References

Adams, O. J., & Gaspelin, N. (2020). Assessing introspective awareness of attention capture. Attention, Perception, & Psychophysics, 1–13.

Adams, O. J., & Gaspelin, N. (2021). Introspective awareness of oculomotor attentional capture. Journal of Experimental Psychology: Human Perception and Performance.

Adelson, E. H., & Bergen, J. R. (1985). Spatiotemporal energy models for the perception of motion. Josa a, 2(2), 284–299.

Albonico, A., Furubacke, A., Barton, J. J., & Oruc, I. (2018). Perceptual efficiency and the inversion effect for faces, words and houses. Vision Research, 153, 91–97.

Andersson, J. L., Hutton, C., Ashburner, J., Turner, R., & Friston, K. (2001). Modeling geometric deformations in EPI time series. Neuroimage, 13(5), 903–919.

Angel, E. (2000). Interactive computer graphics : A top-down approach with OpenGL. Boston, MA: Addison Wesley Longman.

Angel, E. (2001a). Batch-file computer graphics : A bottom-up approach with QuickTime. Boston, MA: Wesley Addison Longman.

Angel, E. (2001b). Test second book by angel. Boston, MA: Wesley Addison Longman.

Ashburner, J., & Friston, K. J. (2005). Unified segmentation. Neuroimage, 26(3), 839–851.

Aust, F., & Barth, M. (2020). papaja: Create APA manuscripts with R Markdown. Retrieved from https://github.com/crsh/papaja

Bahrami, B., Olsen, K., Latham, P. E., Roepstorff, A., Rees, G., & Frith, C. D. (2010). Optimally interacting minds. Science, 329(5995), 1081–1085.

Baker, C., Saxe, R., & Tenenbaum, J. (2011). Bayesian theory of mind: Modeling joint belief-desire attribution. In Proceedings of the annual meeting of the cognitive science society (Vol. 33).

Bang, D., & Fleming, S. M. (2018). Distinct encoding of decision confidence in human medial prefrontal cortex. Proceedings of the National Academy of Sciences, 115(23), 6082–6087.

Banks, W. P. (1970). Signal detection theory and human memory. Psychological Bulletin, 74(2), 81.

Bartra, O., McGuire, J. T., & Kable, J. W. (2013). The valuation system: A coordinate-based meta-analysis of BOLD fMRI experiments examining neural correlates of subjective value. Neuroimage, 76, 412–427.

Battaglia, P. W., Hamrick, J. B., & Tenenbaum, J. B. (2013). Simulation as an engine of physical scene understanding. Proceedings of the National Academy of Sciences, 110(45), 18327–18332.

Begg, I., Duft, S., Lalonde, P., Melnick, R., & Sanvito, J. (1989). Memory predictions are based on ease of processing. Journal of Memory and Language, 28(5), 610–632.

Benjamin, A. S. (2003). Predicting and postdicting the effects of word frequency on memory. Memory & Cognition, 31(2), 297–305.

Blackwell, H. R. (1952). Studies of psychophysical methods for measuring visual thresholds. JOSA, 42(9), 606–616.

Blakemore, S.-J., Wolpert, D. M., & Frith, C. D. (1998). Central cancellation of self-produced tickle sensation. Nature Neuroscience, 1(7), 635–640.

Bonawitz, E., Ullman, T. D., Bridgers, S., Gopnik, A., & Tenenbaum, J. B. (2019). Sticking to the evidence? A behavioral and computational case study of micro-theory change in the domain of magnetism. Cognitive Science, 43(8), e12765.

Boorman, E. D., Behrens, T. E., Woolrich, M. W., & Rushworth, M. F. (2009). How green is the grass on the other side? Frontopolar cortex and the evidence in favor of alternative courses of action. Neuron, 62(5), 733–743.

Borchers, H. W. (2019). Pracma: Practical numerical math functions. Retrieved from https://CRAN.R-project.org/package=pracma

Botvinick, M., & Cohen, J. (1998). Rubber hands ‘feel’touch that eyes see. Nature, 391(6669), 756–756.

Brown, J., Lewis, V., & Monk, A. (1977). Memorability, word frequency and negative recognition. The Quarterly Journal of Experimental Psychology, 29(3), 461–473.

Burgess, P. W., Gilbert, S. J., & Dumontheil, I. (2007). Function and localization within rostral prefrontal cortex (area 10). Philosophical Transactions of the Royal Society B: Biological Sciences, 362(1481), 887–899.

Calder-Travis, J., Charles, L., Bogacz, R., & Yeung, N. (2020). Bayesian confidence in optimal decisions.

Cassini, M. H., Kacelnik, A., & Segura, E. T. (1990). The tale of the screaming hairy armadillo, the guinea pig and the marginal value theorem. Animal Behaviour, 39(6), 1030–1050.

Cavagnaro, D. R., Pitt, M. A., & Myung, J. I. (2011). Model discrimination through adaptive experimentation. Psychonomic Bulletin & Review, 18(1), 204–210.

Champely, S. (2020). Pwr: Basic functions for power analysis. Retrieved from https://CRAN.R-project.org/package=pwr

Charnov, E. L. (1976). Optimal foraging, the marginal value theorem. Theoretical Population Biology, 9(2), 129–136.

Christensen, M. S., Ramsøy, T. Z., Lund, T. E., Madsen, K. H., & Rowe, J. B. (2006). An fMRI study of the neural correlates of graded visual perception. Neuroimage, 31(4), 1711–1725.

