Dissociable prior influences of signal probability and relevance on visual contrast sensitivity
Open accessAbstract
According to signal detection theoretical analyses, visual signals occurring at a cued location are detected more accurately, whereas frequently occurring ones are reported more often but are not better distinguished from noise. However, conventional analyses that estimate sensitivity and bias by comparing true- and false-positive rates offer limited insights into the mechanisms responsible for these effects. Here, we reassessed the prior influences of signal probability and relevance on visual contrast detection using a reverse-correlation technique that quantifies how signal-like fluctuations in noise predict trial-to-trial variability in choice discarded by conventional analyses. This approach allowed us to estimate separately the sensitivity of true and false positives to parametric changes in signal energy. We found that signal probability and relevance both increased energy sensitivity, but in dissociable ways. Cues predicting the relevant location increased primarily the sensitivity of true positives by suppressing internal noise during signal processing, whereas cues predicting greater signal probability increased both the frequency and the sensitivity of false positives by biasing the baseline activity of signal-selective units. We interpret these findings in light of “predictive-coding” models of perception, which propose separable top-down influences of expectation (probability driven) and attention (relevance driven) on bottom-up sensory processing.
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 [62]
The Conventional Signal Detection Analyses section reports detection sensitivity and false-alarm rates for relevant and irrelevant stimuli, not subjects’ confidence judgments. Searches for Lau, Rahnev, peripheral vision, and confidence overestimation found no passage in our copy addressing the attributed finding; page numbers were unavailable. (LLM, conf=0.76)
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
Signal detection theory and psychophysics
Ingleby, D. (1967) · Journal of Sound and Vibration · doi:10.1016/0022-460x(67)90197-6 · Cited by 8,616 · see citing works
Neural Mechanisms of Selective Visual Attention
Desimone, R., & Duncan, J. (1995) · Annual Review of Neuroscience · doi:10.1146/annurev.ne.18.030195.001205 · Cited by 8,388 · see citing works
The free-energy principle: a unified brain theory?
Friston, K. (2010) · Nature Reviews Neuroscience · doi:10.1038/nrn2787 · Cited by 8,120 · cited 1× · see citing works
“This top-down mechanism allows for optimal perceptual inference byminimizing the amount of surprise (or prediction error) left to be encoded by bottom-up signals (36) and is mathematically equivalent to computational descriptions of how attention biases visual processing (37–39).”
BackgroundRao, R. P. N., & Ballard, D. H. (1999) · Nature Neuroscience · doi:10.1038/4580 · Cited by 5,483 · see citing works
Receptive fields of single neurones in the cat's striate cortex
Hubel, D. H., & Wiesel, T. N. (1959) · The Journal of Physiology · doi:10.1113/jphysiol.1959.sp006308 · Cited by 4,653 · see citing works
A theory of cortical responses.
Friston, K. (2005) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2005.1622 · Cited by 4,578 · see citing works
Attention and the detection of signals.
Posner, M. I., Snyder, C. R., & Davidson, B. J. (1980) · Journal of Experimental Psychology: General · doi:10.1037/0096-3445.109.2.160 · Cited by 3,778 · see citing works
Detection theory: A user's guide
Lories, G. (1993) · Behavioural Processes · doi:10.1016/0376-6357(93)90083-4 · Cited by 2,927 · see citing works
Neural correlates of decision variables in parietal cortex
Platt, M. L., & Glimcher, P. W. (1999) · Nature · doi:10.1038/22268 · Cited by 1,721 · see citing works
The Normalization Model of Attention
Reynolds, J. H., & Heeger, D. J. (2009) · Neuron · doi:10.1016/j.neuron.2009.01.002 · Cited by 1,457 · see citing works
Decision Processes In Perception.
