Relationship Between Prone Skills and Motor-Based Problem-Solving Abilities in Full-Term and Preterm Infants During the First 6 Months of Life.

Motor experiences shape cognitive development in infancy, with the prone position being one such crucial motor experience in the first 6 months of life. Although the motor benefits of the prone position are well-documented, its influence on early cognitive abilities remains insufficiently explored. This study quantified the relationship between prone motor skills and motor-based problem-solving abilities in 48 full-term and preterm infants aged 3-6 months. Prone skills were assessed using the Alberta Infant Motor Scale's prone domain. The Assessment of Problem-Solving in Play was utilized to measure motor-based problem-solving by observing how motor actions were used to solve toys. Advanced prone motor skills were correlated with an increase in sophisticated exploration skills and a concurrent decline in lower order exploration skills in all infants, with correlations being stronger in preterm infants. Notably, a 1-point increase in prone skills was associated with a 1.3-point increase in total motor-based problem-solving abilities in all infants. Our findings provide preliminary evidence for the contribution of prone play to cognitive development in infants, prompting considerations for assessment and intervention strategies. Further research is needed to ascertain if the delayed acquisition of prone motor skills is indicative of poor early problem-solving abilities in preterm infants.

Model-agnostic counterfactual reasoning for identifying and mitigating answer bias in knowledge tracing.

Knowledge tracing (KT) aims to monitor students' evolving knowledge states through their learning interactions with concept-related questions, and can be indirectly evaluated by predicting how students will perform on future questions. In this paper, we observe that there is a common phenomenon of answer bias, i.e., a highly unbalanced distribution of correct and incorrect answers for each question. Existing models tend to memorize the answer bias as a shortcut for achieving high prediction performance in KT, thereby failing to fully understand students' knowledge states. To address this issue, we approach the KT task from a causality perspective. A causal graph of KT is first established, from which we identify that the impact of answer bias lies in the direct causal effect of questions on students' responses. A novel COunterfactual REasoning (CORE) framework for KT is further proposed, which separately captures the total causal effect and direct causal effect during training, and mitigates answer bias by subtracting the latter from the former in testing. The CORE framework is applicable to various existing KT models, and we implement it based on the prevailing DKT, DKVMN, and AKT models, respectively. Extensive experiments on three benchmark datasets demonstrate the effectiveness of CORE in making the debiased inference for KT. We have released our code at https://github.com/lucky7-code/CORE.

Reasoning More Efficiently with Primary Knowledge Despite Extraneous Cognitive Load.

Geary's evolutionary approach in educational psychology differentiates between primary (low cognitive costs and motivational advantage) and secondary knowledge (high cognitive costs and no motivational benefit). Although these features have been well demonstrated in previous work, the underlying mechanisms remain unclear. To investigate it, in a reasoning task, the present study varies (i) the content of the problems (primary knowledge vs. secondary; e.g., food vs. grammar rules), (ii) the intrinsic cognitive load (conflict or non-conflict syllogism, the former requiring more cognitive resources to be properly processed than the latter) and (iii) the extraneous cognitive load (via a Dot Memory Task with three modalities: low, medium and high cognitive load). Analyses assessed the influence of these variables on performance, problem solving speed and perceived cognitive load. Results confirmed the positive impact of primary knowledge on efficiency, particularly when intrinsic cognitive load was high. Surprisingly, the extraneous cognitive load did not influence the performance in secondary knowledge content but that in primary knowledge content: the higher the additional load was, the better the performance was, only for primary knowledge and especially for syllogisms with high intrinsic load. Findings support evolutionary theory as secondary knowledge would overload cognitive resources, preventing participants from allocating sufficient resources to solve problems. Primary knowledge would allow participants to process the additional load and to increase their performance despite this. This study also raises the hypothesis that a minimum cognitive load is necessary for participants to be invested in the task.

Sex differences in visuospatial cognition- a female advantage in jigsaw puzzle solving.

