This introduction to the special issue entitled "Network Science in Experimental Psychology" describes how complex networks are used by experimental psychologists to examine questions from a range of topics in psychology. Complex networks use nodes to represent individual entities and connections between nodes that are related in some way. The overall weblike structure that emerges influences the processes that operate in that system. The articles summarized here illustrate the various definitions of nodes (e.g., people, words, parts of the brain) and connections between nodes (e.g., friendships, semantic similarity, coactivation of brain regions) and also illustrate a wide range of metrics that reveal information that could not be found using contemporary and conventional approaches. The guest editors and authors hope that these examples encourage other researchers to apply the computational techniques from network science to their questions of interest to make new and interesting discoveries. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Recent research on multilingualism highlights the role of language diversity in modulating the cognitive capacities of communication and suggests a gap in available measures for quantifying socially realistic language experience. One questionnaire-based measure that potentially fills this gap is Language Entropy (e.g., Gullifer & Titone, 2018, 2020), which quantifies the balance between compartmentalised and integrated language use. However, an open question is whether questionnaire-based Language Entropy is a valid reflection of socially realistic language behaviours. To address this question, we grounded questionnaire-based Language Entropy using personal social network data for a linguistically diverse sample of speakers of French and English in the city of Montréal ( = 95). Specifically, we used exploratory factor analysis to characterise the factor structures resulting from questionnaire-based and social network-based Entropy. In addition, we examined the generalisability and stability of the relationship between both entropies across three bilingual groups with different social network compositions: simultaneous, English-dominant, and French-dominant. Our findings indicated that both questionnaire-based and social network-based entropies loaded onto the same factors and that the relationship between them was not affected by group differences in social network composition or by context. This suggests that questionnaire-based Language Entropy aligns well with social network-based Entropy and that this relationship is stable across different sociolinguistic realities, validating Language Entropy as a useful tool for quantifying language diversity. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Using network representations of the lexicon has expanded our understanding of vocabulary growth processes and vocabulary structure during early development. These models of vocabulary development have used multiple types of sources to create lexical representations. More recently, Weber and Colunga (2022) demonstrated that predictions of early vocabulary norms can be improved by using network representations based on a corpus incorporating language a young child might typically hear. The present work goes a step further by evaluating the accuracy of network representations for predicting individual children's word learning that are based on embeddings that are readily available or embeddings gathered from the same child language corpus. We predicted the specific words that individual children add to their vocabulary over time, using a longitudinal data set of 86 monolingual English-speaking toddler's changing vocabulary from 18 to 30 months of age. The toddler-based network predicted word learning more accurately than the off-the-shelf network. Further, there was an advantage for prediction methods that took into account the individual child's particular network structure rather than overall network connectivity. These results highlight the importance of tailoring representational and processing choices to the population of interest. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

While in society mathematics is often thought of as formal and rigid, mathematicians themselves frequently consider the discipline creative and visual. To challenge stereotypes, we focus on visuo-spatial thinking by research mathematicians ( = 232). Via the Object-Spatial Imagery and Verbal Questionnaire (Blazhenkova & Kozhevnikov, 2009), together with open questions, we ask the following: (1) Are mathematicians visuo-spatial thinkers? (2) Is the degree of visual thinking correlated with mathematical subdiscipline? (3) Which role does visual thinking play in mathematical research? The Object-Spatial Imagery and Verbal Questionnaire results indicate that mathematicians are more strongly visuo-spatial thinkers than scientists, humanities researchers or visual artists. The degree of visuo-spatial thinking does not correlate to how 'visual' the mathematical subdiscipline is as measured by average figure environment per article, obtained through text mining 3,799 arXiv articles. In open questions, two thirds of respondents ( = 222) report using visual mental imagery during mathematical research. Some mathematicians mention metaphors for research that refer to spatial movement, such as rock climbing, moving through a jungle or attacking the problem like an insect. Our study contributes to the research agenda set by Alcock et al. (2016), which aims to improve our understanding of mathematical cognition for the purpose of elucidating the nature of mathematical thinking and inform policymakers to address challenges in mathematics education. We conclude that visualisation plays an important part in the practice of mathematics, contrary to common belief. As Hadamard wrote in 1945: 'deductions in the realm of numbers may be, at least in several mathematical minds, most generally accompanied by images'. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

