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The influence of nociceptive and neuropathic pain states on the processing of acute electrical nociceptive stimulation : a dynamic causal modeling study

(2020) BRAIN RESEARCH. 1733.
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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.
Keywords
General Neuroscience, Pain, fMRI, computational neuroscience, Nociceptive stimulation, Dynamic causal modeling, Effective connectivity, Electroencephalography, LOW-BACK-PAIN, CATASTROPHIZING SCALE, LEG PAIN, RELIABILITY, EEG, CONNECTIVITY, RESPONSES, REFLEX, MANAGEMENT, SELECTION

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MLA
Goudman, Lisa, et al. “The Influence of Nociceptive and Neuropathic Pain States on the Processing of Acute Electrical Nociceptive Stimulation : A Dynamic Causal Modeling Study.” BRAIN RESEARCH, vol. 1733, 2020, doi:10.1016/j.brainres.2020.146728.
APA
Goudman, L., Marinazzo, D., Van de Steen, F., Nagels, G., De Smedt, A., Huysmans, E., … Moens, M. (2020). The influence of nociceptive and neuropathic pain states on the processing of acute electrical nociceptive stimulation : a dynamic causal modeling study. BRAIN RESEARCH, 1733. https://doi.org/10.1016/j.brainres.2020.146728
Chicago author-date
Goudman, Lisa, Daniele Marinazzo, Frederik Van de Steen, Guy Nagels, Ann De Smedt, Eva Huysmans, Koen Putman, et al. 2020. “The Influence of Nociceptive and Neuropathic Pain States on the Processing of Acute Electrical Nociceptive Stimulation : A Dynamic Causal Modeling Study.” BRAIN RESEARCH 1733. https://doi.org/10.1016/j.brainres.2020.146728.
Chicago author-date (all authors)
Goudman, Lisa, Daniele Marinazzo, Frederik Van de Steen, Guy Nagels, Ann De Smedt, Eva Huysmans, Koen Putman, Ronald Buyl, Kelly Ickmans, Jo Nijs, Iris Coppieters, and Maarten Moens. 2020. “The Influence of Nociceptive and Neuropathic Pain States on the Processing of Acute Electrical Nociceptive Stimulation : A Dynamic Causal Modeling Study.” BRAIN RESEARCH 1733. doi:10.1016/j.brainres.2020.146728.
Vancouver
1.
Goudman L, Marinazzo D, Van de Steen F, Nagels G, De Smedt A, Huysmans E, et al. The influence of nociceptive and neuropathic pain states on the processing of acute electrical nociceptive stimulation : a dynamic causal modeling study. BRAIN RESEARCH. 2020;1733.
IEEE
[1]
L. Goudman et al., “The influence of nociceptive and neuropathic pain states on the processing of acute electrical nociceptive stimulation : a dynamic causal modeling study,” BRAIN RESEARCH, vol. 1733, 2020.
@article{8648496,
  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.}},
  articleno    = {{146728}},
  author       = {{Goudman, Lisa and Marinazzo, Daniele and Van de Steen, Frederik and Nagels, Guy and De Smedt, Ann and Huysmans, Eva and Putman, Koen and Buyl, Ronald and Ickmans, Kelly and Nijs, Jo and Coppieters, Iris and Moens, Maarten}},
  issn         = {{0006-8993}},
  journal      = {{BRAIN RESEARCH}},
  keywords     = {{General Neuroscience,Pain,fMRI,computational neuroscience,Nociceptive stimulation,Dynamic causal modeling,Effective connectivity,Electroencephalography,LOW-BACK-PAIN,CATASTROPHIZING SCALE,LEG PAIN,RELIABILITY,EEG,CONNECTIVITY,RESPONSES,REFLEX,MANAGEMENT,SELECTION}},
  language     = {{eng}},
  pages        = {{9}},
  title        = {{The influence of nociceptive and neuropathic pain states on the processing of acute electrical nociceptive stimulation : a dynamic causal modeling study}},
  url          = {{http://dx.doi.org/10.1016/j.brainres.2020.146728}},
  volume       = {{1733}},
  year         = {{2020}},
}

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