Mentally visualizing objects, understanding relationships between two- or three- dimensional objects, and manipulating objects in space are some examples of visuospatial abilities. Numerous studies have shown that male participants outperform female participants in visuospatial tasks, particularly in mental rotation. One exception is solving jigsaw puzzles. Performance by seven- to eight-year-old girls was found to be superior to that of boys of the same age (Kocijan et al. 2017). No study, however, has confirmed this finding in an adult population, where sex differences are often detectable. Seventy-nine young adult participants were given four different jigsaw puzzles and the Shepard and Metzler mental rotation test (MRT) with two main goals: First, to investigate possible sex differences in jigsaw puzzle solving, and second, to explore a potential relationship between mental rotation and jigsaw puzzle solving. We hypothesized that female participants would outperform males in the jigsaw puzzles but males would outperform females in the MRT. The findings confirmed this hypothesis. Notably, the male performance in jigsaw puzzle solving was attributed to their sex and mediated by their higher MRT scores. These results yielded two key insights. First, they indicate a dissociation between these two visuospatial abilities, jigsaw puzzle solving and mental rotation; and second, female and male participants capitalize on their distinct cognitive strengths when solving visuospatial tasks.

Dynamic modulation of the processing of unpredicted technical errors by the posterior cingulate and the default mode network.

The pervasive use of information technologies (IT) has tremendously benefited our daily lives. However, unpredicted technical breakdowns and errors can lead to the experience of stress, which has been termed technostress. It remains poorly understood how people dynamically respond to unpredicted system runtime errors occurring while interacting with the IT systems on a behavioral and neuronal level. To elucidate the mechanisms underlying such processes, we conducted a functional magnetic resonance imaging (fMRI) study in which 15 young adults solved arithmetic problems of three difficulty levels (easy, medium and hard) while two types of system runtime errors (problem errors and feedback errors) occurred in an unexpected manner. The problem error condition consisted of apparently defective displays of the arithmetic problem and the feedback error condition involved erroneous feedback. We found that the problem errors positively influenced participants' problem-solving performance at the high difficulty level (i.e., hard tasks) at the initial stage of the session, while feedback errors disturbed their performance. These dynamic behavioral changes are mainly associated with brain activation changes in the posterior cingulate and the default mode network, including the posterior cingulate cortex, the mPFC, the retrosplenial cortex and the parahippocampal gyrus. Our study illustrates the regulatory role of the posterior cingulate in coping with unpredicted errors as well as with dynamic changes in the environment.

Evaluating language models for mathematics through interactions.

There is much excitement about the opportunity to harness the power of large language models (LLMs) when building problem-solving assistants. However, the standard methodology of evaluating LLMs relies on static pairs of inputs and outputs; this is insufficient for making an informed decision about which LLMs are best to use in an interactive setting, and how that varies by setting. Static assessment therefore limits how we understand language model capabilities. We introduce CheckMate, an adaptable prototype platform for humans to interact with and evaluate LLMs. We conduct a study with CheckMate to evaluate three language models (InstructGPT, ChatGPT, and GPT-4) as assistants in proving undergraduate-level mathematics, with a mixed cohort of participants from undergraduate students to professors of mathematics. We release the resulting interaction and rating dataset, MathConverse. By analyzing MathConverse, we derive a taxonomy of human query behaviors and uncover that despite a generally positive correlation, there are notable instances of divergence between correctness and perceived helpfulness in LLM generations, among other findings. Further, we garner a more granular understanding of GPT-4 mathematical problem-solving through a series of case studies, contributed by experienced mathematicians. We conclude with actionable takeaways for ML practitioners and mathematicians: models that communicate uncertainty, respond well to user corrections, and can provide a concise rationale for their recommendations, may constitute better assistants. Humans should inspect LLM output carefully given their current shortcomings and potential for surprising fallibility.

External constraints that led to physiology lab improvements.

The modifications were in response to changing constraints, including time, money, space, student background, and my knowledge and comfort. The lab went from emphasizing experiments with the attendant troubleshooting and data analysis skills to a lab focused more on giving prehealth professional students the motivation to learn physiology problem-solving skills by providing real cases. In the lab, students watched and listened to a random student try to use these problem-solving skills to solve the problem. This made them appreciate how much others also struggle in solving the problem. Some students with imposter syndrome think their classmates immediately know how to solve a problem, and therefore, seeing others also struggle has the potential to reduce imposter syndrome. Rather than having the students do experiments, they did kinesthetic activities with mechanical models to generate data without biological variation. They then graphed their data, thus improving their ability to actually read graphs rather than memorize patterns.NEW & NOTEWORTHY I learned to explicitly recognize the current and projected constraints of instructor comfort, money, space, student background (poor graph reading and problem-solving skills), student safety, and time and energy on the possible goals and methods to attain them for an undergraduate physiology lab. I cannot decide if changing constraints allowed me to reexamine my goals or whether it forced me to reexamine my goals. In either case, the reexamination of my goals (and their priorities), within the context of the constraints, allowed me to redesign the labs to better meet my new goals within this new context.

