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Year : 2020  |  Volume : 41  |  Issue : 1  |  Page : 7-13

Brain electrical activity mapping in the diagnosis of attention-deficit hyperactivity disorder

1 Department of Neuropsychiatry, Faculty of Medicine, Alexandria University, Alexandria, Egypt
2 Department of Pediatrics, Faculty of Medicine, Alexandria University, Alexandria, Egypt

Correspondence Address:
MD Osama A Elmagd Elkholy
Amin Fekry Street, Alexandria, Postal Code (002/03)
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/ejpsy.ejpsy_18_19

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Background Attention-deficit/hyperactivity disorder (ADHD) is the most common neurodevelopmental disorder of childhood. It affects approximately 4% of all children, although estimates vary widely from 3% to 11% or more. Neuroimaging and neurophysiological tests have been increasingly used to understand the relation between brain functionality and ADHD symptoms. QEEG provides a method that can measure the neurophysiological mechanisms underlying neurodevelopmental disorders. By using spectral analysis is able to find abnormalities of brain functionality and connectivity linked to abnormal ADHD behaviors. The objective of the current work was to study and compare the efficacy & accuracy of QEEG for diagnosis of ADHD children, to assess the spectral characteristic of QEEG findings within cases of ADHD, to detect the presence of specific EEG findings that might help in diagnosis. Methodology The current study was conducted on 60 school aged children range from 6-15 years (60 ADHD children matching DSM-5 criteria) and 20 typically developing children. All cases were subjected to thorough history taking and clinical examination with special attention to neurological examination. Both cases and controls were subjected to QEEG analysis and interpretation. All studied children had undergone assessment with Arabic form of Conners’ Parent Rating Scale short form, IQ test, Arabic version of DSM-5. The present study revealed that: Increased levels of slow waves (predominantly theta) , decreased levels of relative Beta LF activity, and increased levels of Theta/Beta LF ratio, in QEEG of ADHD when compared to QEEGs of normal controls. The present study revealed significant differences between ADHD cases & control at all regions of brain; according to average amplitude of power spectrum of all bands (Theta, Beta LF&HF) and Theta/Beta LF ratio. From this study we concluded that children with ADHD have QEEG dysfunctions that underlie their symptomatology. QEEG average of power spectral analysis (theta, beta LF and theta/beta LF ratio) can differentiate between ADHD cases (abnormal power) & normal population (normal power).

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