Running head : GUESSING IN CHANGE DETECTION 1 Informed Guessing in Change Detection

Provided stimuli are highly distinct, the detection of changes between two briefly separated arrays appears to be achieved by an all-or-none process where either the relevant information is in working memory or observers guess. This observation suggests that it is possible to estimate the average number of items an observer was able to retain across a series of trials, a potentially highly informative cognitive characteristic. For each version of the change detection paradigm, for this estimate to be accurate, it is important to specify how observers use the information available to them. For some instantiations of this task it is possible that observers use knowledge of the contents of working memory even when they are in a guessing state, rather than selecting between the response alternatives at random. Here we test the suggestion that observers may be able to use their knowledge of the number of items in memory to guide guessing in two versions of the change detection task. The four experiments reported here suggest that participants are, in fact, able to use the parameters of the task to update their base expectation of a change occurring to arrive at more informed guessing. (194 words)

[1]  Kyle O. Hardman,et al.  Reasoning and memory: People make varied use of the information available in working memory. , 2016, Journal of experimental psychology. Learning, memory, and cognition.

[2]  Edward K. Vogel,et al.  The Contribution of Attentional Lapses to Individual Differences in Visual Working Memory Capacity , 2015, Journal of Cognitive Neuroscience.

[3]  John K. Kruschke,et al.  Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan , 2014 .

[4]  Dominic W. Massaro,et al.  Understanding variability in binary and continuous choice , 1998 .

[5]  Sumio Watanabe,et al.  Asymptotic Equivalence of Bayes Cross Validation and Widely Applicable Information Criterion in Singular Learning Theory , 2010, J. Mach. Learn. Res..

[6]  M. Chun,et al.  Organization of visual short-term memory. , 2000, Journal of experimental psychology. Learning, memory, and cognition.

[7]  M. Plummer Penalized loss functions for Bayesian model comparison. , 2008, Biostatistics.

[8]  Jeffrey N. Rouder,et al.  How to measure working memory capacity in the change detection paradigm , 2011, Psychonomic bulletin & review.

[9]  H Pashler,et al.  Familiarity and visual change detection , 1988, Perception & psychophysics.

[10]  Robert Taylor,et al.  Resources masquerading as slots: Flexible allocation of visual working memory , 2016, Cognitive Psychology.

[11]  N. Cowan,et al.  Working memory inefficiency: minimal information is utilized in visual recognition tasks. , 2013, Journal of experimental psychology. Learning, memory, and cognition.

[12]  D. Shanks,et al.  A Re-examination of Probability Matching and Rational Choice , 2002 .

[13]  Frank Tong,et al.  Introspective judgments predict the precision and likelihood of successful maintenance of visual working memory. , 2012, Journal of vision.

[14]  Andrew R. A. Conway,et al.  On the capacity of attention: Its estimation and its role in working memory and cognitive aptitudes , 2005, Cognitive Psychology.

[15]  Richard D. Morey,et al.  A Bayesian hierarchical model for the measurement of working memory capacity , 2011 .

[16]  Timothy F. Brady,et al.  Hierarchical Encoding in Visual Working Memory , 2010, Psychological science.

[17]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[18]  Jonathan W. Peirce,et al.  PsychoPy—Psychophysics software in Python , 2007, Journal of Neuroscience Methods.

[19]  Christopher Donkin,et al.  Discrete-slots models of visual working-memory response times. , 2013, Psychological review.

[20]  Mackenzie A. Sunday,et al.  Detection of the number of changes in a display in working memory. , 2016, Journal of experimental psychology. Learning, memory, and cognition.

[21]  D. Rubin,et al.  Inference from Iterative Simulation Using Multiple Sequences , 1992 .

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

[23]  Martyn Plummer,et al.  JAGS: A program for analysis of Bayesian graphical models using Gibbs sampling , 2003 .

[24]  Andrew Gelman,et al.  General methods for monitoring convergence of iterative simulations , 1998 .

[25]  Carly J. Leonard,et al.  The relationship between working memory capacity and broad measures of cognitive ability in healthy adults and people with schizophrenia. , 2013, Neuropsychology.

[26]  Chris Donkin,et al.  Landscaping analyses of the ROC predictions of discrete-slots and signal-detection models of visual working memory , 2014, Attention, perception & psychophysics.

[27]  W. Ma,et al.  Factorial comparison of working memory models. , 2014, Psychological review.

[28]  Nelson Cowan,et al.  Attention to attributes and objects in working memory. , 2013, Journal of experimental psychology. Learning, memory, and cognition.

[29]  W. Ma,et al.  Changing concepts of working memory , 2014, Nature Neuroscience.

[30]  N. Cowan The magical number 4 in short-term memory: A reconsideration of mental storage capacity , 2001, Behavioral and Brain Sciences.

[31]  Bradley P. Carlin,et al.  Bayesian measures of model complexity and fit , 2002 .

[32]  Aki Vehtari,et al.  Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC , 2015, Statistics and Computing.

[33]  Jeffrey N Rouder,et al.  An assessment of fixed-capacity models of visual working memory , 2008, Proceedings of the National Academy of Sciences.

[34]  S. Luck,et al.  Qualitative Similarities in the Visual Short-term Memory of Pigeons and People , 2011 .

[35]  W. Ma,et al.  A detection theory account of change detection. , 2004, Journal of vision.

[36]  E. Vogel,et al.  Visual working memory capacity: from psychophysics and neurobiology to individual differences , 2013, Trends in Cognitive Sciences.

[37]  Nelson Cowan,et al.  A two-stage search of visual working memory: investigating speed in the change-detection paradigm , 2014, Attention, perception & psychophysics.

[38]  William A. Link,et al.  On thinning of chains in MCMC , 2012 .

[39]  A. Treisman,et al.  Binding in short-term visual memory. , 2002, Journal of experimental psychology. General.