Sensory noise increases metacognitive efficiency

Metacognitive efficiency quantifies people’s ability to introspect into their own decision making relative to their ability to perform the primary task. Despite years of research, it is still unclear how visual metacognitive efficiency can be manipulated. Here, we show that a hierarchical model of confidence generation makes a counterintuitive prediction: Higher sensory noise should increase metacognitive efficiency. The reason for this is that hierarchical models assume that although the primary decision is corrupted only by sensory noise, the confidence judgment is corrupted by both sensory and metacognitive noise. Therefore, increasing sensory noise has a smaller negative influence on the confidence judgment than on the perceptual decision, resulting in increased metacognitive efficiency. To test this prediction, we used a perceptual learning paradigm to decrease sensory noise. In Experiment 1, 7 days of training led to a significant decrease in sensory noise and a corresponding decrease in metacognitive efficiency. Experiment 2 showed the same effect in a brief 97-trial learning for each of 2 different tasks. Finally, in Experiment 3, we combined increasingly dissimilar stimulus contrasts to create conditions with higher sensory noise and observed a corresponding increase in metacognitive efficiency. Our findings demonstrate the existence of a robust positive relationship between across-trial sensory noise and metacognitive efficiency. These results could not be captured by a standard model in which decision and confidence judgments are made based on the same underlying information. Thus, our study provides direct evidence for the existence of metacognitive noise that corrupts confidence but not the perceptual decision.

[1]  Alexandre Pouget,et al.  Confidence and certainty: distinct probabilistic quantities for different goals , 2016, Nature Neuroscience.

[2]  Hakwan Lau,et al.  Continuous theta burst transcranial magnetic stimulation reduces resting state connectivity between visual areas. , 2013, Journal of neurophysiology.

[3]  Christopher Summerfield,et al.  Metacognition in human decision-making: confidence and error monitoring , 2012, Philosophical Transactions of the Royal Society B: Biological Sciences.

[4]  Neil A. Macmillan,et al.  Detection theory: A user's guide, 2nd ed. , 2005 .

[5]  D H Brainard,et al.  The Psychophysics Toolbox. , 1997, Spatial vision.

[6]  Shane T. Mueller,et al.  Decision noise: An explanation for observed violations of signal detection theory , 2008, Psychonomic bulletin & review.

[7]  B. Dosher,et al.  Mechanisms of perceptual learning , 1999, Vision Research.

[8]  B. Dosher,et al.  Visual Perceptual Learning and Models. , 2017, Annual review of vision science.

[9]  H. Lau,et al.  Attention induces conservative subjective biases in visual perception , 2011, Nature Neuroscience.

[10]  Hakwan Lau,et al.  Manipulation of working memory contents selectively impairs metacognitive sensitivity in a concurrent visual discrimination task , 2015, Neuroscience of consciousness.

[11]  Matthew Davidson,et al.  Awareness-related activity in prefrontal and parietal cortices in blindsight reflects more than superior visual performance , 2011, NeuroImage.

[12]  Barbara Anne Dosher,et al.  Visual perceptual learning , 2011, Neurobiology of Learning and Memory.

[13]  B. Dosher,et al.  The dynamics of perceptual learning: an incremental reweighting model. , 2005, Psychological review.

[14]  Rachel N. Denison,et al.  Supra-optimality may emanate from suboptimality, and hence optimality is no benchmark in multisensory integration , 2018, Behavioral and Brain Sciences.

[15]  V. Lamme,et al.  Repression of unconscious information by conscious processing: evidence from affective blindsight induced by transcranial magnetic stimulation. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[16]  David Soto,et al.  On the independence of visual awareness and metacognition: a signal detection theoretic analysis. , 2015, Journal of experimental psychology. Human perception and performance.

[17]  Caspar M. Schwiedrzik,et al.  Subjective and objective learning effects dissociate in space and in time , 2011, Proceedings of the National Academy of Sciences.

[18]  Takeo Watanabe,et al.  Perceptual learning incepted by decoded fMRI neurofeedback without stimulus presentation , 2012 .

[19]  Sarah Weigelt,et al.  Online psychophysics: reaction time effects in cognitive experiments , 2017, Behavior research methods.

[20]  M. D’Esposito,et al.  Causal evidence for frontal cortex organization for perceptual decision making , 2016, Proceedings of the National Academy of Sciences.

[21]  Davide Bruno,et al.  Investigating strength and frequency effects in recognition memory using type-2 signal detection theory. , 2009, Journal of experimental psychology. Learning, memory, and cognition.

[22]  Aaron R. Seitz,et al.  Rewards Evoke Learning of Unconsciously Processed Visual Stimuli in Adult Humans , 2009, Neuron.

[23]  A. Tolias,et al.  Trial-to-trial, uncertainty-based adjustment of decision boundaries in visual categorization , 2013, Proceedings of the National Academy of Sciences.

[24]  Diego E. Shalom,et al.  Perceptual learning effect on decision and confidence thresholds , 2016, Consciousness and Cognition.

[25]  Li Yan McCurdy,et al.  Limited Cognitive Resources Explain a Trade-Off between Perceptual and Metacognitive Vigilance , 2017, The Journal of Neuroscience.

[26]  H. Lau,et al.  How to measure metacognition , 2014, Front. Hum. Neurosci..

[27]  H. Pashler,et al.  Confidence and Accuracy of Near-Threshold Discrimination Responses , 2001, Consciousness and Cognition.

[28]  Anthony S. David,et al.  Failures of metacognition and lack of insight in neuropsychiatric disorders , 2014, Philosophical Transactions of the Royal Society B: Biological Sciences.

[29]  T. Haarmeier,et al.  Metacognitive Confidence Increases with, but Does Not Determine, Visual Perceptual Learning , 2016, PloS one.

