Cognitive Psychology最新文献

Exposing learners to variability during training has been demonstrated to improve performance in subsequent transfer testing. Such variability benefits are often accounted for by assuming that learners are developing some general task schema or structure. However much of this research has neglected to account for differences in similarity between varied and constant training conditions. In a between-groups manipulation, we trained participants on a simple projectile launching task, with either varied or constant conditions. We replicate previous findings showing a transfer advantage of varied over constant training. Furthermore, we show that a standard similarity model is insufficient to account for the benefits of variation, but, if the model is adjusted to assume that varied learners are tuned towards a broader generalization gradient, then a similarity-based model is sufficient to explain the observed benefits of variation. Our results therefore suggest that some variability benefits can be accommodated within instance-based models without positing the learning of some schemata or structure.

Geometry defines entities that can be physically realized in space, and our knowledge of abstract geometry may therefore stem from our representations of the physical world. Here, we focus on Euclidean geometry, the geometry historically regarded as “natural”. We examine whether humans possess representations describing visual forms in the same way as Euclidean geometry – i.e., in terms of their shape and size. One hundred and twelve participants from the U.S. (age 3–34 years), and 25 participants from the Amazon (age 5–67 years) were asked to locate geometric deviants in panels of 6 forms of variable orientation. Participants of all ages and from both cultures detected deviant forms defined in terms of shape or size, while only U.S. adults drew distinctions between mirror images (i.e. forms differing in “sense”). Moreover, irrelevant variations of sense did not disrupt the detection of a shape or size deviant, while irrelevant variations of shape or size did. At all ages and in both cultures, participants thus retained the same properties as Euclidean geometry in their analysis of visual forms, even in the absence of formal instruction in geometry. These findings show that representations of planar visual forms provide core intuitions on which humans’ knowledge in Euclidean geometry could possibly be grounded.

Theory of mind (ToM) is an essential ability for social competence and communication, and it is necessary for understanding behaviors that differ from our own (Premack & Woodruff, 1978). Recent research suggests that tasks designed to measure ToM do not adequately capture a single ToM ability (Warnell and Redcay, 2019, Quesque and Rossetti, 2020) and, instead, might be related to tasks of general cognitive ability (Coyle, Elpers, Gonzalez, Freeman, & Baggio, 2018). This hinders the interpretation of experimental findings and puts into question the validity of the ToM construct. The current study is the first psychometric assessment of the structure of ToM to date. Comparing ToM to crystallized intelligence (Gc) and fluid intelligence (Gf), the study aims to (a) understand whether ToM should be considered a monolithic ability and (b) explore whether tasks of ToM adequately assess ToM, above and beyond general cognitive ability. For this, confirmatory factor analyses (CFAs), exploratory factor analysis (EFA), and exploratory network analysis (NMA) were conducted. The results of the models largely point to the same conclusion: while ToM tasks are not merely assessing cognitive ability, they are not purely assessing a single ToM construct either. Importantly, these findings align with recent theoretical accounts proposing that ToM should not be considered a monolithic construct (Quesque and Rossetti, 2020, Schaafsma et al., 2015, Devaine et al., 2014), and should instead be explored and measured as multiple domains.

People deciding between alternatives have at their disposal a toolbox containing both compensatory strategies, which take into account all available attributes of those alternatives, and noncompensatory strategies, which consider only some of the attributes. It is commonly assumed that noncompensatory strategies play only a minor role in decisions from givens, where attribute information is openly presented, because all attributes can be processed automatically “at a glance.” Based on a literature review, however, I establish that previous studies on strategy selection in decisions from givens have yielded highly heterogeneous findings, including evidence of widespread use of noncompensatory strategies. Drawing on insights from visual attention research on subitizing, I argue that this heterogeneity might be due to differences across studies in the number of attributes and in whether the same or different symbols are used to represent high/low attribute values across attributes. I tested the impact of these factors in two experiments with decisions from givens in which both the number of attributes shown for each alternative and the coding of attribute values was manipulated. An analysis of participants’ strategy use with a Bayesian multimethod approach (taking into account both decisions and response-time patterns) showed that a noncompensatory strategy was more frequently selected in conditions with a higher number of attributes; the type of attribute coding scheme did not affect strategy selection. Using a compensatory strategy in the conditions with eight (vs. four) attributes was associated with rather long response times and a high rate of strategy execution errors. The results suggest that decisions from givens can incur cognitive costs that prohibit reliance on automatic compensatory decision making and that can favor the adaptive selection of a noncompensatory strategy.

Motivation can improve performance when the potential rewards outweigh the cost of effort expended. In working memory (WM), people can prioritise rewarded items at the expense of unrewarded items, suggesting a fixed memory capacity. But can capacity itself change with motivation? Across four experiments (N = 30–34) we demonstrate motivational improvements in WM even when all items were rewarded. However, this was not due to better memory precision, but rather better selection of the probed item within memory. Motivational improvements operated independently of encoding, maintenance, or attention shifts between items in memory. Moreover, motivation slowed responses. This contrasted with the benefits of rewarding items unequally, which allowed prioritisation of one item over another. We conclude that motivation can improve memory recall, not via precision or capacity, but via speed-accuracy trade-offs when selecting the item to retrieve.

