# Cognitive Psychology

• The role of domain-general cognitive resources in children’s construction of a vitalist theory of biology
Publication date: August 2018
Source:Cognitive Psychology, Volume 104

Author(s): Igor Bascandziev, Nathan Tardiff, Deborah Zaitchik, Susan Carey

Some episodes of learning are easier than others. Preschoolers can learn certain facts, such as “my grandmother gave me this purse,” only after one or two exposures (easy to learn; fast mapping), but they require several years to learn that plants are alive or that the sun is not alive (hard to learn). One difference between the two kinds of knowledge acquisition is that hard cases often require conceptual construction, such as the construction of the biological concept alive, whereas easy cases merely involve forming new beliefs formulated over concepts the child already has (belief revision, a form of knowledge enrichment). We asked whether different domain-general cognitive resources support these two types of knowledge acquisition (conceptual construction and knowledge enrichment that supports fast mapping) by testing 82 6-year-olds in a pre-training/training/post-training study. We measured children’s improvement in an episode involving theory construction (the beginning steps of acquisition of the framework theory of vitalist biology, which requires conceptual change) and in an episode involving knowledge enrichment alone (acquisition of little known facts about animals, such as the location of crickets’ ears and the color of octopus blood). In addition, we measured children’s executive functions and receptive vocabulary to directly compare the resources drawn upon in the two episodes of learning. We replicated and extended previous findings highlighting the differences between conceptual construction and knowledge enrichment, and we found that Executive Functions predict improvement on the Vitalism battery but not on the Fun Facts battery and that Receptive Vocabulary predicts improvement the Fun Facts battery but not on the Vitalism battery. This double dissociation provides new evidence for the distinction between the two types of knowledge acquisition, and bears on the nature of the learning mechanisms involved in each.

• Dynamic cognitive models of intertemporal choice
Publication date: August 2018
Source:Cognitive Psychology, Volume 104

Author(s): Junyi Dai, Timothy J. Pleskac, Thorsten Pachur

Traditionally, descriptive accounts of intertemporal choice have relied on static and deterministic models that assume alternative-wise processing of the options. Recent research, by contrast, has highlighted the dynamic and probabilistic nature of intertemporal choice and provided support for attribute-wise processing. Currently, dynamic models of intertemporal choice—which account for both the resulting choice and the time course over which the construction of a choice develops—rely exclusively on the framework of evidence accumulation. In this article, we develop and rigorously compare several candidate schemes for dynamic models of intertemporal choice. Specifically, we consider an existing dynamic modeling scheme based on decision field theory and develop two novel modeling schemes—one assuming lexicographic, noncompensatory processing, and the other built on the classical concepts of random utility in economics and discrimination thresholds in psychophysics. We show that all three modeling schemes can accommodate key behavioral regularities in intertemporal choice. When empirical choice and response time data were fit simultaneously, the models built on random utility and discrimination thresholds performed best. The results also indicated substantial individual differences in the dynamics underlying intertemporal choice. Finally, model recovery analyses demonstrated the benefits of including both choice and response time data for more accurate model selection on the individual level. The present work shows how the classical concept of random utility can be extended to incorporate response dynamics in intertemporal choice. Moreover, the results suggest that this approach offers a successful alternative to the dominating evidence accumulation approach when modeling the dynamics of decision making.

• Learning physical parameters from dynamic scenes
Publication date: August 2018
Source:Cognitive Psychology, Volume 104

Author(s): Tomer D. Ullman, Andreas Stuhlmüller, Noah D. Goodman, Joshua B. Tenenbaum

Humans acquire their most basic physical concepts early in development, and continue to enrich and expand their intuitive physics throughout life as they are exposed to more and varied dynamical environments. We introduce a hierarchical Bayesian framework to explain how people can learn physical parameters at multiple levels. In contrast to previous Bayesian models of theory acquisition (Tenenbaum, Kemp, Griffiths, &amp; Goodman, 2011), we work with more expressive probabilistic program representations suitable for learning the forces and properties that govern how objects interact in dynamic scenes unfolding over time. We compare our model to human learners on a challenging task of estimating multiple physical parameters in novel microworlds given short movies. This task requires people to reason simultaneously about multiple interacting physical laws and properties. People are generally able to learn in this setting and are consistent in their judgments. Yet they also make systematic errors indicative of the approximations people might make in solving this computationally demanding problem with limited computational resources. We propose two approximations that complement the top-down Bayesian approach. One approximation model relies on a more bottom-up feature-based inference scheme. The second approximation combines the strengths of the bottom-up and top-down approaches, by taking the feature-based inference as its point of departure for a search in physical-parameter space.

