Peripheral vision and crowding in mental maze-solving.

Solving a maze effectively relies on both perception and cognition. Studying maze-solving behavior contributes to our knowledge about these important processes. Through psychophysical experiments and modeling simulations, we examine the role of peripheral vision, specifically visual crowding in the periphery, in mental maze-solving. Experiment 1 measured gaze patterns while varying maze complexity, revealing a direct relationship between visual complexity and maze-solving efficiency. Simulations of the maze-solving task using a peripheral vision model confirmed the observed crowding effects while making an intriguing prediction that saccades provide a conservative measure of how far ahead observers can perceive the path. Experiment 2 confirms that observers can judge whether a point lies on the path at considerably greater distances than their average saccade. Taken together, our findings demonstrate that peripheral vision plays a key role in mental maze-solving.

Neural mechanisms distinguishing two types of cooperative problem-solving approaches: An fNIRS hyperscanning study.

Collaborative cooperation (CC) and division of labor cooperation (DLC) are two prevalent forms of cooperative problem-solving approaches in daily life. Despite extensive research on the neural mechanisms underlying cooperative problem-solving approaches, a notable gap exists between the neural processes that support CC and DLC. The present study utilized a functional near-infrared spectroscopy (fNIRS) hyperscanning technique along with a classic cooperative tangram puzzle task to investigate the neural mechanisms engaged by both friends and stranger dyads during CC versus DLC. The key findings of this study were as follows: (1) Dyads exhibited superior behavioral performance in the DLC task than in the CC task. The CC task bolstered intra-brain functional connectivity and inter-brain synchrony (IBS) in regions linked to the mirror neuron system (MNS), spatial perception (SP) and cognitive control. (2) Friend dyads showed stronger IBS in brain regions associated with the MNS than stranger dyads. (3) Perspective-taking predicted not only dyads' behavioral performance in the CC task but also their IBS in brain regions associated with SP during the DLC task. Taken together, these findings elucidate the divergent behavioral performance and neural connection patterns between the two cooperative problem-solving approaches. This study provides novel insights into the various neurocognitive processes underlying flexible coordination strategies in real-world cooperative contexts.

Neural Correlates of Analogical Reasoning on Syntactic Patterns.

Analogical reasoning is central to thought and learning. However, previous neuroscience studies have focused mainly on neural substrates for visuospatial and semantic analogies. There has not yet been research on the neural correlates of analogical reasoning on syntactic patterns generated by the syntactic rules, a key feature of human language faculty. The present investigation took an initial step to address this paucity. Twenty-four participants, whose brain activity was monitored by fMRI, engaged in first-order and second-order relational judgments of syntactic patterns as well as simple and complex working memory tasks. After scanning, participants rated the difficulty of each step during analogical reasoning; these ratings were related to signal intensities in activated regions of interest using Spearman correlation analyses. After prior research, differences in activation levels during second-order and first-order relational judgments were taken as evidence of analogical reasoning. These analyses showed that analogical reasoning on syntactic patterns recruited brain regions consistent with those supporting visuospatial and semantic analogies, including the anterior and posterior parts of the left middle frontal gyrus, anatomically corresponding to the left rostrolateral pFC and the left dorsolateral pFC. The correlation results further revealed that the posterior middle frontal gyrus might be involved in analogical access and mapping with syntactic patterns. Our study is the first to investigate the process of analogical reasoning on syntactic patterns at the neurobiological level and provide evidence of the specific functional roles of related regions during subprocesses of analogical reasoning.

Potential cognitive risks of generative transformer-based AI chatbots on higher order executive functions.

