Literature DB >> 34338564

Neurofeedback Training Protocol Based on Selecting Distinctive Features to Treat or Reduce ADHD Symptoms.

Parham Jalali1, Nasrin Sho'ouri1.   

Abstract

Resent research has shown that electroencephalography (EEG) theta/beta ratio (TBR) in cases with attention deficit hyperactivity disorder (ADHD) has thus far been reported lower than that in healthy individuals. Accordingly, utilizing EEG-TBR as a biomarker to diagnose ADHD has been called into question. Besides, employing known protocol to reduce EEG-TBR in the vertex (Cz) channel to treat ADHD via neurofeedback (NFB) has been doubted. The present study was to propose a new NFB treatment protocol to manage ADHD using EEG signals from 30 healthy controls and 30 children with ADHD through an attention-based task and to calculate relative power in their different frequency bands. Then, the most significant distinguishing features of EEG signals from both groups were determined via a genetic algorithm (GA). The results revealed that EEG-TBR values in children with ADHD were lower compared with those in healthy peers; however, such a difference was not statistically significant. Likewise, inhibiting alpha band activity and enhancing delta one in F7 or T5 channels was proposed as a new NFB treatment protocol for ADHD. No significant increase in EEG-TBR in the Cz channel among children with ADHD casts doubt on the effectiveness of using EEG-TBR inhibitory protocols in the Cz channel. Consequently, it was proposed to apply the new protocol along with reinforced beta-band activity to treat or reduce ADHD symptoms.

Entities:  

Keywords:  ADHD; EEG; genetic algorithm; neurofeedback; power spectral density

Year:  2021        PMID: 34338564     DOI: 10.1177/15500594211033435

Source DB:  PubMed          Journal:  Clin EEG Neurosci        ISSN: 1550-0594            Impact factor:   1.843


  1 in total

1.  Detection of ADHD From EOG Signals Using Approximate Entropy and Petrosain's Fractal Dimension.

Authors:  Nasrin Sho'ouri
Journal:  J Med Signals Sens       Date:  2022-07-26
  1 in total

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