Update paper

paper.bib

@@ -1,5 +1,5 @@
 
-@article{Rausch:2017,
+@article{Rausch2017,
 	title = {Should metacognition be measured by logistic regression?},
 	volume = {49},
 	rights = {All rights reserved},
@@ -14,14 +14,33 @@ @article{Rausch:2017
 	file = {PDF:C\:\\Users\\mru\\Zotero\\storage\\S5EC6DSC\\Rausch (2017) Should metacognition be measured by logistic regression.pdf:application/pdf},
 }
 
-@book{Green:1966,
+@book{Green1966,
 	location = {New York},
 	title = {Signal detection theory and psychophysics},
 	publisher = {Wiley},
 	author = {Green, D. M. and Swets, J. A.},
 	date = {1966},
 }
 
+@article{pereira_evidence_2021,
+	title = {Evidence accumulation relates to perceptual consciousness and monitoring},
+	volume = {12},
+	issn = {2041-1723},
+	url = {http://www.nature.com/articles/s41467-021-23540-y},
+	doi = {10.1038/s41467-021-23540-y},
+	abstract = {Abstract
+            A fundamental scientific question concerns the neural basis of perceptual consciousness and perceptual monitoring resulting from the processing of sensory events. Although recent studies identified neurons reflecting stimulus visibility, their functional role remains unknown. Here, we show that perceptual consciousness and monitoring involve evidence accumulation. We recorded single-neuron activity in a participant with a microelectrode in the posterior parietal cortex, while they detected vibrotactile stimuli around detection threshold and provided confidence estimates. We find that detected stimuli elicited neuronal responses resembling evidence accumulation during decision-making, irrespective of motor confounds or task demands. We generalize these findings in healthy volunteers using electroencephalography. Behavioral and neural responses are reproduced with a computational model considering a stimulus as detected if accumulated evidence reaches a bound, and confidence as the distance between maximal evidence and that bound. We conclude that gradual changes in neuronal dynamics during evidence accumulation relates to perceptual consciousness and perceptual monitoring in humans.},
+	pages = {3261},
+	number = {1},
+	journaltitle = {Nature Communications},
+	shortjournal = {Nat Commun},
+	author = {Pereira, Michael and Megevand, Pierre and Tan, Mi Xue and Chang, Wenwen and Wang, Shuo and Rezai, Ali and Seeck, Margitta and Corniola, Marco and Momjian, Shahan and Bernasconi, Fosco and Blanke, Olaf and Faivre, Nathan},
+	urldate = {2022-09-21},
+	date = {2021-12},
+	langid = {english},
+	file = {Pereira et al. - 2021 - Evidence accumulation relates to perceptual consci.pdf:C\:\\Users\\mru\\Zotero\\storage\\N2HZYAJZ\\Pereira et al. - 2021 - Evidence accumulation relates to perceptual consci.pdf:application/pdf},
+}
+
 @article{Rausch2018,
 	title = {Confidence in masked orientation judgments is informed by both evidence and visibility},
 	volume = {80},
@@ -92,6 +111,19 @@ @article{Shekhar2020a
 	file = {PDF:C\:\\Users\\mru\\Zotero\\storage\\I2Y99AIH\\Shekhar (2020) The nature of metacognitive inefficiency.pdf:application/pdf},
 }
 
