Psychological Review

  • The construct–behavior gap in behavioral decision research: A challenge beyond replicability. 20170515
    Behavioral decision research compares theoretical constructs like preferences to behavior such as observed choices. Three fairly common links from constructs to behavior are (1) to tally, across participants and decision problems, the number of choices consistent with one predicted pattern of pairwise preferences; (2) to compare what most people choose in each decision problem against a predicted preference pattern; or (3) to enumerate the decision problems in which two experimental conditions generate a 1-sided significant difference in choice frequency ‘consistent’ with the theory. Although simple, these theoretical links are heuristics. They are subject to well-known reasoning fallacies, most notably the fallacy of sweeping generalization and the fallacy of composition. No amount of replication can alleviate these fallacies. On the contrary, reiterating logically inconsistent theoretical reasoning over and again across studies obfuscates science. As a case in point, we consider pairwise choices among simple lotteries and the hypotheses of overweighting or underweighting of small probabilities, as well as the description–experience gap. We discuss ways to avoid reasoning fallacies in bridging the conceptual gap between hypothetical constructs, such as, for example, “overweighting” to observable pairwise choice data. Although replication is invaluable, successful replication of hard-to-interpret results is not. Behavioral decision research stands to gain much theoretical and empirical clarity by spelling out precise and formally explicit theories of how hypothetical constructs translate into observable behavior. (PsycINFO Database Record (c) 2017 APA, all rights reserved)
  • Interference and memory capacity limitations. 20170417
    Working memory (WM) is thought to have a fixed and limited capacity. However, the origins of these capacity limitations are debated, and generally attributed to active, attentional processes. Here, we show that the existence of interference among items in memory mathematically guarantees fixed and limited capacity limits under very general conditions, irrespective of any processing assumptions. Assuming that interference (a) increases with the number of interfering items and (b) brings memory performance to chance levels for large numbers of interfering items, capacity limits are a simple function of the relative influence of memorization and interference. In contrast, we show that time-based memory limitations do not lead to fixed memory capacity limitations that are independent of the timing properties of an experiment. We show that interference can mimic both slot-like and continuous resource-like memory limitations, suggesting that these types of memory performance might not be as different as commonly believed. We speculate that slot-like WM limitations might arise from crowding-like phenomena in memory when participants have to retrieve items. Further, based on earlier research on parallel attention and enumeration, we suggest that crowding-like phenomena might be a common reason for the 3 major cognitive capacity limitations. As suggested by Miller (1956) and Cowan (2001), these capacity limitations might arise because of a common reason, even though they likely rely on distinct processes. (PsycINFO Database Record (c) 2017 APA, all rights reserved)
  • The complementary roles of auditory and motor information evaluated in a Bayesian perceptuo-motor model of speech perception. 20170504
    There is a consensus concerning the view that both auditory and motor representations intervene in the perceptual processing of speech units. However, the question of the functional role of each of these systems remains seldom addressed and poorly understood. We capitalized on the formal framework of Bayesian Programming to develop COSMO (Communicating Objects using Sensory-Motor Operations), an integrative model that allows principled comparisons of purely motor or purely auditory implementations of a speech perception task and tests the gain of efficiency provided by their Bayesian fusion. Here, we show 3 main results: (a) In a set of precisely defined “perfect conditions,” auditory and motor theories of speech perception are indistinguishable; (b) When a learning process that mimics speech development is introduced into COSMO, it departs from these perfect conditions. Then auditory recognition becomes more efficient than motor recognition in dealing with learned stimuli, while motor recognition is more efficient in adverse conditions. We interpret this result as a general “auditory-narrowband versus motor-wideband” property; and (c) Simulations of plosive-vowel syllable recognition reveal possible cues from motor recognition for the invariant specification of the place of plosive articulation in context that are lacking in the auditory pathway. This provides COSMO with a second property, where auditory cues would be more efficient for vowel decoding and motor cues for plosive articulation decoding. These simulations provide several predictions, which are in good agreement with experimental data and suggest that there is natural complementarity between auditory and motor processing within a perceptuo-motor theory of speech perception. (PsycINFO Database Record (c) 2017 APA, all rights reserved)
