A decisional account of subjective inflation of visual perception at the periphery
Open accessAbstract
Human peripheral vision appears vivid compared to foveal vision; the subjectively perceived level of detail does not seem to drop abruptly with eccentricity. This compelling impression contrasts with the fact that spatial resolution is substantially lower at the periphery. A similar phenomenon occurs in visual attention, in which subjects usually overestimate their perceptual capacity in the unattended periphery. We have previously shown that at identical eccentricity, low spatial attention is associated with liberal detection biases, which we argue may reflect inflated subjective perceptual qualities. Our computational model suggests that this subjective inflation occurs because under the lack of attention, the trial-by-trial variability of the internal neural response is increased, resulting in more frequent surpassing of a detection criterion. In the current work, we hypothesized that the same mechanism may be at work in peripheral vision. We investigated this possibility in psychophysical experiments in which participants performed a simultaneous detection task at the center and at the periphery. Confirming our hypothesis, we found that participants adopted a conservative criterion at the center and liberal criterion at the periphery. Furthermore, an extension of our model predicts that detection bias will be similar at the center and at the periphery if the periphery stimuli are magnified. A second experiment successfully confirmed this prediction. These results suggest that, although other factors contribute to subjective inflation of visual perception in the periphery, such as top-down filling-in of information, the decision mechanism may be relevant too.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In detection and coarse discrimination tasks, Lau, Rahnev, and colleagues report that subjects overestimate their confidence in the periphery and for unattended stimuli.
“In detection and coarse discrimination tasks, Lau, Rahnev, and colleagues report that subjects overestimate their confidence in the periphery and for unattended stimuli.”
From Comparing Bayesian and non-Bayesian accounts of human confidence reports (2018) · cites this paper as [63]
The Results (p. 5) show a more liberal detection criterion and more false alarms for peripheral than central stimuli. The introduction (p. 1) reports a similar liberal detection bias for unattended stimuli in earlier work. But this paper does not report confidence ratings or a coarse-discrimination result, so it does not establish that subjects overestimated their confidence in both tasks. (LLM, conf=0.87)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Experimental and theoretical approaches to conscious processing
Dehaene, S., & Changeux, J.-P. (2011) · Neuron · doi:10.1016/j.neuron.2011.03.018 · Cited by 2,573 · see citing works
Empirical support for higher-order theories of conscious awareness
Lau, H., & Rosenthal, D. (2011) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2011.05.009 · Cited by 869 · see citing works
Self-citationWhat Is Stochastic Resonance? Definitions, Misconceptions, Debates, and Its Relevance to Biology
McDonnell, M. D., & Abbott, D. (2009) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000348 · Cited by 774 · see citing works
Attentional stimulus selection through selective synchronization between monkey visual areas
Bosman, C. A., Schoffelen, J.-M., Brunet, N., Oostenveld, R., Bastos, A. M., Womelsdorf, T., Rubehn, B., Stieglitz, T., De Weerd, P., & Fries, P. (2012) · Neuron · doi:10.1016/j.neuron.2012.06.037 · Cited by 720 · see citing works
Signal detection theory, uncertainty, and Poisson-like population codes
Ma, W. J. (2010) · Vision Research · doi:10.1016/j.visres.2010.08.035 · Cited by 60 · see citing works
Flagged first, then by citations
Research works printed but not linked: 53
- Alvarez, G. A. (2011). Representing multiple objects as an ensemble enhances visual cognition. Trends in Cognitive Sciences, 15 (3), 122 -131. doi:10.1016/j.tics.2011.01.003 · DOI
- Anstis, S. (1998). Picturing peripheral acuity. Perception, 27 (7), 817 -825.
- Azzopardi, P., & Cowey, A. (1993). Preferential representation of the fovea in the primary visual cortex. Nature, 361 (6414), 719 -721. doi: 10.1038/361719a0 · DOI
- Balas, B., Nakano, L., & Rosenholtz, R. (2009). A summary-statistic representation in peripheral vision explains visual crowding. Journal of Vision, 9 (12), 13.1 -18. doi:10.1167/9.12.13 · DOI · Paper page
- Banks, M. S., Sekuler, A. B., & Anderson, S. J. (1991). Peripheral spatial vision: limits imposed by optics, photoreceptors, and receptor pooling. Journal of the Optical Society of America A, Optics and Image Science, 8 (11), 1775 -1787.
