A network pharmacology-based approach to explore mechanism of action of medicinal herbs for alopecia treatment.

Hair loss is one of the most common skin problems experienced by more than half of the world's population. In East Asia, medicinal herbs have been used widely in clinical practice to treat hair loss. Recent studies, including systematic literature reviews, indicate that medicinal herbs may demonstrate potential effects for hair loss treatment. In a previous study, we identified medical herbs used frequently for alopecia treatment. Herein, we explored the potential novel therapeutic mechanisms of 20 vital medicinal herbs for alopecia treatment that could distinguish them from known mechanisms of conventional drugs using network pharmacology analysis methods. We determined the herb-ingredient-target protein networks and ingredient-associated protein (gene)-associated pathway networks and calculated the weighted degree centrality to define the strength of the connections. Data showed that 20 vital medicinal herbs could exert therapeutic effects on alopecia mainly mediated via regulation of various target genes and proteins, including acetylcholinesterase (AChE), phospholipase A2 (PLA2) subtypes, ecto-5-nucleotidase (NTE5), folate receptor (FR), nicotinamide N-methyltransferase (NNMT), and quinolinate phosphoribosyltransferase (QPRT). Findings regarding target genes/proteins and pathways of medicinal herbs associated with alopecia treatment offer insights for further research to better understand the pathogenesis and therapeutic mechanism of medicinal herbs for alopecia treatment with traditional herbal medicine.

Enhanced Expectation of External Sensations of the Chest Regulates the Emotional Perception of Fearful Faces.

Emotional perception can be shaped by inferences about bodily states. Here, we investigated whether exteroceptive inferences about bodily sensations in the chest area influence the perception of fearful faces. Twenty-two participants received pseudo-electrical acupuncture stimulation at three different acupoints: CV17 (chest), CV23 (chin), and PC6 (left forearm). All stimuli were delivered with corresponding visual cues, and the control condition included visual cues that did not match the stimulated body sites. After the stimulation, the participants were shown images with one of five morphed facial expressions, ranging from 100% fear to 100% disgust, and asked to classify them as fearful or disgusted. Brain activity was measured using functional magnetic resonance imaging during the facial expression classification task. When the participants expected that they would receive stimulation of the chest (CV17), the ratio of fearful to non-fearful classifications decreased compared to the control condition, and brain activities within the periaqueductal gray and the default mode network decreased when they viewed fearful faces. Our findings suggest that bodily sensations around the chest, but not the other tested body parts, were selectively associated with fear perception and that altering external inferences inhibited the perception of fearful faces.

Neural Oscillation Associated with Contagious Itch in Patients with Atopic Dermatitis.

OBJECTIVE: Itch is an unpleasant sensation associated with an urge to scratch and is a major health care issue associated with atopic dermatitis (AD). Contagious itch, i.e., subjective feelings of itchiness induced by watching others' scratching behavior, is common in patients with AD. Using electroencephalography, we examined alpha (8-13 Hz) oscillations in sensorimotor areas associated with the desire to scratch in patients with AD. METHODS: Thirty-six patients with AD and 34 healthy controls (HCs) participated in this study. They evaluated their itch levels after watching short videos of a model scratching or tapping parts of his body. Neural oscillations were recorded from nine electrodes, including those placed over sensorimotor areas. Time-frequency analysis was used to compare mu rhythm suppression over the sensorimotor areas in response to these videos between patients with AD and HCs. RESULTS: The behavioral test showed that the visual stimuli induced increased feelings of itchiness in patients with AD relative to HCs under the tapping and scratching conditions. The time-frequency analysis revealed that mu rhythm suppression in response to scratching images was significantly prominent in patients with AD, but not in HCs. CONCLUSION: Patients with AD exhibited increased susceptibility to contagious itch. This phenomenon might be related to enhanced mu rhythm suppression in sensorimotor areas of the brain in these patients. Our findings provide new insight into the neurophysiological basis of itch sensations in patients with AD.

Predominance of eyes and surface information for face race categorization.