Swets, J. A., Jr. Tanner Wilson, P., & Birdsall, T. G. (1961) · Psychological Review · doi:10.1037/h0040547 · Cited by 1,328 · see citing works
Attentional modulation of visual processing
Reynolds, J. H., & Chelazzi, L. (2004) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.26.041002.131039 · Cited by 1,158 · see citing works
Attention improves performance primarily by reducing interneuronal correlations
Cohen, M. R., & Maunsell, J. H. R. (2009) · Nature Neuroscience · doi:10.1038/nn.2439 · Cited by 1,126 · see citing works
On the computational architecture of the neocortex: II The role of cortico-cortical loops
Mumford, D. (1992) · Biological Cybernetics · doi:10.1007/bf00198477 · Cited by 1,074 · see citing works
Attention Increases Sensitivity of V4 Neurons
Reynolds, J. H., Pasternak, T., & Desimone, R. (2000) · Neuron · doi:10.1016/s0896-6273(00)81206-4 · Cited by 1,017 · see citing works
Expectation (and attention) in visual cognition
Summerfield, C., & Egner, T. (2009) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2009.06.003 · Cited by 950 · see citing works
Self-citationOn the computational architecture of the neocortex: I. The role of the thalamo-cortical loop
Mumford, D. (1991) · Biological Cybernetics · doi:10.1007/bf00202389 · Cited by 929 · see citing works
Neural computation of log likelihood in control of saccadic eye movements
Carpenter, R. H. S., & Williams, M. L. L. (1995) · Nature · doi:10.1038/377059a0 · Cited by 823 · see citing works
Attention improves or impairs visual performance by enhancing spatial resolution
Yeshurun, Y., & Carrasco, M. (1998) · Nature · doi:10.1038/23936 · Cited by 767 · see citing works
Spatial attention decorrelates intrinsic activity fluctuations in macaque area V4
Mitchell, J. F., Sundberg, K. A., & Reynolds, J. H. (2009) · Neuron · doi:10.1016/j.neuron.2009.09.013 · Cited by 710 · see citing works
The zone of comfort: Predicting visual discomfort with stereo displays
Shibata, T., Kim, J., Hoffman, D. M., et al. (2011) · Journal of Vision · doi:10.1167/11.8.11 · Cited by 601 · see citing works
Attention activates winner-take-all competition among visual filters
Lee, D. K., Itti, L., Christof Koch, A., & Braun, J. (1999) · Nature Neuroscience · doi:10.1038/7286 · Cited by 458 · see citing works
Enhancement of perceptual sensitivity as the result of selectively attending to spatial locations
Bashinski, H. S., & Bacharach, V. R. (1980) · Perception & Psychophysics · doi:10.3758/bf03204380 · Cited by 449 · see citing works
Neuronal correlates of perception in early visual cortex
Ress, D. B., & Heeger, D. J. (2003) · Nature Neuroscience · doi:10.1038/nn1024 · Cited by 352 · see citing works
Expectation and Surprise Determine Neural Population Responses in the Ventral Visual Stream
Egner, T., Monti, J. M., & Summerfield, C. (2010) · The Journal of Neuroscience · doi:10.1523/jneurosci.2770-10.2010 · Cited by 350 · see citing works
Self-citationVerghese, P. (2001) · Neuron · doi:10.1016/s0896-6273(01)00392-0 · Cited by 347 · see citing works
Measuring the effect of attention on simple visual search.
Palmer, J. C., Ames, C. T., & Lindsey, D. T. (1993) · Journal of Experimental Psychology Human Perception & Performance · doi:10.1037//0096-1523.19.1.108 · Cited by 335 · see citing works
An integrated theory of attention and decision making in visual signal detection.
Smith, P. L., & Ratcliff, R. (2009) · Psychology Review · doi:10.1037/a0015156 · Cited by 315 · see citing works
Neural Theories of Simple Visual Discriminations*†
Blackwell, H. R. (1963) · Journal of the Optical Society of America · doi:10.1364/josa.53.000129 · Cited by 303 · see citing works
Effects of Attention on the Reliability of Individual Neurons in Monkey Visual Cortex
McAdams, C. J., & Maunsell, J. H. R. (1999) · Neuron · doi:10.1016/s0896-6273(01)80034-9 · Cited by 286 · see citing works
Noise Exclusion in Spatial Attention
Dosher, B. A., & Lu, Z. (2000) · Psychological Science · doi:10.1111/1467-9280.00229 · Cited by 277 · see citing works
Lu, Z., & Dosher, B. A. (2008) · Psychological Review · doi:10.1037/0033-295x.115.1.44 · Cited by 245 · see citing works
Predictive coding as a model of biased competition in visual attention
Spratling, M. (2008) · Vision Research · doi:10.1016/j.visres.2008.03.009 · Cited by 240 · see citing works
Signal Detection Theory and ROC Analysis in Psychology and Diagnostics
Swets, J. A. (2014) · Psychology Press eBooks · doi:10.4324/9781315806167 · Cited by 209 · see citing works
Classification images: A review
Murray, R. F. (2011) · Journal of Vision · doi:10.1167/11.5.2 · Cited by 195 · see citing works
Shape-specific preparatory activity mediates attention to targets in human visual cortex
Stokes, M. G., Thompson, R., Nobre, A. C., & Duncan, J. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0905306106 · Cited by 192 · see citing works
Self-citationMeasuring the effect of attention on simple visual search.
