Résumés
Résumé
Les probabilités subjectives ont un rôle central dans la prise de décision. Si les modèles théoriques et les données expérimentales sont relativement silencieux en économie sur la façon dont se forment ces croyances lors du processus décisionnel, il n’est pas de même en sciences cognitives. Nous proposons ici une revue de littérature de l’étude de la métacognition au travers de modèles computationnels de détection du signal. Cette méthodologie est ensuite importée à la décision non perceptive et nous montrons comment son utilisation ouvre de nouvelles pistes de recherche dans l’étude des croyances subjectives en économie expérimentale.
Parties annexes
Bibliographie
- Bahrami, B., K. Olsen, D. Bang, A. Roepstorff, G. Rees et D. Frith (2012), « What Failure in Collective Decision-Making Tells us about Metacognition », Philosophical Transactions of the Royal Society B: Biological Sciences, 367 (1594) : 1350-1365.
- Bahrami, B., K. Olsen, P.E. Latham, A. Roepstorff, G. Rees et C.D. Frith (2010), « Optimally Interacting Minds », Science, 329 (5995) : 1081-1085.
- Baird, B., J. Smallwood, K.J. Gorgolewski et D.S. Margulies (2013), « Medial and Lateral Networks in Anterior Prefrontal Cortex Support Metacognitive Ability for Memory and Perception », Journal of Neuroscience, 33 : 16657-16665.
- Bang, D., R. Fusaroli, K. Tylen, K. Olsen, P.E. Latham, J.Y.F. Lau, A. Roepstorff, G. Rees, C.D. Frith et B. Bahrami (2014), « Does Interaction Matter? Testing whether a Confidence Heuristic can Replace Interaction in Collective Decision-Making », Consciousness and Cognition, 26 : 13-23.
- Barett, A.B., Z. Dienes et A.K. Seth (2013), « Measures of Metacognition on Signal-Detection Theoretic Models », Psychological Methods, 18 (4) : 535-552.
- Bogacz, R., E. Brown, J. Moehlis, P. Holmes et J.D. Cohen (2006), « The Physics of Optimal Decision Making: a Formal Analysis of Models of Performance in Two-Alternative Forced Choice Tasks », Psychological Review, 113 (4) : 700-765.
- Brier, G.W. (1950), « Verification of Forecasts Expressed in Terms of Probability », Monthly Weather Review, 78 (1) : 1-3.
- Busemeyer, J.R. et J.T. Townsend (1993), « Decision Field Theory: a Dynamic-Cognitive Approach to Decision Making in an Uncertain Environment », Psychological Review, 100 (3) : 432-459.
- Camerer, C. et D. Lovallo (1999), « Overconfidence and Excess Entry: an Experimental Approach », The American Economic Review, 89 (1) : 306-318.
- Charles, L., F. Van Opstal, S. Marti et S. Dehaene (2013), « Distinct Brain Mechanisms for Conscious versus Subliminal Error Detection », NeuroImage, 73 : 80-94.
- David, A.S., N. Bedford, B. Wiffen et J. Gilleen (2012), « Failures of Metacognition and Lack of Insight in Neuropsychiatric Disorders », Philosophical Transactions of the Royal Society B: Biological Sciences, 367 (1594) : 1379-1390.
- Del Cul, A., S. Dehaene, P. Reyes, E. Bravo et A. Slachevsky (2009), « Causal Role of Prefrontal Cortex in the Threshold for Access to Consciousness », Brain, 132 (9) : 2531-2540.
- De Martino, B., S.M. Fleming, N. Garrett et R.J. Dolan (2013), « Confidence in Value-Based Choice », Nature Neuroscience, 16 (5787) : 105-110.
- Diederich, A. (2003), « MDFT Account of Decision Making under Time Pressure », Psychonomic Bulletin and Review, 10 (1) : 157-166.
- Dienes Z. et A.K. Seth (2010), « Gambling on the Unconscious: a Comparison of Wagering and Confidence Ratings as Measures of Awareness in an Artificial Grammar Task », Consciousness and Cognition, 19 (2) : 674-681.
- Egan, J.P. (1975), Signal Detection Theory and ROC Analysis, New York, NY : Academic Press, 277 p.
- Evans, S. et P. Azzopardi (2007), « Evaluation of a “Bias-Free” Measure of Awareness », Spatial Vision, 20 (1-2) : 61-77.
- Fehr, E. et A. Rangel (2011), « Neuroeconomics Foundations of Economic Choices – Recent Advances », Journal of Economic Perspectives, 25 (4) : 3-30.
- Fleming, S.M. et R.J. Dolan (2012), « The Neural Basis of Accurate Metacognition », Philosophical Transactions of the Royal Society B: Biological Sciences, 367 (1594) : 1338-1349.
- Fleming, S.M. et C. Frith (2014), The Cognitive Neuroscience of Metacognition, Springer-Verlag : Berlin, Heidelberg.
- Fleming, S.M. et H.C. Lau (2014), « How to Measure Metacognition », Frontiers in Human Neuroscience, 8 : 443, 2014.
- Fleming, S.M., J. Ryu, J.G. Golfinos et K. Blackmon (2014), « A Domain-Specific Impairment in Metacognitive Accuracy Following Anterior Prefrontal Lesions », Brain, 137 (10) : 2811-2822.
- Fleming, s.M., S. Massoni, t. Gajdos et j.-C. Vergnaud (2016), « Metacognition about the Past and Future: Quantifying Common and Distinct Influences on Prospective and Retrospective Judgments of Self-Performance », Neuroscience of Consciousness, 2016 (1) : niw018.
- Fleming, S.M., R.S. Weil, Z. Nagy, R.J. Dolan et G. Rees (2010), « Relating Introspective Accuracy to Individual Differences in Brain Structure », Science, 329 (5998) : 1541-1543.
- Galvin, S.J., J.V. Podd, V. Drga et J. Whitmore (2003), « Type 2 Tasks in the Theory of Signal Detectability: Discrimination between Correct and Incorrect Decisions », Psychonomic Bulletin and Review, 10 : 843-876.
- Garfinkel, S.N., A.B. Barrett, L. Minati, R.J. Dolan, A.K. Seth et H.D. Critchley (2013), « What the Heart Forgets: Cardiac Timing Influence Memory for Words and is Modulated by Metacognition and Introspective Sensitivity », Psychophysiology, 50 (6) : 505-512.
- Gold, J.I. et M.N. Shadlen (2007), « The Neural Basis of Decision Making », Annual Review of Neuroscience, 30 : 535-574.
- Green, D. M. et J. A. Swets (1966), Signal Detection Theory and Psychophysics, John Wiley and Sons.
- Harvey, N. (1997), « Confidence in Judgment », Trends in Cognitive Sciences, 1 (2) : 78-82.
- Hollard, G., S. Massoni et J.-C. Vergnaud (2016), « In Search of Good Probability Assessors: An Experimental Comparison of Elicitation Rules for Confidence Judgments », Theory and Decision, 80 (3) : 363-387.
- Kepecs, A., N. Uchida, H. Zariwala et Z.F. Mainen (2008), « Neural Correlates, Computation and Behavioural Impact of Decision Confidence », Nature, 455 (7210) : 227-231.
- Kiani, R. et M. Shalden (2009), « Representation of Confidence Associated with a Decision by Neurons in Parietal Cortex Knowledge: Some Calibration Studies », Science, 324 (5928) : 759-764.
- Koriat, A. (2012), « When are Two Heads Better than one and Why? », Science, 336 (6079) : 360-362.
- Krantz, D.H. (1969), « Threshold Theories of Signal Detection », Psychological Review, 76 (3) : 308-324.
