Humans often fail to identify a target because of nearby flankers. The nature and stages at which this crowding occurs are unclear, and whether crowding operates via a common mechanism across visual dimensions is unknown. Using a dual-estimation report (N = 42), we quantitatively assessed the processing of features alone and in conjunction with another feature both within and between dimensions. Under crowding, observers misreported colors and orientations (i.e., reported a flanker value instead of the target’s value) but averaged the target’s and flankers’ spatial frequencies (SFs). Interestingly, whereas orientation and color errors were independent, orientation and SF errors were interdependent. These qualitative differences of errors across dimensions revealed a tight link between crowding and feature binding, which is contingent on the type of feature dimension. These results and a computational model suggest that crowding and misbinding are due to pooling across a joint coding of orientations and SFs but not of colors.

Bays, P. M., Catalao, R. F. G., Husain, M. (2009). The precision of visual working memory is set by allocation of a shared resource. Journal of Vision, 9(10), Article 7. doi:10.1167/9.10.7
Google Scholar | Crossref | Medline | ISI
Bouma, H. (1970). Interaction effects in parafoveal letter recognition. Nature, 226, 177178. doi:10.1038/226177a0
Google Scholar | Crossref | Medline | ISI
Caelli, T., Brettel, H., Rentschler, I., Hilz, R. (1983). Discrimination thresholds in the two-dimensional spatial frequency domain. Vision Research, 23, 129133.
Google Scholar | Crossref | Medline | ISI
Derrington, A. M., Krauskopf, J., Lennie, P. (1984). Chromatic mechanisms in lateral geniculate nucleus of macaque. The Journal of Physiology, 357, 241265.
Google Scholar | Crossref | Medline | ISI
De Valois, R. L., Albrecht, D. G., Thorell, L. G. (1982). Spatial frequency selectivity of cells in macaque visual cortex. Vision Research, 22, 545559. doi:10.1016/0042-6989(82)90113-4
Google Scholar | Crossref | Medline | ISI
Di Lollo, V . (2012). The feature-binding problem is an ill-posed problem. Trends in Cognitive Sciences, 16, 317321. doi:10.1016/j.tics.2012.04.007
Google Scholar | Crossref | Medline | ISI
Dowd, E. W., Golomb, J. D. (2019). Object-feature binding survives dynamic shifts of spatial attention. Psychological Science, 30, 343361. doi:10.1177/0956797618818481
Google Scholar | SAGE Journals | ISI
Ester, E. F., Klee, D., Awh, E. (2014). Visual crowding cannot be wholly explained by feature pooling. Journal of Experimental Psychology: Human Perception and Performance, 40, 10221033. doi:10.1037/a0035377
Google Scholar | Crossref | Medline | ISI
Ester, E. F., Zilber, E., Serences, J. T. (2015). Substitution and pooling in visual crowding induced by similar and dissimilar distractors. Journal of Vision, 15(1), Article 4. doi:10.1167/15.1.4
Google Scholar | Crossref | Medline
Freeman, J., Simoncelli, E. P. (2011). Metamers of the ventral stream. Nature Neuroscience, 14, 11951201. doi:10.1038/nn.2889
Google Scholar | Crossref | Medline | ISI
Goris, R. L. T., Simoncelli, E. P., Movshon, J. A. (2015). Origin and function of tuning diversity in macaque visual cortex. Neuron, 88, 819831. doi:10.1016/j.neuron.2015.10.009
Google Scholar | Crossref | Medline
Greenwood, J. A., Bex, P. J., Dakin, S. C. (2009). Positional averaging explains crowding with letter-like stimuli. Proceedings of the National Academy of Sciences, USA, 106, 1313013135. doi:10.1073/pnas.0901352106
Google Scholar | Crossref | Medline | ISI
Greenwood, J. A., Bex, P. J., Dakin, S. C. (2010). Crowding changes appearance. Current Biology, 20, 496501. doi:10.1016/j.cub.2010.01.023
Google Scholar | Crossref | Medline | ISI
Greenwood, J. A., Bex, P. J., Dakin, S. C. (2012). Crowding follows the binding of relative position and orientation. Journal of Vision, 12(3), Article 18. doi:10.1167/12.3.18
Google Scholar | Crossref | ISI
Harrison, W. J., Bex, P. J. (2015). A unifying model of orientation crowding in peripheral vision. Current Biology, 25, 32133219. doi:10.1016/j.cub.2015.10.052
Google Scholar | Crossref | Medline
Huckauf, A., Heller, D. (2014). What various kinds of errors tell us about lateral masking effects. Visual Cognition, 9, 889910. doi:10.1080/13506280143000548A
Google Scholar | Crossref
Keshvari, S., Rosenholtz, R. (2016). Pooling of continuous features provides a unifying account of crowding. Journal of Vision, 16(3), Article 39. doi:10.1167/16.3.39
Google Scholar | Crossref | Medline
Kimchi, R., Pirkner, Y. (2015). Multiple level crowding: Crowding at the object parts level and at the object configural level. Perception, 44, 12751292.
Google Scholar | SAGE Journals | ISI
Kleiner, M., Brainard, D. H., Pelli, D. G. (2007). What’s new in Psychtoolbox-3? Perception, 36(ECVP Abstract Suppl.).
Google Scholar | ISI
Levi, D. M. (2008). Crowding—An essential bottleneck for object recognition: A mini-review. Vision Research, 48, 635654. doi:10.1016/j.visres.2007.12.009
Google Scholar | Crossref | Medline | ISI
Levi, D. M., Klein, S. A. (1986). Sampling in spatial vision. Nature, 320, 360362. doi:10.1038/320360a0
Google Scholar | Crossref | Medline | ISI
Manassi, M., Whitney, D. (2018). Multi-level crowding and the paradox of object recognition in clutter. Current Biology, 28, R127R133. doi:10.1016/j.cub.2017.12.051
Google Scholar | Crossref | Medline
Mareschal, I., Morgan, M. J., Solomon, J. A. (2010). Cortical distance determines whether flankers cause crowding or the tilt illusion. Journal of Vision, 10(8), Article 13. doi:10.1167/10.8.13
Google Scholar | Crossref
Morey, R. D. (2008). Confidence intervals from normalized data: A correction to Cousineau (2005). Tutorials in Quantitative Methods for Psychology, 4, 6164. doi:10.3758/s13414-012-0291-2
Google Scholar | Crossref
Nandy, A. S., Tjan, B. S. (2012). Saccade-confounded image statistics explain visual crowding. Nature Neuroscience, 15, 463469. doi:10.1038/nn.3021
Google Scholar | Crossref | Medline
Parkes, L., Lund, J., Angelucci, A., Solomon, J. A., Morgan, M. (2001). Compulsory averaging of crowded orientation signals in human vision. Nature Neuroscience, 4, 739744.
Google Scholar | Crossref | Medline | ISI
Pelli, D. G., Palomares, M., Majaj, N. J. (2004). Crowding is unlike ordinary masking: Distinguishing feature integration from detection. Journal of Vision, 4, 11361169. doi:10.1167/4.12.12
Google Scholar | Crossref | Medline | ISI
Pelli, D. G., Tillman, K. A. (2008). The uncrowded window of object recognition. Nature Neuroscience, 11, 11291135.
Google Scholar | Crossref | Medline | ISI
Põder, E., Wagemans, J. (2007). Crowding with conjunctions of simple features. Journal of Vision, 7(2), Article 23. doi:10.1167/7.2.23
Google Scholar | Crossref | Medline
Robson, J. G., Graham, N. (1981). Probability summation and regional variation in contrast sensitivity across the visual field. Vision Research, 21, 409418.
Google Scholar | Crossref | Medline | ISI
Scolari, M., Kohnen, A., Barton, B., Awh, E. (2007). Spatial attention, preview, and popout: Which factors influence critical spacing in crowded displays? Journal of Vision, 7(2), Article 7. doi:10.1167/7.2.7
Google Scholar | Crossref | Medline
Strasburger, H., Harvey, L. O., Rentschler, I. (1991). Contrast thresholds for identification of numeric characters in direct and eccentric view. Perception & Psychophysics, 49, 495508. doi:10.3758/BF03212183
Google Scholar | Crossref | Medline
Suchow, J. W., Brady, T. F., Fougnie, D., Alvarez, G. A. (2013). Modeling visual working memory with the MemToolbox. Journal of Vision, 13(10), Article 9. doi:10.1167/13.10.9
Google Scholar | Crossref | Medline
Treisman, A., Schmidt, H. (1982). Illusory conjunctions in the perception of objects. Cognitive Psychology, 14, 107141. doi:10.1016/0010-0285(82)90006-8
Google Scholar | Crossref | Medline | ISI
van den Berg, R., Roerdink, J. B. T. M., Cornelissen, F. W. (2007). On the generality of crowding: Visual crowding in size, saturation, and hue compared to orientation. Journal of Vision, 7(2), Article 14. doi:10.1167/7.2.14
Google Scholar | Crossref | ISI
van den Berg, R., Roerdink, J. B. T. M., Cornelissen, F. W. (2010). A neurophysiologically plausible population code model for feature integration explains visual crowding. PLOS Computational Biology, 6(1), Article e1000646. doi:10.1371/journal.pcbi.1000646
Google Scholar | Crossref | Medline
Vul, E., Rich, A. N. (2010). Independent sampling of features enables conscious perception of bound objects. Psychological Science, 21, 11681175. doi:10.1177/0956797610377341
Google Scholar | SAGE Journals | ISI
Whitney, D., Levi, D. M. (2011). Visual crowding: A fundamental limit on conscious perception and object recognition. Trends in Cognitive Sciences, 15, 160168. doi:10.1016/j.tics.2011.02.005
Google Scholar | Crossref | Medline | ISI
Yashar, A., Chen, J., Carrasco, M. (2015). Rapid and long-lasting reduction of crowding through training. Journal of Vision, 15(10), Article 15. doi:10.1167/15.10.15
Google Scholar | Crossref | Medline
Access Options

My Account

Welcome
You do not have access to this content.



Chinese Institutions / 中国用户

Click the button below for the full-text content

请点击以下获取该全文

Institutional Access

does not have access to this content.

Purchase Content

24 hours online access to download content

Research off-campus without worrying about access issues. Find out about Lean Library here.

Your Access Options


Purchase

PSS-article-ppv for $35.00

Cookies Notification

This site uses cookies. By continuing to browse the site you are agreeing to our use of cookies. Find out more.
Top