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Feng Y.,CAS Institute of Automation | Bai L.,CAS Institute of Automation | Zhang W.,CAS Institute of Automation | Xue T.,Xidian University | And 10 more authors.
Journal of Magnetic Resonance Imaging | Year: 2011

Purpose: To investigate the acupoint specificity by exploring the effective connectivity patterns of the poststimulus resting brain networks modulated by acupuncture at the PC6, with the same meridian acupoint PC7 and different meridian acupoint GB37. Materials and Methods: The functional MRI (fMRI) study was performed in 36 healthy right-handed subjects receiving acupuncture at three acupoints, respectively. Due to the sustained effects of acupuncture, a novel experimental paradigm using the nonrepeated event-related (NRER) design was adopted. Psychophysical responses (deqi sensations) were also assessed. Finally, a newly multivariate Granger causality analysis (mGCA) was used to analyze effective connectivity patterns of the resting fMRI data taken following acupuncture at three acupoints. Results: Following acupuncture at PC6, the red nucleus and substantia nigra emerged as central hubs, in comparison with the fusiform gyrus following acupuncture at GB37. Red nucleus was also a target following acupuncture at PC7, but with fewer inputs than those of PC6. In addition, the most important target following acupuncture at PC7 was located at the parahippocampus. Conclusion: Our findings demonstrated that acupuncture at different acupoints may exert heterogeneous modulatory effects on the causal interactions of brain areas during the poststimulus resting state. These preliminary findings provided a clue to elucidate the relatively function-oriented specificity of acupuncture effects. © 2011 Wiley-Liss, Inc.


Feng Y.,CAS Institute of Automation | Bai L.,CAS Institute of Automation | Ren Y.,Chinese Academy of Traditional Medicine | Chen S.,Southern Medical University | And 4 more authors.
Magnetic Resonance Imaging | Year: 2012

The increased risk for the elderly with mild cognitive impairment (MCI) to progress to Alzheimer's disease makes it an appropriate condition for investigation. While the use of acupuncture as a complementary therapeutic method for treating MCI is popular in certain parts of the world, the underlying mechanism is still elusive. We sought to investigate the acupuncture effects on the functional connectivity throughout the entire brain in MCI patients compared to healthy controls (HC). The functional magnetic resonance imaging experiment was performed with two different paradigms, namely, deep acupuncture (DA) and superficial acupuncture (SA), at acupoint KI3. We first identified regions showing abnormal functional connectivity in the MCI group compared to HC during the resting state and subsequently tested whether these regions could be modulated by acupuncture. Then, we made the comparison of MCI vs. HC to test whether there were any specific modulatory patterns in the poststimulus resting brain between the two groups. Finally, we made the comparisons of DA vs. SA in each group to test the effect of acupuncture with different needling depths. We found the temporal regions (hippocampus, thalamus, fusiform gyrus) showing abnormal functional connectivity during the resting state. These regions are implicated in memory encoding and retrieving. Furthermore, we found significant changes in functional connectivity related with the abnormal regions in MCI patients following acupuncture. Compared to HC, the correlations related with the temporal regions were enhanced in the poststimulus resting brain in MCI patients. Compared to SA, significantly increased correlations related with the temporal regions were found for the DA condition. The enhanced correlations in the memory-related brain regions following acupuncture may be related to the purported therapeutically beneficial effects of acupuncture for the treatment of MCI. The heterogeneous modulatory patterns between DA and SA may suggest that deep muscle insertion of acupuncture is necessary to achieve the appreciable clinical effect. © 2012 Elsevier Inc.