We search for objects every day using touch alone, as in reaching for keys in our pockets or reaching for pens in our desk drawers. In such contexts, we engage in a "free-range" haptic search. The objects we feel can be moved freely and our hands can move freely. Free-range haptic search has been little studied, so we developed a laboratory task to do so. We invited college student to feel for a plastic pipe of fixed length among a variable number of uniformly shorter or longer plastic pipes, giving half of our participants informative precues (pictures showing the number of distractors and size difference between the target and distractors) and the other half uninformative precues (a simple "go-ahead" message). The informative precues boosted efficiency only when the target was much larger than the distractors. The result suggests that participants could take advantage of the informative precues to opt for a quick sweep of the search area to pick out the object that would "stick out like a sore thumb." Otherwise, they would resort to that strategy with a lower probability. Because our task has high ecological validity, we can recommend that informative advance information may help haptically impaired individuals search more efficiently. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Collective memory broadly refers to the memories shared by a group of people. Interest in collective memory among cognitive psychologists has boomed in recent years, with many studies leveraging fluency tasks to probe what events and people come to mind given a prompt. As other research using fluency tasks has benefitted greatly from network analysis (e.g., semantic memory research), it seems there is an opportunity to deepen our understanding of collective cognition and changes in collective cognition by adopting a network perspective. In the current article, we ask whether collective memory investigations could be enriched by harnessing the tools of network science. We start by reviewing the relevant collective memory literature and touch on the deep semantic memory literature to the extent it provides ties to network analysis for present goals. Our novel contributions to the topic include the introduction of a large fluency data set collected over the course of a decade as part of a task embedded within several research projects. We conduct several descriptive analyses and initial, proof-of-concept network analyses examining collective memory for U.S. cities. Some cities-those that are recalled most frequently-are recalled at similar rates and in similar output positions across time and task contexts. Our network approach suggests that recall transitions (e.g., recalling and in adjacent positions) are made at similar rates as well. Together, these complementary approaches suggest a striking stability in both what people recall and their ordering, providing a window into the composition of collective memories. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Phonological word form networks of the mental lexicon are of psycholinguistic relevance, offering insights into the efficiency of lexical access. While much research has concentrated on first languages, there is growing evidence suggesting that phonological networks of second languages are equally significant for lexical processes. Bilingual language processing is proposed to involve the integration of first and second languages, with lexical activation spreading between similar word forms in both languages. Multiplex networks provide a framework to combine different phonological networks, allowing for the analysis of the integrated lexical system's behaviour during lexical processing. In the context of the present study, which focusses on German learners of English as a second language, a multiplex network analysis was constructed to model the interactive complexity of the bilingual mental lexicon. The study tested cross-linguistic effects in a word recognition task using English stimuli. Results revealed that during lexical processing in their second language English, German speakers also activate phonological neighbours from German. In addition, the bilinguals are attuned to the interconnectedness (i.e., clustering) of the German and English neighbours with one another in the phonological neighbourhood of the English target words. These findings can contribute to the ongoing debate on the degree of integration in the bilingual mental lexicon and shed light on the role that phonological networks can play in modelling bilingual lexical processing. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

The goal of this article was to determine if second language (L2) speakers benefit from living in mixed-language environments and whether said benefit applies across proficiency levels. To this end, we reanalyzed a subset of data from Gilbert et al. (2019) considering language entropy scores as a proxy for linguistic environment predictability. The task involved producing sentences designed around oronyms in French and English. Participants produced sentences in both languages, allowing the comparison of first language and L2 productions. Their results demonstrated the production of L2-appropriate prosodic cues, albeit after having reached a high level of L2 proficiency. Adding language entropy scores to the original statistical models revealed significant interactions suggesting that participants benefited from living in a mixed-languages environment whereby even low-proficiency speakers produced L2-appropriate prosodic cues. However, low-proficiency L2 speakers living in predictable linguistic environments failed to adapt their prosodic production to their L2, as previously observed. These results suggest that, irrespective of proficiency, the language environment has a significant impact on nonnative language production. This has implications for language development and models of language acquisition. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

The difficulty of a word problem is influenced by both linguistic and arithmetic processes. However, whether these processes are sequential or interactive is a matter of debate. Little is known about how eye-movement behaviour changes when faced with different linguistic and arithmetic task characteristics, both in relation to the entire problem and to specific components (i.e., numerical and textual elements). To address this gap, we conducted a study monitoring the eye movements of children aged 10-13 years during word problem solving. We manipulated linguistic and arithmetic task characteristics independently, focusing on the mathematical factor operation (addition/subtraction) and the linguistic factors consistency (consistent/inconsistent) and nominalization (verbalized/nominalized). The results revealed that eye movements generally increased as linguistic difficulty (e.g., nominalization) or arithmetic difficulty (e.g., operation) increased. Thereby, specific parts of the text were differentially affected based on the task characteristics. Increasing arithmetic difficulty led to a shift in eye movements towards numerical elements, while increasing linguistic difficulty resulted in a shift towards textual elements. Interestingly, the increase in arithmetic difficulty also influenced processing in the linguistic domain. For example, textual parts of the word problem received more fixations when the arithmetic difficulty increased, but not vice versa. This suggests that text comprehension and calculation processes in word problem solving are not separate and not strictly sequential; instead, they interact and/or do partially rely on shared cognitive resources. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Verbs and nouns vary in many ways-including in how they are used in language and in the timing of their early learning. We compare the distribution of semantic features that comprise early acquired verb and noun meanings and measure their effect on learning. First, couched in prior literature, we use semantic feature data to establish that features pattern on a hierarchy of complexity, with perceptual features being less complex than other features like encyclopaedic features. Second, given overall semantic and syntactic differences between nouns and verbs, we hypothesize that the preference for directly perceptible features observed for nouns will be attenuated for verbs. Building on prior work using semantic features and semantic networks in nouns, we find that compared to early learned nouns ( = 359), early learned verbs ( = 103) have meanings disproportionately built from complex information inaccessible to the senses. Third, we find that 16- to 30-month-old children's early noun and verb vocabularies ( = 3,804) show semantic relationships that differ in their use of this complex information from the beginning of vocabulary development. Last, we find that the complexity of nouns' and verbs' meanings affects their typical order of learning in early vocabulary development. Complexity differs in early noun and verb meanings, affects the semantic structure of children's vocabularies, and shapes the course of word learning. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

The application of techniques from network science to create single-layer networks of the brain and mind has resulted in significant advances in the neuro- (i.e., structural and functional brain networks) and cognitive sciences (i.e., cognitive network science). Recent advances in network science on multilayer networks increase the possibility that a "network of networks" might finally connect the physical brain to the intangible mind, much like physical fibre optic cables and wires connect to other layers of the internet to allow intangible social networks to form in various social media platforms. Several advances in structural brain networks, functional brain networks, cognitive networks, and multilayer networks are briefly reviewed. The possibility that these single-layer networks can be connected in a multilayer network to connect the brain to the mind is discussed, as well as some of the challenges that face such an ambitious endeavour. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

This article provides an analysis of structural changes in second-language (L2)-based semantic memory networks-graphs composed of L2 words as nodes and semantic relations between them as edges, during L2 learning. We used snowball sampling paradigm to create individual semantic networks of participants divided into two groups differing in L2 learning time and then compare their structural characteristics cross-sectionally. The results showed that as L2 learning progresses, semantic memory networks tend to become more connected (by increasing the average node degree), more efficient (by decreasing the average shortest path length), less fragmented (by decreasing the modularity), less centralized (by decreasing the centralization), less dense (by decreasing the density), and no more "small-worlded" (by similar average clustering coefficients and small-world indices). The findings provide quantitative evidence of how the duration of L2 learning shapes the structure of L2-based semantic memory networks generated in the snowball sampling paradigm. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Thousands of phonological word forms known to a speaker can be organised as a lexical network using the tools of network science. In these networks, nodes represent words and edges are placed between phonological neighbours. Previous work has shown that phonological networks of various languages have similar macrolevel network properties. The present study aimed to investigate if phonological networks of different languages also have similar mesolevel properties, specifically, the presence of robust community structure. Prior community detection analyses revealed robust community structure for English. Community detection analyses conducted on French, German, Dutch, and Spanish networks indicate that all networks showed strong evidence of community structure-mesolevel clustering of word forms whereby larger communities tended to contain shorter, frequent words with many phonological neighbours. Words of the same community tended to share similar phonotactic structures. Results suggest that the organisation of phonological word forms in language are governed by similar principles that could have important implications for lexical processing. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Reading and math are related due to many codeveloping skills. Historically, theorizing in these two areas has progressed separately, despite well-documented empirical evidence for a range of shared underlying developmental processes subserving these learning domains. The purpose of this article was to describe the links between the Triple Code Model, an influential model of numerical cognition, and the Triangle Framework, a dominant model of learning to read. We describe several parallels between the theoretical models and discuss how the cognitive mechanisms posited by the Triangle Framework might be used to understand the commonalities in learning processes across these learning domains. In particular, we discuss how the cognitive mechanisms implemented in the Triangle Framework can be used to understand linguistic aspects of numerical cognition, specifically, learning the connections among numerals (e.g., 24) and spoken words (e.g., twenty-four), and linking those to semantic representations of magnitude. Following from these commonalities between the two models, we discuss several ways that interdisciplinary work integrating both models can benefit math cognition research. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

The present study investigated global and local processing of hierarchical digits using a selective attention paradigm. Behavioural and event-related potentials measures were collected while participants performed global and local tasks in which hierarchical digits were presented to the centre of the screen. The first aim of this study was to investigate the global precedence effect. The second aim was to examine the lateralization patterns associated with global and local processing. The behavioural results indicated that the global precedence effect was not evident. In addition, the event-related potential findings showed that the global and local levels were processed in parallel during certain phases of processing, while different lateralization effects were found during processing. Although the N2 findings in the present study support the notion that this component is an index for global versus local processing even for hierarchical digits, the overall findings suggest that complex interactions between the hemispheres exist during the different phases of processing. The results are discussed in terms of the effects of both centrally presented hierarchical digits and the selective attention paradigm. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Mathematical orthography comprises knowledge of mathematical symbols and the conventions for combining those symbols. For example, in the expression x3 + 3x, the positions of the symbol "3" in each term dictate its meanings in the expression. To be successful mathematical problem solvers, people need to know these conventional orthographic patterns. In this study, mathematical orthography skills were assessed in an online format for 189 adults using a timed dichotomous symbol-decision task (e.g., are these expressions conventional? (|| or ||)). The symbol-decision task predicted unique variance in whole-number arithmetic, word problem solving, and algebra, controlling for verbal working memory. These results support the role of individual differences in mathematical orthography as a predictor of advanced mathematical skills. In contrast, a written language orthography task only predicted unique variance in word problem solving, where participants read texts. The role of mathematical orthography should be considered in models of mathematical cognition. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Episodic future thinking is the ability to project the self forward in time to preexperience a potential future event. It has been hypothesized that two components enhance simulations of future events: personal likelihood and event familiarity. Personal likelihood varies depending on the dynamics of personal goals throughout an individual's lifetime. In contrast, event familiarity varies depending on a person's accumulated schematic (also called event or semantic) knowledge about a type of event. We investigated these two components through individuals' belief in the likelihood of an event's occurrence during the next 10 years and their familiarity with a type of event. We predicted that likelihood and familiarity enhance future event simulations, making them clearer and more detailed. We used two norming studies to develop participant-specific sets of future events. In the experiment, participants simulated and described events, and they rated phenomenological aspects of their simulations. Likelihood and familiarity played individual and combined roles during future event simulation. The strongest effects were found with phenomenological ratings, with likelihood and familiarity influencing three of four measures, including interacting for other sensory details ratings. For internal details as measured using the Autobiographical Interview, likelihood influenced total details and perceptual details, and familiarity influenced total, perceptual, and time details, including their interaction for perceptual details. We conclude that event future thinking is a dynamic simulation process that uses event knowledge learned from past experience and is influenced by a person's belief of how likely an event is to occur via mental rehearsal of likely events. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Working memory is associated with general intelligence and is crucial for performing complex cognitive tasks. Neuroimaging investigations have recognized that working memory is supported by a distribution of activity in regions across the entire brain. Identification of these regions has come primarily from general linear model analyses of statistical parametric maps to reveal brain regions whose activation is linearly related to working memory task conditions. This approach can fail to detect nonlinear task differences or differences reflected in distributed patterns of activity. In this study, we take advantage of the increased sensitivity of multivariate pattern analysis in a multiple-constraint deep learning classifier to analyze patterns of whole-brain blood oxygen level dependent (BOLD) activity in children performing two different conditions of the emotional -back task. Regional (supervoxel) whole-brain activation patterns from functional imaging runs of 20 children were used to train a set of neural network classifiers to identify task category (0-back vs. 2-back) and activation co-occurrence probability, which encoded functional connectivity. These simultaneous constraints promote the discovery of coherent networks that contribute towards task performance in each memory load condition. Permutation analyses discovered the global activation patterns and interregional coactivations that distinguish memory load. Examination of model weights identified the brain regions most predictive of memory load and the functional networks integrating these regions. Community detection analyses identified functional networks integrating task-predictive regions and found distinct patterns of network activation for each task type. Comparisons to functional network literature suggest more focused attentional network activation during the 2-back task. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Previous research on attitudes towards mathematics has mostly been assessed in a single language. We examined whether math attitudes differ by language in multilingual younger adults (ages 18-25). Furthermore, we evaluated the relationships between math attitudes, verbal memory, and calculation fluency in this sample. Eighty-seven French-English multilingual young adults self-reported their math attitudes using the Mathematics Anxiety Scale-Revised (Bai et al., 2009) in both English and French. Participants also self-reported verbal memory, calculation fluency, and general language proficiency in English and French. Results showed that attitudes towards mathematics for English and French were similar. Exploratory factor analysis also confirmed that the extracted factors revealed negative and positive attitudes towards mathematics, with English and French items loading on the same factors. Correlation analysis showed a negative relationship between negative attitudes towards mathematics and verbal memory only in English. This relationship remained statistically significant after controlling for general language proficiency. However, neither positive nor negative math attitudes were correlated with calculation fluency. Building on the examination of symbolic representations of mathematical cognition by Campbell, results from the study were interpreted as the first step to investigating math attitudes in individuals with diverse linguistic backgrounds. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

The present study was an investigation of the relation between cognitive coupling, a correlation between text difficulty and reading time, and other measures of mind wandering during reading. To measure cognitive coupling, we manipulated the text difficulty of individual sentences. Because mind wandering may shift attention away from the text, we predicted a cognitive coupling interaction, that is, that the effect of difficulty on processing time should be less when readers are off task. We also manipulated the consistency of a target sentence's content with a prior information. Analogous to the text-based cognitive coupling, we predicted an interaction of consistency with task focus: The impact of this consistency should be less noticeable when readers are off task. The results demonstrated the predicted text-based cognitive-coupling effect: There was less of an effect of text difficulty when readers reported being off task. However, there was no such interaction between consistency and task focus. We conclude that the consistency effect may depend on the relatively automatic activation of prior information rather than requiring consciously retrieving related information from memory. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Continuing ongoing commitment to Open Science, we invited Oshiro et al. (2024) to submit a peer-reviewed tutorial of the typical format and to offer key pieces of advice when preparing Registered Reports. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Faces and body parts play a crucial role in human social communication. Numerous studies emphasize their significance as sociobiological stimuli in daily interactions. Two experiments were conducted to examine the following: (a) whether faces or body parts are processed more quickly than other visual objects when relevant to the task and serving as targets, and (b) the effects of presenting faces or body parts as distractors on task reaction times and error rates. The first experiment focused on either faces or body parts, with five different visual objects. The second experiment examined effector body parts (e.g., hands) and core body parts (e.g., the torso), paired with the same visual objects. Thirty-six participants took part in the study, equally divided between Experiment 1 ( = 18) and Experiment 2 ( = 18). Participants were instructed to find if a target item, indicated by a green placeholder, matched a previously presented word cue, while they were instructed to keep ignoring the singleton object that was surrounded by the red placeholder. The results indicated that participants responded more quickly when finding faces but not body parts in Experiment 1. No such advantage was seen in Experiment 2 for either effector or core body parts compared to other objects. Interestingly, when faces were presented as distractors as a singleton, reaction times increased (Experiment 1), indicating that faces capture attention. This effect was not observed for effector or core body parts (Experiment 2). These findings suggest that faces capture attention more effectively than body parts. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

In young children in particular, processing numerical magnitudes is influenced by spatial characteristics of those magnitudes (e.g., extent). Gradually, children will learn to dissociate numerosity from spatial information and understand that objects represent discrete numerical quantities. In the present study, we investigated whether 5-year-old children extract numerosity disregarding spatial stimulus characteristics and in what way numerosity extraction is associated with verbal number skills (counting and initial addition). Five-year-old children were presented with a newly developed task to measure numerosity extraction on two timepoints, several months apart. Each item contained three rows of differently sized rectangles. Children had to identify which two rows contained the same number of rectangles. On congruent items, these two rows were similar in length. On incongruent items, the two rows equal in numerosity varied in length. Analyses indicated that some 5-year-old children showed numerosity extraction, but others had difficulties to disentangle numerosity from spatial characteristics. Numerosity extraction was predicted over time by initial addition but not counting skills, although there was a concurrent association between counting skills and numerosity extraction at timepoint 2. Numerosity extraction did not predict either initial addition or counting over time. These results suggest that the ability to disentangle numerosity from spatial characteristics is still developing around 5 years of age and that verbal number skills foster this development. Verbal number skills probably further refine nonsymbolic magnitude processing (in this study, numerosity extraction), while nonsymbolic magnitude processing does not underlie verbal number skills. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Arithmetic requires the use of multiple cognitive processes, such as short-term memory (STM). However, findings on the association between STM and simple multiplication solving are mixed, potentially due to large interindividual differences in multiplication proficiency within and between samples. The present study aims to explore further the relationship between visual and verbal STM and simple multiplication solving with a large Malaysian sample ( = 230). Adults (age = 17-42) completed an online production-based multiplication-solving task, STM measures (verbal and visuospatial STM tasks), and a demographic survey. A mixed-model analysis found that verbal STM and visual STM predict multiplication performance, with lower span participants having longer reaction times during multiplication solving. Interestingly, we also observed the relationship between verbal STM and multiplication was moderated by interference, the impact of verbal STM was stronger in high-interference problems, while the visual STM-multiplication relation was moderated by problem size, high visual span participants took more advantage of their visual STM when presented with large size problems. Thus, our findings show that both verbal and visual STM in interaction with problem properties predict simple multiplication solving in adults. Hypotheses on the concrete mechanisms involved in these relationships are discussed. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Experiential theories of cognition propose that the external environment shapes cognitive processing, shifting emphasis from internal mechanisms to the learning of environmental structure. Computational modelling, particularly distributional models of lexical semantics (e.g., Landauer & Dumais, 1997) and models of lexical organization (e.g., Johns, 2021a), exemplifies this, highlights the influence of language experience on cognitive representations. While these models have been successful, comparatively less attention has been paid to the training materials used to train these models. Recent research has explored the role of social/communicatively oriented training materials on models of lexical semantics and organization (Johns, 2021a, 2021b, 2023, 2024), introducing discourse- and user-centred text training materials. However, determining the optimal training materials for these two model types remains an open question. This article addresses this problem by using experiential optimization (Johns, Jones, & Mewhort, 2019), which selects the materials that maximize model performance. This study will use experiential optimization to compare user-based and discourse-based corpora in optimizing models of lexical organization and semantics, offering insight into pathways towards integrating cognitive models in these areas. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Humans have a proclivity for storytelling and narration. Although a lot of attention in the field of episodic memory focuses on the mnemonic content of narratives, memory narratives are not just for conveying the past. Instead, narratives provide a vehicle for meaning-making, social connection, and other complex facets of human cognition and thinking. This short reflection piece discusses the importance of narratives in these diverse realms. In addition, it briefly touches on the role of memory narration in the modern digital era. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

We examined the human ability to encode and utilize local and global uncertainty information during a navigational task. Participants were tasked with navigating a virtual maze in which wall locations were obscured. Local cues and a global direction provided guidance. The validities of the global and local cues were separately and jointly varied across the two experiments. The results demonstrated that participants effectively utilized both global and local cues for navigation with a stronger reliance on local cues and a heightened precision in estimating their reliability. Our findings suggest that the representation of uncertainty for proximate events can be dissociated from that of distal events. Furthermore, humans effectively integrate both forms of information when making decisions during navigation tasks. This research advances our understanding of uncertainty processing and its implications for decision making in complex environments. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

In this article, I describe my academic journey as a Canadian researcher in the field of mathematical cognition. The article is a version of the talk I gave when I was presented with the Donald O. Hebb Award from the Canadian Society for Brain, Behaviour and Cognitive Science in July 2023 at the University of Guelph. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Ordinal number processing skills are important for adults and children. Recent work demonstrates that children have difficulty with judging the ordinality of sequences that are in-order but do not match the typical count-list (i.e., in-order non-adjacent sequences, such as 2-4-6). Limited evidence in the literature suggests that dyscalculic children show a similar pattern of behavior. In the present study, we sought to explicitly test the hypothesis that children with developmental dyscalculia struggle primarily with extending notions of ordinality to sequences outside of the count-list. We test this hypothesis using a sample of children with persistent developmental dyscalculia, and a comparison group of typically performing children. Both groups completed an ordinality judgment task, in which triplet sequences were judged as being in-order (e.g., 3-4-5; 2-4-6) or in mixed-order (e.g., 3-5-4; 2-6-4). In line with our prediction, results demonstrate that children with persistent developmental dyscalculia make more errors, compared to typically performing children, but only on the in-order non-adjacent trials (e.g., 2-4-6). Broadly, this finding suggests that ordinality processing abilities are impaired in children with developmental dyscalculia, and that this characteristic appears primarily in extending notions of ordinality beyond adjacent sequences. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Numeracy is the ability to understand, manipulate, and make sense of numerical information. It is crucial for everyday decision making that involves dealing with numbers. In this study, we tested whether we can help people make better choices in monetary lotteries by communicating numerical values (i.e., payoffs and probabilities) using visual aids. We also checked whether presenting this information in a visual form reduces affect negativity. Participants ( = 210) made choices in 10 monetary lotteries accompanied with visual aids (experimental condition) or without visual aids (control condition). After the lottery task, participants completed questionnaires measuring experienced emotions and numerical skills. Despite finding no hypothesized effect of visual aids on performance in a lottery task, the exploratory analysis revealed the interaction effect. In a visual aid condition, participants who were relatively less educated scored significantly higher in a lottery task in comparison to those in the control condition. Additionally, participants in the visual aid condition reported significantly lower intensity of negative emotions after the lottery task than those in the control condition. We discuss possible causes and mechanisms that can explain the results we obtained. We argue that visual aids are a promising tool for future learning, and their friendly format can positively influence people's reactions to decisions involving numerical information. However, we also point out the necessity for further research and exploration of the role of different designs of visual aids and individual differences. (PsycInfo Database Record (c) 2024 APA, all rights reserved).