Faces can be categorized in various ways, for example as male or female or as belonging to a specific biogeographic ancestry (race). Here we tested the importance of the main facial features for race perception. We exchanged inner facial features (eyes, mouth or nose), face contour (everything but those) or texture (surface information) between Asian and Caucasian faces. Features were exchanged one at a time, creating for each Asian/Caucasian face pair ten facial variations of the original face pair. German and Korean participants performed a race classification task on all faces presented in random order. The results show that eyes and texture are major determinants of perceived biogeographic ancestry for both groups of participants and for both face types. Inserting these features in a face of another race changed its perceived biogeographic ancestry. Contour, nose and mouth, in that order, had decreasing and much weaker influence on race perception for both participant groups. Exchanging those features did not induce a change of perceived biogeographic ancestry. In our study, all manipulated features were imbedded in natural looking faces, which were shown in an off-frontal view. Our findings confirm and extend previous studies investigating the importance of various facial features for race perception.

Operant and classical learning principles underlying mind-body interaction in pain modulation: a pilot fMRI study.

The operant conditioning has been less studied than the classical conditioning as a mechanism of placebo-like effect, and two distinct learning mechanisms have never been compared to each other in terms of their neural activities. Twenty-one participants completed cue-learning based pain rating tasks while their brain responses were measured using functional magnetic resonance imaging. After choosing (instrumental) or viewing (classical) one of three predictive cues (low- and high-pain cues with different level of certainty), they received painful stimuli according to the selected cues. Participants completed the same task during the test session, except that they received only a high pain stimulus regardless of the selected cues to identify the effects of two learning paradigms. While receiving a high pain stimulation, low-pain cue significantly reduced pain ratings compared to high-pain cue, and the overall ratings were significantly lower under operant than under classical conditioning. Operant behavior activated the temporoparietal junction significantly more than the passive behavior did, and neural activity in the primary somatosensory cortex was significantly reduced during pain in instrumental as compared with classical conditioning trials. The results suggest that pain modulation can be induced by classical and operant conditioning, and mechanisms of attention and context change are involved in instrumental learning.

Identification of Alzheimer's disease using a convolutional neural network model based on T1-weighted magnetic resonance imaging.

The classification of Alzheimer's disease (AD) using deep learning methods has shown promising results, but successful application in clinical settings requires a combination of high accuracy, short processing time, and generalizability to various populations. In this study, we developed a convolutional neural network (CNN)-based AD classification algorithm using magnetic resonance imaging (MRI) scans from AD patients and age/gender-matched cognitively normal controls from two populations that differ in ethnicity and education level. These populations come from the Seoul National University Bundang Hospital (SNUBH) and Alzheimer's Disease Neuroimaging Initiative (ADNI). For each population, we trained CNNs on five subsets using coronal slices of T1-weighted images that cover the medial temporal lobe. We evaluated the models on validation subsets from both the same population (within-dataset validation) and other population (between-dataset validation). Our models achieved average areas under the curves of 0.91-0.94 for within-dataset validation and 0.88-0.89 for between-dataset validation. The mean processing time per person was 23-24 s. The within-dataset and between-dataset performances were comparable between the ADNI-derived and SNUBH-derived models. These results demonstrate the generalizability of our models to different patients with different ethnicities and education levels, as well as their potential for deployment as fast and accurate diagnostic support tools for AD.

Enhanced bodily states of fear facilitates bias perception of fearful faces.

We investigated whether enhanced interoceptive bodily states of fear would facilitate recognition of the fearful faces. Participants performed an emotional judgment task after a bodily imagery task inside a functional magnetic resonance imaging scanner. In the bodily imagery task, participants were instructed to imagine feeling the bodily sensations of two specific somatotopic patterns: a fear-associated bodily sensation (FBS) or a disgust-associated bodily sensation (DBS). They were shown faces expressing various levels of fearfulness and disgust and instructed to classify the facial expression as fear or disgust. We found a stronger bias favoring the "fearful face" under the congruent FBS condition than under the incongruent DBS condition. The brain response to fearful versus intermediate faces increased in the fronto-insular-temporal network under the FBS condition, but not the DBS condition. The fearful face elicited activity in the anterior cingulate cortex and extrastriate body area under the FBS condition relative to the DBS condition. Furthermore, functional connectivity between the anterior cingulate cortex/extrastriate body area and the fronto-insular-temporal network was modulated according to the specific bodily sensation. Our findings suggest that somatotopic patterns of bodily sensation provide informative access to the collective visceral state in the fear processing via the fronto-insular-temporal network.

Identification of candidate medicinal herbs for skincare via data mining of the classic Donguibogam text on Korean medicine.

