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.

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.

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.

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.

A functional role for oculomotor preparation in mental arithmetic evidenced by the abducted eye paradigm

Solving subtraction and addition problems is accompanied by spontaneous leftward and rightward gaze shifts, respectively. These shifts have been related to attentional processes involved in mental arithmetic, but whether these processes induce overt attentional shifts mediated by the activation of the motor programs underlying lateral eye movements or covert shifts only is still unknown. Here, we used the abducted eye paradigm to selectively disrupt activation of the oculomotor system and prevent oculomotor preparation, which affects overt but not covert attentional shifts. Participants had to mentally solve addition and subtraction problems while fixating a screen positioned either in front of them or laterally to their left or right such that they were physically unable to programme and execute saccades further into their temporal field while they still could do so in their nasal field. In comparison to the frontal condition, rightward eye abduction impaired additions (with carrying), and leftward eye abduction impaired subtractions (with borrowing) showing that at least some arithmetic problems rely on processes dedicated to overt attentional shifts. We propose that when solving arithmetic problems requires procedures such as carrying and borrowing, oculomotor mechanisms operating on a mental space transiently built in working memory are recruited to represent one numerical magnitude in relation to another (e.g. the first operand and the result).

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.

Graph Mapping: A novel and simple test to validly assess fluid reasoning

We present Graph Mapping - a simple and effective computerized test of fluid intelligence (reasoning ability). The test requires structure mapping - a key component of the reasoning process. Participants are asked to map a pair of corresponding nodes across two mathematically isomorphic but visually different graphs. The test difficulty can be easily manipulated - the more complex structurally and dissimilar visually the graphs, the higher response error rate. Graph Mapping offers high flexibility in item generation, ranging from trivial to extremally difficult items, supporting progressive item sequences suitable for correlational studies. It also allows multiple item instances (clones) at a fixed difficulty level as well as full item randomization, both particularly suitable for within-subject experimental designs, longitudinal studies, and adaptive testing. The test has short administration times and is unfamiliar to participants, yielding practical advantages. Graph Mapping has excellent psychometric properties: Its convergent validity and reliability is comparable to the three leading traditional fluid reasoning tests. The convenient software allows a researcher to design the optimal test variant for a given study and sample. Graph Mapping can be downloaded from: https://osf.io/wh7zv/.

The underlying neural bases of the reversal error while solving algebraic word problems

Problem solving is a core element in mathematical learning. The reversal error in problem solving occurs when students are able to recognize the information in the statement of comparison word problems, but they reverse the relationship between two variables when building the equations. Functional magnetic resonance images were acquired to identify for the first time the neural bases associated with the reversal error. The neuronal bases linked to this error have been used as inputs in 13 classifiers to discriminate between reversal error and non-reversal error groups. We found brain activation in bilateral fronto-parietal areas in the participants who committed reversal errors, and only left fronto-parietal activation in those who did not, suggesting that the reversal error group needed a greater cognitive demand. Instead, the non-reversal error group seems to show that they have developed solid algebraic knowledge. Additionally, the results showed brain activation in the right middle temporal gyrus when comparing the reversal error vs non-reversal error groups. This activation would be associated with the semantic processing which is required to understand the statement and build the equation. Finally, the classifier results show that the brain areas activated could be considered good biomarkers to help us identify competent solvers.

Brain Activity Associated with the Planning Process during the Long-Time Learning of the Tower of Hanoi (ToH) Task: A Pilot Study

Planning and decision-making are critical managerial functions involving the brain's executive functions. However, little is known about the effect of cerebral activity during long-time learning while planning and decision-making. This study investigated the impact of planning and decision-making processes in long-time learning, focusing on a cerebral activity before and after learning. The methodology of this study involves the Tower of Hanoi (ToH) to investigate executive functions related to the learning process. Generally, ToH is used to measure baseline performance, learning rate, offline learning (following overnight retention), and transfer. However, this study performs experiments on long-time learning effects for ToH solving. The participants were involved in learning the task over seven weeks. Learning progress was evaluated based on improvement in performance and correlations with the learning curve. All participants showed a significant improvement in planning and decision-making over seven weeks of time duration. Brain activation results from fMRI showed a statistically significant decrease in the activation degree in the dorsolateral prefrontal cortex, parietal lobe, inferior frontal gyrus, and premotor cortex between before and after learning. Our pilot study showed that updating information and shifting issue rules were found in the frontal lobe. Through monitoring performance, we can describe the effect of long-time learning initiated at the frontal lobe and then convert it to a task execution function by analyzing the frontal lobe maps. This process can be observed by comparing the learning curve and the fMRI maps. It was also clear that the degree of activation tends to decrease with the number of tasks, such as through the mid-phase and the end-phase of training. The elucidation of this structure is closely related to decision-making in human behavior, where brain dynamics differ between "thinking and behavior" during complex thinking in the early stages of training and instantaneous "thinking and behavior" after sufficient training. Since this is related to human learning, elucidating these mechanisms will allow the construction of a brain function map model that can be used universally for all training tasks.

