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Volume 22, Issue 1 (1-2024)                   Int J Radiat Res 2024, 22(1): 185-192 | Back to browse issues page

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Vardian M, Oghabian M, Arbabi M, Ebrahimi T. Assessment of altered brain function in patients with psychogenic non-epileptic seizures using resting-state functional MRI. Int J Radiat Res 2024; 22 (1) :185-192
URL: http://ijrr.com/article-1-5253-en.html
Assessment of altered brain function in patients with psychogenic non-epileptic seizures using resting-state functional MRI
M. Vardian , M.A. Oghabian , M. Arbabi , T. Ebrahimi
Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran , vardian.medphys@gmail.com
Abstract:   (1497 Views)
Background: Psychogenic non-epileptic seizure (PNES) is a disease characterized by the alternations in the brain network. The current study aimed to assess the global and local brain network changes in various brain regions for the patients with PNES using functional magnetic resonance imaging (fMRI). Materials and Methods: The resting-state fMRI (rs-fMRI) data of 32 adults (ranged from 22-61 years; mean: 33.1±7.2), including 16 healthy controls and 16 PNES patients, were obtained. Several standard global network parameters, including small-worldness, average clustering coefficient, characteristic path length, and global efficiency, were investigated. Nodal characteristics, such as the degree of centrality (DC), betweenness centrality (BC), nodal efficiency (NF), nodal local efficiency (NLF), nodal clustering coefficient (NCC), and shortest route, were also determined independently for each node (region) to represent local changes in the brain network. The local and global parameters’ values were compared between healthy individuals and PNES patients using Mann-Whitney statistical test. Results: There was no significant difference among the global parameter values obtained from PNES patients and healthy individuals (P˃0.05). However, many local brain network parameters showed statistically significant differences in the functional connectivity networks (P˂0.05), including attentional, sensorimotor, default mode, executive control networks, and subcortical area. Conclusion: Although global brain network parameters calculated from fMRI images were similar between healthy and PNES participants, many local brain network parameters showed statistically significant differences. Our findings support PNES patients' hypoactivity in the regions associated with awareness and motor control as well as their hyperactivity in the areas associated with emotion and motion control.
Keywords: Brain networks, PNES, graph theory, functional connectivity, rs-fMRI.
Full-Text [PDF 1042 kb]   (563 Downloads)    
Type of Study: Original Research | Subject: Radiation Biology
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