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.

  • Article
  • Published:

Stream-dependent development of higher visual cortical areas

Abstract

Multiple cortical areas contribute to visual processing in mice. However, the functional organization and development of higher visual areas are unclear. Here we used intrinsic signal optical imaging and two-photon calcium imaging to map visual responses in adult and developing mice. We found that visually driven activity was well correlated among higher visual areas within two distinct subnetworks resembling the dorsal and ventral visual streams. Visual response magnitude in dorsal stream areas slowly increased over the first 2 weeks of visual experience. By contrast, ventral stream areas exhibited strong responses shortly after eye opening. Neurons in a dorsal stream area showed little change in their tuning sharpness to oriented gratings while those in a ventral stream area increased stimulus selectivity and expanded their receptive fields significantly. Together, these findings provide a functional basis for grouping subnetworks of mouse visual areas and revealed stream differences in the development of receptive field properties.

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

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

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

Figure 1: Mapping and functional grouping of putative dorsal and ventral stream higher visual areas (HVAs) in mice.
Figure 2: Functional responses in dorsal stream areas develop more slowly and are more dependent on experience than in ventral stream areas.
Figure 3: Visually evoked responses were validated by correlating ISOI signals with action-potential-associated 2p Ca2+ signals measured in the same mice.
Figure 4: Response magnitude increases in areas PM and LM from P20 to P36 measure with 2p Ca2+ imaging.
Figure 5: Orientation tuning changes in areas V1, LM and PM from P20 to P36.
Figure 6: Receptive field subregion changes in areas V1, LM and PM from P20 to P36.

Similar content being viewed by others

References

  1. Wang, Q. & Burkhalter, A. Area map of mouse visual cortex. J. Comp. Neurol. 502, 339–357 (2007).

    Article  PubMed  Google Scholar 

  2. Wang, Q., Gao, E. & Burkhalter, A. Gateways of ventral and dorsal streams in mouse visual cortex. J. Neurosci. 31, 1905–1918 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Wang, Q., Sporns, O. & Burkhalter, A. Network analysis of corticocortical connections reveals ventral and dorsal processing streams in mouse visual cortex. J. Neurosci. 32, 4386–4399 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Liu, Y.J. et al. Tracing inputs to inhibitory or excitatory neurons of mouse and cat visual cortex with a targeted rabies virus. Curr. Biol. 23, 1746–1755 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Coogan, T.A. & Burkhalter, A. Hierarchical organization of areas in rat visual cortex. J. Neurosci. 13, 3749–3772 (1993).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Montero, V.M. Retinotopy of cortical connections between the striate cortex and extrastriate visual areas in the rat. Exp. Brain Res. 94, 1–15 (1993).

    Article  CAS  PubMed  Google Scholar 

  7. Mishkin, M. & Ungerleider, L.G. Contribution of striate inputs to the visuospatial functions of parieto-preoccipital cortex in monkeys. Behav. Brain Res. 6, 57–77 (1982).

    Article  CAS  PubMed  Google Scholar 

  8. Mishkin, M. & Ungerleider, L.G. Two cortical visual systems. in Analysis of Visual Behavior (ed. Ingle, D.J.E.A.) 549–586 (MIT Press, 1982).

  9. Newsome, W.T. & Paré, E.B. A selective impairment of motion perception following lesions of the middle temporal visual area (MT). J. Neurosci. 8, 2201–2211 (1988).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Barton, J.J. Disorders of higher visual processing. Handb. Clin. Neurol. 102, 223–261 (2011).

    Article  PubMed  Google Scholar 

  11. Wang, Q. & Burkhalter, A. Stream-related preferences of inputs to the superior colliculus from areas of dorsal and ventral streams of mouse visual cortex. J. Neurosci. 33, 1696–1705 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. De Pasquale, R. & Sherman, S.M. A modulatory effect of the feedback from higher visual areas to V1 in the mouse. J. Neurophysiol. 109, 2618–2631 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. De Pasquale, R. & Sherman, S.M. Modulatory effects of metabotropic glutamate receptors on local cortical circuits. J. Neurosci. 32, 7364–7372 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. De Pasquale, R. & Sherman, S.M. Synaptic properties of corticocortical connections between the primary and secondary visual cortical areas in the mouse. J. Neurosci. 31, 16494–16506 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Ji, W. et al. Modularity in the organization of mouse primary visual cortex. Neuron 87, 632–643 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Sherman, S.M. The function of metabotropic glutamate receptors in thalamus and cortex. Neuroscientist 20, 136–149 (2014).