BACKGROUND: Chat generative retrained transformer (ChatGPT) represents a groundbreaking advancement in Artificial Intelligence (AI-chatbot) technology, utilizing transformer algorithms to enhance natural language processing and facilitating their use for addressing specific tasks. These AI chatbots can respond to questions by generating verbal instructions similar to those a person would provide during the problem-solving process. AIM: ChatGPT has become the fastest growing software in terms of user adoption in history, leading to an anticipated widespread use of this technology in the general population. Current literature is predominantly focused on the functional aspects of these technologies, but the field has not yet explored hypotheses on how these AI chatbots could impact the evolutionary aspects of human cognitive development. Thesis: The "neuronal recycling hypothesis" posits that the brain undergoes structural transformation by incorporating new cultural tools into "neural niches," consequently altering individual cognition. In the case of technological tools, it has been established that they reduce the cognitive demand needed to solve tasks through a process called "cognitive offloading." In this theoretical article, three hypotheses were proposed via forward inference about how algorithms such as ChatGPT and similar models may influence the cognitive processes and structures of upcoming generations. CONCLUSIONS: By forecasting the neurocognitive effects of these technologies, educational and political communities can anticipate future scenarios and formulate strategic plans to either mitigate or enhance the cognitive influence that these factors may have on the general population. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Eye movements reveal that young school children shift attention when solving additions and subtractions.

Adults shift their attention to the right or to the left along a spatial continuum when solving additions and subtractions, respectively. Studies suggest that these shifts not only support the exact computation of the results but also anticipatively narrow down the range of plausible answers when processing the operands. However, little is known on when and how these attentional shifts arise in childhood during the acquisition of arithmetic. Here, an eye-tracker with high spatio-temporal resolution was used to measure spontaneous eye movements, used as a proxy for attentional shifts, while children of 2nd (8 y-o; N = 50) and 4th (10 y-o; N = 48) Grade solved simple additions (e.g., 4+3) and subtractions (e.g., 3-2). Gaze patterns revealed horizontal and vertical attentional shifts in both groups. Critically, horizontal eye movements were observed in 4th Graders as soon as the first operand and the operator were presented and thus before the beginning of the exact computation. In 2nd Graders, attentional shifts were only observed after the presentation of the second operand just before the response was made. This demonstrates that spatial attention is recruited when children solve arithmetic problems, even in the early stages of learning mathematics. The time course of these attentional shifts suggests that with practice in arithmetic children start to use spatial attention to anticipatively guide the search for the answer and facilitate the implementation of solving procedures. RESEARCH HIGHLIGHTS: Additions and subtractions are associated to right and left attentional shifts in adults, but it is unknown when these mechanisms arise in childhood. Children of 8-10 years old solved single-digit additions and subtractions while looking at a blank screen. Eye movements showed that children of 8 years old already show spatial biases possibly to represent the response when knowing both operands. Children of 10 years old shift attention before knowing the second operand to anticipatively guide the search for plausible answers.

Time course of EEG power during creative problem-solving with insight or remote thinking.

Problem-solving often requires creativity and is critical in everyday life. However, the neurocognitive mechanisms underlying creative problem-solving remain poorly understood. Two mechanisms have been highlighted: the formation of new connections among problem elements and insight solving, characterized by sudden realization of a solution. In this study, we investigated EEG activity during a modified version of the remote associates test, a classical insight problem task that requires finding a word connecting three unrelated words. This allowed us to explore the brain correlates associated with the semantic remoteness of connections (by varying the remoteness of the solution word across trials) and with insight solving (identified as a Eurêka moment reported by the participants). Semantic remoteness was associated with power increase in the alpha band (8-12 Hz) in a left parieto-temporal cluster, the beta band (13-30 Hz) in a right fronto-temporal cluster in the early phase of the task, and the theta band (3-7 Hz) in a bilateral frontal cluster just prior to participants' responses. Insight solving was associated with power increase preceding participants' responses in the alpha and gamma (31-60 Hz) bands in a left temporal cluster and the theta band in a frontal cluster. Source reconstructions revealed the brain regions associated with these clusters. Overall, our findings shed new light on some of the mechanisms involved in creative problem-solving.

Cognitive processes that underlie mathematically gifted emergent bilinguals.

