Resting-state Electroencephalography Microstates Correlate with Pain Intensity in Patients with Complex Regional Pain Syndrome

  • Michihiro Osumi
    Graduate School of Health Science, Kio University. 4-2-2 Umaminaka, Kitakatsuragigun, Nara, Japan
  • Masahiko Sumitani
    Department of Pain and Palliative Medicine, The University of Tokyo Hospital. 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan
  • Katsuyuki Iwatsuki
    Department of Hand Surgery, Graduate School of Medicine, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi, Japan
  • Minoru Hoshiyama
    Department of Health Sciences, Faculty of Medicine, Nagoya University, 1-1-20 Daiko-minami, Higashi-ku, Nagoya, Aichi, Japan
  • Ryota Imai
    School of Rehabilitation, Osaka Kawasaki Rehabilitation University, Kaizuka, Osaka, Japan
  • Shu Morioka
    Graduate School of Health Science, Kio University. 4-2-2 Umaminaka, Kitakatsuragigun, Nara, Japan
  • Hitoshi Hirata
    Department of Hand Surgery, Graduate School of Medicine, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi, Japan

書誌事項

公開日
2023-10-16
資源種別
journal article
権利情報
  • https://journals.sagepub.com/page/policies/text-and-data-mining-license
DOI
  • 10.1177/15500594231204174
公開者
SAGE Publications

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説明

<jats:p> Objective: Severe pain and other symptoms in complex regional pain syndrome (CRPS), such as allodynia and hyperalgesia, are associated with abnormal resting-state brain network activity. No studies to date have examined resting-state brain networks in CRPS patients using electroencephalography (EEG), which can clarify the temporal dynamics of brain networks. Methods: We conducted microstate analysis using resting-state EEG signals to prospectively reveal direct correlations with pain intensity in CRPS patients (n = 17). Five microstate topographies were fitted back to individual CRPS patients’ EEG data, and temporal microstate measures were subsequently calculated. Results: Our results revealed five distinct microstates, termed microstates A to E, from resting EEG data in patients with CRPS. Microstates C, D and E were significantly correlated with pain intensity before pain treatment. Particularly, microstates D and E were significantly improved together with pain alleviation after pain treatment. As microstates D and E in the present study have previously been related to attentional networks and the default mode network, improvement in these networks might be related to pain relief in CRPS patients. Conclusions: The functional alterations of these brain networks affected the pain intensity of CRPS patients. Therefore, EEG microstate analyses may be used to identify surrogate markers for pain intensity. </jats:p>

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