Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Protocol
  • Published:

Juxtacellular recording and morphological identification of single neurons in freely moving rats

Abstract

It is well established that neural circuits consist of a great diversity of cell types, but very little is known about how neuronal diversity contributes to cognition and behavior. One approach to addressing this problem is to directly link cellular diversity to neuronal activity recorded in vivo in behaving animals. Here we describe the technical procedures for obtaining juxtacellular recordings from single neurons in trained rats engaged in exploratory behavior. The recorded neurons can be labeled to allow subsequent anatomical identification. In its current format, the protocol can be used for resolving the cellular identity of spatially modulated neurons (i.e., head-direction cells and grid cells), which form the basis of the animal's internal representation of space, but this approach can easily be extended to other unrestrained behaviors. The procedures described here, from the beginning of animal training to the histological processing of brain sections, can be completed in 3–4 weeks.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Recording durations.
Figure 2: Implant components for obtaining juxtacellular recordings in freely moving animals.
Figure 3: Assembled implant for juxtacellular recordings in freely moving animals.
Figure 4: Morphological identification of a grid cell.
Figure 5: Morphological identification of a head-direction cell.

Similar content being viewed by others

References

  1. Klausberger, T. & Somogyi, P. Neuronal diversity and temporal dynamics: the unity of hippocampal circuit operations. Science 321, 53–57 (2008).

    Article  CAS  Google Scholar 

  2. Krook-Magnuson, E., Varga, C., Lee, S.H. & Soltesz, I. New dimensions of interneuronal specialization unmasked by principal cell heterogeneity. Trends Neurosci. 35, 175–184 (2012).

    Article  CAS  Google Scholar 

  3. Klausberger, T. et al. Brain-state– and cell-type–specific firing of hippocampal interneurons in vivo. Nature 421, 844–848 (2003).

    Article  CAS  Google Scholar 

  4. Ascoli, G.A. et al. Petilla terminology: nomenclature of features of GABAergic interneurons of the cerebral cortex. Nat. Rev. Neurosci. 9, 557–568 (2008).

    Article  CAS  Google Scholar 

  5. Lee, W.C.A. & Reid, R.C. Specificity and randomness: structure-function relationships in neural circuits. Curr. Opin. Neurobiol. 21, 801–807 (2011).

    Article  CAS  Google Scholar 

  6. Harris, K.D. & Mrsic-Flogel, T.D. Cortical connectivity and sensory coding. Nature 503, 51–8 (2013).

    Article  CAS  Google Scholar 

  7. Varga, C., Lee, S.Y. & Soltesz, I. Target-selective GABAergic control of entorhinal cortex output. Nat. Neurosci. 13, 822–824 (2010).

    Article  CAS  Google Scholar 

  8. Ray, S. et al. Grid-layout and theta-modulation of layer 2 pyramidal neurons in medial entorhinal cortex. Science 343, 891–896 (2014).

    Article  CAS  Google Scholar 

  9. Kerr, J.N.D. et al. Spatial organization of neuronal population responses in layer 2/3 of rat barrel cortex. J. Neurosci. 27, 13316–13328 (2007).

    Article  CAS  Google Scholar 

  10. de Kock, C.P.J. & Sakmann, B. Spiking in primary somatosensory cortex during natural whisking in awake head-restrained rats is cell-type specific. Proc. Natl. Acad. Sci. USA 106, 16446–16450 (2009).

    Article  CAS  Google Scholar 

  11. Dong, H.-W., Swanson, L.W., Chen, L., Fanselow, M.S. & Toga, A.W. Genomic-anatomic evidence for distinct functional domains in hippocampal field CA1. Proc. Natl. Acad. Sci. USA 106, 11794–11799 (2009).

    Article  CAS  Google Scholar 

  12. Thompson, C.L. et al. Genomic anatomy of the hippocampus. Neuron 60, 1010–1021 (2008).

    Article  CAS  Google Scholar 

  13. Kamme, F. et al. Single-cell microarray analysis in hippocampus CA1: demonstration and validation of cellular heterogeneity. J. Neurosci. 23, 3607–3615 (2003).

