Nonlinear Analysis of Electroencephalogram in Writing-Disabled Children for a Better Understanding of Brain Functions

• Main Authors: Mahboubeh Parastar-Feizabadi, Mohammadreza Yazdchi, Majid Ghoshuni, Peyman Hashemian
• Format: Article
• Language: fas
• Published: Vesnu Publications 2014-06-01
• Series: مجله دانشکده پزشکی اصفهان
• Subjects: Electroencephalography; Entropy; Power spectral density; Learning disability; Writing and rest condition
• Online Access: http://jims.mui.ac.ir/index.php/jims/article/view/2579
• ISSN: 1027-7595; 1735-854X

Background: Electroencephalogram (EEG) shows the electrical activity of the brain and is one of the most important diagnostic tools for neurological diseases and disabilities. Dysgraphia is one of the most common learning disabilities occurs regardless of the ability to read and is not due to intellectual impairments. Nonlinear methods are used in recent studies to access the electroencephalogram in children with dysgraphia. Methods: In this study, nonlinear analysis of electroencephalogram in writing-disabled children for a better understanding of brain functions was done. The Renyi entropy estimation and Welch power spectrum estimation methods were used. Findings: Writing-disabled children's brains were more complex at the time of writing than the rest condition as a result of more erratic behavior and thus, more asynchronous activation of neurons in the central brain zone. There was a higher proportion of Theta/Beta and Theta/Alpha in writing mood showed more brain insufficiency in writing compared to the rest condition. Conclusion: Neurofeedback, as a new approach in the treatment of learning disabilities, is proposed to modify the electrical activity of the brain in writing-disabled children.