The purpose of this study was to determine those cognitive measures that increase the likelihood of identifying mathematically gifted students who are emerging bilinguals. Elementary school children (Grades 1, 2, and 3) were administered a battery of math, vocabulary, reading, and cognitive measures (short-term memory, inhibition, and working memory in their first language (L1: Spanish) and second language (L2: English). Multilevel polytomous logistic modeling compared mathematically gifted children with children who were average math achievers or low math achievers. The results indicated that cognitive parameters that included estimation and working memory in the L2 and problem-solving in the L1 were unique predictors that significantly influenced whether a child was categorized as gifted relative to average achievers. Relative to average achievers, L2 parameters (magnitude judgment) and English reading were significantly related to the identification of children with low math computation. The results are discussed in terms of a multidimensional model that taps domain-specific skills and general cognitive processes that increase the ability to correctly identify children who score in the gifted range in both their L1 and L2.

Common operational pictures as collective problem representations: The case of the 2018 wildfires in Sweden.

Common operational pictures (COPs) can be seen as collective problem representations that facilitate effective problem solving during emergency response. This article investigates how problems are represented in COPs and discusses how such problem representations could be improved to better inform ongoing response operations. A content analysis of 41 COPs created by a Swedish county board during the large-scale wildfires that broke out in 2018 shows that most problems are represented in terms of geographic references and the status of fires, what problems to avoid, or risks, and resource type and status. These representations were found to be key for managing the response, as they enabled the scope of the response to be determined and facilitated proactive strategies; actions could be planned; the response organization could be set up. Further investigations could examine if problem representations described in terms of a gap between an undesirable current state and desired goal state would improve the usefulness of COPs, and, ultimately, better inform ongoing response operations.

Neural evidence for procedural automatization during cognitive development: Intraparietal response to changes in very-small addition problem-size increases with age.

Cognitive development is often thought to depend on qualitative changes in problem-solving strategies, with early developing algorithmic procedures (e.g., counting when adding numbers) considered being replaced by retrieval of associations (e.g., between operands and answers of addition problems) in adults. However, algorithmic procedures might also become automatized with practice. In a large cross-sectional fMRI study from age 8 to adulthood (n = 128), we evaluate this hypothesis by measuring neural changes associated with age-related reductions in a behavioral hallmark of mental addition, the problem-size effect (an increase in solving time as problem sum increases). We found that age-related decreases in problem-size effect were paralleled by age-related increases of activity in a region of the intraparietal sulcus that already supported the problem-size effect in 8- to 9-year-olds, at an age the effect is at least partly due to explicit counting. This developmental effect, which was also observed in the basal ganglia and prefrontal cortex, was restricted to problems with operands ≤ 4. These findings are consistent with a model positing that very-small arithmetic problems-and not larger problems-might rely on an automatization of counting procedures rather than a shift towards retrieval, and suggest a neural automatization of procedural knowledge during cognitive development.

Revisiting the narrow latent scope bias in explanatory reasoning.

Humans are capable explainers and lay people tend to share the same explanatory virtues held in high regard by philosophers and scientists. However, a recent line of studies found a striking deviation from normativity in lay people's explanations, termed the "narrow latent scope bias". When competing explanations with identical a priori probabilities fit observed evidence equally well - but differ in the number of unobserved pieces of evidence they predict (latent scope) - reasoners seem to prefer explanations that predict fewer unobserved pieces of evidence (narrow latent scope). This tendency has been described as a robust explanatory reasoning bias. The present paper empirically demonstrates across six experiments (N=2200) that this bias is less robust than has been claimed, and influenced by nuanced pragmatic inferences on the side of participants. Pragmatic factors shown to influence the bias are assumptions about how easily an unobserved piece of evidence should have been observed if it was present ("feature diagnosability"), and the formulation of the test question being asked. Across studies, genuine narrow latent scope biases resulting from fallacious reasoning were found only in a fraction of participants. It is also demonstrated that the magnitude of the bias depends on response options: it is stronger if participants are forced to commit an error, but at best weak if they are allowed to give the correct answer.

Neural activity and network analysis for understanding reasoning using the matrix reasoning task.

