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

Autor: González-Garrido AA; Instituto de Neurociencias, Universidad de Guadalajara, Francisco de Quevedo #180, Col. Arcos Vallarta, 44130 Guadalajara, Jalisco, México.; O.P.D. Hospital Civil de Guadalajara, Coronel Calderón #777, Col. El Retiro, CP. 44280 Guadalajara, Jalisco, México., Gómez-Velázquez FR; Instituto de Neurociencias, Universidad de Guadalajara, Francisco de Quevedo #180, Col. Arcos Vallarta, 44130 Guadalajara, Jalisco, México., Romo-Vázquez R; Departamento de Ciencias Computacionales, CUCEI, Universidad de Guadalajara, México., Vélez-Pérez H; Departamento de Ciencias Computacionales, CUCEI, Universidad de Guadalajara, México., Salido-Ruiz RA; Departamento de Ciencias Computacionales, CUCEI, Universidad de Guadalajara, México., Espinoza-Valdez A; Departamento de Ciencias Computacionales, CUCEI, Universidad de Guadalajara, México., Gallardo-Moreno GB; Instituto de Neurociencias, Universidad de Guadalajara, Francisco de Quevedo #180, Col. Arcos Vallarta, 44130 Guadalajara, Jalisco, México., Ruiz-Stovel VD; Instituto de Neurociencias, Universidad de Guadalajara, Francisco de Quevedo #180, Col. Arcos Vallarta, 44130 Guadalajara, Jalisco, México., Martínez-Ramos A; Departamento de Neurociencias, CUCS, Universidad de Guadalajara, México.
Jazyk: angličtina
Zdroj: Data in brief [Data Brief] 2018 Oct 30; Vol. 21, pp. 1071-1075. Date of Electronic Publication: 2018 Oct 30 (Print Publication: 2018).
DOI: 10.1016/j.dib.2018.10.105
Abstrakt: 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 in children associates with cognitive processing strategies.
Databáze: MEDLINE
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