[30]  D. M. Green,et al.  Signal detection theory and psychophysics , 1966 .

[31]  Yuka Sasaki,et al.  Perceptual learning: toward a comprehensive theory. , 2015, Annual review of psychology.

[32]  D. Merfeld,et al.  Unbounded evidence accumulation characterizes subjective visual vertical forced-choice perceptual choice and confidence. , 2017, Journal of neurophysiology.

[33]  Pascal Mamassian,et al.  Visual Confidence. , 2016, Annual review of vision science.

[34]  R. Passingham,et al.  Theta-burst transcranial magnetic stimulation to the prefrontal cortex impairs metacognitive visual awareness , 2010 .

[35]  Z L Lu,et al.  Perceptual learning reflects external noise filtering and internal noise reduction through channel reweighting. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[36]  Michael N. Shadlen,et al.  Effects of Cortical Microstimulation on Confidence in a Perceptual Decision , 2014, Neuron.

[37]  Joshua I. Sanders,et al.  Signatures of a Statistical Computation in the Human Sense of Confidence , 2016, Neuron.

[38]  Megan A. K. Peters,et al.  Perceptual confidence neglects decision-incongruent evidence in the brain , 2017, Nature Human Behaviour.

[39]  Aspen H. Yoo,et al.  Fechner’s Law in Metacognition: A Quantitative Model of Visual Working Memory Confidence , 2017, Psychological review.

[40]  S. Fleming,et al.  Domain-specific impairment in metacognitive accuracy following anterior prefrontal lesions , 2014, Brain : a journal of neurology.

[41]  S. Dehaene,et al.  Causal role of prefrontal cortex in the threshold for access to consciousness. , 2009, Brain : a journal of neurology.

[42]  Thomas S Wallsten,et al.  A stochastic detection and retrieval model for the study of metacognition. , 2012, Psychological review.

[43]  H. Lau,et al.  A signal detection theoretic approach for estimating metacognitive sensitivity from confidence ratings , 2012, Consciousness and Cognition.

[44]  Hakwan Lau,et al.  The signal processing architecture underlying subjective reports of sensory awareness , 2016, Neuroscience of consciousness.

[45]  Hakwan Lau,et al.  Signal Detection Theory Analysis of Type 1 and Type 2 Data: Meta-d′, Response-Specific Meta-d′, and the Unequal Variance SDT Model , 2014 .

[46]  A. Pouget,et al.  Perceptual learning as improved probabilistic inference in early sensory areas , 2011, Nature Neuroscience.

[47]  Hakwan Lau,et al.  Heuristic use of perceptual evidence leads to dissociation between performance and metacognitive sensitivity , 2016, Attention, Perception, & Psychophysics.

[48]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[49]  József Fiser,et al.  Neural Variability and Sampling-Based Probabilistic Representations in the Visual Cortex , 2016, Neuron.

[50]  Joshua de Leeuw,et al.  jsPsych: A JavaScript library for creating behavioral experiments in a Web browser , 2014, Behavior Research Methods.

[51]  A. Shimamura Toward a Cognitive Neuroscience of Metacognition , 2000, Consciousness and Cognition.

[52]  Timothy J. Pleskac,et al.  Two-stage dynamic signal detection: a theory of choice, decision time, and confidence. , 2010, Psychological review.

[53]  Joel L. Voss,et al.  Associative Recognition Memory Awareness Improved by Theta-Burst Stimulation of Frontopolar Cortex. , 2016, Cerebral cortex.

[54]  Wei Ji Ma,et al.  Bayesian inference with probabilistic population codes , 2006, Nature Neuroscience.

[55]  Bruce Luber,et al.  Direct injection of noise to the visual cortex decreases accuracy but increases decision confidence. , 2012, Journal of neurophysiology.

[56]  Geraint Rees,et al.  Relating Introspective Accuracy to Individual Differences in Brain Structure , 2010, Science.

[57]  G. Orban,et al.  Learning to See the Difference Specifically Alters the Most Informative V4 Neurons , 2006, The Journal of Neuroscience.

[58]  R. Dolan,et al.  Noradrenaline blockade specifically enhances metacognitive performance , 2017, eLife.

[59]  M. Shadlen,et al.  Representation of Confidence Associated with a Decision by Neurons in the Parietal Cortex , 2009, Science.

[60]  Roger W Li,et al.  Perceptual learning improves efficiency by re-tuning the decision 'template' for position discrimination , 2004, Nature Neuroscience.

[61]  Mark D'Esposito,et al.  Confidence Leak in Perceptual Decision Making , 2015, Psychological science.

[62]  T. O. Nelson,et al.  A comparison of current measures of the accuracy of feeling-of-knowing predictions. , 1984, Psychological bulletin.

[63]  Nathaniel D. Daw,et al.  Self-Evaluation of Decision-Making: A General Bayesian Framework for Metacognitive Computation , 2017, Psychological review.

[64]  P. Sterzer,et al.  Mesolimbic confidence signals guide perceptual learning in the absence of external feedback , 2016, eLife.

[65]  D. V. Cramon,et al.  Manipulation of working memory information is impaired in Parkinson's disease and related to working memory capacity. , 2002, Neuropsychology.

[66]  Ádám Kepecs,et al.  A mathematical framework for statistical decision confidence , 2015, bioRxiv.

[67]  R. Dolan,et al.  Confidence in value-based choice , 2012, Nature Neuroscience.

[68]  H. Lau,et al.  Prestimulus hemodynamic activity in dorsal attention network is negatively associated with decision confidence in visual perception. , 2012, Journal of neurophysiology.

[69]  L. Weiskrantz Blindsight revisited , 1996, Current Opinion in Neurobiology.