Palmer, J. C., Ames, C. T., & Lindsey, D. T. (1993) · Journal of Experimental Psychology Human Perception & Performance · doi:10.1037/0096-1523.19.1.108 · Cited by 183 · see citing works
Carrasco, M. (2006) · Progress in brain research · doi:10.1016/s0079-6123(06)54003-8 · Cited by 174 · see citing works
The footprints of visual attention in the Posner cueing paradigm revealed by classification images
Eckstein, M. P., Shimozaki, S. S., & Abbey, C. K. (2002) · Journal of Vision · doi:10.1167/2.1.3 · Cited by 170 · see citing works
Computations for geometrically accurate visually guided reaching in 3-D space
Blohm, G., & Crawford, J. D. (2007) · Journal of Vision · doi:10.1167/7.5.4 · Cited by 88 · see citing works
Statistical decision theory to relate neurons to behavior in the study of covert visual attention
Eckstein, M. P., Peterson, M., Pham, B. T., & Droll, J. A. (2009) · Vision Research · doi:10.1016/j.visres.2008.12.008 · Cited by 74 · see citing works
Contrast discrimination function: spatial cuing effects
Solomon, J. A., Lavie, N., & Morgan, M. J. (1997) · Journal of the Optical Society of America A · doi:10.1364/josaa.14.002443 · Cited by 74 · see citing works
Effects of Prior Information and Reward on Oculomotor and Perceptual Choices
Liston, D. B., & Stone, L. S. (2008) · Journal of Neuroscience · doi:10.1523/jneurosci.3120-08.2008 · Cited by 66 · see citing works
The stability of steady state accommodation in human infants
Candy, T. R., & Bharadwaj, S. R. (2007) · Journal of Vision · doi:10.1167/7.11.4 · Cited by 55 · see citing works
Concurrent variation of response bias and sensitivity in an operant-psychophysical test
Terman, M., & Terman, J. S. (1972) · Perception & Psychophysics · doi:10.3758/bf03206285 · Cited by 52 · see citing works
Stimulus probability directs spatial attention: an enhancement of sensitivity in humans and monkeys
Ciaramitaro, V. M., Cameron, E. L., & Glimcher, P. W. (2001) · Vision Research · doi:10.1016/s0042-6989(00)00203-0 · Cited by 50 · see citing works
Gould, I. C., Wolfgang, B. J., & Smith, P. L. (2007) · Journal of Vision · doi:10.1167/7.13.4 · Cited by 48 · see citing works
Mendoza-Halliday, D., Schneiderman, M., Kaul, C., & Martínez-Trujillo, J. (2011) · Journal of Vision · doi:10.1167/11.1.11 · Cited by 46 · see citing works
Davis, W., & Valois, K. K. D. (2002) · Journal of Vision · doi:10.1167/2.10.25 · Cited by 22 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Whatever next? Predictive brains, situated agents, and the future of cognitive science
Clark, A. (2013) · Behavioral and Brain Sciences · doi:10.1017/s0140525x12000477 · Cited by 5,924 · see citing works
Canonical Microcircuits for Predictive Coding
Bastos, A. M., Usrey, W. M., Adams, R. A., Mangun, G. R., Fries, P., & Friston, K. J. (2012) · Neuron · doi:10.1016/j.neuron.2012.10.038 · Cited by 2,421 · see citing works
“It should be noted that the suppression of responses to predictable stimuli can coexist with (top-down) attentional enhancement of signal processing (Wyart et al., 2012): in predictive coding, attention is mediated by increasing the gain of populations encoding prediction error (Spratling, 2008; Feldman and Friston, 2…”
Cortical oscillations and sensory predictions
Arnal, L. H., & Giraud, A.-L. (2012) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2012.05.003 · Cited by 1,114 · see citing works
How Do Expectations Shape Perception?
