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Abstract

Children with learning disorders (LD) perform below average in tests of academic abilities and intelligence. These children also have a significantly abnormal resting-state electroencephalogram (EEG) compared to children with typical development (TD), i.e., an excess of slow brain oscillations such as delta and theta that may be markers of inefficient cognitive processing. We aimed to explore the relationship between the performance in an intelligence test and the resting-state EEG power spectrum of children with LD. Ninety-one children with LD and 45 control children with TD were evaluated with the Wechsler Intelligence Scale for Children 4th Edition (WISC-IV) test of intelligence and a 19-channel EEG during an eyes-closed resting-state condition. The EEG dimensionality was reduced with a principal component analysis that yielded several components representing EEG bands with functional meaning. The first seven EEG components and the intelligence values were analyzed with multiple linear regression and a between-group discriminant analysis. The EEG power spectrum was significantly related to children’s intelligence, predicting 13.1% of the IQ variance. Generalized delta and theta power were inversely related to IQ, whereas frontoparietal gamma activity was directly related. The intelligence test and the resting state EEG had a combined 82.4% success rate to discriminate between children with TD and those with LDs.

Details

1009240
Company / organization
Title
Electroencephalographic power spectrum patterns related to the intelligence of children with learning disorders
Publication title
PeerJ; San Diego
Publication year
2025
Publication date
Mar 26, 2025
Publisher
PeerJ, Inc.
Place of publication
San Diego
Country of publication
United States
Publication subject
e-ISSN
21678359
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
ProQuest document ID
3239365259
Document URL
https://www.proquest.com/scholarly-journals/electroencephalographic-power-spectrum-patterns/docview/3239365259/se-2?accountid=208611
Copyright
© 2025 Martínez-Briones et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-09-30
Database
ProQuest One Academic