Test–retest study of fMRI signal change evoked by electroacupuncture stimulation
Introduction
Recently, fMRI has been used to investigate the neurobiological mechanisms of acupuncture needle manipulation (Cho et al., 1998, Wu et al., 1999, Hui et al., 2000, Gareus et al., 2002, Kong et al., 2002, Siedentopf et al., 2002, Wu et al., 2002, Li et al., 2003b, Zhang et al., 2003, Fang et al., 2004, Li et al., 2004, Litscher et al., 2004, Liu et al., 2004b, Napadow et al., 2004, Yoo et al., 2004, Hui et al., 2005, Yan et al., 2005). In these studies, researchers investigated correlations between acupoint stimulation and brain activity as reflected by fMRI signal changes. BOLD signal increases in SII and insula were the most consistently observed findings and were reported regardless of acupoint location or acupuncture mode (Wu et al., 1999, Hui et al., 2000, Kong et al., 2002, Wu et al., 2002, Li et al., 2003b, Zhang et al., 2003, Fang et al., 2004, Li et al., 2004, Liu et al., 2004b, Napadow et al., 2004, Yoo et al., 2004). Aside from this observation, acupuncture needle stimulation was associated with a rather variable pattern of BOLD signal changes across the studies.
These discrepant findings do not necessarily conflict with each other, as there are many sources of variability inherent in fMRI investigations that may contribute to the reported differences. These sources of variability include differences in MR scanner hardware and software, MRI acquisition sequences, data post-processing methods (Smith et al., 2005), and the resting physiological state (level of arousal) of the research subject. Different modes of acupuncture, different acupuncture points, and unequal duration of stimulation may also contribute to the variation in findings. In addition, because acupuncture is a therapeutic modality, it may produce different brain responses across different individuals. A systematic evaluation of the reliability of fMRI signal changes in response to acupuncture stimulation will help to clarify the origin of these variabilities and inform the design of future studies (Friston et al., 1995a, Friston et al., 1995b, Friston et al., 1999, Wei et al., 2004).
Researchers have begun to investigate test–retest reliability of fMRI BOLD signal changes evoked by paradigms ranging from simple sensory motor tasks such as finger tapping and visual simulation to more complex cognitive paradigms such as auditory oddball stimulation, working memory, and learning tasks (Casey et al., 1998, Machielsen et al., 2000, McGonigle et al., 2000, Waldvogel et al., 2000, Loubinoux et al., 2001, Manoach et al., 2001, Rutten et al., 2002, Kurland et al., 2004, Marshall et al., 2004, Wei et al., 2004, Havel et al., 2006, Wagner et al., 2005, Yoo et al., 2005, Aron et al., 2006). For instance, several studies have used the finger-tapping task (Yetkin et al., 1996, McGonigle et al., 2000, Waldvogel et al., 2000, Liu et al., 2004a, Smith et al., 2005, Yoo et al., 2005), one of the most widely used tasks in fMRI studies, to investigate the reliability of fMRI signal changes. Although the methods used across these studies are not exactly the same, they all reach the similar conclusion that a simple motor task produces relatively reliable patterns of fMRI signal increases in primary motor cortex, supplementary motor area (SMA), and cerebellum. Nonetheless, substantial variability in the quantitative measurements of fMRI signal change, such as magnitude and spatial extension of activations, was found across subjects within those brain regions.
To our knowledge, no study has evaluated the test–retest reliability of fMRI signal changes evoked by acupuncture needle stimulation. In this study, we used two Traditional Chinese Medicine (TCM) acupoints (UB 60 and GB 37) to investigate the reliability and reproducibility of fMRI signal changes evoked by acupuncture stimulation. Both UB 60 and GB 37 have been previously studied with fMRI (Cho et al., 1998, Gareus et al., 2002, Li et al., 2003a). We also studied one non-acupoint (NP) to investigate the specificity of our findings. We located the NP about 1.5 cm posterior and inferior to the small head of the fibula where there is neither an acupoint nor a meridian crossing this area according to the TCM theory. To assist in the interpretation of the reliability of BOLD signal change during acupuncture, we also included a finger-tapping task (Yetkin et al., 1996, McGonigle et al., 2000, Waldvogel et al., 2000, Liu et al., 2004a, Smith et al., 2005, Yoo et al., 2005).
Section snippets
Subjects
Eight healthy acupuncture-naive, right-handed subjects (4 males, mean age 29 ± 7 years, mean ± SD) participated in this study. Subjects were told that this study would investigate the reliability of fMRI in the recording of brain activity during stimulation of three acupuncture points across six sessions. The study was conducted with the understanding and written consent of each subject and approval by the Human Research Committee at Massachusetts General Hospital.
Experimental procedures
Each subject participated in six
Subjects
Of the eight volunteers who consented into the study, six (three female) completed all six sessions. Two subjects withdrew from the study after Session 2. Only the data from the subjects who completed all six sessions were analyzed. The average interval in days between Sessions 2 and 3 was 4.5 ± 1.3, Sessions 3 and 4 was 12 ± 4.5, Sessions 4 and 5 was 13.3 ± 4.3, and Sessions 5 and 6 was 14.8 ± 9.
SASS ratings
The average stimulus intensities (mean ± SD) used for GB 37 (5.5 ± 2.1 V) and NP (5.7 ± 2.0 V) were similar to
Discussion
In this study, we investigated the fMRI signal changes evoked by finger-tapping and electroacupuncture stimulation. Group analysis showed that finger tapping of the right hand evoked the expected activation in left M1, S1, thalamus and putamen, bilateral insula/operculum, SMA, and cerebellum. Visual observation showed that the finger-tapping task evoked a reliable brain activation pattern across individual sessions for all subjects, consistent with previous reports (Yetkin et al., 1996,
Acknowledgments
Funding and support for this study came from NIH (NCCAM) R21AT00949 to Randy Gollub, PO1-AT002048 to Bruce Rosen/Randy Gollub, and KO1AT003883 to Jian Kong. M01-RR-01066 for Mallinckrodt General Clinical Research Center Biomedical Imaging Core, P41RR14075 for Center for Functional Neuroimaging Technologies from NCRR, and the MIND Institute.
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