Chun, M. M., & Wolfe, J. M. (1996). Just say no: How are visual searches terminated when there is no target present? Cognitive Psychology, 30(1), 39–78.

Clark, A. (2013). The many faces of precision (replies to commentaries on “whatever next? Neural prediction, situated agents, and the future of cognitive science”). Frontiers in Psychology, 4, 270.

Coldren, J. T., & Haaf, R. A. (2000). Asymmetries in infants’ attention to the presence or absence of features. The Journal of Genetic Psychology, 161(4), 420–434.

Cortese, M. J., Khanna, M. M., & Hacker, S. (2010). Recognition memory for 2,578 monosyllabic words. Memory, 18(6), 595–609.

Cortese, M. J., McCarty, D. P., & Schock, J. (2015). A mega recognition memory study of 2897 disyllabic words. Quarterly Journal of Experimental Psychology, 68(8), 1489–1501.

Cowie, D., Makin, T. R., & Bremner, A. J. (2013). Children’s responses to the rubber-hand illusion reveal dissociable pathways in body representation. Psychological Science, 24(5), 762–769.

Cowie, R. J. (1977). Optimal foraging in great tits (parus major). Nature, 268(5616), 137–139.

D’Zmura, M. (1991). Color in visual search. Vision Research, 31(6), 951–966.

Darwin, C., & Darwin, F. (1958). Autobiography and selected letters (Vol. 479). Courier Corporation.

De Cornulier, B. (1988). Knowing whether, knowing who, and epistemic closure. Questions and Questioning, 182–192.

De Leeuw, J. R. (2015). jsPsych: A JavaScript library for creating behavioral experiments in a web browser. Behavior Research Methods, 47(1), 1–12.

De Martino, B., Bobadilla-Suarez, S., Nouguchi, T., Sharot, T., & Love, B. C. (2017). Social information is integrated into value and confidence judgments according to its reliability. Journal of Neuroscience, 37(25), 6066–6074.

Denecker, M., Marek, V. W., & Truszczynski, M. (2011). Reiter’s default logic is a logic of autoepistemic reasoning and a good one, too. arXiv Preprint arXiv:1108.3278.

Denison, R. N., Adler, W. T., Carrasco, M., & Ma, W. J. (2018). Humans incorporate attention-dependent uncertainty into perceptual decisions and confidence. Proceedings of the National Academy of Sciences, 115(43), 11090–11095.

Dienes, Z. (2019). How do i know what my theory predicts? Advances in Methods and Practices in Psychological Science, 2(4), 364–377.

Domenech, P., & Koechlin, E. (2015). Executive control and decision-making in the prefrontal cortex. Current Opinion in Behavioral Sciences, 1, 101–106.

Donoso, M., Collins, A. G., & Koechlin, E. (2014). Foundations of human reasoning in the prefrontal cortex. Science, 344(6191), 1481–1486.

Dosher, B. A., Han, S., & Lu, Z.-L. (2004). Parallel processing in visual search asymmetry. Journal of Experimental Psychology: Human Perception and Performance, 30(1), 3.

Dugué, L., Merriam, E. P., Heeger, D. J., & Carrasco, M. (2018). Specific visual subregions of TPJ mediate reorienting of spatial attention. Cerebral Cortex, 28(7), 2375–2390.

Ehinger, K. A., & Wolfe, J. M. (2016). When is it time to move to the next map? Optimal foraging in guided visual search. Attention, Perception, & Psychophysics, 78(7), 2135–2151.

Ekstrøm, C. T. (2019). MESS: Miscellaneous esoteric statistical scripts. Retrieved from https://CRAN.R-project.org/package=MESS

Farennikova, A. (2013). Seeing absence. Philosophical Studies, 166(3), 429–454.

Farennikova, A. (2015). Perception of absence and penetration from expectation. Review of Philosophy and Psychology, 6(4), 621–640.

Fechner, G. T., & Adler, H. E. (1860). Elements of psychophysics [elemente der psychophysik]. Leipzig, Germany: Breitkopf and Ha Rtel.

Feldman, H., & Friston, K. (2010). Attention, uncertainty, and free-energy. Frontiers in Human Neuroscience, 4, 215.

Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive–developmental inquiry. American Psychologist, 34(10), 906.

Fleming, S. M., & Dolan, R. J. (2012). The neural basis of metacognitive ability. Philosophical Transactions of the Royal Society B: Biological Sciences, 367(1594), 1338–1349.

Fleming, S. M., Huijgen, J., & Dolan, R. J. (2012). Prefrontal contributions to metacognition in perceptual decision making. Journal of Neuroscience, 32(18), 6117–6125.

Fleming, S. M., & Lau, H. C. (2014). How to measure metacognition. Frontiers in Human Neuroscience, 8, 443.

Fleming, S. M., Van Der Putten, E. J., & Daw, N. D. (2018). Neural mediators of changes of mind about perceptual decisions. Nature Neuroscience, 21(4), 617.

Fleming, S. M., Weil, R. S., Nagy, Z., Dolan, R. J., & Rees, G. (2010). Relating introspective accuracy to individual differences in brain structure. Science, 329(5998), 1541–1543.

Forrester, J. W. (1971). Counterintuitive behavior of social systems. Theory and Decision, 2(2), 109–140.

Friston, K. (2010). The free-energy principle: A unified brain theory? Nature Reviews Neuroscience, 11(2), 127–138.

Frith, C. D. (2012). The role of metacognition in human social interactions. Philosophical Transactions of the Royal Society B: Biological Sciences, 367(1599), 2213–2223.