- Kunimoto, C., J. Miller et H. Pashler (2001), « Confidence and Accuracy of Near-Threshold Discrimination Responses », Consciousness and Cognition, 10 (3) : 294-340.
- Lee, T.G., R.S. Blumenfeld et M. D’Esposito (2013), « Disruption of Dorsolateral but not Ventrolateral Prefrontal Cortex Improves Unconscious Perceptual Memories », Journal of Neuroscience, 33 : 13233-13237.
- Levitt, H. (1971), « Transformed Up-Down Methods in Psychoacoustics », Journal of the Acoustical Society of America, 49 (2) : 467-477.
- Liberman, V. et A. Tversky (1993), « On the Evaluation of Probability Judgments: Calibration, Resolution, and Monotonicity », Psychological Bulletin, 114 : 162-173.
- Lichtenstein, S., B. Fischhoff et L. Phillips (1982), « Calibration of Probabilities: the State of the Art to 1980 », inD. Kahneman, P. Slovic et A. Tversky (éds), Judgment under Uncertainty: Heuristic and Biases, Cambridge, UK : Cambridge University Press, p. 306-334.
- Luce, R.D. (1959), Individual Choice Behavior: A Theoretical Analysis, New York, NY : Wiley.
- Luce, R.D. (1963), « Detection and Recognition », in R.D. Luce, R.R. Bush et E. Galenter (éds), Handbook of Mathematical Psychology, volume 1, New York, NY : Wiley, p. 103-189.
- Luce, R.D. (1963), « A Threshold Theory for Simple Detection Experiments », Psychological Review, 70 (1) : 71-79.
- Macmillan, N.A. et C.D. Creelman (2005), Detection Theory: A User’s Guide (2nd edition), Hove, UK : Psychology Press.
- Maniscalco, B. et H. Lau (2012), « A Signal Detection Theoretic Approach for Estimating Metacognitive Sensitivity from Confidence Ratings », Consciousness and Cognition, 21 (1) : 422-430.
- Maniscalco, B. et H. Lau (2014), « Signal Detection Theory Analysis of Type 1 and Type 2 Data: Meta-d’, Response-Specific Meta-d’, and the Unequal Variance SDT Model », inS.M. Fleming et C. Frith (éds), The Cognitive Neuroscience of Metacognition, Springer : Berlin, Heidelberg, p. 25-66.
- Massoni, S., T. Gajdos et J.-C. Vergnaud (2014), « Confidence Measurement in the Light of Signal Detection Theory », Frontiers in Psychology, 5 : 1455.
- Massoni, S. et N. Roux (2014), « Optimal Group Decision: a Matter of Confidence Calibration », Mimeo.
- Massoni, S. (2013), Essays on Subjective Probabilities and Metacognition, thèse de doctorat, University of Paris 1.
- Massoni, S., « Emotion as a Boost to Metacognition: How Worry Enhances the Quality of Confidence », Consciousness and Cognition, 29 : 189-198.
- Masson, M.E.J. et C.M. Rotello (2009), « Sources of Bias in the GoodmanKruskal Gamma Coefficient Measure of Association: Implications for Studies of Metacognitive Processes », Journal of Experimental Psychology: Learning, Memory and Cognition, 35 : 509-527.
- McCurdy, L.Y., B. Maniscalco, J. Metcalfe, K.Y. Liu, F.P. de Lange et H. Lau (2013), « Anatomical Coupling Between Distinct Metacognitive Systems for Memory and Visual Perception », The Journal of Neuroscience, 33 (5) : 1897-1906.
- Merkle, E.C., M. Smithson et J. Verkuilen (2011), « Hierarchical Models of Simple Mechanisms Underlying Confidence in Decision Making », Journal of Mathematical Psychology, 55 (1) : 57-67.
- Metz, C.E. et X. Pan (1999), « Proper Binormal ROC Curves: Theory and MaximumLikelihood Estimation », Journal of Mathematical Psychology, 43 (1) : 1-33.