Dynamics of hidden brain states when people solve verbal puzzles

When people try to solve a problem, they go through distinct steps (encoding, ideation, evaluation, etc.) recurrently and spontaneously. To disentangle different cognitive processes that unfold throughout a trial, we applied an unsupervised machine learning method to electroencephalogram (EEG) data continuously recorded while 39 participants attempted 153 Compound Remote Associates problems (CRA). CRA problems are verbal puzzles that can be solved in either insight-leaning or analysis-leaning manner. We fitted a Hidden Markov Model to the time-frequency transformed EEG signals and decoded each trial as a time-resolved state sequence. The model characterizes hidden brain states with spectrally resolved power topography. Seven states were identified with distinct activation patterns in the theta (4-7 Hz), alpha (8-9 Hz and 10-13 Hz), and gamma (25-50 Hz) bands. Notably, a state featuring widespread activation only in alpha-band frequency emerged, from this data-driven approach, which exhibited dynamic characteristics associated with specific temporal stages and outcomes (whether solved with insight or analysis) of the trials. The state dynamics derived from the model overlap and extend previous literature on the cognitive function of alpha oscillation: the "alpha-state" probability peaks before stimulus onset and decreases before response. In trials solved with insight, relative to solved with analysis, the alpha-state is more likely to be visited and maintained during preparation and solving periods, and its probability declines more sharply immediately preceding a response. This novel paradigm provides a way to extract dynamic features that characterize problem-solving stages and potentially provide a novel window into the nature of the underlying cognitive processes.

Uncovering the global task-modulated brain network in chunk decomposition with Chinese characters

Chunk decomposition, which requires the mental representation transformation in accordance with behavioral goals, is of vital importance to problem solving and creative thinking. Previous studies have identified that the frontal, parietal, and occipital cortex in the cognitive control network selectively activated in response to chunk tightness, however, functional localization strategy may overlook the interaction brain regions. Based on the notion of a global brain network, we proposed that multiple specialized regions have to be interconnected to maintain goal representation during the course of chunk decomposition. Therefore, the present study applied a beta-series correlation method to investigate interregional functional connectivity in the event-related design of chunk decomposition tasks using Chinese characters, which would highlight critical nodes irrespective to chunk tightness. The results reveal a network of functional hubs with highly within or between module connections, including the orbitofrontal cortex, superior/inferior parietal lobule, hippocampus, and thalamus. We speculate that the thalamus integrates information across modular as an integrative hub while the orbitofrontal cortex tracks the mental states of chunk decomposition on a moment-to-moment basis. The superior and inferior parietal lobule collaborate to manipulate the mental representation of chunk decomposition and the hippocampus associates the relationship between elements in the question and solution phase. Furthermore, the tightness of chunks is not only associated with different processors in visual systems but also leads to increased intermodular connections in right superior frontal gyrus and left precentral gyrus. To summary up, the present study first reveals the task-modulated brain network of chunk decomposition in addition to the tightness-related nodes in the frontal and occipital cortex.

Task dynamics define the contextual emergence of human corralling behaviors

Social animals have the remarkable ability to organize into collectives to achieve goals unobtainable to individual members. Equally striking is the observation that despite differences in perceptual-motor capabilities, different animals often exhibit qualitatively similar collective states of organization and coordination. Such qualitative similarities can be seen in corralling behaviors involving the encirclement of prey that are observed, for example, during collaborative hunting amongst several apex predator species living in disparate environments. Similar encirclement behaviors are also displayed by human participants in a collaborative problem-solving task involving the herding and containment of evasive artificial agents. Inspired by the functional similarities in this behavior across humans and non-human systems, this paper investigated whether the containment strategies displayed by humans emerge as a function of the task's underlying dynamics, which shape patterns of goal-directed corralling more generally. This hypothesis was tested by comparing the strategies naïve human dyads adopt during the containment of a set of evasive artificial agents across two disparate task contexts. Despite the different movement types (manual manipulation or locomotion) required in the different task contexts, the behaviors that humans display can be predicted as emergent properties of the same underlying task-dynamic model.