Frith, U. (1974). Acurious effect with reversed letters explained by a theory of schema. Perception & Psychophysics, 16(1), 113–116.

Gandolfo, M., & Downing, P. E. (2020). Asymmetric visual representation of sex from human body shape. Cognition, 205, 104436.

Geng, J. J., & Vossel, S. (2013). Re-evaluating the role of TPJ in attentional control: Contextual updating? Neuroscience & Biobehavioral Reviews, 37(10), 2608–2620.

Gershman, S. J., Vul, E., & Tenenbaum, J. B. (2012). Multistability and perceptual inference. Neural Computation, 24(1), 1–24.

Gerstenberg, T., & Tenenbaum, J. B. (2017). Intuitive theories. Oxford Handbook of Causal Reasoning, 515–548.

Gherman, S., & Philiastides, M. G. (2018). Human VMPFC encodes early signatures of confidence in perceptual decisions. Elife, 7, e38293.

Ghetti, S., & Alexander, K. W. (2004). “If it happened, i would remember it”: Strategic use of event memorability in the rejection of false autobiographical events. Child Development, 75(2), 542–561.

Ghetti, S., Castelli, P., & Lyons, K. E. (2010). Knowing about not remembering: Developmental dissociations in lack-of-memory monitoring. Developmental Science, 13(4), 611–621.

Ghetti, S., Lyons, K. E., Lazzarin, F., & Cornoldi, C. (2008). The development of metamemory monitoring during retrieval: The case of memory strength and memory absence. Journal of Experimental Child Psychology, 99(3), 157–181.

Glanzer, M., & Adams, J. K. (1990). The mirror effect in recognition memory: Data and theory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 16(1), 5.

Glanzer, M., Adams, J. K., Iverson, G. J., & Kim, K. (1993). The regularities of recognition memory. Psychological Review, 100(3), 546.

Glanzer, M., & Bowles, N. (1976). Analysis of the word-frequency effect in recognition memory. Journal of Experimental Psychology: Human Learning and Memory, 2(1), 21.

Glanzer, M., Hilford, A., & Maloney, L. T. (2009). Likelihood ratio decisions in memory: Three implied regularities. Psychonomic Bulletin & Review, 16(3), 431–455.

Gold, J. I., & Shadlen, M. N. (2001). Neural computations that underlie decisions about sensory stimuli. Trends in Cognitive Sciences, 5(1), 10–16.

Gopnik, A., & Meltzoff, A. N. (1997). Words, thoughts, and theories. Mit Press.

Gopnik, A., & Wellman, H. M. (1992). Why the child’s theory of mind really is a theory.

Gow, L. (2021). A new theory of absence experience. European Journal of Philosophy, 29(1), 168–181.

Graziano, M. S. (2013). Consciousness and the social brain. Oxford University Press.

Graziano, M. S., & Webb, T. W. (2015). The attention schema theory: A mechanistic account of subjective awareness. Frontiers in Psychology, 6, 500.

Greene, R. L., & Thapar, A. (1994). Mirror effect in frequency discrimination. Journal of Experimental Psychology: Learning, Memory, and Cognition, 20(4), 946.

Guggenmos, M., Wilbertz, G., Hebart, M. N., & Sterzer, P. (2016). Mesolimbic confidence signals guide perceptual learning in the absence of external feedback. Elife, 5, e13388.

Guttentag, R., & Carroll, D. (1998). Memorability judgments for high-and low-frequency words. Memory & Cognition, 26(5), 951–958.

Haarsma, J., Fletcher, P. C., Ziauddeen, H., Spencer, T. J., Diederen, K. M., & Murray, G. K. (2018). Precision weighting of cortical unsigned prediction errors is mediated by dopamine and benefits learning. bioRxiv, 288936.

He, Y., Chen, P., & Li, Y. (2020). New efficient and practicable adaptive designs for calibrating items online. Applied Psychological Measurement, 44(1), 3–16.

Hearst, E. (1991). Psychology and nothing. American Scientist, 79(5), 432–443.

Hebart, M. N., Görgen, K., & Haynes, J.-D. (2015). The decoding toolbox (TDT): A versatile software package for multivariate analyses of functional imaging data. Frontiers in Neuroinformatics, 8, 88.

Helmholtz, H. von. (1948). Concerning the perceptions in general, 1867. In Readings in the history of psychology (pp. 214–230). East Norwalk, CT, US: Appleton-Century-Crofts. http://doi.org/10.1037/11304-027

Henmon, V. A. C. (1911). The relation of the time of a judgment to its accuracy. Psychological Review, 18(3), 186.

Henninger, F., Shevchenko, Y., Mertens, U., Kieslich, P. J., & Hilbig, B. E. (2019). Lab. Js: A free, open, online study builder.

Higham, P. A., Perfect, T. J., & Bruno, D. (2009). Investigating strength and frequency effects in recognition memory using type-2 signal detection theory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 35(1), 57.

Hoffman, J. E. (1979). A two-stage model of visual search. Perception & Psychophysics, 25(4), 319–327.

Hsu, A. S., Horng, A., Griffiths, T. L., & Chater, N. (2017). When absence of evidence is evidence of absence: Rational inferences from absent data. Cognitive Science, 41, 1155–1167.

Hsu, A. S., Martin, J. B., Sanborn, A. N., & Griffiths, T. L. (2019). Identifying category representations for complex stimuli using discrete markov chain monte carlo with people. Behavior Research Methods, 51(4), 1706–1716.