- Bisley, J. W. (2011). The neural basis of visual attention. The Journal of Physiology, 589 (Pt 1), 49 -57. doi:10.1113/jphysiol.2010.192666 · DOI
- Block, N. (2011). Perceptual consciousness overflows cognitive access. Trends in Cognitive Sciences, 15 (12), 567 -575. doi:10.1016/j.tics. 2011.11.001 · DOI
- Boucart, M., Moroni, C., Thibaut, M., Szaffarczyk, S., & Greene, M. (2013). Scene categorization at large visual eccentricities. Vision Research, 86, 35 -42. doi:10.1016/j.visres.2013.04.006 · DOI
- Brainard, D. H. (1997). The Psychophysics Toolbox. Spatial Vision, 10 (4), 433 -436.
- Bressler, D. W., & Silver, M. A. (2010). Spatial attention improves reliability of fMRI retinotopic mapping signals in occipital and parietal cortex. NeuroImage, 53 (2), 526 -533. doi:10.1016/j. neuroimage.2010.06.063 · DOI
- Burnham, K. P., & Anderson, D. R. (2002). Model Selection and MultiModel Inference: A Practical Information-Theoretic Approach (p. 488). Springer.
- Cafaro, J., & Rieke, F. (2010). Noise correlations improve response fidelity and stimulus encoding. Nature, 468 (7326), 964 -967. doi: 10.1038/nature09570 · DOI
- Carrasco, M. (2011). Visual attention: The past 25 years. Vision Research . doi:10.1016/j.visres.2011.04.012 · DOI
- Carrasco, M., & Frieder, K. S. (1997). Cortical magnification neutralizes the eccentricity effect in visual search. Vision Research, 37 (1), 63 -82.
- Curcio, C. A., Sloan, K. R., Kalina, R. E., & Hendrickson, A. E. (1990). Human photoreceptor topography. The Journal of Comparative Neurology, 292 (4), 497 -523. doi:10.1002/cne. 902920402 · DOI
- Daniel, P. M., & Whitteridge, D. (1961). The representation of the visual field on the cerebral cortex in monkeys. The Journal of Physiology, 159, 203 -221.
- DeValois, R. L., & DeValois, K. K. (1988). Spatial Vision (p. 400). Oxford University Press.
- Dorfman, D. D., & Alf, E. (1969). Maximum-likelihood estimation of parameters of signal-detection theory and determination of confidence intervals -Rating-method data. Journal of Mathematical Psychology, 6 (3), 487 -496.
- Eckstein, M. P., Peterson, M. F., Pham, B. T., & Droll, J. A. (2009). Statistical decision theory to relate neurons to behavior in the study of covert visual attention. Vision Research, 49 (10), 1097 -1128. doi: 10.1016/j.visres.2008.12.008 · DOI
- Efron, B., & Tibshirani, R. J. (1994). An Introduction to the Bootstrap (p. 456). CRC Press.
- Gorea, A., & Sagi, D. (2000). Failure to handle more than one internal representation in visual detection tasks. Proceedings of the National Academy of Sciences of the United States of America, 97 (22), 12380 -12384. doi:10.1073/pnas.97.22.12380 · DOI
- Kirkpatrick, S., Gelatt, C. D., & Vecchi, M. P. (1983). Optimization by simulated annealing. Science (New York, N.Y.) , 220 (4598), 671 -80. doi:10.1126/science.220.4598.671 · DOI · Paper page
- Kouider, S., de Gardelle, V ., Sackur, J., & Dupoux, E. (2010). How rich is consciousness? The partial awareness hypothesis. Trends in Cognitive Sciences, 14 (7), 301 -307. doi:10.1016/j.tics.2010.04.006 · DOI
- Lamme, V. A. F. (2010). How neuroscience will change our view on consciousness. Cognitive Neuroscience, 1 (3), 204 -220. doi:10. 1080/17588921003731586
- Lau, H., & Rahnev, D. A. (2011). The paradoxical negative relationship between attention-related spontaneous neural activity and perceptual decisions. Journal of Vision, 11 (11), 20 -20. doi:10.1167/11.11.20 · DOI
- Levi, D. M. (2008). Crowding -an essential bottleneck for object recognition: a mini-review. Vision Research, 48 (5), 635 -654. doi:10. 1016/j.visres.2007.12.009
- Lima, B., Singer, W., Chen, N.-H., & Neuenschwander, S. (2010). Synchronization dynamics in response to plaid stimuli in monkey V1. Cerebral Cortex (New York, N.Y.: 1991) , 20 (7), 1556 -73. doi: 10.1093/cercor/bhp218 · DOI
- Macmillan, N. A., & Creelman, C. D. (2004). Detection Theory: A User ' s Guide (p. 512). Psychology Press.
- Mullen, K. T. (1991). Colour vision as a post-receptoral specialization of the central visual field. Vision Research, 31 (1), 119 -130.