    Article  CAS  Google Scholar 

  14. Oberlaender, M. et al. 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, 4188–4193 (2011).

    Article  CAS  Google Scholar 

  15. Fenno, L., Yizhar, O. & Deisseroth, K. The development and application of optogenetics. Annu. Rev. Neurosci. 34, 389–412 (2011).

    Article  CAS  Google Scholar 

  16. Zhang, F. et al. Optogenetic interrogation of neural circuits: technology for probing mammalian brain structures. Nat. Protoc. 5, 439–456 (2010).

    Article  CAS  Google Scholar 

  17. Deisseroth, K. & Schnitzer, M.J. Engineering approaches to illuminating brain structure and dynamics. Neuron 80, 568–577 (2013).

    Article  CAS  Google Scholar 

  18. Wang, J. et al. Integrated device for combined optical neuromodulation and electrical recording for chronic in vivo applications. J. Neural Eng. 9, 016001 (2012).

    Article  Google Scholar 

  19. Anikeeva, P. et al. Optetrode: a multichannel readout for optogenetic control in freely moving mice. Nat. Neurosci. 15, 163–170 (2011).

    Article  Google Scholar 

  20. Prakash, R. et al. Two-photon optogenetic toolbox for fast inhibition, excitation and bistable modulation. Nat. Methods 9, 1171–1179 (2012).

    Article  CAS  Google Scholar 

  21. Zhang, F. et al. Multimodal fast optical interrogation of neural circuitry. Nature 446, 633–639 (2007).

    Article  CAS  Google Scholar 

  22. Aravanis, A.M. et al. An optical neural interface: in vivo control of rodent motor cortex with integrated fiber-optic and optogenetic technology. J. Neural Eng. 4, S143–S156 (2007).

    Article  Google Scholar 

  23. Lee, J.H. et al. Global and local fMRI signals driven by neurons defined optogenetically by type and wiring. Nature 465, 788–792 (2010).

    Article  CAS  Google Scholar 

  24. Cardin, J.A. et al. Targeted optogenetic stimulation and recording of neurons in vivo using cell-type-specific expression of channelrhodopsin-2. Nat. Protoc. 5, 247–254 (2010).

    Article  CAS  Google Scholar 

  25. Chung, K. et al. Structural and molecular interrogation of intact biological systems. Nature 497, 332–337 (2013).

    Article  CAS  Google Scholar 

  26. Kepecs, A. & Fishell, G. Interneuron cell types are fit to function. Nature 505, 318–326 (2014).

    Article  CAS  Google Scholar 

  27. Battaglia, D., Karagiannis, A., Gallopin, T., Gutch, H.W. & Cauli, B. Beyond the frontiers of neuronal types. Front. Neural Circuits 7, 13 (2013).

    Article  Google Scholar 

  28. Denk, W., Briggman, K.L. & Helmstaedter, M. Structural neurobiology: missing link to a mechanistic understanding of neural computation. Nat. Rev. Neurosci. 13, 351–358 (2012).

    Article  CAS  Google Scholar 

  29. Lang, S., Dercksen, V.J., Sakmann, B. & Oberlaender, M. Simulation of signal flow in 3D reconstructions of an anatomically realistic neural network in rat vibrissal cortex. Neural Netw. 24, 998–1011 (2011).

    Article  Google Scholar 

  30. Potjans, T.C. & Diesmann, M. The cell-type specific cortical microcircuit: relating structure and activity in a full-scale spiking network model. Cereb. Cortex 24, 785–806 (2014).

    Article  Google Scholar 

  31. Brown, S.P. & Hestrin, S. Cell-type identity: a key to unlocking the function of neocortical circuits. Curr. Opin. Neurobiol. 19, 415–421 (2009).

    Article  CAS  Google Scholar 

  32. Pinault, D. Golgi-like labeling of a single neuron recorded extracellularly. Neurosci. Lett. 170, 255–260 (1994).

    Article  CAS  Google Scholar 

  33. Deschênes, M., Bourassa, J. & Pinault, D. Corticothalamic projections from layer V cells in rat are collaterals of long-range corticofugal axons. Brain Res. 664, 215–219 (1994).

