Saba Amiri1, Mehdi M Mirbagheri2, Ali A Asadi-Pooya3, Fatemeh Badragheh1, Hamideh Ajam Zibadi4, Mohammad Arbabi5. 1. Medical Physics and Biomedical Engineering Department, Tehran University of Medical Sciences (TUMS), Tehran, Iran. 2. Medical Physics and Biomedical Engineering Department, Tehran University of Medical Sciences (TUMS), Tehran, Iran; Physical Medicine and Rehabilitation Department, Northwestern University, USA. Electronic address: mehdi@northwestern.edu. 3. Epilepsy Research Center, Shiraz University of Medical Sciences, Shiraz, Iran; Jefferson Comprehensive Epilepsy Center, Department of Neurology, Thomas Jefferson University, Philadelphia, Pennsylvania, PA, USA. 4. Department of Psychiatry, Psychosomatic Medicine Research Center, Tehran University of Medical Sciences, Iran. 5. Department of Psychiatry, Brain & Spinal Cord Injury Research Centre, Psychosomatic Medicine Research Center, Tehran University of Medical Sciences, Iran. Electronic address: arbabimo@sina.tums.ac.ir.
Abstract
OBJECTIVE: To determine brain functional connectivity (FC), based on the graph theory, in individuals with psychogenic nonepileptic seizures (PNES), in order to better understand the mechanisms underlying this disease. METHODS: Twenty-three patients with PNES and twenty-five healthy control subjects were examined. Alterations in FC within the whole brain were examined using resting-state functional magnetic resonance imaging (MRI). We calculated measures of the nodal degree, a major feature of the graph theory, for all the cortical and subcortical regions in the brain. Pearson correlation was performed to determine the relationship between nodal degree in abnormal brain regions and patient characteristics. RESULTS: The nodal degrees in the right caudate (CAU), left orbital part of the left inferior frontal gyrus (ORBinf), and right paracentral lobule (PCL) were significantly greater (i.e. hyper-connectivity) in individuals with PNES than in healthy control subjects. On the other hand, a lesser nodal degree (i.e. hypo-connectivity) was detected in several other brain regions including the left and right insula (INS), as well as the right putamen (PUT), and right middle occipital gyrus (MOG). CONCLUSION: Our findings suggest that the FC of several major brain regions can be altered in individuals with PNES. Areas with hypo-connectivity may be involved in emotion processing (e.g., INS) and movement regulation (e.g., PUT), whereas areas with hyper-connectivity may play a role in the inhibition of unwanted movements and cognitive processes (e.g., CAU).
OBJECTIVE: To determine brain functional connectivity (FC), based on the graph theory, in individuals with psychogenic nonepileptic seizures (PNES), in order to better understand the mechanisms underlying this disease. METHODS: Twenty-three patients with PNES and twenty-five healthy control subjects were examined. Alterations in FC within the whole brain were examined using resting-state functional magnetic resonance imaging (MRI). We calculated measures of the nodal degree, a major feature of the graph theory, for all the cortical and subcortical regions in the brain. Pearson correlation was performed to determine the relationship between nodal degree in abnormal brain regions and patient characteristics. RESULTS: The nodal degrees in the right caudate (CAU), left orbital part of the left inferior frontal gyrus (ORBinf), and right paracentral lobule (PCL) were significantly greater (i.e. hyper-connectivity) in individuals with PNES than in healthy control subjects. On the other hand, a lesser nodal degree (i.e. hypo-connectivity) was detected in several other brain regions including the left and right insula (INS), as well as the right putamen (PUT), and right middle occipital gyrus (MOG). CONCLUSION: Our findings suggest that the FC of several major brain regions can be altered in individuals with PNES. Areas with hypo-connectivity may be involved in emotion processing (e.g., INS) and movement regulation (e.g., PUT), whereas areas with hyper-connectivity may play a role in the inhibition of unwanted movements and cognitive processes (e.g., CAU).
Authors: Giuseppe Varone; Wadii Boulila; Michele Lo Giudice; Bilel Benjdira; Nadia Mammone; Cosimo Ieracitano; Kia Dashtipour; Sabrina Neri; Sara Gasparini; Francesco Carlo Morabito; Amir Hussain; Umberto Aguglia Journal: Sensors (Basel) Date: 2021-12-25 Impact factor: 3.576
Authors: David L Perez; Timothy R Nicholson; Ali A Asadi-Pooya; Indrit Bègue; Matthew Butler; Alan J Carson; Anthony S David; Quinton Deeley; Ibai Diez; Mark J Edwards; Alberto J Espay; Jeannette M Gelauff; Mark Hallett; Silvina G Horovitz; Johannes Jungilligens; Richard A A Kanaan; Marina A J Tijssen; Kasia Kozlowska; Kathrin LaFaver; W Curt LaFrance; Sarah C Lidstone; Ramesh S Marapin; Carine W Maurer; Mandana Modirrousta; Antje A T S Reinders; Petr Sojka; Jeffrey P Staab; Jon Stone; Jerzy P Szaflarski; Selma Aybek Journal: Neuroimage Clin Date: 2021-03-11 Impact factor: 4.881