Predicting the orientation of invisible stimuli from activity in human primary visual cortex


Humans can experience aftereffects from oriented stimuli that are not consciously perceived, suggesting that such stimuli receive cortical processing. Determining the physiological substrate of such effects has proven elusive owing to the low spatial resolution of conventional human neuroimaging techniques compared to the size of orientation columns in visual cortex. Here we show that even at conventional resolutions it is possible to use fMRI to obtain a direct measure of orientation-selective processing in V1. We found that many parts of V1 show subtle but reproducible biases to oriented stimuli, and that we could accumulate this information across the whole of V1 using multivariate pattern recognition. Using this information, we could then successfully predict which one of two oriented stimuli a participant was viewing, even when masking rendered that stimulus invisible. Our findings show that conventional fMRI can be used to reveal feature-selective processing in human cortex, even for invisible stimuli.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Figure 1: Orientation selectivity of fMRI responses in V1.
Figure 2: Procedures for experiment 2.
Figure 3: Discrimination accuracy for prediction of orientation of the invisible target stimuli from single samples of V1 activity.
Figure 4: Discrimination accuracy compared across visual areas (averaged across participants, error bars, s.e.m.).


  1. 1

    He, S., Cavanagh, P. & Intriligator, J. Attentional resolution and the locus of visual awareness. Nature 383, 334–337 (1996).

    CAS  Article  Google Scholar 

  2. 2

    He, S. & MacLeod, D.I. Orientation-selective adaptation and tilt after-effect from invisible patterns. Nature 411, 473–476 (2001).

    CAS  Article  Google Scholar 

  3. 3

    Rajimehr, R. Unconscious orientation processing. Neuron 41, 663–673 (2004).

    CAS  Article  Google Scholar 

  4. 4

    Bartfeld, E. & Grinvald, A. Relationships between orientation-preference pinwheels, cytochrome oxidase blobs, and ocular-dominance columns in primate striate cortex. Proc. Natl. Acad. Sci. USA 89, 11905–11909 (1992).

    CAS  Article  Google Scholar 

  5. 5

    Obermayer, K. & Blasdel, G.G. Geometry of orientation and ocular dominance columns in monkey striate cortex. J. Neurosci. 13, 4114–4129 (1993).

    CAS  Article  Google Scholar 

  6. 6

    Tootell, R.B. et al. Functional analysis of primary visual cortex (V1) in humans. Proc. Natl. Acad. Sci. USA 95, 811–817 (1998).

    CAS  Article  Google Scholar 

  7. 7

    Boynton, G.M. & Finney, E.M. Orientation-specific adaptation in human visual cortex. J. Neurosci. 23, 8781–8787 (2003).

    CAS  Article  Google Scholar 

  8. 8

    Duda, O.R., Hart, P.E. & Stork, D.G. Pattern Classification (Wiley, New York, 2001).

    Google Scholar 

  9. 9

    Haxby, J.V. et al. Distributed and overlapping representations of faces and objects in ventral temporal cortex. Science 293, 2425–2430 (2001).

    CAS  Article  Google Scholar 

  10. 10

    Cox, D.D. & Savoy, R.L. Functional magnetic resonance imaging (fMRI) 'brain reading': detecting and classifying distributed patterns of fMRI activity in human visual cortex. Neuroimage 19, 261–270 (2003).

    Article  Google Scholar 

  11. 11

    Carlson, T.A., Schrater, P. & He, S. Patterns of activity in the categorical representation of objects. J. Cogn. Neurosci. 15, 704–717 (2003).

    Article  Google Scholar 

  12. 12

    Dehaene, S. et al. Inferring behavior from functional brain images. Nat. Neurosci. 1, 549–550 (1998).

    CAS  Article  Google Scholar 

  13. 13

    Macknik, S.L. & Livingstone, M.S. Neuronal correlates of visibility and invisibility in the primate visual system. Nat. Neurosci. 1, 144–149 (1998).

    CAS  Article  Google Scholar 

  14. 14

    Furmanski, C.S. & Engel, S.A. An oblique effect in human primary visual cortex. Nat. Neurosci. 3, 535–536 (2000).

    CAS  Article  Google Scholar 

  15. 15

    Westheimer, G. The distribution of preferred orientations in the peripheral visual field. Vision Res. 43, 53–57 (2003).

    Article  Google Scholar 

  16. 16

    Wilkinson, F. et al. An fMRI study of the selective activation of human extrastriate form vision areas by radial and concentric gratings. Curr. Biol. 10, 1455–1458 (2000).

    CAS  Article  Google Scholar 

  17. 17

    Crick, F. & Koch, C. Are we aware of neural activity in primary visual cortex? Nature 375, 121–123 (1995).

    CAS  Article  Google Scholar 

  18. 18

    Tong, F. Primary visual cortex and visual awareness. Nat. Rev. Neurosci. 4, 219–229 (2003).

    CAS  Article  Google Scholar 

  19. 19

    Ress, D. & Heeger, D.J. Neuronal correlates of perception in early visual cortex. Nat. Neurosci. 6, 414–420 (2003).

