Computational protocol: Characterizing Acupuncture Stimuli Using Brain Imaging with fMRI - A Systematic Review and Meta-Analysis of the Literature

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Protocol publication

[…] The three researchers (WJH: Pubmed, Embase and CNKI, KP: Korean databases, YM: Japanese databases) extracted the data for all descriptive information from the publications, namely published journals, language, study place, study type, subjects, handedness, objective, interventions, control groups, block-design, fMRI device type, software for fMRI data analysis, sample size, and results. The extracted data were discussed with three supervisors (CW, DP and VN). Any inconsistencies were discussed and reconsidered until consensus was reached.Results were structured according to the four research questions. Studies that matched multiple research questions were displayed more than once, but only with the part of the study relevant to the respective research question.Furthermore, one figure for different acupuncture points from publications in Talairach coordinates was generated by one author (XYL) using Analysis of Functional NeuroImages (AFNI, and MRIcron software ( The anatomical image was generated using MRIcron software.The meta-analyses were conducted (JN, XYL, WJH) in Talairach space, using the activation likelihood estimation technique (ALE) implemented in GingerALE 2.1.1 software –. This technique assesses the convergence between activation foci from different experiments. Prior to the analysis, coordinates reported in MNI (Montreal Neurological Institute) space were converted to Talairach anatomical space using the Lancaster transform . For each experiment, every reported activation maximum was modeled by a 3-dimensional Gaussian probability distribution centered at the given coordinate. The width of the Gaussian probability distribution was determined individually for each experiment based on empirical estimates of between-subject variability, taking into account the number of subjects in each experiment . Voxel-wise ALE scores were calculated from the union of the Gaussian probability distributions within and across experiments. In a random effects analysis, ALE scores were tested against a null hypothesis of random distribution across the brain, thereby identifying those regions where empirical ALE values were higher than could be expected by chance. Resulting ALE maps were thresholded at p<0.05 (corrected for multiple comparisons by False Discovery Rate). The minimum cluster volume was chosen to exceed the number of voxels corresponding to 5% possible false positives. The contrast studies analysis (subtraction analysis which compares two ALE maps) was performed with randomization testing with 10,000 permutations. As there exists no correction for multiple comparison with this approach, the threshold was set at p<0.05 (uncorrected) with a min. cluster size = 200 mm3 .ALE maps were computed for the following statistical comparisons. From all studies included in the meta-analysis: 1a) greater activation of verum acupuncture points compared to baseline (verum>rest), 1b) greater deactivation of verum acupuncture points compared to baseline (rest>verum). From the studies which provided direct contrasts between verum and sham acupuncture: 2a) greater activation from verum than sham acupuncture (or greater deactivation for sham, i.e. verum>sham), 2b) greater deactivation from verum than sham acupuncture (or greater activation for sham, i.e. sham>verum). From the studies which had both verum and sham acupuncture groups: 3a) greater activation of verum acupuncture points than baseline (verum>rest), 3b) greater deactivation of verum acupuncture points than baseline (rest>verum), 3c) greater activation of sham acupuncture points than baseline (sham>rest), 3d) greater deactivation of sham acupuncture points than baseline (rest>sham), 3e) comparison ALE map of greater activation of verum than sham acupuncture relative to rest (“verum>rest” - “sham>rest”), 3f) comparison ALE map of greater deactivation of verum than sham acupuncture relative to rest (“rest>verum” - “rest>sham”). […]

Pipeline specifications

Software tools AFNI, MRIcron
Applications Magnetic resonance imaging, Functional magnetic resonance imaging
Organisms Homo sapiens