Hulleman, J., & Olivers, C. N. (2017). The impending demise of the item in visual search. Behavioral and Brain Sciences, 40.

Igelström, K. M., Webb, T. W., & Graziano, M. S. (2015). Neural processes in the human temporoparietal cortex separated by localized independent component analysis. Journal of Neuroscience, 35(25), 9432–9445.

Igelström, K. M., Webb, T. W., Kelly, Y. T., & Graziano, M. S. (2016). Topographical organization of attentional, social, and memory processes in the human temporoparietal cortex. Eneuro, 3(2).

Isola, P., Xiao, J., Parikh, D., Torralba, A., & Oliva, A. (2013). What makes a photograph memorable? IEEE Transactions on Pattern Analysis and Machine Intelligence, 36(7), 1469–1482.

Jannati, A., & Di Lollo, V. (2012). Relative blindsight arises from a criterion confound in metacontrast masking: Implications for theories of consciousness. Consciousness and Cognition, 21(1), 307–314.

Kahneman, D. (1968). Method, findings, and theory in studies of visual masking. Psychological Bulletin, 70(6p1), 404.

Kammers, M. P., Vignemont, F. de, Verhagen, L., & Dijkerman, H. C. (2009). The rubber hand illusion in action. Neuropsychologia, 47(1), 204–211.

Kanai, R., Walsh, V., & Tseng, C. (2010). Subjective discriminability of invisibility: A framework for distinguishing perceptual and attentional failures of awareness. Consciousness and Cognition, 19(4), 1045–1057.

Kay, K. N., & Yeatman, J. D. (2017). Bottom-up and top-down computations in word-and face-selective cortex. Elife, 6, e22341.

Kellij, S., Fahrenfort, J., Lau, H., Peters, M. A., & Odegaard, B. (2018). The foundations of introspective access: How the relative precision of target encoding influences metacognitive performance.

Kellij, S., Fahrenfort, J., Lau, H., Peters, M. A., & Odegaard, B. (2021). An investigation of how relative precision of target encoding influences metacognitive performance. Attention, Perception, & Psychophysics, 83(1), 512–524.

King, J.-R., & Dehaene, S. (2014). A model of subjective report and objective discrimination as categorical decisions in a vast representational space. Philosophical Transactions of the Royal Society B: Biological Sciences, 369(1641), 20130204.

Ko, Y., & Lau, H. (2012). A detection theoretic explanation of blindsight suggests a link between conscious perception and metacognition. Philosophical Transactions of the Royal Society B: Biological Sciences, 367(1594), 1401–1411.

Koizumi, A., Maniscalco, B., & Lau, H. (2015). Does perceptual confidence facilitate cognitive control? Attention, Perception, & Psychophysics, 77(4), 1295–1306.

Krebs, J. R., Ryan, J. C., & Charnov, E. L. (1974). Hunting by expectation or optimal foraging? A study of patch use by chickadees. Animal Behaviour, 22, 953–IN3.

Kunimoto, C., Miller, J., & Pashler, H. (2001). Confidence and accuracy of near-threshold discrimination responses. Consciousness and Cognition, 10(3), 294–340.

Kuznetsova, A., Brockhoff, P. B., & Christensen, R. H. B. (2017). lmerTest package: Tests in linear mixed effects models. Journal of Statistical Software, 82(13), 1–26. http://doi.org/10.18637/jss.v082.i13

Labes, D., Schütz, H., Lang, B., & Labes, M. D. (2020). Package ‘PowerTOST.’ Power, 2, 49.

Lake, B., Salakhutdinov, R., Gross, J., & Tenenbaum, J. (2011). One shot learning of simple visual concepts. In Proceedings of the annual meeting of the cognitive science society (Vol. 33).

Lakens, D. (2016, January). Power analysis for default Bayesian t-tests. Retrieved from http://daniellakens.blogspot.com/2016/01/power-analysis-for-default-bayesian-t.html

Lange, K., Kuhn, S., & Filevich, E. (2015). Just another tool for online studies (JATOS): An easy solution for setup and management of web servers supporting online studies. PloS One, 10(6), e0130834.

Lange, K., Kühn, S., & Filevich, E. (2015). " just another tool for online studies”(JATOS): An easy solution for setup and management of web servers supporting online studies. PloS One, 10(6).

Langlois, T. A., Jacoby, N., Suchow, J. W., & Griffiths, T. L. (2021). Serial reproduction reveals the geometry of visuospatial representations. Proceedings of the National Academy of Sciences, 118(13).

Lebreton, M., Abitbol, R., Daunizeau, J., & Pessiglione, M. (2015). Automatic integration of confidence in the brain valuation signal. Nature Neuroscience, 18(8), 1159.

Leckey, S., Selmeczy, D., Kazemi, A., Johnson, E. G., Hembacher, E., & Ghetti, S. (2020). Response latencies and eye gaze provide insight on how toddlers gather evidence under uncertainty. Nature Human Behaviour, 4(9), 928–936.

Lee, S. M., & McCarthy, G. (2016). Functional heterogeneity and convergence in the right temporoparietal junction. Cerebral Cortex, 26(3), 1108–1116.

Levin, D. T., & Angelone, B. L. (2001). Visual search for a socially defined feature: What causes the search asymmetry favoring cross-race faces? Perception & Psychophysics, 63(3), 423–435.

Levin, D. T., & Angelone, B. L. (2008). The visual metacognition questionnaire: A measure of intuitions about vision. The American Journal of Psychology, 451–472.