Question-asking as a mechanism of information seeking.

Ivancovsky et al. explore the relationship between curiosity and creativity, by suggesting they align through novelty-seeking mechanisms. We argue that a general mechanism linking both capacities together is question-asking: Curiosity drives question-asking that leads to creative problem solving. Yet, current findings from our lab suggest that question complexity relates to creativity, but not necessarily to curiosity, warranting further investigation.

ERP evidence for temporal differences between cross-modal and cross-domain analogical reasoning.

Previous studies have shown that individuals not only successfully engage in cross-domain analogies but also accomplish cross-modal reasoning. Yet, the behavioral representation and neurophysiological basis of cross-modal and cross-domain analogical reasoning remain unclear. This study established three analogical reasoning conditions by combining a multi-to-multi learning-test paradigm with a four­term analogy paradigm: within-domain, cross-domain, and cross-modal conditions. Thirty participants were required to judge whether the relationship between C and D was the same as the learned relationship between A and B. Behavioral results revealed no significant differences in reaction times and accuracy between cross-domain and cross-modal conditions, but both conditions showed significantly lower accuracy than within-domain condition. ERP results indicated a larger P2 amplitude in the cross-modal condition, while a larger N400 amplitude was observed in the cross-domain condition. These findings suggest: (1) The P2 in cross-modal analogical reasoning is associated with more difficult access to cross-modal information. (2) The N400 in cross-domain analogical reasoning is related to more challenging semantic processing. This study provides the first evidence of behavioral and ERP differences between cross-modal and cross-domain analogical reasoning, deepening our understanding of the cognitive processes involved in cross-modal analogical reasoning.

Short-term number sense training recapitulates long-term neurodevelopmental changes from childhood to adolescence.

Number sense is fundamental to the development of numerical problem-solving skills. In early childhood, children establish associations between non-symbolic (e.g., a set of dots) and symbolic (e.g., Arabic numerals) representations of quantity. The developmental estrangement theory proposes that the relationship between non-symbolic and symbolic representations of quantity evolves with age, with increased dissociation across development. Consistent with this theory, recent research suggests that cross-format neural representational similarity (NRS) between non-symbolic and symbolic quantities is correlated with arithmetic fluency in children but not in adolescents. However, it is not known if short-term training (STT) can induce similar changes as long-term development. In this study, children aged 7-10 years underwent a theoretically motivated 4-week number sense training. Using multivariate neural pattern analysis, we investigated whether short-term learning could modify the relation between cross-format NRS and arithmetic skills. Our results revealed a significant correlation between cross-format NRS and arithmetic fluency in distributed brain regions, including the parietal and prefrontal cortices, prior to training. However, this association was no longer observed after training, and multivariate predictive models confirmed these findings. Our findings provide evidence that intensive STT during early childhood can promote behavioral improvements and neural plasticity that resemble and recapitulate long-term neurodevelopmental changes that occur from childhood to adolescence. More generally, our study contributes to our understanding of the malleability of number sense and highlights the potential for targeted interventions to shape neurodevelopmental trajectories in early childhood. RESEARCH HIGHLIGHTS: We tested the hypothesis that short-term number sense training induces the dissociation of symbolic numbers from non-symbolic representations of quantity in children. We leveraged a theoretically motivated intervention and multivariate pattern analysis to determine training-induced neurocognitive changes in the relation between number sense and arithmetic problem-solving skills. Neural representational similarity between non-symbolic and symbolic quantity representations was correlated with arithmetic skills before training but not after training. Short-term training recapitulates long-term neurodevelopmental changes associated with numerical problem-solving from childhood to adolescence.

Functional fixedness in chimpanzees.

Differences in the tool use of non-human primates and humans are subject of ongoing debate. In humans, representations of object functions underpin efficient tool use. Yet, representations of object functions can lead to functional fixedness, which describes the fixation on a familiar tool function leading to less efficient problem solving when the problem requires using the tool for a new function. In the current study, we examined whether chimpanzees exhibit functional fixedness. After solving a problem with a tool, chimpanzees were less efficient in solving another problem which required using the same tool with a different function compared to a control group. This fixation effect was still apparent after a period of nine months and when chimpanzees had learned about the function of a tool by observation of a conspecific. These results suggest that functional fixedness in our closest living relatives likely exists and cast doubt on the notion that stable function representations are uniquely human.

Investigating low intelligence stereotype threat in adults with developmental dyslexia.

Stereotype threat (ST) is a phenomenon that leads to decreased test performance and occurs when one deals with added pressure of being judged on the basis of stereotyped group membership. The ST effect has been previously investigated in many contexts but not in individuals with dyslexia who are often stereotyped as less intelligent. Prevalent use of intelligence tests in job selection processes and employment gap between people with dyslexia and those without warrants this investigation. Sixty-three participants (30 with dyslexia and 33 without dyslexia; mean age = 33.7; SD = 13.7; 47 F, 13 M, three non-binary) were asked to complete intelligence test typically used in selection processes. All participants were randomly assigned to one of three test instruction conditions: (1) they were told the test was diagnostic of their intelligence (ST triggering instruction); (2) test was a measure of their problem-solving skills (reduced threat); (3) or they were simply asked to take the test (control). Results showed that participants with dyslexia in ST condition performed poorer than those in other conditions and those in the same condition who did not have dyslexia. This study provides preliminary evidence for diminishing effects of ST in individuals with dyslexia.

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.

The effect of episodic specificity inductions on cognitive tasks involving episodic retrieval: A quantitative review.

A growing body of research suggests that an episodic specificity induction (ESI), that is, training in recalled details of a (recent) past event, impacts performance on subsequent tasks that require episodic retrieval processes. The constructive episodic simulation hypothesis (Schacter and Addis, 2007) posits that various tasks which require, at least partially, episodic retrieval processes rely on a single, flexible episodic memory system. As such, a specificity induction activates that episodic memory system and improves subsequent performance on tasks that require use of that memory system. The present quantitative review analyzed the literature demonstrating that the Episodic Specificity Induction (ESI) improves performance on subsequence cognitive tasks that require (at least partial) episodic retrieval processes. Twenty-three studies met criteria for measuring the impact of ESI, compared to a non-specificity control induction(s), on subsequent tasks requiring edpisodic retrieval, including memory, imagination, problem solving, divergent thinking. The results of this review demonstrate a strong, positive effect of ESI on episodic memory, imagination, divergent thinking, and problem-solving tasks.

The involvement of decomposition and composition processes in restructuring during problem solving.

Decomposition of chunks has been widely accepted as a critical proxy of restructuring, but the role of composition in forming new representations has been largely neglected. This study aims to investigate the roles of both decomposition and composition processes in chunk restructuring, as well as their relationships with "aha" experiences during problem-solving. Participants were asked to move a part of a character to another character to create two new characters. Across three experiments, the characters to be decomposed or composed were varied in terms of tight or loose chunks. The results showed that decomposition or composition of tight chunks led to lower success rates, longer response times, and significantly stronger "Aha!" emotional experiences (mainly in terms of surprise and suddenness). This study provides evidence for the contribution of both decomposition and composition processes to restructuring in creative insight.

Unpacking associations among children's spatial skills, mathematics, and arithmetic strategies: decomposition matters.

Several studies revealed links between mental rotation and mathematical tasks, but the intervening processes in this connection remain rather unexplored. Here, we aimed to investigate whether children's mental rotation skills relate to their accuracy in solving arithmetic problems via their usage of decomposition strategies, thus probing one potential intervening process. To this end, we examined a sample of 6- to 8-year-olds (N = 183) with a chronometric mental rotation task, and asked children to solve several arithmetic problems while assessing their solution strategies. After each arithmetic problem, children were asked about their strategy to solve the respective arithmetic problem and these were classified as either counting, decomposition, or retrieval strategies. Analyses were controlled for age, sex, fluid and verbal reasoning. Results indicated that children's response times and accuracy in the mental rotation task were best explained by linear functions of rotation angle, suggesting the usage of dynamic mental transformation strategies. A multiple mediation model revealed that children with higher mental rotation skills were more inclined to use higher-level mental strategies such as decomposition which in turn increased their accuracy of solving arithmetic problems. None of the other arithmetic strategies revealed significant indirect effects. These findings suggest that children with higher mental rotation skills may profit from visualizing and flexibly transforming numerical magnitudes, increasing the frequency of decomposition strategies. Overall, decomposition may play a unique role in the connection between children's mental rotation and arithmetic skills, which is an essential information for planning future training and experimental studies.

The lack of Aha! experience can be dependent on the problem difficulty.

