Article

The logic of single-cell projections from visual cortex

  • Nature volume 556, pages 5156 (05 April 2018)
  • doi:10.1038/nature26159
  • Download Citation
Received:
Accepted:
Published:

Abstract

Neocortical areas communicate through extensive axonal projections, but the logic of information transfer remains poorly understood, because the projections of individual neurons have not been systematically characterized. It is not known whether individual neurons send projections only to single cortical areas or distribute signals across multiple targets. Here we determine the projection patterns of 591 individual neurons in the mouse primary visual cortex using whole-brain fluorescence-based axonal tracing and high-throughput DNA sequencing of genetically barcoded neurons (MAPseq). Projections were highly diverse and divergent, collectively targeting at least 18 cortical and subcortical areas. Most neurons targeted multiple cortical areas, often in non-random combinations, suggesting that sub-classes of intracortical projection neurons exist. Our results indicate that the dominant mode of intracortical information transfer is not based on ‘one neuron–one target area’ mapping. Instead, signals carried by individual cortical neurons are shared across subsets of target areas, and thus concurrently contribute to multiple functional pathways.

  • Subscribe to Nature for full access:

    $199

    Subscribe

Additional access options:

Already a subscriber?  Log in  now or  Register  for online access.

Accessions

Primary accessions

Sequence Read Archive

References

  1. 1.

    & The neocortical circuit: themes and variations. Nat. Neurosci. 18, 170–181 (2015)

  2. 2.

    , , & The modular organization of projections from areas V1 and V2 to areas V4 and TEO in macaques. J. Neurosci. 13, 3681–3691 (1993)

  3. 3.

    & Comparison of the distributions of ipsilaterally and contralaterally projecting corticocortical neurons in cat visual cortex using two fluorescent tracers. J. Neurosci. 5, 2107–2118 (1985)

  4. 4.

    Collateral branching of long-distance cortical projections in monkey. J. Comp. Neurol. 521, 4112–4123 (2013)

  5. 5.

    & Independent projection streams from macaque striate cortex to the second visual area and middle temporal area. J. Neurosci. 23, 5684–5692 (2003)

  6. 6.

    et al. Membrane potential dynamics of neocortical projection neurons driving target-specific signals. Neuron 80, 1477–1490 (2013)

  7. 7.

    , , & Cortico-cortical projections in mouse visual cortex are functionally target specific. Nat. Neurosci. 16, 219–226 (2013)

  8. 8.

    & The functional properties of barrel cortex neurons projecting to the primary motor cortex. J. Neurosci. 30, 4256–4260 (2010)

  9. 9.

    , , , & Behaviour-dependent recruitment of long-range projection neurons in somatosensory cortex. Nature 499, 336–340 (2013)

  10. 10.

    & Target-specific membrane potential dynamics of neocortical projection neurons during goal-directed behavior. eLife 5, e15798 (2016)

  11. 11.

    & Visual response properties of striate cortical neurons projecting to area MT in macaque monkeys. J. Neurosci. 16, 7733–7741 (1996)

  12. 12.

    & Parallel processing strategies of the primate visual system. Nat. Rev. Neurosci. 10, 360–372 (2009)

  13. 13.

    , , , & Functional specialization of mouse higher visual cortical areas. Neuron 72, 1025–1039 (2011)

  14. 14.

    , , & Functional specialization of seven mouse visual cortical areas. Neuron 72, 1040–1054 (2011). 8

  15. 15.

    ., & in Axons and Brain Architecture (ed.) Ch. 5, 93–116 (Academic, 2016)

  16. 16.

    & Axonal bifurcation in the visual system. Trends Neurosci. 10, 205–210 (1987)

  17. 17.

    et al. A platform for brain-wide imaging and reconstruction of individual neurons. eLife 5, e10566 (2016)

  18. 18.

    , & Morphology and connections of neurons in area 17 projecting to the extrastriate areas MT and 19DM and to the superior colliculus in the monkey Callithrix jacchus. J. Comp. Neurol. 362, 233–255 (1995)

  19. 19.

    , & Inferior parietal lobule projections to the presubiculum and neighboring ventromedial temporal cortical areas. J. Comp. Neurol. 425, 510–530 (2000)

  20. 20.

    et al. Neural networks of the mouse neocortex. Cell 156, 1096–1111 (2014)

  21. 21.

    et al. A mesoscale connectome of the mouse brain. Nature 508, 207–214 (2014)

  22. 22.

    & Area map of mouse visual cortex. J. Comp. Neurol. 502, 339–357 (2007)

  23. 23.

    et al. Serial two-photon tomography for automated ex vivo mouse brain imaging. Nat. Methods 9, 255–258 (2012)

  24. 24.

    & Mapping brain circuitry with a light microscope. Nat. Methods 10, 515–523 (2013)

  25. 25.

    et al. Genome-wide atlas of gene expression in the adult mouse brain. Nature 445, 168–176 (2007)

  26. 26.

    , , , & Recruitment of inhibition and excitation across mouse visual cortex depends on the hierarchy of interconnecting areas. eLife 5, e19332 (2016)

  27. 27.

