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We introduce the Category Abstraction Learning (CAL) model, a cognitive framework formally describing category learning built on similarity-based generalization, dissimilarity-based abstraction, two attention learning mechanisms, error-driven knowledge structuring, and stimulus memorization. Our hypotheses draw on an array of empirical and theoretical insights connecting reinforcement and category learning. The key novelty of the model is its explanation of how rules are learned from scratch based on three central assumptions. (a) Category rules emerge from two processes of stimulus generalization (similarity) and its direct inverse (category contrast) on independent dimensions. (b) Two attention mechanisms guide learning by focusing on rules, or on the contexts in which they produce errors. (c) Knowing about these contexts inhibits executing the rule, without correcting it, and consequently leads to applying partial rules in different situations. The model is designed to capture both systematic and individual differences in a broad range of learning paradigms. We illustrate the model's explanatory scope by simulating several benchmarks, including the classic Six Problems, the 5-4 problem, and linear separability. Beyond the common approach of predicting average response probabilities, we also propose explanations for more recently studied phenomena that challenge existing learning accounts, regarding task instructions, individual differences in rule extrapolation in three different tasks, individual attention shifts to stimulus features during learning, and other phenomena. We discuss CAL's relation to different models, and its potential to measure the cognitive processes regarding attention, abstraction, error detection, and memorization from multiple psychological perspectives. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Cognitive science invokes semantic networks to explain diverse phenomena, from memory retrieval to creativity. Research in these areas often assumes a single underlying semantic network that is shared across individuals. Yet, recent evidence suggests that content, size, and connectivity of semantic networks are experience-dependent, implying sizable individual and age-related differences. Here, we investigate individual and age differences in the semantic networks of younger and older adults by deriving semantic networks from both fluency and similarity rating tasks. Crucially, we use a megastudy approach to obtain thousands of similarity ratings per individual to allow us to capture the characteristics of individual semantic networks. We find that older adults possess lexical networks with smaller average degree and longer path lengths relative to those of younger adults, with older adults showing less interindividual agreement and thus more unique lexical representations relative to younger adults. Furthermore, this approach shows that individual and age differences are not evenly distributed but, rather, are related to weakly connected, peripheral parts of the networks. All in all, these results reveal the interindividual differences in both the content and the structure of semantic networks that may accumulate across the life span as a function of idiosyncratic experiences.

How do we decide what to say to ensure our meanings will be understood? The Rational Speech Act model (RSA, Frank & Goodman, 2012) asserts that speakers plan what to say by comparing the informativity of words in a particular context. We present the first example of an RSA model of sentence level (who-did-what-to-whom) meanings. In these contexts, the set of possible messages must be abstracted from entities in common ground (people and objects) to possible events (Jane eats the apple, Marco peels the banana), with each word contributing unique semantic content. How do speakers accomplish the transformation from context to compositional, informative messages? In a communication game, participants described transitive events (e.g. Jane pets the dog), with only two words, in contexts where two words either were or were not enough to uniquely identify an event. Adults chose utterances matching the predictions of the RSA even when there was no possible fully 'successful' utterance. Thus we show that adults’ communicative behavior can be described by a model that accommodates informativity in context, beyond the set of possible entities in common ground. This study provides the first evidence that adults' language production is affected, at the level of argument structure, by the graded informativity of possible utterances in context, and suggests that full- blown natural speech may result from speakers who model and adapt to the listener’s needs.

How do our valuation systems change to homeostatically correct undesirable psychological or physiological states, such as those caused by hunger? There is evidence that hunger increases discounting for food rewards, biasing choices towards smaller but sooner food reward over larger but later reward. However, it is not understood how hunger modulates delay discounting for non-food items. We outline and quantitatively evaluate six possible models of how our valuation systems modulate discounting of various commodities in the face of the undesirable state of being hungry. With a repeated-measures design, an experimental hunger manipulation, and quantitative modeling, we find strong evidence that hunger causes large increases in delay discounting for food, with an approximately 25% spillover effect to non-food commodities. The results provide evidence that in the face of hunger, our valuation systems increase discounting for commodities, which cannot achieve a desired state change as well as for those commodities that can. Given that strong delay discounting can cause negative outcomes in many non-food (consumer, investment, medical, or inter-personal) domains, the present findings suggest caution may be necessary when making decisions involving non-food outcomes while hungry.

By definition, individuals with absolute pitch (AP) can categorize an isolated musical note with near perfect accuracy without a reference pitch. This definition implies a uniformity of performance across people; however, in reality AP is a complex, multidimensional ability, shaped by both early and recent auditory experiences. In the present study we assess how individual differences in working memory, musical expertise, and language background relate to the accuracy with which an AP possessor can identify an isolated musical note. In a standard test of AP ability, all AP participants performed virtually perfectly. When tested on more challenging notes, drawn from less frequently experienced timbres and octave ranges, we found that working memory positively related to note categorization performance, though only among individuals who reported a tonal language background. This interaction between tonal language and working memory, however, may have been partly grounded by differences in musical expertise reported between tonal and non-tonal language. Supporting this possibility, in a follow-up analysis we observed a general interaction between working memory performance and musical expertise across all participants. Taken together, these results highlight the complexity of AP categorization when considered as an auditory skill rather than a native talent. The observation that working memory may be an important component of auditory processing in AP when the to-be-judged sounds are less easily categorized is consistent with recent theoretical accounts of how working memory and expertise relate to auditory recognition more broadly.

Events that conform to our expectations, i.e, are congruent with our world knowledge or schemas, are better remembered than unrelated events. Yet events that conflict with schemas can also be remembered better. We examined this apparent paradox in four experiments, in which schemas were established by training ordinal relationships between randomly-paired objects, while episodic memory was tested for the number of objects on each trial. Better memory was found for both congruent and incongruent trials, relative to unrelated trials, producing memory performance that was a “U-shaped” function of congruency. Furthermore, the incongruency advantage, but not congruency advantage, emerged even if the information probed by the memory test was irrelevant to the schema, while the congruency advantage, but not incongruency advantage, also emerged after initial encoding. Schemas therefore augment episodic memory in multiple ways, depending on the match between novel and existing information.