  • A computational model of fraction arithmetic. 20170427
    Many children fail to master fraction arithmetic even after years of instruction, a failure that hinders their learning of more advanced mathematics as well as their occupational success. To test hypotheses about why children have so many difficulties in this area, we created a computational model of fraction arithmetic learning and presented it with the problems from a widely used textbook series. The simulation generated many phenomena of children’s fraction arithmetic performance through a small number of common learning mechanisms operating on a biased input set. The biases were not unique to this textbook series—they were present in 2 other textbook series as well—nor were the phenomena unique to a particular sample of children—they were present in another sample as well. Among other phenomena, the model predicted the high difficulty of fraction division, variable strategy use by individual children and on individual problems, relative frequencies of different types of strategy errors on different types of problems, and variable effects of denominator equality on the four arithmetic operations. The model also generated nonintuitive predictions regarding the relative difficulties of several types of problems and the potential effectiveness of a novel instructional approach. Perhaps the most general lesson of the findings is that the statistical distribution of problems that learners encounter can influence mathematics learning in powerful and nonintuitive ways. (PsycINFO Database Record (c) 2017 APA, all rights reserved)
  • Cyclical population dynamics of automatic versus controlled processing: An evolutionary pendulum. 20170713
    Psychologists, neuroscientists, and economists often conceptualize decisions as arising from processes that lie along a continuum from automatic (i.e., “hardwired” or overlearned, but relatively inflexible) to controlled (less efficient and effortful, but more flexible). Control is central to human cognition, and plays a key role in our ability to modify the world to suit our needs. Given its advantages, reliance on controlled processing may seem predestined to increase within the population over time. Here, we examine whether this is so by introducing an evolutionary game theoretic model of agents that vary in their use of automatic versus controlled processes, and in which cognitive processing modifies the environment in which the agents interact. We find that, under a wide range of parameters and model assumptions, cycles emerge in which the prevalence of each type of processing in the population oscillates between 2 extremes. Rather than inexorably increasing, the emergence of control often creates conditions that lead to its own demise by allowing automaticity to also flourish, thereby undermining the progress made by the initial emergence of controlled processing. We speculate that this observation may have relevance for understanding similar cycles across human history, and may lend insight into some of the circumstances and challenges currently faced by our species. (PsycINFO Database Record (c) 2017 APA, all rights reserved)
  • None of the above: A Bayesian account of the detection of novel categories. 20170713
    Every time we encounter a new object, action, or event, there is some chance that we will need to assign it to a novel category. We describe and evaluate a class of probabilistic models that detect when an object belongs to a category that has not previously been encountered. The models incorporate a prior distribution that is influenced by the distribution of previous objects among categories, and we present 2 experiments that demonstrate that people are also sensitive to this distributional information. Two additional experiments confirm that distributional information is combined with similarity when both sources of information are available. We compare our approach to previous models of unsupervised categorization and to several heuristic-based models, and find that a hierarchical Bayesian approach provides the best account of our data. (PsycINFO Database Record (c) 2017 APA, all rights reserved)
  • Noisy preferences in risky choice: A cautionary note. 20170601
    We examine the effects of multiple sources of noise in risky decision making. Noise in the parameters that characterize an individual’s preferences can combine with noise in the response process to distort observed choice proportions. Thus, underlying preferences that conform to expected value maximization can appear to show systematic risk aversion or risk seeking. Similarly, core preferences that are consistent with expected utility theory, when perturbed by such noise, can appear to display nonlinear probability weighting. For this reason, modal choices cannot be used simplistically to infer underlying preferences. Quantitative model fits that do not allow for both sorts of noise can lead to wrong conclusions. (PsycINFO Database Record (c) 2017 APA, all rights reserved)


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