- Middlebrooks, P.G., Z. Abzug et M.A. Sommer (2014), « Studying Metacognitive Processes at the Single-Neuron Level », in Fleming, S.M. et C.D. Frith (éds), The Cognitive Neuroscience of Metacognition, Springer : Berlin, Heidelberg, p. 225-244.
- Murphy, A.H. (1972), « Scalar and Vector Partitions of the Probability Score: Part I. Two-State Situation », Journal of Applied Meteorology, 11 : 273-282.
- Nelson, T.O. (1984), « A Comparison of Current Measures of the Accuracy of Feeling-of-Knowing Predictions », Psychological Bulletin, 95 : 109-133.
- Nieder, A. et S. Dehaene (2009), « Representation of Number in the Brain », Annual Review of Neuroscience, 32 (1) : 185-208.
- Overgaard, M. et K. Sandberg (2012), « Kinds of Access: Different Methods for Report Reveal Different Kinds of Metacognitive Access », Philosophical Transactions of the Royal Society B: Biological Sciences, 367 (1594) : 1287-1296.
- Piazza, M., V. Izard, P. Pinel, D. Le Bihan et S. Dehaene (2004), « Tuning Curves for Approximate Numerosity in the Human Intraparietal Sulcus », Neuron, 44 (3) : 547-555.
- Pica, P., C. Lemer, V. Izard et S. Dehaene (2004), « Exact and Approximate Arithmetic in Amazonian Indigene Group », Science, 306 (5695) : 499-503.
- Pleskac, T.J. et J.R. Busemyer (2010), « Two-Stage Dynamic Signal Detection: A Theory of Choice, Decision Time, and Confidence », Psychological Review, 117 (3) : 864-901.
- Ratcliff, R. et G. McKoon (2008), « The Diffusion Decision Model: Theory and Data for Two-Choice Decision Tasks », Neural Computation, 20 (4) : 873-922.
- Ratcliff, R. et J.J. Starns (2009), « Modeling Confidence and Response Time in Recognition Memory », Psychological Review, 116 (1) : 59-83.
- Ratcliff, R. (1978), « A Theory of Memory Retrieval », Psychological Review, 85 (2) : 59-108.
- Rounis, E., B. Maniscalco, J.C. Rothwell, R.E. Passingham et H. Lau (2010), « Theta-Burst Transcranial Magnetic Stimulation to the Prefrontal Cortex Impairs Metacognitive Visual Awareness », Cognitive Neuroscience, 9 (8) : 165-175.
- Savage, L.J. (1954), The Foundations of Statistics, New York, NY : John Wiley and Sons.
- Sorkin, R.D., C. J. Hays et R. West (2001), « Signal Detection Analysis of Group Decision Making », Psychological Review, 108 : 183-203.
- Summerfield, C. et K. Tsetsos (2012), « Building Bridges between Perceptual and Economic Decision-Making: Neural and Computational Mechanisms », Frontiers in Neuroscience, 6 (70) : 1-20.
- Wallsten, T.S. et D.V. Budescu (1983), « Encoding Subjective Probabilities: a Psychological and Psychometric Review », Management Science, 29 (2) : 151-173.
- Wickens, T.D. (2002), Elementary Signal Detection Theory, New-York, NY : Oxford University Press.
- Yaniv, I., F. Yates et K. Smith (1991), « Measures of Discrimination Skill in Probabilistic Judgment », Psychological Bulletin, 110 (3) : 611-617.
- Yates, J.F. (1982), « External Correspondence: Decompositions of the Mean Probability Score », Organizational Behavior and Human Performance, 30 (1) : 132-156.
- Yeung, N. et C. Summerfield (2012), « Metacognition in Human Decision-Making; Confidence and Error Monitoring », Philosophical Transactions of the Royal Society B: Biological Sciences, 367 (1594) : 1310-1321.