How do humans develop the capacity to reason? In five studies, we examined infants’ emerging ability to make exclusion inferences using negation, as in the disjunctive syllogism (P or Q; not P; therefore Q). Inspired by studies of non-human animals and older children, Experiments 1–3 used an exclusion task adapted from Call’s (2004) 2-cup paradigm and Experiments 4–5 used an exclusion task adapted from the blicket detector paradigm (Sobel & Kirkham, 2006). In both tasks, we found failure to make exclusion inferences at 15 months, fragile success at 17 months, and robust success by 20 months of age. These data converge with some prior evidence that fails to find a capacity to represent negation in infants younger than 15 months of age and conflict with other evidence from different paradigms that suggests infants do have this capacity. We discuss three different resolutions of these conflicting data, and suggest lines of further work that might adjudicate among them.

Cognitive control is guided by learning, as people adjust control to meet changing task demands. The two best-studied instances of “control-learning” are the enhancement of attentional task focus in response to increased frequencies of incongruent distracter stimuli, reflected in the list-wide proportion congruent (LWPC) effect, and the enhancement of switch-readiness in response to increased frequencies of task switches, reflected in the list-wide proportion switch (LWPS) effect. However, the latent architecture underpinning these adaptations in cognitive stability and flexibility – specifically, whether there is a single, domain-general, or multiple, domain-specific learners – is currently not known. To reveal the underlying structure of control-learning, we had a large sample of participants (N = 950) perform LWPC and LWPS paradigms, and afterwards assessed their explicit awareness of the task manipulations, as well as general cognitive ability and motivation. Structural equation modeling was used to evaluate several preregistered models representing different plausible hypotheses concerning the latent structure of control-learning. Task performance replicated standard LWPC and LWPS effects. Crucially, the model that best fit the data had correlated domain- and context-specific latent factors. Thus, people’s ability to adapt their on-task focus and between-task switch-readiness to changing levels of demand was mediated by distinct (though correlated) underlying factors. Model fit remained good when accounting for speed-accuracy trade-offs, variance in individual cognitive ability and self-reported motivation, as well as self-reported explicit awareness of manipulations and the order in which different levels of demand were experienced. Implications of these results for the cognitive architecture of dynamic cognitive control are discussed.

While distributional semantic models that represent word meanings as high-dimensional vectors induced from large text corpora have been shown to successfully predict human behavior across a wide range of tasks, they have also received criticism from different directions. These include concerns over their interpretability (how can numbers specifying abstract, latent dimensions represent meaning?) and their ability to capture variation in meaning (how can a single vector representation capture multiple different interpretations for the same expression?). Here, we demonstrate that semantic vectors can indeed rise up to these challenges, by training a mapping system (a simple linear regression) that predicts inter-individual variation in relational interpretations for compounds such as wood brush (for example brush FOR wood, or brush MADE OF wood) from (compositional) semantic vectors representing the meanings of these compounds. These predictions consistently beat different random baselines, both for familiar compounds (moon light, Experiment 1) as well as novel compounds (wood brush, Experiment 2), demonstrating that distributional semantic vectors encode variations in qualitative interpretations that can be decoded using techniques as simple as linear regression.

An intuition of ambivalence in cognition is particularly strong for complex decisions, for which the merits and demerits of different options are roughly equal but hard to compare. We examined information search in an experimental paradigm which tasked participants with an ambivalent question, while monitoring attentional dynamics concerning the information relevant to each option in different Areas of Interest (AOIs). We developed two dynamical models for describing eye tracking curves, for each response separately. The models incorporated a drift mechanism towards the various options, as in standard drift diffusion theory. In addition, they included a mechanism for intrinsic oscillation, which competed with the drift process and undermined eventual stabilization of the dynamics. The two models varied in the range of drift processes postulated. Higher support was observed for the simpler model, which only included drifts from an uncertainty state to either of two certainty states. In addition, model parameters could be weakly related to the eventual decision, complementing our knowledge of the way eye tracking structure relates to decision (notably the gaze cascade effect).

Most studies of visual-working memory employ one of two experimental paradigms: change-detection or continuous-stimulus reproduction. In this study, we extended the Interference Model (IM; Oberauer & Lin, 2017), which was designed for continuous reproduction, to the single-probe change-detection task. In continuous reproduction, participants occasionally report the non-target items instead of the target. The presence of non-target response is predicted by the Interference Model, which relies in part on the interference of non-target items to explain the set-size effect. By presenting a probe matching a non-target item, we can investigate the amount of interference from non-target items in change detection. As predicted by the Interference Model, we observed poorer performance in rejecting a probe matching a non-target item compared to a new probe (i.e., a cost due to intrusions from non-targets). We fitted the IM along with the Variable Precision, the Slot-Averaging, and the Neural-Population model to the data from two change-detection experiments. The models were equipped with a Bayesian decision rule based on the one used in Keshvari, van den Berg, and Ma (2013). The Interference Model and the Neural-Population model successfully predicted the set-size effect and the non-target intrusion cost, whereas the Variable Precision (VP) and Slot-Averaging (SA) models failed to predict the intrusion cost at all. Even with additional assumptions enabling VP and SA to produce intrusion costs, the IM still performed better than the competing models quantitatively.