Reasoning requires the ability to manipulate mental representations and understand relationships between objects. There is a paucity of research regarding the functional connections between multiple brain areas that may interact during commonly used reasoning tasks. The present study aimed to examine functional activation and connectivity of frontoparietal regions during a Matrix Decision Making Task, completed by twenty-one right-handed healthy participants while undergoing fMRI. Voxel-wise whole brain analysis of neural response to the task revealed activation spanning dorsal and lateral prefrontal, occipital, and parietal regions. Utilizing Group Iterative Multiple Model Estimation, a data-driven approach that estimates the presence and direction of connectivity between specific ROIs, connectivity between prefrontal and sensory processing regions were revealed. Moreover, the magnitude of connectivity strength between the left precentral gyrus and left dorsal cingulate (dACC) was positively correlated with MR behavioral performance. Taken together, results are consistent with earlier work demonstrating involvement of regions comprising the central executive network in relational reasoning. These data expand existing knowledge regarding communication of key brain regions during the task and demonstrate that understanding how key brain regions are interconnected can effectively predict the quality of behavioral output.

Electrophysiological connectivity of logical deduction: Early cortical MEG study.

Complex human reasoning involves minimal abilities to extract conclusions implied in the available information. These abilities are considered "deductive" because they exemplify certain abstract relations among propositions or probabilities called deductive arguments. However, the electrophysiological dynamics which supports such complex cognitive processes has not been addressed yet. In this work we consider typically deductive logico-probabilistically valid inferences and aim to verify or refute their electrophysiological functional connectivity differences from invalid inferences with the same content (same relational variables, same stimuli, same relevant and salient features). We recorded the brain electrophysiological activity of 20 participants (age = 20.35 ± 3.23) by means of an MEG system during two consecutive reasoning tasks: a search task (invalid condition) without any specific deductive rules to follow, and a logically valid deductive task (valid condition) with explicit deductive rules as instructions. We calculated the functional connectivity (FC) for each condition and conducted a seed-based analysis in a set of cortical regions of interest. Finally, we used a cluster-based permutation test to compare the differences between logically valid and invalid conditions in terms of FC. As a first novel result we found higher FC for valid condition in beta band between regions of interest and left prefrontal, temporal, parietal, and cingulate structures. FC analysis allows a second novel result which is the definition of a propositional network with operculo-cingular, parietal and medial nodes, specifically including disputed medial deductive "core" areas. The experiment discloses measurable cortical processes which do not depend on content but on truth-functional propositional operators. These experimental novelties may contribute to understand the cortical bases of deductive processes.

Protecting against mental impasses: Evidence of selective retrieval mitigating the impact of fixation in creative problem solving.

A common issue in creative problem solving is the unintended fixation on strongly associated, yet inappropriate solutions. In two experiments, we investigated whether lowering their accessibility by means of selective retrieval can positively affect subsequent problem-solving performance in a Compound Remote Associate test. Misleading associates were strengthened by letting participants memorize them alongside with neutral words. Half of the participants then selectively retrieved the neutral words in a cued recall test, temporarily weakening the activation level of induced fixation. In both experiments, this resulted in less impairment of subsequent performance for fixated CRA problems in early problem-solving stages (0-30 s). Additional results further revealed that participants who had engaged in prior selective retrieval perceived an increased feeling of having had immediate access to target solutions. These findings correspond to the assumption of inhibitory processes being a critical factor in both retrieval-induced forgetting and overcoming fixation in creative problem solving or preventing it from occurring in the first place. Also, they provide important insight into how strongly problem solving success is influenced by fixation.

Arithmetic problem size modulates brain activations in females but not in males.