BACKGROUND: Korean cosmetics are widely exported throughout Asia. Cosmetics exploiting traditional Korean medicine lead this trend; thus, the traditional medicinal literature has been invaluable in terms of cosmetic development. We sought candidate medicinal herbs for skincare. METHODS: We used data mining to investigate associations between medicinal herbs and skin-related keywords (SRKs) in a classical text. We selected 26 SRKs used in the Donguibogam text; these referred to 626 medicinal herbs. Using a term frequency-inverse document frequency approach, we extracted data on herbal characteristics by assessing the co-occurrence frequencies of 52 medicinal herbs and the 26 SRKs. RESULTS: We extracted the characteristics of the 52 herbs, each of which exhibited a distinct skin-related action profile. For example Ginseng Radix was associated at a high-level with tonification and anti-aging, but Rehmanniae Radix exhibited a stronger association with anti-aging. Of the 52 herbs, 46 had been subjected to at least one modern study on skincare-related efficacy. CONCLUSIONS: We made a comprehensive list of candidate medicinal herbs for skincare via data mining a classical medical text. This enhances our understanding of such herbs and will help with discovering new candidate herbs.

Spatial Information of Somatosensory Stimuli in the Brain: Multivariate Pattern Analysis of Functional Magnetic Resonance Imaging Data.

Background: Multivoxel pattern analysis has provided new evidence on somatotopic representation in the human brain. However, the effects of stimulus modality (e.g., penetrating needle versus non-penetrating touch) and level of classification (e.g., multiclass versus binary classification) on patterns of brain activity encoding spatial information of body parts have not yet been studied. We hypothesized that performance of brain-based prediction models may vary across the types of stimuli, and neural patterns of voxels in the SI and parietal cortex would significantly contribute to the prediction of stimulated locations. Objective: We aimed to (1) test whether brain responses to tactile stimuli could distinguish among stimulated locations on the body surface, (2) investigate whether the stimulus modality and number of classes affect classification performance, and (3) localize brain regions encoding the spatial information of somatosensory stimuli. Methods: Fifteen healthy participants completed two functional magnetic resonance imaging (MRI) scans and were stimulated via the insertion of acupuncture needles or by non-invasive touch stimuli (5.46-sized von Frey filament). Participants received the stimuli at four different locations on the upper and lower limbs (two sites each) for 5 min while blood-oxygen-level-dependent activity (BOLD) was measured using 3-Tesla MRI. We performed multivariate pattern analysis (MVPA) using parameter estimate images of each trial for each participant and the support vector classifier (SVC) function, and the prediction accuracy and other MVPA outcomes were evaluated using stratified five-fold cross validation. We estimated the significance of the classification accuracy using a permutation test with randomly labeled training data (n = 10,000). Searchlight analysis was conducted to identify brain regions associated with significantly higher accuracy compared to predictions based on chance as obtained from a random classifier. Results: For the four-class classification (classifying four stimulated points on the body), SVC analysis of whole-brain beta values in response to acupuncture stimulation was able to discriminate among stimulated locations (mean accuracy, 0.31; q < 0.01). The searchlight analysis found that values related to the right primary somatosensory cortex (SI) and intraparietal sulcus were significantly more accurate than those due to chance (p < 0.01). On the other hand, the same classifier did not predict stimulated locations accurately for touch stimulation (mean accuracy, 0.25; q = 0.66). For binary classification (discriminating between two stimulated body parts, i.e., the arm or leg), the SVC algorithm successfully predicted the stimulated body parts for both acupuncture (mean accuracy, 0.63; q < 0.001) and touch stimulation (mean accuracy, 0.60; q < 0.01). Searchlight analysis revealed that predictions based on the right SI, primary motor cortex (MI), paracentral gyrus, and superior frontal gyrus were significantly more accurate compared to predictions based on chance (p < 0.05). Conclusion: Our findings suggest that the SI, as well as the MI, intraparietal sulcus, paracentral gyrus, and superior frontal gyrus, is responsible for the somatotopic representation of body parts stimulated by tactile stimuli. The MVPA approach for identifying neural patterns encoding spatial information of somatosensory stimuli may be affected by the stimulus type (penetrating needle versus non-invasive touch) and the number of classes (classification of four small points on the body versus two large body parts). Future studies with larger samples will identify stimulus-specific neural patterns representing stimulated locations, independent of subjective tactile perception and emotional responses. Identification of distinct neural patterns of body surfaces will help in improving neural biomarkers for pain and other sensory percepts in the future.

