyer D, Lubke J, Silver RA, Sakmann B (2002) Synaptic connections between layer 4 spiny neurone-layer 2/3 pyramidal cell pairs in juvenile rat barrel cortex: physiology and anatomy of interlaminar signalling within a cortical column. J Physiol 538(Pt 3):803–822PubMedCrossRefGoogle Scholar
  22. Grewe BF, Helmchen F (2009) Optical probing of neuronal ensemble activity. Curr Opin Neurobiol 19(5):520–529PubMedCrossRefGoogle Scholar
  23. Groh A, de Kock CP, Wimmer VC, Sakmann B, Kuner T (2008) Driver or coincidence detector: modal switch of a corticothalamic giant synapse controlled by spontaneous activity and short-term depression. J Neurosci 28(39):9652–9663PubMedCrossRefGoogle Scholar
  24. Groh A, Meyer HS, Schmidt EF, Heintz N, Sakmann B, Krieger P (2010) Cell-type specific properties of pyramidal neurons in neocortex underlying a layout that is modifiable depending on the cortical area. Cereb Cortex 20(4):826–836PubMedCrossRefGoogle Scholar
  25. Hay E, Hill S, Schurmann F, Markram H, Segev I (2011) Models of neocortical layer 5b pyramidal cells capturing a wide range of dendritic and perisomatic active properties. PLoS Comput Biol 7(7):e1002107PubMedCrossRefGoogle Scholar
  26. Helmstaedter M, Briggman KL, Denk W (2008) 3D structural imaging of the brain with photons and electrons. Curr Opin Neurobiol 18(6):633–641PubMedCrossRefGoogle Scholar
  27. Helmstaedter M, Sakmann B, Feldmeyer D (2009) The relation between dendritic geometry, electrical excitability, and axonal projections of L2/3 interneurons in rat barrel cortex. Cereb Cortex 19(4):938–950Google Scholar
  28. Hill DN, Curtis JC, Moore JD, Kleinfeld D (2011) Primary motor cortex reports efferent control of vibrissa motion on multiple timescales. Neuron 72(2):344–356PubMedCrossRefGoogle Scholar
  29. Holmes WR, Rall W (1992) Estimating the electrotonic structure of neurons with compartmental models. J Neurophysiol 68(4):1438–1452PubMedGoogle Scholar
  30. Horikawa K, Armstrong WE (1988) A versatile means of intracellular labeling: injection of biocytin and its detection with avidin conjugates. J Neurosci Methods 25(1):1–11PubMedCrossRefGoogle Scholar
  31. Hubel DH, Wiesel TN (1959) Receptive fields of single neurones in the cat’s striate cortex. J Physiol 148:574–591PubMedGoogle Scholar
  32. Hutson KA, Masterton RB (1986) The sensory contribution of a single vibrissa’s cortical barrel. J Neurophysiol 56(4):1196–1223PubMedGoogle Scholar
  33. Kerr JN, de Kock CP, Greenberg DS, Bruno RM, Sakmann B, Helmchen F (2007) Spatial organization of neuronal population responses in layer 2/3 of rat barrel cortex. J Neurosci 27(48):13316–13328PubMedCrossRefGoogle Scholar
  34. Kozloski J, Sfyrakis K, Hill S, Schurmann F, Peck C, Markram H (2008) Identifying, tabulating, and analyzing contacts between branched neuron morphologies. IBM J Res Dev 52(1–2):43–55CrossRefGoogle Scholar
  35. Land PW, Buffer SA Jr, Yaskosky JD (1995) Barreloids in adult rat thalamus: three-dimensional architecture and relationship to somatosensory cortical barrels. J Comp Neurol 355(4):573–588PubMedCrossRefGoogle Scholar
  36. Lang S, Dercksen VJ, Sakmann B, Oberlaender M (2011) Simulation of signal flow in 3D reconstructions of an anatomically realistic neural network in rat vibrissal cortex. Neural Netw 24(9):998–1011PubMedCrossRefGoogle Scholar
