Document Type : Original Research


1 Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran

2 Department of Neuroimaging and Analysis, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran

3 Department of Medical Physics, School of Medicine, Fasa University of Medical Sciences, Fasa, Iran

4 Department of Psychiatry, Brain & Spinal Cord Injury Research Center, Psychosomatic Medicine Research Center, Tehran University of Medical Sciences, Tehran, Iran

5 Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, Oxford, UK/Statistics Department, University of Oxford, Oxford, UK


Background: Psychogenic non-epileptic seizures (PNES), is a type of seizure that is caused by emotional factors. Symptoms of PNES are similar to epileptic seizures including disturbance in involuntary movement. Previous studies showed that neural activity altered in PNES detected through the resting-state functional magnetic resonance imaging (rs-fMRI) thus this study was designed for a better understanding of PNES pathophysiology using the rs-fMRI technique.
Objective: This study was conducted to examine dynamic functional connectivity (dFC) in the brain networks between PNES and healthy control subjects.
Material and Methods: In this experimental study, the rs-fMRI was collected from 16 PNES subjects and 16 healthy subjects. After surrogating data, the sliding window technique was used for dFC detection in nine brain networks which chosen from Stanford Findlab.
Results: Our results indicate that there were no differences in the presence or absence of dFC between the PNES group and the control group in the ventral default mode network (vDMN), language network (LN), and visuospatial network (VSN). However, dFC was elevated in the PNES group in comparison to the normal control group within the sensorimotor network (SMN), Posterior salience network (PSN), and anterior salience network (ASN). 
Conclusion: The findings suggest that dFC analyses hold significant potential for uncovering abnormal patterns of brain network connections in the PNES. This offers a promising finding for a better comprehension of PNES.