The Context of Values in Pain Control: Understanding the Price Effect in Placebo Analgesia.

The experience of pain relief arises from physiological and psychological factors, and attributes such as the commercial features of analgesic treatments have been shown to influence placebo analgesia by affecting treatment expectations. Therefore, treatment valuation from price information should influence the placebo analgesic effect. This hypothesis was tested in a functional magnetic resonance imaging study in which healthy subjects were enrolled in a 2-day experiment. On day 1, the participants (n = 19) had treatment experiences with 2 different placebo creams during a conditioning session without receiving information on treatment price. On day 2, placebo analgesia was tested after providing price information (high vs low) while functional magnetic resonance imaging was performed. The results showed that the higher priced placebo treatment leads to enhanced pain relief. Placebo analgesia in response to the higher priced treatment was associated with activity in the ventral striatum, ventromedial prefrontal cortex, and ventral tegmental area. The behavioral results indicate that the experience of pain was influenced by treatment valuation from price. Our findings reveal that the context of values in pain control is associated with activity in expectation- and reward-related circuitry. PERSPECTIVE: Treatment with higher price was associated with enhanced placebo analgesia, and this effect was influenced by activities in expectation and reward processing brain areas. The context of value such as medical cost influences cognitive evaluation processes to modulate pain. Our study may help evaluate a patient's preference toward high-priced drugs.

Acupuncture Improves Comorbid Cognitive Impairments Induced by Neuropathic Pain in Mice.

Growing evidence indicates that neuropathic pain is frequently accompanied by cognitive impairments, which aggravate the quality of life of chronic pain patients. Here, we investigated whether acupuncture treatments can improve cognitive dysfunction as well as allodynia induced by neuropathic pain in mice. One week after the left partial sciatic nerve ligation (PSNL), acupuncture treatments on the acupoints GB30-GB34 (AP1), HT7-GV20 (AP2), or control points (CP) were performed for 4 weeks. Notably, the significant attenuations of mechanical allodynia and cognitive impairment were observed in the AP1 group, but not in PSNL, AP2, or CP groups. A random decision forest classifier based on the pain and cognitive functions displayed that the acupuncture group was clearly segregated from the other groups. We also demonstrated that acupuncture restored the reduced field excitatory post-synaptic potentials and was able to elevate the expression levels of glutamate receptors (NR2B and GluR1) in the hippocampus. Moreover, the expressions of Ca2+/calmodulin-dependent protein kinase II and synaptic proteins (pPSD-95 and pSyn-1) were enhanced by acupuncture treatment. These results suggest that acupuncture can enhance hippocampal long-term action through the regulation of the synaptic efficacy and that acupuncture may provide a viable option for managing both pain and cognitive functions associated with chronic neuropathic pain.

Revealing Associations between Diagnosis Patterns and Acupoint Prescriptions Using Medical Data Extracted from Case Reports.

OBJECTIVE: The optimal acupoints for a particular disease can be determined by analysis of diagnosis patterns. The objective of this study was to reveal the association between such patterns and the acupoints prescribed in clinical practice using medical data extracted from case reports. METHODS: This study evaluated online virtual diagnoses made by currently practicing Korean medical doctors (N = 80). The doctors were presented with 10 case reports published in Korean medical journals and were asked to diagnose the patients and prescribe acupoints accordingly. A network analysis and the term frequency-inverse document frequency (tf-idf) method were used to analyse and quantify the relationship between diagnosis patterns and prescribed acupoints. RESULTS: The network analysis showed that ST36, LI4, LR3, and SP6 were the most frequently used acupoints across all diagnoses. The tf-idf values showed the acupoints used for specific diseases, such as BL40 for bladder disease and LU9 for lung disease. CONCLUSIONS: The associations between diagnosis patterns and prescribed acupoints were identified using an online virtual diagnosis modality. Network and text mining analyses revealed commonly applied and disease-specific acupoints in both qualitative and quantitative terms.

Deep CT to MR Synthesis Using Paired and Unpaired Data.