    , , , & Distinct balance of excitation and inhibition in an interareal feedforward and feedback circuit of mouse visual cortex. J. Neurosci. 33, 17373–17384 (2013)

  28. 28.

    et al. An extended retinotopic map of mouse cortex. eLife 6, e18372 (2017)

  29. 29.

    et al. High-throughput dual-colour precision imaging for brain-wide connectome with cytoarchitectonic landmarks at the cellular level. Nat. Commun. 7, 12142 (2016)

  30. 30.

    et al. High-throughput mapping of single-neuron projections by sequencing of barcoded RNA. Neuron 91, 975–987 (2016)

  31. 31.

    , & Network analysis of corticocortical connections reveals ventral and dorsal processing streams in mouse visual cortex. J. Neurosci. 32, 4386–4399 (2012)

  32. 32.

    , , , & Stream-dependent development of higher visual cortical areas. Nat. Neurosci. 20, 200–208 (2017)

  33. 33.

    , & Functional segregation and development of mouse higher visual areas. J. Neurosci. 37, 9424–9437 (2017)

  34. 34.

    , , & Experience-dependent specialization of receptive field surround for selective coding of natural scenes. Neuron 84, 457–469 (2014)

  35. 35.

    , & ScanImage: flexible software for operating laser scanning microscopes. Biomed. Eng. Online 2, 13 (2003)

  36. 36.

    , & Knife-edge scanning microscopy for imaging and reconstruction of three-dimensional anatomical structures of the mouse brain. J. Microsc. 231, 134–143 (2008)

  37. 37.

    et al. aMAP is a validated pipeline for registration and segmentation of high-resolution mouse brain data. Nat. Commun. 7, 11879 (2016)

  38. 38.

    , , , & P. elastix: a toolbox for intensity-based medical image registration. IEEE Trans. Med. Imaging 29, 196–205 (2010)

  39. 39.

    et al. Whole-brain mapping of neuronal activity in the learned helplessness model of depression. Front. Neural Circuits 10, 3 (2016)

  40. 40.

    et al. Mapping of brain activity by automated volume analysis of immediate early genes. Cell 165, 1789–1802 (2016)

  41. 41.

    et al. Thalamic nuclei convey diverse contextual information to layer 1 of visual cortex. Nat. Neurosci. 19, 299–307 (2016)

  42. 42.

    & A calcium chloride solution, dry-ice, low temperature bath. J. Chem. Educ. 47, 361 (1970)

  43. 43.

    , & Transcriptome analysis of single cells. J. Vis. Exp. 50, e2634 (2011)

Download references

Acknowledgements

We thank A. Juavinett, L. Huang, S. Hofer and P. Znamenskiy for comments on the manuscript. This study was funded by National Institutes of Health (5RO1NS073129 and 5RO1DA036913 to A.M.Z.); Brain Research Foundation (BRF-SIA-2014-03 to A.M.Z.); IARPA (MICrONS D16PC0008 to A.M.Z.); Simons Foundation (382793/SIMONS to A.M.Z.); Paul Allen Distinguished Investigator Award (to A.M.Z.); PhD fellowship from the Boehringer Ingelheim Fonds (to J.M.K.); PhD fellowship from the Genentech Foundation (to J.M.K.); National Natural Science Foundation of China (NSFC 31600847 to Y.H.); European Research Council (NeuroV1sion 616509 to T.D.M.-F.), and Swiss National Science Foundation (SNSF 31003A_169802 to T.D.M.-F.).

Author information

Author notes

    • Yunyun Han
    • , Justus M. Kebschull
    •  & Robert A. A. Campbell

    These authors contributed equally to this work.

    • Anthony M. Zador
    •  & Thomas D. Mrsic-Flogel

    These authors jointly supervised this work.

Affiliations

  1. Department of Neurobiology, School of Basic Medicine and Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China

    • Yunyun Han
  2. Institute for Brain Research, Collaborative Innovation Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China

    • Yunyun Han
  3. Biozentrum, University of Basel, 4056 Basel, Switzerland

    • Yunyun Han
    • , Robert A. A. Campbell
    • , Devon Cowan
    • , Fabia Imhof
    •  & Thomas D. Mrsic-Flogel
  4. Watson School of Biological Sciences, Cold Spring Harbor, New York, USA

    • Justus M. Kebschull
  5. Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA

    • Justus M. Kebschull
    •  & Anthony M. Zador
  6. Sainsbury Wellcome Centre, University College London, London, UK

    • Thomas D. Mrsic-Flogel

Authors

  1. Search for Yunyun Han in:

  2. Search for Justus M. Kebschull in:

  3. Search for Robert A. A. Campbell in:

  4. Search for Devon Cowan in:

  5. Search for Fabia Imhof in:

  6. Search for Anthony M. Zador in:

  7. Search for Thomas D. Mrsic-Flogel in:

Contributions

Y.H. generated the dataset for fluorescence-based axonal tracing. D.C. and Y.H. traced the cells. R.A.A.C. analysed the serial two-photon imaging data and axonal projection patterns. J.M.K. and F.I. collected the MAPseq dataset. J.M.K. and A.M.Z. performed the analysis of projection patterns. J.M.K., T.D.M.-F. and A.M.Z. wrote the paper.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Anthony M. Zador or Thomas D. Mrsic-Flogel.

Reviewer Information Nature thanks M. Helmstaedter, O. Sporns and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Supplementary information

PDF files

  1. 1.

    Supplementary Information

    This file contains Supplementary Notes 1-4, Supplementary Table 1 and Supplementary References.

  2. 2.

    Life Sciences Reporting Summary

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.