Certain "generic" generalizations concern functions and purposes, e.g., cars are for driving. Some functional properties yield unacceptable teleological generics: for instance, cars are for parking seems false even though people park cars as often as they drive them. No theory of teleology in philosophy or psychology can explain what makes teleological generics acceptable. However, a recent theory (Prasada, 2017; PrasadaDillingham, 2006; Prasada, Khemlani, Leslie,Glucksberg, 2013) argues that a certain type of mental representation - a "principled" connection between a kind and a property - licenses generic generalizations. The account predicts that people should accept teleological generics that describe kinds and properties linked by a principled connection. Under the analysis, car bears a principled connection to driving (a car's primary purpose) and a non-principled connection to parking (an incidental consequence of driving). We report four experiments that tested and corroborated the theory's predictions, and we describe a regression analysis that rules out alternative accounts. We conclude by showing how the theory we developed can serve as the foundation for a general theory of teleological thinking.

Although euphemisms are intended to put a more positive spin on the words they replace, some euphemisms are ineffective. Our study examined the effectiveness of a popular euphemism for persons with disabilities, special needs. Most style guides prescribe against using the euphemism special needs and recommend instead using the non-euphemized term disability; disability advocates argue adamantly against the euphemism special needs, which they find offensive. In contrast, many parents of children with disabilities prefer to use special needs rather than disability. But no empirical study has examined whether special needs is more or less positive than the term it replaces. Therefore, we gathered a sample of adult participants from the general population (N = 530) and created a set of vignettes that allowed us to measure how positively children, college students, and middle-age adults are viewed when they are described as having special needs, having a disability, having a certain disability (e.g., is blind, has Down syndrome), or with no label at all. We predicted and observed that persons are viewed more negatively when described as having special needs than when described as having a disability or having a certain disability, indicating that special needs is an ineffective euphemism. Even for members of the general population who have a personal connection to disability (e.g., as parents of children with disabilities), the euphemism special needs is no more effective than the non euphemized term disability. We also collected free associations to the terms special needs and disability and found that special needs is associated with more negativity; special needs conjures up more associations with developmental disabilities (such as intellectual disability) whereas disability is associated with a more inclusive set of disabilities; and special needs evokes more unanswered questions. These findings recommend against using the euphemism special needs.

This paper investigates how cognition facilitates the adoption of new words through a study of the large-scale Reddit corpus, which contains written, threaded conversations conducted over the internet. Parameters for the cognitive architecture are estimated. Using ACT-R's account of declarative memory, the activation of memory chunks representing words is traced and compared to usage statistics sampled from a year of data. Potential values for decay and retrieval threshold are identified according to model fit and growth rates of word adoption. The resulting estimate for the decay parameter, d, is 0.22, and the estimate for the retrieval threshold parameter, rt, lies between 3.4 and 4.5.

[Correction Notice: An Erratum for this article was reported in Vol 115(6) of Journal of Personality and Social Psychology (see record 2018-63189-002). In the article, the original supplemental material has been revised to include a clarifying note to the Tests of model fit over larger sample (Samples C-G) section and post-peer review analyses added to the Post-peer review Factor Analytic Tests section. All versions of this article have been corrected.] Philosophers and behavioral scientists refer to wisdom as unbiased reasoning that guides one toward a balance of interests and promotes a good life. However, major instruments developed to test wisdom appear biased, and it is unclear whether they capture balance-related tendencies. We examined whether shifting from global, de-contextualized reports to state-level reports about concrete situations provides a less biased method to assess wise reasoning (e.g., intellectual humility, recognition of uncertainty and change, consideration of the broader context at hand and perspectives of others, integration of these perspectives or compromise), which may be aligned with the notion of balancing interests. Results of a large-scale psychometric investigation (N = 4,463) revealed that the novel Situated WIse Reasoning Scale (SWIS) is reliable and appears independent of psychological biases (attribution bias, bias blind spot, self-deception, and impression management), whereas global wisdom reports are subject to such biases. Moreover, SWIS scores were positively related to indices of living well (e.g., adaptive emotion regulation, mindfulness), and balancing of cooperative and self-protective interests, goals (influence-vs.-adjustment), and causal inferences about conflict (attribution to the self-vs.-other party). In contrast, global wisdom reports were unrelated or negatively related to balance-related measures. Notably, people showed modest within-person consistency in wise reasoning across situations or over time, suggesting that a single-shot measurement may be insufficient for whole understanding of trait-level wisdom. We discuss theoretical and practical implications for research on wisdom, judgment and decision making, well-being, and prosociality. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

We discuss two relatively understudied yet important phenomena relevant to the ecologically crucial task of gathering reliable information from human faces. First, facial width-to-height ratio (fWHR) predicts aggressiveness judgments and is associated with aggression-related behavior and life history outcomes. A significant body of research indicates fWHR is an honest evolutionary signal of propensity to aggression yet little is known about how or if this signal is preserved in judgments across race boundaries. Evidence for a universal relationship between increased fWHR and enhanced aggression perception has been found using Asian and white face stimuli, but race moderated the relationship between high fWHR and ratings in a pain ascription task using black and white faces. Second, we examine research on olfactory cues to face perception and focus particular attention on the possibility that face judgments may be influenced by putrescine, an organic compound found recently to heighten threat and escape-related cognitions in a single subliminal odor presentation study. Here we probe how fWHR and face race interact in aggression judgments during subliminal exposure to putrescine and a control condition. We present a standardized method of subliminal putrescine delivery and find null effects of putrescine on face judgments. Overall, our primarily white participants show a reduced difference in aggressiveness ratings to black faces from low to high levels of fWHR compared to the same contrast in white face stimuli, consistent with an account in which black faces are not perceived with the same configural precision as white faces.

The present study examined the effect of stimulus valence on two levels of selection in the cognitive system, selection of a task-set and selection of a response. In the first experiment, participants performed a spatial compatibility task (pressing left and right key according to the locations of stimuli) in which stimulus-response mappings were determined by stimulus valence. There was a standard spatial stimulus-response compatibility (SRC) effect for positive stimuli (flowers) and a reversed SRC effect for negative stimuli (spiders), but the same data could be interpreted as showing faster responses when positive and negative stimuli were assigned to compatible and incompatible mappings, respectively, than when the assignment was opposite. Experiment 2 disentangled these interpretations, showing that valence did not influence a spatial SRC effect (Simon effect) when task-set retrieval was unnecessary. Experiments 3 and 4 replaced keypress responses with joystick deflections that afforded approach/avoidance action coding. Stimulus valence modulated the Simon effect (but did not reverse it) when the valence was task-relevant (Experiment 3) as well as when it was task-irrelevant (Experiment 4). Therefore, stimulus valence influences task-set selection and response selection, but the influence on the latter is limited to conditions where responses afford approach/avoidance action coding.

This study intended to investigate the effects of varying factors on the use of verbal and implicit classification systems when learning novel categories in an interactive video game environment by measuring the effects of feature type (easy vs difficult to describe verbally). Verbal and implicit classification were operationalized by measuring rule-based and family resemblance strategy use respectively. This experiment found that participants presented with stimuli that were easy to describe verbally were more likely to use rule- based classification, while participants presented with stimuli that were difficult to describe verbally showed no preference for one form of classification. The results of this study open up a novel field of research within category learning, further exploring the effects of feature verbalizablity.

This study used a Web-based naturalistic story-reading paradigm to investigate the impact of number of exposures on incidental acquisition and long-term retention of new meanings for known words by native English-speaking adults. Participants read one of four custom written stories in which they encountered novel meanings (e.g., a safe concealed within a piece of furniture) for familiar words (foam). These meanings appeared two, four, six, or eight times in the narrative. Results showed reasonably good memory of the new meanings, assessed by cued recall of novel meanings and word forms, after only two exposures, emphasizing the importance of initial encounters. Accuracy in cued recall of novel meanings showed a linear, incremental increase with more exposures. There was no significant forgetting after 1 week, regardless of the number of exposures during training, demonstrating the efficiency with which adults acquire new word meanings incidentally through reading and retain them over time. Open Practices: This article has been awarded an Open Data badge. All data and analysis scripts are publicly accessible via the Open Science Framework at https://osf.io/ybu6r. Learn more about the Open Practices badges from the Center for Open Science: https://osf.io/tvyxz/wiki.

Humans can see through the complexity of scenes, faces, and objects by quickly extracting their redundant low-spatial and low-dimensional global properties, or their style. It remains unclear, however, whether semantic coding is necessary, or whether visual stylistic information is sufficient, for people to recognize and discriminate complex images and categories. In two experiments, we systematically reduce the resolution of hundreds of unique paintings, birds, and faces, and test people's ability to discriminate and recognize them. We show that the stylistic information retained at extremely low image resolutions is sufficient for visual recognition of images and visual discrimination of categories. Averaging over the 3 domains, people were able to reliably recognize images reduced down to a single pixel, with large differences from chance discriminability across 8 different image resolutions. People were also able to discriminate categories substantially above chance with an image resolution as low as 2 × 2 pixels. We situate our findings in the context of contemporary computational accounts of visual recognition and contend that explicit encoding of the local features in the image, or knowledge of the semantic category, is not necessary for recognizing and distinguishing complex visual stimuli. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

An emerging area of research in cognitive science is the utilization of networks to model the structure and processes of the mental lexicon in healthy and clinical populations, like aphasia. Previous research has focused on only one type of word similarity at a time (e.g., semantic relationships), even though words are multi-faceted. Here, we investigate lexical retrieval in a picture naming task from people with Broca’s and Wernicke’s aphasia and healthy controls by utilizing a multiplex network structure that accounts for the interplay between multiple semantic and phonological relationships among words in the mental lexicon. Extending upon previous work, we focused on the global network measure of closeness centrality which is known to capture spreading activation, an important process supporting lexical retrieval. We conducted a series of logistic regression models predicting the probability of correct picture naming. We tested whether multiplex closeness centrality was a better predictor of picture naming performance than single-layer closeness centralities, other network measures assessing local and meso-scale structure, psycholinguistic variables and group differences. We also examined production gaps, or the difference between the likelihood of producing a word with the lowest and highest closeness centralities. Our results indicated that multiplex closeness centrality was a significant predictor of picture naming performance, where words with high closeness centrality were more likely to be produced than words with low closeness centrality. Additionally, multiplex closeness centrality outperformed single-layer closeness centralities and other multiplex network measures, and remained a significant predictor after controlling for psycholinguistic variables and group differences. Furthermore, we found that the facilitative effect of closeness centrality was similar for both types of aphasia. Our results underline the importance of integrating multiple measures of word similarities in cognitive language networks for better understanding lexical retrieval in aphasia, with an eye towards future clinical applications.

Humanlike but not perfectly human agents frequently evoke feelings of eeriness, a phenomenon termed the Uncanny Valley (UV). The Categorical Perception Hypothesis proposes that effects associated with the UV are due to uncertainty as to whether to categorize agents falling into the valley as “human” or “nonhuman”. However, since UV studies have traditionally looked at agents of varying human-likeness, it remains unclear whether UV-related effects are due to categorical uncertainty in general or are specifically evoked by categorizations that require decisions regarding an agent’s human-likeness. Here, we used mouse tracking to determine whether agent spectra with (i.e., robot-human) and without (i.e., robot-animal and robot-stuffed animal) a human endpoint cause phenomena related to categorical perception to comparable extents. Specifically, we compared human and nonhuman agent spectra with respect to existence and location of a category boundary (H1-1 and H2-1), as well as the magnitude of cognitive conflict around the boundary (H1-2 and H2-2). The results show that human and nonhuman spectra exhibit category boundaries (H1-1) at which cognitive conflict is higher than for less ambiguous parts of the spectra (H1-2). However, in human agent spectra cognitive conflict maxima were more pronounced than for nonhuman agent spectra (H2-1) and category boundaries were shifted towards the human endpoint of the spectrum (H2-2). Overall, these results suggest a quantitatively, though not qualitatively, different categorization process for spectra containing human endpoints. Possible reasons and the impact for virtual and robotic agent design are discussed.