Previous research on how problem-difficulty affects solution-types of insight-problems has yielded contradictory findings. Thus, we aimed to examine the impact of problem-difficulty on solution-types in both inter- and intra-problem-difficulty contexts. For this, we employed the original 8-coin, and 9-dot problems and four hinted-versions of those that were manipulated by using hints-to-remove-sources-of-difficulty to alter their difficulty level. Those manipulations were executed based on the assumptions of constraint-relaxation and chunk-decomposition as posited by representational change theory. The study involved a total of 165 participants who were tested in five groups (33 per se), with each group receiving an original or hinted problem. Following their correct solutions, problem-solvers classified their solution-types (insight or non-insight solutions) by whether they had an Aha!-experience during the solution. Across all groups, 56.1% of correctly solved insight problems were solved with Aha!-experience, based on participants' self-reports, implying that correct solutions should not be equated with insight. Subsequently, the solution-type rates were compared for both original problems (inter-problem-difficulty) and hinted versions of those at each difficulty level (intra-problem-difficulty). Inter-problem-difficulty comparisons demonstrated that the easier 8-coin problem was more likely to be solved with insight than the harder 9-dot problem. In contrast, intra-problem-difficulty comparisons revealed that harder problems were more likely to be solved with insight. These findings suggest that problem-difficulty should be considered in future studies of insight. Finally, separate analyses on the predictive values of the cognitive-affective-dimensions on solution-types revealed that, after adjusting for problem-difficulty, problem-solvers with higher suddenness scores in both problems exhibited a significantly higher probability of generating insight solutions.

The relationship between numerical magnitude processing and math anxiety, and their joint effect on adult math performance, varied by indicators of numerical tasks.

According to the hypothesis of Maloney et al. (Cognition 114(2):293-297, 2010. https://doi.org/10.1016/j.cognition.2009.09.013), math anxiety is related to deficits in numerical magnitude processing, which in turn compromises the development of advanced math skills. Because previous studies on this topic are contradictory, which may be due to methodological differences in the measurement of numerical magnitude processing, we tested Maloney et al.'s hypothesis using different tasks and their indicators: numerical magnitude processing (symbolic and non-symbolic comparison tasks: accuracy, reaction time, numerical ratio, distance and size effects, and Weber fraction; number line estimation task: estimation error), math anxiety (combined scores of learning, testing, math problem solving, and general math anxiety), and math performance. The results of our study conducted on 119 young adults mostly support the hypothesis proposed by Maloney et al. that deficiency in symbolic magnitude processing is related to math anxiety, but the relationship between non-symbolic processes and math anxiety was opposite to the assumptions. Moreover, the results indicate that estimation processes (but not comparison processes) and math anxiety are related to math performance in adults. Finally, high math anxiety moderated the relationship between reaction time in the symbolic comparison task, reaction time in the non-symbolic comparison task, numerical ratio effect in the symbolic comparison task, and math performance. Because the results of the joint effect of numerical magnitude processing and math anxiety on math performance were inconsistent, this part of the hypothesis is called into question.

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.

Spindle-slow wave coupling and problem-solving skills: impact of age.

We examined how aging affects the role of sleep in the consolidation of newly learned cognitive strategies. Forty healthy young adults (20-35 years) and 30 healthy older adults (60-85 years) were included. Participants were trained on the Tower of Hanoi (ToH) task, then, half of each age group were assigned to either the 90-minute nap condition, or stayed awake, before retesting. The temporal co-occurrence between slow waves (SW) and sleep spindles (SP) during non-rapid eye movement sleep was examined as a function of age in relation to memory consolidation of problem-solving skills. We found that despite intact learning, older adults derived a reduced benefit of sleep for problem-solving skills relative to younger adults. As expected, the percentage of coupled spindles was lower in older compared to younger individuals from control to testing sessions. Furthermore, coupled spindles in young adults were more strongly coupled to the SW upstate compared to older individuals. Coupled spindles in older individuals were lower in amplitude (mean area under the curve; µV) compared to the young group. Lastly, there was a significant relationship between offline gains in accuracy on the ToH and percent change of spindles coupled to the upstate of the slow wave in older, but not younger adults. Multiple regression revealed that age accounted for differences in offline gains in accuracy, as did spindle coupling during the upstate. These results suggest that with aging, spindle-slow wave coupling decreases. However, the degree of the preservation of coupling with age correlates with the extent of problem-solving skill consolidation during sleep.