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Jessica Luedke, Scott L Decker, A-31 Distinguishing Neuro-Markers of Math Learning Disability Using EEG Coherence, Archives of Clinical Neuropsychology, Volume 36, Issue 6, September 2021, Page 1072, https://doi.org/10.1093/arclin/acab062.49
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Abstract
The current study evaluated brain connectivity in math learning disability (MLD) by examining intra- and interhemispheric electroencephalography (EEG) coherence in three groups of children with differing math profiles. Differential patterns of connectivity were evaluated during “at-rest” conditions and statistically evaluated across three groups.
Testing occurred in a university laboratory setting. Participants were recruited through media and local agencies serving children with disabilities. The Woodcock Johnson cognitive and achievement tests were used to determine general intelligence and skills across all math achievement subtests. Additionally, 3-minute eye-closed EEG resting data was collected. Groups used in the current study were: neurotypical controls (NC) (n = 30), math learning disability (MLD) (n = 15), and lower achievement (LA) (n = 15). Participants’ mean age was 9.58 (SD = 1.38) with 53.3% being male.
Intrahemispheric comparisons suggest MLD children demonstrated reduced left hemispheric coherence to NC’s (p = 0.006), not seen in LA children. Additionally, NC’s had greater beta coherence (p = 0.002). Interhemispheric analyses revealed the MLD group had reduced alpha occipital coherence compared to the LA group (p = 0.031).
The current study provides supporting evidence for implicating brain connectivity as an underlying cause of MLD. Specifically, left hemispheric differences in delta coherence were found in children with MLD not observed in children with LA profiles. Weaknesses in areas of visuo-spatial integration in the MLD group were also observed. Results suggest atypical patterns of brain connectivity in the default-mode network (DMN) in delta wavelengths may serve as a useful biomarker of MLD.