Previous studies found that an automatic meaning-composition process affects the processing of morphologically complex words, and related this operation to conceptual combination. However, research on embodied cognition demonstrates that concepts are more than just lexical meanings, rather being also grounded in perceptual experience. Therefore, perception-based information should also be involved in mental operations on concepts, such as conceptual combination. Consequently, we should expect to find perceptual effects in the processing of morphologically complex words. In order to investigate this hypothesis, we present the first fully-implemented and data-driven model of perception-based (more specifically, vision-based) conceptual combination, and use the predictions of such a model to investigate processing times for compound words in four large-scale behavioral experiments employing three paradigms (naming, lexical decision, and timed sensibility judgments). We observe facilitatory effects of vision-based compositionality in all three paradigms, over and above a strong language-based (lexical and semantic) baseline, thus demonstrating for the first time perceptually grounded effects at the sub-lexical level. This suggests that perceptually-grounded information is not only utilized according to specific task demands but rather automatically activated when available.

Does language reflect the categories of our mind or does it help create them? On one widespread view (cognitive priority), learning a language involves mapping words onto pre-existing categories, leaving little room for language to change the structure of conceptual content. On another view (linguistic priority), conceptual structure is shaped by experience with and use of language. We argue for the latter perspective and present experimental findings showing that nameability – the ease with which a feature can be named – influences problem-solving, category learning, and geometric reasoning. Even subtle manipulations affecting the availability of verbal labels can impact the categories people discover and use. Words do not simply reflect joints of nature, but are used to flexibly carve joints into nature.

People often have difficulty understanding processes of biological change, and they typically reject drastic life cycle changes such as metamorphosis, except for animals with which they are familiar. Even after a lesson about metamorphosis, people often do not generalize to animals not seen during the lesson. This might be partially due to the perceptual richness of the diagrams typically used during lessons on metamorphosis, which serves to emphasize the individual animal rather than a class of animals. In two studies, we examined whether the perceptual richness of a diagram influences adults’ learning and transfer of knowledge about metamorphosis. One study was conducted in a laboratory setting and the other online. In both studies, adults who saw the bland diagram during the lesson accurately transferred more than adults who saw the rich diagram during the lesson.

Polymorphous concepts are hard to learn, and this is perhaps surprising because they, like many natural concepts, have an overall similarity structure. However, the dimensional summation hypothesis (Milton and Wills Journal of Experimental Psychology: Learning, Memory and Cognition, 30, 407–415 2004) predicts this difficulty. It also makes a number of other predictions about polymorphous concept formation, which are tested here. In Experiment 4, we confirm the theory’s prediction that polymorphous concept formation should be facilitated by deterministic pretraining on the constituent features of the stimulus. This facilitation is relative to an equivalent amount of training on the polymorphous concept itself. In further experiments, we compare the predictions of the dimensional summation hypothesis with a more general strategic account (Experiment 2), a seriality of training account (Experiment 3), a stimulus decomposition account (also Experiment 3), and an error-based account (Experiment 4). The dimensional summation hypothesis provides the best account of these data. In Experiment 5, a further prediction is confirmed—the single feature pretraining effect is eliminated by a concurrent counting task. The current experiments suggest the hypothesis that natural concepts might be acquired by the deliberate serial summation of evidence. This idea has testable implications for classroom learning.

Following the influential thought experiments by Hilary Putnam and others, philosophers of language have for the most part adopted semantic externalism concerning natural kind terms. In this paper, we present results from three experiments on the reference of natural kind terms. Our results confirm some standard externalist assumptions, but are in conflict with others: ordinary speakers take both appearance and underlying nature to be central in their categorization judgments. Moreover, our results indicate that speakers’ categorization judgments are gradual, and proportional to the degree of similarity between new samples and familiar, “standard” samples. These findings pose problems for traditional theories, both externalist and internalist.

In the present study, we provide a comprehensive analysis and a multi-dimensional dataset of semantic transparency measures for 1,810 German compound words. Compound words are considered semantically transparent when the contribution of the constituents’ meaning to the compound meaning is clear (as in airport), but the degree of semantic transparency varies between compounds (compare strawberry or sandman). Our dataset includes both compositional and relatedness-based semantic transparency measures, also differentiated by constituents. The measures are obtained from a computational and fully implemented semantic model based on distributional semantics. We validate the measures using data from four behavioral experiments: Explicit transparency ratings, two different lexical decision tasks using different nonwords, and an eye-tracking study. We demonstrate that different semantic effects emerge in different behavioral tasks, which can only be capturedusing a multi-dimensional approach to semantic transparency. We further provide the semantic transparency measures derived from the model for a dataset of 40,475 additional German compounds, as well as for 2,061 novel German compounds.

Objectives Across the life span, deficits in executive functioning (EF) are associated with poor behavioral control and failure to achieve goals. Though EF is often discussed as one broad construct, a prominent model of EF suggests that it is composed of three subdomains: inhibition, set shifting, and updating. These subdomains are seen in both younger (YA) and older adults (OA), with performance deficits across subdomains in OA. Therefore, our goal was to investigate whether subdomains of EF might be differentially affected by age, and how these differences may relate to broader global age differences in EF. Methods To assess these age differences, we conducted a meta-analysis at multiple levels, including task level, subdomain level, and of global EF. Based on previous work, we hypothesized that there would be overall differences in EF in OA. Results Using 1,268 effect sizes from 401 articles, we found overall differences in EF with age. Results suggested that differences in performance are not uniform, such that variability in age effects emerged at the task level, and updating was not as affected by age as other subdomains. Discussion These findings advance our understanding of age differences in EF, and stand to inform early detection of EF decline.

Abstract. Language comprehenders have been arguing to mentally represent the implied orientation of objects. However, compared to the effects of shape, size, and color, the effect of orientation is rather small. We examined a potential explanation for the relatively low magnitude of the orientation effect: Object size moderates the orientation effect. Theoretical considerations led us to predict a smaller orientation effect for small objects than for large objects in a sentence–picture verification task. We furthermore investigated whether this pattern generalizes across languages (Chinese, Dutch, and English) and tasks (picture-naming task). The results of the verification task show an orientation effect overall, which is not moderated by object size (contrary to our hypothesis) and language (consistent with our hypothesis). Meanwhile, the preregistered picture–picture verification task showed the predicted interaction between object size and orientation effect. We conducted exploratory analyses to address additional questions.