  37. Margrie TW, Brecht M, Sakmann B (2002) In vivo, low-resistance, whole-cell recordings from neurons in the anaesthetized and awake mammalian brain. Pflugers Arch 444(4):491–498PubMedCrossRefGoogle Scholar
  38. Martinez LM, Wang Q, Reid RC, Pillai C, Alonso JM, Sommer FT, Hirsch JA (2005) Receptive field structure varies with layer in the primary visual cortex. Nat Neurosci 8(3):372–379PubMedCrossRefGoogle Scholar
  39. Meyer HS, Wimmer VC, Hemberger M, Bruno RM, de Kock CP, Frick A, Sakmann B, Helmstaedter M (2010a) Cell type-specific thalamic innervation in a column of rat vibrissal cortex. Cereb Cortex 20(10):2287–2303PubMedCrossRefGoogle Scholar
  40. Meyer HS, Wimmer VC, Oberlaender M, de Kock CP, Sakmann B, Helmstaedter M (2010b) Number and laminar distribution of neurons in a thalamocortical projection column of rat vibrissal cortex. Cereb Cortex 20(10):2277–2286PubMedCrossRefGoogle Scholar
  41. Meyer HS, Schwarz D, Wimmer VC, Schmitt AC, Kerr JN, Sakmann B, Helmstaedter M (2011) Inhibitory interneurons in a cortical column form hot zones of inhibition in layers 2 and 5A. Proc Natl Acad Sci USA 108(40):16807–16812PubMedCrossRefGoogle Scholar
  42. Meyer HS, Egger R, Guest JM, Foerster R, Reissl S, Oberlaender M (in press) The cellular organization of cortical barrel columns is whisker-specific. Proc Natl Acad Sci USAGoogle Scholar
  43. Mishchenko Y, Hu T, Spacek J, Mendenhall J, Harris KM, Chklovskii DB (2010) Ultrastructural analysis of hippocampal neuropil from the connectomics perspective. Neuron 67(6):1009–1020PubMedCrossRefGoogle Scholar
  44. Mountcastle VB (1957) Modality and topographic properties of single neurons of cat’s somatic sensory cortex. J Neurophysiol 20(4):408–434PubMedGoogle Scholar
  45. Oberlaender M, Bruno RM, Sakmann B, Broser PJ (2007) Transmitted light brightfield mosaic microscopy for three-dimensional tracing of single neuron morphology. J Biomed Opt 12(6):064029PubMedCrossRefGoogle Scholar
  46. Oberlaender M, Broser PJ, Sakmann B, Hippler S (2009a) Shack-Hartmann wave front measurements in cortical tissue for deconvolution of large three-dimensional mosaic transmitted light brightfield micrographs. J Microsc 233(2):275–289PubMedCrossRefGoogle Scholar
  47. Oberlaender M, Dercksen VJ, Egger R, Gensel M, Sakmann B, Hege HC (2009b) Automated three-dimensional detection and counting of neuron somata. J Neurosci Methods 180(1):147–160PubMedCrossRefGoogle Scholar
  48. Oberlaender M, Boudewijns ZS, Kleele T, Mansvelder HD, Sakmann B, de Kock CP (2011) Three-dimensional axon morphologies of individual layer 5 neurons indicate cell type-specific intracortical pathways for whisker motion and touch. Proc Natl Acad Sci USA 108(10):4188–4193PubMedCrossRefGoogle Scholar
  49. Oberlaender M, de Kock CP, Bruno RM, Ramirez A, Meyer HS, Dercksen VJ, Helmstaedter M, Sakmann B (2012a) Cell type-specific three-dimensional structure of thalamocortical circuits in a column of rat vibrissal cortex. Cereb Cortex 22(10):2375–2391Google Scholar
  50. Oberlaender M, Ramirez A, Bruno RM (2012b) Sensory experience restructures thalamocortical axons during adulthood. Neuron 74(4):648–655PubMedCrossRefGoogle Scholar
  51. O’Connor DH, Clack NG, Huber D, Komiyama T, Myers EW, Svoboda K (2010a) Vibrissa-based object localization in head-fixed mice. J Neurosci 30(5):1947–1967PubMedCrossRefGoogle Scholar
