Intergenerational Transmission of Functional Connectivity Profiles in Isolated Reading and Math Networks: A Scoping Review and Study Proposal

The scoping review surveyed the existing literature on the topic of resting-state functional connectivity (rsFC) and mathematical cognition. The review revealed that rsFC is indicative of distinct long-term developmental trends in mathematical processing, alluding to individual differences in math abilities. Though there have been multiple studies that investigate individual differences in functional connectivity patterns related to math development and math learning disorders, no study has directly investigated to what degree these neurobiological factors are heritable. To address this topic, the following intergenerational transmission (IT) study is proposed. IT is the transfer of personal values, abilities, behaviours, and traits, from parents to children (Durlauf & Blume, 2016). A recent study conducted by Takagi et al. (2021) investigated the effects of IT via neurobiological substrates. The investigation was primarily concerned with whether identification of a parent-child dyad was possible based on brain similarity, using both structural and functional information. Using a similar method as Takagi et al., we plan to use data from the Parents and Children: Measuring Academic skills using Neuroimaging (PACMAN) project to investigate whether parent-child dyads are identifiable based on brain similarity - specifically using the reading- and math-related networks. Similar to the Takagi et al. (2021) study, we predict that parent-child dyads will be identifiable based on functional connectivity profiles localized in reading- and math-related brain networks

Task Features Change the Relation Between Math Anxiety and Number Line Estimation Performance With Rational Numbers: Two Large-Scale Online Studies

Math performance is negatively related to math anxiety (MA), though MA may impact certain math skills more than others.We investigated whether the relation between MA and math performance is affected by task features, such as number type (e.g., fractions, whole numbers, percentages), number format (symbolic vs. nonsymbolic), and ratio component size (small vs. large). Across two large-scale studies (combined n = 3,822), the MA-performance relation was strongest for large whole numbers and fractions, and stronger for symbolic than nonsymbolic fractions. The MA-performance relation was also stronger for smaller relative to larger components, and MA relating to specific number types may be a better predictor of performance than general MA for certain tasks. The relation between MA and estimation performance changes depending on task features, which suggests that MA may relate to certain math skills more than others, which may have implications for how people reason with numerical information and may inform future interventions

Numeracy and COVID-19: Examining interrelationships between numeracy, health numeracy and behaviour

During the COVID-19 pandemic, people across the globe have been exposed to large amounts of statistical data. Previous studies have shown that individuals mathematical understanding of health-related information affects their attitudes and behaviours. Here, we investigate the relation between (i) basic numeracy, (ii) COVID-19 health numeracy, and (iii) COVID-19 health-related attitudes and behaviours. An online survey measuring these three variables was distributed in Canada, the United States (US) and the United Kingdom (UK) (n = 2032). In line with predictions, basic numeracy was positively related to COVID-19 health numeracy. However, predictions, neither basic numeracy nor COVID-19 health numeracy was related to COVID-19 healthrelated attitudes and behaviours (e.g. follow experts recommendations on social distancing, wearing masks etc.). Multi-group analysis was used to investigate mean differences and differences in the strength of the correlation across countries. Results indicate there were no between-country differences in the correlations between the main constructs but there were between-country differences in latent means. Overall, results suggest that while basic numeracy is related to one s understanding of data about COVID-19, better numeracy alone is not enough to influence a population s health-related attitudes about disease severity and to increase the likelihood of following public health advice

Numeracy and COVID-19: examining interrelationships between numeracy, health numeracy and behaviour

During the COVID-19 pandemic, people across the globe have been exposed to large amounts of statistical data. Previous studies have shown that individuals' mathematical understanding of health-related information affects their attitudes and behaviours. Here, we investigate the relation between (i) basic numeracy, (ii) COVID-19 health numeracy, and (iii) COVID-19 health-related attitudes and behaviours. An online survey measuring these three variables was distributed in Canada, the United States (US) and the United Kingdom (UK) (n = 2032). In line with predictions, basic numeracy was positively related to COVID-19 health numeracy. However, predictions, neither basic numeracy nor COVID-19 health numeracy was related to COVID-19 health-related attitudes and behaviours (e.g. follow experts’ recommendations on social distancing, wearing masks etc.). Multi-group analysis was used to investigate mean differences and differences in the strength of the correlation across countries. Results indicate there were no between-country differences in the correlations between the main constructs but there were between-country differences in latent means. Overall, results suggest that while basic numeracy is related to one's understanding of data about COVID-19, better numeracy alone is not enough to influence a population's health-related attitudes about disease severity and to increase the likelihood of following public health advice

Open Science Workshop

In this project, you can find open science resources and the presentation of our workshop at MCLS (Ottawa, 2019

Challenging the neurobiological link between number sense and symbolic numerical abilities

A significant body of research links individual differences in symbolic numerical abilities, such as arithmetic, to number sense, the neurobiological system used to approximate and manipulate quantities without language or symbols. However, recent findings from cognitive neuroscience challenge this influential theory. Our current review presents an overview of evidence for the number sense account of symbolic numerical abilities and then reviews recent studies that challenge this account, organized around the following four assertions. (1) There is no number sense as traditionally conceived. (2) Neural substrates of number sense are more widely distributed than common consensus asserts, complicating the neurobiological evidence linking number sense to numerical abilities. (3) The most common measures of number sense are confounded by other cognitive demands, which drive key correlations. (4) Number sense and symbolic number systems (Arabic digits, number words, and so on) rely on distinct neural mechanisms and follow independent developmental trajectories. The review follows each assertion with comments on future directions that may bring resolution to these issues

Predicting children’s math skills from task-based and resting-state functional brain connectivity

A critical goal of cognitive neuroscience is to predict behavior from neural structure and function, thereby providing crucial insight into who might benefit from clinical and/or educational interventions. Across development, the strength of functional connectivity among a distributed set of brain regions is associated with children’s math skills. Therefore, in the present study we use Connectome-based Predictive Modeling to investigate whether functional connectivity during numerical processing and at rest predicts children’s math skills (N = 31, Mage = 9.21 years, 14 Female). Overall, we found that functional connectivity during symbolic number comparison and rest, but not during non-symbolic number comparison, predicts children’s math skills. Each task revealed a largely distinct set of predictive connections distributed across canonical brain networks and major brain lobes. Most of these predictive connections were negatively correlated with children’s math skills, such that weaker connectivity predicted better math skills. Notably, these predictive connections were largely non-overlapping across task states, suggesting children’s math abilities may depend on state-dependent patterns of network segregation and/or regional specialization. Furthermore, the current predictive modeling approach moves beyond brain- behavior correlations and toward building models of brain connectivity that may eventually aid in predicting future math skills