Do children learn number words by associating them with perceptual magnitudes? Recent studies argue that approximate numerical magnitudes play a foundational role in the development of integer concepts. Against this, we argue that approximate number representations fail both empirically and in principle to provide the content required of integer concepts. Instead, we suggest that children’s understanding of integer concepts proceeds in two phases. In the first phase, children learn small exact number word meanings by associating words with small sets. In the second phase, children learn the meanings of larger number words by mastering the logic of exact counting algorithms, which implement the successor function and Hume’s principle (that 1-to-1 correspondence guarantees exact equality). In neither phase do approximate number representations play a foundational role.

Agents that can make better use of computation, experience, time, and memory can solve a greater range of problems more effectively. A crucial ingredient for managing such finite resources is intelligently chosen abstract representations. But, how do abstractions facilitate problem solving under limited resources? What makes an abstraction useful? To answer such questions, we review several trends in recent reinforcement-learning research that provide insight into how abstractions interact with learning and decision making. During learning, abstraction can guide exploration and generalization as well as facilitate efficient tradeoffs---e.g., time spent learning versus the quality of a solution. During computation, good abstractions provide simplified models for computation while also preserving relevant information about decision-theoretic quantities. These features of abstraction are not only key for scaling up artificial problem solving, but can also shed light on what pressures shape the use of abstract representations in humans and other organisms.

Forensic science techniques are often used in criminal trials to infer the identity of theperpetrator of crime and jurors often find this evidence very persuasive. Unfortunately, two of the leading causes of wrongful convictions are forensic science testing errors and false or misleading forensic testimony (Saks & Koehler, 2005). Therefore, it is important to understand jurors pre- existing beliefs about forensic science, as these beliefs may impact how they evaluate forensic evidence in the courtroom. In this study, we examine people’s perceptions of the likelihood of error and human judgment involved at each stage of the forensic science process (i.e., collection, storage, testing, analysis, reporting, and presenting). In addition, we examine peoples’ perceptions of the accuracy of — and human judgment involved in — 16 different forensic techniques. We find that, in contrast to what would be expected by the CSI effect literature, participants believed that the process of forensic science involved considerable human judgment and was relatively error-prone. In addition, participants had wide-ranging beliefs about the accuracy of various forensic techniques, ranging from 65.18% (document analysis) up to 89.95% (DNA). For some forensic techniques, estimates were lower than that found in experimental proficiency studies, suggesting that our participants are more skeptical of certain forensic evidence than they need to be. Keywords: Forensic science, forensic evidence, accuracy, error rate, CSI effect.

Evaluative conditioning (EC) is an assimilative change in liking of neutral conditioned stimuli (CS) following pairings with positive or negative stimuli (unconditioned stimulus, US). Dual-process theories postulate that, in addition to a controlled propositional process underlying conscious learning of CS-US contingencies, a second automatic and associative learning process exists that underlies EC effects. A central argument for dual-process theories is the dissociation between US expectancy and CS evaluation in extinction learning: When CSs are presented alone subsequent to CS-US pairings, participants cease to expect USs but continue to exhibit EC effects. This dissociation is typically interpreted as demonstration that EC is resistant to extinction, and consequently, that EC is driven by a distinct learning process. We tested an alternative single-process account, namely that expectancy-liking dissociations are caused by different judgment strategies afforded by the dependent measures rather than due to separable learning processes. According to this view, CS evaluations are by default integrative judgments---summaries of large portions of the learning history---whereas US expectancy reflects momentary judgments focusing on recent events. In a counterconditioning and two extinction experiments, we eliminate the expectancy-liking dissociations reported in the literature by inducing nondefault momentary evaluative judgments, and demonstrate a reversed dissociation when we additionally induced integrative expectancy judgments. Our findings corroborated a-priori predictions based on MINERVA 2, a formal single-process memory model. Hence, dissociations between US expectancy and conditioned CS liking reflect judgment properties and can be accounted for parsimoniously by a single learning process.

A recent surge of interest in the empirical measurement of mind-wandering has led to an increase in the use of thought-probing to measure attentional states, which has led to large variation in methodologies across studies (Weinstein in Behavior Research Methods, 50, 642-661, 2018). Three sources of variation in methodology include the frequency of thought probes during a task, the number of response options provided for each probe, and the way in which various attentional states are framed during the task instructions. Method variation can potentially affect behavioral performance on the tasks in which thought probes are embedded, the experience of various attentional states within those tasks, and/or response biases to the thought probes. Therefore, such variation can be problematic, both pragmatically and theoretically. Across three experiments, we examined how manipulating probe frequency, response options, and framing affected behavioral performance and responses to thought probes. Probe frequency and framing did not affect behavioral performance or probe responses. But, in light of the present results, we argue that thought probes need at least three responses, corresponding to on-task, off-task, and task-related interference. When researchers are specifically investigating mind-wandering, the probe responses should also distinguish between mind-wandering, external distraction, and mind-blanking.

Event-related potentials (ERPs) provide a window into how the brain is processing language. Here, we propose a theory that argues that ERPs such as the N400 and P600 arise as side effects of an error-based learning mechanism that explains linguistic adaptation and language learning. We instantiated this theory in a connectionist model that can simulate data from three studies on the N400 (amplitude modulation by expectancy, contextual constraint, and sentence position), five studies on the P600 (agreement, tense, word category, subcategorization and garden-path sentences), and a study on the semantic P600 in role reversal anomalies. Since ERPs are learning signals, this account explains adaptation of ERP amplitude to within-experiment frequency manipulations and the way ERP effects are shaped by word predictability in earlier sentences. Moreover, it predicts that ERPs can change over language development. The model provides an account of the sensitivity of ERPs to expectation mismatch, the relative timing of the N400 and P600, the semantic nature of the N400, the syntactic nature of the P600, and the fact that ERPs can change with experience. This approach suggests that comprehension ERPs are related to sentence production and language acquisition mechanisms.

Cognitive control is applied in situations that require overriding a habitual and automatic response. The conflict monitoring hypothesis and the Expected Value of Control (EVC) theory as its extension posit a control system responsible for detecting conflicting occasions and adapting to them dynamically within a task. Here we evaluate this prediction in two versions of one of the most popular tasks in cognitive control, namely the Stroop task. We hypothesized that nearby-items interference combines with task interference in the multi-item version effectively turning it into a multi-task that may challenge cognitive control. Adopting an alternative methodology tracking within-task performance, we compared the classical multi-item version of the Stroop task and its single-item counterpart in adults and children. The results revealed a within-task performance decline only in the multi-item version of the task, in both incongruent and neutral conditions, modulated by the presumed maturity of the control system. These findings suggest capacity constraints in control implementation and allocation under conditions requiring parallel execution of multiple cognitive tasks. Task complexity and demands seem to modulate effects on performance. We discuss implications for cognitive control as well as substantial concerns regarding the calculation and use of indices of interference based on the commonly used multi-item version of the Stroop task.

