1. Felleman, D. J. & Van Essen, D. C. Distributed hierarchical processing in the primate cerebral cortex. Cereb. Cortex 1, 1–47 (1991).

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

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

4. Larkum, M. A cellular mechanism for cortical associations: an organizing principle for the cerebral cortex. Trends Neurosci. 36, 141–151 (2013).

5. Zhang, S. et al. Selective attention. Long-range and local circuits for top-down modulation of visual cortex processing. Science 345, 660–665 (2014).

6. Manita, S. et al. A top-down cortical circuit for accurate sensory perception. Neuron 86, 1304–1316 (2015).

7. Gilbert, C. D. & Li, W. Top-down influences on visual processing. Nat. Rev. Neurosci. 14, 350–363 (2013).

8. Roelfsema, P. R. & de Lange, F. P. Early visual cortex as a multiscale cognitive blackboard. Annu. Rev. Vis. Sci. 2, 131–151 (2016).

9. Angelucci, A. & Bressloff, P. C. Contribution of feedforward, lateral and feedback connections to the classical receptive field center and extra-classical receptive field surround of primate V1 neurons. Prog. Brain Res. 154, 93–120 (2006).

10. Petreanu, L. et al. Activity in motor-sensory projections reveals distributed coding in somatosensation. Nature 489, 299–303 (2012).

11. Makino, H. & Komiyama, T. Learning enhances the relative impact of top-down processing in the visual cortex. Nat. Neurosci. 18, 1116–1122 (2015).

12. Kwon, S. E., Yang, H., Minamisawa, G. & O’Connor, D. H. Sensory and decision-related activity propagate in a cortical feedback loop during touch perception. Nat. Neurosci. 19, 1243–1249 (2016).

13. Rao, R. P. & Ballard, D. H. Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects. Nat. Neurosci. 2, 79–87 (1999).

14. Mumford, D. On the computational architecture of the neocortex. II. The role of cortico-cortical loops. Biol. Cybern. 66, 241–251 (1992).

15. Bastos, A. M. M. A. M. et al. Canonical microcircuits for predictive coding. Neuron 76, 695–711 (2012).

16. Brosch, T., Neumann, H. & Roelfsema, P. R. Reinforcement learning of linking and tracing contours in recurrent neural networks. PLOS Comput. Biol. 11, e1004489 (2015).

17. Barlow, H. B. Why have multiple cortical areas? Vision Res. 26, 81–90 (1986).

18. Angelucci, A. & Bullier, J. Reaching beyond the classical receptive field of V1 neurons: horizontal or feedback axons? J. Physiol. Paris 97, 141–154 (2003).

19. Shmuel, A. et al. Retinotopic axis specificity and selective clustering of feedback projections from V2 to V1 in the owl monkey. J. Neurosci. 25, 2117–2131 (2005).

20. Stettler, D. D., Das, A., Bennett, J. & Gilbert, C. D. Lateral connectivity and contextual interactions in macaque primary visual cortex. Neuron 36, 739–750 (2002).

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

22. 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).

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

24. Chen, T.-W. et al. Ultrasensitive fluorescent proteins for imaging neuronal activity. Nature 499, 295–300 (2013).

25. 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).

26. Cox, C. L., Denk, W., Tank, D. W. & Svoboda, K. Action potentials reliably invade axonal arbors of rat neocortical neurons. Proc. Natl. Acad. Sci. USA 97, 9724–9728 (2000).

27. Koester, H. J. & Sakmann, B. Calcium dynamics associated with action potentials in single nerve terminals of pyramidal cells in layer 2/3 of the young rat neocortex. J. Physiol. (Lond.) 529, 625–646 (2000).

28. Niell, C. M. & Stryker, M. P. Highly selective receptive fields in mouse visual cortex. J. Neurosci. 28, 7520–7536 (2008).

29. Bonin, V., Histed, M. H., Yurgenson, S. & Reid, R. C. Local diversity and fine-scale organization of receptive fields in mouse visual cortex. J. Neurosci. 31, 18506–18521 (2011).