    Article  Google Scholar 

  34. Pinault, D. 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, 113–136 (1996).

    Article  CAS  Google Scholar 

  35. Pinault, D. The juxtacellular recording-labeling technique. In Electrophysiol. Rec. Tech. Neuromethods (eds. Vertes, R.P. & Stackman, R.W. Jr.) 54, 41–75 (Humana Press, 2011).

    Article  Google Scholar 

  36. Pinault, D., Bourassa, J. & Deschenes, M. The axonal arborization of single thalamic reticular neurons in the somatosensory thalamus of the rat. Eur. J. Neurosci. 7, 31–40 (1995).

    Article  CAS  Google Scholar 

  37. Houweling, A. & Brecht, M. Behavioral report of single neurons stimulation in somatosensory cortex. Nature 451, 65–69 (2008).

    Article  CAS  Google Scholar 

  38. Mileykovskiy, B. & Morales, M. Duration of inhibition of ventral tegmental area dopamine neurons encodes a level of conditioned fear. J. Neurosci. 31, 7471–7476 (2011).

    Article  CAS  Google Scholar 

  39. Boucetta, S., Cisse, Y., Mainville, L., Morales, M. & Jones, B.E. Discharge profiles across the sleep-waking cycle of identified cholinergic, GABAergic, and glutamatergic neurons in the pontomesencephalic tegmentum of the rat. J. Neurosci. 34, 4708–4727 (2014).

    Article  Google Scholar 

  40. Pinault, D. & Deschênes, M. Projection and innervation patterns of individual thalamic reticular axons in the thalamus of the adult rat: a three-dimensional, graphic, and morphometric analysis. J. Comp. Neurol. 391, 180–203 (1998).

    Article  CAS  Google Scholar 

  41. Burgalossi, A. et al. Microcircuits of functionally identified neurons in the rat medial entorhinal cortex. Neuron 70, 773–786 (2011).

    Article  CAS  Google Scholar 

  42. Herfst, L. et al. Friction-based stabilization of juxtacellular recordings in freely moving rats. J. Neurophysiol. 108, 697–707 (2012).

    Article  Google Scholar 

  43. Lee, A.K., Epsztein, J. & Brecht, M. Head-anchored whole-cell recordings in freely moving rats. Nat. Protoc. 4, 385–392 (2009).

    Article  CAS  Google Scholar 

  44. Judkewitz, B., Rizzi, M., Kitamura, K. & Häusser, M. Targeted single-cell electroporation of mammalian neurons in vivo. Nat. Protoc. 4, 862–869 (2009).

    Article  CAS  Google Scholar 

  45. Veenman, C.L., Reiner, A. & Honig, M.G. Biotinylated dextran amine as an anterograde tracer for single- and double-labeling studies. J. Neurosci. Methods 41, 239–254 (1992).

    Article  CAS  Google Scholar 

  46. Furuta, T., Kaneko, T. & Deschênes, M. Septal neurons in barrel cortex derive their receptive field input from the lemniscal pathway. J. Neurosci. 29, 4089–4095 (2009).

    Article  CAS  Google Scholar 

  47. Domnisoru, C., Kinkhabwala, A.A. & Tank, D.W. Membrane potential dynamics of grid cells. Nature 495, 199–204 (2013).

    Article  CAS  Google Scholar 

  48. Schwarz, C. et al. The head-fixed behaving rat—procedures and pitfalls. Somatosens. Mot. Res. 27, 131–148 (2010).

    Article  Google Scholar 

  49. Muller, R.U., Kubie, J.L. & Ranck, J.B. Spatial firing patterns of hippocampal complex-spike cells in a fixed environment. J. Neurosci. 7, 1935–1950 (1987).

    Article  CAS  Google Scholar 

  50. Paxinos, G. & Watson, C. The Rat Brain in Stereotaxic Coordinates (Elsevier Science, 2006).

  51. Lee, A.K., Manns, I.D., Sakmann, B. & Brecht, M. Whole-cell recordings in freely moving rats. Neuron 51, 399–407 (2006).

    Article  CAS  Google Scholar 

  52. Mizuseki, K., Sirota, A., Pastalkova, E. & Buzsáki, G. Theta oscillations provide temporal windows for local circuit computation in the entorhinal-hippocampal loop. Neuron 64, 267–280 (2009).

