Cognitive heterogeneity of math difficulties: A bottom-up classification approach

Abstract

Math learning difficulties (MD) correspond to math achievement below the 25th percentile and are cognitively heterogeneous. It is not known precisely how cognitive mechanisms underlie distinct subtypes of MD. A bottom-up, cluster-analytic strategy, based on visuoconstructional, visuospatial and phonological working memory, and non-symbolic and symbolic magnitude processing accuracy, was used to form subgroups of children from 3rd to 5th grades according to their math achievement. All children had nonverbal intelligence above the 20th percentile and presented a broad spectrum of variation in math ability. External validity of subgroups was examined considering intelligence and math achievement. Groups did not differ in age. Two groups with a high incidence of MD were associated, respectively, with low visuospatial/visuoconstructional and low magnitude processing accuracy. One group with average cognitive performance also presented above average intelligence and a small incidence of MD. A fourth group with high cognitive performance presented high math performance and high intelligence. Phonological working memory was associated with high but not with low math achievement. MD may be related to complex patterns of associations and dissociations between intelligence and specific cognitive abilities in distinct subgroups. Consistency and stability of these subgroups must be further characterized. However, a bottom-up classification strategy contributes to reducing the cognitive complexity of MD.

Are Different Types of Learning Disorder Associated With Distinct Cognitive Functioning Profiles?

“…Thirdly, although we included a wide range of measures prominent in current LD research, our selection of cognitive skills entered in the LPA was still limited. Especially the inclusion of additional domain-specific measures in the mathematical domain such as magnitude comparison and basic number processing rather than only visual-spatial short-term memory would be worthy to consider in future studies as those skills have not only been found to contribute largely to mathematical skill development in general (e.g., Lonnemann et al, 2011 ), but also to differentiate between children with and without MD in previous person-centered approaches (e.g., de Souza Salvador et al, 2019 ). For instance, it seems reasonable to assume that profile 4 (single attention deficit and at risk of visual-spatial short-term memory), which was after all to 40% made up of children with MD-only, may show additional at-risk performance (or even deficits) in these domain-specific skills relevant in mathematics.…”

“…In the domain of mathematics, the second study by de Souza Salvador et al ( 2019 ) used a clustering approach based on measures of magnitude comparison, visual-spatial working memory, and verbal working memory to identify distinct cognitive subgroups among 192 typical achievers and 150 children with MD. In addition to two profiles without any cognitive deficits, two low achieving profiles were identified, consisting of children with low visuospatial abilities and with poor magnitude processing, respectively.…”

Reading and writing words and numbers: Similarities, differences, and implications

“…Importantly, the significant role of WM for number transcoding may reflect one of the underlying factors associated with specific learning difficulties in the domains of both mathematics (Salvador et al, 2019) and reading (Peterson & Pennington, 2015). These respective developmental disabilities frequently cooccur and, in the next sections, we discuss hypotheses put forward to explain this high comorbidity.…”

Dysfunctions associated with the intraparietal sulcus and a distributed network in individuals with math learning difficulties: An ALE meta‐analysis

“…This ability is also shown to be anchored in the IPS in the lateral parietal lobe (Dehaene et al, 2003 ; Piazza et al, 2004 ; Price et al, 2013 , 2016 ; Rosenberg‐Lee et al, 2011 ; Schel & Klingberg, 2016 ). In comparison, individuals with MLD have been shown to suffer from impairments in processing symbolic quantity information and maybe also in nonsymbolic quantity information (Lyons & Ansari, 2015 ; Reigosa‐Crespo et al, 2012 ; Salvador et al, 2019 ; Schwenk et al, 2017 ; Wong & Chan, 2019 ). Moreover, neuroimaging studies have revealed that MLD is indeed associated with brain dysfunction or atypical structures in the IPS (Ashkenazi et al, 2012 ; Isaacs et al, 2001 ; Jolles et al, 2016 ; Mussolin et al, 2010 ; Price et al, 2007 ; Rotzer et al, 2008 ).…”

“…This ability is also shown to be anchored in the IPS in the lateral parietal lobe (Dehaene et al, 2003;Piazza et al, 2004;Price et al, 2013Price et al, , 2016Rosenberg-Lee et al, 2011;Schel & Klingberg, 2016). In comparison, individuals with MLD have been shown to suffer from impairments in processing symbolic quantity information and maybe also in nonsymbolic quantity information (Lyons & Ansari, 2015;Reigosa-Crespo et al, 2012;Salvador et al, 2019;Schwenk et al, 2017;Wong & Chan, 2019).…”