  52. O’Connor DH, Peron SP, Huber D, Svoboda K (2010b) Neural activity in barrel cortex underlying vibrissa-based object localization in mice. Neuron 67(6):1048–1061PubMedCrossRefGoogle Scholar
  53. Petreanu L, Mao T, Sternson SM, Svoboda K (2009) The subcellular organization of neocortical excitatory connections. Nature 457(7233):1142–1145PubMedCrossRefGoogle Scholar
  54. Pinault D (1996) A novel single-cell staining procedure performed in vivo under electrophysiological control: morpho-functional features of juxtacellularly labeled thalamic cells and other central neurons with biocytin or neurobiotin. J Neurosci Methods 65(2):113–136PubMedCrossRefGoogle Scholar
  55. Poulet JF, Petersen CC (2008) Internal brain state regulates membrane potential synchrony in barrel cortex of behaving mice. Nature 454(7206):881–885PubMedCrossRefGoogle Scholar
  56. Sakata S, Harris KD (2009) Laminar structure of spontaneous and sensory-evoked population activity in auditory cortex. Neuron 64(3):404–418PubMedCrossRefGoogle Scholar
  57. Sarid L, Bruno R, Sakmann B, Segev I, Feldmeyer D (2007) Modeling a layer 4-to-layer 2/3 module of a single column in rat neocortex: interweaving in vitro and in vivo experimental observations. Proc Natl Acad Sci USA 104(41):16353–16358PubMedCrossRefGoogle Scholar
  58. Schaefer AT, Larkum ME, Sakmann B, Roth A (2003) Coincidence detection in pyramidal neurons is tuned by their dendritic branching pattern. J Neurophysiol 89(6):3143–3154PubMedCrossRefGoogle Scholar
  59. Simons DJ, Carvell GE, Hershey AE, Bryant DP (1992) Responses of barrel cortex neurons in awake rats and effects of urethane anesthesia. Exp Brain Res 91(2):259–272PubMedCrossRefGoogle Scholar
  60. Staiger JF, Flagmeyer I, Schubert D, Zilles K, Kotter R, Luhmann HJ (2004) Functional diversity of layer IV spiny neurons in rat somatosensory cortex: quantitative morphology of electrophysiologically characterized and biocytin labeled cells. Cereb Cortex 14(6):690–701PubMedCrossRefGoogle Scholar
  61. Svoboda K, Denk W, Kleinfeld D, Tank DW (1997) In vivo dendritic calcium dynamics in neocortical pyramidal neurons. Nature 385(6612):161–165PubMedCrossRefGoogle Scholar
  62. Wallace DJ, Sakmann B (2008) Plasticity of representational maps in somatosensory cortex observed by in vivo voltage-sensitive dye imaging. Cereb Cortex 18(6):1361–1373PubMedCrossRefGoogle Scholar
  63. Welker C (1976) Receptive fields of barrels in the somatosensory neocortex of the rat. J Comp Neurol 166(2):173–189PubMedCrossRefGoogle Scholar
  64. White EL (1979) Thalamocortical synaptic relations: a review with emphasis on the projections of specific thalamic nuclei to the primary sensory areas of the neocortex. Brain Res 180(3):275–311PubMedGoogle Scholar
  65. Woolsey TA, Van der Loos H (1970) The structural organization of layer IV in the somatosensory region (SI) of mouse cerebral cortex. The description of a cortical field composed of discrete cytoarchitectonic units. Brain Res 17(2):205–242PubMedCrossRefGoogle Scholar
  66. Yu C, Derdikman D, Haidarliu S, Ahissar E (2006) Parallel thalamic pathways for whisking and touch signals in the rat. PLoS Biol 4(5):e124PubMedCrossRefGoogle Scholar

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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