Levitt, H. (1971). Transformed up-down methods in psychoacoustics. The Journal of the Acoustical Society of America, 49(2B), 467–477.

Limanowski, J., & Friston, K. (2018). ‘Seeing the dark’: Grounding phenomenal transparency and opacity in precision estimation for active inference. Frontiers in Psychology, 9, 643.

Locke, J. (1836). An essay concerning human understanding (bk. iv. Chap. XXVII.

Malinowski, P., & Hübner, R. (2001). The effect of familiarity on visual-search performance: Evidence for learned basic features. Perception & Psychophysics, 63(3), 458–463.

Maniscalco, B., & Lau, H. (2010). Comparing signal detection models of perceptual decision confidence. Journal of Vision, 10(7), 213–213.

Maniscalco, B., & Lau, H. (2012). A signal detection theoretic approach for estimating metacognitive sensitivity from confidence ratings. Consciousness and Cognition, 21(1), 422–430.

Maniscalco, B., & Lau, H. (2014). Signal detection theory analysis of type 1 and type 2 data: Meta-d′, response-specific meta-d′, and the unequal variance SDT model. In The cognitive neuroscience of metacognition (pp. 25–66). Springer.

Maniscalco, B., Peters, M. A., & Lau, H. (2016). Heuristic use of perceptual evidence leads to dissociation between performance and metacognitive sensitivity. Attention, Perception, & Psychophysics, 78(3), 923–937.

Marois, R., Yi, D.-J., & Chun, M. M. (2004). The neural fate of consciously perceived and missed events in the attentional blink. Neuron, 41(3), 465–472.

Mayo, D. G. (2018). Statistical inference as severe testing. Cambridge: Cambridge University Press.

Mazor, M. (2021). Inference about absence as a window into the mental self-model.

Mazor, M., & Fleming, S. (2021). Zero-shot search termination reveals a dissociation between implicit and explicit metacognitive knowledge.

Mazor, M., & Fleming, S. M. (2020). Distinguishing absence of awareness from awareness of absence. Philosophy and the Mind Sciences, 1(II).

Mazor, M., Friston, K. J., & Fleming, S. M. (2020). Distinct neural contributions to metacognition for detecting, but not discriminating visual stimuli. Elife, 9, e53900.

Mazor, M., Mazor, N., & Mukamel, R. (2019). A novel tool for time-locking study plans to results. European Journal of Neuroscience, 49(9), 1149–1156.

Mazor, M., Moran, R., & Fleming, S. (2021). Stage 2 registered report: Metacognitive asymmetries in visual perception.

McCarthy, L. (2015). p5. js. URL: Https://P5js. Org, 3.

McCurdy, L. Y., Maniscalco, B., Metcalfe, J., Liu, K. Y., De Lange, F. P., & Lau, H. (2013). Anatomical coupling between distinct metacognitive systems for memory and visual perception. Journal of Neuroscience, 33(5), 1897–1906.

Merkle, E. C., & Van Zandt, T. (2006). An application of the poisson race model to confidence calibration. Journal of Experimental Psychology: General, 135(3), 391.

Metzinger, T. (2003). Phenomenal transparency and cognitive self-reference. Phenomenology and the Cognitive Sciences, 2(4), 353–393.

Meuwese, J. D., Loon, A. M. van, Lamme, V. A., & Fahrenfort, J. J. (2014). The subjective experience of object recognition: Comparing metacognition for object detection and object categorization. Attention, Perception, & Psychophysics, 76(4), 1057–1068.

Meyniel, F., Sigman, M., & Mainen, Z. F. (2015). Confidence as bayesian probability: From neural origins to behavior. Neuron, 88(1), 78–92.

Miller, P. H., & Bigi, L. (1977). Children’s understanding of how stimulus dimensions affect performance. Child Development, 1712–1715.

Miyoshi, K., & Lau, H. (2020). A decision-congruent heuristic gives superior metacognitive sensitivity under realistic variance assumptions. Psychological Review, 127(5), 655.

Morales, J., Lau, H., & Fleming, S. M. (2018). Domain-general and domain-specific patterns of activity supporting metacognition in human prefrontal cortex. Journal of Neuroscience, 38(14), 3534–3546.

Moran, R., Teodorescu, A. R., & Usher, M. (2015). Post choice information integration as a causal determinant of confidence: Novel data and a computational account. Cognitive Psychology, 78, 99–147.

Moran, R., Zehetleitner, M., Liesefeld, H. R., Müller, H. J., & Usher, M. (2016). Serial vs. Parallel models of attention in visual search: Accounting for benchmark RT-distributions. Psychonomic Bulletin & Review, 23(5), 1300–1315.

Moran, R., Zehetleitner, M., Müller, H. J., & Usher, M. (2013). Competitive guided search: Meeting the challenge of benchmark RT distributions. Journal of Vision, 13(8), 24–24.

Morey, Richard D., & Rouder, J. N. (2018). BayesFactor: Computation of bayes factors for common designs. Retrieved from https://CRAN.R-project.org/package=BayesFactor

Morey, Richard D., Rouder, J. N., Jamil, T., & Morey, M. R. D. (2015). Package ‘bayesfactor.’ URLh Http://Cran/r-Projectorg/Web/Packages/BayesFactor/BayesFactor Pdf i (Accessed 1006 15).