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

31. Salin, P. A., Girard, P., Kennedy, H. & Bullier, J. Visuotopic organization of corticocortical connections in the visual system of the cat. J. Comp. Neurol. 320, 415–434 (1992).

32. Zhuang, J. et al. An extended retinotopic map of mouse cortex. eLife 6, 1–29 (2017).

33. Hillier, D. et al. Causal evidence for retina-dependent and -independent visual motion computations in mouse cortex. Nat. Neurosci. 20, 960–968 (2017).

34. Murphy, P. C., Duckett, S. G. & Sillito, A. M. Feedback connections to the lateral geniculate nucleus and cortical response properties. Science 286, 1552–1554 (1999).

35. Schmidt, K. E., Goebel, R., Löwel, S. & Singer, W. The perceptual grouping criterion of colinearity is reflected by anisotropies of connections in the primary visual cortex. Eur. J. Neurosci. 9, 1083–1089 (1997).

36. Bosking, W. H., Zhang, Y., Schofield, B. & Fitzpatrick, D. Orientation selectivity and the arrangement of horizontal connections in tree shrew striate cortex. J. Neurosci. 17, 2112–2127 (1997).

37. Sincich, L. C. & Blasdel, G. G. Oriented axon projections in primary visual cortex of the monkey. J. Neurosci. 21, 4416–4426 (2001).

38. Iacaruso, M. F., Gasler, I. T. & Hofer, S. B. Synaptic organization of visual space in primary visual cortex. Nature 547, 449–452 (2017).

39. Gilbert, C. D. & Wiesel, T. N. Columnar specificity of intrinsic horizontal and corticocortical connections in cat visual cortex. J. Neurosci. 9, 2432–2442 (1989).

40. Kapadia, M. K., Ito, M., Gilbert, C. D. & Westheimer, G. Improvement in visual sensitivity by changes in local context: parallel studies in human observers and in V1 of alert monkeys. Neuron 15, 843–856 (1995).

41. Chisum, H. J., Mooser, F. & Fitzpatrick, D. Emergent properties of layer 2/3 neurons reflect the collinear arrangement of horizontal connections in tree shrew visual cortex. J. Neurosci. 23, 2947–2960 (2003).

42. Yang, W., Carrasquillo, Y., Hooks, B. M., Nerbonne, J. M. & Burkhalter, A. Distinct balance of excitation and inhibition in an interareal feedforward and feedback circuit of mouse visual cortex. J. Neurosci. 33, 17373–17384 (2013).

43. Jiang, X., Wang, G., Lee, A. J., Stornetta, R. L. & Zhu, J. J. The organization of two new cortical interneuronal circuits. Nat. Neurosci. 16, 210–218 (2013).

44. Li, Z. A neural model of contour integration in the primary visual cortex. Neural Comput. 10, 903–940 (1998).

45. Polack, P.-O. & Contreras, D. Long-range parallel processing and local recurrent activity in the visual cortex of the mouse. J. Neurosci. 32, 11120–11131 (2012).

46. Sigman, M., Cecchi, G. A., Gilbert, C. D. & Magnasco, M. O. On a common circle: natural scenes and gestalt rules. Proc. Natl. Acad. Sci. USA 98, 1935–1940 (2001).

47. Geisler, W. S. Visual perception and the statistical properties of natural scenes. Annu. Rev. Psychol. 59, 167–192 (2008).

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

49. 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).

50. Murakami, T., Yoshida, T., Matsui, T. & Ohki, K. Wide-field Ca(2+) imaging reveals visually evoked activity in the retrosplenial area. Front. Mol. Neurosci. 8, 20 (2015).

51. Dana, H. et al. Thy1-GCaMP6 transgenic mice for neuronal population imaging in vivo. PLoS One 9, e108697 (2014).

52. Suter, B. A. B. A. et al. Ephus: multipurpose data acquisition software for neuroscience experiments. Front. Neural Circuits 4, 100 (2010).

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

54. Guizar-Sicairos, M., Thurman, S. T. & Fienup, J. R. Efficient subpixel image registration algorithms. Opt. Lett. 33, 156–158 (2008).