Literature DB >> 2265960

Correlation between EEG spectral parameters and an educational evaluation.

T Harmony1, G Hinojosa, E Marosi, J Becker, M Rodriguez, A Reyes, C Rocha.   

Abstract

EEG spectral parameters were computed in a group of children with different degrees of difficulty in learning to read and write. For statistical analyses, Z-transformed values according to normative age-regression equations were used to control the age effects. Canonical Correlation Analysis between absolute power in different bands and the categories of the educational evaluation (good, regular, poor and very poor) showed that more delta was probably related to a poor evaluation and more alpha in occipital areas to a good one. MONOVA also showed highly significant differences in the absolute power in many leads between children with different evaluations. As children with a poor evaluation very frequently had antecedents of risk factors related to brain damage and were from a low socioeconomic status, and both factors have been shown to affect absolute power, it may be that the differences observed were due to these causes. However, relative power correlated more with the learning problems. Children with minor difficulties, with no antecedents and with good socioeconomic status had more theta in almost all leads than children with a good evaluation and with the same characteristics. Children with a poor, or very poor, evaluation had more delta in left frontal and temporal areas (F3, F7 and T3) which may reflect underlying cerebral dysfunction of these regions directly involved in reading and writing processes.

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Year:  1990        PMID: 2265960     DOI: 10.3109/00207459008986630

Source DB:  PubMed          Journal:  Int J Neurosci        ISSN: 0020-7454            Impact factor:   2.292


  7 in total

1.  Assessing a learning process with functional ANOVA estimators of EEG power spectral densities.

Authors:  David Gutiérrez; Mauricio A Ramírez-Moreno
Journal:  Cogn Neurodyn       Date:  2015-12-01       Impact factor: 5.082

2.  Infants of mothers with higher physiological stress show alterations in brain function.

Authors:  Sonya V Troller-Renfree; Natalie H Brito; Pooja M Desai; Ana G Leon-Santos; Cynthia A Wiltshire; Summer N Motton; Jerrold S Meyer; Joseph Isler; William P Fifer; Kimberly G Noble
Journal:  Dev Sci       Date:  2020-05-13

3.  Electroencephalographic characterization of subgroups of children with learning disorders.

Authors:  Milene Roca-Stappung; Thalía Fernández; Jorge Bosch-Bayard; Thalía Harmony; Josefina Ricardo-Garcell
Journal:  PLoS One       Date:  2017-07-14       Impact factor: 3.240

4.  Influence of neurofeedback in improving the deaf students' reading after cochlear implantation.

Authors:  S Soltani Kouhbanani; R Khosrorad; M Hashemian; M Nasehnezhad
Journal:  J Med Life       Date:  2015

5.  The impact of a poverty reduction intervention on infant brain activity.

Authors:  Sonya V Troller-Renfree; Molly A Costanzo; Greg J Duncan; Katherine Magnuson; Lisa A Gennetian; Hirokazu Yoshikawa; Sarah Halpern-Meekin; Nathan A Fox; Kimberly G Noble
Journal:  Proc Natl Acad Sci U S A       Date:  2022-02-01       Impact factor: 12.779

6.  Stable Sparse Classifiers Identify qEEG Signatures that Predict Learning Disabilities (NOS) Severity.

Authors:  Jorge Bosch-Bayard; Lídice Galán-García; Thalia Fernandez; Rolando B Lirio; Maria L Bringas-Vega; Milene Roca-Stappung; Josefina Ricardo-Garcell; Thalía Harmony; Pedro A Valdes-Sosa
Journal:  Front Neurosci       Date:  2018-01-15       Impact factor: 4.677

7.  Clinical and Electrophysiological Differences between Subjects with Dysphonetic Dyslexia and Non-Specific Reading Delay.

Authors:  Jorge Bosch-Bayard; Valeria Peluso; Lidice Galan; Pedro Valdes Sosa; Giuseppe A Chiarenza
Journal:  Brain Sci       Date:  2018-09-10
  7 in total

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