In two ERP experiments, we investigated whether readers prioritize animacy over real-world event-knowledge during sentence comprehension. We used the paradigm of Paczynski and Kuperberg (2012), who argued that animacy is prioritized based on the observations that the ‘related anomaly effect’ (reduced N400s for context-related anomalous words compared to unrelated words) does not occur for animacy violations, and that animacy violations but not relatedness violations elicit P600 effects. Participants read passive sentences with plausible agents (e.g., The prescription for the mental disorder was written by the psychiatrist) or implausible agents that varied in animacy and semantic relatedness (schizophrenic/guard/pill/fence). In Experiment 1 (with a plausibility judgment task), plausible sentences elicited smaller N400s relative to all types of implausible sentences. Crucially, animate words elicited smaller N400s than inanimate words, and related words elicited smaller N400s than unrelated words, but Bayesian analysis revealed substantial evidence against an interaction between animacy and relatedness. Moreover, at the P600 time-window, we observed more positive ERPs for animate than inanimate words and for related than unrelated words at anterior regions. In Experiment 2 (without judgment task), we observed an N400 effect with animacy violations, but no other effects. Taken together, the results of our experiments fail to support a prioritized role of animacy information over real-world event-knowledge, but they support an interactive, constraint-based view on incremental semantic processing.

Humans have the unique ability to represent and manipulate symbols. It is widely believed that this ability is rooted in an evolutionarily ancient system used to process nonsymbolic quantities in the human brain. In the current study, we used an fMRI adaptation paradigm to isolate the representations of symbols, quantities, and physical size in forty-five human adults. Results indicate that the neural correlates supporting symbolic number processing are entirely distinct from those supporting nonsymbolic magnitude processing. At the univariate level, symbolic number processing is associated with activation in the left inferior parietal lobule, whereas the processing of nonsymbolic magnitudes (both quantity and physical size), relates to activation in the right intraparietal sulcus. At the multivariate level, normalized patterns of activation for symbolic number processing exhibit a dissimilar pattern of activation compared to nonsymbolic magnitude processing in both the left and right parietal lobes. Additionally, the patterns of activation that associate with quantity and physical size are practically indistinguishable from one another. These findings challenge the longstanding belief that the culturally acquired ability to conceptualize symbolic numbers is rooted in an evolutionarily ancient system for nonsymbolic magnitude processing. Moreover, these data reveal that the system used to process nonsymbolic numbers may actually be a general magnitude processing system used to process numerical and non-numerical magnitudes. These findings highlight the need for the field to shift away from exploring how symbols are grounded in analog nonsymbolic representations, and toward more complex questions related to the neural consequences of learning symbolic numbers.

In uncertain environments we must balance our need to gather information with our desire to reap rewards by exploiting current knowledge. Achieving this balance is further complicated in reactive environments where actions produce long-lasting change to the system. In four experiments, we investigate how people learn to make effective decisions from experience in a dynamic multiarmed bandit task. In contrast to the typical exploitation-dependent diminishing rewards found in previous studies, options were framed as skills that developed greater rewards the more they were chosen. In Experiment 1, we provide a proof of concept, and in Experiments 2-4 we explore the boundaries of participants' sensitivity to reactive dynamics. Our results suggest that most individuals can learn effective strategies for coping with these reactive environments. A two-part comparison of several competing psychological models supports several conclusions: (a) a sizable minority of individuals learned that their environment was reactive, (b) evidence suggests several distinct groups of individuals employed unique decision strategies, and (c) testing models with the simulation method reveals qualitative misfits that motivate future theory development. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Sensorimotor-based theories of cognition predict that even subtle developmental motor differences, such as those found in individuals on the autism spectrum, affect how we represent the meaning of manipulable objects (e.g., faucet). Here, we test 85 participants, who completed the Adult Autism Spectrum Quotient (to measure autism-spectrum characteristics), on a visual world experiment designed to assess conceptual representations of manipulable objects. Participants heard words referring to manually manipulable objects (e.g., faucet) while we recorded their eye movements to arrays of four objects: the named object, a related object typically manipulated similarly (e.g., jar), and two unrelated objects. Consistent with prior work, we observed more looks to the related object than to the unrelated ones (i.e., a manipulation-relatedness effect). This effect has been taken to reflect overlapping conceptual representations of objects sharing manipulation characteristics (e.g., faucet and jar) due to embodied sensorimotor properties being part of their representations. Critically, we observed that as participant-level autism-spectrum characteristics increased, manipulation-relatedness effects became smaller, whereas in control trials that included a shape (instead of manipulation) related object, relatedness effects increased. The results support the hypothesis that differences in object-concept representations on the autism spectrum emerge at least in part via differences in sensorimotor experience.

We explore whether children’s strategies on a causal learning task show a bias observed in adults towards “exploitative” hypothesis revision. Adults and children (ages 4–6) were presented with evidence which initially seemed to conform to a simple, salient rule (e.g. blue blocks activate a machine), but then encountered evidence that violated this rule. The true rule in the "near" condition was more complex, but could be reached through iterative revision of the salient rule, while in the "distant" condition, the true rule was comparatively simple, but incremental revision could not yield the true rule. Participants then predicted the behaviour of a set of new blocks. Adults performed better in the near condition, while in the distant condition adults did not appear to revise their initial hypothesis significantly. Unlike adults, children's overall performance in both conditions was similar, while condition differences may reflect a broader search for alternative solutions.

The current study investigated category learning across two experiments using face-blend stimuli that formed face families controlled for within- and between-category similarity. Experiment 1 was a traditional feedback-based category learning task, with three family names serving as category labels. In Experiment 2, the shared family name was encountered in the context of a face—full name paired-associate learning task, with a unique first name for each face. A subsequent test that required participants to categorize new faces from each family showed successful generalization in both experiments. Furthermore, perceived similarity ratings for pairs of faces were collected before and after learning, prior to generalization test. In Experiment 1, similarity ratings increased for faces within a family and decreased for faces that were physically similar but belonged to different families. In Experiment 2, overall similarity ratings decreased after learning, driven primarily by decreases for physically similar faces from different families. The post-learning category bias in similarity ratings was predictive of subsequent generalization success in both experiments. The results indicate that individuals formed generalizable category knowledge prior to an explicit demand to generalize, and did so both when attention was directed towards category-relevant similarities (Experiment 1) and when attention was directed towards individuating faces within a family (Experiment 2). The results tie together research on category learning and categorical perception and extend them beyond a traditional category learning task. NOTE: This paper has not yet been published in a peer-reviewed journal.

We can understand and express an unlimited variety of meaningful ideas using language. This remarkable ability depends on the fact that as we learn words, they become organized according to meaningful, semantic links, such as those connecting apple, juicy, eat, and pear. Extensive computational evidence attests that everyday language is rich in statistical regularities that could, in principle, drive the formation of these links: (1) Direct co-occurrence (e.g., eat - apple) may foster links between words that can be combined to express meaningful ideas, and (2) Shared patterns of co-occurrence (e.g., apple and pear both co-occur with eat) may foster links between words similar in meaning. Here, we investigated whether humans can harness these simple but powerful statistics to integrate new words into their existing networks of organized word knowledge. In three reported experiments (N=128), participants came to link novel with familiar words based on both direct and shared patterns of co-occurrence following mere exposure to sentences containing these statistics. This novel finding highlights a potentially key role for co-occurrence regularities in building the organized word knowledge that is fundamental to our unique fluency with language.

When learning to partition the world into categories, people rely on a set of assumptions (overhypotheses) about possible category structures. Here we propose that the nature of these overhypotheses depends on the presence of a verbal label associated with a given category. We describe a computational model that demonstrates how labels can either accelerate or hinder category learning, depending on whether or not the prior beliefs imposed by their presence align with the true category structure. This account provides an explanation for the phenomena described in prior experimental work (Lupyan, Rakison, & McClelland, 2007; Brojde, Porter, & Colunga, 2011) that have remained unexplained by other models. Based on these results, we argue that the overhypothesis theory of label effects provides a way to formalize and quantify the effect of language on category learning and to develop a more precise delineation between linguistic and non-linguistic thought.

We examined whether the processing of semantic relations shows typicality effects similar to those found for the processing of entity concepts. Participants performed four relational processing tasks with the same set of word-pair stimuli: relational exemplar generation; similarity ranking; analogical verification; and a paired-associate learning task. In the similarity ranking task, we gathered separate rankings for relational, role and semantic similarity between word pairs. We found significant correlations at the item level among relational generation frequencies, analogical verification RTs/accuracy and relational luring in associative memory. Relational similarity predicted exemplar generation frequencies, analogical verification RTs/accuracy, and relational luring in associative memory. Role similarity predicted exemplar generation frequency, and analogical verification RTs, but not relational luring. Semantic similarity did not predict any of the tasks, after controlling for the other two factors. Contrary to current theories which posit that semantic similarity is more important for retrieving relevant analogues, and that analogical mapping is based on role-filler bindings, relational similarity was the strongest predictor across all tasks. These results suggest that just like entity concepts, semantic relations have an internal structure that gives rise to typicality effects across a variety of tasks, which could provide constraints for testing competing theories of relational representation.

The implied order of a ranked set of visual images can be learned by transitive inference, without reliance on stimulus features that explicitly signal their order. Such learning is difficult to explain by associative mechanisms but can be accounted for by cognitive representations and processes such as transitive inference. Our study seeks to determine if those representations may be applied to categories of images without explicit verbal instruction. Specifically, we asked whether participants can (a) infer that images being presented belonged to familiar categories, even when every image presented during every trial is unique, and (b) perform transitive inferences about the ordering of those categories. To address these questions, we compared the performance of humans during a standard TI task, which used the same set of images throughout the session, to performance in a category TI tasks, which drew images from a set of categories. Each of the images used in the category TI task was only presented once, limiting the extent to which stimulus-outcome associations could be learned. Participants were able to learn the order of the categories based on transitive inference. However, participants in the category TI condition did not produce a symbolic distance effect. These findings collectively suggest that differing cognitive processes may underpin serial learning when learning about specific stimuli versus stimulus categories.

Many decision makers are thought to economize on attention by processing information at the simpler level of a category. We directly test whether such category focus reflects an adaptive response to attention constraints, in five preregistered experiments using an information sampling paradigm with mouse tracking. Consistent with rational principles, participants focus more on category-level information when individual differences are small, when the category contains more members, and when time constraints are more severe, though cognitive load has no effect. Participants are sensitive to the statistical structure of the category even when it must be learned from experience, and they respond to a latent shift in this structure. Beliefs about category members tend to cluster together more when category focus is high—a key element of rational inattention. However, this is counteracted by greater weight placed on salient and idiosyncratic information when the category is large. Our results broadly substantiate influential theories of categorical thinking, giving us a clearer view on the drivers and consequences of inattention.

We explore how linguistic categories extend over time as novel items are assigned to existing categories. As a case study we consider how Chinese numeral classifiers were extended to emerging nouns over the past half century. Numeral classifiers are common in East and Southeast Asian languages, and are prominent in the cognitive linguistics literature as examples of radial categories. Each member of a radial category is linked to a central prototype, and this view of categorization therefore contrasts with exemplar-based accounts that deny the existence of category prototypes. We explore these competing views by evaluating computational models of category growth that draw on existing psychological models of categorization. We find that an exemplar-based approach closely related to the Generalized Context Model provides the best account of our data. Our work suggests that numeral classifiers and other categories previously described as radial categories may be better understood as exemplar-based categories, and thereby strengthens the connection between cognitive linguistics and psychological models of categorization.