    Article  PubMed  Google Scholar 

  17. Sherman, S.M. Thalamus plays a central role in ongoing cortical functioning. Nat. Neurosci. 19, 533–541 (2016).

    Article  CAS  PubMed  Google Scholar 

  18. Marshel, J.H., Garrett, M.E., Nauhaus, I. & Callaway, E.M. Functional specialization of seven mouse visual cortical areas. Neuron 72, 1040–1054 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Andermann, M.L., Kerlin, A.M., Roumis, D.K., Glickfeld, L.L. & Reid, R.C. Functional specialization of mouse higher visual cortical areas. Neuron 72, 1025–1039 (2011).

    Article  CAS  PubMed  Google Scholar 

  20. Glickfeld, L.L., Andermann, M.L., Bonin, V. & Reid, R.C. Cortico-cortical projections in mouse visual cortex are functionally target specific. Nat. Neurosci. 16, 219–226 (2013).

    Article  CAS  PubMed  Google Scholar 

  21. Gao, E., DeAngelis, G.C. & Burkhalter, A.H. Specialized areas for shape and motion analysis in mouse visual cortex. in Society for Neuroscience Annual Meeting 32, 641.6 (2006).

    Google Scholar 

  22. Juavinett, A.L. & Callaway, E.M. Pattern and component motion responses in mouse visual cortical areas. Curr. Biol. 25, 1759–1764 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Tohmi, M., Takahashi, K., Kubota, Y., Hishida, R. & Shibuki, K. Transcranial flavoprotein fluorescence imaging of mouse cortical activity and plasticity. J. Neurochem. 109 (Suppl. 1), 3–9 (2009).

    Article  CAS  PubMed  Google Scholar 

  24. Garrett, M.E., Nauhaus, I., Marshel, J.H. & Callaway, E.M. Topography and areal organization of mouse visual cortex. J. Neurosci. 34, 12587–12600 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Pisauro, M.A., Dhruv, N.T., Carandini, M. & Benucci, A. Fast hemodynamic responses in the visual cortex of the awake mouse. J. Neurosci. 33, 18343–18351 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Smith, S.L. & Trachtenberg, J.T. The refinement of ipsilateral eye retinotopic maps is increased by removing the dominant contralateral eye in adult mice. PLoS One 5, e9925 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  27. Zuo, Y., Lin, A., Chang, P. & Gan, W.B. Development of long-term dendritic spine stability in diverse regions of cerebral cortex. Neuron 46, 181–189 (2005).

    Article  CAS  PubMed  Google Scholar 

  28. Smith, S.L. & Trachtenberg, J.T. Experience-dependent binocular competition in the visual cortex begins at eye opening. Nat. Neurosci. 10, 370–375 (2007).

    Article  CAS  PubMed  Google Scholar 

  29. Kalatsky, V.A. & Stryker, M.P. New paradigm for optical imaging: temporally encoded maps of intrinsic signal. Neuron 38, 529–545 (2003).

    Article  CAS  PubMed  Google Scholar 

  30. Cang, J. et al. Development of precise maps in visual cortex requires patterned spontaneous activity in the retina. Neuron 48, 797–809 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Schuett, S., Bonhoeffer, T. & Hübener, M. Mapping retinotopic structure in mouse visual cortex with optical imaging. J. Neurosci. 22, 6549–6559 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Rochefort, N.L. et al. Development of direction selectivity in mouse cortical neurons. Neuron 71, 425–432 (2011).