• Modeling the dynamics of recognition memory testing with an integrated model of retrieval and decision making
Publication date: August 2018
Source:Cognitive Psychology, Volume 104

Author(s): Adam F. Osth, Anna Jansson, Simon Dennis, Andrew Heathcote

A robust finding in recognition memory is that performance declines monotonically across test trials. Despite the prevalence of this decline, there is a lack of consensus on the mechanism responsible. Three hypotheses have been put forward: (1) interference is caused by learning of test items (2) the test items cause a shift in the context representation used to cue memory and (3) participants change their speed-accuracy thresholds through the course of testing. We implemented all three possibilities in a combined model of recognition memory and decision making, which inherits the memory retrieval elements of the Osth and Dennis (2015) model and uses the diffusion decision model (DDM: Ratcliff, 1978) to generate choice and response times. We applied the model to four datasets that represent three challenges, the findings that: (1) the number of test items plays a larger role in determining performance than the number of studied items, (2) performance decreases less for strong items than weak items in pure lists but not in mixed lists, and (3) lexical decision trials interspersed between recognition test trials do not increase the rate at which performance declines. Analysis of the model’s parameter estimates suggests that item interference plays a weak role in explaining the effects of recognition testing, while context drift plays a very large role. These results are consistent with prior work showing a weak role for item noise in recognition memory and that retrieval is a strong cause of context change in episodic memory.

• Editorial Board
Publication date: June 2018
Source:Cognitive Psychology, Volume 103

• Modeling 2-alternative forced-choice tasks: Accounting for both magnitude and difference effects
Publication date: June 2018
Source:Cognitive Psychology, Volume 103

Author(s): Roger Ratcliff, Chelsea Voskuilen, Andrei Teodorescu

We present a model-based analysis of two-alternative forced-choice tasks in which two stimuli are presented side by side and subjects must make a comparative judgment (e.g., which stimulus is brighter). Stimuli can vary on two dimensions, the difference in strength of the two stimuli and the magnitude of each stimulus. Differences between the two stimuli produce typical RT and accuracy effects (i.e., subjects respond more quickly and more accurately when there is a larger difference between the two). However, the overall magnitude of the pair of stimuli also affects RT and accuracy. In the more common two-choice task, a single stimulus is presented and the stimulus varies on only one dimension. In this two-stimulus task, if the standard diffusion decision model is fit to the data with only drift rate (evidence accumulation rate) differing among conditions, the model cannot fit the data. However, if either of one of two variability parameters is allowed to change with stimulus magnitude, the model can fit the data. This results in two models that are extremely constrained with about one tenth of the number of parameters than there are data points while at the same time the models account for accuracy and correct and error RT distributions. While both of these versions of the diffusion model can account for the observed data, the model that allows across-trial variability in drift to vary might be preferred for theoretical reasons. The diffusion model fits are compared to the leaky competing accumulator model which did not perform as well.

• The role of sensorimotor processes in social group contagion
Publication date: June 2018
Source:Cognitive Psychology, Volume 103

Author(s): Emiel Cracco, Marcel Brass

Although it is well known that action observation triggers an imitative response, not much is known about how these responses develop as a function of group size. Research on social contagion suggests that imitative tendencies initially increase but then stabilize as groups become larger. However, these findings have mainly been explained in terms of interpretative processes. Across seven experiments (N = 322), the current study investigated the contribution of sensorimotor processes to social group contagion by looking at the relation between group size and automatic imitation in a task that involved minimal interpretation. The results of Experiments 1–2 revealed that automatic imitation increased with group size according to an asymptotic curve on congruent trials but a linear curve on incongruent trials. The results of Experiments 3–7 showed that the asymptote on congruent trials disappeared when no control was needed, namely in the absence of incongruent trials. This suggests that the asymptote in the relation between group size and automatic imitation can be explained in terms of strategic control mechanisms that aim to prevent unintended imitative responses. The findings of the current study are in close correspondence with previous research in the social domain and as such support the hypothesis that sensorimotor processes contribute to the relation between group size and social contagion.

• Beyond Markov: Accounting for independence violations in causal reasoning
Publication date: June 2018
Source:Cognitive Psychology, Volume 103

Author(s): Bob Rehder

Although many theories of causal cognition are based on causal graphical models, a key property of such models—the independence relations stipulated by the Markov condition—is routinely violated by human reasoners. This article presents three new accounts of those independence violations, accounts that share the assumption that people’s understanding of the correlational structure of data generated from a causal graph differs from that stipulated by causal graphical model framework. To distinguish these models, experiments assessed how people reason with causal graphs that are larger than those tested in previous studies. A traditional common cause network ($Y 1 ← X → Y 2$) was extended so that the effects themselves had effects ($Z 1 ← Y 1 ← X → Y 2 → Z 2$). A traditional common effect network ($Y 1 → X ← Y 2$) was extended so that the causes themselves had causes ($Z 1 → Y 1 → X ← Y 2 ← Z 2$). Subjects’ inferences were most consistent with the beta-Q model in which consistent states of the world—those in which variables are either mostly all present or mostly all absent—are viewed as more probable than stipulated by the causal graphical model framework. Substantial variability in subjects’ inferences was also observed, with the result that substantial minorities of subjects were best fit by one of the other models (the dual prototype or a leaky gate models). The discrepancy between normative and human causal cognition stipulated by these models is foundational in the sense that they locate the error not in people’s causal reasoning but rather in their causal representations. As a result, they are applicable to any cognitive theory grounded in causal graphical models, including theories of analogy, learning, explanation, categorization, decision-making, and counterfactual reasoning. Preliminary evidence that independence violations indeed generalize to other judgment types is presented.