Differential spatial activity patterns of acupuncture by a machine learning based analysis

  • Youbo You
  • , Lijun Bai
  • , Ting Xue
  • , Chongguang Zhong
  • , Zhenyu Liu
  • , Jie Tian*
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Acupoint specificity, lying at the core of the Traditional Chinese Medicine, underlies the theoretical basis of acupuncture application. However, recent studies have reported that acupuncture stimulation at nonacupoint and acupoint can both evoke similar signal intensity decreases in multiple regions. And these regions were spatially overlapped. We used a machine learning based Support Vector Machine (SVM) approach to elucidate the specific neural response pattern induced by acupuncture stimulation. Group analysis demonstrated that stimulation at two different acupoints (belong to the same nerve segment but different meridians) could elicit distinct neural response patterns. Our findings may provide evidence for acupoint specificity.

Original languageEnglish
Title of host publicationMedical Imaging 2011
Subtitle of host publicationBiomedical Applications in Molecular, Structural, and Functional Imaging
DOIs
StatePublished - 2011
Externally publishedYes
EventMedical Imaging 2011: Biomedical Applications in Molecular, Structural, and Functional Imaging - Lake Buena Vista, FL, United States
Duration: 13 Feb 201116 Feb 2011

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume7965
ISSN (Print)1605-7422

Conference

ConferenceMedical Imaging 2011: Biomedical Applications in Molecular, Structural, and Functional Imaging
Country/TerritoryUnited States
CityLake Buena Vista, FL
Period13/02/1116/02/11

Keywords

  • Acupuncture
  • Functional magnetic resonance imaging (fMRI)
  • Support Vector Machine (SVM)

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