Bout-associated intrinsic functional network changes in cluster headache: A longitudinal resting-state functional MRI study

Kun Hsien Chou, Fu Chi Yang, Jong Ling Fuh, Chen Yuan Kuo, Yi Hsin Wang, Jiing Feng Lirng, Yung Yang Lin, Shuu Jiun Wang*, Ching Po Lin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

Background Previous imaging studies on the pathogenesis of cluster headache (CH) have implicated the hypothalamus and multiple brain networks. However, very little is known regarding dynamic bout-associated, large-scale resting state functional network changes related to CH. Methods Resting-state functional magnetic resonance imaging data were obtained from CH patients and matched controls. Data were analyzed using independent component analysis for exploratory assessment of the changes in intrinsic brain networks and their relationship between in-bout and out-of-bout periods, as well as correlations with clinical observations. Results Compared to healthy controls, CH patients had functional connectivity (FC) changes in the temporal, frontal, salience, default mode, somatosensory, dorsal attention, and visual networks, independent of bout period. Compared to out-of-bout scans, in-bout scans showed altered FC in the frontal and dorsal attention networks. Lower frontal network FC correlated with longer duration of CH. Conclusions The present findings suggest that episodic CH with dynamic bout period shifts may involve bout-associated FC changes in multiple discrete cortical areas within networks outside traditional pain processing areas. Dynamic changes in FC in frontal and dorsal attention networks between bout periods could be important for understanding episodic CH pathophysiology.

Original languageEnglish
Pages (from-to)1152-1163
Number of pages12
JournalCephalalgia
Volume37
Issue number12
DOIs
StatePublished - 1 Oct 2017

Keywords

  • Bout period
  • Cluster headache
  • functional connectivity
  • hypothalamus
  • independent component analysis

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