Numerous empirical studies have reported that males and females perform equally well in mathematical achievement. However, still to date, very limited is understood about the brain response profiles that are particularly characteristic of males and females when solving mathematical problems. The present study aimed to tackle this issue by manipulating arithmetic problem size to investigate functional significance using functional magnetic resonance imaging (fMRI) in young adults. Participants were instructed to complete two runs of simple calculation tasks with either large or small problem sizes. Behavioural results suggested that the performance did not differ between females and males. Neuroimaging data revealed that sex/gender-related patterns of problem size effect were found in the brain regions that are conventionally associated with arithmetic, including the left middle frontal gyrus (MFG), left intraparietal sulcus (IPS) and insula. Specifically, females demonstrated substantial brain responses of problem size effect in these regions, whereas males showed marginal effects. Moreover, the machine learning method implemented over the brain signal levels within these regions demonstrated that sex/gender is discriminable. These results showed sex/gender effects in the activating patterns varying as a function of the distinct math problem size, even in a simple calculation task. Accordingly, our findings suggested that females and males use two complementary brain resources to achieve equally successful performance levels and highlight the pivotal role of neuroimaging facilities in uncovering neural mechanisms that may not be behaviourally salient.

Proposal for Investigating Self-Efficacy in Mathematics Using a Portable EEG System.

The present research proposal focuses on the search for the relation-ship between self-efficacy in mathematics, performance in mathematical tests, cognitive function during solving mathematical problems, and characteristics of the participants. The purpose of this study is to clarify the role of neurocognitive findings in the interpretation of perceived mathematical self-efficacy and, in addition, to investigate to what extent can neurophysiological data complement findings from socio-cognitive research and thus enrich general cognitive theories for mathematics education. The proposed research will use data from different datasets (questionnaire, neurophysiological, and biometric measurements). For the EEG measures the MUSE 2 portable EEG system will be used. The proposed study attempts to investigate (a) if there is a correlation between overall math self-efficacy scores and brain function during math problem-solving, (b) if there is a correlation between high self-efficacy and high math test performance, and (c) how math self-efficacy relates to participants' demographic characteristics and perceived math self-efficacy before and after the experiment.

Conflict detection and base-rate extremity.

People tend to ignore the probabilistic rules cued by the base-rate information and rely on the heuristic intuition cued by the descriptive information to make "stereotypical" responses in base-rate problems. Conflict detection studies have shown that reasoners can detect conflicts between heuristic intuition and probabilistic considerations despite ultimately stereotypical responses. However, these studies primarily used extreme base-rate tasks. A critical open question is the extent to which successful conflict detection relies on an extreme base rate. The present study explores this issue by manipulating the base-rate extremity of problems in which the descriptive information and the base-rate information conflict or not. As a result, when reasoners made stereotypical responses in the conflict version of the moderate base-rate task, they took longer to respond, had lower confidence in their responses, and were slower to evaluate their confidence than in the no-conflict version of the task. All three measures indicate that stereotypical reasoners can stably detect conflict in moderate base-rate tasks, which expands the scope of successful conflict detection. Moreover, our response confidence data found a larger detection effect size in the extreme base-rate condition than in the moderate base-rate condition. This suggests that conflict detection is more efficient as the base-rate extremity increases. Implications for the boundary conditions of conflict detection are discussed.

Heterogeneity of rules in Bayesian reasoning: A toolbox analysis.

How do people infer the Bayesian posterior probability from stated base rate, hit rate, and false alarm rate? This question is not only of theoretical relevance but also of practical relevance in medical and legal settings. We test two competing theoretical views: single-process theories versus toolbox theories. Single-process theories assume that a single process explains people's inferences and have indeed been observed to fit people's inferences well. Examples are Bayes's rule, the representativeness heuristic, and a weighing-and-adding model. Their assumed process homogeneity implies unimodal response distributions. Toolbox theories, in contrast, assume process heterogeneity, implying multimodal response distributions. After analyzing response distributions in studies with laypeople and professionals, we find little support for the single-process theories tested. Using simulations, we find that a single process, the weighing-and-adding model, nevertheless can best fit the aggregate data and, surprisingly, also achieve the best out-of-sample prediction even though it fails to predict any single respondent's inferences. To identify the potential toolbox of rules, we test how well candidate rules predict a set of over 10,000 inferences (culled from the literature) from 4,188 participants and 106 different Bayesian tasks. A toolbox of five non-Bayesian rules plus Bayes's rule captures 64% of inferences. Finally, we validate the Five-Plus toolbox in three experiments that measure response times, self-reports, and strategy use. The most important conclusion from these analyses is that the fitting of single-process theories to aggregate data risks misidentifying the cognitive process. Antidotes to that risk are careful analyses of process and rule heterogeneity across people.