Objective: The term "trauma" seems to have expanded from a narrow usage (referring exclusively to extreme events such as rape and warfare) to a broad usage (encompassing almost any event that results in emotional distress). Today, individuals vary widely in the extent to which their personal "trauma concept" is relatively narrow or broad. In this study, we explore whether this variation is important to individuals' actual experience when facing a stressful event. Method: Participants were randomized to a set of "Narrow" or "Broad" belief induction tasks. They then watched a short film clip involving a mutilated corpse and completed self-report response measures. Days following the task, participants reported event-related symptoms. Results: Individuals with broader beliefs about trauma experienced more intense negative emotions and were more likely to report viewing the film clip as a personal trauma. Moreover, those who saw the film clip as a personal trauma reported more event-related distress (e.g., intrusions, nightmares) in the days after they watched it. We found limited support for causality, with the experimental manipulation showing a significant direct effect on personal trauma concepts but only indirect effects on other outcomes. Conclusion: Broader personal trauma concepts were related to increased vulnerability in a trauma film paradigm. While some evidence suggests causality, it remains possible that at least part of the effect is explained by a third variable causing both broad concepts and vulnerability (e.g., high trait anxiety). (PsycInfo Database Record (c) 2021 APA, all rights reserved).

The world contains not only objects and features, but also relations between them. When a piece of fruit is in a bowl, and the bowl is on a table, we appreciate not only the individual objects and their features, but also the relations containment and support, which abstract away from the particular objects involved. How does the mind represent relations themselves, separately from the objects participating in them? Though abstraction of this sort is frequently studied within the domains of language and higher-level reasoning, here we show that abstract relations may also arise in automatic visual processing, by exploring a surprising perceptual “error” that such relations can produce. In four experiments, participants saw a stream of images containing different objects arranged in force- dynamic relations — e.g., a phone contained inside a basket, a marker resting on a garbage can, or a knife sitting inside a cup. Participants’ task was to respond to a single target image (e.g., phone-in- basket) within the stream of distractors. Surprisingly, even though participants completed this task quickly and accurately, they false-alarmed more often to images that matched the target’s relational category than to those that did not — even when such images involved completely different objects. In other words, when participants were searching for a phone in a basket, they were more likely to mistakenly respond to a knife in a cup than to a marker on a garbage can. Follow-up experiments using this “image confusion” paradigm ruled out strategic responding, and also controlled for various image features that may have been confounded with these relations. We suggest that relational properties are automatically extracted by the mind, and in ways that are abstract: We see relations themselves, beyond the identities of the objects participating in them.

How does the order of individuals' interactions affect the emergence of shared conventions at the population level? The answer to this question is relevant for a number of fields, such as cultural evolution, linguistics, cognitive science or behavioral economics. In this study we investigate experimentally how two different network connectivity dynamics affect the evolution of the diversity of cultural variants of the communication system. We report an experiment in the lab in which participants engage in a Pictionary-like graphical communication task as members of a 4-participant micro-society, interacting in pairs with the other three members of the community across 4 rounds. The experiment has two main goals: First, to evaluate the effect of two network connectivity dynamics (early and late) on the evolution of the convergence of micro-societies on shared communicative conventions under controlled conditions. Second, to compare the predictions of the agent-based model described in a previous study (Segovia-Martín, Walker, Fay, & Tamariz, 2019) against experimental data, and calibrate the model to find the best-fitting parameter setting. Our experimental data shows that, as predicted by the model, an early connectivity dynamic increases convergence and a late connectivity dynamic slows down convergence. We found significant differences between conditions in round 3 and round 4. We estimate the best-fit parameter combination for the 96 data structures coded. Medium to high content bias, neutral to egocentric coordination bias and memory size of 3 rounds was associated with a better model fit. In the light of the model evaluation and the experiment outcome, we discuss the impact of our predictions on social influence research and possible factors that might help to improve model precision.

Speakers of many languages prefer allocentric frames of reference (FoR) when talking about small-scale space, using words like ‘east’ or ‘downhill.’ Ethnographic work has suggested that this preference is also reflected in how such speakers gesture. Here, we investigate this possibility with a field experiment in Juchitán, Mexico. In Juchitán, a preferentially allocentric language (Isthmus Zapotec) co-exists with a preferentially egocentric one (Spanish). Using a novel task, we elicited spontaneous co-speech gestures about small-scale motion events (e.g., toppling blocks) in Zapotec-dominant speakers and in balanced Zapotec-Spanish bilinguals. Consistent with prior claims, speakers’ spontaneous gestures reliably reflected either an egocentric or allocentric FoR. The use of the egocentric FoR was predicted—not by speakers’ dominant language or the language they used in the task—but by mastery of words for ‘right’ and ‘left,’ as well as by properties of the event they were describing. Additionally, use of the egocentric FoR in gesture predicted its use in a separate non-linguistic memory task, suggesting a cohesive cognitive style. Our results show that the use of spatial FoRs in gesture is pervasive, systematic, and shaped by several factors. Spatial gestures, like other forms of spatial conceptualization, are thus best understood within broader ecologies of communication and cognition.

From an early age, humans intuitively expect physical objects to obey core principles, including continuity (objects follow spatiotemporally continuous paths) and solidity (two solid objects cannot occupy the same space at the same time). These 2 principles are sometimes viewed as deriving from a single overarching "persistence" principle. Indeed, violations of solidity where one solid object seemingly passes through another could theoretically be interpreted as a violation of continuity, with an object "teleporting" to switch places rather than passing through a solid obstacle. However, it is an empirical issue whether the two principles are processed distinctly or identically to one another. Here, adult participants tracked objects during dynamic events in a novel location detection task, which sometimes involved violations of the principles of continuity or solidity. Although participants explicitly noticed both types of violations and reported being equally surprised at both, they made more errors and answered more slowly after continuity violations than after solidity violations. Our results demonstrate that the two principles show different signature patterns and are thus represented distinctly in the mind. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

The present study tested whether the degree of phonological difference between the labels of categories influence category learning and generalization. For this purpose, two experiments were conducted. In the first experiment, participants learned two categories labelled with pseudo-words that were controlled for the degree of difference between the phonetic features of their labels, such that they each pair was maximally different, minimally different, or somewhere in between. These labelled conditions were compared against a no-label control condition. Results showed that participants learned faster and generalized better for categories when category labels differed more.In the second experiment we tested whether these effects could be attributed to the sound symbolic congruence of the labels to the category members. Results showed that phonological differences influence learning independently from the sound symbolic match. Further we specify a category learning model based on generalized perceptual discriminability of the to-be categorized information, including perceptual features of both items and their labels: Categories are easier to learn when their features (including labels) are easier to discriminate.