Wang H.,CAS Institute of Automation | Ren Y.,Chinese Academy of Traditional Medicine | Bai L.,CAS Institute of Automation | Zhang W.,CAS Institute of Automation | And 2 more authors.
PLoS ONE | Year: 2012

Local features in volumetric images have been used to identify correspondences of localized anatomical structures for brain morphometry. However, the correspondences are often sparse thus ineffective in reflecting the underlying structures, making it unreliable to evaluate specific morphological differences. This paper presents a morphometry method (MEACOLP) based on correspondences with improved effectiveness and accuracy. A novel two-level scale-invariant feature transform is used to enhance the detection repeatability of local features and to recall the correspondences that might be missed in previous studies. Template patterns whose correspondences could be commonly identified in each group are constructed to serve as the basis for morphometric analysis. A matching algorithm is developed to reduce the identification errors by comparing neighboring local features and rejecting unreliable matches. The two-sample t-test is finally adopted to analyze specific properties of the template patterns. Experiments are performed on the public OASIS database to clinically analyze brain images of Alzheimer's disease (AD) and normal controls (NC). MEACOLP automatically identifies known morphological differences between AD and NC brains, and characterizes the differences well as the scaling and translation of underlying structures. Most of the significant differences are identified in only a single hemisphere, indicating that AD-related structures are characterized by strong anatomical asymmetry. In addition, classification trials to differentiate AD subjects from NC confirm that the morphological differences are reliably related to the groups of interest. © 2012 Wang et al.


Feng Y.,CAS Institute of Automation | Bai L.,CAS Institute of Automation | Zhang W.,CAS Institute of Automation | Ren Y.,Chinese Academy of Traditional Medicine | And 4 more authors.
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS | Year: 2011

Previous neuroimaging studies on acupuncture have primarily adopted functional connectivity analysis associated with one or a few preselected brain regions. Few have investigated how these brain regions interacted at the whole brain level. In this study, we sought to investigate the acupoint specificity by exploring the whole brain functional connectivity analysis on the post-stimulus resting brain modulated by acupuncture at acupoint PC6, with the same meridian acupoint PC7 and different meridian acupoint GB37. We divided the whole brain into 90 regions and analyzed functional connectivity for each condition. Then we identified statistically significant differences in functional correlations throughout the entire brain following acupuncture at PC6 in comparison with PC7 as well as GB37. For direct comparisons, increased correlations for PC6 compared to PC7 were primarily between the prefrontal regions and the limbic/paralimbic and subcortical regions, whereas decreased correlations were mainly between the parietal regions and the limbic/paralimbic and subcortical regions. On the other hand, increased correlations for PC6 compared to GB37 were primarily between the prefrontal regions and somatosensory regions, whereas decreased correlations were mainly related with the occipital regions. Our findings demonstrated that acupuncture at different acupoints may exert heterogeneous modulatory effects on the post-stimulus resting brain, providing new evidences for the relatively function-oriented specificity of acupuncture effects. © 2011 IEEE.


Xue T.,Xidian University | Bai L.,CAS Institute of Automation | Chen S.,Southern Medical University | Zhong C.,CAS Institute of Automation | And 9 more authors.
Magnetic Resonance Imaging | Year: 2011

Acupoint specificity, as a crucial issue in acupuncture neuroimaging studies, is still a controversial topic. Previous studies have generally adopted a block-based general linear model (GLM) approach, which predicts the temporal changes in the blood oxygenation level-dependent signal conforming to the "on-off" specifications. However, this method might become impractical since the precise timing and duration of acupuncture actions cannot be specified a priori. In the current study, we applied a data-driven multivariate classification approach, namely, support vector machine (SVM), to explore the neural specificity of acupuncture at gall bladder 40 (GB40) using kidney 3 (KI3) as a control condition (belonging to different meridians but the same nerve segment). In addition, to verify whether the typical GLM approach is sensitive enough in exploring the neural response patterns evoked by acupuncture, we also employed the GLM method to the same data sets. The SVM analysis detected distinct neural response patterns between GB40 and KI3 - positive predominantly for the GB40, while negative following the KI3. By contrast, group analysis from the GLM showed that acupuncture at these different acupoints can both evoke similar widespread signal decreases in multiple brain regions, and most of these regions were spatially overlapped, mainly distributing in the limbic and subcortical structures. Our findings may provide additional evidence to support the specificity of acupuncture, relevant to its clinical efficacy. Moreover, we also proved that GLM analysis is prone to be susceptible to errors and is not appropriate for detecting neural response patterns evoked by acupuncture stimulation. © 2011 Elsevier Inc.

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