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A decisional account of subjective inflation of visual perception at the periphery

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Abstract

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.

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References

  • 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

    Article  PubMed  Google Scholar 

  • Anstis, S. (1998). Picturing peripheral acuity. Perception, 27(7), 817–825.

    Article  PubMed  Google Scholar 

  • Azzopardi, P., & Cowey, A. (1993). Preferential representation of the fovea in the primary visual cortex. Nature, 361(6414), 719–721. doi:10.1038/361719a0

    Article  PubMed  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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.

    Article  PubMed  Google Scholar 

  • 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

    Article  PubMed Central  PubMed  Google Scholar 

  • Block, N. (2011). Perceptual consciousness overflows cognitive access. Trends in Cognitive Sciences, 15(12), 567–575. doi:10.1016/j.tics.2011.11.001

    Article  PubMed  Google Scholar 

  • Bosman, C. A., Schoffelen, J.-M., Brunet, N., Oostenveld, R., Bastos, A. M., Womelsdorf, T., … Fries, P. (2012). Attentional stimulus selection through selective synchronization between monkey visual areas. Neuron, 75(5), 875–88. doi:10.1016/j.neuron.2012.06.037

  • 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

    Article  PubMed  Google Scholar 

  • Brainard, D. H. (1997). The Psychophysics Toolbox. Spatial Vision, 10(4), 433–436.

    Article  PubMed  Google Scholar 

  • 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

    Article  PubMed Central  PubMed  Google Scholar 

  • Burnham, K. P., & Anderson, D. R. (2002). Model Selection and Multi-Model 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

    Article  PubMed Central  PubMed  Google Scholar 

  • Carrasco, M. (2011). Visual attention: The past 25 years. Vision Research. doi:10.1016/j.visres.2011.04.012

    Google Scholar 

  • Carrasco, M., & Frieder, K. S. (1997). Cortical magnification neutralizes the eccentricity effect in visual search. Vision Research, 37(1), 63–82.

    Article  PubMed  Google Scholar 

  • Cohen, M. A., & Dennett, D. C. (2011). Consciousness cannot be separated from function. Trends in Cognitive Sciences. doi:10.1016/j.tics.2011.06.008

    Google Scholar 

  • 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

    Article  PubMed  Google Scholar 

  • 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.

    Article  PubMed Central  PubMed  Google Scholar 

  • Dehaene, S., & Changeux, J.-P. (2011). Experimental and theoretical approaches to conscious processing. Neuron, 70(2), 200–227. doi:10.1016/j.neuron.2011.03.018

    Article  PubMed  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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

    Article  PubMed  Google Scholar 

  • 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

    Article  PubMed Central  PubMed  Google Scholar 

  • Green, D. M., & Swets, J. A. (1989). Signal Detection Theory and Psychophysics (p. 521). Peninsula Pub.

  • 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

  • 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

    Article  PubMed  Google Scholar 

  • Lamme, V. A. F. (2010). How neuroscience will change our view on consciousness. Cognitive Neuroscience, 1(3), 204–220. doi:10.1080/17588921003731586

    Article  PubMed  Google Scholar 

  • Lau, H. (2008). A higher order Bayesian decision theory of consciousness. Progress in Brain Research, 168, 35–48.

    Article  PubMed  Google Scholar 

  • 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

    Article  Google Scholar 

  • Lau, H., & Rosenthal, D. (2011). Empirical support for higher-order theories of conscious awareness. Trends in Cognitive Sciences, 15, 365–373. doi:10.1016/j.tics.2011.05.009

    Article  PubMed  Google Scholar 

  • 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

    Article  PubMed Central  PubMed  Google Scholar 

  • 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

  • Ma, W. J. (2010). Signal detection theory, uncertainty, and Poisson-like population codes. Vision Research, 50(22), 2308–2319. doi:10.1016/j.visres.2010.08.035

    Article  PubMed  Google Scholar 

  • Macmillan, N. A., & Creelman, C. D. (2004). Detection Theory: A User’s Guide (p. 512). Psychology Press.