    CAS  Article  Google Scholar 

  20. 20

    Polonsky, A., Blake, R., Braun, J. & Heeger, D.J. Neuronal activity in human primary visual cortex correlates with perception during binocular rivalry. Nat. Neurosci. 3, 1153–1159 (2000).

    CAS  Article  Google Scholar 

  21. 21

    Tong, F. & Engel, S.A. Interocular rivalry revealed in the human cortical blind-spot representation. Nature 411, 195–199 (2001).

    CAS  Article  Google Scholar 

  22. 22

    Super, H., Spekreijse, H. & Lamme, V.A. Two distinct modes of sensory processing observed in monkey primary visual cortex (V1). Nat. Neurosci. 4, 304–310 (2001).

    CAS  Article  Google Scholar 

  23. 23

    Gur, M. & Snodderly, D.M. A dissociation between brain activity and perception: chromatically opponent cortical neurons signal chromatic flicker that is not perceived. Vision Res. 37, 377–382 (1997).

    CAS  Article  Google Scholar 

  24. 24

    Leopold, D.A. & Logothetis, N.K. Activity changes in early visual cortex reflect monkeys' percepts during binocular rivalry. Nature 379, 549–553 (1996).

    CAS  Article  Google Scholar 

  25. 25

    Moutoussis, K. & Zeki, S. The relationship between cortical activation and perception investigated with invisible stimuli. Proc. Natl. Acad. Sci. USA 99, 9527–9532 (2002).

    CAS  Article  Google Scholar 

  26. 26

    Rees, G. et al. Unconscious activation of visual cortex in the damaged right hemisphere of a parietal patient with extinction. Brain 123, 1624–1633 (2000).

    Article  Google Scholar 

  27. 27

    Vuilleumier, P. et al. Neural fate of seen and unseen faces in visuospatial neglect: a combined event-related functional MRI and event-related potential study. Proc. Natl. Acad. Sci. USA 98, 3495–3500 (2001).

    CAS  Article  Google Scholar 

  28. 28

    Dehaene, S. et al. Imaging unconscious semantic priming. Nature 395, 597–600 (1998).

    CAS  Article  Google Scholar 

  29. 29

    Luck, S.J., Vogel, E.K. & Shapiro, K.L. Word meanings can be accessed but not reported during the attentional blink. Nature 383, 616–618 (1996).

    CAS  Article  Google Scholar 

  30. 30

    Yukie, M. & Iwai, E. Direct projection from the dorsal lateral geniculate nucleus to the prestriate cortex in macaque monkeys. J. Comp. Neurol. 201, 81–97 (1981).

    CAS  Article  Google Scholar 

  31. 31

    Goebel, R., Muckli, L., Zanella, F.E., Singer, W. & Stoerig, P. Sustained extrastriate cortical activation without visual awareness revealed by fMRI studies of hemianopic patients. Vision Res. 41, 1459–1474 (2001).

    CAS  Article  Google Scholar 

  32. 32

    Hannula, D.E., Simons, D.J. & Cohen, N.J. Imaging implicit perception: promise and pitfalls. Nat. Rev. Neurosci. 6, 247–255 (2005).

    CAS  Article  Google Scholar 

  33. 33

    Friston, K.J. et al. Statistical parametric maps in functional imaging: a general linear approach. Hum. Brain Mapp. 2, 189–210 (1995).

    Article  Google Scholar 

  34. 34

    Sereno, M.I. et al. Borders of multiple visual areas in humans revealed by functional magnetic resonance imaging. Science 268, 889–893 (1995).

    CAS  Article  Google Scholar 

  35. 35

    Teo, P.C., Sapiro, G. & Wandell, B.A. Creating connected representations of cortical gray matter for functional MRI visualization. IEEE Trans. Med. Imaging 16, 852–863 (1997).

    CAS  Article  Google Scholar 

  36. 36

    Wandell, B.A., Chial, S. & Backus, B.T. Visualization and measurement of the cortical surface. J. Cogn. Neurosci. 12, 739–752 (2000).

    CAS  Article  Google Scholar 

  37. 37

    Everitt, B.S. & Dunn, G. Applied Multivariate Data Analysis (Edward Arnold, London, 1991).

    Google Scholar 

Download references


We thank K. Friston and J. Driver for comments on the manuscript. The Wellcome Trust funded this work.

Author information



Corresponding author

Correspondence to John-Dylan Haynes.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Fig. 1

Simulation of expected orientation bias. (PDF 104 kb)

Supplementary Fig. 2

Spatial distribution of orientation biases of voxels entering into the discriminant analysis. (PDF 246 kb)

Supplementary Fig. 3

Analysis of radial and tangential contributions to orientation bias in V1. (GIF 75 kb)

Supplementary Fig. 4

Details of pattern classification for experiment 1. (PDF 181 kb)

Supplementary Fig. 5

Comparison of prediction using conventional and pattern signals. (PDF 90 kb)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Haynes, J., Rees, G. Predicting the orientation of invisible stimuli from activity in human primary visual cortex. Nat Neurosci 8, 686–691 (2005).

Download citation

Further reading