Common and distinct predictors of non-symbolic and symbolic ordinal number processing across the early primary school years

What are the cognitive mechanisms supporting non-symbolic and symbolic order processing? Preliminary evidence suggests that non-symbolic and symbolic order processing are partly distinct constructs. The precise mechanisms supporting these skills, however, are still unclear. Moreover, predictive patterns may undergo dynamic developmental changes during the first years of formal schooling. This study investigates the contribution of theoretically relevant constructs (non-symbolic and symbolic magnitude comparison, counting and storage and manipulation components of verbal and visuo-spatial working memory) to performance and developmental change in non-symbolic and symbolic numerical order processing. We followed 157 children longitudinally from Grade 1 to 3. In the order judgement tasks, children decided whether or not triplets of dots or digits were arranged in numerically ascending order. Non-symbolic magnitude comparison and visuo-spatial manipulation were significant predictors of initial performance in both non-symbolic and symbolic ordering. In line with our expectations, counting skills contributed additional variance to the prediction of symbolic, but not of non-symbolic ordering. Developmental change in ordering performance from Grade 1 to 2 was predicted by symbolic comparison skills and visuo-spatial manipulation. None of the predictors explained variance in developmental change from Grade 2 to 3. Taken together, the present results provide robust evidence for a general involvement of pair-wise magnitude comparison and visuo-spatial manipulation in numerical ordering, irrespective of the number format. Importantly, counting-based mechanisms appear to be a unique predictor of symbolic ordering. We thus conclude that there is only a partial overlap of the cognitive mechanisms underlying non-symbolic and symbolic order processing.

Functional neuroanatomy of arithmetic in monolingual and bilingual adults and children

Prior studies on the brain bases of arithmetic have not focused on (or even described) their participants' language backgrounds. Yet, unlike monolinguals, early bilinguals have the capacity to solve arithmetic problems in both of their two languages. This raises the question whether this ability, or any other experience that comes with being bilingual, affects brain activity for arithmetic in bilinguals relative to monolinguals. Here, we used functional magnetic resonance imaging to compare brain activity in 44 English monolinguals and 44 Spanish-English early bilinguals, during the solving of arithmetic problems in English. We used a factorial design to test for a main effect of bilingual Language Experience. Based on the known modulating roles of arithmetic operation and age, we used two arithmetic tasks (addition and subtraction) and studied two age groups (adults and children). When collapsing across operations and age, we found broad bilateral activation for arithmetic in both the monolingual group and the bilingual group. However, an analysis of variance revealed that there was no effect of Language Experience, nor an interaction of Language Experience with Operation or Age Group. Bayesian analyses within regions of interest chosen for their role in arithmetic further supported the finding of no effect of Language Experience on brain activity underlying arithmetic. We conclude that early bilingualism does not influence the functional neuroanatomy of simple arithmetic.

The relation between parietal GABA concentration and numerical skills

Several scientific, engineering, and medical advancements are based on breakthroughs made by people who excel in mathematics. Our current understanding of the underlying brain networks stems primarily from anatomical and functional investigations, but our knowledge of how neurotransmitters subserve numerical skills, the building block of mathematics, is scarce. Using 1H magnetic resonance spectroscopy (N = 54, 3T, semi-LASER sequence, TE = 32 ms, TR = 3.5 s), the study examined the relation between numerical skills and the brain's major inhibitory (GABA) and excitatory (glutamate) neurotransmitters. A negative association was found between the performance in a number sequences task and the resting concentration of GABA within the left intraparietal sulcus (IPS), a key region supporting numeracy. The relation between GABA in the IPS and number sequences was specific to (1) parietal but not frontal regions and to (2) GABA but not glutamate. It was additionally found that the resting functional connectivity of the left IPS and the left superior frontal gyrus was positively associated with number sequences performance. However, resting GABA concentration within the IPS explained number sequences performance above and beyond the resting frontoparietal connectivity measure. Our findings further motivate the study of inhibition mechanisms in the human brain and significantly contribute to our current understanding of numerical cognition's biological bases.

Is prediction nothing more than multi-scale pattern completion of the future?

While the notion of the brain as a prediction machine has been extremely influential and productive in cognitive science, there are competing accounts of how best to model and understand the predictive capabilities of brains. One prominent framework is of a "Bayesian brain" that explicitly generates predictions and uses resultant errors to guide adaptation. We suggest that the prediction-generation component of this framework may involve little more than a pattern completion process. We first describe pattern completion in the domain of visual perception, highlighting its temporal extension, and show how this can entail a form of prediction in time. Next, we describe the forward momentum of entrained dynamical systems as a model for the emergence of predictive processing in non-predictive systems. Then, we apply this reasoning to the domain of language, where explicitly predictive models are perhaps most popular. Here, we demonstrate how a connectionist model, TRACE, exhibits hallmarks of predictive processing without any representations of predictions or errors. Finally, we present a novel neural network model, inspired by reservoir computing models, that is entirely unsupervised and memoryless, but nonetheless exhibits prediction-like behavior in its pursuit of homeostasis. These explorations demonstrate that brain-like systems can get prediction "for free," without the need to posit formal logical representations with Bayesian probabilities or an inference machine that holds them in working memory.

Gray matter volume in left intraparietal sulcus predicts longitudinal gains in subtraction skill in elementary school

Although behavioral studies show large improvements in arithmetic skills in elementary school, we do not know how brain structure supports math gains in typically developing children. While some correlational studies have investigated the concurrent association between math performance and brain structure, such as gray matter volume (GMV), longitudinal studies are needed to infer if there is a causal relation. Although discrepancies in the literature on the relation between GMV and math performance have been attributed to the different demands on quantity vs. retrieval mechanisms, no study has experimentally tested this assumption. We defined regions of interests (ROIs) associated with quantity representations in the bilateral intraparietal sulcus (IPS) and associated with the storage of arithmetic facts in long-term memory in the left middle and superior temporal gyri (MTG/STG), and studied associations between GMV in these ROIs and children's performance on operations having greater demands on quantity vs. retrieval mechanisms, namely subtraction vs. multiplication. The aims of this study were threefold: First, to study concurrent associations between GMV and math performance, second, to investigate the role of GMV at the first time-point (T1) in predicting longitudinal gains in math skill to the second time-point (T2), and third, to study whether changes in GMV over time were associated with gains in math skill. Results showed no concurrent association between GMV in IPS and math performance, but a concurrent association between GMV in left MTG/STG and multiplication skill at T1. This association showed that the higher the GMV in this ROI, the higher the children's multiplication skill. Results also revealed that GMV in left IPS and left MTG/STG predicted longitudinal gains in subtraction skill only for younger children (approximately 10 years old). Whereas higher levels of GMV in left IPS at T1 predicted larger subtraction gains, higher levels of GMV in left MTG/STG predicted smaller gains. GMV in left MTG/STG did not predict longitudinal gains in multiplication skill. No significant association was found between changes in GMV over time and longitudinal gains in math. Our findings support the early importance of brain structure in the IPS for mathematical skills that rely on quantity mechanisms.

The RCA ReCAst: A Root Cause Analysis Simulation for the Interprofessional Clinical Learning Environment

PROBLEM

The Accreditation Council for Graduate Medical Education calls for resident participation in real or simulated interprofessional analysis of a patient safety event. There are far more residents who must participate in these investigations than available institutional root cause analyses (RCAs) to accommodate them. To correct this imbalance, the authors developed an institutionally sponsored, interprofessional RCA simulation program and implemented it across all graduate medical education (GME) residency programs at the Hospital of the University of Pennsylvania.

APPROACH

The authors developed RCA simulations based upon authentic adverse events experienced at their institution. To provide relevance to all GME programs, RCA simulation cases varied widely and included examples of errors involving high-risk medications, communication, invasive procedures, and specimen labeling. Each simulation included residents and other health care professionals such as nurses or pharmacists whose disciplines were involved in the actual event. Participants adopted the role of RCA investigation team, and in small groups systematically progressed through the RCA process.

OUTCOMES

A total of 289 individuals from 18 residency programs participated in an RCA simulation in 2019-2020. This included 84 interns (29%), 123 residents (43%), 20 attending physicians (7%), and 62 (21%) other health care professionals. There was an increase in ability of GME trainees to correctly identify factors required for an RCA investigation (62% pre vs 80% post, P = .02) and an increase in intent to "always report" for each adverse event category (3% pre vs 37% post, P < .001) following the simulation.

NEXT STEPS

The authors plan to expand the RCA simulation program to other GME clinical sites while striving to involve all GME learners in this educational experience at least once during training. Additionally, by collaborating with health system patient safety leaders, they will annually review all new RCAs to identify cases suitable for simulation adaptation.

Integrating a problem-solving intervention with routine care to improve psychosocial functioning among mothers of children with sickle cell disease: A randomized controlled trial

OBJECTIVE

To assess the feasibility of a problem-solving skills training intervention in improving psychological outcomes in mothers of infants with sickle cell disease (SCD).

DESIGN AND METHODS

This parallel randomized controlled trial recruited 64 babies with SCD, 6 to 12 months of age, and their mothers. Baseline measurements assessed mothers' coping and problem-solving skills, depression, and parental stress before random assignment to intervention or control groups (n = 32 each). Problem-solving skills intervention was delivered through 6 monthly sessions, when babies attended for routine penicillin prophylaxis. All measurements were repeated for both groups at the end of the intervention period. Intention to treat analysis used repeated measures mixed models with the restricted estimation maximum likelihood approach.

RESULTS

The problem-solving intervention had no significant effect on mothers' problem-solving skills (adjusted treatment effect: -1.69 points (95% CI:-5.62 to 2.25)), coping behaviours (adjusted treatment effect: 0.65 points (95% CI:- -7.13 to 8.41)) or depressive symptoms (adjusted treatment effect: -0.41 (95% CI: -6.00 to 5.19)). It reduced mothers' level of difficulty in managing stressful events by 9.5 points (95% CI (-16.86 to -2.16); effect size: 0.21 SD). In the subgroup of mothers at risk of depression (n = 31 at baseline), the intervention reduced depression scores with treatment effect of 10.4 points (95%CI: -18.83 to -1.88; effect size: 0.67 SD).

CONCLUSION

This problem-solving skills intervention study suggests feasibility and possible efficacy in improving some maternal outcomes. Further refinement and culturally appropriate adaptations of the intervention could lead to stronger effects.

Reevaluating pragmatic reasoning in language games

The results of a highly influential study that tested the predictions of the Rational Speech Act (RSA) model suggest that (a) listeners use pragmatic reasoning in one-shot web-based referential communication games despite the artificial, highly constrained, and minimally interactive nature of the task, and (b) that RSA accurately captures this behavior. In this work, we reevaluate the contribution of the pragmatic reasoning formalized by RSA in explaining listener behavior by comparing RSA to a baseline literal listener model that is only driven by literal word meaning and the prior probability of referring to an object. Across three experiments we observe only modest evidence of pragmatic behavior in one-shot web-based language games, and only under very limited circumstances. We find that although RSA provides a strong fit to listener responses, it does not perform better than the baseline literal listener model. Our results suggest that while participants playing the role of the Speaker are informative in these one-shot web-based reference games, participants playing the role of the Listener only rarely take this Speaker behavior into account to reason about the intended referent. In addition, we show that RSA's fit is primarily due to a combination of non-pragmatic factors, perhaps the most surprising of which is that in the majority of conditions that are amenable to pragmatic reasoning, RSA (accurately) predicts that listeners will behave non-pragmatically. This leads us to conclude that RSA's strong overall correlation with human behavior in one-shot web-based language games does not reflect listener's pragmatic reasoning about informative speakers.

Inter-brain synchrony in teams predicts collective performance

Despite decades of research in economics and psychology attempting to identify ingredients that make up successful teams, neuroscientists have only just begun to study how multiple brains interact. Recent research has shown that people's brain activity becomes synchronized with others' (inter-brain synchrony) during social engagement. However, little is known as to whether inter-brain synchrony relates to collective behavior within teams. Here, we merge the nascent field of group neuroscience with the extant literature of team dynamics and collective performance. We recruited 174 participants in groups of 4 and randomly assigned them to complete a series of problem-solving tasks either independently or as a team, while simultaneously recording each person's brain activity using an electroencephalography hyperscanning setup. This design allowed us to examine the relationship between group identification and inter-brain synchrony in explaining collective performance. As expected, teammates identified more strongly with one another, cooperated more on an economic game, and outperformed the average individual on most problem-solving tasks. Crucially, inter-brain synchrony, but not self-reported group identification, predicted collective performance among teams. These results suggest that inter-brain synchrony can be informative in understanding collective performance among teams where self-report measures may fail to capture behavior.

