Date of Award

Fall 2019

Document Type

Open Access Thesis



First Advisor

Scott Decker


The current study investigated the prognostic utility of resting state EEG coherence in the prediction of standardized mathematics scores. Quantitative EEG analyses were performed for 60 school-aged children (ages 7 to 12 years) with and without math learning disabilities (MLD). Analyses assessing intrahemispheric coherence at rest were performed across the entire sample and several coherence networks were extracted.

Specifically, networks that included Brodmann area 40 (BA 40) -- a region of the brain heavily involved in the cognitive processes responsible for mathematics performance (Anderson, Betts, Ferris, & Fincham, 2011; Cohen, Dehaene, Chochon, Lehericy, & Naccache, 2000; Kroger, Nystrom, Cohen, & Johnson-Laird, 2008) -- and whose coherence was significantly correlated with standardized math scores were examined. Results indicated that there was a total of four coherence networks, two in each hemisphere, that had prognostic utility for math ability. These networks included coherence in multiple frequency bands between BA 40 and several other brain regions (left frontotemporal cortex in delta, left occipitotemporal cortex in theta, whole right hemisphere in alpha, and right medial prefrontal cortex in theta). These findings address a relatively large void in the research literature as there are few studies investigating the neurological foundations of mathematics in children. Further, these results lend credence for the supplementary use of EEG for identifying specific learning disabilities in addition to providing a basis for which interventions can be targeted toward.