Lisa Goudman1, Daniele Marinazzo2, Frederik Van de Steen2, Guy Nagels3, Ann De Smedt4, Eva Huysmans5, Koen Putman6, Ronald Buyl7, Kelly Ickmans8, Jo Nijs9, Iris Coppieters9, Maarten Moens10. 1. Department of Neurosurgery, Universitair Ziekenhuis Brussel, Laarbeeklaan 101, Brussels 1090, Belgium; Center for Neurosciences (C4N), Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, Brussels 1090, Belgium. 2. Department of Data Analysis, University of Ghent, Ghent 9000, Belgium. 3. Center for Neurosciences (C4N), Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, Brussels 1090, Belgium; National MS Center, Neurology, Vanheylenstraat 16, Melsbroek 1820, Belgium; St Edmund Hall, Queen's Lane, Oxford OX1 4AR, United Kingdom. 4. Center for Neurosciences (C4N), Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, Brussels 1090, Belgium; Department of Physical Medicine and Rehabilitation, Universitair ziekenhuis Brussel, Laarbeeklaan 101, Brussels 1090, Belgium. 5. Department of Public Health (GEWE), Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Laarbeeklaan 103, Brussels 1090, Belgium; Interuniversity Centre for Health Economics Research (I-CHER), Belgium; Department of Physical Medicine and Physiotherapy, Universitair Ziekenhuis Brussel, Laarbeeklaan 101, Brussels 1090, Belgium; Department of Physiotherapy, Human Physiology and Anatomy, Faculty of Physical Education & Physiotherapy, Vrije Universiteit Brussel, Laarbeeklaan 103, Brussels 1090, Belgium; Research Foundation - Flanders (FWO), Brussels, Belgium. 6. Department of Public Health (GEWE), Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Laarbeeklaan 103, Brussels 1090, Belgium; Interuniversity Centre for Health Economics Research (I-CHER), Belgium. 7. Department of Biostatistics and Medical Informatics, Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Laarbeeklaan 103, Brussels 1090, Belgium. 8. Department of Physical Medicine and Physiotherapy, Universitair Ziekenhuis Brussel, Laarbeeklaan 101, Brussels 1090, Belgium; Department of Physiotherapy, Human Physiology and Anatomy, Faculty of Physical Education & Physiotherapy, Vrije Universiteit Brussel, Laarbeeklaan 103, Brussels 1090, Belgium; Research Foundation - Flanders (FWO), Brussels, Belgium. 9. Department of Physical Medicine and Physiotherapy, Universitair Ziekenhuis Brussel, Laarbeeklaan 101, Brussels 1090, Belgium; Department of Physiotherapy, Human Physiology and Anatomy, Faculty of Physical Education & Physiotherapy, Vrije Universiteit Brussel, Laarbeeklaan 103, Brussels 1090, Belgium. 10. Department of Neurosurgery, Universitair Ziekenhuis Brussel, Laarbeeklaan 101, Brussels 1090, Belgium; Center for Neurosciences (C4N), Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, Brussels 1090, Belgium; Department of Radiology, Universitair Ziekenhuis Brussel, Laarbeeklaan 101, Brussels 1090, Belgium. Electronic address: maarten.moens@uzbrussel.be.
Abstract
INTRODUCTION: Despite the worldwide increase in prevalence of chronic pain and the subsequent scientific interest, researchers studying the brain and brain mechanisms in pain patients have not yet clearly identified the exact underlying mechanisms. Quantifying the neuronal interactions in electrophysiological data could help us gain insight into the complexity of chronic pain. Therefore, the aim of this study is to examine how different underlying pain states affect the processing of nociceptive information. METHODS: Twenty healthy participants, 20 patients with non-neuropathic low back-related leg pain and 20 patients with neuropathic failed back surgery syndrome received nociceptive electrical stimulation at the right sural nerve with simultaneous electroencephalographic recordings. Dynamic Causal Modeling (DCM) was used to infer hidden neuronal states within a Bayesian framework. RESULTS: Pain intensity ratings and stimulus intensity of the nociceptive stimuli did not differ between groups. Compared to healthy participants, both patient groups had the same winning DCM model, with an additional forward and backward connection between the somatosensory cortex and right dorsolateral prefrontal cortex. DISCUSSION: The additional neuronal connection with the prefrontal cortex as seen in both pain patient groups could be a reflection of the higher attention towards pain in pain patients and might be explained by the higher levels of pain catastrophizing in these patients. CONCLUSION: In contrast to the similar pain intensity ratings of an acute nociceptive electrical stimulus between pain patients and healthy participants, the brain is processing these stimuli in a different way.
INTRODUCTION: Despite the worldwide increase in prevalence of chronic pain and the subsequent scientific interest, researchers studying the brain and brain mechanisms in painpatients have not yet clearly identified the exact underlying mechanisms. Quantifying the neuronal interactions in electrophysiological data could help us gain insight into the complexity of chronic pain. Therefore, the aim of this study is to examine how different underlying pain states affect the processing of nociceptive information. METHODS: Twenty healthy participants, 20 patients with non-neuropathic low back-related leg pain and 20 patients with neuropathic failed back surgery syndrome received nociceptive electrical stimulation at the right sural nerve with simultaneous electroencephalographic recordings. Dynamic Causal Modeling (DCM) was used to infer hidden neuronal states within a Bayesian framework. RESULTS:Pain intensity ratings and stimulus intensity of the nociceptive stimuli did not differ between groups. Compared to healthy participants, both patient groups had the same winning DCM model, with an additional forward and backward connection between the somatosensory cortex and right dorsolateral prefrontal cortex. DISCUSSION: The additional neuronal connection with the prefrontal cortex as seen in both painpatient groups could be a reflection of the higher attention towards pain in painpatients and might be explained by the higher levels of pain catastrophizing in these patients. CONCLUSION: In contrast to the similar pain intensity ratings of an acute nociceptive electrical stimulus between painpatients and healthy participants, the brain is processing these stimuli in a different way.
Authors: Natalie R Osborne; Dimitri J Anastakis; Junseok Andrew Kim; Rima El-Sayed; Joshua C Cheng; Anton Rogachov; Kasey S Hemington; Rachael L Bosma; Camille Fauchon; Karen D Davis Journal: Brain Commun Date: 2022-09-22
Authors: Jingya Miao; Isaiah Ailes; Laura Krisa; Kristen Fleming; Devon Middleton; Kiran Talekar; Peter Natale; Feroze B Mohamed; Kevin Hines; Caio M Matias; Mahdi Alizadeh Journal: Front Neurosci Date: 2022-09-23 Impact factor: 5.152