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fMRI
Neurophysiological Evidence
Of Acupuncture Mechanisms
Zang-Hee Cho, PhD; Young-Don Son, MSc; Jae-Yong Han,
MSc;
Edward K. Wong, MD; Chang-Ki Kang, MSc; Kyung-Yo Kim, PhD;
Hyung-Kyoon Kim, PhD; Byung-Yeol Lee, PhD;
Yoon-Kyung Yim, PhD; Ki-Hyon Kim, PhD
ABSTRACT
Background Although acupuncture is often used for pain treatment,
its effect has been suspected as a “placebo” for which biological
evidence has not been shown. In addition, skeptics question the “point
specificity” of acupuncture, particularly in acupuncture analgesia.
Objectives To address whether pain-specific acupoints are point
specific, and to determine if evoking a “pain-like” stimulation
activates the appropriate cortical areas, thereby inhibiting the perception
of pain.
Design, Setting, and Subjects Prospective brain imaging studies
in 12 subjects.
Interventions Pain stimulation was achieved by immersing subjects’
index fingers in hot water (52ºC) for 30 seconds. Meridian acupuncture
was administered by manually twirling the needle in LR 3 for 30 seconds,
needling for 30 seconds without twirling, and then removing the needle
and repeating the paradigm 5 times without removing the needle. Sham
acupuncture was performed with an arbitrary body point where no meridians
or points passed of sufficient distance from pain relief acupoints.
Main Outcome Measures Findings on functional magnetic resonance
imaging (fMRI) in the anterior cingulate cortex and thalamic areas after
each intervention.
Results The anterior cingulate cortex and thalamic areas were
activated as a result of pain stimulation. Decreased activation in these
areas was noted following both meridian acupuncture and sham acupuncture
(P=.0001 for all).
Conclusions Acupuncture appears to inactivate the brain regions
involved in the transmission and perception of pain. Because the effects
of meridian and sham acupuncture were similar, acupuncture may not be
entirely point specific. Further research in this area is necessary.
KEY WORDS
Acupuncture Analgesia, Functional MRI, Meridian Acupuncture, Sham Acupuncture,
Point Specificity
INTRODUCTION
Although acupuncture has been used for many centuries,1-4 the scientific
evidence for the physiology of efficacious pain treatment has not been
definitively established, and many scientists suspect it to be a placebo
effect. Possible mechanisms for pain relief in acupuncture analgesia
have been studied in the West since 1965, beginning with the pioneering
work of Melzack and Wall.5 Although rigorous scientific explanations
are rare and most are anecdotal, acupuncture is reported to treat some
classes of diseases and to control pain.3,4,6-9 Of many studies in acupuncture
analgesia,4,6-9 most have been theories and hypotheses obtained using
animal models, while some were inferentially obtained by using human
subjects. In the past 2 decades, brain imaging tools such as positron
emission tomography (PET)10-12 and functional magnetic resonance imaging
(fMRI)13-18 have made it possible to directly visualize brain function
in vivo. With the development of these functional brain imaging techniques,
especially fMRI, observations have been made of cortical correlation
using a few specific acupuncture points.19-22 Based on our previous
experience in acupuncture and with the availability of in vivo functional
brain imaging, especially with the new dynamic data processing (differential
correlation function [DCF] technique [to be published]), it is now possible
to directly observe physiologically modulated cortical activation due
to pain stimulation as well as pain stimulation after the administration
of acupuncture.
We describe some new observations on the much-debated relationship between
cortical activation and pain, as well as the pain-relief mechanism of
acupuncture. Our study focused on observing changes in cortical activation
due to pain stimulation with and without acupuncture administration.
Special attention was paid to the areas related to pain signal relaying,
attention focusing or riveting, perception, and modulation or control
of pain signals that include the anterior cingulate cortices (ACCs)
and the thalamic areas.23-26 We also performed a set of experiments
that may clarify the “point specificity” of acupuncture, especially
for the pain-specific acupoints. To perform the pain-specific acupuncture
experiments, we divided acupuncture into 2 categories: traditional meridian
acupuncture and sham acupuncture. The latter was defined as an arbitrary
point on the body surface where no traditional meridian lines and points
pass, and also sufficiently distant from meridian lines and acupoints
for pain relief.
Anatomical Descriptions
Regarding the description of our experimental results, a few relevant
illustrations of the anatomical images and cortical areas that are activated
during pain stimulation are shown in Figure 1. In Figure 2a, those experimentally-observed
activation areas due to pain stimulation are specifically marked for
illustration of pain perception an dynamics.
In Figure 2b, a corresponding sketch, together with possible functional
roles of each area, are shown. In Figure 3, time-dependent activation
images due to pain stimulation plotted for the 4 selected times (d =
0 seconds, 6 seconds, 18 seconds, and 30 seconds) demonstrate the pain
dynamics of the fMRI data processed with the DCF technique. Pain stimulation
is achieved by immersing the index finger into a hot bath of water with
a temperature of 52ºC for 30 seconds. We conducted thermal stimulation
as basal pain stimulation in conjunction with the meridian and sham
acupuncture study to be performed.
 |
 |
Figure
1. A typical anatomical image and corresponding functional magnetic
resonance imaging (fMRI) data of the mid-sagittal view obtained
by pain stimulation. Locations of the various pain-related brain
areas are also shown: (a) An anatomical image showing the anterior
cingulate cortex (ACC) (dACC [dorsal], rACC [rostral], and cACC
[caudal]), the supplementary and primary motor areas, and the thalamic
nuclei overlaid on a mid-sagittal view of an anatomical image of
a human brain. (b) Averaged fMRI data obtained by pain stimulation
overlaid on a mid-sagittal view image (average of 12 subjects).
|
Figure
2. Illustration of the major cortical areas believed to be involved
in pain signal “relay,” attention “riveting,”
and emotional pain “perception.” (a) The approximate
areas of the subcingulate cortices (dACC, rACC, and cACC) and the
thalamus overlaid on an activation image obtained by pain stimulation.
(b) A sketch of those subcingulate cortices and the thalamus with
possible functional roles of each component. |
From this data set (Figure 3), the sequentially varying cortical activation
pattern of pain signal processing can be seen. This particular set is
one of typical sets of images of a single subject (without averaging)
that represents the typical pain dynamic data we have obtained from
most of the experiments. This pain dynamic data set demonstrates a much-suspected,
time-dependent activation pattern due to pain as detailed below. Single-subject
data are given because the activation data vary substantially from one
individual to another, and from one experiment to another.
 |
| Figure 3. These
pain dynamic data show how various cortical areas are sequentially
activated as a function of time. The dynamic fMRI data are obtained
by use of the time-varying differential correlation function (DCF)
technique that uses a set of discretely delayed correlation functions
rather than a fixed correlation function. This DCF technique is
an essential component for the extraction of the pain signals as
well as the pain signals affected by acupuncture since these stimuli
invariably result in physiologically complex and delayed activations.
|
As noted in Figures 1, 2, and 3 (where the activation images are overlaid
on the mid-sagittal image), 3 subcortices of the cingulate cortex (dACC,
cACC, and rACC), together with the thalamus, are involved in pain signal
“relay,” “perception,” and possibly “modulation
or control.” There is also involvement of other cortical areas
including the supplementary motor, the primary motor, and the tectal
areas. Note the physiologically-delayed responses obtained by fMRI data
using the time-varying DCF techniques. For example, with the conventional
signal processing method using the correlation or regression analysis
technique, the processed data will be either time-integrated data or
data with significant loss in activation due to physiologically-delayed
responses of pain stimulation (see and compare, for example, the activation
data shown at d = 0 seconds and at d = 18 seconds). Time differential
activation data shown in Figure 3 are contrasted with many prompt responses
seen in the field of fMRI study in which simple photic or auditory stimulation
is norm.
In the area of pain perception (pain alone), a number of studies have
been reported using brain imaging such as PET and fMRI techniques.27-34
However, because the reported results vary, no conclusive findings have
yet been made. These variable results may be due to physiological delay
of the stimuli’s response. In addition, cortical areas related
to pain perception differ widely from person to person and between different
time periods even for the same subject. Despite these individual variations
and other environmental factors, pain perception appears involved with
several cortical areas related to pain signal “relay” (switching),
“attention riveting” (selection), “perception” (emotional
aspect), and “control or modulation.”35,36 Our experimentally-observed
data shown in Figure 3, the pain dynamic data, suggest support for the
aforementioned ideas that pain signal “riveting” is closely
related to the cognitive division of the cingulate cortex of the brain,
especially the dorsal aspect of the cingulate cortex (dACC);5,25 the
posterior or caudal aspect of the cingulate cortex (cACC) is believed
to be involved with pain signal “perception,” and the more
rostral aspect of the cingulate cortex (rACC) is thought to be involved
in modulation or control of pain. It is important to observe how pain
signal perception varies as a function of time, since the dynamic data
allow inference of the following pain signal pathways: relay Æ
attention focusing or riveting Æ perception Æ modulation
(see Figure 3 for the corresponding activation pattern, i.e., sequential
activation pattern of thalamus Æ dACC Æ cACC Æ rACC).
Our purpose was to report the findings that may reveal important clues
in understanding the mechanisms underlying pain perception and pain
relief. This may lead to an understanding of the mechanism of acupuncture
analgesia since these 2 may share the same pain-related cortical areas.
We have observed that acupuncture analgesia is closely related with
the cortical centers involved with pain perception. Therefore, we hypothesized
that the analgesic effect of acupuncture stimulation is related to the
same cortical areas as pain perception, specifically, the ACCs and the
thalamic nuclei.
METHODS
All research subjects signed a written consent form. This research project
was reviewed and approved by the University of California-Irvine Institutional
Review Board.
After studying pain dynamics as discussed above, we directed our attention
to acupuncture analgesia by extending our pain study paradigm to include
acupuncture administration. LR 3 was chosen because of its accessibility
for fMRI scanning techniques; namely, insertion of a needle in the foot
does not require moving the subject’s head. In addition, LR 3 is
a major acupuncture point: it is to the foot as LI 4 is to the hand.
Thermal stimulation (immersing the index finger into a hot bath of water
at a temperature of 52ºC for 30 seconds) was used as pain stimulation.
Immersion of the finger into the hot water results in several steps
of different sensations from feeling heat to unpleasantness to extreme
pain. To maximize exposure to hot temperature (pain), we pre-warmed
the finger with 43ºC water. Care was taken not to injure the subject’s
skin and no damage was observed.
Acupuncture stimulation at LR 3 was accomplished by (a) manually rotating
(twirling) the needle for 30 seconds, needling 30 seconds without twirling,
and finally, removing the needle, and (b) repeating the same paradigm
5 times without removing the needle, after which the needle was removed
for the remainder of the data acquisition period. These “pain”
and “acupuncture with pain” stimulation paradigms are shown
in Figure 4a and 4b. For the first part of study with the meridian acupuncture,
a single set of twirling was applied (paradigm Figure 4b[i], the “weak”
stimulation). In the latter part of the experiments with sham acupuncture,
we applied “strong” stimulation, as shown in Figure 4b(ii).
 |
Figure 4.
Stimulation paradigms used in the pain and acupuncture + pain experiments
(a) Paradigm I: Pain is achieved by immersing the index finger into
a hot bath of water (52ºC) for 30 seconds. (b) Paradigm II:
Acupuncture + pain stimulation is further divided into: (i) a weak
stimulation for the meridian acupuncture + pain experiment while
(ii) a strong stimulation was used for the sham acupuncture + pain
experiment. This paradigm consists of pain stimulation after 9 minutes
from the initial start of acupuncture stimulation. |
Data were collected for both intrapersonal as well as interpersonal
averages to obtain statistically reliable data. Averaging the data of
many individuals often obscures the fine details of time-dependent activation
due to the widely varying response time delays as well as differences
in the pain perception pattern of each individual. Summary data presented
in this article are mixed with intrapersonal and interpersonal averages
of 9-12 experiments that show a similar pattern of pain perception as
well as the acupuncture analgesia effect. Many variables are inherent
in acupuncture, including uncertainty of localization of the acupuncture
point, the differences in nerve distributions for different subjects,
needling methods, responses of the individual as a responder or non-responder,
the individual’s mental status and health condition, and pain perception
pattern or differences in pain tolerance. Due to such variability as
well as the technical difficulties such as the movement associated with
painful stimuli (both the pain stimulus itself and acupuncture needling),
data sets with severe motion artifact and non-responders were excluded.
We selected and averaged 9-12 data sets of similar patterns for each
mode out of 50 experimental sets. The fMRI pulse sequence used was the
gradient echo planar imaging sequence with 3 seconds repetition time,
35 milliseconds echo time, and 24 slices with a Marconi 1.5-T scanner.
Three experiments were performed on each subject: (1) pain stimulation
only, (2) meridian acupuncture followed by pain stimulation, and (3)
sham acupuncture followed by pain stimulation. Their corresponding stimulation
paradigms are shown in Figure 4a and 4b, respectively. For each set,
consisting of 24 axial slice images or data, 60 image data sets/slice
image at 3-second intervals were collected. To further visualize the
dynamic or time-dependent physiological responses of cortical activation,
all the data sets were processed with the DCF technique. The total activation
data or images obtained for each experimental set were 24 (slices) x
60 (time course images/ slice) x 3 (pain, meridian acupuncture, sham
acupuncture) = 4320 image data. The total activation images processed
were 24 (slices) x 12 (processed activation data) x 3 (pain, meridian
acupuncture + pain, sham acupuncture + pain) x 3 (axial, sagittal, coronal)
= 2592. Among these vast amounts of activation data, we selected a data
set of 4 representative time-dependent responses (d = 0 seconds, 9 seconds,
18 seconds, and 27 seconds, respectively) and displayed 3 representative
selected slices for each time response for each mode (pain, meridian
acupuncture + pain, sham acupuncture + pain).
Each image data set is made of axial, coronal, and sagittal images for
visualization. In each image data, P values are indicated at the upper
left corner and response time d is given in the final column of each
data set. Our data processing was performed by SPM99.33,34 To correct
for motion artifacts, a realignment algorithm was used. Since the size
or the shape of the human brain varies, we used a standard template
image such as the Talairach space37 for normalization of brain sizes.
In SPM99, the option was available to superimpose the activation data
on SPM standard template images such as EPI; therefore, it has been
used throughout the data display herein.
RESULTS
In Figure 5a, 5b, and 5c, a set of pain responses (axial, coronal, and
sagittal views) obtained by fMRI and processed by DCF technique is displayed
for a number of selected slices on 4 different delayed responses (d
= 0, 9, 18, and 27 seconds) to demonstrate pain-stimulation-dependent
cortical activation as a function of time. The ACC and the thalamic
areas were activated as a result of pain stimulation (see Figures 1
and 2 for anatomical correlation). In this data set as well as the other
sets below, the responses were time-dependent and obtained by DCF data
processing. These pain data are based on an intra- interpersonal average
of 12 subjects.
 |
Figure 5. Cortical
activation by pain stimulation observed by fMRI
The marked areas are the activated areas of the anterior cingulate
gyrus (blue circles) and the thalamic areas (red circles). (This
data set is an intra-inter average of 12 subjects).
M0 = center of mid-sagittal view slice, M1 or M-1= right or left
side lateral slices of mid-sagittal view, L= left, R= right, P =
posterior, M = middle,
and A = anterior. |
 |
Figure 6. Cortical
activation by traditional meridian acupuncture + pain stimulation
observed by fMRI
Note the markedly decreased activation in both the entire ACC as
well as the thalamic areas. In the upper cortical areas, the only
regions that showed activation were the supplementary and primary
motor areas as shown in mid-line sagittal view images (M0 column).
Similarly, only a small area in the thalamus remained activated
in the center slice at the mid-sagittal view (M0 column). The nuclei
involved in decreased activation appeared to be the midline nuclei.
(This data set is an average of 9 subjects.)
M0 = center of mid-sagittal view slice, M1 or M-1= right or left
side lateral slices of mid-sagittal view, P = posterior, M = middle,
and A = anterior. |
In Figure 6, activation patterns of the meridian acupuncture + pain
experiment seen by axial, coronal, and sagittal views are shown. To
obtain this data set, pain stimulation was applied 9 minutes after the
acupuncture stimulation (Figure 4b[i]). Significantly decreased activations
were seen in the ACC and the thalamic areas. Further detailed observation
demonstrated that most of the activation seen in the cingulate cortex
and the thalamic nuclei with the pain study were deactivated.
Specifically, the significantly decreased activation in dACC and cACC
as well as rACC suggests that the pain signal attention “riveting”
center (dACC) and the “perception” center (cACC), as well
as the “modulation or control” center (rACC), were in a deactivated
state. In Figure 3, activation of dACC precedes cACC and coincides with
pain sensations perceived by the subjects, suggesting that cACC probably
is the perception center of pain, especially the emotional component
of pain. The rACC, which is always activated last, is one of those pain-modulating
or controlling centers. Another notable decrease in activation was in
the mid-line thalamic area which includes the dorsomedial nucleus, anterior
nucleus, dorsal superficial nucleus, intralaminar nuclei, and centromedian
nucleus, most of which are connected either directly or indirectly to
the cingulate cortex. Activation and deactivation of these thalamic
nuclei in close correlation with dACC suggest that these thalamic nuclei
are the relay center of the upstream pain signals from the brainstem
and spinal cord to the upper brain, including the cingulate cortex.
Finally, decreased pain-dependent activation by the administration of
acupuncture clearly contrasts with pain stimulation alone, thereby showing
the evidence of the acupuncture effect on cortical centers, especially
the pain-related cortical areas such as the cingulate cortex and thalamus
(see and compare Figures 5 and 6). In Figure 6, with meridian acupuncture
+ pain data, most of the activation simply disappeared. The only remaining
activation sites were the supplementary motor area and a small area
in the motor cortex. In the thalamic area, much reduced activity was
again seen. In the tectal area, the activity previously seen with pain
stimulation alone also decreased significantly.
In Figure 7, activation patterns of the sham acupuncture + pain were
observed after using the stimulation paradigm shown in Figure 4b[ii].
Images are displayed in axial, coronal, and sagittal views, similar
to the previous 2 activation data sets. To obtain this data set, pain
stimulation was again applied 9 minutes after the initiation of sham
acupuncture stimulation, which lasted 5 minutes for this paradigm. Significantly
decreased activation similar to meridian acupuncture was seen both in
the ACCs and the thalamic areas. This sham result is the most surprising
new observation since it suggests that the traditionally believed “point
specificity” of acupuncture may not be entirely true. These findings
require further and may have far-reaching impact on acupuncture research
in general, including target-specific as well as target-
non-specific acupuncture studies. To further elucidate the new findings,
a direct comparison of the results of meridian acupuncture + pain and
sham acupuncture + pain are shown in Figure 8. Overall activation results
of pain, meridian acupuncture + pain, and sham acupuncture + pain are
displayed in Figure 9 for better comparison of the 3 paradigms.
 |
Figure 7. Sham
acupuncture + pain stimulation
Similar decreases were noted in activation in the major pain perception
and relay areas. (This data set is an average of 9 subjects.) |
 |
| Figure 8. Side-by-side
comparison of 2 cortical activations seen at the mid-line sagittal
view due to: (a) pain vs meridian acupuncture (LI 3) + pain stimulation
and (b) pain vs sham acupuncture + pain stimulation, respectively.
Decreases in activation of the 2 appear similar, suggesting that
they are based on similar neural mechanisms. |
CONCLUSION
Is the acupuncture effect real or simply a placebo effect? If it is
real, is acupuncture in reality point specific? We have attempted to
answer some of these questions using functional brain imaging. Our data
suggest that acupuncture stimulation clearly desensitizes or reduces
activation in the cortical areas that are believed to be involved with
pain signal processing, thereby alleviating pain perception. Our data
support the efficacy of acupuncture in pain relief, and support the
biological bases of acupuncture analgesia. Conversely, our sham acupuncture
+ pain study strongly suggests that the point specificity claimed by
acupuncturists and by the traditional acupuncture literature is not
fully supported in these experiments. However, our study suggests that
traditional acupuncture points indicated for pain control are more effective
than “sham” points since the meridian acupuncture points appear
effective with less stimulation than the sham point (Figure 4). Although
these preliminary data do not support point specificity of acupuncture,
corroboration will require more systematic studies with a number of
additional pain control acupuncture points together with carefully selected
sham points.
In addition to the above observations, our results strongly suggest
that the previously hypothesized descending pain inhibitory theory of
endogenous opioids at the level of the spinal cord may be only a part
of the whole pain inhibitory mechanism of acupuncture. Our observations
indicate that the pain perception and relaying centers are the cingulate
cortex and thalamus where acupuncture analgesia is probably mediated
by decreased activation in the pain, attention-riveting and perception,
and signal-relaying circuitry, namely the cingulate gyrus and the thalamus.
These observations indicate that acupuncture analgesia is a central
process involved with higher cortical and subcortical areas such as
the cerebral cortex (prefrontal cortex), the diencephalon (midline nuclei),
and the cingulate cortex where pain “perception,” attention
“riveting,” pain signal “modulation,” and “relay”
are orchestrated.
 |
| Figure 9. Comparison
of the cortical activation in 3 experiments, namely the activations
observed due to (a) pain stimulation (alone), (b) meridian acupuncture
+ pain stimulation, and (c) sham acupuncture + pain stimulation,
respectively. Note the markedly decreased activation in (b) and
(c) compared with (a), especially in the dACC, rACC, and cACC and
thalamic areas. This result implies that both centers are involved
in pain perception, attention riveting, and relay. In both (b) and
(c), the only areas that remained activated were the supplementary
motor and primary motor areas. In addition, activation in the tectal
area (TA) also decreased markedly and was no longer visible. AN
indicates anterior nucleus; DsF, dorsal superficial nucleus; DM,
dorsomedial nucleus; IL, intralaminar nuclei; and CM, centromedian
nucleus. |
Funding/Support
This work was supported in part by an NIH-NCCAM (National Center for
Complementary and Alternative Medicine) grant.
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AUTHORS’
INFORMATION
Zang-Hee Cho, PhD, is Professor of Radiological Sciences at the University
of California at Irvine, and Director of Functional Brain Imaging Laboratory
for Acupuncture Research. Dr Cho pioneered the first Acupuncture-fMRI
in 1997 and since then, has developed a number of acupuncture and fMRI
related techniques. Previous to acupuncture-fMRI research, he pioneered
the first Circular Ring PET scanner and BGO in the mid-70s. Since then,
he has been engaged in various aspects of medical imaging, especially
functional MRI imaging since the early 90s. Dr Cho is a member of US
National Academy of Sciences-Institute of Medicine for his contribution
to the development of PET scanner and related BGO detector.
Zang-Hee Cho, PhD*
Professor, Radiological Sciences, Psychiatry and Human Behavior,
and Ophthalmology
University of California at Irvine
Irvine, CA 92697
Phone: 949-824-5905 • Fax: 949-824-8032 • E-mail: zcho@uci.edu
Young-Don Son, MSc, is a graduate student working toward a PhD in Bio-
medical Engineering at University of California-Irvine under Professor
Cho. He has been instrumental in developing many acupuncture-related
functional imaging techniques, including the differential correlation
function technique developed recently.
Young-Don Son, MSc
Phone: 949-824-6333 • E-mail: sony@uci.edu
Jae-Yong Han, MSc, is a graduate student visiting University of California-Irvine
from Kyung-Hee University in Seoul, Korea. He participated in the functional
pain dynamic study and was responsible for the data processing.
Jae-Yong Han, MSc
Phone: 949-824-6333 • Email: jaiyong@hanmail.net
Dr Edward K. Wong is a member of the faculty of Department of Ophthalmology,
University of California-Irvine. Dr Wong was a participant in the first
acupuncture-fMRI work in 1997, and is responsible for the medical aspect
of the acupuncture experiment currently ongoing at University of California-Irvine.
Edward K. Wong, MD
Phone: 949-824-2668 • E-mail: ekwong@uci.edu
Chang-Ki
Kang, MSc, is a graduate student working toward a PhD in Biomedical
Engineering at University of California-Irvine under Professor Cho.
He has been instrumental in developing many acupuncture-related functional
imaging techniques and data processing, including the early work of
the target-specific acupuncture data processing.
Chang-Ki Kang, MSc
Phone: 949-824-6333 • E-mail: changkik@uci.edu
Kyung-Yo Kim, PhD, is Professor of Oriental Medicine at the Won Kwang
University in Iksan, Korea. Dr Kim has been a member of the acupuncture
research team at UCI, and designed and performed acupuncture-fMRI studies.
Kyung-Yo Kim, OMD, PhD
Phone: +82-62-670-6427 • E-mail: kykim@wonkwang.ac.kr
Hyung-Kyoon Kim, PhD, is Associate Professor of Oriental Medicine at
the Won Kwang University in Iksan, Korea. Dr Kim has been a member of
the acupuncture research team at UCI, and designed and performed acupuncture-fMRI
studies.
Hyung-Kyoon Kim, OMD, PhD
Phone: +82-62-270-1110 • E-mail: hkkim@wonkwang.ac.kr
Byung-Yeol Lee, PhD, is Professor of Oriental Medicine at the Won Kwang
University in Iksan, Korea. Dr Lee has been a member of the acupuncture
research team at UCI, and designed and performed acupuncture-fMRI studies.
Byung-Yeol Lee, OMD, PhD
Phone: +82-43-229-3700 • E-mail: acup@dju.ac.kr
Yoon-Kyung Yim, PhD, is Assistant Professor of Oriental Medicine at
the Taejon University in Taejon, Korea. He has been a member of the
acupuncture research team at UCI, and designed and performed acupuncture-fMRI
studies. Dr Yim was one of the key people of the aforementioned experiment,
and is currently a post-doctoral Researcher at UCI.
Yoon-Kyung Yim, OMD, PhD
Phone: 949-824-6333 • E-mail: docwindy@dju.ac.kr
Ki-Hyon Kim, PhD, is Professor at the Emperor’s College of Oriental
Medicine in Los Angeles, California. Dr Kim has been a member of the
acupuncture research team at UCI since 1998, designing and performing
acupuncture-fMRI studies.
Ki-Hyon Kim, OMD, PhD
Phone: 818-501-8227 • E-mail: khkim1@prodigy.net
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