Oscillatory EEG Correlates of Arithmetic Strategies: A Training Study

Abstract

There has been a long tradition of research on mathematics education showing that children and adults use different strategies to solve arithmetic problems. Neurophysiological studies have recently begun to investigate the brain correlates of these strategies. The existing body of data, however, reflect static end points of the learning process and do not provide information on how brain activity changes in response to training or intervention. In this study, we explicitly address this issue by training participants in using fact retrieval strategies. We also investigate whether brain activity related to arithmetic fact learning is domain-specific or whether this generalizes to other learning materials, such as the solution of figural-spatial problems. Twenty adult students were trained on sets of two-digit multiplication problems and figural-spatial problems. After the training, they were presented with the trained and untrained problems while their brain activity was recorded by means of electroencephalography (EEG). In both problem types, the training resulted in accuracies over 90% and significant decreases in solution times. Analyses of the oscillatory EEG data also revealed training effects across both problem types. Specifically, we observed training-related activity increases in the theta band (3–6 Hz) and decreases in the lower alpha band (8–10 Hz), especially over parietooccipital and parietal brain regions. These results provide the first evidence that a short-term fact retrieval training results in significant changes in oscillatory EEG activity. These findings further corroborate the role of the theta band in the retrieval of semantic information from memory and suggest that theta activity is sensitive to fact retrieval not only in mental arithmetic but also in other domains.

Language-dependent knowledge acquisition: investigating bilingual arithmetic learning

“…Overlearned problems are commonly retrieved from memory as facts, while new or large problems are indicated as solveable by the use of procedural strategies. Different strategies have also been found to be accompanied by specific neural correlates in fMRI as well as EEG (e.g., Dehaene, Piazza, Pinel & Cohen, 2003; Jost, Beinhoff, Hennighausen & Rösler, 2004; Núñez-Peña, Cortiñas & Escera, 2006; De Smedt, Grabner & Studer, 2009; Grabner & De Smedt, 2012). Thus, future research should employ strategy reports to further study the cognitive mechanisms underlying LSC.…”

“…Three different arithmetic tasks were included as experimental stimuli, comprising a) six multiplication problems: two-digit times one-digit numbers with two-digit solutions (00 x 0 = 00); b) six subtraction problems: two-digit minus two-digit numbers, including only carry-over calculations with two-digit solutions (00 - 00 = 00); and c) six artificial problems: two-digit and one-digit numbers connected via an arbitrary symbol (box) with two-digit solutions (00 box 0 = 00). The multiplication and subtraction problems resembled those used in previous arithmetic training studies (Delazer, Domahs, Bartha, Brenneis, Lochy, Trieb & Benke, 2003; Ischebeck et al, 2006; Grabner & De Smedt, 2012; Saalbach et al, 2013). The first operand ranged from 14 to 17, and the second operand ranged from 3 to 7, keeping two-digit outcomes, and excluding solutions divisible by 5 or 10.…”

Specific Cognitive Predictors of Early Math Problem Solving

“…Additionally, the intraparietal sulcus is key for numerical representation (Nieder & Dehaene, ), and injury to this region can result in compromised processing (Ashkenazi, Henik, Ifergane, & Shelef, ). Together, there is strong evidence for linking specific brain regions to cognitive functions that are related to math learning (Grabner & De Smedt, ).…”

Untitled

“…Neuroeducation has been informative on crucial aspects of learning not tractable using traditional approaches in education. Notably, this field has shed new light on aspects of learning to read (Hruby, Goswami, Frederiksen, & Perfetti, 2011) and mathematics (Grabner & De Smedt, 2012). However, so far, the nature of these findings makes it difficult to translate them into prescriptions for educational practice (Hruby, 2012).…”