Navarro, D. (2015). Learning statistics with r: A tutorial for psychology students and other beginners. (Version 0.5). Adelaide, Australia: University of Adelaide. Retrieved from http://ua.edu.au/ccs/teaching/lsr

Neubert, F.-X., Mars, R. B., Thomas, A. G., Sallet, J., & Rushworth, M. F. (2014). Comparison of human ventral frontal cortex areas for cognitive control and language with areas in monkey frontal cortex. Neuron, 81(3), 700–713.

Newman, J. P., Wolff, W. T., & Hearst, E. (1980). The feature-positive effect in adult human subjects. Journal of Experimental Psychology: Human Learning and Memory, 6(5), 630.

Neyman, J., & Pearson, E. S. (1933). IX. On the problem of the most efficient tests of statistical hypotheses. Philosophical Transactions of the Royal Society of London. Series A, Containing Papers of a Mathematical or Physical Character, 231(694-706), 289–337.

Norman, K. A., Polyn, S. M., Detre, G. J., & Haxby, J. V. (2006). Beyond mind-reading: Multi-voxel pattern analysis of fMRI data. Trends in Cognitive Sciences, 10(9), 424–430.

Oaksford, M. (2002). Contrast classes and matching bias as explanations of the effects of negation on conditional reasoning. Thinking & Reasoning, 8(2), 135–151.

Oaksford, M., & Chater, N. (2001). The probabilistic approach to human reasoning. Trends in Cognitive Sciences, 5(8), 349–357.

Oaksford, M., & Hahn, U. (2004). A bayesian approach to the argument from ignorance. Canadian Journal of Experimental Psychology = Revue Canadienne de Psychologie Experimentale, 58(November 2015), 75–85. http://doi.org/10.1037/h0085798

Odegaard, B., Chang, M. Y., Lau, H., & Cheung, S.-H. (2018). Inflation versus filling-in: Why we feel we see more than we actually do in peripheral vision. Philosophical Transactions of the Royal Society B: Biological Sciences, 373(1755), 20170345.

Ooms, J. (2014). The jsonlite package: A practical and consistent mapping between JSON data and r objects. arXiv:1403.2805 [Stat.CO]. Retrieved from https://arxiv.org/abs/1403.2805

Palmer, C. E., Auksztulewicz, R., Ondobaka, S., & Kilner, J. M. (2019). Sensorimotor beta power reflects the precision-weighting afforded to sensory prediction errors. NeuroImage.

Papeo, L., & Vega, M. de. (2020). The neurobiology of lexical and sentential negation. In The oxford handbook of negation.

Parr, T., Benrimoh, D. A., Vincent, P., & Friston, K. J. (2018). Precision and false perceptual inference. Frontiers in Integrative Neuroscience, 12.

Parr, T., & Friston, K. J. (2019). Attention or salience? Current Opinion in Psychology, 29, 1–5.

Peters, M. A., Thesen, T., Ko, Y. D., Maniscalco, B., Carlson, C., Davidson, M., … others. (2017). Perceptual confidence neglects decision-incongruent evidence in the brain. Nature Human Behaviour, 1(7), 1–8.

Pleskac, T. J., & Busemeyer, J. R. (2010). Two-stage dynamic signal detection: A theory of choice, decision time, and confidence. Psychological Review, 117(3), 864.

R Core Team. (2019). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Retrieved from https://www.R-project.org/

Rahnev, D., 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.

Rausch, M., Hellmann, S., & Zehetleitner, M. (2018). Confidence in masked orientation judgments is informed by both evidence and visibility. Attention, Perception, & Psychophysics, 80(1), 134–154.

Reder, L. M., & Schunn, C. D. (1996). Metacognition does not imply awareness: Strategy choice is governed by implicit learning and memory.

Reiter, R. (1980). A logic for default reasoning. Artificial Intelligence, 13(1-2), 81–132.

Robinson, D., & Hayes, A. (2020). Broom: Convert statistical analysis objects into tidy tibbles. Retrieved from https://CRAN.R-project.org/package=broom

Rollwage, M., Loosen, A., Hauser, T. U., Moran, R., Dolan, R. J., & Fleming, S. M. (2020). Confidence drives a neural confirmation bias. Nature Communications, 11(1), 1–11.

Rouault, M., Seow, T., Gillan, C. M., & Fleming, S. M. (2018). Psychiatric symptom dimensions are associated with dissociable shifts in metacognition but not task performance. Biological Psychiatry, 84(6), 443–451.

Rouder, J. N., Morey, R. D., Speckman, P. L., & Province, J. M. (2012). Default bayes factors for ANOVA designs. Journal of Mathematical Psychology, 56(5), 356–374.

Rouder, J. N., Speckman, P. L., Sun, D., Morey, R. D., & Iverson, G. (2009). Bayesian t tests for accepting and rejecting the null hypothesis. Psychonomic Bulletin & Review, 16(2), 225–237.

Rust, N. C., & Mehrpour, V. (2020). Understanding image memorability. Trends in Cognitive Sciences.

Rutishauser, U., Aflalo, T., Rosario, E. R., Pouratian, N., & Andersen, R. A. (2018). Single-neuron representation of memory strength and recognition confidence in left human posterior parietal cortex. Neuron, 97(1), 209–220.

Saiki, J. (2008). Stimulus-driven mechanisms underlying visual search asymmetry revealed by classification image analyses. Journal of Vision, 8(4), 30–30.

Sainsbury, R. (1971). The “feature positive effect” and simultaneous discrimination learning. Journal of Experimental Child Psychology, 11(3), 347–356.

Samaha, J., & Denison, R. (2020). The positive evidence bias in perceptual confidence is not post-decisional. bioRxiv.

