Investigating the Effectiveness of LORETA Z-score Neurofeedback on Modulating the Default Mode Network Activity in Adult ADHD Patients

Background and Aim: Patients with attention deficit hyperactivity disorder (ADHD) have deficits in cool executive functions such as sustained attention and working memory. Functional magnetic resonance imaging (fMRI) studies have identified the default mode network (DMN) as one of the networks involved in attention control. There is compelling evidence that the hyperactivity of DMN during the tasks that require attention disrupts the proper activation of attentional networks in ADHD people. Neurofeedback (NFB), a type of EEG operant conditioning, trains self-regulation skills using a computer interface. Traditional models of neurofeedback can only target limited frequency bands in limited brain regions. However, newer neurofeedback technology like LORETA z-score neurofeedback (ZNFB) can train multiple frequency bands in multiple head regions and thus allows for training of neural networks such as DMN. It is theorized that LORETA ZNFB can train deeper sources of the EEG, and better results can be achieved with fewer therapy sessions. Methods: ۱۰ Adults diagnosed with ADD received ۲۰ sessions of LORETA ZNFB. Every session lasts ۳۵ minutes, targeting all regions within The DMN and attentional networks that are impaired based on resting-state EEG of subjects. The resting-state EEG was recorded every five sessions to see if there were changes in brain activity. To determine if these changes were evident on behavioral measures, Subjects also performed an intermediate visual and auditory test (IVA) and an N-back test. Results: This study aims to investigate the efficacy of LORETA ZNFB, targeting and training DMN and attentional networks, on enhancing sustained attention and working memory in the inattentive subtype of ADHD (ADD). Z-scores unify different EEG metrics (e.g., power, coherence, phase) to a single metric. It is hypothesized that by training to move their z scores toward z=۰ (which is normal), the subjects would be able to suppress the activity of DMN and enhance the attentional ones (dorsal and ventral) during the task. Conclusion: The generalized estimating equations (GEE) approach were used in this study to assess the effect of DMN training by using LORETA ZNFB. The results indicated that following LORETA ZNFB treatment, participants exhibited significant improvement in all visual and auditory attention parameters of IVA and N-back sub-scores after ten sessions. Low-Resolution Brain Electromagnetic Tomography analysis also showed significant changes in Frontal, parietal, and temporal regions in all frequency bands after ۲۰ sessions. These results suggested that LORETA ZNFB can be an effective treatment for attention difficulties of ADHD.

کلیدواژه ها:

LORETA Z-score neurofeedback ، ADHD ، default mode network ، EEG