    Article  CAS  PubMed  Google Scholar 

  33. Smith, S.L. & Häusser, M. Parallel processing of visual space by neighboring neurons in mouse visual cortex. Nat. Neurosci. 13, 1144–1149 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Kremkow, J., Jin, J., Wang, Y. & Alonso, J.M. Principles underlying sensory map topography in primary visual cortex. Nature 533, 52–57 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. van den Boomen, C., van der Smagt, M.J. & Kemner, C. Keep your eyes on development: the behavioral and neurophysiological development of visual mechanisms underlying form processing. Front. Psychiatry 3, 16 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Ko, H. et al. The emergence of functional microcircuits in visual cortex. Nature 496, 96–100 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Braddick, O., Atkinson, J. & Wattam-Bell, J. Normal and anomalous development of visual motion processing: motion coherence and 'dorsal-stream vulnerability'. Neuropsychologia 41, 1769–1784 (2003).

    Article  PubMed  Google Scholar 

  38. Spencer, J. et al. Motion processing in autism: evidence for a dorsal stream deficiency. Neuroreport 11, 2765–2767 (2000).

    Article  CAS  PubMed  Google Scholar 

  39. Tohmi, M., Meguro, R., Tsukano, H., Hishida, R. & Shibuki, K. The extrageniculate visual pathway generates distinct response properties in the higher visual areas of mice. Curr. Biol. 24, 587–597 (2014).

    Article  CAS  PubMed  Google Scholar 

  40. Hoy, J.L. & Niell, C.M. Layer-specific refinement of visual cortex function after eye opening in the awake mouse. J. Neurosci. 35, 3370–3383 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Vorobyov, V., Kwok, J.C., Fawcett, J.W. & Sengpiel, F. Effects of digesting chondroitin sulfate proteoglycans on plasticity in cat primary visual cortex. J. Neurosci. 33, 234–243 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Ellemberg, D., Lewis, T.L., Maurer, D., Brar, S. & Brent, H.P. Better perception of global motion after monocular than after binocular deprivation. Vision Res. 42, 169–179 (2002).

    Article  PubMed  Google Scholar 

  43. Le Grand, R., Mondloch, C.J., Maurer, D. & Brent, H.P. Neuroperception. Early visual experience and face processing. Nature 410, 890 (2001).

    Article  CAS  PubMed  Google Scholar 

  44. Le Grand, R., Mondloch, C.J., Maurer, D. & Brent, H.P. Expert face processing requires visual input to the right hemisphere during infancy. Nat. Neurosci. 6, 1108–1112 (2003).

    Article  CAS  PubMed  Google Scholar 

  45. Ebert, D.H. & Greenberg, M.E. Activity-dependent neuronal signalling and autism spectrum disorder. Nature 493, 327–337 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Association, A.P. Diagnostic and Statistical Manual of Mental Disorders 5th edn. (American Psychiatric Publishing, Arlington, VA, 2013).

  47. Kogan, C.S. et al. Differential impact of the FMR1 gene on visual processing in fragile X syndrome. Brain 127, 591–601 (2004).

    Article  PubMed  Google Scholar 

  48. Brainard, D.H. The psychophysics toolbox. Spat. Vis. 10, 433–436 (1997).

    Article  CAS  PubMed  Google Scholar 

  49. Pelli, D.G. The VideoToolbox software for visual psychophysics: transforming numbers into movies. Spat. Vis. 10, 437–442 (1997).

    Article  CAS  PubMed  Google Scholar 

  50. Smith, S.L., Smith, I.T., Branco, T. & Häusser, M. Dendritic spikes enhance stimulus selectivity in cortical neurons in vivo. Nature 503, 115–120 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Pologruto, T.A., Sabatini, B.L. & Svoboda, K. ScanImage: flexible software for operating laser scanning microscopes. Biomed. Eng. Online 2, 13 (2003).

    PubMed  PubMed Central  Google Scholar 

  52. Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012).

    Article  CAS  PubMed  Google Scholar 

  53. Cottam, J.C., Smith, S.L. & Häusser, M. Target-specific effects of somatostatin-expressing interneurons on neocortical visual processing. J. Neurosci. 33, 19567–19578 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We are grateful to D. Ferster for generously providing software for intrinsic signal optical imaging and to J. Stirman for customizing the software for these experiments. We thank B. Philpot, P. Manis and J. Stirman for discussion and comments on the manuscript and C. Mazzone for early contributions to the project. I.T.S. was supported by a Helen Lyng White Fellowship. L.B.S. was supported by a fellowship from the Howard Hughes Medical Institute/UNC-Chapel Hill Med into Grad program and by the NIH (T32NS007431). Work by R.H. and H.Z. was partially supported by the NIH (MH086633) and the NSF (SES-1357666 and DMS-1407655). This work was supported by a Career Development Award from the Human Frontier Science Program to S.L.S. (CDA 00063/2012) and by grants from the Whitehall Foundation and the NIH (R01EY024294, R01NS091335) (S.L.S.).