Sanborn, A., & Griffiths, T. L. (2008). Markov chain monte carlo with people. In Advances in neural information processing systems (pp. 1265–1272).

Sanborn, A. N., Mansinghka, V. K., & Griffiths, T. L. (2013). Reconciling intuitive physics and newtonian mechanics for colliding objects. Psychological Review, 120(2), 411.

Saxe, R., & Wexler, A. (2005). Making sense of another mind: The role of the right temporo-parietal junction. Neuropsychologia, 43(10), 1391–1399.

Semmelmann, K., & Weigelt, S. (2017). Online psychophysics: Reaction time effects in cognitive experiments. Behavior Research Methods, 49(4), 1241–1260.

Sepulveda, P., Usher, M., Davies, N., Benson, A. A., Ortoleva, P., & De Martino, B. (2020). Visual attention modulates the integration of goal-relevant evidence and not value. Elife, 9, e60705.

Shen, J., & Reingold, E. M. (2001). Visual search asymmetry: The influence of stimulus familiarity and low-level features. Perception & Psychophysics, 63(3), 464–475.

Shepard, R. N., & Metzler, J. (1971). Mental rotation of three-dimensional objects. Science, 171(3972), 701–703.

Shulman, G. L., Astafiev, S. V., McAvoy, M. P., d’Avossa, G., & Corbetta, M. (2007). Right TPJ deactivation during visual search: Functional significance and support for a filter hypothesis. Cerebral Cortex, 17(11), 2625–2633.

Siegel, M. H., Magid, R. W., Pelz, M., Tenenbaum, J. B., & Schulz, L. E. (2021). Children’s exploratory play tracks the discriminability of hypotheses. Nature Communications, 12(1), 1–9.

Simons, J. S., Davis, S. W., Gilbert, S. J., Frith, C. D., & Burgess, P. W. (2006). Discriminating imagined from perceived information engages brain areas implicated in schizophrenia. Neuroimage, 32(2), 696–703.

Sladky, R., Friston, K. J., Tröstl, J., Cunnington, R., Moser, E., & Windischberger, C. (2011). Slice-timing effects and their correction in functional MRI. Neuroimage, 58(2), 588–594.

Smith, K. A., & Vul, E. (2013). Sources of uncertainty in intuitive physics. Topics in Cognitive Science, 5(1), 185–199.

Solovey, G., Graney, G. G., & Lau, H. (2015). A decisional account of subjective inflation of visual perception at the periphery. Attention, Perception, & Psychophysics, 77(1), 258–271.

Stanislaw, H., & Todorov, N. (1999). Calculation of signal detection theory measures. Behavior Research Methods, Instruments, & Computers, 31(1), 137–149.

Starns, J. J., White, C. N., & Ratcliff, R. (2012). The strength-based mirror effect in subjective strength ratings: The evidence for differentiation can be produced without differentiation. Memory & Cognition, 40(8), 1189–1199.

Stein, T., & Peelen, M. V. (2021). Dissociating conscious and unconscious influences on visual detection effects. Nature Human Behaviour, 1–13.

Strack, F., Förster, J., & Werth, L. (2005). “Know thyself!” The role of idiosyncratic self-knowledge in recognition memory. Journal of Memory and Language, 52(4), 628–638.

Stretch, V., & Wixted, J. T. (1998). On the difference between strength-based and frequency-based mirror effects in recognition memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 24(6), 1379.

Takeda, Y., & Yagi, A. (2000). Inhibitory tagging in visual search can be found if search stimuli remain visible. Perception & Psychophysics, 62(5), 927–934.

Tanner Jr, W. P., & Swets, J. A. (1954). A decision-making theory of visual detection. Psychological Review, 61(6), 401.

Tenenbaum, J. B., Kemp, C., Griffiths, T. L., & Goodman, N. D. (2011). How to grow a mind: Statistics, structure, and abstraction. Science, 331(6022), 1279–1285.

Treisman, A. (1986). Features and objects in visual processing. Scientific American, 255(5), 114B–125.

Treisman, A., & Gormican, S. (1988). Feature analysis in early vision: Evidence from search asymmetries. Psychological Review, 95(1), 15.

Treisman, A. M., & Gelade, G. (1980). A feature-integration theory of attention. Cognitive Psychology, 12(1), 97–136.

Treisman, A., & Sato, S. (1990). Conjunction search revisited. Journal of Experimental Psychology: Human Perception and Performance, 16(3), 459.

Treisman, A., & Souther, J. (1985). Search asymmetry: A diagnostic for preattentive processing of separable features. Journal of Experimental Psychology: General, 114(3), 285.

Tsakiris, M., & Haggard, P. (2005). The rubber hand illusion revisited: Visuotactile integration and self-attribution. Journal of Experimental Psychology: Human Perception and Performance, 31(1), 80.

Turner, M. S., Simons, J. S., Gilbert, S. J., Frith, C. D., & Burgess, P. W. (2008). Distinct roles for lateral and medial rostral prefrontal cortex in source monitoring of perceived and imagined events. Neuropsychologia, 46(5), 1442–1453.

Tversky, A. (1977). Features of similarity. Psychological Review, 84(4), 327.

Ushey, K., Allaire, J., & Tang, Y. (2020). Reticulate: Interface to ’python’. Retrieved from https://github.com/rstudio/reticulate

Vallesi, A. (2014). Monitoring mechanisms in visual search: An fMRI study. Brain Research, 1579, 65–73.