de Lange, F. P., Heilbron, M., & Kok, P. (2018) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2018.06.002 · Cited by 975 · see citing works
Expectation in perceptual decision making: neural and computational mechanisms
Summerfield, C., & de Lange, F. P. (2014) · Nature Reviews Neuroscience · doi:10.1038/nrn3838 · Cited by 832 · see citing works
Self-citationHow prediction errors shape perception, attention, and motivation
den Ouden, H. E. M., Kok, P., & de Lange, F. P. (2012) · Frontiers in Psychology · doi:10.3389/fpsyg.2012.00548 · Cited by 512 · see citing works
The Border Between Seeing and Thinking
Block, N. (2023) · doi:10.1093/oso/9780197622223.001.0001 · Cited by 367 · see citing works
Prior expectations induce prestimulus sensory templates
Kok, P., Mostert, P., & de Lange, F. P. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1705652114 · Cited by 340 · see citing works
Prior Expectations Evoke Stimulus Templates in the Primary Visual Cortex
Kok, P., Failing, M. F., & de Lange, F. P. (2014) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00562 · Cited by 293 · see citing works
Forms of prediction in the nervous system
Teufel, C., & Fletcher, P. C. (2020) · Nature Reviews Neuroscience · doi:10.1038/s41583-020-0275-5 · Cited by 155 · see citing works
Measures of metacognition on signal-detection theoretic models
Barrett, A. B., Dienes, Z., & Seth, A. K. (2013) · Psychological Methods · doi:10.1037/a0033268 · Cited by 155 · see citing works
Attention Sharpens the Distinction between Expected and Unexpected Percepts in the Visual Brain
Jiang, J., Summerfield, C., & Egner, T. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.3308-13.2013 · Cited by 133 · see citing works
Self-citationComparing 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
Predictive Coding in Sensory Cortex
Kok, P., & de Lange, F. P. (2015) · An Introduction to Model-Based Cognitive Neuroscience · doi:10.1007/978-1-4939-2236-9_11 · Cited by 98 · see citing works
Antunes, F. M., & Malmierca, M. S. (2021) · Frontiers in Neural Circuits · doi:10.3389/fncir.2021.721186 · Cited by 71 · see citing works
Grounding predictive coding models in empirical neuroscience research
Egner, T., & Summerfield, C. (2013) · Behavioral and Brain Sciences · doi:10.1017/s0140525x1200218x · Cited by 36 · see citing works
Self-citationPrior probability modulates anticipatory activity in category-specific areas
Trapp, S., Lepsien, J., Kotz, S. A., & Bar, M. (2016) · Cognitive, Affective, & Behavioral Neuroscience · doi:10.3758/s13415-015-0373-4 · Cited by 24 · see citing works
Feature-specific prediction errors for visual mismatch
Stefanics, G., Stephan, K. E., & Heinzle, J. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.04.020 · Cited by 26 · see citing works
Haarsma, J., Deveci, N., Corbin, N., Callaghan, M. F., & Kok, P. (2023) · The Journal of Neuroscience · doi:10.1523/jneurosci.0998-23.2023 · Cited by 26 · see citing works
Predictive codes of interoception, emotion, and the self.
Sel, A. (2014) · Frontiers in Psychology · doi:10.3389/fpsyg.2014.00189 · Cited by 26 · see citing works
- Authors
- Wyart, V., Nobre, A. C., & Summerfield, C.
- Affiliations
- University of Oxford (GB)
- Warneford Hospital (GB)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2012-02-13
- Volume
- 109
- Issue
- 9
- Pages
- 3593-3598
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC3295248
- OpenAlex
- W2088247269
- Cited by
- 268
- References
- 49
- Citations by year
- 2026: 13 · 2025: 23 · 2024: 23 · 2023: 44 · 2022: 23 · 2021: 18 · 2020: 15 · 2019: 21 · 2018: 16 · 2017: 15 · 2016: 9 · 2015: 15 · 2014: 13 · 2013: 13 · 2012: 7
- FWCI
- 7.85
- Type
- journal article
- Language
- en
- Update notices
- correction (2012-03-27)
- Open access
- bronze
- doi.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Fondation Fyssen
- 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 › Neural and Behavioral Psychology Studies
- Keywords
- contrast sensitivity, signal probability, spatial cueing, predictive coding, false positives, top-down expectations, attention, reverse correlation, trial-to-trial variability, signal detection theory
- MeSH terms
- Adult, Attention, Cues, False Positive Reactions, Female, Humans, Male, Models, Psychological, Photic Stimulation, Probability, Contrast Sensitivity, Signal Detection, 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