+@article{guggenmos_reverse_2022,
+	title = {Reverse engineering of metacognition},
+	volume = {11},
+	doi = {10.7554/eLife.75420},
+	abstract = {The human ability to introspect on thoughts, perceptions or actions − metacognitive ability − has become a focal topic of both cognitive basic and clinical research. At the same time it has become increasingly clear that currently available quantitative tools are limited in their ability to make unconfounded inferences about metacognition. As a step forward, the present work introduces a comprehensive modeling framework of metacognition that allows for inferences about metacognitive noise and metacognitive biases during the readout of decision values or at the confidence reporting stage. The model assumes that confidence results from a continuous but noisy and potentially biased transformation of decision values, described by a confidence link function. A canonical set of metacognitive noise distributions is introduced which differ, amongst others, in their predictions about metacognitive sign flips of decision values. Successful recovery of model parameters is demonstrated, and the model is validated on an empirical data set. In particular, it is shown that metacognitive noise and bias parameters correlate with conventional behavioral measures. Crucially, in contrast to these conventional measures, metacognitive noise parameters inferred from the model are shown to be independent of performance. This work is accompanied by a toolbox ({ReMeta}) that allows researchers to estimate key parameters of metacognition in confidence datasets.},
+	pages = {1--29},
+	journaltitle = {{eLife}},
+	author = {Guggenmos, Matthias},
+	date = {2022},
+	langid = {english},
+	file = {Guggenmos - 2021 - Reverse engineering of metacognition.pdf:C\:\\Users\\mru\\Zotero\\storage\\MGJ2IMC6\\Guggenmos - 2021 - Reverse engineering of metacognition.pdf:application/pdf},
+}
+
 @incollection{Maniscalco2014,
 	location = {Berlin Heidelberg},
 	title = {Signal Detection Theory Analysis of Type 1 and Type 2 Data: Meta-d', Response- Specific Meta-d', and the Unequal Variance {SDT} Model},
@@ -117,6 +149,24 @@ @article{Maniscalco2016
 	file = {PDF:C\:\\Users\\mru\\Zotero\\storage\\FUXY3PI9\\Maniscalco (2016) The signal processing architecture underlying subjective reports of sensory awareness.pdf:application/pdf},
 }
 
+@article{Desender2021,
+	title = {Dynamic expressions of confidence within an evidence accumulation framework},
+	volume = {207},
+	issn = {18737838},
+	url = {https://doi.org/10.1016/j.cognition.2020.104522},
+	doi = {10.1016/j.cognition.2020.104522},
+	abstract = {Human observers can reliably report their confidence in the choices they make. An influential framework conceptualizes decision confidence as the probability of a decision being correct, given the choice made and the evidence on which it was based. This framework accounts for three diagnostic signatures of human confidence reports, including an opposite dependence of confidence on evidence strength for correct and error trials. However, the framework does not account for the temporal evolution of these signatures, because it only describes the transformation of a static representation of evidence into choice and the associated confidence. Here, we combine this framework with another influential framework: dynamic accumulation of evidence over time, and build on the notion that confidence reflects the probability of being correct, given the choice and accumulated evidence up until that point. Critically, we show that such a dynamic model predicts that the diagnostic signatures of confidence depend on time; most critically, it predicts a stronger opposite dependence of confidence on evidence strength and choice correctness as a function of time. We tested, and confirmed, these predictions in human behaviour during random dot motion discrimination, in which confidence judgments were queried at different points in time. We conclude that human confidence reports reflect the dynamics of the probability of being correct given the accumulated evidence and choice.},
+	pages = {1--11},
+	number = {104522},
+	journaltitle = {Cognition},
+	author = {Desender, Kobe and Donner, Tobias H. and Verguts, Tom},
+	date = {2021},
+	pmid = {33256974},
+	note = {Publisher: Elsevier B.V.},
+	keywords = {Confidence, Decision making, Drift diffusion model, Metacognition},
+	file = {PDF:C\:\\Users\\mru\\Zotero\\storage\\7ZB7YBS8\\Desender (2021) Dynamic expressions of confidence.pdf:application/pdf},
+}
+
 @article{Rausch2020,
 	title = {Cognitive modelling reveals distinct electrophysiological markers of decision confidence and error monitoring},
 	volume = {218},
@@ -130,6 +180,52 @@ @article{Rausch2020
 	file = {PDF:C\:\\Users\\mru\\Zotero\\storage\\CVK3TM6G\\Rausch (2020) Distinct EEG correlates of confidence and error monitoring.pdf:application/pdf},
 }
 