Ordinal models to analyze strategy sophistication: Evidence from a learning trajectory efficacy study.

Investigators often rely on the proportion of correct responses in an assessment when describing the impact of early mathematics interventions on child outcomes. Here, we propose a shift in focus to the relative sophistication of problem-solving strategies and offer methodological guidance to researchers interested in working with strategies. We leverage data from a randomized teaching experiment with a kindergarten sample whose details are outlined in Clements et al. (2020). First, we describe our problem-solving strategy data, including how strategies were coded in ways that are amenable to analysis. Second, we explore what kinds of ordinal statistical models best fit the nature of arithmetic strategies, describe what each model implies about problem-solving behavior, and how to interpret model parameters. Third, we discuss the effect of "treatment", operationalized as instruction aligned with an arithmetic Learning Trajectory (LT). We show that arithmetic strategy development is best described as a sequential stepwise process and that children who receive LT instruction use more sophisticated strategies at post-assessment, relative to their peers in a teach-to-target skill condition. We introduce latent strategy sophistication as an analogous metric to traditional Rasch factor scores and demonstrate a moderate correlation them (r = 0.58). Our work suggests strategy sophistication carries information that is unique from, but complimentary to traditional correctness-based Rasch scores, motivating its expanded use in intervention studies.

The causal mechanisms underlying analogical reasoning performance improvement by executive attention intervention.

Analogical reasoning is important for human. We have found that a short executive attention intervention improved analogical reasoning performance in healthy young adults. Nevertheless, previous electrophysiological evidence was limited for comprehensively characterizing the neural mechanisms underlying the improvement. And although we hypothesized that the intervention improved active inhibitory control and attention shift first and then relation integration, it is still unclear whether there are two sequential cognitive neural activities were indeed changed during analogical reasoning. In the present study, we combined hypothesis with multivariate pattern analysis (MVPA) to explore the effects of the intervention on electrophysiology. Results showed that in the resting state after the intervention, alpha and high gamma power and the functional connectivity between the anterior and middle in the alpha band could discriminate the experimental group from the active control group, respectively. These indicated that the intervention influenced the activity of multiple bands and the interaction of frontal and parietal regions. In the analogical reasoning, alpha, theta, and gamma activities could also fulfill such discrimination, and furthermore, they were sequential (alpha first, theta, and gamma later). These results directly supported our previous hypothesis. The present study deepens our understanding about how executive attention contributes to higher-order cognition.

Response generation, not response execution, influences feelings of rightness in reasoning.

It has been argued that the experience of ease (i.e., the ability to quickly generate an initial response) during processing influences one's likelihood of engaging reflectively when reasoning. This is a key facet of Metacognitive Reasoning Theory (MRT) and numerous studies have found support for this claim by showing that answers that come to mind quickly, are associated with higher feelings of rightness (FORs), and less reflective processing. However, the possibility remains that the critical determinant of FORs may be the speed of executing a response and not generating a response, given the nature of the evidence for this claim. Across two experiments, we manipulated the duration of the response execution to identify whether participants' FOR judgements are at least partially based on factors occurring after the initial mental generation of an answer. We found no evidence that FORs nor reflection are influenced by a manipulation of response execution. Broadly, the present investigation provides evidence that the relation between speed of response and FORs is likely due to the speed with which an answer is generated internally, and not the response execution phase. These findings are consistent with Metacognitive Reasoning Theory and provide further support for the suggestion that answer fluency is the critical variable in determining FORs. All data, scripts, and materials can be found at https://osf.io/f48az/.