Author information

Authors and Affiliations

Authors

Contributions

I.T.S. and S.L.S. conceived and designed the experiments. I.T.S. and L.B.T. performed the intrinsic signal optical imaging experiments and analyzed data. I.T.S. and S.L.S. performed the calcium imaging experiments and analyzed data. R.H. and H.Z. performed some of the statistical analysis. I.T.S. and S.L.S. interpreted the data and wrote the paper.

Corresponding authors

Correspondence to Ikuko T Smith or Spencer L Smith.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Quantifications of responses are reproducible between experts

Two experts (I.T.S. and L.B.T.), blind to the age and conditions, independently quantified the same data set. They drew the boundaries of V1 and HVAs according to the retinotopic maps, and quantified responses to gratings and kinematograms. Their quantifications were highly correlated, demonstrating the robustness of this approach.

Supplementary Figure 2 Activity in HVAs correlates with activity in V1

Visual response magnitudes in HVAs in response to drifting gratings (a) and moving dot kinematograms (b) were well correlated (Pearson’s R) with response magnitudes in V1 within the same maps. All data are from adult mice.

Supplementary Figure 3 Intrinsic signal magnitude as affected by increasing isoflurane concentration

Response magnitude in (a) dorsal stream HVAs and (b) ventral stream HVAs declined with increasing concentrations of isoflurane anesthetic. Normalization of response magnitudes in (c) dorsal stream HVAs and (d) ventral stream HVAs to those in V1 for each map, resulted in measurements that varied less with isoflurane concentration. Shaded region indicates SEM.

Supplementary Figure 4 Skull thickness by age

In mice, the occipital skull rapidly thickens around age P20, which precludes high fidelity transcranial imaging. Thus, for ages beyond P20, chronic or acute craniotomy preparations were made prior to imaging. Shaded region indicates SEM.

Supplementary Figure 5 Developmental time course of individual HVAs

The developmental time course of individual (a) dorsal and (b) ventral stream HVAs shows that the overall trends of dorsal stream HVA development lagging that of ventral stream HVAs are apparent at the single cortical area level. Shaded region indicates SEM.

Supplementary Figure 6 Direction selectivity index changes in areas V1, LM and PM from P20 to P36

(a) Population data for direction selectivity in areas V1, LM, and PM at P20 and P36 for 0.04 cycles/degree and (b) 0.32 cycles/degree gratings are shown. Both cumulative histograms (top rows) and bar graphs (bottom rows; mean ± SEM) are shown for each data set.

Supplementary Figure 7 Additional quantification of RF subregion metrics in areas V1, LM and PM at P20 and P36

(a) Average radius, (b) half long axis, and (c) half short axis measurements for RF subregions in areas V1, LM, and PM at ages P20 and P36. Each box plot indicates the median (thick line), the range of the middle two quartiles (shaded boxes), and the full data range (whiskers).

Supplementary Figure 8 Delay-to-peak responses of receptive field subregions are comparable in areas V1, LM and PM from P20 to P36

In the reverse correlation analysis to recover RF subregions, the time delay between visual stimulus and activity that yielded the strongest RF subregions (measured by Z-score) was similar across areas (V1, LM, and PM), ages (P20 and P36), and subregion signs (ON and OFF). Each box plot indicates the median (thick line), the range of the middle two quartiles (shaded boxes), and the full data range (whiskers).

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–8 and Supplementary Table 1 (PDF 965 kb)

Supplementary Methods Checklist (PDF 497 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Smith, I., Townsend, L., Huh, R. et al. Stream-dependent development of higher visual cortical areas. Nat Neurosci 20, 200–208 (2017). https://doi.org/10.1038/nn.4469

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nn.4469

This article is cited by

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