    Article  CAS  Google Scholar 

  53. Horikawa, K. & Armstrong, W.E. A versatile means of intracellular labeling: injection of biocytin and its detection with avidin conjugates. J. Neurosci. Methods 25, 1–11 (1988).

    Article  CAS  Google Scholar 

  54. Huang, Q., Zhou, D. & DiFiglia, M. Neurobiotin, a useful neuroanatomical tracer for in vivo anterograde, retrograde and transneuronal tract-tracing and for in vitro labeling of neurons. J. Neurosci. Methods 41, 31–43 (1992).

    Article  CAS  Google Scholar 

  55. Marx, M., Günter, R.H., Hucko, W., Radnikow, G. & Feldmeyer, D. Improved biocytin labeling and neuronal 3D reconstruction. Nat. Protoc. 7, 394–407 (2012).

    Article  CAS  Google Scholar 

  56. Brecht, M. et al. An isomorphic mapping hypothesis of the grid representation. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 369, 20120521 (2014).

    Article  Google Scholar 

  57. Hafting, T., Fyhn, M., Molden, S., Moser, M.-B. & Moser, E.I. Microstructure of a spatial map in the entorhinal cortex. Nature 436, 801–806 (2005).

    Article  CAS  Google Scholar 

  58. Taube, J.S., Muller, R.U. & Ranck, J.B. Head-direction cells recorded from the postsubiculum in freely moving rats. I. Description and quantitative analysis. J. Neurosci. 10, 420–435 (1990).

    Article  CAS  Google Scholar 

  59. Taube, J.S. The head direction signal: origins and sensory-motor integration. Annu. Rev. Neurosci. 30, 181–207 (2007).

    Article  CAS  Google Scholar 

  60. Moser, E.I., Kropff, E. & Moser, M.-B. Place cells, grid cells, and the brain's spatial representation system. Annu. Rev. Neurosci. 31, 69–89 (2008).

    Article  CAS  Google Scholar 

  61. Moser, E.I. & Moser, M.-B. Grid cells and neural coding in high-end cortices. Neuron 80, 765–774 (2013).

    Article  CAS  Google Scholar 

  62. Canto, C.B. & Witter, M.P. Cellular properties of principal neurons in the rat entorhinal cortex. II. The medial entorhinal cortex. Hippocampus 22, 1277–1299 (2012).

    Article  Google Scholar 

  63. Burgalossi, A. & Brecht, M. Cellular, columnar and modular organization of spatial representations in medial entorhinal cortex. Curr. Opin. Neurobiol. 24, 47–54 (2014).

    Article  CAS  Google Scholar 

  64. Sargolini, F. et al. Conjunctive representation of position, direction, and velocity in entorhinal cortex. Science 312, 758–762 (2006).

    Article  CAS  Google Scholar 

  65. Boccara, C.N. et al. Grid cells in pre- and parasubiculum. Nat. Neurosci. 13, 987–994 (2010).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank A. Stern and M. Kunert (Berlin, Germany) and K. Vollmer (Tübingen, Germany) for excellent fine mechanical support, and U. Schneeweiß and J. Steger for excellent technical support. We are particularly grateful to R. Naumann and S. Ray for histological processing of the cells shown in Figures 4 and 5, U. Schneeweiß for reconstructing the neuron shown in Figure 4a and C. Mende for contributions to figures. We thank G. Doron for comments on earlier versions of the manuscript. This work was supported by Neurocure, the Bernstein Center for Computational Neuroscience (BMBF) and Humboldt University, an EU Biotact-grant and a Neuro-behavior European Research Council grant.

Author information

Authors and Affiliations

Authors

Contributions

A.B. and Q.T. performed experiments in the establishment of the protocol. A.B. and M.B. supervised the experiments. A.B. drafted the manuscript. Q.T., M.B. and A.B. contributed to, and have approved, the final version of the manuscript.

Corresponding authors

Correspondence to Michael Brecht or Andrea Burgalossi.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tang, Q., Brecht, M. & Burgalossi, A. Juxtacellular recording and morphological identification of single neurons in freely moving rats. Nat Protoc 9, 2369–2381 (2014). https://doi.org/10.1038/nprot.2014.161

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nprot.2014.161

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing