QEEG coherence patterns related to mathematics ability in children. Issue 3 (3rd July 2022)

• Record Type: Journal Article
• Authors: Anzalone, Christopher; Luedke, Jessica C.; Green, Jessica J.; Decker, Scott L.
• Is Part Of: Applied neuropsychology. Volume 11:Issue 3(2022)
• Page Start: 328
• Page End: 338
• Publication Date: 2022-07-03
• Subjects: Assessment -- EEG -- learning disability -- mathematics -- QEEG; Pediatric neuropsychology -- Periodicals; Neuropsychology -- Periodicals; Brain -- Physiology -- Periodicals; Brain -- Imaging -- Periodicals; Nervous system -- Diseases -- Diagnosis -- Periodicals; Nervous system -- Diseases -- Treatment -- Periodicals; 618.928
• DOI: 10.1080/21622965.2020.1830403
• Languages: English
• ISSNs: 2162-2965

Abstract

Abstract: The current study investigates the utility of resting-state EEG coherence values in predicting standardized math scores in children. Quantitative EEG and standardized academic achievement analyses were performed on 60 school-aged children. Analyses assessing intrahemispheric coherence at rest were conducted across the sample of participants and several coherence networks were extracted and compared to standardized math achievement values. Specifically, networks that included Brodmann area 40 (a brain region involved in the cognitive processes responsible for mathematics performance) and whose coherence values were significantly correlated with standardized math scores were examined. Results indicate a total of four coherence networks, two in each hemisphere, that have utility in predicting general math skills in children. In addition to BA 40, these coherence networks include BAs in the right temporal lobe, right frontoparietal lobe, left superior temporal lobe, and the left medial prefrontal cortex. These findings address the current dearth of research on the neurological connectivity patterns that are foundational for mathematics abilities in children. Further, these results lay a foundation for the supplementary use of EEG in the assessment and identification practices surrounding math learning disabilities in children and additionally provide a neurocognitive framework upon which intervention research may be targeted.