Vincent, B. T. (2011). Search asymmetries: Parallel processing of uncertain sensory information. Vision Research, 51(15), 1741–1750.

Von Grünau, M., & Dubé, S. (1994). Visual search asymmetry for viewing direction. Perception & Psychophysics, 56(2), 211–220.

Walton, D. (1992). Nonfallacious arguments from ignorance. American Philosophical Quarterly, 29(4), 381–387.

Wang, Q., Cavanagh, P., & Green, M. (1994). Familiarity and pop-out in visual search. Perception & Psychophysics, 56(5), 495–500.

Watanabe, A., Grodzinski, U., & Clayton, N. S. (2014). Western scrub-jays allocate longer observation time to more valuable information. Animal Cognition, 17(4), 859–867.

Webb, T., Miyoshi, K., So, T. Y., & Lau, H. (2021). A task-optimized neural network model of decision confidence. In Proceedings of the annual meeting of the cognitive science society (Vol. 43).

Whitney, D., & Yamanashi Leib, A. (2018). Ensemble perception. Annual Review of Psychology, 69, 105–129.

Wickens, T. D. (2002). Elementary signal detection theory. Oxford University Press, USA.

Wickham, H. (2016). ggplot2: Elegant graphics for data analysis. Springer-Verlag New York. Retrieved from https://ggplot2.tidyverse.org

Wickham, H., François, R., Henry, L., & Müller, K. (2020). Dplyr: A grammar of data manipulation. Retrieved from https://CRAN.R-project.org/package=dplyr

Wickham, H., & Henry, L. (2020). Tidyr: Tidy messy data. Retrieved from https://CRAN.R-project.org/package=tidyr

Wilke, C. O. (2019). Cowplot: Streamlined plot theme and plot annotations for ’ggplot2’. Retrieved from https://CRAN.R-project.org/package=cowplot

Wilterson, A. I., Kemper, C. M., Kim, N., Webb, T. W., Reblando, A. M., & Graziano, M. S. (2020). Attention control and the attention schema theory of consciousness. Progress in Neurobiology, 195, 101844.

Wixted, J. T. (1992). Subjective memorability and the mirror effect. Journal of Experimental Psychology: Learning, Memory, and Cognition, 18(4), 681.

Wixted, J. T. (2007). Dual-process theory and signal-detection theory of recognition memory. Psychological Review, 114(1), 152.

Wokke, M. E., Cleeremans, A., & Ridderinkhof, K. R. (2017). Sure i’m sure: Prefrontal oscillations support metacognitive monitoring of decision making. Journal of Neuroscience, 37(4), 781–789.

Wolfe, J., & Horowitz, T. S. (2008). Visual search. Scholarpedia, 3(7), 3325.

Wolfe, J. M. (1994). Guided search 2.0 a revised model of visual search. Psychonomic Bulletin & Review, 1(2), 202–238.

Wolfe, J. M. (1998). What can 1 million trials tell us about visual search? Psychological Science, 9(1), 33–39.

Wolfe, J. M. (2001). Asymmetries in visual search: An introduction. Perception & Psychophysics, 63(3), 381–389.

Wolfe, J. M. (2012). When do i quit? The search termination problem in visual search. The Influence of Attention, Learning, and Motivation on Visual Search, 183–208.

Wolfe, J. M. (2021). Guided search 6.0: An updated model of visual search. Psychonomic Bulletin & Review, 1–33.

Wolfe, J. M., Cave, K. R., & Franzel, S. L. (1989). Guided search: An alternative to the feature integration model for visual search. Journal of Experimental Psychology: Human Perception and Performance, 15(3), 419.

Wolfe, J. M., & Gray, W. (2007). Guided search 4.0. Integrated Models of Cognitive Systems, 99–119.

Wolfe, J. M., & Horowitz, T. S. (2017). Five factors that guide attention in visual search. Nature Human Behaviour, 1(3), 1–8.

Wolfe, J. M., Palmer, E. M., & Horowitz, T. S. (2010). Reaction time distributions constrain models of visual search. Vision Research, 50(14), 1304–1311.

Wolpert, D. M., Ghahramani, Z., & Jordan, M. I. (1995). An internal model for sensorimotor integration. Science, 269(5232), 1880–1882.

Xue, G., Chen, C., Jin, Z., & Dong, Q. (2006). Language experience shapes fusiform activation when processing a logographic artificial language: An fMRI training study. Neuroimage, 31(3), 1315–1326.

Yokoyama, O., Miura, N., Watanabe, J., Takemoto, A., Uchida, S., Sugiura, M., … Nakamura, K. (2010). Right frontopolar cortex activity correlates with reliability of retrospective rating of confidence in short-term recognition memory performance. Neuroscience Research, 68(3), 199–206.

Yonelinas, A. P., Dobbins, I., Szymanski, M. D., Dhaliwal, H. S., & King, L. (1996). Signal-detection, threshold, and dual-process models of recognition memory: ROCs and conscious recollection. Consciousness and Cognition, 5(4), 418–441.

Yovel, G., & Kanwisher, N. (2005). The neural basis of the behavioral face-inversion effect. Current Biology, 15(24), 2256–2262.

Zhang, Y. R., & Onyper, S. (2020). Visual search asymmetry depends on target-distractor feature similarity: Is the asymmetry simply a result of distractor rejection speed? Attention, Perception, & Psychophysics, 82(1), 80–97.

Zylberberg, A., Barttfeld, P., & Sigman, M. (2012). The construction of confidence in a perceptual decision. Frontiers in Integrative Neuroscience, 6, 79.