  • McDonnell, M. D., & Abbott, D. (2009). What is stochastic resonance? Definitions, misconceptions, debates, and its relevance to biology. PLoS Computational Biology, 5(5), e1000348. doi:10.1371/journal.pcbi.1000348

    Article  PubMed Central  PubMed  Google Scholar 

  • Morales, J., Solovey, G., Maniscalco, B., Rahnev, D., De Lange, F. P., & Lau, H. (2014). Low Attention Impairs Optimal Incorporation of Prior Knowledge in Perceptual Decisions. Manuscript submitted for publication.

  • Mullen, K. T. (1991). Colour vision as a post-receptoral specialization of the central visual field. Vision Research, 31(1), 119–130.

    Article  PubMed  Google Scholar 

  • 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.

    Article  PubMed  Google Scholar 

  • 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

    Article  PubMed  Google Scholar 

  • Oliva, A. (2005). Gist of the Scene. In L. Itti, G. Rees, & J. Tsotsos (Eds.), Neurobiology of Attention (pp. 251–256). San Diego: Elsevier.

    Chapter  Google Scholar 

  • 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

    Article  PubMed  Google Scholar 

  • Pelli, D. G. (1997). The VideoToolbox software for visual psychophysics: transforming numbers into movies. Spatial Vision, 10(4), 437–442.

    Article  PubMed  Google Scholar 

  • Pelli, D. G., & Tillman, K. A. (2008). The uncrowded window of object recognition. Nature Neuroscience, 11(10), 1129–1135.

    Article  PubMed Central  PubMed  Google Scholar 

  • 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

    Article  PubMed Central  PubMed  Google Scholar 

  • Posner, M. I. (1980). Orienting of attention. Quarterly Journal of Experimental Psychology. doi:10.1080/00335558008248231

    PubMed  Google Scholar 

  • Rahnev, D. A., Bahdo, L., De Lange, F. P., & Lau, H. (2012a). Pre-Stimulus 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

    Article  PubMed  Google Scholar 

  • 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

    Article  PubMed  Google Scholar 

  • 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

    Article  PubMed  Google Scholar 

  • 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

    Article  PubMed  Google Scholar 

  • Scholl, B. J. (2001). Objects and attention: The state of the art. Cognition. doi:10.1016/S0010-0277(00)00152-9

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • Simons, D. J., & Chabris, C. F. (1999). Gorillas in our midst: sustained inattentional blindness for dynamic events. Perception, 28(9), 1059–1074.

    Article  PubMed  Google Scholar 

  • Simons, D. J., & Levin, D. T. (1997). Change blindness. Trends in Cognitive Sciences, 1(7), 261–267.

    Article  PubMed  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  PubMed  Google Scholar 

  • Van Pelt, S., & Fries, P. (2013). Visual stimulus eccentricity affects human gamma peak frequency. NeuroImage, 78, 439–447. doi:10.1016/j.neuroimage.2013.04.040

    Article  PubMed  Google Scholar 

  • 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

    Article  Google Scholar 

  • Watson, A. B., & Pelli, D. G. (1983). QUEST: a Bayesian adaptive psychometric method. Perception & Psychophysics, 33(2), 113–120.

    Article  Google Scholar 

  • 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

    Article  PubMed Central  PubMed  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  PubMed Central  PubMed  Google Scholar 

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Acknowledgments

This work is partially supported by a grant from the Templeton Foundation (6–40689) awarded to Hakwan Lau. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We thank Megan Peters and Jorge Morales for valuable comments on the manuscript, Brian Maniscalco for assistance with model fitting, and Dobromir Rahnev for task design suggestions.

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Correspondence to Guillermo Solovey.

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Solovey, G., Graney, G.G. & Lau, H. A decisional account of subjective inflation of visual perception at the periphery. Atten Percept Psychophys 77, 258–271 (2015). https://doi.org/10.3758/s13414-014-0769-1

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