Evaluating the Effect of Quran Memorizing on the Event‑related Potential Features by Using Graphs Created from the Neural Gas Networks
عنوان مقاله: Evaluating the Effect of Quran Memorizing on the Event‑related Potential Features by Using Graphs Created from the Neural Gas Networks
شناسه ملی مقاله: JR_JMSI-12-1_006
منتشر شده در در سال 1401
شناسه ملی مقاله: JR_JMSI-12-1_006
منتشر شده در در سال 1401
مشخصات نویسندگان مقاله:
Hadi Akbari - Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University,Tehran,Iran
Ali Sheikhani - Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University,Tehran,Iran
Ali Motie Nasrabadi - Department of Biomedical Engineering, Shahed University, Tehran, Iran
Mohammad Reza Mohammadi - Department of Child and Adolescent Psychiatry, Psychiatry and Psychology Center, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran
خلاصه مقاله:
Hadi Akbari - Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University,Tehran,Iran
Ali Sheikhani - Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University,Tehran,Iran
Ali Motie Nasrabadi - Department of Biomedical Engineering, Shahed University, Tehran, Iran
Mohammad Reza Mohammadi - Department of Child and Adolescent Psychiatry, Psychiatry and Psychology Center, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran
Background: Quran memorizing causes a state of trance, which its result is the changes in the amplitude
and time of P۳۰۰ and N۲۰۰ components in the event related potential (ERP) signal. Nevertheless, a
limited number of studies that have examined the effects of Quran memorizing on brain signals to
enhance relaxation and attention, and improve the lives of patients with autism and stroke, generally have
not presented any analysis based on comparing structural differences relevant to features extracted from
ERP signal obtained from the two groups of Quran memorizer and nonmemorizer by using the hybrid
of graph theory and competitive networks.Methods: In this study, we investigated structural differences
relevant to the graph obtained from the weight of neural gas (NG) and growing NG (GNG) networks
trained by features extracted from the ERP signal recorded from two groups during the PRM test. In this
analysis, we actually estimated the ERP signal by averaging the brain background data in the recovery
phase. Then, we extracted six features related to the power and the complexity of these signals and selected
optimal channels in each of the features by using the t test analysis. Then, these features extracted from the
optimal channels are applied for developing the NG and GNG networks. Finally, we evaluated different
parameters calculated from graphs, in which their connection matrix was obtained from the weight
matrix of the networks.Results:. The outcomes of this analysis show that increasing the power of low
frequency components and the power ratio of low frequency components to high frequency components
in the memorizers, which represents patience, concentration, and relaxation, is more than that of the
nonmemorizers. These outcomes also show that the optimal channels in different features, which were
often in frontal, peritoneal, and occipital regions, had a significant difference (P < ۰.۰۵). It is remarkable
that two parameters of the graphs established based on two competitive networks, i.e. average path length
and the average of the weights in the memorizers, were larger than the nonmemorizers, which means more
data scattering in this group.Conclusion: This condition in the mentioned graphs suggests that the Quran
memorizing causes a significant change in ERP signals, so that its features have usually more scattering.
کلمات کلیدی: Event‑related potential signal, neural gas and growing neural gas networks, Quran memorizer and nonmemorizer, visual memory
صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1700805/