- Noorlander, C., Koenderink, J. J., Den Olden, R. J., & Edens, B. W. (1983). Sensitivity to spatiotemporal colour contrast in the peripheral visual field. Vision Research, 23 (1), 1 -11.
- O ' Regan, J. K. (1992). Solving the ' real ' mysteries of visual perception: the world as an outside memory. Canadian Journal of Psychology, 46, 461 -488. doi:10.1037/h0084327 · DOI · Paper page
- Oliva, A. (2005). Gist of the Scene. In L. Itti, G. Rees, & J. Tsotsos (Eds.), Neurobiology of Attention (pp. 251 -256). San Diego: Elsevier.
- Parkes, L., Lund, J., Angelucci, A., Solomon, J. A., & Morgan, M. (2001). Compulsory averaging of crowded orientation signals in human vision. Nature Neuroscience, 4 (7), 739 -744. doi:10.1038/ 89532
- Pelli, D. G. (1997). The VideoToolbox software for visual psychophysics: transforming numbers into movies. Spatial Vision, 10 (4), 437 -442.
- Pelli, D. G., & Tillman, K. A. (2008). The uncrowded window of object recognition. Nature Neuroscience, 11 (10), 1129 -1135.
- Pestilli, F., Carrasco, M., Heeger, D. J., & Gardner, J. L. (2011). Attentional enhancement via selection and pooling of early sensory responses in human visual cortex. Neuron, 72 (5), 832 -846. doi:10. 1016/j.neuron.2011.09.025
- Posner, M. I. (1980). Orienting of attention. Quarterly Journal of Experimental Psychology . doi:10.1080/00335558008248231 · DOI · Paper page
- Rahnev, D. A., Bahdo, L., De Lange, F. P., & Lau, H. (2012a). PreStimulus hemodynamic activity in dorsal attention network is negatively associated with decision confidence in visual perception. Journal of Neurophysiology, 108 (5), 1529 -1536. doi:10.1152/jn. 00184.2012 · DOI
- Rahnev, D. A., Maniscalco, B., Graves, T., Huang, E., de Lange, F. P., & Lau, H. (2011). Attention induces conservative subjective biases in visual perception. Nature Neuroscience, 14 (12), 1513 -1515. doi:10. 1038/nn.2948
- Rahnev, D. A., Maniscalco, B., Luber, B., Lau, H., & Lisanby, S. H. (2012b). Direct injection of noise to the visual cortex decreases accuracy but increases decision confidence. Journal of Neurophysiology, 107 (6), 1556 -1563. doi:10. 1152/jn.00985.2011
- Rounis, E., Maniscalco, B., Rothwell, J. C., Passingham, R. E., & Lau, H. (2010). Theta-burst transcranial magnetic stimulation to the prefrontal cortex impairs metacognitive visual awareness. Cognitive Neuroscience, 1 (3), 165 -175. doi:10.1080/ 17588921003632529
- Scholl, B. J. (2001). Objects and attention: The state of the art. Cognition . doi:10.1016/S0010-0277(00)00152-9 · DOI
- Simonotto, E., Riani, M., Seife, C., Roberts, M., Twitty, J., & Moss, F. (1997). Visual Perception of Stochastic Resonance. Physical Review Letters, 78 (6), 1186 -1189.
- Simons, D. J., & Chabris, C. F. (1999). Gorillas in our midst: sustained inattentional blindness for dynamic events. Perception, 28 (9), 1059 -1074.
- Simons, D. J., & Levin, D. T. (1997). Change blindness. Trends in Cognitive Sciences, 1 (7), 261 -267.
- Strasburger, H., Rentschler, I., & Jüttner, M. (2011). Peripheral vision and pattern recognition: A review. Journal of Vision, 11, 1 -82. doi:10. 1167/11.5.13.Contents
- Summerfield, C., & Egner, T. (2009). Expectation (and attention) in visual cognition. Trends in Cognitive Sciences, 13 (9), 403 -409. doi:10.1016/j.tics.2009.06.003 · DOI · Paper page
- VanPelt, S., & Fries, P. (2013). Visual stimulus eccentricity affects human gamma peak frequency. NeuroImage, 78, 439 -447. doi:10.1016/j. neuroimage.2013.04.040 · DOI
- Virsu, V., Näsänen, R., & Osmoviita, K. (1987). Cortical magnification and peripheral vision. Journal of the Optical Society of America. A, 4 (8), 1568. doi:10.1364/JOSAA.4.001568 · DOI
- Watson, A. B., & Pelli, D. G. (1983). QUEST: a Bayesian adaptive psychometric method. Perception & Psychophysics, 33 (2), 113 -120.
