Dataset on the EEG time-frequency representation in children with different levels of mathematical achievement.

ABSTRACT: This article presents the data related to the research paper entitled "The analysis of EEG coherence reflects middle childhood differences in mathematical achievement" (González-Garrido et al., 2018). The dataset is derived from the electroencephalographic (EEG) records registered from a total of 60 8-9-years-old children with different math skill levels (High: HA, Average: AA, and Low Achievement: LA) while performing a symbolic magnitude comparison task. The average brain patterns are shown through Time-Frequency Representations (TFR) for each group, and also grand-mean amplitudes within specific EEG epochs in a 19-electrode array are provided. Making this information publicly available for further analyses could significantly contribute to a better understanding on how math achievement

SUBMITTER: Gonzalez-Garrido AA 

PROVIDER: S-EPMC6226595 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature