Cognitive components of a mathematical processing network in 9‐year‐old children

Abstract

We determined how various cognitive abilities, including several measures of a proposed domain-specific number sense, relate to mathematical competence in nearly 100 9-year-old children with normal reading skill. Results are consistent with an extended number processing network and suggest that important processing nodes of this network are phonological processing, verbal knowledge, visuo-spatial short-term and working memory, spatial ability and general executive functioning. The model was highly specific to predicting arithmetic performance. There were no strong relations between mathematical achievement and verbal short-term and working memory, sustained attention, response inhibition, finger knowledge and symbolic number comparison performance. Non-verbal intelligence measures were also non-significant predictors when added to our model. Number sense variables were non-significant predictors in the model and they were also non-significant predictors when entered into regression analysis with only a single visuo-spatial WM measure. Number sense variables were predicted by sustained attention. Results support a network theory of mathematical competence in primary school children and falsify the importance of a proposed modular ‘number sense’. We suggest an ‘executive memory function centric’ model of mathematical processing. Mapping a complex processing network requires that studies consider the complex predictor space of mathematics rather than just focusing on a single or a few explanatory factors.

Multiple skills underlie arithmetic performance: A large-scale structural equation modeling analysis

“…Studies investigating the role of sustained attention in explaining individual differences in mathematics abilities is inconsistent, some studies demonstrated a relationship (Ashkenazi, Golan, & Silverman, 2014;Steele, Karmiloff-Smith, Cornish, & Scerif, 2012), while others have not (Szűcs et al, 2014). Steele et al (2012) examined the explanatory role of attention for literacy and numeracy among 6-year-old children over the course of a year.…”

“…Moreover, there is evidence that these cognitive skills affect individual differences in arithmetic abilities across the spectrum of mathematics proficiency. Szűcs, Devine, Soltesz, Nobes, and Gabriel (2014) demonstrated that individual differences in arithmetic abilities was predicted by phonological processing, verbal knowledge, visuospatial short-term and working memory, spatial ability and executive functioning. …”

Mechanisms of interactive specialization and emergence of functional brain circuits supporting cognitive development in children

“…35 In addition, frontal systems anchored in the insula, dorsolateral and ventrolateral prefrontal cortex (PFC) support working memory and other cognitive control functions important for effortful problem solving. 26,36 Cross-sectional studies have suggested that IPS and VTOC activity increase with age, while PFC activity decreases with age, reflecting decreasing demands on the working memory system accompanied by increasing utilization of mature problem solving abilities. [37][38][39] However, how interactions between these systems change over the course of development and which factors drive these changes are currently unknown.…”

Magnitude Processing in Developmental Dyscalculia : A Heterogeneous Learning Disability with Different Cognitive Profiles

“…Semantic long-term memory (Geary, 1993) and working memory (e.g., Bull, Espy, & Wiebe, 2008;Swanson & Beebe-Frankenberger, 2004;Szücs, Devine, Soltesz, Nobes, & Gabriel, 2014) are crucial during mathematical reasoning (Meyer et al, 2010). Baddeley and Hitch (1974) formulated the now widely accepted working memory model that comprises three main components.…”

“…Although the conceptualization of the central executive is debated, one way of assessing it is by administrating tasks requiring participants to shift between tasks while inhibiting distracting elements. Performance on this type of task has proved to be a strong predictor of mathematical achievement (Szücs et al, 2014). Meyer and colleagues (2010) argue that executive attention is especially important during the early stages of mathematics learning prior to neurocognitive maturation, after which mathematical procedures and knowledge becomes more automatized and reliant upon areas in the parietal cortex.…”