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Brain imaging studies of tinnitus patients have revealed marked changes in brain structure and function, but there are inconsistencies in those findings. In this meta-analysis, we investigated concurrence across studies to clarify those abnormalities in brain structure and function in tinnitus. Neuroimaging studies published up to December 6, 2019 were searched in the PubMed, Web of Science, EMBASE, and Cochrane Library databases, Chinese Nation Knowledge Infrastructure, Chinese Biomedical Literature Database, the Chongqing VIP, and Wanfang Database. Study selection, quality assessment, and data extraction were performed by two independent researchers. Anisotropic effect size signed differential mapping (AES-SDM) was used to perform a multimodal analysis of available studies reporting whole-brain structural or functional data in tinnitus patients. There were 14 studies that met the inclusion criteria. The structural dataset comprised 242 tinnitus patients and 217 matched healthy subjects (HS), while the functional dataset included 130 tinnitus patients and 140 matched HS. Our analysis revealed structural alterations in the superior temporal gyrus, middle temporal gyrus (MTG), angular gyrus, caudate nucleus, superior frontal gyrus, and supplementary motor area, as well as functional differences in the MTG, middle occipital gyrus, precuneus, and right inferior parietal (excluding supramarginal and angular) gyri. The multimodal analysis revealed significant differences in the right MTG of tinnitus patients relative to HS. These findings suggest the involvement of the cortico-striatal circuits in the neuropathology of tinnitus.

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INTRODUCTION: The influence of sex on the prevalence and clinical manifestations of functional dyspepsia (FD) has recently been a topic of increasing interest. However, brain MRI pathology based on sexual dimorphism in FD has not yet been investigated. The amygdala, which plays a vital role in processing gastrointestinal signals, may be associated with the sex-related pathophysiology of FD. METHODS: We investigated the resting-state functional connectivity (rsFC) of amygdala subregions in patients with FD and healthy subjects as well as the sex differences between male and female FD patients. RESULTS: The results showed that FD patients manifested altered rsFC in the basolateral amygdala (BLA) and centromedial amygdala subregions compared with HS and that female FD patients showed increased BLA rsFC with the insula (INS) and decreased BLA rsFC with the medial prefrontal cortex and dorsal lateral prefrontal cortex compared with male FD patients and female HS. DISCUSSION: Our findings suggest that FD females tend to have more severe dysfunction of cognitive-affective processing among the brain regions associated with the salience network, central executive network, and default mode network.

Objectives: This study was conducted in order to investigate the study design and main outcomes of acupuncture neuroimaging studies on low back pain (LBP).Methods: Neuroimaging studies of acupuncture on LBP were collected from three English databases such as PubMed and four Chinese databases such as China National Knowledge Infrastructure (CNKI) from inception to December 31, 2020. Study selection, data extraction, and assessment of risk of bias were performed independently by two investigators. The quality of studies was appraised with the Cochrane's risk of bias tools. Information on basic information, methodology, and brain imaging data were extracted.Results: The literature search returned 310 potentially eligible studies and 19 articles met inclusion criteria; 78.9% of studies chose manual acupuncture as the intervention, 89.5% of studies evaluated functional changes elicited by acupuncture, and 68.4% of studies used resting-state fMRI as imaging condition. The most frequently reported acupuncture-induced brain alterations of LBP patients were in the prefrontal cortex, insula, cerebellum, primary somatosensory cortex, and anterior cingulate cortex. There was a significant correlation between improved clinical outcomes and changes in the brain.Conclusions: The results suggested that improving abnormal structure and functional activities in the brain of the LBP patient is an important mechanism of acupuncture treatment for LBP. The brain regions involved in acupuncture analgesia for LBP were mainly located in the pain matrix, default mode network (DMN), salience network (SN), and descending pain modulatory system (DPMS). However, it was difficult to draw a generalized conclusion due to the heterogeneity of study designs. Further well-designed multimodal neuroimaging studies investigating the mechanism of acupuncture on LBP are warranted.

Acupuncture has been widely used as an alternative and complementary therapy for migraine. With the development of neuroimaging techniques, the central mechanism of acupuncture for migraine has gained increasing attention. This review aimed to analyze the study design and main findings of neuroimaging studies of acupuncture for migraine to provide the reference for future research. The original studies were collected and screened in three English databases (PubMed, Embase, and Cochrane Library) and four Chinese databases (Chinese National Knowledge Infrastructure, Chinese Biomedical Literature database, the Chongqing VIP database, and Wanfang database). As a result, a total of 28 articles were included. Functional magnetic resonance imaging was the most used neuroimaging technique to explore the cerebral activities of acupuncture for migraine. This review manifested that acupuncture could elicit cerebral responses on patients with migraine, different from sham acupuncture. The results indicated that the pain systems, including the medial pain pathway, lateral pain pathway, and descending pain modulatory system, participated in the modulation of the cerebral activities of migraine by acupuncture.

The patient–acupuncturist interaction was a critical influencing factor for acupuncture effects but its mechanism remains unclear. This study aimed to examine the inter‐brain mechanism of patient–acupuncturist dyad during acupuncture stimulation in a naturalistic clinical setting. Seventy healthy subjects (simulated “patients”) were randomly assigned to two groups and received verum acupuncture group or sham acupuncture by one acupuncturist. Functional near‐infrared spectroscopy hyperscanning was used to simultaneously record the neural responses of “patient”–acupuncturist dyad during acupuncture stimulation in each group. The results showed that inter‐brain neural synchronization (INS) in the prefrontal cortex (PFC) of “patient”–acupuncturist dyad was significantly increased during verum but not sham acupuncture stimuli, and positively correlated with the needling sensations of “patients.” Granger causality analysis demonstrated that there were no significant differences in INS direction between the “patient” and the acupuncturist. This study identified the increase of INS between “patient” and acupuncturist, and suggested that PFC was important to the interaction of “patient”–acupuncturist dyad.

The diagnosis of functional dyspepsia (FD) presently relies on the self-reported symptoms. This study aimed to determine the potential of functional brain network features as biomarkers for the identification of FD patients. Firstly, the functional brain Magnetic Resonance Imaging data were collected from 100 FD patients and 100 healthy subjects, and the functional brain network features were extracted by the independent component analysis. Then, a support vector machine classifier was established based on these functional brain network features to discriminate FD patients from healthy subjects. Features that contributed substantially to the classification were finally identified as the classifying features. The results demonstrated that the classifier performed pretty well in discriminating FD patients. Namely, the accuracy of classification was 0.84 ± 0.03 in cross-validation set and 0.80 ± 0.07 in independent test set, respectively. A total of 15 connections between the subcortical nucleus (the thalamus and caudate) and sensorimotor cortex, parahippocampus, orbitofrontal cortex were finally determined as the classifying features. Furthermore, the results of cross-brain atlas validation showed that these classifying features were quite robust in the identification of FD patients. In summary, the current findings suggested the potential of using machine learning method and functional brain network biomarkers to identify FD patients.