Magnetic resonance (MR) imaging plays a highly important role in radiotherapy treatment planning for the segmentation of tumor volumes and organs. However, the use of MR is limited, owing to its high cost and the increased use of metal implants for patients. This study is aimed towards patients who are contraindicated owing to claustrophobia and cardiac pacemakers, and many scenarios in which only computed tomography (CT) images are available, such as emergencies, situations lacking an MR scanner, and situations in which the cost of obtaining an MR scan is prohibitive. From medical practice, our approach can be adopted as a screening method by radiologists to observe abnormal anatomical lesions in certain diseases that are difficult to diagnose by CT. The proposed approach can estimate an MR image based on a CT image using paired and unpaired training data. In contrast to existing synthetic methods for medical imaging, which depend on sparse pairwise-aligned data or plentiful unpaired data, the proposed approach alleviates the rigid registration of paired training, and overcomes the context-misalignment problem of unpaired training. A generative adversarial network was trained to transform two-dimensional (2D) brain CT image slices into 2D brain MR image slices, combining the adversarial, dual cycle-consistent, and voxel-wise losses. Qualitative and quantitative comparisons against independent paired and unpaired training methods demonstrated the superiority of our approach.

Acupuncture for Histamine-Induced Itch: Association With Increased Parasympathetic Tone and Connectivity of Putamen-Midcingulate Cortex.

Previous studies have suggested that acupuncture is effective for ameliorating itch intensity. However, factors associated with the antipruritic effects of acupuncture have yet to be clarified. In a randomized, sham-controlled, crossover trial, we investigated the antipruritic effects of acupuncture against histamine-induced itch in healthy volunteers. Autonomic changes using heart rate variability (HRV) and brain connectivity using functional magnetic resonance imaging (fMRI) were also assessed to identify physiological factors associated with the acupuncture response. Acupuncture significantly reduced itch intensity and skin blood perfusion as assessed by laser Doppler perfusion imaging compared to sham control, indicating the antipruritic effects of acupuncture. In responder and non-responder analysis, the power of normalized high frequency (HF norm) was significantly higher, while the power of normalized low frequency (LF norm) and LF/HF ratio were significantly lower in responders compared to non-responders, suggesting the acupuncture response involved parasympathetic activation. In fMRI analysis, the putamen and the posterior part of the midcingulate cortex (pMCC) were positively connected to itch and negatively correlated with itch intensity in responders. These results suggest that parasympathetic activity and functional connectivity of the putamen and pMCC could be associated with antipruritic response to acupuncture.

Expectations of the Physiological Responses Can Change the Somatosensory Experience for Acupuncture Stimulation.

Objective: Humans interpret sensory inputs based on actual stimuli and expectations of the stimuli. We investigated whether manipulating information related to the physiological response could change the somatosensory experience of acupuncture. Methods: Twenty-four participants received tactile stimulations with a von Frey filament on the left arm. Participants were informed that they would receive acupuncture stimulations at different angles while they were presented with changes in their peripheral blood flow (PBF) measured with Laser Doppler perfusion imaging. However, in reality, they were observing premade pseudo-biosignal images (six sessions: one circular, two rectangular elongated, two diagonally elongated, and one cross-fixation [control] shape). After each session, the participants reported the intensity and location of the de qi sensations perceived on their arm using a bodily sensation mapping tool. The spatial patterns of the somatic sensations were visualized using statistical parametric mapping. The F1 score was calculated to measure the similarity between the presented pseudo-biosignals and reported de qi response images. Results: The spatial configurations of the presented pseudo-biosignal images and de qi response images were similar. The rectangular elongated pseudo-biosignal shape had a significantly higher F1 score compared to the control. All tactile stimulations produced similar levels of enhanced PBF regardless of the pseudo-biosignal shape. Conclusion: The spatial configurations of somatic sensations changed according to the presented pseudo-biosignal shape, suggesting that expectations of the physiological response to acupuncture stimulation can influence the perceived somatic sensation.

Psychophysical and psychophysiological effects of heat stimulation by electric moxibustion.

OBJECTIVES: Traditional moxibustion might be not safe due to the excessive heat stimulation or toxic chemical components involved. Electric moxibustion (EM), which has been recently developed as an alternative, offers adjustable and constant heat stimulation. This study aimed to investigate the psychophysical and psychophysiological responses to EM heat stimulation. METHODS: Twenty-seven healthy volunteers received two different levels of heat stimulation using EM. High-temperature (HT) and medium-temperature (MT) heat stimulations were randomly delivered at the TE5 acupoint on the left or right arm. Participants rated the intensity and the spatial information of the heat sensations immediately after each EM stimulation. Local blood flow around the acupoint was measured with Laser Doppler perfusion imaging before and after heat stimulation. RESULTS: Both HT-EM and MT-EM induced considerable heat sensations and enhanced local blood flow around the acupoints. HT-EM resulted in greater heat sensation compared to MT-EM. HT-EM induced a higher increase in local blood flow around the stimulation site compared to MT-EM. No remarkable adverse effects were noted. CONCLUSION: Two different levels of EM heat stimulation induced two different levels of heat sensations and enhanced local blood flow. This preliminary study suggests that the newly developed EM can be further applied to examine the effectiveness of moxibustion in clinical trials.