+@article{boundy-singer_confidence_2022,
+	title = {Confidence reflects a noisy decision reliability estimate},
+	volume = {7},
+	issn = {2397-3374},
+	url = {https://www.nature.com/articles/s41562-022-01464-x},
+	doi = {10.1038/s41562-022-01464-x},
+	pages = {142--154},
+	number = {1},
+	journaltitle = {Nature Human Behaviour},
+	shortjournal = {Nat Hum Behav},
+	author = {Boundy-Singer, Zoe M. and Ziemba, Corey M. and Goris, Robbe L. T.},
+	urldate = {2023-03-10},
+	date = {2022-11-07},
+	langid = {english},
+	file = {Boundy-Singer et al. - 2022 - Confidence reflects a noisy decision reliability e.pdf:C\:\\Users\\mru\\Zotero\\storage\\I8G9FSF7\\Boundy-Singer et al. - 2022 - Confidence reflects a noisy decision reliability e.pdf:application/pdf},
+}
+
+@article{hellmann_simultaneous_2023,
+	title = {Simultaneous modeling of choice, confidence, and response time in visual perception},
+	volume = {130},
+	rights = {All rights reserved},
+	doi = {10.1037/rev0000411},
+	abstract = {How can choice, confidence, and response times be modeled simultaneously? Here, we propose the new dynamical weighted evidence and visibility model ({dynWEV}), an extension of the drift diffusion model of decision making, to account for choices, reaction times, and confidence simultaneously. The decision process in a binary perceptual task is described as a Wiener process accumulating sensory evidence about the choice options bounded by two constant thresholds. To account for confidence judgments, we assume a period of postdecisional accumulation of sensory evidence and parallel accumulation of information about the reliability of the present stimulus. We examined model fits in two experiments, a motion discrimination task with random dot kinematograms and a post-masked orientation discrimination task. A comparison between the dynamical weighted evidence and visibility model, two-stage dynamical signal detection theory, and several versions of race models of decision making showed that only {dynWEV} produced acceptable fits of choices, confidence, and reaction time. This finding suggests that confidence judgments depend not only on choice evidence but also on a parallel estimate of stimulus discriminability and postdecisional accumulation of evidence.},
+	pages = {1521--1543},
+	number = {6},
+	journaltitle = {Psychological Review},
+	author = {Hellmann, Sebastian and Zehetleitner, Michael and Rausch, Manuel},
+	date = {2023},
+	langid = {english},
+	file = {Hellmann et al. - Simultaneous modeling of choice, confidence, and r.pdf:C\:\\Users\\mru\\Zotero\\storage\\NXX7SB92\\Hellmann et al. - Simultaneous modeling of choice, confidence, and r.pdf:application/pdf},
+}
+
+@article{rahnev_consensus_2022,
+	title = {Consensus Goals in the Field of Visual Metacognition},
+	volume = {17},
+	doi = {10.1177/174569162210756},
+	abstract = {Despite the tangible progress in psychological and cognitive sciences over the last several years, these disciplines still trail other more mature sciences in identifying the most important questions that need to be solved. Reaching such consensus could lead to greater synergy across different laboratories, faster progress, and increased focus on solving important problems rather than pursuing isolated, niche efforts. Here, 26 researchers from the field of visual metacognition reached consensus on four long-term and two medium-term common goals. We describe the process that we followed, the goals themselves, and our plans for accomplishing these goals. If this effort proves successful within the next few years, such consensus building around common goals could be adopted more widely in psychological science.},
+	pages = {1746--1765},
+	number = {6},
+	journaltitle = {Perspectives on Psychological Science},
+	author = {Rahnev, Dobromir and Balsdon, Tarryn and Charles, Lucie and de Gardelle, Vincent and Denison, Rachel and Desender, Kobe and Faivre, Nathan and Filevich, Elisa and Fleming, Stephen M. and Jehee, Janneke and Lau, Hakwan and Lee, Alan L. F. and Locke, Shannon M. and Mamassian, Pascal and Odegaard, Brian and Peters, Megan A K and Reyes, Gabriel and Rouault, Marion and Sackur, Jérôme and Samaha, Jason and Sergent, Claire and Sherman, Maxine T. and Siedlecka, Marta and Soto, David and Vlassova, Alexandra and Zylberberg, Ariel},
+	date = {2022},
+	langid = {english},
+	file = {Rahnev et al. - Consensus Goals in the Field of Visual Metacogniti.pdf:C\:\\Users\\mru\\Zotero\\storage\\8NXYYQUS\\Rahnev et al. - Consensus Goals in the Field of Visual Metacogniti.pdf:application/pdf},
+}
+
 @article{shekhar_how_2023,
 	title = {How Do Humans Give Confidence? A Comprehensive Comparison of Process Models of Perceptual Metacognition},
 	doi = {10.1037/xge0001524},
@@ -141,6 +237,27 @@ @article{shekhar_how_2023
 	file = {Shekhar und Rahnev - How Do Humans Give Confidence A Comprehensive Comp.pdf:C\:\\Users\\mru\\Zotero\\storage\\549ZQDCI\\Shekhar und Rahnev - How Do Humans Give Confidence A Comprehensive Comp.pdf:application/pdf},
 }
 
