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An fMRI study of acupuncture using independent component analysis

  • Yi Zhang
  • , Wei Qin
  • , Peng Liu
  • , Jie Tian*
  • , Jimin Liang
  • , Karen M. von Deneen
  • , Yijun Liu
  • *Corresponding author for this work
  • Xidian University
  • Northeastern University China
  • CAS - Institute of Automation
  • University of Florida

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, we studied the brain functional networks corresponding to the traditional multiple-block acupuncture task paradigm. Due to the complexity and sustainability seen during acupuncture, we wanted to investigate whether or not the effects during acupuncture are changing according to the multiple-block paradigm. We introduced the data driven method of independent component analysis (ICA) to identify brain functional networks activated during the course of acupuncture and to isolate different networks likely related to different aspects of the acupuncture experience. The comparisons between different resting states disclosed the discrepancies between the pre- and post-needling effects in the brain. Furthermore, the distinction between needle stimulation and the resting state indicated that there existed different functional brain networks. These results also portray time variability during the course of acupuncture.

Original languageEnglish
Pages (from-to)6-9
Number of pages4
JournalNeuroscience Letters
Volume449
Issue number1
DOIs
StatePublished - 2 Jan 2009
Externally publishedYes

Keywords

  • Acupuncture
  • Functional brain network
  • Independent component analysis (ICA)
  • fMRI

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