Characterization of hidden rules linking symptoms and selection of acupoint using an artificial neural network model.

Comprehension of the medical diagnoses of doctors and treatment of diseases is important to understand the underlying principle in selecting appropriate acupoints. The pattern recognition process that pertains to symptoms and diseases and informs acupuncture treatment in a clinical setting was explored. A total of 232 clinical records were collected using a Charting Language program. The relationship between symptom information and selected acupoints was trained using an artificial neural network (ANN). A total of 11 hidden nodes with the highest average precision score were selected through a tenfold cross-validation. Our ANN model could predict the selected acupoints based on symptom and disease information with an average precision score of 0.865 (precision, 0.911; recall, 0.811). This model is a useful tool for diagnostic classification or pattern recognition and for the prediction and modeling of acupuncture treatment based on clinical data obtained in a real-world setting. The relationship between symptoms and selected acupoints could be systematically characterized through knowledge discovery processes, such as pattern identification.

Exploring the combination and modular characteristics of herbs for alopecia treatment in traditional Chinese medicine: an association rule mining and network analysis study.

BACKGROUND: Although alopecia affects the quality of life, its pathogenesis is unknown, because cellular interactions in the hair follicle are complex. Several authors have suggested using herbal medicine to treat alopecia, and bioinformatics and network pharmacology may constitute a new research strategy in this regard because herbal medicines contain various chemical components. This study used association rule mining (ARM) and network analysis to analyze the combinations of medicinal herbs used to treat alopecia. METHODS: We searched Chinese, Korean, and English databases for literature about alopecia treatment, extracting the names of each herbal prescription and herb. The meridian tropism and classification category of each herb were also investigated. Using ARM, we identified frequently combined two-herb and three-herb sets. Using network analysis, we divided the herbs into several modules according to prescription pattern. RESULTS: Fifty-six articles and 489 herbal medicines were included-312 internal and 177 external medicines. Among the 312 medicinal herbs used in internal medicine group, the most frequently combined two-herb set was Polygonum multiflorum Thunb. () and Angelica sinensis (Oliv.) Dlels (). The most frequently used three-herb combination was Polygonum multiflorum Thunb., Angelica sinensis (Oliv.) Dlels, and Ligusticum chuanxiong Hort. (). In network analysis, three modules were identified. The herbs of Module 1 were related to the liver and kidney meridians, and those of Module 3 were related to the Stomach meridian. CONCLUSIONS: We identified the frequency, characteristics, and functional modules of herb combinations frequently used in alopecia treatment. We confirmed the value of classical medicinal herb theory. This finding will prompt further bioinformatics and network pharmacology research on alopecia.

Brain activation during the expectations of sensory experience for cutaneous electrical stimulation.

The brain actively interprets sensory inputs by integrating top-down and bottom-up information. Humans can make inferences on somatosensation based on prior experiences and expectations even without the actual stimulation. We used functional magnetic resonance imaging to investigate the neural substrates of the expectations of the sensory experience of cutaneous electrical stimulation on acupoint without actual stimuli. This study included 22 participants who wore sticker-type electrodes attached on three different acupoints on different body regions: CV17 (chest), CV23 (chin), and left PC6 (arm). Participants evaluated de qi sensations after they expected electrical stimulation on those points in random order without actual stimulation. All stimuli were presented with corresponding visual information of the stimulation sites. The control condition included the same visual information but outside the body. The expectations of cutaneous electrical stimuli without actual stimulation on three acupoints resulted in greater de qi sensation compared to the control condition. Cognitive components of cutaneous electrical stimulation exhibited greater brain activation in the anterior insula, pre-supplementary motor area, and secondary somatosensory area. The expectations of acupuncture stimulation exhibited a distinct experience of somatosensation as well as brain activations in insula and pre-supplementary motor area. Our findings suggest that the sensory experience of the pseudo-cutaneous stimulation may be derived from the predictive role of the salience network in monitoring internal and external body states.