+@book{hautus_detection_2021,
+	location = {New York},
+	edition = {3},
+	title = {Detection theory: A user's guide},
+	publisher = {Routledge},
+	author = {Hautus, Michael J and Macmillan, Neil A and Creelman, C Douglas},
+	date = {2021},
+}
+
+@article{egan_operating_1959,
+	title = {Operating Characteristics Determined by Binary Decisions and by Ratings},
+	volume = {31},
+	pages = {768--773},
+	number = {6},
+	journaltitle = {Journal of the Acoustical Society of America},
+	author = {Egan, James P and Schulman, Arthur I and Greenberg, Gordon Z},
+	date = {1959},
+	langid = {english},
+	file = {Egan et al. - Operating Characteristics Determined by Binary Dec.pdf:C\:\\Users\\mru\\Zotero\\storage\\ZSFH43UD\\Egan et al. - Operating Characteristics Determined by Binary Dec.pdf:application/pdf},
+}
+
 @article{rausch_measures_2023,
 	title = {Measures of metacognitive efficiency across cognitive models of decision confidence.},
 	rights = {All rights reserved},
@@ -156,3 +273,16 @@ @article{rausch_measures_2023
 	langid = {english},
 	file = {Rausch et al. - 2023 - Measures of metacognitive efficiency across cognit.pdf:C\:\\Users\\mru\\Zotero\\storage\\JZ2J69PU\\Rausch et al. - 2023 - Measures of metacognitive efficiency across cognit.pdf:application/pdf},
 }
+
+@misc{hellmann_confidence_2024,
+	title = {Confidence is influenced by evidence accumulation time in dynamical decision models},
+	rights = {https://creativecommons.org/licenses/by/4.0/legalcode},
+	url = {https://osf.io/5ze8t},
+	doi = {10.31234/osf.io/5ze8t},
+	abstract = {Confidence judgments are closely correlated with response times across a wide range of decision tasks. Sequential sampling models offer two competing explanations for the relationship between confidence and response time: According to some models, decision time directly influences confidence. Other models explain the correlation by linking subjective confidence computation to the decision process dynamics. In previous model comparisons, drift diffusion-based confidence models that do not explicitly consider decision time in the computation of confidence, provided superior model fits compared to race models that directly included decision time in the internal computation of confidence.},
+	author = {Hellmann, Sebastian and Zehetleitner, Michael and Rausch, Manuel},
+	urldate = {2024-03-26},
+	date = {2024},
+	langid = {english},
+	file = {Hellmann et al. - 2023 - Confidence is influenced by evidence accumulation .pdf:C\:\\Users\\mru\\Zotero\\storage\\XRR256WT\\Hellmann et al. - 2023 - Confidence is influenced by evidence accumulation .pdf:application/pdf},
+}