Diet induces parallel changes to the gut microbiota and problem solving performance in a wild bird

The microbial community in the gut is influenced by environmental factors, especially diet, which can moderate host behaviour through the microbiome-gut-brain axis. However, the ecological relevance of microbiome-mediated behavioural plasticity in wild animals is unknown. We presented wild-caught great tits (Parus major) with a problem-solving task and showed that performance was weakly associated with variation in the gut microbiome. We then manipulated the gut microbiome by feeding birds one of two diets that differed in their relative levels of fat, protein and fibre content: an insect diet (low content), or a seed diet (high content). Microbial communities were less diverse among individuals given the insect compared to those on the seed diet. Individuals were less likely to problem-solve after being given the insect diet, and the same microbiota metrics that were altered as a consequence of diet were also those that correlated with variation in problem solving performance. Although the effect on problem-solving behaviour could have been caused by motivational or nutritional differences between our treatments, our results nevertheless raise the possibility that dietary induced changes in the gut microbiota could be an important mechanism underlying individual behavioural plasticity in wild populations.

Evaluating effectiveness of information visualizations using cognitive fit theory: A neuroergonomics approach

Information visualizations may be evaluated from the perspective of how they match tasks that must be performed with them, a cognitive fit perspective. However, there is a gap between the high-level references made to cognitive fit and the low-level ability to identify and measure it during human interaction with visualizations. We bridge this gap by using an electroencephalography metric derived from frontal midline theta power and parietal alpha power, known as the task load index, to determine if cognitive effort measured at the level of cortical activity is less when cognitive fit is present compared to when cognitive fit is not. We found that when there is cognitive fit between the type of problem to be solved and the information displayed by a system, the task load index is lower compared to when cognitive fit is not present. We support this finding with subjective (NASA task load index) and performance (response time and accuracy) measures. Our approach, using electroencephalography, provides supplemental information to self-report and performance measures. Findings from this study are important because they (1) provide more validity to the cognitive fit theory using a neurophysiological measure, and (2) use the electroencephalography task load index metric as a means to assess cognitive workload and effort in general.

The neural bases of argumentative reasoning

Most reasoning tasks used in behavioral and neuroimaging studies are abstract, triggering slow, effortful processes. By contrast, most of everyday life reasoning is fast and effortless, as when we exchange arguments in conversation. Recent behavioral studies have shown that reasoning tasks with the same underlying logic can be solved much more easily if they are embedded in an argumentative context. In the present article, we study the neural bases of this type of everyday, argumentative reasoning. Such reasoning is both a social and a metarepresentational process, suggesting it should share some mechanisms, and thus some neural bases, with other social, metarepresentational process such as pragmatics, metacognition, or theory of mind. To isolate the neural bases of argumentative reasoning, we measured fMRI activity of participants who read the same statement presented either as the conclusion of an argument, or as an assertion. We found that conclusions of arguments, compared to assertions, were associated with greater activity in a region of the medial prefrontal cortex that was identified in quantitative meta-analyses of studies on theory of mind. This study shows that it is possible to use more ecologically valid tasks to study the neural bases of reasoning, and that using such tasks might point to different neural bases than those observed with the more abstract and artificial tasks typically used in the neuroscience of reasoning. Specifically, we speculate that reasoning in an argumentative context might rely on mechanisms supporting metarepresentational processes in the medial prefrontal cortex.

Problem-solving in technology-rich environments and cancer screening in later life

Routine cancer screening is widely recognized as an effective preventive strategy to reduce cancer mortality - the second leading cause of death in the US. However, cancer screening requires a complex array of tasks such as seeking up-to-date guidelines, making appointments, planning hospital visits, and communicating with health care professionals. Importantly, modern health care largely relies on technology to disseminate the latest information and administer the system. Yet, little is known about the technology-related skills that are relevant to regular cancer screening. This study examined the association between problem-solving skills in the technology-rich environment and cancer screening in later life. Using 2012/2014 Program for International Assessment of Adult Competencies data, binary logistic regressions with survey weights were used to estimate the association between problem-solving skills in the technology-rich environment and four cancer screening behaviors among the corresponding target populations aged between 45 and 74 years old (n = 1374 for cervical screening; n = 1373 for breast screening; n = 1166 for prostate screening; n = 2563 for colon screening). Results showed that greater problem-solving skills in the technology-rich environment scores (0-500 points) were significantly and positively associated with prostate cancer screening (odds ratio = 1.005, P < 0.05) among men, but not with colon (men and women) or cervical or breast (women) cancer screenings. Improvement in problem-solving skills in the technology-rich environment may promote specific cancer screening behaviors. Our findings inform future policy discussions and interventions that seek to improve cancer screening among a vulnerable section of older populations.