- Wyart, V., Nobre, A. C., & Summerfield, C. (2012). Dissociable prior influences of signal probability and relevance on visual contrast sensitivity. Proceedings of the National Academy of Sciences of the United States of America, 109 (9), 3593 -3598. doi:10.1073/ pnas.1120118109
- Zak, I., Katkov, M., Gorea, A., & Sagi, D. (2012). Decision criteria in dual discrimination tasks estimated using external-noise methods. Attention, Perception, & Psychophysics, 74 (5), 1042 -1055. doi:10. 3758/s13414-012-0269-0
- Zhang, H., Morvan, C., & Maloney, L. T. (2010). Gambling in the visual periphery: a conjoint-measurement analysis of human ability to judge visual uncertainty. PLoS Computational Biology, 6 (12), e1001023. doi:10.1371/journal.pcbi.1001023 · DOI
Cited by
Sorted by citations
Suboptimality in perceptual decision making
Rahnev, D., & Denison, R. N. (2018) · Behavioral and Brain Sciences · doi:10.1017/s0140525x18000936 · Cited by 342 · see citing works
Spatial attention alters visual appearance
Carrasco, M., & Barbot, A. (2019) · Current Opinion in Psychology · doi:10.1016/j.copsyc.2018.10.010 · Cited by 161 · see citing works
Comparing Bayesian and non-Bayesian accounts of human confidence reports
Adler, W. T., & Ma, W. J. (2018) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006572 · Cited by 118 · see citing works
Behavioral, Modeling, and Electrophysiological Evidence for Supramodality in Human Metacognition
Faivre, N., Filevich, E., Solovey, G., Kühn, S., & Blanke, O. (2018) · The Journal of Neuroscience · doi:10.1523/jneurosci.0322-17.2017 · Cited by 129 · see citing works
Self-citationConsensus Goals in the Field of Visual Metacognition
Rahnev, D., Balsdon, T., Charles, L., de Gardelle, V., Denison, R., Desender, K., Faivre, N., Filevich, E., Fleming, S. M., Jehee, J., et al. (2022) · Perspectives on Psychological Science · doi:10.1177/17456916221075615 · Cited by 63 · see citing works
Self-citationQianchen, L., Gallagher, R. M., & Tsuchiya, N. (2022) · Royal Society Open Science · doi:10.1098/rsos.210394 · Cited by 21 · see citing works
Is fear perception special? Evidence at the level of decision-making and subjective confidence
Koizumi, A., Mobbs, D., & Lau, H. (2016) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsw084 · Cited by 13 · see citing works
Self-citationWinter, C. J., & Peters, M. A. K. (2022) · Attention, Perception, & Psychophysics · doi:10.3758/s13414-021-02358-2 · Cited by 17 · see citing works
An embarrassment of richnesses: the PFC isn’t the content NCC
Kozuch, B. (2024) · Neuroscience of Consciousness · doi:10.1093/nc/niae017 · Cited by 9 · see citing works
Neuroscience undermines the higher-order theorists' preferred solution to the targetless HOT problem
Kozuch, B. (2026) · Philosophical Psychology · doi:10.1080/09515089.2026.2629514
- Authors
- Solovey, G., Graney, G. G., & Lau, H.
- Affiliations
- Columbia University (US)
- University of California, Los Angeles (US)
- Corresponding author
- Solovey, Guillermo
- Venue
- Attention, Perception, & Psychophysics
- Published
- 2014-09-24
- Volume
- 77
- Issue
- 1
- Pages
- 258-271
- ISSN
- 1943-3921 (ISSN-L)
- 1943-393X
- OpenAlex
- W1970227435
- Cited by
- 63
- References
- 5
- Citations by year
- 2026: 7 · 2025: 4 · 2024: 7 · 2023: 8 · 2022: 6 · 2021: 4 · 2020: 4 · 2019: 3 · 2018: 10 · 2017: 2 · 2016: 8
- FWCI
- 1.86
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- cc-by-nc-sa
- www.springer.com/tdm (tdm)
- Locations
- Attention Perception & Psychophysics (publishedVersion)
- PubMed (publishedVersion)
- The HKU Scholars Hub (University of Hong Kong) (submittedVersion)
- Conicet (submittedVersion, cc-by-nc-sa)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Visual Attention and Saliency Detection
- Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
- Keywords
- peripheral vision, visual detection, detection criteria, eccentricity, spatial resolution, trial-to-trial variability, neural response variability, decision-making mechanisms, visual attention, magnification, filling-in
- MeSH terms
- Attention, Decision Making, Eye Movements, Fovea Centralis, Humans, Psychomotor Performance, Vision, Ocular, Visual Perception, Signal Detection, Psychological, Feedback, Psychological, Young Adult
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review